- Email: [email protected]
Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application
international journal of hydrogen energy xxx (xxxx) xxx
Available online at www.sciencedirect.com
ScienceDirect journal homepage: www.elsevier.com/locate/he
Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application John M. Stansberry, Jacob Brouwer* National Fuel Cell Research Center, University of California, Irvine, CA 92697, USA
highlights A 60 kW PEM Electrolyzer system load follows solar PV and wind farm dynamics. Cycling on/off from cold start leads to better electrolyzer efficiency. Ancillary losses, particularly for H2 drying, dominate at low load conditions. Mass flow controller-based control was used to dispatch the electrolyzer. Operating conditions were varied and performance impacts assessed.
article info
abstract
Article history:
A 60 kW PEM electrolyzer was modified to have dynamic dispatch capabilities through the
Received 23 November 2019
use of an external mass flow controller and was subsequently operated and studied in
Received in revised form
detail as a part of the UC Irvine power-to-gas (P2G) demonstration project. The system
15 January 2020
operated in load following for both rooftop solar PV output and aggregated wind farm
Accepted 29 January 2020
power. The electrolyzer system was able to handle 100% up and down ramps of the elec-
Available online xxx
trolyzer stack in sub-second intervals during variable renewable energy load following experiments. Overall system efficiency was improved by imposing a minimum load con-
Keywords:
dition to avoid high parasitic losses at low power conditions, and cycling the system off/on
Proton exchange membrane
as required and enabled by quick cold start-up capability. Performance was characterized
electrolyzer
for varying levels of part load and dynamic operation. The gas drying process was found to
Solar photovoltaic
be a significant source of loss at low power conditions.
Power-to-gas
© 2020 Published by Elsevier Ltd on behalf of Hydrogen Energy Publications LLC.
Wind power Electrolysis
Introduction Issues associated with the finite nature of fossil fuels and their association with the emissions of both criteria pollutants and greenhouse gases has directed a shift in the energy sector
towards renewable resources. Of the many forms of renewable energy resources available, photovoltaic (PV) solar and wind power generation have seen the greatest increase in proliferation [1]. Along with this deployment has come an increasing cost-competitiveness with fossil fueled power generation, with solar PV modules and land-based wind
* Corresponding author. E-mail address: [email protected] (J. Brouwer). https://doi.org/10.1016/j.ijhydene.2020.01.228 0360-3199/© 2020 Published by Elsevier Ltd on behalf of Hydrogen Energy Publications LLC. Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
2
international journal of hydrogen energy xxx (xxxx) xxx
turbines projected to be the least expensive source of new electricity generation capacity by 2020 [2]. To-date, much has been accomplished in terms of integrating the relative small amounts (up to around 30%) of solar and wind power generation with current electrical grid architecture and infrastructure. Integrating larger amounts of these variable renewable energy sources (VRES) is expected to be a greater challenge due to their intermittency and uncontrollability [3,4]. The need for long term energy storage on the order of days up to months has been well established to ultimately ensure the effectiveness of a highly renewable electrical grid [5,6]. Storing energy in the form of hydrogen is currently one of the most appropriate options for meeting these long-term energy storage requirements [7e9]. Hydrogen can be produced through a number of different methods; electrolysis using electricity as the primary energy source, steam methane reforming (SMR) or hydrolysis using thermal energy, or various photolytic processes [10e12]. Today, production of hydrogen through SMR dominates because it is cheapest, with production via electrolysis being the only other appreciable commercial method. Electrolysis utilizing VRES in the form of solar PV or wind farm power, also known as power-to-gas (P2G) has the lowest environmental impact from a climate and air quality perspective for producing hydrogen [13]. Falling costs of electrolyzers, solar PV, and wind power in combination with favorable regulatory and policy environments has led to cost competitive applications for P2G today (e.g., to produce hydrogen for fuel cell vehicles in California with support of the Low Carbon Fuel Standard policy), with the potential to be broadly competitive with non-renewable hydrogen sources within the decade [14]. In some regions of the U.S., electrolysis produced hydrogen is already costcompetitive with gasoline vehicle use today [15]; although building out the infrastructure for transmitting, distributing, and dispensing of hydrogen remains a challenge. Other pathways of interest include the storage and subsequent utilization of hydrogen in either a fuel cell or gas-turbine based power plants, or the injection of hydrogen into natural gas infrastructure to increase the renewable content of pipeline gas and reduce carbon intensity. Converting existing carbon intensive gas grid infrastructure in a piecewise manner through the introduction of hydrogen provides an opportunity to accelerate the transition away from fossil fuels, however much work remains to be done before appreciable amounts of hydrogen can be introduced [16]. The combustion of hydrogen-enriched natural gas without modification of existing end uses is an active and vital area of research, with applications ranging from stovetops [17e19], oven burners [20], and water heaters [21] as well as gas-fired turbines [22,23]. The gas grids could further be utilized as a transport medium for hydrogen end-uses by utilizing separation techniques to extract hydrogen from the hydrogen-enriched natural gas for fueling of fuel cells in either transportation or power generation applications or other industrial end uses requiring high purity hydrogen [24]. Numerous power-to-gas projects have demonstrated integration with natural gas infrastructure [25,26] and the current European Union (EU) energy roadmap has identified the natural gas system as critical for meeting deep decarbonization and renewable penetration goals for
their overall energy system due to the critical flexibility that the gas network provides [27]. On June 22nd, 2016, the University of California, Irvine (UCI) in collaboration with the Southern California Gas Company (SoCalGas) launched the UCI P2G demonstration comprised of a 60 kW proton exchange membrane (PEM) electrolyzer co-located with the UCI combined heat and power combined cycle power plant. The main research objectives of the UCI P2G demonstration included evaluating the dynamic dispatch of a commercial PEM electrolyzer system in load following both solar PV and wind farm power dynamics and characterizing the PEM electrolyzer performance. Furthermore, produced hydrogen was injected directly to the gas grid upstream of the campus combustion turbine in the first injection of hydrogen gas to existing natural gas infrastructure for the United States. There are a number of studies which model P2G systems that deploy real-scale PEM electrolyzers in P2G scenarios [28e30]. Additionally, there exists significant depth of research on the modeling of the electrolyzer's themselves [31e34]; however, data and analysis from the actual deployment of PEM systems in P2G applications is lacking in the literature. There are a number of experimental studies on PEM electrolyzer systems either operated dynamically or directly integrated with VRES [35e38], but larger-scale systems have not been studied extensively in the peer-reviewed literature, with the lone exception of the 46 kW PEM electrolyzer studied as a part of the MYRTE demonstration platform at the University of Corsica [39]. The objective of this paper is to provide an in-depth look into the operation of a commercial full-scale PEM electrolyzer system, deployed in a P2G operation setting following PV and wind farm power dynamics. Baseline performance is characterized, then compared to the performance of the system when load following intermittent dynamics associated with solar PV and wind power. The performance of the electrolysis process and the balance of plant components are studied, and ancillary aspects of system performance are measured (startup and shut down times, stack slew rates, water consumption, etc.). Recommendations for further research and development for deployment of PEM systems in P2G applications are identified and discussed.
Experimental methods & materials Electrolyzer system The UCI P2G demonstration involves the integration of an electrolyzer system with the UCI Central Plant. Hydrogen produced from the electrolyzer system is mixed into the highpressure natural gas pipeline upstream of the gas turbine and subsequently combusted to complete the P2G2P utilization pathway. The PEM electrolyzer deployed is a Proton Onsite Model C10. The C10 system is a differential pressure PEM electrolyzer system. The C Series PEM electrolysis cell stack is comprised of 65 circular cells with an active area of 214 cm2. Key characteristics and operating parameters of the electrolyzer system are shown in Table 1. The balance of plant for the PEM
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
international journal of hydrogen energy xxx (xxxx) xxx
Table 1 e Operating parameters for the Model C10 electrolyzer system. Hydrogen e Cathode Production (kg/hr) Pressure (barg) Oxygen - Anode Production (kg/hr) Pressure (barg) Feed Water - Anode Circulation Rate (L/min) Consumption Rate (L/min) Temperature (C ) Quality (MU-cm) Electrical Breaker Rating System Power (kW AC) Electrolysis Stack (Volts/Amps DC) Cooling Chiller System Chiller Capacity (kWth) Cooling Requirement (kWth)
0e0.91 0e34.5 14e128 0e2.76 37.9 0.15 5e65 >1.0 480 VAC 3-phase, 100 kVA 60 140/410 Accuchiller air-cooled chiller (PN#: NQA13C1E213C) 55.7 33.4
3
electrolyzer is shown in a simplified process flow diagram (Fig. 1), along with supporting data acquisition (DAQ) and control systems. As shown in Fig. 1, a hydrogen management subsystem maintains hydrogen pressure in the system and removes water before heading to the process connection. Generated hydrogen gas first enters a hydrogen-water phase separator vessel where system-side hydrogen pressure is monitored and maintained. Liquid water is dropped out by gravity in this vessel, and intermittently ‘flushed’ to send the water back into the deionized (DI) water loop. From the hydrogen water phase separator, hydrogen gas passes through a heat exchanger, further condensing out water, before entering a secondary larger volume hydrogen-water phase separator vessel. In the final drying stage hydrogen gas enters a pressure swing adsorption (PSA) dryer system. After the drying process a series of check valves, pressure transducers, and a back-pressure regulator control the output pressure of the hydrogen gas to the delivery point. This pressure feedback control loop is the primary control variable for determining the amount of electrical power that is delivered to the electrolysis process.
Fig. 1 e Simplified process flow diagram for the electrolyzer system in the UCI P2G demonstration project.
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
4
international journal of hydrogen energy xxx (xxxx) xxx
Generated oxygen gas is entrained in the water electrode and exits with the DI water. This mixture goes to a wateroxygen phase separator, after which oxygen gas exits to an exterior vent with a small amount of water (saturated conditions). Sensors on this subsystem monitor pressure and for the presence of hydrogen gas to prevent a flammable mixture.
Data acquisition systems The electrolyzer system has an internal data stream that provides high resolution, accurate data concerning system operation and control through a Modbus protocol. Onboard metrics of interest to the study of the system include the system hydrogen pressure at the outlet of the hydrogen electrode (in barg), oxygen pressure at the oxygen-water phase separator (in barg), system water temperature at the outlet of the DI water subsystem heat exchanger (in C), hydrogen gas temperature at the hydrogen management subsystem heat exchanger (in C), the stack voltage (in volts), and the stack current command signal (in amps). The states of the system solenoid valves, water levels, coolant temperature at the heat exchangers, DI water quality at the inlet and in the recirculating water loop are also monitored and recorded. To complement the on-board data acquisition and provide verification of some measurements, some external sensing and data acquisition was implemented. Power meters (Dent ElitePro) were installed at the electrolyzer system connection to the grid, on the electrolyzer system breaker to the ancillary power demands, and at the grid connection to the chiller system, to record the net power consumption (in kW), voltage across the 3-phases (in volts AC), amperage across the 3phases (in amps AC), and the power factor. Having power monitoring on both the overall system consumption and on the ancillary systems circuit allowed for the characterization of the AC electricity consumption of the electrolysis process separate from conversion losses and from the electrical power needed to run the pumps, blowers, valves, etc; that make up the ancillary power demands. An additional Dent Elitepro system was connected to the cell stack to independently measure the stack voltage at a higher resolution than the internal data stream. The stack current was measured using two split-core current transducers (CR Magnetics CR5220S Split Core Current Transducers) rated for 0e300 amps DC. Verification of the current reading was accomplished intermittently with a Fluke split-core current transformer (Fluke i410 AC/DC Current Clamp). Hydrogen gas mass flow from the system to the end process was measured using a Sierra Instruments 840H HiTrak Mass Flow Controller. The 4e20 mA analog output logic from the split-core current transducers and mass flow controller were logged using a Dent DataLogger Pro.
Mass flow controller & control system To control the dispatch of the Model C10 system for dynamic response, a mass flow controller was installed on the hydrogen product line. The mass flow controller is able to dispatch the electrolyzer system by manipulating the hydrogen flow, simulating a reduced hydrogen demand downstream of the system. The hydrogen management
subsystem's pressure feedback loop subsequently senses the higher downstream pressure and reduces the current throughput to the electrolysis stack accordingly. For dynamic dispatch, a dispatch profile from a selected data source, or a general load profile such as a stepwise ramp, is converted to comma-separated variable (.csv) file format. The .csv file is read by a Python script, which outputs the signal value through serial communication to a Seeed Studio Seeeduino microcontroller. The microcontroller reads the serial value and then outputs an equivalent 0e5V DC analog signal through pulse width modulation. This signal is converted to a 4e20 mA signal by way of a signal conditioning circuit comprised of an RC circuit for conditioning the Volts DC signal which then goes through a Texas Instruments XTR110 precision Voltage-to-Current converter integrated circuit (IC). This 4e20 mA signal is then communicated to the mass flow controller which controls the hydrogen flow from the system. Hydrogen mass flow was measured and controlled using Sierra Instruments Hi-Trak 840H mass flow controllers (P/N#: 840H-4-OV1-SV1-D-V4-S4-HP).
Results Steady state performance benchmarking For the first 1000 h of operation the Model C10 electrolyzer system was operated at full throughput to establish baseline operation characteristics and performance. Table 2 compares several performance characteristics at 100, 600, and 1000 h of operation. Notably, an appreciable increase in stack current, and associated improvements in AC/DC power electronics efficiency (higher DC output), H2 dryer efficiency (higher H2 throughput), and overall system efficiency, occurred over this time period. After 800 h, stack current was consistently around the rated 410 amps DC. This suggests a slight ‘breakin’ period, which can be attributed to the electrolysis stack, rather than the power supply, as the DC power supply was replaced at 600 h of operation without any impact on the increasing current trend. In PEM electrolyzers, the membrane electrode assembly (MEA) typically undergoes an activation process immediately after manufacturing that can last anywhere from several hours to several days, resulting in progressively better cell performance that ultimately plateaus [40]. Generally, ‘break-in’ periods are more commonly observed in studies of high temperature proton exchange membranes for application in phosphoric acid fuel cells (PAFC) and direct methanol fuel cells (DMFC) [41,42], but are not unheard of for PEM fuel cell MEAs [43]. An increase in current density without an increase in applied potential is typical of these ‘break in’ or activation processes, which involve cycling of the cell [45]. The electrolyzer system rated water consumption by the OEM is given as ‘roughly’ 2.4 gallons per hour at full output, matching the water requirement for the electrolysis reaction alone. Actual system water consumption during benchmarking was found to be approximately 3.1 gal/hr on average, varying minimally as operation time went on. Losses associated with power electronics and hydrogen drying are comparable and are the most significant
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
5
international journal of hydrogen energy xxx (xxxx) xxx
Table 2 e Full throughput benchmarking of electrolyzer system versus specifications.
H2 Output (kg/hr) Stack Current (Amps) Water Consumption (Gal/hr) Stack Power (kW DC) System Power (kW AC) H2 Dryer Efficiency (%) AC/DC Efficiency (%) Stack Efficiency (%HHV H2) System Efficiency (%HHV H2) System Efficiency w/Chiller (%HHV H2)
Baseline Specifications
Run 1 100 Hours
Run 2 600 Hours
Run 3 1000 Hours
0.910 410.00 2.400 57.40 62.00 ~90.00% N/A N/A 57.24% N/A
0.899 401.52 3.095 54.54 61.67 90.85% 92.09% 72.03% 57.47% 45.99%
0.912 407.99 3.031 55.09 61.68 90.49% 93.03% 72.06% 58.25% 46.79%
0.936 411.30 3.116 55.38 61.56 92.24% 93.69% 72.17% 59.88% e
contributors to system losses. The majority of system energy conversion occurs in the electrolysis process itself and in the chiller system operation that provides thermal management. The magnitude of energy conversion that goes to the chiller is more than twice the amount lost to the rest of the balance of plant, including power electronics conversion losses. In terms of hydrogen production, a quarter of the electricity consumption is directed to the chiller system, equivalent to 17 kWh of electricity per kg of hydrogen produced. The power meter associated with the chiller failed around the ~800 operating hours mark. As the power consumption of the chiller was not of major interest to this study, the meter was not replaced.
System losses characterization The specific energy consumption of the electrolyzer system describes the net amount of electrical power in kWh consumed per kg of H2 produced. This metric was measured for all experiments and is presented as a function of stack current density in Fig. 2. Specific energy remains relatively flat as power is reduced until around a current density of 1 A/cm2, corresponding to roughly a 50% load condition. Beyond this point, specific energy costs begin to rise significantly, becoming prohibitive at any current densities of about 0.6 A/ cm2 and below.
Fig. 2 e Full- and part-load system specific energy consumption (kWh electricity per kg H2 produced) presented versus stack current density.
The specific energy consumption of the system can be broken down into four sources of energy consumption; the electrolysis process or ‘stack’ energy consumption, the energy losses associated with physical loss of H2, energy consumption associated with the AC/DC power electronics, and the ancillary balance of plant energy consumption. The contribution of each of these components on a percentage basis is presented in Fig. 3. It is clear that the electrolysis stack is the dominant source of energy consumption for the range of practical specific energy values, but at low part-load conditions the physical loss of hydrogen to parasitic stack and system level processes begins to dominate the specific energy consumption. The ancillary balance of plant loads also increase in proportion to the amount of hydrogen produced below current densities of around 0.9 A/cm2, but contribute less to total system losses than the physical hydrogen losses.
Stack performance The cell voltage at which electrolysis is carried out for a given current density is known to vary with several parameters, including variable operating conditions. Lower cell voltages are desirable for a given current density as it results in lower power consumption for the same amount of hydrogen production, meaning a higher stack efficiency. Fig. 4 below shows the input current density versus cell voltage data including the temperature correlation for the wider range of stack operating temperatures studied. Due to transients from dynamic operation, stack temperature would fluctuate from a given set point, which correlates with the fluctuation in cell voltage for a given current density. It is evident that stack temperature has a strong influence on cell voltage even with low settling times between load changes. Increasing pressures on the hydrogen side increases cell voltage slightly, which is the expected trend. Going from 28 barg to 32 barg hydrogen incurs an overvoltage of 4.6 ± 3.5 mV per cell using 95% confidence intervals and analysis of variance (ANOVA) statistical methods on the data. The overvoltage incurred by pressurization of the hydrogen side is typically attributed to the predicted change in Nernst (reversible) voltage as described in equation (1) below. EOCV ðT; PÞ ¼ 1:228 0:0009ðT 298:15Þ !# " PH2;cathode P0:5 RT O2;anode þ ln 2F aH2O;anode
(1)
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
6
international journal of hydrogen energy xxx (xxxx) xxx
Fig. 3 e Sources of energy consumption in electrolyzer system per unit kg H2 produced.
Fig. 4 e j-V measurements with stack temperature for dynamic operation at Pcathode ¼ 30 Barg, Panode ¼ 1.6 Barg.
where T is the operating temperature of the electrolyzer in Kelvin, P is the partial pressures of the participating species, and R and F are the ideal gas constant and Faraday constant respectively. Other losses could also have a pressure dependence, especially concentration polarization, but current operation never occurred at very high current densities where the pressure dependence of such losses could potentially be observed. The observed voltage change due to hydrogen pressurization is in line with the change in voltage predicted by the Nernst equation of 1.7 mV per cell going from 28 to 32 barg (compared to 4.6 ± 3.5 mV). The losses due to pressurization of hydrogen in this fashion are of great interest due to the potentially higher compression efficiency relative to traditional mechanical compression methods. The overvoltage penalty is not entirely indicative of the electrical work needed to pressurize hydrogen in this fashion as it does not account for losses of hydrogen to membrane cross-over that occurs with increasing operating pressure in the cathode.
influencing variable appeared to be the ambient temperature and output current to a very small extent. For the most part, the AC/DC power electronics produced the most flexible losses with regards to part-load performance.
Ancillary balance of plant power consumption All other power consumption of the system not associated with the stack or losses to the AC/DC power electronics is treated as the balance of plant or ‘ancillary’ power consumption. While this refers to a number of blowers, solenoid valves, controls, and pumps, the vast majority of the 2.5 kW of electrical consumption observed as going to ancillary components was associated with the primary recirculating water pump, which consumed a fixed 2.2 kW of electrical power. Due to the inflexible nature of this load, ancillary power consumption takes an increasing percentage of the system energy share as stack load decreases. No notable correlation was found between other operating conditions and ancillary balance of plant power consumption.
AC/DC power electronics The AC/DC rectifier power supply for the stack maintained a flat contribution to system power consumption due to a relatively fixed efficiency for the range of output considered, down to 20% of rated power supply output. The only
Physical H2 loss The loss of product hydrogen is the major source of energy consumption after the stack at load conditions above 30% and dominates at lower load conditions. The contribution of this
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
international journal of hydrogen energy xxx (xxxx) xxx
loss makes operation of the electrolyzer system below a certain level prohibitive due to significant performance loss. Fig. 5 displays the ratio between expected hydrogen output due to measured current throughput according to Faraday's Law versus the actual measured hydrogen output, and how this varies with current density and H2 pressure. Faraday's Law is given below in equation (2) for molar hydrogen where j is the current density (A/cm2), A is the active stack area (cm2), n is the number of cells in the stack and MWH2 is the molecular weight of hydrogen gas (2 kg/kmol). m_ H2;prod;cath ¼
jAncells MWH2 2F
(2)
This loss primarily occurs at the PSA dryer system, as a continuous slipstream of dried hydrogen is sent from the actively adsorbing bed to the saturated bed to purge it of entrained moisture before the bed switches back. This flow is orifice driven and as such is a function of hydrogen pressure, nominally rated at 0.0744 kg H2/hr at 30 barg. There is secondary hydrogen loss due to gas cross-over in the stack, but the dryer-driven losses account for 90% of the physical H2 losses using the nominal flow rate and orifice flow relations. This hydrogen loss is primarily driven by the hydrogen pressure, largely independent of the total hydrogen throughput and not strongly dependent on temperature for the temperatures considered. This load condition independence of hydrogen cross-over leads to the increasingly dramatic losses at low load conditions. Recent years have seen preliminary work on mitigating the losses due to fixed PSA drying systems on electrolyzers through the implantation of variable PSA dryers [46]. The use of PSA dryer systems is standard in electrolyzer systems, both PEM [47,48] and Alkaline [49,50]. For many applications, dry hydrogen is desired (industrial end use, fueling etc.). In the case of pipeline injection, there is potential for some flexibility in the moisture content of the hydrogen. Guidelines for injection of customer owned gas are outlined in Southern California Gas Company's Rule 30, which calls for moisture content not exceeding 7 lbs of water per million standard cubic feet (MMscf) of gas [51]. This level of moisture is a common standard along many of the North American interstate gas transfer agreements [52]. For the case of the
7
saturated hydrogen at 20 C and 30 Barg entering the PSA dryer, the moisture content is approximately 39.5 lbs of water per MMscf gas. Further conditioning could be accomplished through cooling of the gas pre-injection and blending with dry natural gas for injection would further dry the overall mixture. For the 20 C and 30 Barg saturated condition, blends of up to 17% by volume H2 in dry natural gas would be within the 7 lbs water per MMscf gas limit.
Dynamic operation Solar load following A 75 kW rooftop PV system monitored remotely by the UCI campus's Melrok power monitoring network was chosen as the solar PV source to test electrolyzer system load following. The selected solar profiles demonstrated many of the expected changes in output of a fixed solar photovoltaic system due to seasonal variation in the southern California region. The greatest amount of solar irradiance occurred in the summer and spring, the lowest in the winter. Greater intermittency is experienced in the spring and winter when weather events such as rain and cloud cover are more common. The highest peak outputs are observed in the spring, due to the confluence of high solar irradiation giving greater throughput with lower ambient temperatures resulting in a higher PV module efficiency. Each run was carried out for a week's worth of solar PV output. To speed up the experiments, the solar PV system ‘downtime’ (I.e., nighttime) was eliminated from the control signal sent to the electrolyzer system for these tests. The control signal in terms of power is the rated PV output normalized to the 62 kW capacity of the electrolyzer system. System set points are 55 C stack temperature, 30 Barg cathodic pressure and 1.6 Barg anodic pressure. Fig. 6 shows the control signal (orange dots) in terms of power consumption versus measured power consumption (blue line) for the four PV load following runs. The winter and spring PV cases are the most dynamic cases for comparison of capacity factor and transient weather effects. The fall solar PV load following case includes some transients associated with intermittent cloud cover on days two and three. Testing was interrupted by drift in the valve
Fig. 5 e Physical H2 losses as a percentage of total parasitic system losses; net H2 output measured over Faradaic H2 production versus stack current density and H2 pressure. Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
8
international journal of hydrogen energy xxx (xxxx) xxx
Fig. 6 e Solar photovoltaic load following tests, system power consumption versus control signal.
Table 3 e Seasonal comparison for results of solar photovoltaic load following tests.
Capacity Factor -Test Only (%System Power Consumption) Capacity Factor - Overall (%System Power Consumption) Hydrogen production (Average kg/day) System Efficiency (%HHV H2) Stack Efficiency (%HHV H2) Maximum Slew Rate Up/Down (kW/sec)
spring tension on the mass flow controller, requiring disassembly and multiple readjustments of the spring tension. This readjustment resulted in a zero-flow event during the fall run (hours 36 to 38), requiring restart of the mass flow controller. This outage of the flow controller left the electrolyzer system in an idling state, and the test resumed seamlessly. Except for this excursion, the system power consumption very closely followed the control signal's trend and handled even the steepest transient power dynamics of solar PV. An additional exception to this is the minimum power consumption level of 14 kW, below which the electrolyzer system could not operate. An extended period of PV output transients (day three of spring) due to extensive marine layer that day was one such scenario where the electrolyzer could not as effectively follow such a low load. Included in Table 3 are both the capacity factor of the system as the tests were run (zero downtime due to lack of solar radiation at night) and including the down time. The latter result serves to highlight an issue encountered by many energy storage strategies when paired with solar PV systems; low capacity factors. To maximize the electricity arbitrage capabilities of the energy storage system and prevent curtailment from the PV system, the power capacity of the energy storage system would typically be sized close to the peak over-generation of the PV system. With a peak power
Winter
Spring
Fall
Summer
47.25% 15.89% 3.10 51.60% 77.70% 40.8/54.5
62.49% 28.97% 5.75 52.55% 73.92% 45.8/55.1
55.88% 26.05% 5.03 51.08% 75.53% 41.8/54.7
63.48% 38.07% 7.39 51.37% 73.92% 45.1/54.7
capacity of 75 kW on the PV system and 60 kW on the electrolyzer system, the two systems are relatively well matched. The result is a capacity factor of at most 38.07% during peak solar activity in the summer season, and as low as 15.89% in the winter. An encouraging result is the consistent overall system efficiency for all cases in the range of 51e53% on a higher heating value basis. Also of interest is the extremity of power transients that the electrolyzer is subjected to when load following solar PV dynamics. Due to limitations in sampling rate for the system power consumption metering and combined with the fact that the stack accounts for the vast majority of the variable power consumption (barring very slight variation in losses to the AC/ DC power electronics), the maximum slew rates are defined in terms of stack power change on a second to second basis. The maximum down ramp rate observed was a 100% turndown in the span of 1 s based off the previously established 55 kW maximum stack power observed in the benchmarking tests. Maximum up-ramps of approximately 80% of dispatchable load/second were also observed.
Wind load following The wind load following experiments utilized 3 weeks of measured net electrical power output from the Tehachapi wind farm with 5-min resolution. Normalization was applied
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
9
international journal of hydrogen energy xxx (xxxx) xxx
Fig. 7 e Wind load following test, weeks 1 through 3, system power consumption versus control signal. to match the wind farm output power to scale 1:1 with the electrolyzer system power capacity. As in the solar PV load following case system set points are 55 C stack temperature, 30 Barg cathodic pressure and 1.6 Barg anodic pressure. In contrast to the solar load following runs (in which nighttime periods were eliminated), the wind load following experiments involved prolonged minimum H2 output operation (~0.03 kg/h H2), representative of an idling state. Particularly throughout week one and the first half of week three. Fig. 7 displays the electrolyzer system power consumption (blue line) compared to the control signal (orange dots). The electrolyzer system was found to be fully capable of following the rapid power transients called for by the wind farm dynamics. The results of the three separate weeks and the overall performance for wind power load following are tabulated in Table 4. Splitting the runs up serves to highlight the effects that the dynamic nature of wind power, even in an aggregated wind farm averaged over a week-long period, has on the electrolyzer system, with capacity factors as low as 30% in week one up to 62% the next week. System efficiency suffers at lower capacity factors, even as stack efficiency climbs. More dramatic is the observed slew rates, with the stack ramping up as much as 54.8 kW in a second. Stack maximum power varies with operating conditions, but typically is in the range of
53e55 kW. For the current test conditions, this was effectively a 100% up-ramp in power from zero. Similar down-ramps were observed more regularly throughout the wind power dynamic testing. To mitigate losses at low load capacities, power cycling of the electrolyzer system below an effective power set point can be considered. The minimum effective power consumption set point of the electrolyzer system can be set at around 21 kWel correlated to when the hydrogen output is at 0.30 kg/h set point. These set points correlate to the 0.7 A/cm2 stack current density regime, below which system efficiency dropped off dramatically (Fig. 2). Going as low as 0.03 kg/h H2, the specific energy cost of hydrogen production was found to be 433 kWhel/kg H2, while at 0.30 kg/h H2 and above, efficiency flattens out at around 70 kWhel/kg H2; a six-fold improvement in efficiency. By extension, the 21-kW system power consumption set point can be treated as a minimum at which the electrolyzer system produces hydrogen at a reasonable efficiency. The amount of time the system takes to start from a completely de-energized state, or ‘cold’ start, is an important metric for high transient load following applications. From a cold start, electrolyzer systems generally go through three stages of start-up; the booting of the onboard pc and controls, the venting of the hydrogen process piping to clear any air
Table 4 e Wind load following tests with and without minimum power condition cycling.
Capacity Factor (%System Power Consumption) Hydrogen production (Average kg/day) System Efficiency (%HHV H2) Stack Efficiency (%HHV H2) Maximum Slew Rate Up/Down (kW/sec)
Week 1
Week 2
Week 3
Overall
30.24% 3.55 31.07% 80.96% 46.4/-55.2
62.09% 12.05 51.35% 73.48% 44.7/-55.2
44.15% 7.04 42.06% 75.73% 54.7/-55.1
45.68% 7.60 43.96% 75.73% e
10 73.43% 14.44% 3.03 55.55%
11 30.07% 55.72% 11.78 55.95%
10 60.38% 31.16% 6.62 56.19%
31 54.62% 33.77% 7.14 55.90%
With Power Cycling Power Cycles (# of) Downtime (% Hours off/Hours Total) Capacity Factor (%System Power Consumption) Hydrogen production (Average kg/day) System Efficiency (%HHV H2)
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
10
international journal of hydrogen energy xxx (xxxx) xxx
gases present, and the ramping of the stack current up to full capacity. In the case of the Model C10 electrolyzer system, these steps are specified to take 30 s for initial start-up, 130e600 s for venting of the hydrogen process piping, and 180 s to ramp the electrolyzer stack, for a total specified start-up time of anywhere between 5 min and 40 s to upwards of 13 and a half minutes. Actual observed start-up times were far closer to the lower end of the system specs. Furthermore, the system starts producing H2 to the process connection rather than venting once the set point pressure is reached, which happens before full stack current is reached. The fastest observed start-up reached full hydrogen pressure and started production in 4 and a half minutes, full stack current at 5 and a half minutes. To simulate the concept of regular on/off dynamic operation, the three-week period studied in the wind load following experiments are pruned of any system activity below a 14 kW system power consumption signal. A start-up period of 5 min is added to each on cycle based upon the analysis of the system cold start behavior. Hydrogen lost when the system cycles off and vents on-board gas is accounted for. Power consumption on shutdown was not considered as the system shutdown takes less than 1 min to entirely shut down, with stack power being cut instantaneously, leaving only ancillary systems using power during the shutdown. Table 4 summarizes the results of the wind power experiments using the power cycling approach. The electrolyzer system went through a power cycle on average one to two times per day, and spent over half of the total operation time turned off. This highlights, once again, the expected issue of sizing these energy storage systems for meeting the needs of balancing variable renewable energy resources. On the other hand, system efficiency did improve with this on/off control approach to a much more reasonable 55% HHV H2.
Summary and conclusions Over 4000 h of operation of a 60 kW PEM electrolyzer system integrated with natural gas pipeline injection followed by combustion in a gas turbine were achieved. Over the course of the 4000 h of operation several hundred hours of sustained part-load operation, and over 2000 h of VRES load following were accomplished. The control of the PEM electrolyzer system for dynamic dispatch response to VRES load following was accomplished using an external mass flow controller. VRES load following was demonstrated for both a solar PV system across a wide range of conditions, and for aggregated wind turbine farm resources. The data acquired from the dynamic operation of the electrolyzer system indicates that PEM electrolyzers can operate under extreme power transients on a second-to-second time scale, not only at a stack level but from an overall system level, supporting the idea that PEM electrolyzer systems can provide a number of ancillary grid services as well as load balancing support [53]. Analysis of the electrolyzer system included benchmarking of the overall electrolyzer system including water consumption, power electronics, ancillary system power
consumption, hydrogen drying components, and the electrolysis process itself. Dynamic operation of the electrolyzer system across the available range of operating parameters allowed for extended characterization of part-load performance, which is essential to the success of such a system in power-to-gas applications where lower equipment capacity factors are expected due to the intermittency of solar and wind resources. Quick start-up times from a ‘cold state’ on the order of 5 min can be utilized to further improve system performance in low utilization factor cases. Such scenarios also lend themselves to the notion of a hybrid P2G energy storage system incorporating batteries [28,54]. Statistical analysis on operational data provided insight regarding the primary performance influencing operating conditions of the electrolyzer system and its components. The experimental analysis indicated relatively stable system efficiency down to 35% load condition (0.7 A/cm2 at the stack). Exceedingly poor performance below 35% load condition (0.7 A/cm2) was observed primarily due to high percentage losses of the hydrogen product due to the timed switching control of the PSA drying beds. This finding suggests a recommended minimum operating condition of 35%, rather than the rated 10% part-load condition. The increasing discrepancy between the measured hydrogen output and the amount of hydrogen produced according to the Faradaic relation at lower current densities explained the large drop in system efficiency below 35% part-load. In this case the PSA dryer system accounted for the majority of H2 loss. For pipeline injection applications, it is apparent that the PSA drying system may not be necessary, due to less stringent moisture content requirements as compared to industrial or commercial operations.
Acknowledgements This work was supported by the National Fuel Cell Research Center at the University of California, Irvine with partial funding support from Southern California Gas Company.
Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.ijhydene.2020.01.228.
references
[1] Koebrich S, Chen E, Bowen T, Forrester S, Tian T. Renewable energy data book. U.S. Department of Energy; 2017. [2] Anuta H, Ralon P, Taylor M. Renewable power generation costs in 2018. Abu Dhabi: International Renewable Energy Agency (IRENA); 2019. [3] Bird JCXWL. Wind and solar energy curtailment: experience and practices in the United States. Golden, CO: National Renewable Energy Laboratory (NREL); 2014. [4] N M, V C, P C, D C, M F, F A, et al. Intermittent and stochastic character of renewable energy sources: consequences, cost of intermittence and benefit of forecasting. Renew Sustain Energy Rev 2018;87:96e105.
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
international journal of hydrogen energy xxx (xxxx) xxx
[5] Shaner MR, Davis SJ, Lewis NS, Caldeira K. Geophysical constraints on the reliability of solar and wind power in the United States. Energy Environ Sci 2018;11:914e25. [6] J JH, N EW, Felix Cebulla PM. How much electrical energy storage do we need? A synthesis for the U.S., Europe, and Germany. J Clean Prod 2018;181:449e59. [7] Aneke M, Wang M. Energy storage technologies and real life applications - a state of the art review. Appl Energy 2016;179:350e77. [8] Saeedmanesh A, Mac Kinnon MA, Brouwer J. Hydrogen is essential for sustainability. Curr Opin Electrochem 2018;12:166e81. [9] Amrouche SO, Rekioua D, Rekioua T, Bacha S. Overview of energy storage in renewable energy systems. Int J Hydrogen Energy 2016;41(45):20914e27. [10] Dincer I, Acar C. Review and evaluation of hydrogen production methods for better sustainability. Int J Hydrogen Energy 2015;40:11094e111. [11] Celik D, Yıldız M. Investigation of hydrogen production methods in accordance with green chemistry principles. Int J Hydrogen Energy 2017;42:23395e401. [12] Zhang F, Zhao P, Niu M, Maddy J. The survey of key technologies in hydrogen energy storage. Int J Hydrogen Energy 2016;41(33):14535e52. [13] Dincer I, Suleman F, Agelin-Chaab M. Comparative impact assessment study of various hydrogen production methods in terms of emissions. Int J Hydrogen Energy 2016;41(19):8364e75. [14] Glenk G, Reichelstein S. Economics of converting renewable power to hydrogen. Nat Energy 2019;4:216e22. [15] Eichman J, Hodge B-M, Kurtz J. Cost-competitive electrolysisbased hydrogen under current U.S. electric utility rates. In: 2018 AIChEAnnual meeting, Pittsburgh, Pennsylvania; 2018. [16] Messaoudani ZL, Rigas F, Hamid MDB, Hassan CRC. Hazards, safety and knowledge gaps on hydrogen transmission via natural gas grid: a critical review. Int J Hydrogen Energy 2016;41(39):17511e25. [17] Zhao Y, McDonell V, Samuelsen S. Influence of hydrogen addition to pipeline natural gas on the combustion performance of a cooktop burner. Int J Hydrogen Energy 2019;44(23):12239e53. [18] Gimeno-Escobedo E, Cubero A, Ochoa JS, Fueyo N. A reduced mechanism for the prediction of methane-hydrogen flames in cooktop burners. Int J Hydrogen Energy 2019;44(49):27123e40. [19] Zhao Y, Soto Leytan KN, McDonell V, Samuelsen S. Investigation of visible light emissions from hydrogen-air research flames. Int J Hydrogen Energy 2019;44(39):22347e54. [20] Zhao Y, McDonell V, Samuelsen S. Experimental assessment of the combustion performance of an oven burner operated on pipeline natural gas mixed with hydrogen. Int J Hydrogen Energy 2019;44(47):26049e62. [21] Choudhury S, McDonell V, Samuelsen S. Combustion performance of low-NOx and conventional storage water heaters operated on hydrogen enriched natural gas. Int J Hydrogen Energy 2020;45(3):2405e17. [22] Valera-Medina A, Morris S, Runyon J, Pugh D, Marsh R, Beasley P, et al. Ammonia, methane, and hydrogen for gas turbines. Energy Procedia 2015;75:118e23. [23] Jiang Y, del Alamo G, Gruber A, Bothien MR, Seshadri K, Williams FA. A skeletal mechanism for prediction of ignition delay times and laminar premixed flame velocities of hydrogen-methane mixtures under gas turbine conditions. Int J Hydrogen Energy 2019;44(33):18573e85. [24] Liemberger W, Halmschlager D, Miltner M, Harasek M. Efficient extraction of hydrogen transported as co-stream in the natural gas grid - the importance of process design. Appl Energy 2019;233e234:747e63.
11
[25] Vlap H. Technical assumptions, technology demonstration and results P2G project. Groningen, Netherlands: DNV GL Oil & Gas; 2015. [26] Schulze P, Holstein J, van den Noort A, Knijp J. Power-to-gas in a decarbonized european energy system based on renewable energy sources. European Power To Gas Platform; 2018. [27] European Commission. Energy roadmap 2050. Luxembourg: European Union; 2011. [28] Papadopoulos V, Desmet J, Knockaert J, Develder C. Improving the utilization factor of a PEM electrolyzer powered by a 15 MW PV park by combining wind power and battery storage- Feasibility study. Int J Hydrogen Energy 2018;43:16468e78. [29] Laoun B, Khellaf A, Naceur MW, Kannan AM. Modeling of solar photovoltaic polymer electrolyte membrane electrolyzer direct coupling for hydrogen generation. Int J Hydrogen Energy 2016;41(24):10120e35. ndez-Ramı´rez LM, Garcı´a-Va zquez CA, [30] Sarrias-Mena R, Ferna Jurado F. Electrolyzer models for hydrogen production from wind energy systems. Int J Hydrogen Energy 2015;40(7):2927e38. [31] Aouali FZ, Becherif M, Ramadan HS, Emziane M. Analytical modelling and experimental validation of proton exchange membrane electrolyser for hydrogen production. Int J Hydrogen Energy 2017;42(2):1366e74. [32] Grigoriev SA, Kalinnikov AA. Mathematical modeling and experimental study of the performance of PEM water electrolysis cell with different loadings of platinum metals in electrocatalytic layers. Int J Hydrogen Energy 2017;42(3):1590e7. [33] Lee B, Park K, Kim H-M. Dynamic simulation of PEM water electrolysis and comparison with experiments. Int J Electrochem Sci 2013;8:235e48. [34] Schalenbach M, Carmo M, Fritz DL, Mergel J, Stolten D. Pressurized PEM water electrolysis: efficiency and gas crossover. Int J Hydrogen Energy 2013;38:14921e33. [35] K J, R A, H V, N K, A M, Koponen J. Control and energy efficiency of PEM water electrolyzers in renewable energy systems. Int J Hydrogen Energy 2017;42(50):29648e60. [36] Mraoui A, Benyoucef B, Hassaine L. Experiment and simulation of electrolytic hydrogen production: case study of photovoltaic electrolyzer direct connection. Int J Hydrogen Energy 2018;43(6):3441e50. [37] Stansberry J, Hormaza Mejia A, Zhao L, Brouwer J. Experimental analysis of photovoltaic integration with a proton exchange membrane electrolysis system for powerto-gas. Int J Hydrogen Energy 2017;42(52):30569e83. [38] Saadi A, Becherif M, Ramadan H. Hydrogen production horizon using solar energy in Biksra, Algeria. Int J Hydrogen Energy 2016;41:21899e912. [39] Espinosa-Lopez M, Darras C, Poggi P, Glises R, Baucour P, Rakotondrainibe A, et al. Modelling and experimental validation of a 46 kW PEM high pressure water electrolyzer. Renew Energy 2018;119:160e73. [40] Alaefour I, Shahgaldi S, Ozden A, Li X, Hamdullahpur F. The role of flow-field layout on the conditioning of a proton exchange membrane fuel cell. Fuel 2018;230:98e103. [41] Vang JR, Andreasen SJ, Araya SS, Kaer SK. Comparative study of the break in process of post doped and sol-gel high temperature proton exchange membrane fuel cells. Int J Hydrogen Energy 2014;39(277):14959e68. [42] Thomas S, Araya SS, Vang JR, Kaer SK. Investigating different break-in procedures for reformed methanol high temperature proton exchange membrane fuel cells. Int J Hydrogen Energy 2018;43(31):14691e700. [43] Silva VB, Rouboa A. Hydrogen-fed PEMFC: overvoltage analysis during an activation procedure. J Electroanal Chem 2012;671:58e66.
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
12
international journal of hydrogen energy xxx (xxxx) xxx
[45] Qi Z, Kaufman A. Quick and effective activation of protonexchange membrane fuel cells. J Power Sources 2002;114. 21-13. [46] Peters M, Harrison K, Dinh H. Renewable eletrolysis integrated systems development and testing. Golden, CO: U.S. Department of Energy Hydrogen and Fuel Cells Program; 2016. [47] Harrison K, Martin G. Renewable hydrogen: integration, validation and demonstration. In: NHA annual hydrogen conference, Sacramento, California; 2008. [48] Hydrogenics. OnSite hydrogen generation: HyLYZER PEM electrolysis technology. In: Hydrogenics Europe NV, on-site generation, Nijverheidsstraat 48-C, Oevel, B-2260, Belgium; 2018. nchez M, Amores E, Rodrı´guez L, Clemente-Jul C. Semi[49] Sa empirical model and experimental validation for the performance evaluation of a 15 kW alkaline water electrolyzer. Int J Hydrogen Energy 2018;vol. 43:20332e45.
[50] Hydrogenics. HYSTAT hydrogen generators. In: Hydrogenics on-site generation, Nijverheidsstraat 48c, 2260 Oevel, Belgium; 2018. [51] Southern California Gas Company. Rule No. 30 transportation of customer-owned gas. Los Angeles, California: California Public Utilities Commission (CPUC); 2016. [52] Foss MM. Interstate natural gas- quality specifications & interchangeability. In: Energy economics research at the Bureau of Economic Geology, Sugar Land, Texas; 2004. [53] Hovsapian R. Role of electrolyzers in grid services. Washington D.C.: National Renewable Energy Laboratory (NREL) & Idaho National Laboratory (INL); 2017. [54] Maclay JD, Brouwer J, Samuelsen SG. Experimental results for hybrid energy storage systems coupled to photovoltaic generation in residential applications. Int J Hydrogen Energy 2011;vol. 36:12130e40. 19.
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
Available online at www.sciencedirect.com
ScienceDirect journal homepage: www.elsevier.com/locate/he
Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application John M. Stansberry, Jacob Brouwer* National Fuel Cell Research Center, University of California, Irvine, CA 92697, USA
highlights A 60 kW PEM Electrolyzer system load follows solar PV and wind farm dynamics. Cycling on/off from cold start leads to better electrolyzer efficiency. Ancillary losses, particularly for H2 drying, dominate at low load conditions. Mass flow controller-based control was used to dispatch the electrolyzer. Operating conditions were varied and performance impacts assessed.
article info
abstract
Article history:
A 60 kW PEM electrolyzer was modified to have dynamic dispatch capabilities through the
Received 23 November 2019
use of an external mass flow controller and was subsequently operated and studied in
Received in revised form
detail as a part of the UC Irvine power-to-gas (P2G) demonstration project. The system
15 January 2020
operated in load following for both rooftop solar PV output and aggregated wind farm
Accepted 29 January 2020
power. The electrolyzer system was able to handle 100% up and down ramps of the elec-
Available online xxx
trolyzer stack in sub-second intervals during variable renewable energy load following experiments. Overall system efficiency was improved by imposing a minimum load con-
Keywords:
dition to avoid high parasitic losses at low power conditions, and cycling the system off/on
Proton exchange membrane
as required and enabled by quick cold start-up capability. Performance was characterized
electrolyzer
for varying levels of part load and dynamic operation. The gas drying process was found to
Solar photovoltaic
be a significant source of loss at low power conditions.
Power-to-gas
© 2020 Published by Elsevier Ltd on behalf of Hydrogen Energy Publications LLC.
Wind power Electrolysis
Introduction Issues associated with the finite nature of fossil fuels and their association with the emissions of both criteria pollutants and greenhouse gases has directed a shift in the energy sector
towards renewable resources. Of the many forms of renewable energy resources available, photovoltaic (PV) solar and wind power generation have seen the greatest increase in proliferation [1]. Along with this deployment has come an increasing cost-competitiveness with fossil fueled power generation, with solar PV modules and land-based wind
* Corresponding author. E-mail address: [email protected] (J. Brouwer). https://doi.org/10.1016/j.ijhydene.2020.01.228 0360-3199/© 2020 Published by Elsevier Ltd on behalf of Hydrogen Energy Publications LLC. Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
2
international journal of hydrogen energy xxx (xxxx) xxx
turbines projected to be the least expensive source of new electricity generation capacity by 2020 [2]. To-date, much has been accomplished in terms of integrating the relative small amounts (up to around 30%) of solar and wind power generation with current electrical grid architecture and infrastructure. Integrating larger amounts of these variable renewable energy sources (VRES) is expected to be a greater challenge due to their intermittency and uncontrollability [3,4]. The need for long term energy storage on the order of days up to months has been well established to ultimately ensure the effectiveness of a highly renewable electrical grid [5,6]. Storing energy in the form of hydrogen is currently one of the most appropriate options for meeting these long-term energy storage requirements [7e9]. Hydrogen can be produced through a number of different methods; electrolysis using electricity as the primary energy source, steam methane reforming (SMR) or hydrolysis using thermal energy, or various photolytic processes [10e12]. Today, production of hydrogen through SMR dominates because it is cheapest, with production via electrolysis being the only other appreciable commercial method. Electrolysis utilizing VRES in the form of solar PV or wind farm power, also known as power-to-gas (P2G) has the lowest environmental impact from a climate and air quality perspective for producing hydrogen [13]. Falling costs of electrolyzers, solar PV, and wind power in combination with favorable regulatory and policy environments has led to cost competitive applications for P2G today (e.g., to produce hydrogen for fuel cell vehicles in California with support of the Low Carbon Fuel Standard policy), with the potential to be broadly competitive with non-renewable hydrogen sources within the decade [14]. In some regions of the U.S., electrolysis produced hydrogen is already costcompetitive with gasoline vehicle use today [15]; although building out the infrastructure for transmitting, distributing, and dispensing of hydrogen remains a challenge. Other pathways of interest include the storage and subsequent utilization of hydrogen in either a fuel cell or gas-turbine based power plants, or the injection of hydrogen into natural gas infrastructure to increase the renewable content of pipeline gas and reduce carbon intensity. Converting existing carbon intensive gas grid infrastructure in a piecewise manner through the introduction of hydrogen provides an opportunity to accelerate the transition away from fossil fuels, however much work remains to be done before appreciable amounts of hydrogen can be introduced [16]. The combustion of hydrogen-enriched natural gas without modification of existing end uses is an active and vital area of research, with applications ranging from stovetops [17e19], oven burners [20], and water heaters [21] as well as gas-fired turbines [22,23]. The gas grids could further be utilized as a transport medium for hydrogen end-uses by utilizing separation techniques to extract hydrogen from the hydrogen-enriched natural gas for fueling of fuel cells in either transportation or power generation applications or other industrial end uses requiring high purity hydrogen [24]. Numerous power-to-gas projects have demonstrated integration with natural gas infrastructure [25,26] and the current European Union (EU) energy roadmap has identified the natural gas system as critical for meeting deep decarbonization and renewable penetration goals for
their overall energy system due to the critical flexibility that the gas network provides [27]. On June 22nd, 2016, the University of California, Irvine (UCI) in collaboration with the Southern California Gas Company (SoCalGas) launched the UCI P2G demonstration comprised of a 60 kW proton exchange membrane (PEM) electrolyzer co-located with the UCI combined heat and power combined cycle power plant. The main research objectives of the UCI P2G demonstration included evaluating the dynamic dispatch of a commercial PEM electrolyzer system in load following both solar PV and wind farm power dynamics and characterizing the PEM electrolyzer performance. Furthermore, produced hydrogen was injected directly to the gas grid upstream of the campus combustion turbine in the first injection of hydrogen gas to existing natural gas infrastructure for the United States. There are a number of studies which model P2G systems that deploy real-scale PEM electrolyzers in P2G scenarios [28e30]. Additionally, there exists significant depth of research on the modeling of the electrolyzer's themselves [31e34]; however, data and analysis from the actual deployment of PEM systems in P2G applications is lacking in the literature. There are a number of experimental studies on PEM electrolyzer systems either operated dynamically or directly integrated with VRES [35e38], but larger-scale systems have not been studied extensively in the peer-reviewed literature, with the lone exception of the 46 kW PEM electrolyzer studied as a part of the MYRTE demonstration platform at the University of Corsica [39]. The objective of this paper is to provide an in-depth look into the operation of a commercial full-scale PEM electrolyzer system, deployed in a P2G operation setting following PV and wind farm power dynamics. Baseline performance is characterized, then compared to the performance of the system when load following intermittent dynamics associated with solar PV and wind power. The performance of the electrolysis process and the balance of plant components are studied, and ancillary aspects of system performance are measured (startup and shut down times, stack slew rates, water consumption, etc.). Recommendations for further research and development for deployment of PEM systems in P2G applications are identified and discussed.
Experimental methods & materials Electrolyzer system The UCI P2G demonstration involves the integration of an electrolyzer system with the UCI Central Plant. Hydrogen produced from the electrolyzer system is mixed into the highpressure natural gas pipeline upstream of the gas turbine and subsequently combusted to complete the P2G2P utilization pathway. The PEM electrolyzer deployed is a Proton Onsite Model C10. The C10 system is a differential pressure PEM electrolyzer system. The C Series PEM electrolysis cell stack is comprised of 65 circular cells with an active area of 214 cm2. Key characteristics and operating parameters of the electrolyzer system are shown in Table 1. The balance of plant for the PEM
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
international journal of hydrogen energy xxx (xxxx) xxx
Table 1 e Operating parameters for the Model C10 electrolyzer system. Hydrogen e Cathode Production (kg/hr) Pressure (barg) Oxygen - Anode Production (kg/hr) Pressure (barg) Feed Water - Anode Circulation Rate (L/min) Consumption Rate (L/min) Temperature (C ) Quality (MU-cm) Electrical Breaker Rating System Power (kW AC) Electrolysis Stack (Volts/Amps DC) Cooling Chiller System Chiller Capacity (kWth) Cooling Requirement (kWth)
0e0.91 0e34.5 14e128 0e2.76 37.9 0.15 5e65 >1.0 480 VAC 3-phase, 100 kVA 60 140/410 Accuchiller air-cooled chiller (PN#: NQA13C1E213C) 55.7 33.4
3
electrolyzer is shown in a simplified process flow diagram (Fig. 1), along with supporting data acquisition (DAQ) and control systems. As shown in Fig. 1, a hydrogen management subsystem maintains hydrogen pressure in the system and removes water before heading to the process connection. Generated hydrogen gas first enters a hydrogen-water phase separator vessel where system-side hydrogen pressure is monitored and maintained. Liquid water is dropped out by gravity in this vessel, and intermittently ‘flushed’ to send the water back into the deionized (DI) water loop. From the hydrogen water phase separator, hydrogen gas passes through a heat exchanger, further condensing out water, before entering a secondary larger volume hydrogen-water phase separator vessel. In the final drying stage hydrogen gas enters a pressure swing adsorption (PSA) dryer system. After the drying process a series of check valves, pressure transducers, and a back-pressure regulator control the output pressure of the hydrogen gas to the delivery point. This pressure feedback control loop is the primary control variable for determining the amount of electrical power that is delivered to the electrolysis process.
Fig. 1 e Simplified process flow diagram for the electrolyzer system in the UCI P2G demonstration project.
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
4
international journal of hydrogen energy xxx (xxxx) xxx
Generated oxygen gas is entrained in the water electrode and exits with the DI water. This mixture goes to a wateroxygen phase separator, after which oxygen gas exits to an exterior vent with a small amount of water (saturated conditions). Sensors on this subsystem monitor pressure and for the presence of hydrogen gas to prevent a flammable mixture.
Data acquisition systems The electrolyzer system has an internal data stream that provides high resolution, accurate data concerning system operation and control through a Modbus protocol. Onboard metrics of interest to the study of the system include the system hydrogen pressure at the outlet of the hydrogen electrode (in barg), oxygen pressure at the oxygen-water phase separator (in barg), system water temperature at the outlet of the DI water subsystem heat exchanger (in C), hydrogen gas temperature at the hydrogen management subsystem heat exchanger (in C), the stack voltage (in volts), and the stack current command signal (in amps). The states of the system solenoid valves, water levels, coolant temperature at the heat exchangers, DI water quality at the inlet and in the recirculating water loop are also monitored and recorded. To complement the on-board data acquisition and provide verification of some measurements, some external sensing and data acquisition was implemented. Power meters (Dent ElitePro) were installed at the electrolyzer system connection to the grid, on the electrolyzer system breaker to the ancillary power demands, and at the grid connection to the chiller system, to record the net power consumption (in kW), voltage across the 3-phases (in volts AC), amperage across the 3phases (in amps AC), and the power factor. Having power monitoring on both the overall system consumption and on the ancillary systems circuit allowed for the characterization of the AC electricity consumption of the electrolysis process separate from conversion losses and from the electrical power needed to run the pumps, blowers, valves, etc; that make up the ancillary power demands. An additional Dent Elitepro system was connected to the cell stack to independently measure the stack voltage at a higher resolution than the internal data stream. The stack current was measured using two split-core current transducers (CR Magnetics CR5220S Split Core Current Transducers) rated for 0e300 amps DC. Verification of the current reading was accomplished intermittently with a Fluke split-core current transformer (Fluke i410 AC/DC Current Clamp). Hydrogen gas mass flow from the system to the end process was measured using a Sierra Instruments 840H HiTrak Mass Flow Controller. The 4e20 mA analog output logic from the split-core current transducers and mass flow controller were logged using a Dent DataLogger Pro.
Mass flow controller & control system To control the dispatch of the Model C10 system for dynamic response, a mass flow controller was installed on the hydrogen product line. The mass flow controller is able to dispatch the electrolyzer system by manipulating the hydrogen flow, simulating a reduced hydrogen demand downstream of the system. The hydrogen management
subsystem's pressure feedback loop subsequently senses the higher downstream pressure and reduces the current throughput to the electrolysis stack accordingly. For dynamic dispatch, a dispatch profile from a selected data source, or a general load profile such as a stepwise ramp, is converted to comma-separated variable (.csv) file format. The .csv file is read by a Python script, which outputs the signal value through serial communication to a Seeed Studio Seeeduino microcontroller. The microcontroller reads the serial value and then outputs an equivalent 0e5V DC analog signal through pulse width modulation. This signal is converted to a 4e20 mA signal by way of a signal conditioning circuit comprised of an RC circuit for conditioning the Volts DC signal which then goes through a Texas Instruments XTR110 precision Voltage-to-Current converter integrated circuit (IC). This 4e20 mA signal is then communicated to the mass flow controller which controls the hydrogen flow from the system. Hydrogen mass flow was measured and controlled using Sierra Instruments Hi-Trak 840H mass flow controllers (P/N#: 840H-4-OV1-SV1-D-V4-S4-HP).
Results Steady state performance benchmarking For the first 1000 h of operation the Model C10 electrolyzer system was operated at full throughput to establish baseline operation characteristics and performance. Table 2 compares several performance characteristics at 100, 600, and 1000 h of operation. Notably, an appreciable increase in stack current, and associated improvements in AC/DC power electronics efficiency (higher DC output), H2 dryer efficiency (higher H2 throughput), and overall system efficiency, occurred over this time period. After 800 h, stack current was consistently around the rated 410 amps DC. This suggests a slight ‘breakin’ period, which can be attributed to the electrolysis stack, rather than the power supply, as the DC power supply was replaced at 600 h of operation without any impact on the increasing current trend. In PEM electrolyzers, the membrane electrode assembly (MEA) typically undergoes an activation process immediately after manufacturing that can last anywhere from several hours to several days, resulting in progressively better cell performance that ultimately plateaus [40]. Generally, ‘break-in’ periods are more commonly observed in studies of high temperature proton exchange membranes for application in phosphoric acid fuel cells (PAFC) and direct methanol fuel cells (DMFC) [41,42], but are not unheard of for PEM fuel cell MEAs [43]. An increase in current density without an increase in applied potential is typical of these ‘break in’ or activation processes, which involve cycling of the cell [45]. The electrolyzer system rated water consumption by the OEM is given as ‘roughly’ 2.4 gallons per hour at full output, matching the water requirement for the electrolysis reaction alone. Actual system water consumption during benchmarking was found to be approximately 3.1 gal/hr on average, varying minimally as operation time went on. Losses associated with power electronics and hydrogen drying are comparable and are the most significant
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
5
international journal of hydrogen energy xxx (xxxx) xxx
Table 2 e Full throughput benchmarking of electrolyzer system versus specifications.
H2 Output (kg/hr) Stack Current (Amps) Water Consumption (Gal/hr) Stack Power (kW DC) System Power (kW AC) H2 Dryer Efficiency (%) AC/DC Efficiency (%) Stack Efficiency (%HHV H2) System Efficiency (%HHV H2) System Efficiency w/Chiller (%HHV H2)
Baseline Specifications
Run 1 100 Hours
Run 2 600 Hours
Run 3 1000 Hours
0.910 410.00 2.400 57.40 62.00 ~90.00% N/A N/A 57.24% N/A
0.899 401.52 3.095 54.54 61.67 90.85% 92.09% 72.03% 57.47% 45.99%
0.912 407.99 3.031 55.09 61.68 90.49% 93.03% 72.06% 58.25% 46.79%
0.936 411.30 3.116 55.38 61.56 92.24% 93.69% 72.17% 59.88% e
contributors to system losses. The majority of system energy conversion occurs in the electrolysis process itself and in the chiller system operation that provides thermal management. The magnitude of energy conversion that goes to the chiller is more than twice the amount lost to the rest of the balance of plant, including power electronics conversion losses. In terms of hydrogen production, a quarter of the electricity consumption is directed to the chiller system, equivalent to 17 kWh of electricity per kg of hydrogen produced. The power meter associated with the chiller failed around the ~800 operating hours mark. As the power consumption of the chiller was not of major interest to this study, the meter was not replaced.
System losses characterization The specific energy consumption of the electrolyzer system describes the net amount of electrical power in kWh consumed per kg of H2 produced. This metric was measured for all experiments and is presented as a function of stack current density in Fig. 2. Specific energy remains relatively flat as power is reduced until around a current density of 1 A/cm2, corresponding to roughly a 50% load condition. Beyond this point, specific energy costs begin to rise significantly, becoming prohibitive at any current densities of about 0.6 A/ cm2 and below.
Fig. 2 e Full- and part-load system specific energy consumption (kWh electricity per kg H2 produced) presented versus stack current density.
The specific energy consumption of the system can be broken down into four sources of energy consumption; the electrolysis process or ‘stack’ energy consumption, the energy losses associated with physical loss of H2, energy consumption associated with the AC/DC power electronics, and the ancillary balance of plant energy consumption. The contribution of each of these components on a percentage basis is presented in Fig. 3. It is clear that the electrolysis stack is the dominant source of energy consumption for the range of practical specific energy values, but at low part-load conditions the physical loss of hydrogen to parasitic stack and system level processes begins to dominate the specific energy consumption. The ancillary balance of plant loads also increase in proportion to the amount of hydrogen produced below current densities of around 0.9 A/cm2, but contribute less to total system losses than the physical hydrogen losses.
Stack performance The cell voltage at which electrolysis is carried out for a given current density is known to vary with several parameters, including variable operating conditions. Lower cell voltages are desirable for a given current density as it results in lower power consumption for the same amount of hydrogen production, meaning a higher stack efficiency. Fig. 4 below shows the input current density versus cell voltage data including the temperature correlation for the wider range of stack operating temperatures studied. Due to transients from dynamic operation, stack temperature would fluctuate from a given set point, which correlates with the fluctuation in cell voltage for a given current density. It is evident that stack temperature has a strong influence on cell voltage even with low settling times between load changes. Increasing pressures on the hydrogen side increases cell voltage slightly, which is the expected trend. Going from 28 barg to 32 barg hydrogen incurs an overvoltage of 4.6 ± 3.5 mV per cell using 95% confidence intervals and analysis of variance (ANOVA) statistical methods on the data. The overvoltage incurred by pressurization of the hydrogen side is typically attributed to the predicted change in Nernst (reversible) voltage as described in equation (1) below. EOCV ðT; PÞ ¼ 1:228 0:0009ðT 298:15Þ !# " PH2;cathode P0:5 RT O2;anode þ ln 2F aH2O;anode
(1)
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
6
international journal of hydrogen energy xxx (xxxx) xxx
Fig. 3 e Sources of energy consumption in electrolyzer system per unit kg H2 produced.
Fig. 4 e j-V measurements with stack temperature for dynamic operation at Pcathode ¼ 30 Barg, Panode ¼ 1.6 Barg.
where T is the operating temperature of the electrolyzer in Kelvin, P is the partial pressures of the participating species, and R and F are the ideal gas constant and Faraday constant respectively. Other losses could also have a pressure dependence, especially concentration polarization, but current operation never occurred at very high current densities where the pressure dependence of such losses could potentially be observed. The observed voltage change due to hydrogen pressurization is in line with the change in voltage predicted by the Nernst equation of 1.7 mV per cell going from 28 to 32 barg (compared to 4.6 ± 3.5 mV). The losses due to pressurization of hydrogen in this fashion are of great interest due to the potentially higher compression efficiency relative to traditional mechanical compression methods. The overvoltage penalty is not entirely indicative of the electrical work needed to pressurize hydrogen in this fashion as it does not account for losses of hydrogen to membrane cross-over that occurs with increasing operating pressure in the cathode.
influencing variable appeared to be the ambient temperature and output current to a very small extent. For the most part, the AC/DC power electronics produced the most flexible losses with regards to part-load performance.
Ancillary balance of plant power consumption All other power consumption of the system not associated with the stack or losses to the AC/DC power electronics is treated as the balance of plant or ‘ancillary’ power consumption. While this refers to a number of blowers, solenoid valves, controls, and pumps, the vast majority of the 2.5 kW of electrical consumption observed as going to ancillary components was associated with the primary recirculating water pump, which consumed a fixed 2.2 kW of electrical power. Due to the inflexible nature of this load, ancillary power consumption takes an increasing percentage of the system energy share as stack load decreases. No notable correlation was found between other operating conditions and ancillary balance of plant power consumption.
AC/DC power electronics The AC/DC rectifier power supply for the stack maintained a flat contribution to system power consumption due to a relatively fixed efficiency for the range of output considered, down to 20% of rated power supply output. The only
Physical H2 loss The loss of product hydrogen is the major source of energy consumption after the stack at load conditions above 30% and dominates at lower load conditions. The contribution of this
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
international journal of hydrogen energy xxx (xxxx) xxx
loss makes operation of the electrolyzer system below a certain level prohibitive due to significant performance loss. Fig. 5 displays the ratio between expected hydrogen output due to measured current throughput according to Faraday's Law versus the actual measured hydrogen output, and how this varies with current density and H2 pressure. Faraday's Law is given below in equation (2) for molar hydrogen where j is the current density (A/cm2), A is the active stack area (cm2), n is the number of cells in the stack and MWH2 is the molecular weight of hydrogen gas (2 kg/kmol). m_ H2;prod;cath ¼
jAncells MWH2 2F
(2)
This loss primarily occurs at the PSA dryer system, as a continuous slipstream of dried hydrogen is sent from the actively adsorbing bed to the saturated bed to purge it of entrained moisture before the bed switches back. This flow is orifice driven and as such is a function of hydrogen pressure, nominally rated at 0.0744 kg H2/hr at 30 barg. There is secondary hydrogen loss due to gas cross-over in the stack, but the dryer-driven losses account for 90% of the physical H2 losses using the nominal flow rate and orifice flow relations. This hydrogen loss is primarily driven by the hydrogen pressure, largely independent of the total hydrogen throughput and not strongly dependent on temperature for the temperatures considered. This load condition independence of hydrogen cross-over leads to the increasingly dramatic losses at low load conditions. Recent years have seen preliminary work on mitigating the losses due to fixed PSA drying systems on electrolyzers through the implantation of variable PSA dryers [46]. The use of PSA dryer systems is standard in electrolyzer systems, both PEM [47,48] and Alkaline [49,50]. For many applications, dry hydrogen is desired (industrial end use, fueling etc.). In the case of pipeline injection, there is potential for some flexibility in the moisture content of the hydrogen. Guidelines for injection of customer owned gas are outlined in Southern California Gas Company's Rule 30, which calls for moisture content not exceeding 7 lbs of water per million standard cubic feet (MMscf) of gas [51]. This level of moisture is a common standard along many of the North American interstate gas transfer agreements [52]. For the case of the
7
saturated hydrogen at 20 C and 30 Barg entering the PSA dryer, the moisture content is approximately 39.5 lbs of water per MMscf gas. Further conditioning could be accomplished through cooling of the gas pre-injection and blending with dry natural gas for injection would further dry the overall mixture. For the 20 C and 30 Barg saturated condition, blends of up to 17% by volume H2 in dry natural gas would be within the 7 lbs water per MMscf gas limit.
Dynamic operation Solar load following A 75 kW rooftop PV system monitored remotely by the UCI campus's Melrok power monitoring network was chosen as the solar PV source to test electrolyzer system load following. The selected solar profiles demonstrated many of the expected changes in output of a fixed solar photovoltaic system due to seasonal variation in the southern California region. The greatest amount of solar irradiance occurred in the summer and spring, the lowest in the winter. Greater intermittency is experienced in the spring and winter when weather events such as rain and cloud cover are more common. The highest peak outputs are observed in the spring, due to the confluence of high solar irradiation giving greater throughput with lower ambient temperatures resulting in a higher PV module efficiency. Each run was carried out for a week's worth of solar PV output. To speed up the experiments, the solar PV system ‘downtime’ (I.e., nighttime) was eliminated from the control signal sent to the electrolyzer system for these tests. The control signal in terms of power is the rated PV output normalized to the 62 kW capacity of the electrolyzer system. System set points are 55 C stack temperature, 30 Barg cathodic pressure and 1.6 Barg anodic pressure. Fig. 6 shows the control signal (orange dots) in terms of power consumption versus measured power consumption (blue line) for the four PV load following runs. The winter and spring PV cases are the most dynamic cases for comparison of capacity factor and transient weather effects. The fall solar PV load following case includes some transients associated with intermittent cloud cover on days two and three. Testing was interrupted by drift in the valve
Fig. 5 e Physical H2 losses as a percentage of total parasitic system losses; net H2 output measured over Faradaic H2 production versus stack current density and H2 pressure. Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
8
international journal of hydrogen energy xxx (xxxx) xxx
Fig. 6 e Solar photovoltaic load following tests, system power consumption versus control signal.
Table 3 e Seasonal comparison for results of solar photovoltaic load following tests.
Capacity Factor -Test Only (%System Power Consumption) Capacity Factor - Overall (%System Power Consumption) Hydrogen production (Average kg/day) System Efficiency (%HHV H2) Stack Efficiency (%HHV H2) Maximum Slew Rate Up/Down (kW/sec)
spring tension on the mass flow controller, requiring disassembly and multiple readjustments of the spring tension. This readjustment resulted in a zero-flow event during the fall run (hours 36 to 38), requiring restart of the mass flow controller. This outage of the flow controller left the electrolyzer system in an idling state, and the test resumed seamlessly. Except for this excursion, the system power consumption very closely followed the control signal's trend and handled even the steepest transient power dynamics of solar PV. An additional exception to this is the minimum power consumption level of 14 kW, below which the electrolyzer system could not operate. An extended period of PV output transients (day three of spring) due to extensive marine layer that day was one such scenario where the electrolyzer could not as effectively follow such a low load. Included in Table 3 are both the capacity factor of the system as the tests were run (zero downtime due to lack of solar radiation at night) and including the down time. The latter result serves to highlight an issue encountered by many energy storage strategies when paired with solar PV systems; low capacity factors. To maximize the electricity arbitrage capabilities of the energy storage system and prevent curtailment from the PV system, the power capacity of the energy storage system would typically be sized close to the peak over-generation of the PV system. With a peak power
Winter
Spring
Fall
Summer
47.25% 15.89% 3.10 51.60% 77.70% 40.8/54.5
62.49% 28.97% 5.75 52.55% 73.92% 45.8/55.1
55.88% 26.05% 5.03 51.08% 75.53% 41.8/54.7
63.48% 38.07% 7.39 51.37% 73.92% 45.1/54.7
capacity of 75 kW on the PV system and 60 kW on the electrolyzer system, the two systems are relatively well matched. The result is a capacity factor of at most 38.07% during peak solar activity in the summer season, and as low as 15.89% in the winter. An encouraging result is the consistent overall system efficiency for all cases in the range of 51e53% on a higher heating value basis. Also of interest is the extremity of power transients that the electrolyzer is subjected to when load following solar PV dynamics. Due to limitations in sampling rate for the system power consumption metering and combined with the fact that the stack accounts for the vast majority of the variable power consumption (barring very slight variation in losses to the AC/ DC power electronics), the maximum slew rates are defined in terms of stack power change on a second to second basis. The maximum down ramp rate observed was a 100% turndown in the span of 1 s based off the previously established 55 kW maximum stack power observed in the benchmarking tests. Maximum up-ramps of approximately 80% of dispatchable load/second were also observed.
Wind load following The wind load following experiments utilized 3 weeks of measured net electrical power output from the Tehachapi wind farm with 5-min resolution. Normalization was applied
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
9
international journal of hydrogen energy xxx (xxxx) xxx
Fig. 7 e Wind load following test, weeks 1 through 3, system power consumption versus control signal. to match the wind farm output power to scale 1:1 with the electrolyzer system power capacity. As in the solar PV load following case system set points are 55 C stack temperature, 30 Barg cathodic pressure and 1.6 Barg anodic pressure. In contrast to the solar load following runs (in which nighttime periods were eliminated), the wind load following experiments involved prolonged minimum H2 output operation (~0.03 kg/h H2), representative of an idling state. Particularly throughout week one and the first half of week three. Fig. 7 displays the electrolyzer system power consumption (blue line) compared to the control signal (orange dots). The electrolyzer system was found to be fully capable of following the rapid power transients called for by the wind farm dynamics. The results of the three separate weeks and the overall performance for wind power load following are tabulated in Table 4. Splitting the runs up serves to highlight the effects that the dynamic nature of wind power, even in an aggregated wind farm averaged over a week-long period, has on the electrolyzer system, with capacity factors as low as 30% in week one up to 62% the next week. System efficiency suffers at lower capacity factors, even as stack efficiency climbs. More dramatic is the observed slew rates, with the stack ramping up as much as 54.8 kW in a second. Stack maximum power varies with operating conditions, but typically is in the range of
53e55 kW. For the current test conditions, this was effectively a 100% up-ramp in power from zero. Similar down-ramps were observed more regularly throughout the wind power dynamic testing. To mitigate losses at low load capacities, power cycling of the electrolyzer system below an effective power set point can be considered. The minimum effective power consumption set point of the electrolyzer system can be set at around 21 kWel correlated to when the hydrogen output is at 0.30 kg/h set point. These set points correlate to the 0.7 A/cm2 stack current density regime, below which system efficiency dropped off dramatically (Fig. 2). Going as low as 0.03 kg/h H2, the specific energy cost of hydrogen production was found to be 433 kWhel/kg H2, while at 0.30 kg/h H2 and above, efficiency flattens out at around 70 kWhel/kg H2; a six-fold improvement in efficiency. By extension, the 21-kW system power consumption set point can be treated as a minimum at which the electrolyzer system produces hydrogen at a reasonable efficiency. The amount of time the system takes to start from a completely de-energized state, or ‘cold’ start, is an important metric for high transient load following applications. From a cold start, electrolyzer systems generally go through three stages of start-up; the booting of the onboard pc and controls, the venting of the hydrogen process piping to clear any air
Table 4 e Wind load following tests with and without minimum power condition cycling.
Capacity Factor (%System Power Consumption) Hydrogen production (Average kg/day) System Efficiency (%HHV H2) Stack Efficiency (%HHV H2) Maximum Slew Rate Up/Down (kW/sec)
Week 1
Week 2
Week 3
Overall
30.24% 3.55 31.07% 80.96% 46.4/-55.2
62.09% 12.05 51.35% 73.48% 44.7/-55.2
44.15% 7.04 42.06% 75.73% 54.7/-55.1
45.68% 7.60 43.96% 75.73% e
10 73.43% 14.44% 3.03 55.55%
11 30.07% 55.72% 11.78 55.95%
10 60.38% 31.16% 6.62 56.19%
31 54.62% 33.77% 7.14 55.90%
With Power Cycling Power Cycles (# of) Downtime (% Hours off/Hours Total) Capacity Factor (%System Power Consumption) Hydrogen production (Average kg/day) System Efficiency (%HHV H2)
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
10
international journal of hydrogen energy xxx (xxxx) xxx
gases present, and the ramping of the stack current up to full capacity. In the case of the Model C10 electrolyzer system, these steps are specified to take 30 s for initial start-up, 130e600 s for venting of the hydrogen process piping, and 180 s to ramp the electrolyzer stack, for a total specified start-up time of anywhere between 5 min and 40 s to upwards of 13 and a half minutes. Actual observed start-up times were far closer to the lower end of the system specs. Furthermore, the system starts producing H2 to the process connection rather than venting once the set point pressure is reached, which happens before full stack current is reached. The fastest observed start-up reached full hydrogen pressure and started production in 4 and a half minutes, full stack current at 5 and a half minutes. To simulate the concept of regular on/off dynamic operation, the three-week period studied in the wind load following experiments are pruned of any system activity below a 14 kW system power consumption signal. A start-up period of 5 min is added to each on cycle based upon the analysis of the system cold start behavior. Hydrogen lost when the system cycles off and vents on-board gas is accounted for. Power consumption on shutdown was not considered as the system shutdown takes less than 1 min to entirely shut down, with stack power being cut instantaneously, leaving only ancillary systems using power during the shutdown. Table 4 summarizes the results of the wind power experiments using the power cycling approach. The electrolyzer system went through a power cycle on average one to two times per day, and spent over half of the total operation time turned off. This highlights, once again, the expected issue of sizing these energy storage systems for meeting the needs of balancing variable renewable energy resources. On the other hand, system efficiency did improve with this on/off control approach to a much more reasonable 55% HHV H2.
Summary and conclusions Over 4000 h of operation of a 60 kW PEM electrolyzer system integrated with natural gas pipeline injection followed by combustion in a gas turbine were achieved. Over the course of the 4000 h of operation several hundred hours of sustained part-load operation, and over 2000 h of VRES load following were accomplished. The control of the PEM electrolyzer system for dynamic dispatch response to VRES load following was accomplished using an external mass flow controller. VRES load following was demonstrated for both a solar PV system across a wide range of conditions, and for aggregated wind turbine farm resources. The data acquired from the dynamic operation of the electrolyzer system indicates that PEM electrolyzers can operate under extreme power transients on a second-to-second time scale, not only at a stack level but from an overall system level, supporting the idea that PEM electrolyzer systems can provide a number of ancillary grid services as well as load balancing support [53]. Analysis of the electrolyzer system included benchmarking of the overall electrolyzer system including water consumption, power electronics, ancillary system power
consumption, hydrogen drying components, and the electrolysis process itself. Dynamic operation of the electrolyzer system across the available range of operating parameters allowed for extended characterization of part-load performance, which is essential to the success of such a system in power-to-gas applications where lower equipment capacity factors are expected due to the intermittency of solar and wind resources. Quick start-up times from a ‘cold state’ on the order of 5 min can be utilized to further improve system performance in low utilization factor cases. Such scenarios also lend themselves to the notion of a hybrid P2G energy storage system incorporating batteries [28,54]. Statistical analysis on operational data provided insight regarding the primary performance influencing operating conditions of the electrolyzer system and its components. The experimental analysis indicated relatively stable system efficiency down to 35% load condition (0.7 A/cm2 at the stack). Exceedingly poor performance below 35% load condition (0.7 A/cm2) was observed primarily due to high percentage losses of the hydrogen product due to the timed switching control of the PSA drying beds. This finding suggests a recommended minimum operating condition of 35%, rather than the rated 10% part-load condition. The increasing discrepancy between the measured hydrogen output and the amount of hydrogen produced according to the Faradaic relation at lower current densities explained the large drop in system efficiency below 35% part-load. In this case the PSA dryer system accounted for the majority of H2 loss. For pipeline injection applications, it is apparent that the PSA drying system may not be necessary, due to less stringent moisture content requirements as compared to industrial or commercial operations.
Acknowledgements This work was supported by the National Fuel Cell Research Center at the University of California, Irvine with partial funding support from Southern California Gas Company.
Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.ijhydene.2020.01.228.
references
[1] Koebrich S, Chen E, Bowen T, Forrester S, Tian T. Renewable energy data book. U.S. Department of Energy; 2017. [2] Anuta H, Ralon P, Taylor M. Renewable power generation costs in 2018. Abu Dhabi: International Renewable Energy Agency (IRENA); 2019. [3] Bird JCXWL. Wind and solar energy curtailment: experience and practices in the United States. Golden, CO: National Renewable Energy Laboratory (NREL); 2014. [4] N M, V C, P C, D C, M F, F A, et al. Intermittent and stochastic character of renewable energy sources: consequences, cost of intermittence and benefit of forecasting. Renew Sustain Energy Rev 2018;87:96e105.
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
international journal of hydrogen energy xxx (xxxx) xxx
[5] Shaner MR, Davis SJ, Lewis NS, Caldeira K. Geophysical constraints on the reliability of solar and wind power in the United States. Energy Environ Sci 2018;11:914e25. [6] J JH, N EW, Felix Cebulla PM. How much electrical energy storage do we need? A synthesis for the U.S., Europe, and Germany. J Clean Prod 2018;181:449e59. [7] Aneke M, Wang M. Energy storage technologies and real life applications - a state of the art review. Appl Energy 2016;179:350e77. [8] Saeedmanesh A, Mac Kinnon MA, Brouwer J. Hydrogen is essential for sustainability. Curr Opin Electrochem 2018;12:166e81. [9] Amrouche SO, Rekioua D, Rekioua T, Bacha S. Overview of energy storage in renewable energy systems. Int J Hydrogen Energy 2016;41(45):20914e27. [10] Dincer I, Acar C. Review and evaluation of hydrogen production methods for better sustainability. Int J Hydrogen Energy 2015;40:11094e111. [11] Celik D, Yıldız M. Investigation of hydrogen production methods in accordance with green chemistry principles. Int J Hydrogen Energy 2017;42:23395e401. [12] Zhang F, Zhao P, Niu M, Maddy J. The survey of key technologies in hydrogen energy storage. Int J Hydrogen Energy 2016;41(33):14535e52. [13] Dincer I, Suleman F, Agelin-Chaab M. Comparative impact assessment study of various hydrogen production methods in terms of emissions. Int J Hydrogen Energy 2016;41(19):8364e75. [14] Glenk G, Reichelstein S. Economics of converting renewable power to hydrogen. Nat Energy 2019;4:216e22. [15] Eichman J, Hodge B-M, Kurtz J. Cost-competitive electrolysisbased hydrogen under current U.S. electric utility rates. In: 2018 AIChEAnnual meeting, Pittsburgh, Pennsylvania; 2018. [16] Messaoudani ZL, Rigas F, Hamid MDB, Hassan CRC. Hazards, safety and knowledge gaps on hydrogen transmission via natural gas grid: a critical review. Int J Hydrogen Energy 2016;41(39):17511e25. [17] Zhao Y, McDonell V, Samuelsen S. Influence of hydrogen addition to pipeline natural gas on the combustion performance of a cooktop burner. Int J Hydrogen Energy 2019;44(23):12239e53. [18] Gimeno-Escobedo E, Cubero A, Ochoa JS, Fueyo N. A reduced mechanism for the prediction of methane-hydrogen flames in cooktop burners. Int J Hydrogen Energy 2019;44(49):27123e40. [19] Zhao Y, Soto Leytan KN, McDonell V, Samuelsen S. Investigation of visible light emissions from hydrogen-air research flames. Int J Hydrogen Energy 2019;44(39):22347e54. [20] Zhao Y, McDonell V, Samuelsen S. Experimental assessment of the combustion performance of an oven burner operated on pipeline natural gas mixed with hydrogen. Int J Hydrogen Energy 2019;44(47):26049e62. [21] Choudhury S, McDonell V, Samuelsen S. Combustion performance of low-NOx and conventional storage water heaters operated on hydrogen enriched natural gas. Int J Hydrogen Energy 2020;45(3):2405e17. [22] Valera-Medina A, Morris S, Runyon J, Pugh D, Marsh R, Beasley P, et al. Ammonia, methane, and hydrogen for gas turbines. Energy Procedia 2015;75:118e23. [23] Jiang Y, del Alamo G, Gruber A, Bothien MR, Seshadri K, Williams FA. A skeletal mechanism for prediction of ignition delay times and laminar premixed flame velocities of hydrogen-methane mixtures under gas turbine conditions. Int J Hydrogen Energy 2019;44(33):18573e85. [24] Liemberger W, Halmschlager D, Miltner M, Harasek M. Efficient extraction of hydrogen transported as co-stream in the natural gas grid - the importance of process design. Appl Energy 2019;233e234:747e63.
11
[25] Vlap H. Technical assumptions, technology demonstration and results P2G project. Groningen, Netherlands: DNV GL Oil & Gas; 2015. [26] Schulze P, Holstein J, van den Noort A, Knijp J. Power-to-gas in a decarbonized european energy system based on renewable energy sources. European Power To Gas Platform; 2018. [27] European Commission. Energy roadmap 2050. Luxembourg: European Union; 2011. [28] Papadopoulos V, Desmet J, Knockaert J, Develder C. Improving the utilization factor of a PEM electrolyzer powered by a 15 MW PV park by combining wind power and battery storage- Feasibility study. Int J Hydrogen Energy 2018;43:16468e78. [29] Laoun B, Khellaf A, Naceur MW, Kannan AM. Modeling of solar photovoltaic polymer electrolyte membrane electrolyzer direct coupling for hydrogen generation. Int J Hydrogen Energy 2016;41(24):10120e35. ndez-Ramı´rez LM, Garcı´a-Va zquez CA, [30] Sarrias-Mena R, Ferna Jurado F. Electrolyzer models for hydrogen production from wind energy systems. Int J Hydrogen Energy 2015;40(7):2927e38. [31] Aouali FZ, Becherif M, Ramadan HS, Emziane M. Analytical modelling and experimental validation of proton exchange membrane electrolyser for hydrogen production. Int J Hydrogen Energy 2017;42(2):1366e74. [32] Grigoriev SA, Kalinnikov AA. Mathematical modeling and experimental study of the performance of PEM water electrolysis cell with different loadings of platinum metals in electrocatalytic layers. Int J Hydrogen Energy 2017;42(3):1590e7. [33] Lee B, Park K, Kim H-M. Dynamic simulation of PEM water electrolysis and comparison with experiments. Int J Electrochem Sci 2013;8:235e48. [34] Schalenbach M, Carmo M, Fritz DL, Mergel J, Stolten D. Pressurized PEM water electrolysis: efficiency and gas crossover. Int J Hydrogen Energy 2013;38:14921e33. [35] K J, R A, H V, N K, A M, Koponen J. Control and energy efficiency of PEM water electrolyzers in renewable energy systems. Int J Hydrogen Energy 2017;42(50):29648e60. [36] Mraoui A, Benyoucef B, Hassaine L. Experiment and simulation of electrolytic hydrogen production: case study of photovoltaic electrolyzer direct connection. Int J Hydrogen Energy 2018;43(6):3441e50. [37] Stansberry J, Hormaza Mejia A, Zhao L, Brouwer J. Experimental analysis of photovoltaic integration with a proton exchange membrane electrolysis system for powerto-gas. Int J Hydrogen Energy 2017;42(52):30569e83. [38] Saadi A, Becherif M, Ramadan H. Hydrogen production horizon using solar energy in Biksra, Algeria. Int J Hydrogen Energy 2016;41:21899e912. [39] Espinosa-Lopez M, Darras C, Poggi P, Glises R, Baucour P, Rakotondrainibe A, et al. Modelling and experimental validation of a 46 kW PEM high pressure water electrolyzer. Renew Energy 2018;119:160e73. [40] Alaefour I, Shahgaldi S, Ozden A, Li X, Hamdullahpur F. The role of flow-field layout on the conditioning of a proton exchange membrane fuel cell. Fuel 2018;230:98e103. [41] Vang JR, Andreasen SJ, Araya SS, Kaer SK. Comparative study of the break in process of post doped and sol-gel high temperature proton exchange membrane fuel cells. Int J Hydrogen Energy 2014;39(277):14959e68. [42] Thomas S, Araya SS, Vang JR, Kaer SK. Investigating different break-in procedures for reformed methanol high temperature proton exchange membrane fuel cells. Int J Hydrogen Energy 2018;43(31):14691e700. [43] Silva VB, Rouboa A. Hydrogen-fed PEMFC: overvoltage analysis during an activation procedure. J Electroanal Chem 2012;671:58e66.
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228
12
international journal of hydrogen energy xxx (xxxx) xxx
[45] Qi Z, Kaufman A. Quick and effective activation of protonexchange membrane fuel cells. J Power Sources 2002;114. 21-13. [46] Peters M, Harrison K, Dinh H. Renewable eletrolysis integrated systems development and testing. Golden, CO: U.S. Department of Energy Hydrogen and Fuel Cells Program; 2016. [47] Harrison K, Martin G. Renewable hydrogen: integration, validation and demonstration. In: NHA annual hydrogen conference, Sacramento, California; 2008. [48] Hydrogenics. OnSite hydrogen generation: HyLYZER PEM electrolysis technology. In: Hydrogenics Europe NV, on-site generation, Nijverheidsstraat 48-C, Oevel, B-2260, Belgium; 2018. nchez M, Amores E, Rodrı´guez L, Clemente-Jul C. Semi[49] Sa empirical model and experimental validation for the performance evaluation of a 15 kW alkaline water electrolyzer. Int J Hydrogen Energy 2018;vol. 43:20332e45.
[50] Hydrogenics. HYSTAT hydrogen generators. In: Hydrogenics on-site generation, Nijverheidsstraat 48c, 2260 Oevel, Belgium; 2018. [51] Southern California Gas Company. Rule No. 30 transportation of customer-owned gas. Los Angeles, California: California Public Utilities Commission (CPUC); 2016. [52] Foss MM. Interstate natural gas- quality specifications & interchangeability. In: Energy economics research at the Bureau of Economic Geology, Sugar Land, Texas; 2004. [53] Hovsapian R. Role of electrolyzers in grid services. Washington D.C.: National Renewable Energy Laboratory (NREL) & Idaho National Laboratory (INL); 2017. [54] Maclay JD, Brouwer J, Samuelsen SG. Experimental results for hybrid energy storage systems coupled to photovoltaic generation in residential applications. Int J Hydrogen Energy 2011;vol. 36:12130e40. 19.
Please cite this article as: Stansberry JM, Brouwer J, Experimental dynamic dispatch of a 60 kW proton exchange membrane electrolyzer in power-to-gas application, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2020.01.228