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Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study
i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y x x x ( 2 0 1 2 ) 1 e8
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Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study Beatriz Escobar a, Jose´ Herna´ndez b, Romeli Barbosa b, Ysmael Verde-Go´mez a,* a b
Instituto Tecnolo´gico de Cancu´n, Av. Kabah Km. 3, Cancu´n 77500, Q. Roo, Mexico Universidad de Quintana Roo, Boulevard Bahı´a s/n, Chetumal 77019, Q. Roo, Mexico
article info
abstract
Article history:
The main advantage of the hybrid system compared with separate array solar photovoltaic
Received 3 September 2012
and stand-alone wind turbine is the possibility of the surplus energy storage by trans-
Received in revised form
forming it to hydrogen that can be use in fuel cells. However the design and sizing of this
1 November 2012
kind of technologies need to meet the local microclimate in order to reach higher efficacies.
Accepted 2 November 2012
A tool based on an analytical model to sizing, analyze and assess the feasibility of the
Available online xxx
hybrid wind/photovoltaic/H2 energy conversion systems using real weather data is presented in this work. The model considers an energy balance analysis and electrical
Keywords:
variables of the system components; the tool calculates the subsystems efficacy and
Hydrogen
proposes the improvements to increase the efficiency of the use in surplus energy
Modeling hybrid systems
produced by the hybrid system. To validate the analytical model, simulation based on wind
Renewable energy
speed and solar radiation measurements from meteorological monitoring station in
Fuel cells
a Mexican Caribbean City is discussed.
Energy balance
Copyright ª 2012, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights
Sizing system
1.
Introduction
Renewable energy sources are seen as an alternative energy generation instead of fossil fuels, it is not only to reduce the environmental pollution and global warming [1] but also to help in the sustainable development in emerging countries. The most known renewable energy, which it has become a mature technology for power generation are the photovoltaic arrays (PV). During the last decade PV’s applications have increased and extended to industrial and domestic use. This technology is characterized not only by its modularity and zero emissions of pollutants, but also by its low efficiency, and its production dependence on the sunlight. There are two main disadvantages: 1) the availability of solar resources, which depends on geographic location and weather
reserved.
conditions, and 2) the storage, since the solar energy needs to be transformed into another type of power source. On its hand, wind energy (WE) has been also established as an option in power generation, having a large technological growth in the recent years. However, it is also an intermittent energy, dependant of the weather. PV and WE have become two of the most promising technologies due to the fact that their energy sources are free and environmental friendly. The integration of renewable energy sources to form a hybrid system is an excellent option for power generation with a more stable working time [2]. However, we should consider the weather conditions, including solar irradiance and wind speed which are changing daily and seasonally. One of the major issues confronted by the users as well as the designers of PVeWE energy systems is the
* Corresponding author. Tel.: þ52 998 8807432; fax: þ52 998 8807433. E-mail addresses: [email protected], [email protected] (Y. Verde-Go´mez). 0360-3199/$ e see front matter Copyright ª 2012, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ijhydene.2012.11.018
Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018
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random and fluctuating nature of the energy sources. This makes the systems unpredictable or even unreliable [3], besides the limitation on energy storage for long periods of time. Then, the optimum conditions for the proper functioning of PVeWE systems are areas with high solar radiation levels evenly distributed, and places with large densities of wind energy. The recent interest in the use of wind and solar energies has promoted the measure and register of the locals weather in potential sites to use sustainable power sources, but it has been limited to short period of time [4e6]. This is the case of the anemometric stations located in Cancun, Quintana Roo, where the available information is only referred to the last decades. Mexico has identified several areas with high potential for renewable energy production. The coastal state of Quintana Roo (Q. Roo) is considered an area with high wind potential, especially during spring and summer, which is enhanced by the breeze sea [7]. The National Renewable Energy Laboratory in USA (NREL) has realized wind maps of the Yucatan Peninsula and according to its results, the Quintana Roo coastal has been classified from good to very good, due to the wind characteristics, with average speeds between 5.6 and 6.7 m/s at height of 30 m [8]. Herna´ndez-Escobedo et al. reported the calculations from the years of 2000 to 2008, and the average wind speed for the north of Yucatan Peninsula was estimated between 3 and 5 m/s [9]. On the other hand, Mexico receives an average solar irradiation of about 5 kWh/m2 [10], which provides to the Yucatan Peninsula considerable potential to generate solar electricity. In order to meet the continuous power delivery in PVeWE system, it is often realized by the use of high capacity and expensive energy storage [3]. Solar and wind energy are stored during sunny and windy days and released later during cloudy days, at night, in grid outages (emergencies, i.e., after hurricanes or natural disasters) or to smooth power demands. In addition, the electric energy is stored during low demand and later used in peak periods [11]. Usually, rechargeable and disposable batteries are used as energy storage systems. However, after many charges and discharges, the battery loses capacity and it has to be discarded by the user, which implicates an increment on the cost of the hybrid systems as well as considerable environment impact. One option to solve this problem is to use hydrogen as storage system of renewable energy, in order to increase the reliability of the stand-alone systems [12]. Hydrogen is one of the most promising alternative fuels for the future and it is emerging as a sustainable process to solve the energy storage [13]. The main characteristic of the above mentioned process is that it provides the opportunity to produce and store energy in-situ, eliminating in consequence the necessity of transportation of the fuel for backup purposes. On the other hand, fuel cells (FC’s) are by excellence the technology for an efficient consumption of hydrogen. It has achieved a global focus attention due to its versatility and special features as modularity, quiet operation, friendly environment, and efficiency which is about 60% [14] and it can reach up to 75% in cogeneration systems [15]. As a consequence, fuel cells are considered a viable, efficient and promising technology to use as backup power system, feed by the hydrogen produced using an electrolyzer activated by the excess energy generated in the renewable energy system (PVeWE). This electrochemical
subsystem (electrolyzerefuel cell) is integrated into hybrid systems to ensure energy supply. There are several experimental and theoretical studies of “PhotovoltaiceWindeHydrogen” (PVeWEeH2) hybrid systems in the world [12,16e19]. Even though in Mexico some theoretical and experimental studies of PVeH2 hybrid systems [20] had been reported, there is not any recent evaluation of WEePVeH2 hybrid systems available. In this work, an analytic model, design and simulation of a PVeWEeH2 hybrid system is developed. The paper presents a strategy based on efficacies to improve, in an easy way, the selection of power subsystems. As an example of this strategy, the optimal combination of PV, WE, proton exchange water electrolyzer (PEWE), and proton exchange membrane fuel cell (PEMFC) was studied for the solar and wind experimental data of Mexican Caribbean. The PVeWEeH2 system delivered electric power from primary sources (PVeWE) to satisfy the electric load. Surplus energy is supplied to an electrolyzer in order to generate hydrogen. In energy deficit hours a PEMFC generates part or the total of the electric demand. Therefore a hybrid system efficacy is calculated based on the level of energy stored, and the fulfillment of the electric load.
2.
Theory and calculation
The sizing of a hybrid system has to consider the steady state characteristics, unsteady profiles of the site energy source and the electricity loading demand [21]. Although these profiles restrict the power of the subsystems to a limited range of possibilities, the numbers of possible combinations are numerous. The overall configuration of a WEePVeH2 hybrid system proposed for a grid of an independent house is shown in Fig. 1. This system consists of a wind turbine, PV, PEWE, PEMFC, power control system, and hydrogen storage system [22e24]. If the total power generated by the primary system (PV and WE) is higher than the electrical demand, the surplus energy is used in PEWE to produce hydrogen as long as the power excess exists and the maximum of the PEWE nominal power and storage level allow. If the primary system is not sufficient to meet the loading, the energy required will be provided from a hydrogen tank, and used in the PEMFC, as long as the power deficit exists and the maximum of the PEMFC nominal power and storage level allow. In other words, nominal power of the subsystems should be carefully selected to satisfy the electric demand but without oversizing the system. This system operation features allow us to define the “efficacy” term (functionality) of the system in both conditions (undersizing or oversizing). Undersizing condition exists when the electrical demand is not entirely fulfilled, and oversizing will be when the input energy is not completely useful. Eq. (1) determines the “Load efficacy” (hL), hL ¼ εL;actual =εL;nom
(1)
where εL,actual is the actual energy consumed and εL,nom the nominal energy demanded. The “Useful efficacy” (hU) is determined by Eq. (2), (2) hU ¼ ðεL;actual þ εS Þ εin
Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018
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Fig. 1 e General diagram of the hybrid system.
where εS is the energy stored and εin the input energy. System’s global efficacy can be determined by a “Mixed efficacy” (hM), hM ¼ hL hU
(3)
The design strategy consists in makes a parametric combination of the subsystems power and simulates the instantaneous system behavior using experimental profiles along the time. Average of the instantaneous efficacies helps to select the best combination. Instantaneous system behavior will be determining by an energy balance analysis. In following sections are summarized the analytical models to simulate: input, stored and output electrical energy.
2.1.
Energy input
The input energy (εin) of the hybrid system is the sum of the electrical energy output of the PV and WE subsystems. εin ¼ εPV þ εWE
of a 1000 W commercial turbine (Whisper H-80) is showed in Fig. 2. In this particular case, there are two equations to calculate εWE, when wS is in the range of 3.3e11.3 m/s (upper equation) and 11.3e25.0 m/s, (bottom equation).
2.2.
Energy storage
Electrical energy stored can be determined by the balance of mass in the storage subsystem, NHs ¼ NHg NHc
(6)
where NHs is the hydrogen stored, NHg is the hydrogen generated and NHc the hydrogen consumed. In a PEMFC, NHc is directly proportional to the electrical energy produced. This can be determined by Faraday’s law [19]. NHc ¼ ðNCFC IFC tÞ=ð2FhFC Þ
(7)
(4)
where εPV is the energy output of the PV and εWE is the energy output of the WE. These energies are in function of solar and wind resource of the site and the physical characteristics of the devices. Instantaneous electric energy output from a PV (εPV) is given for the following Equation: εPV ¼ hPV APV IT
(5)
where hPV is the instantaneous PV efficiency, APV the total area of the PV and IT equals to instantaneous solar radiation per area incident on PV surface. Strictly, hPV is dependent of three parameters: the temperature, the packing factor and the module reference efficiency. However, the efficiency used in this work is a global parameter of a hypothetical PV (hPV ¼ 0.11%). In this work, the size of wind turbine was not varied. However, instantaneous electric energy output from WE (εWE), is in function of the wind speed (wS). The characteristic curve
Fig. 2 e Power curve and lineal regression equation of a commercial wind turbine (Whisper H-80). Wind turbine power (WTP) as a function of the wind speed (wS); two equations are necessary for two different ranges of wS.
Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018
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hFC ¼ EFC =ðErev NCFC Þ
(8)
where Erev is the reversible potential of one cell of the PEMFC stack and EFC is the total potential of the stack. On the other hand, in electrical terms, the energy produced by the PEMFC stack (εFC) is in function of the operating time (t), the total current (IFC) and the total potential of the stack (EFC), εFC ¼ IFC EFC t
1000 800 600 400 200 0 0
2
4
6
8
NHc ¼ ðεFC Þ= 2FErev h2FC
10 12 14 16 18 20 22 24 Time / hour
(9)
Fig. 4 e Hourly electricity demand of a hypothetical house in Mexican Caribbean City.
In this way, the hydrogen consumed is:
(10)
Likewise, according to Faraday’s law, hydrogen production rate in an electrolyzer is directly proportional to the electrical current in the electrolyzer circuit [19]. NHg ¼ ðNCPEE IPEE thPEE Þ=ð2FÞ
(11)
where NHg are the H2 produced (in mol), NCPEE is the total number of cells in the electrolyzer, IPEE is the total electric current, t is the operating time and F the Faraday constant. The electrolyzer efficiency (hPEE) can be defined thermodynamically as follow: hPEE ¼ ðErev NCPEE Þ=EPEE
(12)
where Erev is the reversible potential of one cell in the electrolyzer and EPEE is the total potential of the electrolyzer. In electrical terms, the energy consumed by the electrolyzer (εPEE) is: εPEE ¼ IPEE EPEE t
(13)
In this way, the hydrogen generated is: NHg ¼ εPEE h2PEE
1200
Load power / Wh
where NHc are the mol of H2 consumed, NCFC is the total number of cells in the PEMFC stack, IFC is the total electric current, t is the operating time and F the Faraday’s constant. The PEMFC stack efficiency (hFC) can be defined thermodynamically by,
ð2FErev Þ
(14)
If the hydrogen stored will be used exclusively by the same PEMFC stack of the system, the electrical energy stored (εS) can be determined systematically using Eq. (10), εS ¼ NHS 2FErev h2FC
(15)
Substituting Eq. (6) in Eq. (15) and then substituting Eqs. (10) and (14), we can determine the εS of the hybrid system in terms of the efficiencies and energy of the PEMFC and PEWE, in the time interval studied: εS ¼ h2FC h2PEE εPEE εFC
(16)
The PEMFC and PEWE efficiency are as a function of their total potentials (Eqs. (8) and (12), respectively). Hence, Fig. 3 shows the performance of PEMFC and PEWE single-cell used in this work, which are experimental polarization curves carried out in our laboratory.
2.3.
Energy output
The electrical output of the hybrid system is equal to the power consumed by the electrical load. The nominal load profile proposed corresponding to the hypothetical consume of a house is showed in Fig. 4. The nominal energy output can be obtained by the curve integration in the time period required. It assumed that this load pattern would remain during all days of the year. However when the PEMFC power is not enough to complete the electrical deficit, the electrical output is only the maximum energy available. So, under this condition the actual energy consumed (εL,actual) is not always
Cell potential / V
1.6 1.4 1.2 PEMFC
1 0.8
PEWE
0.6 0.4 0.2
14
8 7
12
6
10
5
8
4
6
3 4
2
2
1 0
0
0 0
0
0.2
0.4 0.6 0.8 1 Current density / A cm-2
1.2
Fig. 3 e Single-cell polarization curve of fuel cell (PEMFC) and electrolyzer (PEWE).
Wind speed / m s-1
1.8
Insolation / kWh m-2 month-1
9
2
1
2
3
4
5
6
7
8
9 10 11 12
Time / month
Fig. 5 e Experimental data of weather in Cancun, Mexico, insolation monthly average and wind speed monthly average.
Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018
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Table 1 e Limits and interval of the parametric combination of the nominal powers of PV, PEMFC and PEWE subsystem.
Minimum Maximum Interval
PPV (W)
PFC (W)
PE (W)
110 5060 330
30 1463 75
163 6350 651
the nominal energy demanded (εL,nom), thus we can evaluate the load efficacy.
3.
Simulation conditions
The net hourly electrical power according to the solar irradiance and wind speed in Cancun, Mexico was determined by experimental data, including the average of two periods of time: 2001e2005 and 2007e2009. This annual average behavior is showed in Fig. 5. A commercial wind turbine was studied, energy output of the WE (εWE) was calculated from the equations showed in Fig. 2. Furthermore the number of bipolar plates of the PEMFC and PEWE were constant. However, the nominal power of PV (PPV) defined from exposure area, the nominal power of PEMFC (PFC) and the nominal power of PEWE (PE) defined from the electrode area, these variables were systematically studied as shown in Table 1. In this work, the storage tank capacity is considered to meet up 10 autonomous operation days at rated load. This storage maximum capacity was taken to satisfy a critical shortage of energy after a Hurricane, situation which is very likely in Mexican Caribbean; however, this condition can be fixed for different scenarios. The storage of energy in hydrogen form is a current technological challenge which is
under extensive research [25,26]. In this work, the technology of hydrogen storage systems (e.g. metal hydride, compressed/ liquid storage and sorbents) as well as the secondary devices (i.e., sensors, actuators, valves and controllers) are not included. Simulation in variations of the wind turbine size and tank capacity will be integrated in future work.
4.
Results
The energy input (subject to experimental data), the energy stored (evaluated by Eq. (16)) and the strategy to evaluate the actual energy consumed, allow to determinate the mixed efficacy (Eq. (3)) with several hypothetical nominal powers (Table 1). The hourly efficacy is averaged to evaluate annual behaviors and then compared in order to found the best solution. Fig. 6 shows the dependence of the mixed efficacy (hM) respects to PPV. In this Figure, the “points” are plotted for all possible combinations, and the marker lines indicate five different scenarios for electrochemical subsystem power (PFC and PE), where the minimum, intermediate and maximum rated powers correspond to Table 1: PEmin ¼ 163 W; PEint ¼ 3094 W; PEmax ¼ 6350 W; PFCmin ¼ 30 W; PFCint ¼ 709 W; and PFCmax ¼ 1463 W. Depending on the PE and PFC values, hM reaches a maximum in a specific PPV value. hM increases because load efficacy (hL) is higher with the input power increment (i.e. PPV and PFC increment), but when the surplus energy of the system exceeds the maximum energy level of the hydrogen storage system, useful efficacy (hU) decreases to have a surplus that is not used, this suggests that the system is “oversizing”. In addition, it can also observe that if the system includes a PEmin, then hM is the lowest due to the hydrogen production does not meet the gas demand. This behavior is similar when the PEmax and PFCmin, in this case hydrogen production is Selected
0.75
η M max = 0.73 %
0.7
Mixed efficacy / %
0.65 0.6 0.55 0.5 PEmin - PFCmin PEmin - PFCmax PEmax - PFCmin PEmax - PFCmax PEint - PFCint
0.45 0.4 0.35 0
1000
2000
3000
4000
5000
PPV / W Fig. 6 e Dependence of the mixed efficacy (hM) with respect to photovoltaic array power (PPV). Different powers of fuel cell (PEMFC) and electrolyzer (PEWE) conditions are indicated in the marker lines. Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018
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PPV=2420 W ηM =0.723 %
0.75
PPV=2750 W ηM=0.727 %
0.7
Mixed efficacy / %
0.65 0.6 0.55 0.5 0.45 PPVmin - PEmin PPVmin - PEmax PPVmax - PEmin PPVmax - PEmax PPV=2420 - PEmax PPV=2750 - PEmax PPV=3080 - PEmax
0.4 0.35 0.3 0
200
400
600
800
1000
1200
1400
PFC / W Fig. 7 e Dependence of the mixed efficacy (hM) with respect to fuel cell power (PEMFC). Different powers of photovoltaic array (PPV) and electrolyzer (PEWE) conditions are indicated in the marker lines. Dotted lines indicate the points selected in Fig. 6.
bigger than the fuel cell capacity; in both cases the systems power is wasted. The best scenario occurs when the hybrid system uses a PEmax and PFCmax. This is an expected behavior because of the high PPV is capable of meet the energy demand of the electrolyzer which is able to feed the fuel cell to produce electricity. Similar performance is observed when intermediate values are used. Three interesting PPV points at 2420, 2750 and 3080 W, were selected for further comparison.
Dependence of hM respect to PFC is shown in Fig. 7. The “points” are plotted for all studied combinations, i.e. the maximum and minimum limit conditions of PPV and PE. It can be observed that the lowest hM value corresponds to PPVmax in combination with PEmin, it means that the entire solar power is not used by the electrolyzer. Also it should be noticed that the maximum powers condition does not promote the maximum efficacy reached in some scenarios of the Fig. 6. The
Fig. 8 e Dependence of the mixed efficacy (hM) with respect to electrolyzer power (PEWE). Different powers of photovoltaic array (PPV) and fuel cell (PEWE) conditions are indicated in the marker lines. Dotted lines indicate the points selected in Fig. 7. Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018
i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y x x x ( 2 0 1 2 ) 1 e8
a
b
ηM 0.8
0.7 0.65 0.6 S1) PPV=2750; PE=6350; PFC=634
Load efficacy / %
Mixed efficacy / %
ηL 1
0.75
0.55
7
0.9 0.8 0.7 S1) PPV=2750; PE=6350; PFC=634
0.6
S2) PPV=2420; PE=6350; PFC=558
S2) PPV=2420; PE=6350; PFC=558
S3) PPV=2420; PE=2750; PFC=558
S3) PPV=2420; PE=2750; PFC=558
0.5
0.5 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Fig. 9 e Monthly performance of the mixed efficacy (a) and load efficacy (b), for S1, S2 and S3 identified in Fig. 8.
three dotted lines correspond, in combination with the PEmax condition, to PPV selected points from Fig. 6. These conditions show the best performance of hM, reaching around the 0.72% efficacy. Following with the analysis strategy, two interesting points also were selected: 1) PPV ¼ 2420 W @ PFC ¼ 558 W and 2) PPV ¼ 2750 W @ PFC ¼ 634 W. Mixed efficacy (hM) versus PE is showed in Fig. 8. The marker lines indicate the four limit conditions of PPV and PFC, where “min” and “max” corresponds to the rated power shown in Table 1. In this graph, hM increases while PE increases. The lowest value condition is PPVmax PFCmin due to the two apparent facts: 1) oversizing of PV, and 2) the low capacity of the fuel cell to produce electricity. The hM improves with the use of PFCmax regardless of the PPV value; however they are not reach the maximum values showed in previous scenarios. The two dotted lines correspond to the two interesting conditions selected from Fig. 7 which do not show significant difference, reaching the highest hM at 0.72% with PEmax condition. In order validate the analytical model and calculate the average efficacies hM and hL under real weather conditions, three points at the highest efficacy were selected from previous analyses and they were combined with the Cancun solar and wind weather data: S1) “PPV ¼ 2750 W, PE ¼ 6350 W, PFC ¼ 634 W”; S2) “PPV ¼ 2420 W, PE ¼ 6350 W, PFC ¼ 558 W”; and S3) “PPV ¼ 2420 W, PE ¼ 2750 W; PFC ¼ 558 W”. The system sizing perspective and monthly behavior are detailed in Fig. 9. It is clear that hM do not have a significant dependence of the wind and solar conditions; for example from March to May the insolation is high (Fig. 5) the mixed efficacy is low; it can be attributed to the limited optimization of the power systems, especially the photovoltaic array. Comparing the three conditions selected, it is relevant to note out that hL slightly decreased between 1.0 and 0.95% from January to October. The major difference, for both hM and hL, is in November and December. November presents the highest mixed efficacy for S1 and S2 systems; however is the worst month for S3 system. Also in November, S1 and S2 systems can reach a load efficacy near to w0.95%, while S3 system is the lowest w0.80%. Based on the results, using the analytical model proposed is possible make decisions to choose strategies which allow sizing hydrogen hybrid systems with the best efficacy.
For example, in the present case of study: 1) prioritize hL and select the system S1, and even analyze higher power systems, for example when PPV ¼ 3080 W; 2) adjust the energy management of November (critical month) in order to increase the efficiency without requiring more power; and 3) an “extra” should be provided to meet the energy demand in the critical months. Finally, the analytical model presented can be used as a tool to design and sizing PVeWEeH2 systems considering locals microclimate with the high efficacies.
5.
Conclusions
Theoretical efficacy of a hybrid windesolarehydrogen system at different scenarios was determined using an analytical model tool. Energy balance, electrical and electrochemical characteristics of the systems and microclimate data of solar and wind resource from Mexican Caribbean City were used to validate the model. Results shows that the highest PPV, PFV or PE not always meet the highest efficacy of the hybrid system, therefore the model allows determine the best subsystems configuration to avoid the oversizing or undersizing. The simulation data applied different scenarios show the hM, around the 0.73% at 3 kW of PPV, 0.68 at 1 kW of PFC and 0.68% at 2 kW of PE, respectively. The average efficacies hM and hL under real monthly weather conditions using three points at the highest efficacy were also validate, showing that hM do not have a significant dependence of the wind and solar conditions, but it can be related with the optimal sizing systems; meanwhile solar and wind conditions has a slightly effect over the hL which is maintained between 1.0 and 0.95%. Finally, based on the results, using the analytical model proposed is possible make decisions to choose strategies which allow sizing hydrogen hybrid systems with the high efficacy.
Acknowledgment This work was supported by FORDECYTeCONACYT under project No. 116157.
Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018
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references
[1] Ban˜os R, Manzano FA, Montoya FG, Gil C, Alcayde A, Go´mez J. Optimization methods applied to renewable and sustainable energy: a review. Renew Sust Energy Rev 2011; 15:1753e66. [2] Dufo-Lo´pez R, Bernal-Agustin JL, Mendoza F. Design and economical analysis of hybrid PVewind systems connected to the grid for the intermittent production of hydrogen. Energy Policy 2009;37:3082e95. [3] Ahmed NA, Miyatake M, Al-Othman AK. Power fluctuations suppression of stand-alone hybrid generation combining solar photovoltaic/wind turbine and fuel cell systems. Energy Convers Manage 2008;49:2711e9. [4] Cancino Solo´rzano Y, Xiberta-Bernat J. Statistical analysis of wind power in the region of Veracruz (Mexico). J Renew Energy 2009;34:1628e34. [5] Jung S, Vanli OA, Kwon SD. Wind energy potential assessment considering the uncertainties due to limited data. Appl Energy 2012;102:1492e503. [6] Carta JA, Vela´zquez S, Matı´as JM. Use of Bayesian networks classifiers for long-term mean wind turbine energy output estimation at a potential wind energy conversion site. Energy Convers Manage 2011;52:1137e49. [7] Jaramillo OA, Saldan˜a R, Miranda U. Wind power potential of Baja California Sur, Me´xico. Renew Energy 2004;29:2087e100. [8] National Renewable Energy Laboratory (NREL). Me´xico e Campeche, Quintana Roo and Yucata´n wind resource map. U.S Department of Energy; 2000. [9] Herna´ndez-Escobedo Q, Manzano-Agugliaro F, ZapataSierra A. The wind power of Me´xico. Renew Sust Energy Rev 2010;14:2830e40. [10] Galindo I, Castro S, Valdes M. Satellite derived solar irradiance over Mexico. Atmosphere 1991;4:189e201. [11] Mitchell K, Nagria M, Rizk J. Simulation and optimization of renewable energy systems. Int J Elect Power Energy Syst 2005;27:177e88. [12] Shakya BD, Aye L, Musgrave P. Technical feasibility and financial analysis of hybrid windephotovoltaic system with hydrogen storage for Cooma. Int J Hydrogen Energy 2005;30: 9e20.
[13] Ozbilen A, Dincer I, Naterer GF, Aydin M. Role of hydrogen storage in renewable energy management for Ontario. Int J Hydrogen Energy 2012;37:7343e54. [14] Veziroglu A, Macario R. Fuel cell vehicles: state of the art with economic and environmental concerns. Int J Hydrogen Energy 2011;36:25e43. [15] Wolk RH. Fuel cells for homes and hospitals. IEEE Spectrum 1999;36:45e52. [16] Valenciaga F, Evangelista CA. Control design for an autonomous wind based hydrogen production system. Int J Hydrogen Energy 2010;35:5799e807. [17] Calderon M, Calderon AJ, Ramiro A, Gonzalez JF. Weather data and energy balance of a hybrid photovoltaicewind system with hydrogen storage. Int J Hydrogen Energy 2010;35:7706e15. [18] Kamaruzzaman S, Mohd-Zamri I, Wan Ramli WD, MohdYusof O, Baharuddin Y, Nowshad A. Performance of a PVewind hybrid system for hydrogen production. Renew Energy 2009;34:1973e8. [19] Onara OC, Uzunoglua M, Alam MS. Modeling, control and simulation of an autonomous wind turbine/photovoltaic/ fuel cell/ultra-capacitor hybrid power system. J Power Source 2008;185:1273e83. [20] Arriaga LG, Martı´nez W, Cano U, Blud H. Direct coupling of a solarehydrogen system in Me´xico. Int J Hydrogen Energy 2007;32:2247e52. [21] Elhadidy MA, Shaahid SM. Promoting applications of hybrid (wind þ photovoltaic þ diesel þ battery) power systems in hot regions. Renew Energy 2004;29:517e28. [22] Khan MJ, Iqbal MT. Analysis of a small windehydrogen standalone hybrid energy system. Appl Energy 2009;86:2429e42. [23] Leva S, Zaninelli D. Hybrid renewable energy-fuel cell system: design and performance evaluation. Electric Power Syst Res 2009;79:316e24. [24] Akyuz E, Oktay Z, Dincer I. Performance investigation of hydrogen production from a hybrid windePV system. Int J Hydrogen Energy 2012;37:16623e30. [25] Pedicini R, Sacca` A, Carbone A, Passalacqua E. Hydrogen storage based on polymeric material. Int J Hydrogen Energy 2011;36:9062e8. [26] Pukazhselvan D, Kumar V, Singh SK. High capacity hydrogen storage: basic aspects, new developments and milestones. Nano Energy 2012;1:566e89.
Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018
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Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study Beatriz Escobar a, Jose´ Herna´ndez b, Romeli Barbosa b, Ysmael Verde-Go´mez a,* a b
Instituto Tecnolo´gico de Cancu´n, Av. Kabah Km. 3, Cancu´n 77500, Q. Roo, Mexico Universidad de Quintana Roo, Boulevard Bahı´a s/n, Chetumal 77019, Q. Roo, Mexico
article info
abstract
Article history:
The main advantage of the hybrid system compared with separate array solar photovoltaic
Received 3 September 2012
and stand-alone wind turbine is the possibility of the surplus energy storage by trans-
Received in revised form
forming it to hydrogen that can be use in fuel cells. However the design and sizing of this
1 November 2012
kind of technologies need to meet the local microclimate in order to reach higher efficacies.
Accepted 2 November 2012
A tool based on an analytical model to sizing, analyze and assess the feasibility of the
Available online xxx
hybrid wind/photovoltaic/H2 energy conversion systems using real weather data is presented in this work. The model considers an energy balance analysis and electrical
Keywords:
variables of the system components; the tool calculates the subsystems efficacy and
Hydrogen
proposes the improvements to increase the efficiency of the use in surplus energy
Modeling hybrid systems
produced by the hybrid system. To validate the analytical model, simulation based on wind
Renewable energy
speed and solar radiation measurements from meteorological monitoring station in
Fuel cells
a Mexican Caribbean City is discussed.
Energy balance
Copyright ª 2012, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights
Sizing system
1.
Introduction
Renewable energy sources are seen as an alternative energy generation instead of fossil fuels, it is not only to reduce the environmental pollution and global warming [1] but also to help in the sustainable development in emerging countries. The most known renewable energy, which it has become a mature technology for power generation are the photovoltaic arrays (PV). During the last decade PV’s applications have increased and extended to industrial and domestic use. This technology is characterized not only by its modularity and zero emissions of pollutants, but also by its low efficiency, and its production dependence on the sunlight. There are two main disadvantages: 1) the availability of solar resources, which depends on geographic location and weather
reserved.
conditions, and 2) the storage, since the solar energy needs to be transformed into another type of power source. On its hand, wind energy (WE) has been also established as an option in power generation, having a large technological growth in the recent years. However, it is also an intermittent energy, dependant of the weather. PV and WE have become two of the most promising technologies due to the fact that their energy sources are free and environmental friendly. The integration of renewable energy sources to form a hybrid system is an excellent option for power generation with a more stable working time [2]. However, we should consider the weather conditions, including solar irradiance and wind speed which are changing daily and seasonally. One of the major issues confronted by the users as well as the designers of PVeWE energy systems is the
* Corresponding author. Tel.: þ52 998 8807432; fax: þ52 998 8807433. E-mail addresses: [email protected], [email protected] (Y. Verde-Go´mez). 0360-3199/$ e see front matter Copyright ª 2012, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ijhydene.2012.11.018
Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018
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random and fluctuating nature of the energy sources. This makes the systems unpredictable or even unreliable [3], besides the limitation on energy storage for long periods of time. Then, the optimum conditions for the proper functioning of PVeWE systems are areas with high solar radiation levels evenly distributed, and places with large densities of wind energy. The recent interest in the use of wind and solar energies has promoted the measure and register of the locals weather in potential sites to use sustainable power sources, but it has been limited to short period of time [4e6]. This is the case of the anemometric stations located in Cancun, Quintana Roo, where the available information is only referred to the last decades. Mexico has identified several areas with high potential for renewable energy production. The coastal state of Quintana Roo (Q. Roo) is considered an area with high wind potential, especially during spring and summer, which is enhanced by the breeze sea [7]. The National Renewable Energy Laboratory in USA (NREL) has realized wind maps of the Yucatan Peninsula and according to its results, the Quintana Roo coastal has been classified from good to very good, due to the wind characteristics, with average speeds between 5.6 and 6.7 m/s at height of 30 m [8]. Herna´ndez-Escobedo et al. reported the calculations from the years of 2000 to 2008, and the average wind speed for the north of Yucatan Peninsula was estimated between 3 and 5 m/s [9]. On the other hand, Mexico receives an average solar irradiation of about 5 kWh/m2 [10], which provides to the Yucatan Peninsula considerable potential to generate solar electricity. In order to meet the continuous power delivery in PVeWE system, it is often realized by the use of high capacity and expensive energy storage [3]. Solar and wind energy are stored during sunny and windy days and released later during cloudy days, at night, in grid outages (emergencies, i.e., after hurricanes or natural disasters) or to smooth power demands. In addition, the electric energy is stored during low demand and later used in peak periods [11]. Usually, rechargeable and disposable batteries are used as energy storage systems. However, after many charges and discharges, the battery loses capacity and it has to be discarded by the user, which implicates an increment on the cost of the hybrid systems as well as considerable environment impact. One option to solve this problem is to use hydrogen as storage system of renewable energy, in order to increase the reliability of the stand-alone systems [12]. Hydrogen is one of the most promising alternative fuels for the future and it is emerging as a sustainable process to solve the energy storage [13]. The main characteristic of the above mentioned process is that it provides the opportunity to produce and store energy in-situ, eliminating in consequence the necessity of transportation of the fuel for backup purposes. On the other hand, fuel cells (FC’s) are by excellence the technology for an efficient consumption of hydrogen. It has achieved a global focus attention due to its versatility and special features as modularity, quiet operation, friendly environment, and efficiency which is about 60% [14] and it can reach up to 75% in cogeneration systems [15]. As a consequence, fuel cells are considered a viable, efficient and promising technology to use as backup power system, feed by the hydrogen produced using an electrolyzer activated by the excess energy generated in the renewable energy system (PVeWE). This electrochemical
subsystem (electrolyzerefuel cell) is integrated into hybrid systems to ensure energy supply. There are several experimental and theoretical studies of “PhotovoltaiceWindeHydrogen” (PVeWEeH2) hybrid systems in the world [12,16e19]. Even though in Mexico some theoretical and experimental studies of PVeH2 hybrid systems [20] had been reported, there is not any recent evaluation of WEePVeH2 hybrid systems available. In this work, an analytic model, design and simulation of a PVeWEeH2 hybrid system is developed. The paper presents a strategy based on efficacies to improve, in an easy way, the selection of power subsystems. As an example of this strategy, the optimal combination of PV, WE, proton exchange water electrolyzer (PEWE), and proton exchange membrane fuel cell (PEMFC) was studied for the solar and wind experimental data of Mexican Caribbean. The PVeWEeH2 system delivered electric power from primary sources (PVeWE) to satisfy the electric load. Surplus energy is supplied to an electrolyzer in order to generate hydrogen. In energy deficit hours a PEMFC generates part or the total of the electric demand. Therefore a hybrid system efficacy is calculated based on the level of energy stored, and the fulfillment of the electric load.
2.
Theory and calculation
The sizing of a hybrid system has to consider the steady state characteristics, unsteady profiles of the site energy source and the electricity loading demand [21]. Although these profiles restrict the power of the subsystems to a limited range of possibilities, the numbers of possible combinations are numerous. The overall configuration of a WEePVeH2 hybrid system proposed for a grid of an independent house is shown in Fig. 1. This system consists of a wind turbine, PV, PEWE, PEMFC, power control system, and hydrogen storage system [22e24]. If the total power generated by the primary system (PV and WE) is higher than the electrical demand, the surplus energy is used in PEWE to produce hydrogen as long as the power excess exists and the maximum of the PEWE nominal power and storage level allow. If the primary system is not sufficient to meet the loading, the energy required will be provided from a hydrogen tank, and used in the PEMFC, as long as the power deficit exists and the maximum of the PEMFC nominal power and storage level allow. In other words, nominal power of the subsystems should be carefully selected to satisfy the electric demand but without oversizing the system. This system operation features allow us to define the “efficacy” term (functionality) of the system in both conditions (undersizing or oversizing). Undersizing condition exists when the electrical demand is not entirely fulfilled, and oversizing will be when the input energy is not completely useful. Eq. (1) determines the “Load efficacy” (hL), hL ¼ εL;actual =εL;nom
(1)
where εL,actual is the actual energy consumed and εL,nom the nominal energy demanded. The “Useful efficacy” (hU) is determined by Eq. (2), (2) hU ¼ ðεL;actual þ εS Þ εin
Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018
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Fig. 1 e General diagram of the hybrid system.
where εS is the energy stored and εin the input energy. System’s global efficacy can be determined by a “Mixed efficacy” (hM), hM ¼ hL hU
(3)
The design strategy consists in makes a parametric combination of the subsystems power and simulates the instantaneous system behavior using experimental profiles along the time. Average of the instantaneous efficacies helps to select the best combination. Instantaneous system behavior will be determining by an energy balance analysis. In following sections are summarized the analytical models to simulate: input, stored and output electrical energy.
2.1.
Energy input
The input energy (εin) of the hybrid system is the sum of the electrical energy output of the PV and WE subsystems. εin ¼ εPV þ εWE
of a 1000 W commercial turbine (Whisper H-80) is showed in Fig. 2. In this particular case, there are two equations to calculate εWE, when wS is in the range of 3.3e11.3 m/s (upper equation) and 11.3e25.0 m/s, (bottom equation).
2.2.
Energy storage
Electrical energy stored can be determined by the balance of mass in the storage subsystem, NHs ¼ NHg NHc
(6)
where NHs is the hydrogen stored, NHg is the hydrogen generated and NHc the hydrogen consumed. In a PEMFC, NHc is directly proportional to the electrical energy produced. This can be determined by Faraday’s law [19]. NHc ¼ ðNCFC IFC tÞ=ð2FhFC Þ
(7)
(4)
where εPV is the energy output of the PV and εWE is the energy output of the WE. These energies are in function of solar and wind resource of the site and the physical characteristics of the devices. Instantaneous electric energy output from a PV (εPV) is given for the following Equation: εPV ¼ hPV APV IT
(5)
where hPV is the instantaneous PV efficiency, APV the total area of the PV and IT equals to instantaneous solar radiation per area incident on PV surface. Strictly, hPV is dependent of three parameters: the temperature, the packing factor and the module reference efficiency. However, the efficiency used in this work is a global parameter of a hypothetical PV (hPV ¼ 0.11%). In this work, the size of wind turbine was not varied. However, instantaneous electric energy output from WE (εWE), is in function of the wind speed (wS). The characteristic curve
Fig. 2 e Power curve and lineal regression equation of a commercial wind turbine (Whisper H-80). Wind turbine power (WTP) as a function of the wind speed (wS); two equations are necessary for two different ranges of wS.
Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018
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hFC ¼ EFC =ðErev NCFC Þ
(8)
where Erev is the reversible potential of one cell of the PEMFC stack and EFC is the total potential of the stack. On the other hand, in electrical terms, the energy produced by the PEMFC stack (εFC) is in function of the operating time (t), the total current (IFC) and the total potential of the stack (EFC), εFC ¼ IFC EFC t
1000 800 600 400 200 0 0
2
4
6
8
NHc ¼ ðεFC Þ= 2FErev h2FC
10 12 14 16 18 20 22 24 Time / hour
(9)
Fig. 4 e Hourly electricity demand of a hypothetical house in Mexican Caribbean City.
In this way, the hydrogen consumed is:
(10)
Likewise, according to Faraday’s law, hydrogen production rate in an electrolyzer is directly proportional to the electrical current in the electrolyzer circuit [19]. NHg ¼ ðNCPEE IPEE thPEE Þ=ð2FÞ
(11)
where NHg are the H2 produced (in mol), NCPEE is the total number of cells in the electrolyzer, IPEE is the total electric current, t is the operating time and F the Faraday constant. The electrolyzer efficiency (hPEE) can be defined thermodynamically as follow: hPEE ¼ ðErev NCPEE Þ=EPEE
(12)
where Erev is the reversible potential of one cell in the electrolyzer and EPEE is the total potential of the electrolyzer. In electrical terms, the energy consumed by the electrolyzer (εPEE) is: εPEE ¼ IPEE EPEE t
(13)
In this way, the hydrogen generated is: NHg ¼ εPEE h2PEE
1200
Load power / Wh
where NHc are the mol of H2 consumed, NCFC is the total number of cells in the PEMFC stack, IFC is the total electric current, t is the operating time and F the Faraday’s constant. The PEMFC stack efficiency (hFC) can be defined thermodynamically by,
ð2FErev Þ
(14)
If the hydrogen stored will be used exclusively by the same PEMFC stack of the system, the electrical energy stored (εS) can be determined systematically using Eq. (10), εS ¼ NHS 2FErev h2FC
(15)
Substituting Eq. (6) in Eq. (15) and then substituting Eqs. (10) and (14), we can determine the εS of the hybrid system in terms of the efficiencies and energy of the PEMFC and PEWE, in the time interval studied: εS ¼ h2FC h2PEE εPEE εFC
(16)
The PEMFC and PEWE efficiency are as a function of their total potentials (Eqs. (8) and (12), respectively). Hence, Fig. 3 shows the performance of PEMFC and PEWE single-cell used in this work, which are experimental polarization curves carried out in our laboratory.
2.3.
Energy output
The electrical output of the hybrid system is equal to the power consumed by the electrical load. The nominal load profile proposed corresponding to the hypothetical consume of a house is showed in Fig. 4. The nominal energy output can be obtained by the curve integration in the time period required. It assumed that this load pattern would remain during all days of the year. However when the PEMFC power is not enough to complete the electrical deficit, the electrical output is only the maximum energy available. So, under this condition the actual energy consumed (εL,actual) is not always
Cell potential / V
1.6 1.4 1.2 PEMFC
1 0.8
PEWE
0.6 0.4 0.2
14
8 7
12
6
10
5
8
4
6
3 4
2
2
1 0
0
0 0
0
0.2
0.4 0.6 0.8 1 Current density / A cm-2
1.2
Fig. 3 e Single-cell polarization curve of fuel cell (PEMFC) and electrolyzer (PEWE).
Wind speed / m s-1
1.8
Insolation / kWh m-2 month-1
9
2
1
2
3
4
5
6
7
8
9 10 11 12
Time / month
Fig. 5 e Experimental data of weather in Cancun, Mexico, insolation monthly average and wind speed monthly average.
Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018
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Table 1 e Limits and interval of the parametric combination of the nominal powers of PV, PEMFC and PEWE subsystem.
Minimum Maximum Interval
PPV (W)
PFC (W)
PE (W)
110 5060 330
30 1463 75
163 6350 651
the nominal energy demanded (εL,nom), thus we can evaluate the load efficacy.
3.
Simulation conditions
The net hourly electrical power according to the solar irradiance and wind speed in Cancun, Mexico was determined by experimental data, including the average of two periods of time: 2001e2005 and 2007e2009. This annual average behavior is showed in Fig. 5. A commercial wind turbine was studied, energy output of the WE (εWE) was calculated from the equations showed in Fig. 2. Furthermore the number of bipolar plates of the PEMFC and PEWE were constant. However, the nominal power of PV (PPV) defined from exposure area, the nominal power of PEMFC (PFC) and the nominal power of PEWE (PE) defined from the electrode area, these variables were systematically studied as shown in Table 1. In this work, the storage tank capacity is considered to meet up 10 autonomous operation days at rated load. This storage maximum capacity was taken to satisfy a critical shortage of energy after a Hurricane, situation which is very likely in Mexican Caribbean; however, this condition can be fixed for different scenarios. The storage of energy in hydrogen form is a current technological challenge which is
under extensive research [25,26]. In this work, the technology of hydrogen storage systems (e.g. metal hydride, compressed/ liquid storage and sorbents) as well as the secondary devices (i.e., sensors, actuators, valves and controllers) are not included. Simulation in variations of the wind turbine size and tank capacity will be integrated in future work.
4.
Results
The energy input (subject to experimental data), the energy stored (evaluated by Eq. (16)) and the strategy to evaluate the actual energy consumed, allow to determinate the mixed efficacy (Eq. (3)) with several hypothetical nominal powers (Table 1). The hourly efficacy is averaged to evaluate annual behaviors and then compared in order to found the best solution. Fig. 6 shows the dependence of the mixed efficacy (hM) respects to PPV. In this Figure, the “points” are plotted for all possible combinations, and the marker lines indicate five different scenarios for electrochemical subsystem power (PFC and PE), where the minimum, intermediate and maximum rated powers correspond to Table 1: PEmin ¼ 163 W; PEint ¼ 3094 W; PEmax ¼ 6350 W; PFCmin ¼ 30 W; PFCint ¼ 709 W; and PFCmax ¼ 1463 W. Depending on the PE and PFC values, hM reaches a maximum in a specific PPV value. hM increases because load efficacy (hL) is higher with the input power increment (i.e. PPV and PFC increment), but when the surplus energy of the system exceeds the maximum energy level of the hydrogen storage system, useful efficacy (hU) decreases to have a surplus that is not used, this suggests that the system is “oversizing”. In addition, it can also observe that if the system includes a PEmin, then hM is the lowest due to the hydrogen production does not meet the gas demand. This behavior is similar when the PEmax and PFCmin, in this case hydrogen production is Selected
0.75
η M max = 0.73 %
0.7
Mixed efficacy / %
0.65 0.6 0.55 0.5 PEmin - PFCmin PEmin - PFCmax PEmax - PFCmin PEmax - PFCmax PEint - PFCint
0.45 0.4 0.35 0
1000
2000
3000
4000
5000
PPV / W Fig. 6 e Dependence of the mixed efficacy (hM) with respect to photovoltaic array power (PPV). Different powers of fuel cell (PEMFC) and electrolyzer (PEWE) conditions are indicated in the marker lines. Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018
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PPV=2420 W ηM =0.723 %
0.75
PPV=2750 W ηM=0.727 %
0.7
Mixed efficacy / %
0.65 0.6 0.55 0.5 0.45 PPVmin - PEmin PPVmin - PEmax PPVmax - PEmin PPVmax - PEmax PPV=2420 - PEmax PPV=2750 - PEmax PPV=3080 - PEmax
0.4 0.35 0.3 0
200
400
600
800
1000
1200
1400
PFC / W Fig. 7 e Dependence of the mixed efficacy (hM) with respect to fuel cell power (PEMFC). Different powers of photovoltaic array (PPV) and electrolyzer (PEWE) conditions are indicated in the marker lines. Dotted lines indicate the points selected in Fig. 6.
bigger than the fuel cell capacity; in both cases the systems power is wasted. The best scenario occurs when the hybrid system uses a PEmax and PFCmax. This is an expected behavior because of the high PPV is capable of meet the energy demand of the electrolyzer which is able to feed the fuel cell to produce electricity. Similar performance is observed when intermediate values are used. Three interesting PPV points at 2420, 2750 and 3080 W, were selected for further comparison.
Dependence of hM respect to PFC is shown in Fig. 7. The “points” are plotted for all studied combinations, i.e. the maximum and minimum limit conditions of PPV and PE. It can be observed that the lowest hM value corresponds to PPVmax in combination with PEmin, it means that the entire solar power is not used by the electrolyzer. Also it should be noticed that the maximum powers condition does not promote the maximum efficacy reached in some scenarios of the Fig. 6. The
Fig. 8 e Dependence of the mixed efficacy (hM) with respect to electrolyzer power (PEWE). Different powers of photovoltaic array (PPV) and fuel cell (PEWE) conditions are indicated in the marker lines. Dotted lines indicate the points selected in Fig. 7. Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018
i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y x x x ( 2 0 1 2 ) 1 e8
a
b
ηM 0.8
0.7 0.65 0.6 S1) PPV=2750; PE=6350; PFC=634
Load efficacy / %
Mixed efficacy / %
ηL 1
0.75
0.55
7
0.9 0.8 0.7 S1) PPV=2750; PE=6350; PFC=634
0.6
S2) PPV=2420; PE=6350; PFC=558
S2) PPV=2420; PE=6350; PFC=558
S3) PPV=2420; PE=2750; PFC=558
S3) PPV=2420; PE=2750; PFC=558
0.5
0.5 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Fig. 9 e Monthly performance of the mixed efficacy (a) and load efficacy (b), for S1, S2 and S3 identified in Fig. 8.
three dotted lines correspond, in combination with the PEmax condition, to PPV selected points from Fig. 6. These conditions show the best performance of hM, reaching around the 0.72% efficacy. Following with the analysis strategy, two interesting points also were selected: 1) PPV ¼ 2420 W @ PFC ¼ 558 W and 2) PPV ¼ 2750 W @ PFC ¼ 634 W. Mixed efficacy (hM) versus PE is showed in Fig. 8. The marker lines indicate the four limit conditions of PPV and PFC, where “min” and “max” corresponds to the rated power shown in Table 1. In this graph, hM increases while PE increases. The lowest value condition is PPVmax PFCmin due to the two apparent facts: 1) oversizing of PV, and 2) the low capacity of the fuel cell to produce electricity. The hM improves with the use of PFCmax regardless of the PPV value; however they are not reach the maximum values showed in previous scenarios. The two dotted lines correspond to the two interesting conditions selected from Fig. 7 which do not show significant difference, reaching the highest hM at 0.72% with PEmax condition. In order validate the analytical model and calculate the average efficacies hM and hL under real weather conditions, three points at the highest efficacy were selected from previous analyses and they were combined with the Cancun solar and wind weather data: S1) “PPV ¼ 2750 W, PE ¼ 6350 W, PFC ¼ 634 W”; S2) “PPV ¼ 2420 W, PE ¼ 6350 W, PFC ¼ 558 W”; and S3) “PPV ¼ 2420 W, PE ¼ 2750 W; PFC ¼ 558 W”. The system sizing perspective and monthly behavior are detailed in Fig. 9. It is clear that hM do not have a significant dependence of the wind and solar conditions; for example from March to May the insolation is high (Fig. 5) the mixed efficacy is low; it can be attributed to the limited optimization of the power systems, especially the photovoltaic array. Comparing the three conditions selected, it is relevant to note out that hL slightly decreased between 1.0 and 0.95% from January to October. The major difference, for both hM and hL, is in November and December. November presents the highest mixed efficacy for S1 and S2 systems; however is the worst month for S3 system. Also in November, S1 and S2 systems can reach a load efficacy near to w0.95%, while S3 system is the lowest w0.80%. Based on the results, using the analytical model proposed is possible make decisions to choose strategies which allow sizing hydrogen hybrid systems with the best efficacy.
For example, in the present case of study: 1) prioritize hL and select the system S1, and even analyze higher power systems, for example when PPV ¼ 3080 W; 2) adjust the energy management of November (critical month) in order to increase the efficiency without requiring more power; and 3) an “extra” should be provided to meet the energy demand in the critical months. Finally, the analytical model presented can be used as a tool to design and sizing PVeWEeH2 systems considering locals microclimate with the high efficacies.
5.
Conclusions
Theoretical efficacy of a hybrid windesolarehydrogen system at different scenarios was determined using an analytical model tool. Energy balance, electrical and electrochemical characteristics of the systems and microclimate data of solar and wind resource from Mexican Caribbean City were used to validate the model. Results shows that the highest PPV, PFV or PE not always meet the highest efficacy of the hybrid system, therefore the model allows determine the best subsystems configuration to avoid the oversizing or undersizing. The simulation data applied different scenarios show the hM, around the 0.73% at 3 kW of PPV, 0.68 at 1 kW of PFC and 0.68% at 2 kW of PE, respectively. The average efficacies hM and hL under real monthly weather conditions using three points at the highest efficacy were also validate, showing that hM do not have a significant dependence of the wind and solar conditions, but it can be related with the optimal sizing systems; meanwhile solar and wind conditions has a slightly effect over the hL which is maintained between 1.0 and 0.95%. Finally, based on the results, using the analytical model proposed is possible make decisions to choose strategies which allow sizing hydrogen hybrid systems with the high efficacy.
Acknowledgment This work was supported by FORDECYTeCONACYT under project No. 116157.
Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018
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i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y x x x ( 2 0 1 2 ) 1 e8
references
[1] Ban˜os R, Manzano FA, Montoya FG, Gil C, Alcayde A, Go´mez J. Optimization methods applied to renewable and sustainable energy: a review. Renew Sust Energy Rev 2011; 15:1753e66. [2] Dufo-Lo´pez R, Bernal-Agustin JL, Mendoza F. Design and economical analysis of hybrid PVewind systems connected to the grid for the intermittent production of hydrogen. Energy Policy 2009;37:3082e95. [3] Ahmed NA, Miyatake M, Al-Othman AK. Power fluctuations suppression of stand-alone hybrid generation combining solar photovoltaic/wind turbine and fuel cell systems. Energy Convers Manage 2008;49:2711e9. [4] Cancino Solo´rzano Y, Xiberta-Bernat J. Statistical analysis of wind power in the region of Veracruz (Mexico). J Renew Energy 2009;34:1628e34. [5] Jung S, Vanli OA, Kwon SD. Wind energy potential assessment considering the uncertainties due to limited data. Appl Energy 2012;102:1492e503. [6] Carta JA, Vela´zquez S, Matı´as JM. Use of Bayesian networks classifiers for long-term mean wind turbine energy output estimation at a potential wind energy conversion site. Energy Convers Manage 2011;52:1137e49. [7] Jaramillo OA, Saldan˜a R, Miranda U. Wind power potential of Baja California Sur, Me´xico. Renew Energy 2004;29:2087e100. [8] National Renewable Energy Laboratory (NREL). Me´xico e Campeche, Quintana Roo and Yucata´n wind resource map. U.S Department of Energy; 2000. [9] Herna´ndez-Escobedo Q, Manzano-Agugliaro F, ZapataSierra A. The wind power of Me´xico. Renew Sust Energy Rev 2010;14:2830e40. [10] Galindo I, Castro S, Valdes M. Satellite derived solar irradiance over Mexico. Atmosphere 1991;4:189e201. [11] Mitchell K, Nagria M, Rizk J. Simulation and optimization of renewable energy systems. Int J Elect Power Energy Syst 2005;27:177e88. [12] Shakya BD, Aye L, Musgrave P. Technical feasibility and financial analysis of hybrid windephotovoltaic system with hydrogen storage for Cooma. Int J Hydrogen Energy 2005;30: 9e20.
[13] Ozbilen A, Dincer I, Naterer GF, Aydin M. Role of hydrogen storage in renewable energy management for Ontario. Int J Hydrogen Energy 2012;37:7343e54. [14] Veziroglu A, Macario R. Fuel cell vehicles: state of the art with economic and environmental concerns. Int J Hydrogen Energy 2011;36:25e43. [15] Wolk RH. Fuel cells for homes and hospitals. IEEE Spectrum 1999;36:45e52. [16] Valenciaga F, Evangelista CA. Control design for an autonomous wind based hydrogen production system. Int J Hydrogen Energy 2010;35:5799e807. [17] Calderon M, Calderon AJ, Ramiro A, Gonzalez JF. Weather data and energy balance of a hybrid photovoltaicewind system with hydrogen storage. Int J Hydrogen Energy 2010;35:7706e15. [18] Kamaruzzaman S, Mohd-Zamri I, Wan Ramli WD, MohdYusof O, Baharuddin Y, Nowshad A. Performance of a PVewind hybrid system for hydrogen production. Renew Energy 2009;34:1973e8. [19] Onara OC, Uzunoglua M, Alam MS. Modeling, control and simulation of an autonomous wind turbine/photovoltaic/ fuel cell/ultra-capacitor hybrid power system. J Power Source 2008;185:1273e83. [20] Arriaga LG, Martı´nez W, Cano U, Blud H. Direct coupling of a solarehydrogen system in Me´xico. Int J Hydrogen Energy 2007;32:2247e52. [21] Elhadidy MA, Shaahid SM. Promoting applications of hybrid (wind þ photovoltaic þ diesel þ battery) power systems in hot regions. Renew Energy 2004;29:517e28. [22] Khan MJ, Iqbal MT. Analysis of a small windehydrogen standalone hybrid energy system. Appl Energy 2009;86:2429e42. [23] Leva S, Zaninelli D. Hybrid renewable energy-fuel cell system: design and performance evaluation. Electric Power Syst Res 2009;79:316e24. [24] Akyuz E, Oktay Z, Dincer I. Performance investigation of hydrogen production from a hybrid windePV system. Int J Hydrogen Energy 2012;37:16623e30. [25] Pedicini R, Sacca` A, Carbone A, Passalacqua E. Hydrogen storage based on polymeric material. Int J Hydrogen Energy 2011;36:9062e8. [26] Pukazhselvan D, Kumar V, Singh SK. High capacity hydrogen storage: basic aspects, new developments and milestones. Nano Energy 2012;1:566e89.
Please cite this article in press as: Escobar B, et al., Analytical model as a tool for the sizing of a hydrogen production system based on renewable energy: The Mexican Caribbean as a case of study, International Journal of Hydrogen Energy (2012), http:// dx.doi.org/10.1016/j.ijhydene.2012.11.018