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Integration of High Penetrations of Intermittent Renewable Generation in Future Electricity Networks Using Storage
30 Integration of High Penetrations of Intermittent Renewable Generation in Future Electricity Networks Using Storage David Greenwood1, Sara Walker1, Neal Wade1, Stalin Munoz-Vaca1, Andrew Crossland2, Charalampos Patsios1 1 SCHOOL OF ENGINEERING, NEWCAS TLE UNIVE RSI TY, NEWCASTLE-UPON TYNE, UNITED KINGDOM; 2 ADVANCE FURTHER ENERGY LTD, RETFORD AND INFRATEC, WELLINGTON, NEW ZE ALAND
30.1 The low-carbon transition of electricity networks The global challenge to reduce carbon emissions continues to be a thorny issue for governments worldwide. In the United Kingdom, the 2008 Climate Change Act has required the development of carbon budgets, consistent with an 80% reduction by 2050, although recent concern has been raised regarding the risk of under delivery [1]. While the current 80% by 2050 target is a major driver for electricity sector transformation, pressures for more rapid decarbonization may yet result from the Committee on Climate Change’s analysis of the Paris agreement [1]. Studies identify the electricity sector as a key sector to help achieve the interim target with relatively low cost and low uncertainty [2]. For many electricity networks, decarbonization poses multiple problems. There is the issue of increasing demand for electricity, particularly if heat and transport demand shifts with respect to primary energy source, from liquid and gas fossil fuels to electricity. Within that picture of growing demand is the complexity of growth in peak power and growth in annual energy. To meet that demand, using lower and zero carbon sources of electricity generation means a consequential growth in the use of renewable energy technologies. The available options to decarbonize the electricity sector in the United Kingdom are nuclear power, large-scale renewables, fossil fuel power stations with carbon capture and sequestration (not yet a mature technology), and small-scale renewables [3]. The EU Renewable Energy Directive required the United Kingdom to reach agreed targets by 2020 of 15% of the overall share of energy from renewable sources, which
Future Energy. https://doi.org/10.1016/B978-0-08-102886-5.00030-X Copyright © 2020 Elsevier Ltd. All rights reserved.
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resulted in the UK Government publication of the Renewable Energy Strategy [4], which set an aspirational (nonbinding) target that more than 30% of UK electricity consumption would be generated from renewables in 2020. In June 2018, the contribution of renewables to electricity generation reached 31.7% [5]. Growth in photovoltaic (PV) and wind turbine installations has driven this rapid increase in generation from renewables, up from just 5.5% in 2009. Onshore wind and solar PV together represented around 31% of all renewable capacity, the highest share of renewable technologies. This was followed by offshore wind at 19%, by June 2018. The fall in price of solar PV systems over the last decade [6] and government subsidies have resulted in an increased number of solar PV systems with cumulative installed PV capacity in the United Kingdom reaching 13 GW by mid-2018 [5].The total installed wind capacity by mid-2018 was 21 GW in the United Kingdom [5], driven by falling costs of onshore and offshore wind turbine technology, as well as offshore development driven by the Crown Estate [7]. There are a number of financial support mechanisms in place which enable, and have supported the recent growth of, renewable energy for electricity generation in the United Kingdom: renewables obligation, feed-in tariff, and contracts for difference (CfD). The CfD second round strike price for offshore wind was £74.75 (MWh)1 and £57.50 (MWh)1 [8], lower than the £92.50 (MWh)1 agreed for the new Hinkley nuclear power station. The operational management complexity of intermittent and stochastic generation and demand has been expressed by several authors [9,10].Balancing supply and demand in real time on the electricity network is required to maintain quality of supply. The quality of supply for an electricity network is ensured by managing and mitigating disturbances such as voltage dips, voltage surges, overvoltage, harmonics, power frequency variations, voltage fluctuations, rapid voltage change, voltage imbalance, short- and long-voltage interruptions, and under voltage and transients. Intermittency of some generation sources can be managed through flexibility in other generation technologies, storage, and flexibility (or control) in energy demand. In the remainder of this chapter, we look at the management of electricity networks to enable the connection and generation of large volumes of renewable energy technologies, particularly those impacting on low-voltage (LV) networks.
30.2 Managing intermittency of PV through storage Expansion of PV generation is increasing the challenge for network operators to keep voltages within operational limits. Voltage rise occurs in LV networks when distributed generators export, particularly at times of low demand. However, there is little work quantifying the scale of voltage issues and subsequently potential solutions across large numbers of real networks. In a recent study, we investigated the potential for storage, in combination with PV, to reduce the incidence of overvoltage in LV networks. We considered (1) installation by homeowners and commercial customers for increased self-consumption and (2)
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11kV
a
400V
MV network
b Secondary transformer
Residential rooftop PV
FIGURE 30.1 Locations for LV storage showing (A) storage in homes owned by customers and (B) storage located on the street.
installation directly onto the grid by electricity distribution network operators (DNO) to manage network power flow (Fig. 30.1). We assessed the impact of multiple PV dispersion levels, pn, on the voltage regulation in multiple LV networks and the subsequent effect of energy storage randomly installed in customer homes with dispersion qn or sited by DNOs to manage overvoltage. Load flow was implemented in Matlab using OpenDSS network models. For the domestic installation study, storage was assumed for each home with PV with a probability qn. A load flow was then used to calculate the voltage rise. If there is overvoltage, this is recorded. Storage was represented as a load charging to absorb excess PV with rating PES. For the DNO installation study, a genetic algorithm was used from the Matlab Global Optimisation Toolbox, which identified the locations of storage in network, n, to prevent overvoltage with fewest storage units in the network. Without storage, and for three PV penetration scenarios, we investigate projected PV dispersion levels, pn, in each network n to identify the number of feeders forecast to experience overvoltage (total number of feeders investigated: 43,816), as shown in Fig. 30.2. We then investigated a number of domestic storage adoption scenarios, which are shown for the medium PV integration scenario in Fig. 30.3. Randomly located storage
FIGURE 30.2 Number of problematic feeders under different PV growth scenarios.
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FIGURE 30.3 Amount of storage installed, according to a medium PV scenario, with storage randomly located in different percentages of homes and storage located by the DNO.
does reduce the number of feeders with overvoltage (from 1250 in year 35 with no storage to 1150 with 5% and 1000 with 15% PV with storage). DNO sited storage is, by nature of the algorithm, able to solve overvoltage. It does so with reduced total installed storage capacity compared with the domestic installations (Fig. 30.3). Finally, we considered the costs of each approach. We assumed problematic feeders were upgraded to cope with overvoltage, by multiplying the length of each problematic feeder by a reconductoring cost (£80 m1). The storage was assumed to be lithium-ion batteries, which represented the most widely deployed battery type in residential power networks. Prices of these have fallen significantly in recent years, and representative battery costs were sourced through an industrial survey as well as literature search. Energy storage located by the DNO is cheaper than all other options, for the DNO, as shown in Fig. 30.4. The results of this work showed that, if storage is used along side PV as a means to reduce overvoltage in LV networks, it should be carefully located by the DNO within an LV network using a heuristic method to minimize a DNO’s overall cost. Storage may still offer benefits to homeowners if located in domestic homes, and domestic installation does have a benefit to DNOs in reducing overall reinforcement costs. However, it is found that storage in homes will not prevent all overvoltage because the location of the storage in networks is not optimized for overvoltage reduction in this case.
30.3 Energy storage technologies There is a wide variety of energy storage technologies that could be deployed to fulfill applications within electrical networks. These technologies have been reviewed by numerous other authors, but the goal of this chapter is to summarize and curate that information in such a way that it can be used by technology developers, aggregators, and power system operators when considering the design of new energy storage technologies
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FIGURE 30.4 Total reinforcement cost for the DNOs to reconductor despite storage in homes or cost of storage located by the DNO, high-PV scenario.
or power network services. In this section, we briefly describe each technology and provide a summary of the relevant information for use by energy storage developers, network and system operators, and regulators. The key parameters for each technology are presented in Table 30.1.
30.3.1
Vanadium redox Flow Batteries
Flow batteries are an energy storage technology in which liquid electrolytes are stored in tanks and pumped into cells to produce electrochemical reactions [21,26]. The vanadium redox flow battery is a technology characterized by the redox reactions of different ionic forms of vanadium [11]. As the electrolyte tanks and power stacks are separated, the energy capacity of these batteries can be increased or reduced based on the tanks’ volume, while the power capacity depends on the number of cells in the power stacks. This flexible decoupling of power and energy (from kW and kWh to larger scales of MW and MWh [15]) makes this technology attractive for grid-scale energy applications [13]. For grid-scale applications, this type of battery has a number of strengths attached: long lifetime, low sensitivity to high depths of discharge, low self-discharge, and power and energy independence. The long lifetime of this device is achieved through the nondegradation of its electrolyte through time. This condition makes the cell stack the most likely component to determine battery life duration (more than 10 years with over 10,000 charge/discharge cycles at very high depths of discharge) [11,13,26]. Another
Cost of energya ($/kWh)
Cost of powera ($/kW)
318e880 [11,12]
1000e2133 Around 50 [12] [13] 159e212 [12] 1e30 Wh/kg [13] 159e212 [12] 200e550 [13,19] 159e1994 30e100 [11,12] [12,20] 159e350 100e250 [12,23] Wh/kg [16] 500e2000 0.25e1.5 [12] [17] 500e1750 3e6 [19] [15] 200e300 [19] 80e500 [19]
Supercapacitors 10,600e21,200 [12] Lithium-ion 250e500 [13,19] Lead acid
50e265 [12,20]
Sodium-sulfur
350e742 [12,22]
Pumped hydro
5e75 [12,23]
CAES
3e80 [12,15]
TESb
3e100 or more [13,19] 650 [14]
ZEBRA
Nickelecadmium 400e2400 [20] Flywhee
1000e5000 [17,19]
b
Power density (W/l) 0.15 W/cm2 [13] 100 [13]
Round trip efficiency (%)
Selfdischarge (% per day)
Response time (ms)
Cycle lifetime (100% DoD)
70e85 0.1e0.4 [12] Few [16] Over 10,000 [13] [14,15] 52e96 [18] 10e20 [12] Under 10 [12] Over 100,000 [17] 1000e4000 Over 93 0.1e0.3 [12] 20 [16] 3000e6000 [13] [13] [13] 3e5 [12] 1000e1800 10e500 [12] 63e90 [13] 0.13e0.6 [13] [11,21] 260 W/kg 75 [22,23] Around 10 3e5 [12] 4500 [11,22] [16] [12] 0.5e1.5 [19] 75e82 0.005e0.02 2e10 min [17] Over 13,000 [22] [12,15] [12] 3e12 min Over 10,000 [15] 0.5e2 [19] 40e70 0.5e1 [12] [12,20] [24,25] e 30e72 0.05e1 [19] 2.5 min [13] e [13,19] 3500 [14] 95e120 150 W/kg 85e90 [16] Around 20 [16] 3000 (80% DoD) Wh/kg [14] [19] 15 [19] [16] 500e1500 15e75 50e1000 60e70 [16] 0.2e0.6 [19] e Under 3500 [19] Wh/kg [19,20] W/kg [20] [16,21] 1000e2000 85e95 100 [12,19] 4 [22] Over 100,000 250e350 [19] 20e200 [19] [19,23] [16,17] [12,19]
Conversion rate: £1 ¼ $1.25 and V1 ¼ $1.06. Depending on the thermal technology.
a
Energy density (Wh/l)
Lifetime (years) 10e20 [17] 15 [12] 5e15 [13] 5e15 [21] 15 [11,22] 30e50 [12,15] 20e30 [15] 10e40 [19] e 10e20 [19,20] 15e20 [19,22]
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Specific characteristics of energy storage technologies.
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strength is its low self-discharge characteristic, a consequence of storing electrolytes in separate sealed tanks [21]. This technology can produce an output power higher than its rated capacity as demonstrated in Refs. [27,28] and step from zero to maximum output power in few milliseconds [11]. When the stacks contain electrolyte, the storage system can be used for short duration applications, such as power quality, as the pumping system does not need to be in operation. If the stacks are appropriately designed, balancing and regulation services can be delivered [15]. Energy applications such as arbitrage and load leveling are achieved by storing large volume of electrolytes. However, the system is physically large and has a round trip efficiency between 75% and 85%, depending on electrochemical, shunt current, and pumping losses [13].
30.3.2
Supercapacitors
Supercapacitors store energy as an electrical charge and consist of a porous separator between two conductor electrodes and an electrolyte [13,21]. They can achieve higher energy density than capacitors due to the porous electrodes with high surface area. This technology can reach much higher power rating than batteries with fast charge/ discharge cycles, but it also presents a high self-discharge [21,29,30]. It is attractive for short-term responses such as frequency grid services. Supercapacitors have a long lifetime (i.e., very high number of charge/discharge cycles); their energy efficiency is heavily dependent on their discharge rate [31] and, dependent on construction and voltage, can vary from 52% to 96% [18]; this illustrates the need to design energy storage technologies based on their intended applications. Supercapacitors have a high energy capacity cost in comparison with similar energy storage alternatives [13].
30.3.3
Lead acid batteries
Lead acid batteries are the most mature battery technology, and they initially dominated the world market in small- and medium-scale electrochemical energy storage applications [13,21]. This technology consists of stacked cells submerged into an electrolyte comprising a sulfuric acid [11]. The cells have a lead dioxideepositive electrode and a metallic leadenegative electrode, which together become lead sulfate during the discharge process [13]. There are a number of grid-scale projects using lead acid batteries such as in California (10 MWe14 MWh), Puerto Rico (20 MWe14 MWh), and Germany (8.5 MWe8.5 MWh), among others [13]. Advantages of this technology are its low selfdischarge characteristic (4%e20% per month), safety features, and its well-established recycling process [11,13]. The round trip efficiency of these batteries can range from 63% to 90%, but they have poor cycle life, with only 1000 cycles approximately [13]. This device is also sensitive to high and low ambient temperatures, which can modify its lifetime (5e15 years) [21]. In order to improve the drawbacks, a number of variants are available for this technology: lead acid carbon technology, for example, is a variant of the
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traditional lead acid batteries that improves its power characteristics and reduces its partial state of charge effect [11].
30.3.4
Lithium-ion (Li-ion)
Li-ion batteries consist of a lithiu-based anode and a cathode, typically constructed from graphite or another carbon-based material, separated by an electrolyte that supports the movement of lithium ions during charge and discharge. Power ratings of existing systems vary from 2 kW up to 48 MW at the Gyeongsan Substation in South Korea. The advantages of Li-ion batteries over other battery technologies are high energy density (400e550 Wh L1), high efficiency (>93%), low maintenance costs, and relatively low self-discharge [30]. The capital cost for installation is around $250e$500 (kWh)1.
30.3.5
Sodium-sulfur battery
Sodium-sulfur (NaS) batteries are a promising energy storage technology for a number of applications, particularly those requiring high-power responses [11,21]. It is composed of a sodium-negative electrode, a sulfur cathode, and a beta-alumina solid electrolyte that produces sodium pentasulfide during the discharge reaction [21]. The primary strength of this technology is its long discharge time. It operates at a hightemperature regimen of 300e350 C, which might represent a challenge for certain conditions [11]. Sodium-sulfur batteries require rigorous safety measures, as they contain hazardous components, such as metallic sodium, which is combustible when combined with water [11]. There is a large-scale project is in Rokkasho village, Japan (34 MW), and there are a number of commercially available products such as a 50 kW NaS battery systems that can discharge for 7 h at rated power [15,21]. When NaS batteries are used for short-term applications, the power can reach five times the rated power. These devices have a round trip efficiency of 75%, high energy density, low maintenance, 99% recyclability, and low self-discharge [21,22]. Their lifetime is projected to be 15 years and 4500 cycles [11,22].
30.3.6
Pumped hydro energy storage
Pumped hydro energy storage (PHES) is among the most mature, flexible, and efficient forms of large-scale energy storage [16,17]. The technology works by pumping water from low-altitude reservoirs to upper reservoirs to exploit the gravitational potential energy of the water [21]. The discharging cycle releases the water from the high-altitude reservoir and extracts energy through a hydroelectric turbine. PHES can be used for various grid-connected applications, but operating reserve, capacity provision, and peak demand reduction are the most common [16,26]. PHS can also participate in black start, following a system shutdown [33]. The expected lifetime of PHES is between 30 and 50 years, although this time can be exceeded [12,15]. It presents a round trip efficiency of between 75% and 82%, a relatively short-reaction
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time and rapid ramp rates (3000 MW/min) [12,15,17]. However, the system takes time to switch between charging and discharging modes due to the turbine’s significant inertia and hydrodynamics. The main drawbacks of this energy storage technology are the large initial costs of investment, potential negative impacts on the local environment, low-energy and power densities (large space required), and limited available sites [16].
30.3.7
Compressed air energy storage (CAES)
In compressed air energy storage (CAES), energy is stored in the form of high-pressure compressed air, which is then used to generate electricity via a turbine [24]. Globally, there are a handful of installations, with power capacities varying from 80 kW to 321 MW (at McIntosh CAES plant in the United States). CAES typically has capital costs varying from $400 to $800 (kW)1, a cycle efficiency of 40%e60%, and a lifetime of 20e40 years [24]. Adiabatic CAES offers increased cycle efficiency (50%e70%), but with capital costs closer to $1000 (kW)1 [25]. An extension of this approach is to use liquid air energy storage (LAES), which uses liquefied air or nitrogen as a storage medium [35]. LAES offers round trip efficiencies of 50%e60%, but this can be significantly improved if waste heat is available. Liquid air can be stored in a tank, so it can be deployed on many more sites than CAES.
30.3.8
Thermal energy storage (TES)
Thermal energy storage (TES) comprises a collection of technologies that store energy in thermal form (heat or cold) either directly or indirectly through energy conversion processes. Grid-scale TES technologies include cryogenic energy storage [36] and pumped thermal electricity storage [37]. TES currently accounts for approximately 55% of global nonpumped hydro installations [13], and its installed power capacities vary from 5 kW to 360 MW at Pedro de Valdivia CSP power plant. The existence of gridintegrated systems makes it attractive for wholesale market services coupled with its overall system efficiency and high energy density. TES is the least cost energy storage technology, with sensible thermal energy storage at <5 £ (kWh)1 [39]. Other classes in its family are latent heat storage generally <50 £ (kWh) 1) and the most expensive thermochemical energy storage (>100 £ (kWh)1) [40]. TES technologies have response times of a few minutes to tens of minutes and are therefore suited for energy- rather than power- led applications.
30.3.9
Nickel-based batteries
In nickel-based batteries, nickel is used as the anode and a variety of materials as the cathode. This gives different classes of nickel-based batteries, namely nickel cadmium (NiCd), nickel metal hydride (NiMH), and nickel iron (NiFe). Most applicable for grid energy storage are NiFe [13] due to abundance of materials enabling manufacture at
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relatively low cost. It is also more environmentally friendly than NiCd, with long cycle life; however, their efficiency is currently low [41]. These batteries were successfully commercialized in the 20th century, but new developments received little attention due to low-cost lead acid batteries. There is now renewed interest, and this technology has the potential to provide a cost-effective solution for large-scale energy storage.
30.3.10
Flywheel
Flywheels store kinetic energy in a rotating disk and were among the first commercialized storage technologies to be used in electric power systems. The defining characteristic of this technology is its high-power and low-energy density. This makes it suitable for short-term applications in the ancillary services markets. Flywheel energy storage also has a fast response and can deliver rated power within one second, enabling participation in services that require fast response. This technology has a low environmental impact [42], a long lifetime, and high round trip efficiency (approximately 85%). A number installations exist globally with installed rated power capacity varying from 25 kW to 400 MW at the EFDA Jet Fusion Flywheel. The disadvantage of flywheel storage is the high capital cost of energy ($5000 (kWh)1) and a self-discharge rate as high as 20% of stored energy per hour [44].
30.3.11
Hybridization of energy storage systems
A hybrid energy storage system (HESS) refers to the combination of multiple energy storage technologies with the aim of exploiting their individual advantages and mitigating their drawbacks [45]. The most common configuration in the literature merges high-power, fast-response devices with high-capacity technologies to address one or more services [46]. However, the criteria for selecting hybrid technologies can also account for a number of additional characteristics, such as individual response time, cycle efficiency, cycle lifetime, self-discharge rate, initial investment costs, operation and maintenance costs, location, and potential revenue streams [12,46,47]. As the capital cost of investment required for hybridizing a system might be higher than for a single-energy storage technology, a number of approaches, such as active or passive coupling architecture [48], control techniques, or relative sizing methodologies can be considered to maximize the technical and economic benefits of hybridization [12,19,38]. The optimal sizing of HESS is a planning process to determine the power and energy ratings of each storage device by allocating their cost of power (e.g., $ MW1) and cost of energy ($ (MWh)1) in the most efficient and useful way according to the system’s objectives [49e51]. Table 30.1 presents some of the most pertinent characteristics of individual energy storage technologies while a monetarized mapping scheme between grid services and storage technologies is displayed in Table 30.2. This can be used to visualize the economic impact of using a specific technology for different services in terms of initial costs
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of investment. The annualized capital costs of these values helps to further analyze the value of installing different devices considering their expected lifetime duration. This analysis can be achieved through the capital recovery factor that considers the annual discount rate, i, and the lifetime of each device, LT [49]. CRF ¼
ð1 þ iÞLT $ i ð1 þ iÞLT 1
(30.1)
These annualized costs using Eq. (30.1) are presented in Table 30.3, considering a 6% discount rate and the expected lifetime from Table 30.1. The costs can be interpreted as a constant annuity to be spent for acquiring an energy storage technology for the provision of specific services throughout the lifetime of the device. As example, according to Table 30.2, the lithium-ion batteries can be considered as a potential technology for providing peak shaving services. However, by annualizing the costs of investment, Table 30.3 suggests that pumped hydro storage and CAES might be more suitable for this job due to their large number of years of service. In this context, if the investment aims to analyze the short-term impact, Table 30.2 might provide a clearer picture, while Table 30.3 can be more useful for long-term economic analysis. For a hybrid case, however, a combination of technologies can be initially established by these tables, but further analyses are required depending on the technologies and services required.
30.4 Power conversion and control systems The majority of energy storage media produce DC power and must be coupled to the AC power network via a power conversion system (PCS). In most cases, these systems
Table 30.2 Capital costs of investment mapping: grid serviceseenergy storage technologies.
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Table 30.3 Annualized capital costs of investment mapping: grid serviceseenergy storage technologies.
incorporate various levels of control to ensure the safe, efficient, reliable operation of the energy storage systems (ESSs). These subsystems are described in this section.
30.4.1
Power conversion for energy storage systems
Power electronic conversion units serve as a key enabling technology in the continued growth of grid-scale energy storage. Currently, 30% of all electric power generated uses power electronics technologies somewhere between the point of generation and end use [52,53], and this is expected to increase in the future. In this section, we briefly discuss some technical and commercial considerations for the selection of PCS for battery ESSs and the limitations for applications at different power scales. PCS comes in many forms, and selecting the correct PCS technology and topology depends on a number of factors: 1. The power rating at the battery DC terminals, including the voltage and current rating. Selection of the battery cells/stacks should be based on this. For example, higher voltages are often preferred, as this allows the use of cheaper devices but requires stacking of more cells. 2. The power efficiency of the inverter within the operating range of the storage technology terminal characteristics. This is typically between 95% and 99% for commercially available inverters [54,55]. 3. The battery management system (BMS): The BMS operates down to a cell level to ensure that safe electrical and environmental (principally temperature) operation is maintained at all times. In large (MW-scale) battery systems, many thousands of individual cells need to be continuously monitored on an individual basis [56]. The control modes, for example, grid-connected, islanded, and antiislanding and uninterruptible power supply, can also be included within the BMS.
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4. Multiple functionality: A HESS will require more flexibility on the battery side converter, while a storage system fulfilling multiple applications [57] will require more flexibility on the grid-side converter (for example, to meet both P and Q requirements simultaneously and to operate on different timescales). 5. The communication interface: This is crucial for sending set points and commands to inverters and is usually either though Modbus, Canbus, Ethernet, or a combination. 6. Commercial applications: Inverters at distribution scale are mostly PV inverters, some options such as string inverters connect multiple inverters together. Others include central inverters, battery inverters, transformer, and transformerless inverters [54].
30.4.1.1 Power electronics devices for PCS The future of PCS for BESS will rely on affordable power electronic devices that can deliver high-power densities. Recent advances in research have yielded gallium nitride (GaN) [58] and silicon carbide (SiC) [59] devices, which are at the forefront of making this possible. An example is the ARPAVE ADEPT (Washington, DC, USA) program with HRL Laboratories (Malibu, CA, USA) [53,60]. This converter will utilize GaN devices, offering high speed and efficient performance. Improved efficiency and faster switching (increased modulation range) have been a critical motivation for the use of GaN and SiC devices.
30.4.1.2 Single stage converters A single-stage convertor comprises a bidirectional AC/DC converter that facilitates the transfer of energy between the DC energy storage medium and the AC electrical network, as shown in Fig. 30.5 [61]. A variety of topologies exist, including single- and three-phase H-bridge designs [62] and those based on other technologies, such as buck [63] or bidirectional matrix [64] converters. The main advantages of single-stage converters are the low cost, low device count, and reduced losses. However, they present major disadvantages, particularly in terms of reliability; because the storage medium must interface to a single DC connection, a single cell failure will result in a system failure and the need to bypass or replace the failed cell. There is also a limitation in the magnitudes of voltages that can be accommodated [61].
30.4.1.3 Double-stage converters A double-stage converteredas illustrated in Fig. 30.6ecomprises an AC/DC converter to interface with the wider network, and a DC/DC converter, which connects to the storage medium [61]. There are several DC/DC converter topologies, but the most common is the bidirectional half-bridge [65], which consists of two transistors and one inductor. Its popularity is due to its simplicity combined with a reasonable efficiency (>90%) [66]. A significant advantage of the double-stage converter is that it allows
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FIGURE 30.5 The general topology of a single-stage converter.
multiple DC/DC converters to connect to a single DC bus; this allows the storage medium to be divided into multiple series stacks, which increases the system’s fault tolerance [61], and could act as an enabler for hybrid energy storage. However, the disadvantages include additional complexity and potentially lower efficiency due to the additional converter stage.
30.4.1.4 Multilevel converters A multilevel converter is designed to deliver a desired AC voltage resulting from multiple DC converter stages. A number of multilevel structures exist, including the cascaded Hbridge converter (CHB) [67]; neutral point clamped converters; flying capacitor multilevel inverters (FC) [68]; and modular multilevel converters (MMC), which are based on a combination of CHB and FC topologies. Multilevel converters have several advantages, particularly the CHB and MMC configurations, whose modular structures allow reduced manufacturing costs. The redundant levels can increase reliability, and the multiple stages increase the power quality at the AC terminals [61]. However, the high number of switches leads to higher costs than simpler converter topologies.
30.4.1.5 Price comparison of PCS technology providers The market for inverters has been expanding over recent years with the increase in solar capacity in the grid. The key technology providers in the market include SMA, Victron, Huawei, ABB, SolarEdge, and Sungrow. Of these providers, SMA is the world’s largest supplier with a market share of 14% [69]; but with increased competition from Huawei, SolarEdge, and Sungrow, this has been declining in recent years. To investigate further, we have undertaken some study of retail price comparisons of three of these companies, SMA, Victron, and SolarEdge, from renewable energy distributors and providers Wind & Sun [70]. Fig. 30.7 shows this comparison of 75 battery inverter and solar PV inverter products between these companies. The prices are shown
FIGURE 30.6 The general topology of a double-stage converter.
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FIGURE 30.7 Dollars per kilowatt, $ (kW)1, retail prices of three inverter suppliers.
to reflect of the price per kW and give a picture of how this relates at different power scales. Fig. 30.7 shows that the price range of inverters vary between the $150 (kW)1 and $800 (kW)1 within the power ranges of 1e60 kW. The trend of the moving average of prices is also shown to decay exponentially as power is scaled up. This can be explained as the cost of devices and components in the buildup does not increase linearly with power. For power ratings above 60 kW, these would not be off-the-shelf retail products, and prices would need to be quoted on a case-by-case basis.
30.4.2
Control of energy storage systems
Deploying ESSs to fulfill network service requirements results in unique control challenges on a variety of timescales. Because an ESS has a finite energy capacity, its SoC must be managed to ensure that contracted services can be delivered. The charging and discharging of the asset may be constrained by other service contracts or local network limitations. This leads to the requirement of a forecasting and scheduling system [57] to optimize the system’s operation on a timescale of days to hours. Once a network service is required, a real-time local or distributed [71] control system is required to ensure that the ESS delivers the mandated levels of real and reactive power to fulfill the service obligations. In some cases, these may require modeling of the local network [72], in other cases, it could be sufficient to follow an agreed response profile to a single, local variable. The inputs and interactions between these controllers are illustrated in Fig. 30.8.
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FIGURE 30.8 The inputs and interactions between the controllers of an ESS.
In addition to this, an ESS is a complex system, comprising a number of subsystems to deal with energy conversion and storage [73]; each of these subsystems will typically comprise many components, for example, the storage medium for a grid-scale ESS could contain many thousands of battery cells. BMS is needed to coordinate the operation of these subsystems to ensure the system’s efficiency, reliability, and longevity [74,75]. The most advanced BMS can incorporate physics-based models of the storage medium, enabling online performance management to improve the lifetime and efficiency of the ESS [75]. Finally, many ancillary services may have strict monitoring and control requirements to ensure full remuneration. Therefore, if an ESS is intended to participate in multiple services throughout its lifetime [76], a fast, flexible, and low-level control system is essential.
References [1] Committee on Climate Change, An Independent Assessment of the UK’s Clean Growth Strategy: From Ambition to Action, 2018. [2] P. Gardner, UK Generation and Demand Scenarios for 2030, Garrad Hassan & Partners Ltd, Glasgow, 2011. [3] P. Ekins, I. Keppo, J. Skea, N. Strachan, W. Usher, G. Anandarajah, The UK Energy System in 2050: Comparing Low-Carbon, Resilient Scenarios, 2013. [4] HM Government, The UK Renewable Energy Strategy, The Stationary Office, London, 2009. [5] E. Department, For Business, and Industrial Strategy, 2018. Energy Trends: renewables. Available: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/ file/743591/Renewables.pdf.
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[6] A.P. Reiman, T.E. McDermott, G.F. Reed, B. Enayati, Guidelines for high penetration of singlephase PV on power distribution systems, in: Power & Energy Society General Meeting, IEEE, 2015, pp. 1e5. [7] D.R. Drew, D.J. Cannon, J.F. Barlow, P.J. Coker, T.H.A. Frame, The importance of forecasting regional wind power ramping: a case study for the UK, Renewable Energy 114 (2017) 1201e1208. [8] E., Department for business, and industrial Strategy, Contracts for Difference (CFD) Second Allocation Round Results, 2017. [9] P. Zhou, R.Y. Jin, L.W. Fan, Reliability and economic evaluation of power system with renewables: a review, Renewable and Sustainable Energy Reviews 58 (2016) 537e547. [10] P. Heptonstall, R. Gross, F. Steiner, The Costs and Impacts of Intermittencye2016 Update, UK Energy Research Centre, London Google Scholar, 2017. [11] A.A. Akhil, G. Huff, A.B. Currier, B.C. Kaun, D.M. Rastler, S.B. Chen, et al., DOE/EPRI 2013 Electricity Storage Handbook in Collaboration with NRECA, Sandia National Laboratories, Albuquerque, NM, 2013. [12] T. Bocklisch, Hybrid energy storage approach for renewable energy applications, Journal of Energy Storage 8 (2016) 311e319. [13] N.P. Brandon, J.S. Edge, M. Aunedi, E.R. Barbour, P.G. Bruce, B.K. Chakrabarti, et al., UK Research Needs in Grid Scale Energy Storage Technologies, Energy SuperStore2016, 2016. [14] P. Alotto, M. Guarnieri, F. Moro, Redox flow batteries for the storage of renewable energy: a review, Renewable and Sustainable Energy Reviews 29 (2014) 325e335. [15] V. Viswanathan, M. Kintner-Meyer, P. Balducci, C. Jin, National Assessment of Energy Storage for Grid Balancing and Arbitrage Phase II Volume 2: Cost and Performance Characterization, Report PNNL-21388, Pacific Northwest National Laboratory, Richland, WA, 2013. [16] R. Carnegie, D. Gotham, D. Nderitu, P.V. Preckel, Utility Scale Energy Storage Systems, Benefits, Application, and Technologies, 2013 by State Utility Forecasting Group, June 2013, Posted at, https://www.purdue.edu/discoverypark/energy/assets/pdfs/SUFG/publications/SUFG%20Ener gy %20Storage%20Report.pdf. [17] J.M. Durant, M.J. Duarte, P. Clerens, European Energy Storage Technology Development Roadmap towards 2030, European Association for Storage of Energy (EASE), European Energy Research Alliance (EERA), 2013. [18] A. Lahea¨a¨r, P. Przygocki, Q. Abbas, F. Be´guin, Appropriate methods for evaluating the efficiency and capacitive behavior of different types of supercapacitors, Electrochemistry Communications 60 (2015) 21e25, 2015/11/01. [19] H. Chen, T.N. Cong, W. Yang, C. Tan, Y. Li, Y. Ding, Progress in electrical energy storage system: a critical review, Progress in Natural Science 19 (2009) 291e312. [20] I. Hadjipaschalis, A. Poullikkas, V. Efthimiou, Overview of current and future energy storage technologies for electric power applications, Renewable and Sustainable Energy Reviews 13 (2009) 1513e1522. [21] F. Dı´az-Gonza´lez, A. Sumper, O. Gomis-Bellmunt, R. Villafa´fila-Robles, A review of energy storage technologies for wind power applications, Renewable and Sustainable Energy Reviews 16 (5//2012) 2154e2171. [22] D.M. Rastler, Electricity Energy Storage Technology Options: A White Paper Primer on Applications, Costs and Benefits, Electric Power Research Institute, 2010. [23] S. Schoenung, Energy storage systems cost update a study for the DOE energy storage systems program (Report SAND2011-2730), in: New Mexico and California: Sandia National Laboratories, 2011. Retrieved from: http://prod.sandia.gov/techlib/accesscontrol.cgi/2011/112730.pdf.
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[24] H. Chen, X. Zhang, J. Liu, C. Tan, Compressed air energy storage, in: Energy Storage-Technologies and Applications, InTech, 2013. [25] D. Wolf, M. Budt, LTA-CAES e a low-temperature approach to adiabatic compressed air energy storage, Applied Energy 125 (2014) 158e164, 2014/07/15. [26] V.A. Boicea, Energy storage technologies: the past and the present, Proceedings of the IEEE 102 (2014) 1777e1794. [27] G. Koshimizu, T. Numata, K. Yoshimoto, H. Hasuike, T. Shibata, Subaru Project: Analysis of Field Test Results for Stabilization of 30.6 MW Wind Farm with Energy Storage, Electrical Energy Storage Applications and Technologies, 2007. [28] E.-D. Epri, Handbook of Energy Storage for Transmission and Distribution Applications, EPRI & US Department of Energy, Palo Alto, CA, 2003. [29] T. Tevi, A. Takshi, Modeling and simulation study of the self-discharge in supercapacitors in presence of a blocking layer, Journal of Power Sources 273 (2015) 857e862, 2015/01/01. [30] T. Tevi, H. Yaghoubi, J. Wang, A. Takshi, Application of poly (p-phenylene oxide) as blocking layer to reduce self-discharge in supercapacitors, Journal of Power Sources 241 (2013) 589e596, 2013/11/01. [31] A.B. Cultura, Z.M. Salameh, Performance evaluation of a supercapacitor module for energy storage applications, in: IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008, pp. 1e7. [32] Deleted in review. ´ . Gallacho´ir, E. McKeogh, Techno-economic review of existing and new pumped [33] J.P. Deane, B.O hydro energy storage plant, Renewable and Sustainable Energy Reviews 14 (2010) 1293e1302. [34] Deleted in review. [35] Y. Ding, L. Tong, P. Zhang, Y. Li, J. Radcliffe, L. Wang, Liquid air energy storage, in: Storing Energy: With Special Reference to Renewable Energy Sources, vol. 167, 2016. [36] Y. Li, Cryogen Based Energy Storage: Process Modelling and Optimisation, The University of Leeds, 2011. [37] A. White, G. Parks, C.N. Markides, Thermodynamic analysis of pumped thermal electricity storage, Applied Thermal Engineering 53 (2013) 291e298. [38] Deleted in review. [39] Y. Tian, C.Y. Zhao, A review of solar collectors and thermal energy storage in solar thermal applications, Applied Energy 104 (2013) 538e553, 2013/04/01. [40] A. Gil, M. Medrano, I. Martorell, A. La´zaro, P. Dolado, B. Zalba, et al., State of the art on high temperature thermal energy storage for power generation. Part 1dconcepts, materials and modellization, Renewable and Sustainable Energy Reviews 14 (2010) 31e55, 2010/01/01. [41] J.O.G. Posada, A.J.R. Rennie, S.P. Villar, V.L. Martins, J. Marinaccio, A. Barnes, et al., Aqueous batteries as grid scale energy storage solutions, Renewable and Sustainable Energy Reviews 68 (2017) 1174e1182. Part 2. [42] B. Bolund, H. Bernhoff, M. Leijon, Flywheel energy and power storage systems, Renewable and Sustainable Energy Reviews 11 (2//2007) 235e258. [43] Deleted in review. [44] X. Luo, J. Wang, M. Dooner, J. Clarke, Overview of current development in electrical energy storage technologies and the application potential in power system operation, Applied Energy 137 (2015) 511e536, 2015/01/01. [45] G. Wang, M. Ciobotaru, V.G. Agelidis, Power smoothing of large solar PV plant using hybrid energy storage, IEEE Transactions on Sustainable Energy 5 (2014) 834e842.
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[46] L.W. Chong, Y.W. Wong, R.K. Rajkumar, R.K. Rajkumar, D. Isa, Hybrid energy storage systems and control strategies for stand-alone renewable energy power systems, Renewable and Sustainable Energy Reviews 66 (2016) 174e189. [47] N. Mendis, K.M. Muttaqi, S. Perera, Management of low-and high-frequency power components in demand-generation fluctuations of a DFIG-based wind-dominated RAPS system using hybrid energy storage, IEEE Transactions on Industry Applications 50 (2014) 2258e2268. [48] T. Ma, H. Yang, L. Lu, Development of hybrid batteryesupercapacitor energy storage for remote area renewable energy systems, Applied Energy 153 (2015) 56e62, 2015/09/01. [49] S. Munoz-Vaca, C. Patsios, P. Taylor, Enhancing Frequency Response of Wind Farms Using Hybrid Energy Storage Systems, 2016. [50] A. Abbassi, M.A. Dami, M. Jemli, A statistical approach for hybrid energy storage system sizing based on capacity distributions in an autonomous PV/Wind power generation system, Renewable Energy 103 (2017) 81e93. [51] Q. Jiang, H. Hong, Wavelet-based capacity configuration and coordinated control of hybrid energy storage system for smoothing out wind power fluctuations, IEEE Transactions on Power Systems 28 (2013) 1363e1372. [52] L.M. Tolbert, T.J. King, B. Ozpineci, J.B. Campbell, G. Muralidharan, D.T. Rizy, et al., Power electronics for distributed energy systems and transmission and distribution applications 8, 2005. ORNL/TM-2005/230, UT-Battelle, LLC, Oak Ridge National Laboratory. [53] B.M. Grainger, G.F. Reed, A.R. Sparacino, P.T. Lewis, Power electronics for grid-scale energy storage, Proceedings of the IEEE 102 (2014) 1000e1013. [54] Ingeteam, INGECON SUN “Solar Energy Solutions Product Catalougue”, 2016, National Renewable Energy Centre (CENER), Ingeteam, Ciudad de la Innovacio´n, n 7, 31621 Sarriguren (Navarra), Spain. [55] SMA, Sunny Central Storage “Inverter for Large Scale Battery Storage Systems”, 2016. [56] H. Rahimi-Eichi, U. Ojha, F. Baronti, M.-Y. Chow, Battery management system: an overview of its application in the smart grid and electric vehicles, IEEE Industrial Electronics Magazine 7 (2013) 4e16. [57] D. Greenwood, N. Wade, P. Papadopoulos, N. Heyward, P. Mehtah, P. Taylor, Scheduling power and energy resources on the smarter network storage project, in: Presented at the 23rd Int. Conf. and Exhibition on Electricity Distribution, Lyon, France, 2015. [58] M.A. Khan, G. Simin, S.G. Pytel, A. Monti, E. Santi, J.L. Hudgins, New developments in Gallium Nitride and the impact on power electronics, in: IEEE 36th Power Electronics Specialists Conference, 2005, 2005, pp. 15e26. [59] J. Rabkowski, D. Peftitsis, H.P. Nee, Silicon carbide power transistors: a new era in power electronics is initiated, IEEE Industrial Electronics Magazine 6 (2012) 17e26. [60] L. Xue, Z. Shen, M. Mu, D. Boroyevich, R. Burgos, B. Hughes, et al., Bi-directional PHEV battery charger based on normally-off GaN-on-Si multi-chip module, in: Applied Power Electronics Conference and Exposition (APEC), 2014 Twenty-Ninth Annual IEEE, 2014, pp. 1662e1668. [61] V. Ferna˜o Pires, E. Romero-Cadaval, D. Vinnikov, I. Roasto, J.F. Martins, Power converter interfaces for electrochemical energy storage systems e a review, Energy Conversion and Management 86 (2014) 453e475, 2014/10/01. [62] B. Singh, B.N. Singh, A. Chandra, K. Al-Haddad, A. Pandey, D.P. Kothari, A review of single-phase improved power quality AC-DC converters, IEEE Transactions on Industrial Electronics 50 (2003) 962e981. [63] Z. Yao, L. Xiao, Y. Yan, Control Strategy for series and parallel output dual-buck half bridge inverters based on DSP control, IEEE Transactions on Power Electronics 24 (2009) 434e444.
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[64] J.D. Zhu, Z. Xu, B.H. Jiang, C.H. Zhang, Close-loop control of an AC-DC matrix converter for automotives, in: Electrical Power and Energy Conference (EPEC), 2011, IEEE, 2011, pp. 426e431. [65] X. Fei, R. Yu, W. Yu, A.Q. Huang, D. Yu, A novel bi-directional DC-DC converter for distributed energy storage device, in: IEEE Applied Power Electronics Conference and Exposition (APEC), 2015, 2015, pp. 1126e1130. [66] R.M. Schupbach, J.C. Balda, Comparing DC-DC converters for power management in hybrid electric vehicles, in: Electric Machines and Drives Conference, 2003. IEMDC’03, IEEE International, 2003, pp. 1369e1374. [67] L. Tarisciotti, P. Zanchetta, A. Watson, S. Bifaretti, J.C. Clare, P.W. Wheeler, Active DC voltage balancing PWM technique for high-power cascaded multilevel converters, IEEE Transactions on Industrial Electronics 61 (2014) 6157e6167. [68] M. Narimani, V. Yaramasu, B. Wu, N.R. Zargari, A new simplified approach for capacitor voltage balancing of flying capacitor multilevel converters using space vector modulation, in: 16th European Conference on Power Electronics and Applications, 2014, 2014, pp. 1e9. [69] IHS, SMA Retains Top Ranking in Global PV Inverter Market, but Competitors Are Gaining, IHS Says, 2016. Available: http://news.ihsmarkit.com/press-release/technology/sma-retains-topranking-global-pv-inverter-market-competitors-are-gaining-i. [70] Wind and Sun, Inverter Catalogue, 2017. Available: http://www.windandsun.co.uk/products/ Inverters#.WSQtP4MrKUl. [71] M. Zeraati, M.E.H. Golshan, J. Guerrero, Distributed control of battery energy storage systems for voltage regulation in distribution networks with high PV penetration, IEEE Transactions on Smart Grid (2016), 1-1. [72] Y. Xu, J. Hu, W. Gu, W. Su, W. Liu, Real-time distributed control of battery energy storage systems for security constrained DC-OPF, IEEE Transactions on Smart Grid (2017), 1-1. [73] E. Chatzinikolaou, D.J. Rogers, A comparison of grid-connected battery energy storage system designs, IEEE Transactions on Power Electronics 32 (9) (2016) 6913e6923. [74] L. Lu, X. Han, J. Li, J. Hua, M. Ouyang, A review on the key issues for lithium-ion battery management in electric vehicles, Journal of Power Sources 226 (2013) 272e288. [75] M.T. Lawder, B. Suthar, P.W.C. Northrop, S. De, C.M. Hoff, O. Leitermann, et al., Battery energy storage system (BESS) and battery management system (BMS) for grid-scale applications, in: Proceedings of the IEEE, vol. 102, 2014, pp. 1014e1030. [76] R. Moreno, R. Moreira, G. Strbac, A MILP model for optimising multi-service portfolios of distributed energy storage, Applied Energy 137 (2015) 554e566.
Further reading [1] B. Diouf, R. Pode, Potential of lithium-ion batteries in renewable energy, Renewable Energy 76 (2015) 375e380.
30.1 The low-carbon transition of electricity networks The global challenge to reduce carbon emissions continues to be a thorny issue for governments worldwide. In the United Kingdom, the 2008 Climate Change Act has required the development of carbon budgets, consistent with an 80% reduction by 2050, although recent concern has been raised regarding the risk of under delivery [1]. While the current 80% by 2050 target is a major driver for electricity sector transformation, pressures for more rapid decarbonization may yet result from the Committee on Climate Change’s analysis of the Paris agreement [1]. Studies identify the electricity sector as a key sector to help achieve the interim target with relatively low cost and low uncertainty [2]. For many electricity networks, decarbonization poses multiple problems. There is the issue of increasing demand for electricity, particularly if heat and transport demand shifts with respect to primary energy source, from liquid and gas fossil fuels to electricity. Within that picture of growing demand is the complexity of growth in peak power and growth in annual energy. To meet that demand, using lower and zero carbon sources of electricity generation means a consequential growth in the use of renewable energy technologies. The available options to decarbonize the electricity sector in the United Kingdom are nuclear power, large-scale renewables, fossil fuel power stations with carbon capture and sequestration (not yet a mature technology), and small-scale renewables [3]. The EU Renewable Energy Directive required the United Kingdom to reach agreed targets by 2020 of 15% of the overall share of energy from renewable sources, which
Future Energy. https://doi.org/10.1016/B978-0-08-102886-5.00030-X Copyright © 2020 Elsevier Ltd. All rights reserved.
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resulted in the UK Government publication of the Renewable Energy Strategy [4], which set an aspirational (nonbinding) target that more than 30% of UK electricity consumption would be generated from renewables in 2020. In June 2018, the contribution of renewables to electricity generation reached 31.7% [5]. Growth in photovoltaic (PV) and wind turbine installations has driven this rapid increase in generation from renewables, up from just 5.5% in 2009. Onshore wind and solar PV together represented around 31% of all renewable capacity, the highest share of renewable technologies. This was followed by offshore wind at 19%, by June 2018. The fall in price of solar PV systems over the last decade [6] and government subsidies have resulted in an increased number of solar PV systems with cumulative installed PV capacity in the United Kingdom reaching 13 GW by mid-2018 [5].The total installed wind capacity by mid-2018 was 21 GW in the United Kingdom [5], driven by falling costs of onshore and offshore wind turbine technology, as well as offshore development driven by the Crown Estate [7]. There are a number of financial support mechanisms in place which enable, and have supported the recent growth of, renewable energy for electricity generation in the United Kingdom: renewables obligation, feed-in tariff, and contracts for difference (CfD). The CfD second round strike price for offshore wind was £74.75 (MWh)1 and £57.50 (MWh)1 [8], lower than the £92.50 (MWh)1 agreed for the new Hinkley nuclear power station. The operational management complexity of intermittent and stochastic generation and demand has been expressed by several authors [9,10].Balancing supply and demand in real time on the electricity network is required to maintain quality of supply. The quality of supply for an electricity network is ensured by managing and mitigating disturbances such as voltage dips, voltage surges, overvoltage, harmonics, power frequency variations, voltage fluctuations, rapid voltage change, voltage imbalance, short- and long-voltage interruptions, and under voltage and transients. Intermittency of some generation sources can be managed through flexibility in other generation technologies, storage, and flexibility (or control) in energy demand. In the remainder of this chapter, we look at the management of electricity networks to enable the connection and generation of large volumes of renewable energy technologies, particularly those impacting on low-voltage (LV) networks.
30.2 Managing intermittency of PV through storage Expansion of PV generation is increasing the challenge for network operators to keep voltages within operational limits. Voltage rise occurs in LV networks when distributed generators export, particularly at times of low demand. However, there is little work quantifying the scale of voltage issues and subsequently potential solutions across large numbers of real networks. In a recent study, we investigated the potential for storage, in combination with PV, to reduce the incidence of overvoltage in LV networks. We considered (1) installation by homeowners and commercial customers for increased self-consumption and (2)
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11kV
a
400V
MV network
b Secondary transformer
Residential rooftop PV
FIGURE 30.1 Locations for LV storage showing (A) storage in homes owned by customers and (B) storage located on the street.
installation directly onto the grid by electricity distribution network operators (DNO) to manage network power flow (Fig. 30.1). We assessed the impact of multiple PV dispersion levels, pn, on the voltage regulation in multiple LV networks and the subsequent effect of energy storage randomly installed in customer homes with dispersion qn or sited by DNOs to manage overvoltage. Load flow was implemented in Matlab using OpenDSS network models. For the domestic installation study, storage was assumed for each home with PV with a probability qn. A load flow was then used to calculate the voltage rise. If there is overvoltage, this is recorded. Storage was represented as a load charging to absorb excess PV with rating PES. For the DNO installation study, a genetic algorithm was used from the Matlab Global Optimisation Toolbox, which identified the locations of storage in network, n, to prevent overvoltage with fewest storage units in the network. Without storage, and for three PV penetration scenarios, we investigate projected PV dispersion levels, pn, in each network n to identify the number of feeders forecast to experience overvoltage (total number of feeders investigated: 43,816), as shown in Fig. 30.2. We then investigated a number of domestic storage adoption scenarios, which are shown for the medium PV integration scenario in Fig. 30.3. Randomly located storage
FIGURE 30.2 Number of problematic feeders under different PV growth scenarios.
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FIGURE 30.3 Amount of storage installed, according to a medium PV scenario, with storage randomly located in different percentages of homes and storage located by the DNO.
does reduce the number of feeders with overvoltage (from 1250 in year 35 with no storage to 1150 with 5% and 1000 with 15% PV with storage). DNO sited storage is, by nature of the algorithm, able to solve overvoltage. It does so with reduced total installed storage capacity compared with the domestic installations (Fig. 30.3). Finally, we considered the costs of each approach. We assumed problematic feeders were upgraded to cope with overvoltage, by multiplying the length of each problematic feeder by a reconductoring cost (£80 m1). The storage was assumed to be lithium-ion batteries, which represented the most widely deployed battery type in residential power networks. Prices of these have fallen significantly in recent years, and representative battery costs were sourced through an industrial survey as well as literature search. Energy storage located by the DNO is cheaper than all other options, for the DNO, as shown in Fig. 30.4. The results of this work showed that, if storage is used along side PV as a means to reduce overvoltage in LV networks, it should be carefully located by the DNO within an LV network using a heuristic method to minimize a DNO’s overall cost. Storage may still offer benefits to homeowners if located in domestic homes, and domestic installation does have a benefit to DNOs in reducing overall reinforcement costs. However, it is found that storage in homes will not prevent all overvoltage because the location of the storage in networks is not optimized for overvoltage reduction in this case.
30.3 Energy storage technologies There is a wide variety of energy storage technologies that could be deployed to fulfill applications within electrical networks. These technologies have been reviewed by numerous other authors, but the goal of this chapter is to summarize and curate that information in such a way that it can be used by technology developers, aggregators, and power system operators when considering the design of new energy storage technologies
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FIGURE 30.4 Total reinforcement cost for the DNOs to reconductor despite storage in homes or cost of storage located by the DNO, high-PV scenario.
or power network services. In this section, we briefly describe each technology and provide a summary of the relevant information for use by energy storage developers, network and system operators, and regulators. The key parameters for each technology are presented in Table 30.1.
30.3.1
Vanadium redox Flow Batteries
Flow batteries are an energy storage technology in which liquid electrolytes are stored in tanks and pumped into cells to produce electrochemical reactions [21,26]. The vanadium redox flow battery is a technology characterized by the redox reactions of different ionic forms of vanadium [11]. As the electrolyte tanks and power stacks are separated, the energy capacity of these batteries can be increased or reduced based on the tanks’ volume, while the power capacity depends on the number of cells in the power stacks. This flexible decoupling of power and energy (from kW and kWh to larger scales of MW and MWh [15]) makes this technology attractive for grid-scale energy applications [13]. For grid-scale applications, this type of battery has a number of strengths attached: long lifetime, low sensitivity to high depths of discharge, low self-discharge, and power and energy independence. The long lifetime of this device is achieved through the nondegradation of its electrolyte through time. This condition makes the cell stack the most likely component to determine battery life duration (more than 10 years with over 10,000 charge/discharge cycles at very high depths of discharge) [11,13,26]. Another
Cost of energya ($/kWh)
Cost of powera ($/kW)
318e880 [11,12]
1000e2133 Around 50 [12] [13] 159e212 [12] 1e30 Wh/kg [13] 159e212 [12] 200e550 [13,19] 159e1994 30e100 [11,12] [12,20] 159e350 100e250 [12,23] Wh/kg [16] 500e2000 0.25e1.5 [12] [17] 500e1750 3e6 [19] [15] 200e300 [19] 80e500 [19]
Supercapacitors 10,600e21,200 [12] Lithium-ion 250e500 [13,19] Lead acid
50e265 [12,20]
Sodium-sulfur
350e742 [12,22]
Pumped hydro
5e75 [12,23]
CAES
3e80 [12,15]
TESb
3e100 or more [13,19] 650 [14]
ZEBRA
Nickelecadmium 400e2400 [20] Flywhee
1000e5000 [17,19]
b
Power density (W/l) 0.15 W/cm2 [13] 100 [13]
Round trip efficiency (%)
Selfdischarge (% per day)
Response time (ms)
Cycle lifetime (100% DoD)
70e85 0.1e0.4 [12] Few [16] Over 10,000 [13] [14,15] 52e96 [18] 10e20 [12] Under 10 [12] Over 100,000 [17] 1000e4000 Over 93 0.1e0.3 [12] 20 [16] 3000e6000 [13] [13] [13] 3e5 [12] 1000e1800 10e500 [12] 63e90 [13] 0.13e0.6 [13] [11,21] 260 W/kg 75 [22,23] Around 10 3e5 [12] 4500 [11,22] [16] [12] 0.5e1.5 [19] 75e82 0.005e0.02 2e10 min [17] Over 13,000 [22] [12,15] [12] 3e12 min Over 10,000 [15] 0.5e2 [19] 40e70 0.5e1 [12] [12,20] [24,25] e 30e72 0.05e1 [19] 2.5 min [13] e [13,19] 3500 [14] 95e120 150 W/kg 85e90 [16] Around 20 [16] 3000 (80% DoD) Wh/kg [14] [19] 15 [19] [16] 500e1500 15e75 50e1000 60e70 [16] 0.2e0.6 [19] e Under 3500 [19] Wh/kg [19,20] W/kg [20] [16,21] 1000e2000 85e95 100 [12,19] 4 [22] Over 100,000 250e350 [19] 20e200 [19] [19,23] [16,17] [12,19]
Conversion rate: £1 ¼ $1.25 and V1 ¼ $1.06. Depending on the thermal technology.
a
Energy density (Wh/l)
Lifetime (years) 10e20 [17] 15 [12] 5e15 [13] 5e15 [21] 15 [11,22] 30e50 [12,15] 20e30 [15] 10e40 [19] e 10e20 [19,20] 15e20 [19,22]
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Specific characteristics of energy storage technologies.
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strength is its low self-discharge characteristic, a consequence of storing electrolytes in separate sealed tanks [21]. This technology can produce an output power higher than its rated capacity as demonstrated in Refs. [27,28] and step from zero to maximum output power in few milliseconds [11]. When the stacks contain electrolyte, the storage system can be used for short duration applications, such as power quality, as the pumping system does not need to be in operation. If the stacks are appropriately designed, balancing and regulation services can be delivered [15]. Energy applications such as arbitrage and load leveling are achieved by storing large volume of electrolytes. However, the system is physically large and has a round trip efficiency between 75% and 85%, depending on electrochemical, shunt current, and pumping losses [13].
30.3.2
Supercapacitors
Supercapacitors store energy as an electrical charge and consist of a porous separator between two conductor electrodes and an electrolyte [13,21]. They can achieve higher energy density than capacitors due to the porous electrodes with high surface area. This technology can reach much higher power rating than batteries with fast charge/ discharge cycles, but it also presents a high self-discharge [21,29,30]. It is attractive for short-term responses such as frequency grid services. Supercapacitors have a long lifetime (i.e., very high number of charge/discharge cycles); their energy efficiency is heavily dependent on their discharge rate [31] and, dependent on construction and voltage, can vary from 52% to 96% [18]; this illustrates the need to design energy storage technologies based on their intended applications. Supercapacitors have a high energy capacity cost in comparison with similar energy storage alternatives [13].
30.3.3
Lead acid batteries
Lead acid batteries are the most mature battery technology, and they initially dominated the world market in small- and medium-scale electrochemical energy storage applications [13,21]. This technology consists of stacked cells submerged into an electrolyte comprising a sulfuric acid [11]. The cells have a lead dioxideepositive electrode and a metallic leadenegative electrode, which together become lead sulfate during the discharge process [13]. There are a number of grid-scale projects using lead acid batteries such as in California (10 MWe14 MWh), Puerto Rico (20 MWe14 MWh), and Germany (8.5 MWe8.5 MWh), among others [13]. Advantages of this technology are its low selfdischarge characteristic (4%e20% per month), safety features, and its well-established recycling process [11,13]. The round trip efficiency of these batteries can range from 63% to 90%, but they have poor cycle life, with only 1000 cycles approximately [13]. This device is also sensitive to high and low ambient temperatures, which can modify its lifetime (5e15 years) [21]. In order to improve the drawbacks, a number of variants are available for this technology: lead acid carbon technology, for example, is a variant of the
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traditional lead acid batteries that improves its power characteristics and reduces its partial state of charge effect [11].
30.3.4
Lithium-ion (Li-ion)
Li-ion batteries consist of a lithiu-based anode and a cathode, typically constructed from graphite or another carbon-based material, separated by an electrolyte that supports the movement of lithium ions during charge and discharge. Power ratings of existing systems vary from 2 kW up to 48 MW at the Gyeongsan Substation in South Korea. The advantages of Li-ion batteries over other battery technologies are high energy density (400e550 Wh L1), high efficiency (>93%), low maintenance costs, and relatively low self-discharge [30]. The capital cost for installation is around $250e$500 (kWh)1.
30.3.5
Sodium-sulfur battery
Sodium-sulfur (NaS) batteries are a promising energy storage technology for a number of applications, particularly those requiring high-power responses [11,21]. It is composed of a sodium-negative electrode, a sulfur cathode, and a beta-alumina solid electrolyte that produces sodium pentasulfide during the discharge reaction [21]. The primary strength of this technology is its long discharge time. It operates at a hightemperature regimen of 300e350 C, which might represent a challenge for certain conditions [11]. Sodium-sulfur batteries require rigorous safety measures, as they contain hazardous components, such as metallic sodium, which is combustible when combined with water [11]. There is a large-scale project is in Rokkasho village, Japan (34 MW), and there are a number of commercially available products such as a 50 kW NaS battery systems that can discharge for 7 h at rated power [15,21]. When NaS batteries are used for short-term applications, the power can reach five times the rated power. These devices have a round trip efficiency of 75%, high energy density, low maintenance, 99% recyclability, and low self-discharge [21,22]. Their lifetime is projected to be 15 years and 4500 cycles [11,22].
30.3.6
Pumped hydro energy storage
Pumped hydro energy storage (PHES) is among the most mature, flexible, and efficient forms of large-scale energy storage [16,17]. The technology works by pumping water from low-altitude reservoirs to upper reservoirs to exploit the gravitational potential energy of the water [21]. The discharging cycle releases the water from the high-altitude reservoir and extracts energy through a hydroelectric turbine. PHES can be used for various grid-connected applications, but operating reserve, capacity provision, and peak demand reduction are the most common [16,26]. PHS can also participate in black start, following a system shutdown [33]. The expected lifetime of PHES is between 30 and 50 years, although this time can be exceeded [12,15]. It presents a round trip efficiency of between 75% and 82%, a relatively short-reaction
Chapter 30 Integration of High Penetrations 657
time and rapid ramp rates (3000 MW/min) [12,15,17]. However, the system takes time to switch between charging and discharging modes due to the turbine’s significant inertia and hydrodynamics. The main drawbacks of this energy storage technology are the large initial costs of investment, potential negative impacts on the local environment, low-energy and power densities (large space required), and limited available sites [16].
30.3.7
Compressed air energy storage (CAES)
In compressed air energy storage (CAES), energy is stored in the form of high-pressure compressed air, which is then used to generate electricity via a turbine [24]. Globally, there are a handful of installations, with power capacities varying from 80 kW to 321 MW (at McIntosh CAES plant in the United States). CAES typically has capital costs varying from $400 to $800 (kW)1, a cycle efficiency of 40%e60%, and a lifetime of 20e40 years [24]. Adiabatic CAES offers increased cycle efficiency (50%e70%), but with capital costs closer to $1000 (kW)1 [25]. An extension of this approach is to use liquid air energy storage (LAES), which uses liquefied air or nitrogen as a storage medium [35]. LAES offers round trip efficiencies of 50%e60%, but this can be significantly improved if waste heat is available. Liquid air can be stored in a tank, so it can be deployed on many more sites than CAES.
30.3.8
Thermal energy storage (TES)
Thermal energy storage (TES) comprises a collection of technologies that store energy in thermal form (heat or cold) either directly or indirectly through energy conversion processes. Grid-scale TES technologies include cryogenic energy storage [36] and pumped thermal electricity storage [37]. TES currently accounts for approximately 55% of global nonpumped hydro installations [13], and its installed power capacities vary from 5 kW to 360 MW at Pedro de Valdivia CSP power plant. The existence of gridintegrated systems makes it attractive for wholesale market services coupled with its overall system efficiency and high energy density. TES is the least cost energy storage technology, with sensible thermal energy storage at <5 £ (kWh)1 [39]. Other classes in its family are latent heat storage generally <50 £ (kWh) 1) and the most expensive thermochemical energy storage (>100 £ (kWh)1) [40]. TES technologies have response times of a few minutes to tens of minutes and are therefore suited for energy- rather than power- led applications.
30.3.9
Nickel-based batteries
In nickel-based batteries, nickel is used as the anode and a variety of materials as the cathode. This gives different classes of nickel-based batteries, namely nickel cadmium (NiCd), nickel metal hydride (NiMH), and nickel iron (NiFe). Most applicable for grid energy storage are NiFe [13] due to abundance of materials enabling manufacture at
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relatively low cost. It is also more environmentally friendly than NiCd, with long cycle life; however, their efficiency is currently low [41]. These batteries were successfully commercialized in the 20th century, but new developments received little attention due to low-cost lead acid batteries. There is now renewed interest, and this technology has the potential to provide a cost-effective solution for large-scale energy storage.
30.3.10
Flywheel
Flywheels store kinetic energy in a rotating disk and were among the first commercialized storage technologies to be used in electric power systems. The defining characteristic of this technology is its high-power and low-energy density. This makes it suitable for short-term applications in the ancillary services markets. Flywheel energy storage also has a fast response and can deliver rated power within one second, enabling participation in services that require fast response. This technology has a low environmental impact [42], a long lifetime, and high round trip efficiency (approximately 85%). A number installations exist globally with installed rated power capacity varying from 25 kW to 400 MW at the EFDA Jet Fusion Flywheel. The disadvantage of flywheel storage is the high capital cost of energy ($5000 (kWh)1) and a self-discharge rate as high as 20% of stored energy per hour [44].
30.3.11
Hybridization of energy storage systems
A hybrid energy storage system (HESS) refers to the combination of multiple energy storage technologies with the aim of exploiting their individual advantages and mitigating their drawbacks [45]. The most common configuration in the literature merges high-power, fast-response devices with high-capacity technologies to address one or more services [46]. However, the criteria for selecting hybrid technologies can also account for a number of additional characteristics, such as individual response time, cycle efficiency, cycle lifetime, self-discharge rate, initial investment costs, operation and maintenance costs, location, and potential revenue streams [12,46,47]. As the capital cost of investment required for hybridizing a system might be higher than for a single-energy storage technology, a number of approaches, such as active or passive coupling architecture [48], control techniques, or relative sizing methodologies can be considered to maximize the technical and economic benefits of hybridization [12,19,38]. The optimal sizing of HESS is a planning process to determine the power and energy ratings of each storage device by allocating their cost of power (e.g., $ MW1) and cost of energy ($ (MWh)1) in the most efficient and useful way according to the system’s objectives [49e51]. Table 30.1 presents some of the most pertinent characteristics of individual energy storage technologies while a monetarized mapping scheme between grid services and storage technologies is displayed in Table 30.2. This can be used to visualize the economic impact of using a specific technology for different services in terms of initial costs
Chapter 30 Integration of High Penetrations 659
of investment. The annualized capital costs of these values helps to further analyze the value of installing different devices considering their expected lifetime duration. This analysis can be achieved through the capital recovery factor that considers the annual discount rate, i, and the lifetime of each device, LT [49]. CRF ¼
ð1 þ iÞLT $ i ð1 þ iÞLT 1
(30.1)
These annualized costs using Eq. (30.1) are presented in Table 30.3, considering a 6% discount rate and the expected lifetime from Table 30.1. The costs can be interpreted as a constant annuity to be spent for acquiring an energy storage technology for the provision of specific services throughout the lifetime of the device. As example, according to Table 30.2, the lithium-ion batteries can be considered as a potential technology for providing peak shaving services. However, by annualizing the costs of investment, Table 30.3 suggests that pumped hydro storage and CAES might be more suitable for this job due to their large number of years of service. In this context, if the investment aims to analyze the short-term impact, Table 30.2 might provide a clearer picture, while Table 30.3 can be more useful for long-term economic analysis. For a hybrid case, however, a combination of technologies can be initially established by these tables, but further analyses are required depending on the technologies and services required.
30.4 Power conversion and control systems The majority of energy storage media produce DC power and must be coupled to the AC power network via a power conversion system (PCS). In most cases, these systems
Table 30.2 Capital costs of investment mapping: grid serviceseenergy storage technologies.
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Table 30.3 Annualized capital costs of investment mapping: grid serviceseenergy storage technologies.
incorporate various levels of control to ensure the safe, efficient, reliable operation of the energy storage systems (ESSs). These subsystems are described in this section.
30.4.1
Power conversion for energy storage systems
Power electronic conversion units serve as a key enabling technology in the continued growth of grid-scale energy storage. Currently, 30% of all electric power generated uses power electronics technologies somewhere between the point of generation and end use [52,53], and this is expected to increase in the future. In this section, we briefly discuss some technical and commercial considerations for the selection of PCS for battery ESSs and the limitations for applications at different power scales. PCS comes in many forms, and selecting the correct PCS technology and topology depends on a number of factors: 1. The power rating at the battery DC terminals, including the voltage and current rating. Selection of the battery cells/stacks should be based on this. For example, higher voltages are often preferred, as this allows the use of cheaper devices but requires stacking of more cells. 2. The power efficiency of the inverter within the operating range of the storage technology terminal characteristics. This is typically between 95% and 99% for commercially available inverters [54,55]. 3. The battery management system (BMS): The BMS operates down to a cell level to ensure that safe electrical and environmental (principally temperature) operation is maintained at all times. In large (MW-scale) battery systems, many thousands of individual cells need to be continuously monitored on an individual basis [56]. The control modes, for example, grid-connected, islanded, and antiislanding and uninterruptible power supply, can also be included within the BMS.
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4. Multiple functionality: A HESS will require more flexibility on the battery side converter, while a storage system fulfilling multiple applications [57] will require more flexibility on the grid-side converter (for example, to meet both P and Q requirements simultaneously and to operate on different timescales). 5. The communication interface: This is crucial for sending set points and commands to inverters and is usually either though Modbus, Canbus, Ethernet, or a combination. 6. Commercial applications: Inverters at distribution scale are mostly PV inverters, some options such as string inverters connect multiple inverters together. Others include central inverters, battery inverters, transformer, and transformerless inverters [54].
30.4.1.1 Power electronics devices for PCS The future of PCS for BESS will rely on affordable power electronic devices that can deliver high-power densities. Recent advances in research have yielded gallium nitride (GaN) [58] and silicon carbide (SiC) [59] devices, which are at the forefront of making this possible. An example is the ARPAVE ADEPT (Washington, DC, USA) program with HRL Laboratories (Malibu, CA, USA) [53,60]. This converter will utilize GaN devices, offering high speed and efficient performance. Improved efficiency and faster switching (increased modulation range) have been a critical motivation for the use of GaN and SiC devices.
30.4.1.2 Single stage converters A single-stage convertor comprises a bidirectional AC/DC converter that facilitates the transfer of energy between the DC energy storage medium and the AC electrical network, as shown in Fig. 30.5 [61]. A variety of topologies exist, including single- and three-phase H-bridge designs [62] and those based on other technologies, such as buck [63] or bidirectional matrix [64] converters. The main advantages of single-stage converters are the low cost, low device count, and reduced losses. However, they present major disadvantages, particularly in terms of reliability; because the storage medium must interface to a single DC connection, a single cell failure will result in a system failure and the need to bypass or replace the failed cell. There is also a limitation in the magnitudes of voltages that can be accommodated [61].
30.4.1.3 Double-stage converters A double-stage converteredas illustrated in Fig. 30.6ecomprises an AC/DC converter to interface with the wider network, and a DC/DC converter, which connects to the storage medium [61]. There are several DC/DC converter topologies, but the most common is the bidirectional half-bridge [65], which consists of two transistors and one inductor. Its popularity is due to its simplicity combined with a reasonable efficiency (>90%) [66]. A significant advantage of the double-stage converter is that it allows
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FIGURE 30.5 The general topology of a single-stage converter.
multiple DC/DC converters to connect to a single DC bus; this allows the storage medium to be divided into multiple series stacks, which increases the system’s fault tolerance [61], and could act as an enabler for hybrid energy storage. However, the disadvantages include additional complexity and potentially lower efficiency due to the additional converter stage.
30.4.1.4 Multilevel converters A multilevel converter is designed to deliver a desired AC voltage resulting from multiple DC converter stages. A number of multilevel structures exist, including the cascaded Hbridge converter (CHB) [67]; neutral point clamped converters; flying capacitor multilevel inverters (FC) [68]; and modular multilevel converters (MMC), which are based on a combination of CHB and FC topologies. Multilevel converters have several advantages, particularly the CHB and MMC configurations, whose modular structures allow reduced manufacturing costs. The redundant levels can increase reliability, and the multiple stages increase the power quality at the AC terminals [61]. However, the high number of switches leads to higher costs than simpler converter topologies.
30.4.1.5 Price comparison of PCS technology providers The market for inverters has been expanding over recent years with the increase in solar capacity in the grid. The key technology providers in the market include SMA, Victron, Huawei, ABB, SolarEdge, and Sungrow. Of these providers, SMA is the world’s largest supplier with a market share of 14% [69]; but with increased competition from Huawei, SolarEdge, and Sungrow, this has been declining in recent years. To investigate further, we have undertaken some study of retail price comparisons of three of these companies, SMA, Victron, and SolarEdge, from renewable energy distributors and providers Wind & Sun [70]. Fig. 30.7 shows this comparison of 75 battery inverter and solar PV inverter products between these companies. The prices are shown
FIGURE 30.6 The general topology of a double-stage converter.
Chapter 30 Integration of High Penetrations 663
FIGURE 30.7 Dollars per kilowatt, $ (kW)1, retail prices of three inverter suppliers.
to reflect of the price per kW and give a picture of how this relates at different power scales. Fig. 30.7 shows that the price range of inverters vary between the $150 (kW)1 and $800 (kW)1 within the power ranges of 1e60 kW. The trend of the moving average of prices is also shown to decay exponentially as power is scaled up. This can be explained as the cost of devices and components in the buildup does not increase linearly with power. For power ratings above 60 kW, these would not be off-the-shelf retail products, and prices would need to be quoted on a case-by-case basis.
30.4.2
Control of energy storage systems
Deploying ESSs to fulfill network service requirements results in unique control challenges on a variety of timescales. Because an ESS has a finite energy capacity, its SoC must be managed to ensure that contracted services can be delivered. The charging and discharging of the asset may be constrained by other service contracts or local network limitations. This leads to the requirement of a forecasting and scheduling system [57] to optimize the system’s operation on a timescale of days to hours. Once a network service is required, a real-time local or distributed [71] control system is required to ensure that the ESS delivers the mandated levels of real and reactive power to fulfill the service obligations. In some cases, these may require modeling of the local network [72], in other cases, it could be sufficient to follow an agreed response profile to a single, local variable. The inputs and interactions between these controllers are illustrated in Fig. 30.8.
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FIGURE 30.8 The inputs and interactions between the controllers of an ESS.
In addition to this, an ESS is a complex system, comprising a number of subsystems to deal with energy conversion and storage [73]; each of these subsystems will typically comprise many components, for example, the storage medium for a grid-scale ESS could contain many thousands of battery cells. BMS is needed to coordinate the operation of these subsystems to ensure the system’s efficiency, reliability, and longevity [74,75]. The most advanced BMS can incorporate physics-based models of the storage medium, enabling online performance management to improve the lifetime and efficiency of the ESS [75]. Finally, many ancillary services may have strict monitoring and control requirements to ensure full remuneration. Therefore, if an ESS is intended to participate in multiple services throughout its lifetime [76], a fast, flexible, and low-level control system is essential.
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Further reading [1] B. Diouf, R. Pode, Potential of lithium-ion batteries in renewable energy, Renewable Energy 76 (2015) 375e380.