Battery-assisted low-cost hydrogen production from solar energy: Rational target setting for future technology systems

international journal of hydrogen energy xxx (xxxx) xxx

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Battery-assisted low-cost hydrogen production from solar energy: Rational target setting for future technology systems Yasunori Kikuchi a,b,c,**, Takayuki Ichikawa d, Masakazu Sugiyama e, Michihisa Koyama a,d,f,* a

Global Research Center for Environmental and Energy Based on Nanomaterials Science, National Institute for Materials Science, 1-1 Namiki, Tsukuba, Ibaraki, 305-0044 Japan b Presidential Endowed Chair for “Platinum Society”, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan c Integrated Research System for Sustainability Science, The University of Tokyo Institutes for Advanced Study, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8654, Japan d Graduate School of Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima 739-8527, Japan e Research Center for Advanced Science and Technology, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904 Japan f Center for Energy and Environmental Science, Shinshu University, 4-17-1 Wakasato, Nagano, Nagano 380-8553, Japan

article info

abstract

Article history:

The massive implementation of renewable energy requires sophisticated assessments

Received 16 July 2018

considering the combination of feasible technology options. In this study, a techno-

Received in revised form

economic analysis was conducted for hydrogen production from photovoltaic power gen-

13 November 2018

eration (PV) utilizing a battery-assisted electrolyzer. The installed capacity of each compo-

Accepted 16 November 2018

nent technology was optimized for the wide range of unit costs of electricity from the PV,

Available online xxx

battery, and proton-exchange membrane electrolyzer. Leveling of PV output by battery, the necessary capacity of electrolyzer is suppressed and the operating ratio of electrolyzer in-

Keywords:

creases. The battery-assist will result in a lower hydrogen production cost when the benefit

Techno-economic analysis

associated with the smaller capacity and higher operation ratio of the electrolyzer exceeds

Technology roadmap

the necessary investment for battery installation. The results from this study indicated the

Off-grid production

cost of hydrogen as low as 17 to 27 JPY/Nm3 using a combination of technologies and the

Proton-exchange membrane

achievement of ambitious individual cost targets for batteries, PV, and electrolyzers.

electrolyzer

© 2018 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

Introduction The massive implementation of intermittent renewable energy systems requires the bridging of the temporal and spatial

gaps between supply and demand. Reducing fossil resource consumption has been strongly suggested under international frameworks, including sustainable development goals (SDGs) [1] and the Paris Agreement [2]. Although renewables are one

* Corresponding author., 1-1 Namiki, Tsukuba, Ibaraki 305-0044 Japan ** Corresponding author., 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 Japan E-mail addresses: [email protected] (Y. Kikuchi), [email protected] (M. Koyama). https://doi.org/10.1016/j.ijhydene.2018.11.119 0360-3199/© 2018 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. Please cite this article as: Kikuchi Y et al., Battery-assisted low-cost hydrogen production from solar energy: Rational target setting for future technology systems, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2018.11.119

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Nomenclature AreaPV (m2) Required area for photovoltaic solar cell Capbat (kWh) Installed capacity of battery represented as the charged electricity Capely (kW) Installed capacity of electrolyzer

CapPV

represented as the maximum input of power (kW) Installed capacity of photovoltaic solar cell represented as the output of power

opt

Capbat (kWh) Installed capacity of battery represented as the output of power optimizing CostH2 opt

CapPV (kW) Installed capacity of photovoltaic solar cell represented as the output of power optimizing CostH2 CAPEXbat (JPY) Capital expenditure of battery CAPEXely (JPY) Capital expenditure of electrolyzer OPEXbat (JPY/y) Operating expense of battery OPEXely (JPY/y) Operating expense of electrolyzer UCostbat (JPY/kWh) Unit cost of installation of battery UCostelec (JPY/kWh) Unit cost of generated power from photovoltaic solar cell UCostely (JPY/kW) Unit cost of installation of electrolyzer UCostH2 (JPY/Nm3) Unit cost of hydrogen production UCostPV (JPY/kW) Unit cost of installation of photovoltaic solar cell Lbat (y) Lifetime of battery Lely (y) Lifetime of electrolyzer Powbat ðtÞ (kWh/h) Charged/discharged power in battery at time t Powely ðtÞ (kWh/h) Transmitted power to electrolyzer for hydrogen production at time t Powloss1 ðtÞ (kWh/h) Excess and lost power cut off by EMS at time t Powloss2 ðtÞ (kWh/h) Lost power based on chargingdischarging efficiency of battery storage at time t PowPV ðtÞ (kWh/h) Generated power from photovoltaic solar panel at time t ProdH (Nm3) Produced amount of hydrogen Scaleely (Nm3/h) Production scale of electrolyzer hbat (-) hely (-)

Roundtrip efficiency of battery Hydrogen conversion efficiency of electrolyzer

hPV (-)

Power generation efficiency of photovoltaic solar cell

4base (MJ/(m2$h)) Base solar irradiation 4ðtÞ (MJ/(m2$h)) Solar irradiation at time t

of the key resources for replacing fossil resources, their disadvantages, such as low energy densities, volatility in power supply depending on weather and daytime conditions, and immature infrastructure for grid connections requiring control systems for voltage and frequency, should be addressed adequately for their practical use as the main sources of electricity in future energy systems. Ambitious strategies have been explored for dispatching such resources with existing

infrastructure as smart energy systems [3]. Among the various renewable resources, photovoltaic power generation (PV) is reported to have a large potential in Japan [4,5]. To enhance the usability of PV, several approaches have been examined, especially under the power-to-X concepts. Power-to-gas and power-to-liquid can be key elements in a future sustainable energy system coupling electricity, mobility, heating, and chemical sectors [6]. Power-to-gas has become a major technology for converting electricity into gas, especially with hydrogen as the energy carrier [7], which is one of the most important options for sustainable hydrogen production [8]. Various options with reaction mechanisms have been developed for hydrogen production systems [9e17] including thermochemical hydrogen production [10,11]. Various process chains have been examined for power-to-gas [18] utilizing existing gas and electricity infrastructure [19] with various scales of production of gas, e.g., hydrogen [20]. The combination of power-to-gas technology with other industrial processes can convert electricity into other products. Power-to-methane [21] has also become an option in a region with specific installed and planned capacities for wind energy and biogas plants [22] connected with power grid and thermochemical methanation process [23]. Coupled with catalytic CO2 reduction, power-tomethanol technologies can be established [24]. Biomass-based combined heat and power plants can be integrated with power-to-gas technology [25]. The steel manufacturing process could also utilize the hydrogen produced from power-to-gas technologies [26]. The future role of power-to-gas technologies includes the intensification of regional and local energy infrastructure [27]. The process and system design of power-to-gas technologies should be able to address local conditions, such as existing energy grids, markets, and solar irradiation [28]. Comparative assessments for hydrogen production have also been conducted from the energy, exergy, environmental, and economic aspects [12,29e33]. Techno-economic assessments of power-to-gas systems have been conducted for national energy grids in Germany [18], Spain [34], United Kingdom [19], Belgium [35], and South Korea [36]. Hydrogen derived from biomass and water electrolysis have been compared on the technoeconomic aspects [37]. Various technology options have been examined for hydrogen production from unutilized resources such as waste water [38]. Grid supplemented photovoltaic electrolysis system is an option to stabilize the power input to electrolyzer, which has an advantage in the cost reduction of electrolysis [39]. A hybridization strategy for power-to-gas technologies with batteries has also been reported [40] to explore conditions that reduce the hydrogen production cost, though the design of a costcompetitive system remains open. Integrated power systems have been examined for fixed scales of PV panels, e.g., electrolyzer and fuel cell package and battery-assisted power supply [41]. The sizing algorithms for PV panel and fuel cell were proposed for comparing the fixed or unconstrained hydrogen tank [42]. The configurations of systems composed by PV panels, electrolyzer, hydrogen storage, and fuel cells were simulated, which depicted the further energy cost analyses considering the technology developments [43]. Technology development has been incentivized by sharing development targets among stakeholders by technology roadmapping. Recently, national organizations have

Please cite this article as: Kikuchi Y et al., Battery-assisted low-cost hydrogen production from solar energy: Rational target setting for future technology systems, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2018.11.119

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published technology roadmaps with research targets for PV, batteries, and electrolyzers to meet the international goals. Ideally, the realization of such national targets should lead to changing the implementation of renewable resources in Japan. However, the target settings for individual technologies have met with difficulties in advancing the implementation of renewable resources. For example, the frequency fluctuation associated with the grid connection of PV has necessitated the power output suppression of PV in some regions in Japan, which is recognized as a significant social issue. The Japanese roadmap for PV projected the targets based on the levelized cost of electricity (LCOE) only and did not address the grid connection issue [44]. Therefore, the implementation of PV is ambiguous even though the LCOE target is reached. Batteries can be a solution for such issues; however, the technology targets set for batteries for stationary purposes are relatively obscure [45]. Some technology targets should be examined in the context of systems combining multiple technologies because the focused technology may not function as the system component without adequate development and incorporation of other technologies. Rational targets should be set based on such system design and analysis. In this study, the techno-economic performance of a battery-assisted hydrogen production system is analyzed considering technology development based on governmental incentivization. The case study of off-grid hydrogen production is explored for Japan, where almost all fossil resources are imported. The renewable resource is set as the solar energy in Nagano, one of the best locations for solar irradiation in Japan. A proton-exchange membrane (PEM) electrolyzer is suggested as the hydrogen production technology. An advanced battery is assumed to be connected for managing the balance of PV and PEM electrolysis hydrogen production. Future technoeconomic performance in their individual technology roadmaps are systematically analyzed based on the minimization of the unit cost of hydrogen.

time t, 4ðtÞ, is converted into solar power at time t, PowPV ðtÞ, through a PV. The generated PV power is transmitted to a PEM electrolyzer through a DC/DC converter to adjust its voltage. If the PowPV ðtÞ is larger than the capacity of the electrolyzer, Capely , the generated power is stored in a battery by transmitting Powbat ðtÞ. When the operating ratio of the PEM electrolyzer and the charging ratio of battery storage are both full, the excess power is cut off by an energy management system (EMS) and lost as Powloss1 ðtÞ. A part of the charged electricity in the battery is lost due to the internal resistance during the roundtrip of charging and discharging, and this power loss is denoted as Powloss2 ðtÞ. This operation is managed by the EMS connected to the DC/DC converter. The battery assists the stabilization of the DC flow to PEM electrolyzer, Powely ðtÞ, by charging the excess PowPV ðtÞ during daytime and discharging it during nighttime as Powbat ðtÞ. It resulted in the temporally stabilized production of hydrogen, ProdH . The time integral for generated power is balanced with those of power consumed by the PEM electrolyzer and power losses at the EMS and battery as follows: Z

Z PowPV ðtÞdt ¼

Z Powely ðtÞdt þ

Z Powloss1 ðtÞdt þ

Powloss2 ðtÞdt (1)

Settings for techno-economic performance

Materials and methods

The techno-economic parameters for technology options are selected by referring to the target values found in the technology roadmaps or in the literature. This enables us to examine if those targets separately set for individual technologies will lead to the feasibility of the battery-assisted hydrogen production system as a whole. Table 1 summarizes the parameter settings in this study. At first, the existing technology roadmaps for electricity from PV, batteries, and PEM electrolyzers are investigated. Based on the target values in such roadmaps, the settings for evaluating the levelized unit cost of hydrogen production, UCostH2 , are extracted or assumed in this study. Note that the time of the target values is defined as 2030.

Battery-assisted hydrogen production

Solar cell

Fig. 1 schematically shows the system for battery-assisted hydrogen production from solar cells. The solar irradiation at

The rated capacity of the PV, CapPV , is adopted as the variables in the minimization of hydrogen production cost, UCostH2 . The area required for the installation, AreaPV , is be calculated

Fig. 1 e Boundary of battery-assisted hydrogen production system. Please cite this article as: Kikuchi Y et al., Battery-assisted low-cost hydrogen production from solar energy: Rational target setting for future technology systems, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2018.11.119

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Table 1 e Settings for techno-economic performance. The efficiencies of PV, batteries, and electrolyzers are assumed to be constant in this study. Technology Photovoltaic solar panel

Battery storage

PEM electrolyzer

Parameters

Values

UCostelec CapPV

7 [44], 5, and 3 JPY/kWh assumed from USDOE [46] and IRENA [47] Variables for the minimization of UCostH2 . s, where 4base ¼ 1 kW/m2 and hPV was assumed as 0.15. More than 5000 JPY/kWh [45] Variables for the minimization of UCostH2 20 years [45] Assumed as 0.9 CAPEXely , where CAPEXely is based on Eq. (6) [55], the cases of which are Capely

UCostbat Capbat Lbat hbat UCostely

30 000 JPY/kW (2.47  105 kW), 50 000 JPY/kW (5.01  104 kW), and 100 000 JPY/kW (5.74  103 kW) 3:544 Scaleely , where hely was assumed as 0.826 [55] and 3.544 kWh/Nm3 is hely

Capely

the electrolysis energy requirement calculated from the standard enthalpy change at 298K. 10 years

Lely

Note: The power conversion efficiency of PV depends on conditions, such as the installed angle and direction and temperature. Battery charging/discharging efficiency will degrade during its cycle operation. The part load operation will change the efficiency of the PEM electrolyzer. Although these conditional changes in performance can occur hourly in the actual installation, they were not considered in this study for simplicity.

by Eq. (2), where 4base is the base irradiation and hPV is the power conversion efficiency. The generated power, PowPV ðtÞ, is be obtained in Eq.(3), where 4ðtÞ is the actual hourly irradiation in the target region. As shown in Eq. (3), a larger CapPV induces wider gaps of power generation between daytime and nighttime, which may affect the required capacity for battery storage. AreaPV ¼

 CapPV 4base hPV

(2)

POWPV ðtÞ ¼ AreaPV $hPV $4ðtÞ

(3)

The cost of electricity from a PV is problematic because diversified analyses have been conducted on the LCOE derived from PV, UCostelec . The latest major roadmap for solar cells in Japan is the NEDO PV Challenges [44]. According to their systematic review of solar cells, the LCOE derived from PV is targeted at 14 JPY/kWh after the increase of module conversion efficiency and the decrease in production cost. With material and structural optimization, 7 JPY/kWh in 2030 is the target. The US Department of Energy (USDOE) has launched an initiative for the reduction in the LCOE, with targets of 0.03e0.05 USD/kWh, about 3e5 JPY/kWh, in 2030 [46], which has become an international target [47]. Although UCostelec can be broken down and correlated with CapPV , the actual cost composition is region-specific and based on irradiation condition, land, construction, wheeling charge, and transportation costs. Therefore, UCostelec was set as 7, 5, and 3 JPY/ kWh as discrete variables in this study without explicitly considering its dependence on CapPV . Therefore, the optimization results indicate the minimized CostH2 produced from opt

the electricity with the UCostelec generated from CapPV . The cost of the power converter is also included in the LCOE in the extracted UCostelec .

Battery Various materials have been adopted and examined for the anode and cathode materials in batteries, which have mainly been considered for application in electric vehicles [48]. The costs for battery packs have fallen rapidly [49]. The milestone cost for battery packs, UCostbat , has been recognized as 125 USD/kWhuse, i.e., 13 750 JPY/kWhuse, and 100 USD/kWhuse, i.e., 11 000 JPY/kWhuse, for Lithium-ion and Lithium-metal batteries, respectively [50]. Considering the estimation of UCostbat and applying advanced materials in the anode and cathode, a milestone for the selling price was set as 50 USD/kWhcharge, i.e., 5500 JPY/kWhcharge in 2030 [48]. The latest major technology roadmap for batteries in Japan gives the milestones as 20 000 JPY/kWh, 10 000 JPY/kWh, and 5000 JPY/kWh in 2020, 2030, and after 2030, respectively [45]. Therefore, 5000 JPY/kWh can be regarded as an ambitious target value for UCostbat . Capbat is defined as a variable for minimizing UCostH2 . The fluctuation of irradiation, 4ðtÞ, can be stabilized by a battery for increasing the operation ratio of the electrolyzer. Although the generated power could be utilized, the height of peaks in irradiation sharply changes daily and seasonally and requires significant battery capacity, Capbat . This results in the decrease in the operating ratio of the battery. The optimal balance of the capacities of the electrolyzer, Capely , battery, Capbat , and PV, CapPV , should be scrutinized and can be changed by the balance of their unit costs, UCostely , UCostbat , and UCostelec . Depending on cell chemistry, a high C-rate will increase battery ageing and decrease its lifetime [51,52]. If there is a constraint on the operable C-rate in battery charging/discharging, the Capbat increases and reduces the Crate; otherwise, its lifetime can be shortened compared to the expected life. Note that the lifetime of that battery is a constant in this study at 20 years for simplicity, while the lifetime will depend on the charging/discharging profiles. The scale factor of the battery is not explicitly considered in this study.

Please cite this article as: Kikuchi Y et al., Battery-assisted low-cost hydrogen production from solar energy: Rational target setting for future technology systems, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2018.11.119

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Electrolyzer

set as the capacities of the PEM electrolyzer, Capely , battery

Alkaline electrolyzers, PEM electrolyzers, and anion exchange membrane electrolyzers are commercially available [52]. The PEM electrolyzer techno-economic performance is expected to improve from 1860 to 2320 EUR/kW in 2014 to 250e1270 EUR/kW in 2030 as the system investment cost, which in-

storage, Capbat , and PV solar panel, CapPV , with the conditions as their unit costs, Costely , UCostbat , and UCostelec , respec-

Z UCostH2 ¼

UCostelec $

tively. Fig. 3 shows the algorithm for minimizing hydrogen production cost, UCostH2 , as shown in Eq. (4) for individual settings of the abovementioned parameters.

   PowPV ðtÞdt þ CAPEXely Lely þ OPEXely þ ðCAPEXbat =Lbat þ OPEXbat Þ (4)

ProdH

cludes the peripheral devices [52], assuming 130 JPY/EUR. The lifetime has also been elongated from 20 000e60 000 h (1500e3800 USD/kW) in 2015 to 80 000 h (830 USD/kW) in 2030 [53]. According to the latest major roadmap on hydrogen strategy in Japan, the unit plant cost of the PEM electrolyzer, UCostely , is targeted at 50 000 JPY/kW, i.e., about 385 EUR/kW and 455 USD/kW [54]. Here, the unit cost of an electrolyzer is considered under its scale factor [55].

The LCOE assumed from the PV, UCostelec , is set as shown in Table 1, which is defined by the first part of the algorithm in Fig. 3. The capital expenditure, CAPEXely , and the annual operating expense, OPEXely , of the PEM electrolyzer are defined next. In this study, the existing cost estimation functions [55] are adopted to represent the scaling factors of the electrolyzer as shown below:  0:68 CAPEXely ¼ 4:3  106 $ Scaleely

(5)

Evaluation algorithm of hydrogen production cost Major assumptions in evaluation The ancillary facilities of for PV, batteries, and electrolyzers, such as wiring cables, are implicitly considered in the cost settings above. Independently, a PV power converter, battery management system, and AC/DC converter are equipped in the PV, battery, and electrolyzer, respectively. The set costs above, UCostely , UCostbat , and UCostelec , are expected to be for standalone installations and include such ancillary facilities, some of which are not necessary in the battery-assisted hydrogen production investigated in this study, in their cost targets found in various roadmaps [44,45,56]. Although battery-assisted hydrogen production requires a novel EMS for optimizing the system operation, it is assumed that the cost for the ancillary facilities, which is included in the independent system but is not necessary in the battery-assisted hydrogen production, can compensate for the additionally required cost for the hybridization of the PV, battery storages, and PEM electrolyzer. More specifically, the PV power converter, battery management system, and AC/DC converter included in the unit costs are assumed compensate for those of the DC/DC converter and EMS shown in Fig. 1. The irradiation patterns, 4ðtÞ, can change the optimal points, the location of which is set as Nagano-city in Japan in this study as shown in Fig. 2. The quality and property of produced hydrogen were set for conventional use as fuel gas. The purity of hydrogen produced from a PEM electrolyzer is 99.9e99.9999% [52]. The pressure of hydrogen can range from 3 MPa to 10 MPa [57]. It can be utilized as the heat quantity adjuster for city gas and the pressure in pipelines, which is from 0.3 to 1 MPa for medium pressure or more than 1 MPa for high pressure city gas [58].

Flow chart In the system shown in Fig. 1, the major design parameters of facilities related with hydrogen production cost, UCostH2 , are

OPEXely ¼ 0:075$CAPEXely þ 0:075$CAPEXely $

hely $ 3:544

Z Powely ðtÞdt

ADays$Scaleely (6)

where the coefficients have the physical meaning as parameters of the PEM electrolyzer. The coefficient, 4:3  106 , and power, 0.68, are obtained from the curve fitting of technoeconomic performance for four different scales of hydrogen production, i.e., 300, 3000, 10 000, and 32 000 Nm3/h [55,56]. The coefficient, 0.075, used in (both terms in right hand side of) Eq. (6) indicates the ratio of fixed and variable costs in OPEXely . ADays is the total number of hours per year. The second term in the right side of Eq. (6) is the OPEXely related with operating ratio. The costs of battery were set as shown in Eqs. (7) And (8). The unit cost of battery storage, UCostbat , is assumed as more than 1000 JPY/kWh to include the target value shown in Table 1. In this study, the OPEXbat is not considered. CAPEXbat ¼ Capbat $UCostbat

(7)

OPEXbat ¼ 0

(8)

Based on these equations, the hydrogen production cost, CapH2 , is minimized by adjusting CapPV and Capbat . The profile of generated power, PPV ðtÞ, is obtained from Eqs. (2) And (3), according to the hourly irradiation pattern, 4ðtÞ. If the electrolyzer cannot consume all generated power from the PV due to the limitation shown in Eq. (10), the remaining power is stored in the battery (Eq. (9)). The transmission of power to the battery is constrained by Eq. (11). The power that cannot be consumed by the electrolyzer nor stored by the battery, Powloss1 ðtÞ, is shown as Eq. (12). A part of the stored power in battery is lost during the charging/discharging cycle due to internal losses as shown in Eq. (13). The golden-

Please cite this article as: Kikuchi Y et al., Battery-assisted low-cost hydrogen production from solar energy: Rational target setting for future technology systems, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2018.11.119

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Fig. 2 e Irradiation in Nagano-city for solar photovoltaic power generation. The time begins at 0:00 1 January 2016, which includes 8784 h due to the bissextile. The detailed graphs are shown in Fig. S1.

Powloss1 ðtÞ ¼PowPV ðtÞ  Powely ðtÞ  Powbat ðtÞ ð0  Powloss1 ðtÞ; 0  Powbat ðtÞÞ Powloss2 ðtÞ ¼ ð1  hbat Þ$jPowbat ðtÞj

ðPowbat ðtÞ < 0Þ

(12)

(13)

Results Composition for optimal hydrogen production cost The composition for optimal hydrogen production cost is shown in Fig. 4 for Costbat and Fig. S2 for UCostely . The results are divided in terms of the UCostelec and the C-rate upper limit. The results show the large contribution of UCostelec to the UCostH2 , which is calculated as

3:544 hely

¼ 4:292 kWh=Nm3 ,

with UCostelec . More than half of UCostH2 is a result of UCostelec when it equals 7 JPY/kWh. The costs R Powloss1 ðtÞdt are minimized in all cases by adjusting R CapPV considering Capely . The costs for Powloss1 ðtÞdt are

section search [59] was employed to obtain the sets of opt parameters, Capbat ðUCostelec ; UCostbat ; UCostely Þ opt CapPV ðUCostelec ; UCostbat ; UCostely Þ to minimize UCostH2

adjustable

for the sets of ðUCostelec ; UCostbat ; UCostely Þ, individually. Powbat ðtÞ ¼PowPV ðtÞ  Powely ðtÞ ð0  Powbat ðtÞ; equationsð10Þandð11ÞÞ 0  Powely ðtÞ  Capely

(9)

(10)

Zk 0

Powbat ðtÞdt  Capbat

ð0  k  ADaysÞ

not

null in all cases, meaning that a part of generated power, PowPV ðtÞ, should be discarded in order to increase the profitability from hydrogen production. If CapPV is decreased or Capbat is increased to recover all generated power as Powely ðtÞ

Fig. 3 e Flow chart of evaluation algorithm for hydrogen production cost.

and

the for the

(11)

and Powbat ðtÞ, respectively, the operating ratio of PEM electrolysis and the battery decreases, which results in an increase in the total hydrogen production costs due to the increase in the capital recovery. With the constraint in charge/discharge rate as shown in Fig. 4 (a, c, e), one can see that the battery will not be installed when it is more expensive than ca. 1.6  104 JPY/kWh. Without the battery, the CostH2 is determined by the balance between CapPV and Capely and appears as a constant in the figure. As the battery cost becomes cheaper, the battery is introduced to reduce the hydrogen production cost. When no constraint is applied to the charge/discharge of the battery, the battery is installed for all the ranges investigated as shown in Fig. 4 (b, d, f). With the reduction of UCostbat , the installed battery capacity increases, resulting in an increase in the capital

0

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(a)

(b)

(c)

(d)

(e)

(f)

Fig. 4 e Cost breakdown of optimized CostH2 for Costbat with

expenditure for the battery. Increased battery capacity contributes to the improvement in the operation ratio of the electrolyzer, reducing its capital expenditure. When the battery becomes sufficiently cheap, the installed capacity does not increase further, and the capital expenditure of the battery decreases in proportion to its unit cost. The costs for R Powloss1 ðtÞdt are reduced by the hybridizing battery in all R cases in Fig. 4, although the costs for Powloss2 ðtÞdt, i.e., the

CAPEXely Capely

as 50 000 JPY/kW, i.e., 5.01 £ 104 kW for Capely .

loss associated with charging/discharging of the battery, increase.

Capacities of the battery and PV at the optimal point of hydrogen production cost opt

Fig. 5 and Fig. 6 show the profiles of Capbat =Capely and opt CapPV =Capely ,

respectively, for UCostbat for three cases of

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CAPEX

4 5 4 ely Fig. 5 e Profiles of Capopt bat =Capely for Costbat for the three cases of Capely : 3.00 £ 10 JPY/kW (2.47 £ 10 kW), 5.00 £ 10 JPY/ CAPEXely 4 5 3 kW (5.01 £ 10 kW), and 1.00 £ 10 JPY/kW (5.74 £ 10 kW). The calculation for the three cases of Capely has the range limitation: 2.00 £ 104 JPY/kWh for the 3.00 £ 104 JPY/kW and 5.00 £ 104 JPY/kW cases and 4.00 £ 104 JPY/kWh for 1.00 £ 105 JPY/kW.

CAPEXely Capely :

3.00  104 JPY/kW (2.47  105 kW), 5.00  104 JPY/kW

(5.01  104 kW), and 1.00  105 JPY/kW (5.74  103 kW). The calculated C-rate for 54 patterns is shown in Fig. S4. By tracing the profiles shown in Figs. 5 and 6 from the highest to lowest UCostbat , the system conditions change as observed by major inflection points. At the UCostbat of 1.00  105 JPY/kWh, no opt

battery storage was installed in all cases. The CapPV relative to the capacity of the electrolyzer is obtained to increase the amount of produced hydrogen, ProdH , by decreasing the R Powloss1 ðtÞdt. When the cost of the battery is too expensive to be installed, the capacity ratio of PV and electrolyzer does not change.

The threshold point must be the point where the hybridization of the battery effectively reduces UCostH2 as shown in Figs. 5 and 6 The higher UCostely induces higher incentives for installing batteries to increase the operation ratio of the electrolyzer shown in Fig. S3, that is, the amount of produced hydrogen, ProdH and decrease the costs for the electrolyzer in UCostH2 . A small battery installation needs a relatively higher C-rate to adjust the intermittent power from the PV. This provides the threshold point for the cases with C-rate constraints needing a lower UCostbat than those without the Crate constraint. The inflection points of UCostbat for the UCostely cases without the C-rate constraint were about 2.50  104, 3.30  104, and 6.50  104 JPY/kWh for 3.00  104,

Please cite this article as: Kikuchi Y et al., Battery-assisted low-cost hydrogen production from solar energy: Rational target setting for future technology systems, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2018.11.119

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CAPEX

4 5 4 ely Fig. 6 e Profiles of Capopt PV =Capely for Costbat for the three cases of Capely : 3.00 £ 10 JPY/kW (2.47 £ 10 kW), 5.00 £ 10 JPY/ CAPEXely 4 5 3 kW (5.01 £ 10 kW), and 1.00 £ 10 JPY/kW (5.74 £ 10 kW). The calculation for the three cases of Capely has the range limitation: 2.00 £ 104 JPY/kWh for the 3.00 £ 104 JPY/kW and 5.00 £ 104 JPY/kW cases and 4.00 £ 104 JPY/kWh for 1.00 £ 105 JPY/kW.

5.00  104, and 1.00  105 JPY/kW, respectively, while they were about 1.00  104, 1.60  104, and 3.20  104 JPY/kWh for the cases with the C-rate limit. At the same time, the relative capacity of the PV also increases as shown in Fig. 6. This is because the excess PowPV ðtÞ during the daytime is provided to the battery to use during the nighttime. Through this mechanism, the optimized UCostH2 is reduced as shown in Fig. 4. At the inflection zones circled in Figs. 5 and 6, the slope factors of

opt Capbat

and

opt CapPV

were considerably changed to

reach pseudo-plateau regions. In these zones, the maximum

absolute value of discharging C-rate reached a constant for opt

the entire year according to Fig. S4. This indicates that CapPV = Capely is sufficient for supplying power to the electrolyzer most of the day through the battery installed. The inflection zones correspond to the extremal points of battery capital opt

expenditure in Fig. 4. However, for Capbat =Capely , the values opt

increase. Fig. 5(a) shows an exponential increase in Capbat

along with the reduction in Costbat under the inflection zones, while Fig. 5(b) shows mild increase along with the reduction of

Please cite this article as: Kikuchi Y et al., Battery-assisted low-cost hydrogen production from solar energy: Rational target setting for future technology systems, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2018.11.119

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opt

of batteries and PV, which means that its techno-economic performance can improve much further through large-scale

Costbat . In contrast, CapPV =Capely does not increase, but is constant or decreasing along with the reduction in Costbat under the inflection zones as shown in Fig. 6. This is because the excess PPV ðtÞ stored in the battery cannot be transmitted to the electrolyzer in a day due to the sufficient CapPV and Capbat for Capely . The additional increase of excess PowPV ðtÞ cannot

production and installation. The utilized

opt

of Capbat without the increase of CapPV recovers the loss of excess PowPV ðtÞ and increases the operation ratio of the electrolyzer as shown in Fig. S3. The C-rate limit decreases the UCostbat threshold of effective hybridization of the battery storage due to the increase in the required Capbat . The optimized UCostH2 with the C-rate upper limit is greater than that without the C-rate limitation. This means that the limitation should be removed in order to reduce the optimized UCostH2 . The evaluated Crate required for the cases without the C-rate constraint was around 0.4 to 1.0 as shown in Fig. S4. While the C-rate for charging traced the irradiation shown in Fig. 2 to store the electricity not transmitted to electrolyzer, the C-rate for discharging has a constant maximum in absolute value terms due to the capacity of the electrolyzer. According to Fig. S4, the profiles of the C-rate are changed by the settings of UCostelec , UCostbat , and UCostely . UCostbat has a relationship with the

electrolyzer

with the incentives for the hybridizing battery. When UCostely is sufficiently low and UCostbat is high, the battery should not be hybridized to reduce UCostH2 . This is why no battery was hybridized for the higher UCostbat at lower UCostely .

Discussion Interpretation of obtained result Because the technologies considered in this work are developing and emerging technologies, the techno-economic parameters may or may not go beyond the settings used in this study. This is especially the case for the PEM electrolyzer, as experience with it in the energy market is much less than that

Table 2 e Results of base settings and advanced technology settings for.

UCostH2 [JPY/Nm3] Electricity Lost electricity (loss 1) Storage Lost electricity (loss 2) Electrolysis plant Electrolysis operation Operating ratio of electrolysis opt

Capbat [kWh] opt

CapPV [kW]

CAPEXely Capely ,

5  104 JPY/kW. Because the estimation

[29] is conducted early in this century, we may expect much technological advancement. One of the state-of-the-art cost estimations for a polymer electrolyte fuel cell reports the conditions as follows: 15 USD/kW at 0.75 W/cm2, i.e., at 7.5 kW/m2 [60] with a fuel cell operating voltage of 0.659 V at 1.14A/cm2. If we assume that the reverse operation of the same cell with the electrolysis operation voltage of 1.705 V at 2.5 A/cm2 is possible, this corresponds to 2.64 USD/kW for the cost of an electrolysis cell. Setting 110 JPY/USD, this is 2.90  102 JPY/kW at 42.625 kW/m2. Even if we assume that the configuration and cost of the balance of electrolyzer plants are the same, the unit price of an electrolyzer could become 3.15  104 JPY/kW from 5.00  104 JPY/kW. Assuming this highly advanced PEM electrolyzer technology level, the abovementioned optimization of UCostH2 was conducted for the condition of UCostbat and UCostelec equaling 5.00  103 JPY/ kWh and 2 JPY/kWh, respectively. The electricity cost was set to the lowest cost recorded of 0.02 USD/kWh [47]. Note that the minimum LCOE for the PV was the record from Saudi Arabia, i.e., from 6.69736 to 12.62521 Halalas/kWh [61], which is 1.95470e3.684808 JPY/kWh at 0.291861 JPY/Halalas. Table 2 shows the results for the settings assuming an advanced electrolyzer technology compared with the base settings shown in the previous sections. The UCostH2 is under 20 JPY/Nm3 for both cases of C-rate limitation. The reduction in UCostelec leads to the reduction in electricity and lost or cutoff electricity (loss 1 and loss 2), which becomes two thirds of the base setting. The developed electrolyte cell can provide

applicable Capbat , which means that the required C-rate increase results in a higher UCostbat because the smaller Capbat is applicable. In addition, Costely has a strong relationship

Parameters

and OPEXely

can be divided into the plant cost, i.e., electrolyte cell with peripheral devices, bedding, construction, fixed asset tax, damage insurance, maintenance, payroll, interest cost, and administration cost [55]. Among these items, the electrolyte cell has a large potential for improving its techno-economic performance. The parameters for the electrolyte cell in this study were as follows: 8.00  105 JPY/m2 for the electrolyte cell, 1.705 V for electrolysis, and 2.5 A/cm2 current density, giving an input power of 42.625 kW/m2 [56]. This can be converted into 1.88  104 JPY/kW to be included in the unit price of a PEM

effectively be utilized without sufficient Capbat . The increase opt

CAPEXely Capely

CAPEXely . Capely jC-ratej  0.1

w/o C-rate limitation Base setting

Advanced electrolyzer setting

Base setting

Advanced electrolyzer setting

25.27 12.89 0.62 2.64 0.80 3.71 4.62 0.66 7.12  105

17.42 8.58 0.42 2.53 0.63 2.34 2.91 0.66 6.84  105

UCostH2 [JPY/Nm3] Electricity Lost electricity (loss 1) Storage Lost electricity (loss 2) Electrolysis plant Electrolysis operation Operating ratio of electrolysis

25.27 12.89 0.62 2.64 0.80 3.71 4.62 0.66 7.12  105

5

5

2.13  10

2.16  10

opt

Capbat [kWh] opt

CapPV [kW]

2.13  105

Please cite this article as: Kikuchi Y et al., Battery-assisted low-cost hydrogen production from solar energy: Rational target setting for future technology systems, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2018.11.119

international journal of hydrogen energy xxx (xxxx) xxx

savings in the costs for the electrolyzer and its operation. The change in the balances of UCostelec , UCostbat , and UCostely moved the optimal point of Capbat and CapPV , which results in opt

opt

the reduction in Capbat . Regarding CapPV , it is increased by the reduction in UCostelec , which means that lost electricity can be opt

offset by the reduced UCostbat and Capbat . In both cases of Crate limitation, the optimized UCostH2 could be reduced by ca. 7 JPY/Nm3. The results in Table 2 were compared with the previous studies in literature. Because various system components have been considered in the reported results, the comparison should be carefully conducted to adjust the premises of settings. The results of systems with the same components, i.e., PV, battery, and electrolyzer, were extracted from a literature [40], where UCostH2 are 13.2 JPY/Nm3 for no-battery case, and ranged from 49.0 to 59.2 JPY/Nm3 in 2030 assuming 10.78 MJ/ Nm3 as heat quantity. First of all, the battery assistance has no effect to decrease UCostH2 in Ref. [40]. This is partly because the relative ratios of capacities of component systems were not optimized. The optimization of installation capacity ratios enhances the value of battery assistance. The lowest value in the reference is less than that in this work. This is because UCostelec in the reference was set as zero. If UCostelec was set as zero in Table 2, the modified lowest UCostH2 could become 8.84 JPY/Nm3. Due to the optimization of installed capacity ratios and battery assistance, the modified lowest UCostH2 in this work is less than that in the literature.

Characteristics in this evaluation Optimization for system design The combination of PV and electrolysis with batteries has numerous opportunities for optimization of system design. Their balance is significantly sensitive to hydrogen production cost due to the changes in operation ratio of the electrolysis plant. Optimization can generate edging alternatives, which are the alternatives related to the Pareto solutions of opt

opt

Capbat =Capely and CapPV =Capely ; by screening the possibilities of the combinations. The optimization of UCostH2 by adjusting Capbat and CapPV clarifies the optimized installation capacities of battery-assisted electrolyzers utilizing the electricity from the PV at the set of UCostelec , UCostbat , and UCostely . UCostelec has a relationship with the utilization ratio of generated electricity by the PV. When UCostelec and UCostbat are sufficiently high and low, respectively, the utilization ratio of generated electricity approaches 100% to avoid discarding electricity. However, the results shown in Fig. 4 demonstrate that the optimal settings are not always for 100% use of generated electricity. In Fig. 5, the values around the lowest UCostbat sharply increase, which means that the required relative capacity of the battery is considerably large to recover all of the generated electricity. This is because the vertical axis gives the capacity of the battery at the optimal point. The relative battery capacity in Fig. 5 increases as UCostbat decreases. Through optimization of the adjustable parameters, i.e., Capbat and CapPV and with changes in UCostelec , UCostbat , and UCostely , the rationale for the targets in technology development can be examined.

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The inflection zones clarified by the optimization in this study should be referred to as a rationale for the target in technology roadmaps. Battery-assist has been recognized as the factor for increasing hydrogen production cost according to previous research on the hybridization of power-to-gas with batteries [40]. In that work, the UCostely and UCostbat were set as 550 to 949 EUR/kW and 240 to 1000 EUR/kWh, respectively. The lower values were set referring to future development targets in 2030 [66]. The battery is set for the minimum load requirement of the electrolyzer without connection to the power grid, resulting in an increase in hydrogen production cost for the case of 71 500 and 117 000 JPY/kW for UCostely [40]. This is because the cost of the battery is not low enough to be installed. Here, we optimize the system assuming the same unit cost of 550 and 900 EUR/kW and determine that ca. 60 and 120 EUR/kWh, respectively, are the threshold unit costs of the battery to be installed. Apparently, the UCostbat target for 2030 used in the preceding study are not sufficiently low to support the economic feasibility of the battery-assist hydrogen production; therefore, the battery cost target of 60e120 EUR/kWh should be shared among stakeholders and one should note that such targets depend on the cost target of the PV and electrolyzer. Systems optimizations for hydrogen production should be conducted for process design or operation. The optimization in this study revealed the inflection in the process to be designed based on the values of battery assistance for hydrogen production with the variables of capacities of PV, battery, and electrolysis considering changes in their CAPEXs by technology development. We can find previous studies on power-to-gas technologies analyzing the performances of hybridization of different technologies. For example, the maximum power points (MPP) were simulated for hydrogen production by different number of series and parallel cells of PEM electrolyzer [62], and power generation by battery-assisted PV considering dynamic changes of PV output by every second [63] or applying fuzzy-logic modeling [64]. These optimizations in process operations are based on fixed capacities and CAPEX of devices, rather than the dynamic simulation of power management [65], although the power management in this study was defined as the algorithm represented in the equations in Section Evaluation algorithm of hydrogen production cost. Optimizations of both the design and operation of systems should be addressed for obtaining optimal hydrogen production under the conditions on the renewable resources as primary energy sources, which depends on the technology levels of renewable resource utilization. Such optimization, however, may require heavy computational costs if one intends to obtain rigorous solutions. The results in this study mean the preliminary sets of capacities and CAPEXs near to optimal, which can become the initial values for integrated optimization of process design and operation.

Limitation of modeling The evaluation results are limited in their numerical accuracy originating from the assumption and premises in the adopted data and models. One of the major premises in the data is that hourly data for irradiation are defined as the minimum unit of data shown in Fig. 2. To represent the actual behavior for battery storage and the electrolyzer, the data should be obtained

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with much shorter time interval, such as a second. Such detailed data are not available for irradiation and PV. The use of such data will be useful in identifying the actual battery cycle characteristics and may influence the C-rate requirement of the battery. The required C-rate will change the electrode design; i.e. dense packing of the electrode for high capacity but low C-rate and loose packing for low-capacity and high C-rate. Note that the latter may result in higher capital expenditure for the battery. At the same time, Pely ðtÞ can be stabilized via battery storage for such actual fluctuations because battery storage can adjust the voltage profiles of Pely ðtÞ. These conditions are not included in the simulations evaluated in this study. The lifetimes of the battery and electrolyzer are defined since their operating ratios have no relationship with the lifetimes. However, the actual lifetimes should take into account their usage. For batteries, the C-rate should be adjusted to the design range to avoid electrode degradation [67]. Although the actual lifetime is often defined as cycle times, the full charging/discharging is not always found during actual use. As for the electrolyzer, the operational conditions, such as operating ratio and start-up/shut-down frequency, become the factors for lifetime [68]. The estimation of lifetime under certain conditions of use should be conducted for analyzing the practical expenditures, otherwise the analysis cannot represent the actual situation even if detailed data with short time intervals could become available. The optimization of UCostH2 by adjusting Capbat and CapPV in this study is classified as a nonlinear and multiple solutions problem. If rigorous solutions should be obtained, applied optimization methods could be changed to another algorithm. In this study, the golden-section search [59] was employed for simplification. Although multiple solutions can be found, the optimized UCostH2 is not changed much because the effects of changes in Capbat and CapPV are physically understood as explained in Section Results and are monotonic. However, the optimized UCostH2 can become less than the current values by applying rigorous optimization methods for nonlinear and multiple solution problems.

Limitation of evaluation indicators In addition to economic aspects of hydrogen production, social and environmental aspects should be also examined. The social acceptance of hydrogen and other energy technologies is one of the most important concerns for social implementation and has been assessed through various approaches [69] including analyses on, for example, transportation in Spain [70] and fuel cell vehicles in London [71]. The environmental impacts are also one of most important concerns in massive implementation of hydrogen production. As for the key impact categories induced by battery, abiotic depletion, acidification, and human toxicity have higher potential environmental impacts than global warming [72], which were confirmed for various types of batteries [73]. PV cell production is also associated with various environmental impacts as analyzed in and retrieved from ecoinvent [74], the largest life-cycle inventory database in the world. Fig. S5 and Fig. S6 show the results of cradle-to-gate life cycle assessment on Li-ion battery in ecoinvent, and two types of PV cell productions represented by other impact assessment

methods. Although the results are different due to the differences in the settings and scopes of impact assessment methods [75], not only climate change caused by global warming, but also other environmental impacts should be taken into account for battery and PV cells as a part of chemical risk management [76].

Rational target settings for future technology systems A technology roadmap is a map illustrating the future direction of technological development for advancing technologies and fostering understanding among stakeholders. By articulating technological development and plans, research and development can be accelerated by enabling a concentration of effort toward technological options selected in the roadmap [77]. In this study, the target values for techno-economic performance of electricity from PV, battery storage, and electrolysis were acquired from their roadmaps articulated by NEDO of Japan [44,45,56] and the US DOE [46]. NEDO and DOE are some of the largest organizations promoting research and development and deployment of industrial, energy, and environmental technologies into society. The roadmaps from such organizations have the potential to direct technology development toward their target settings and change the technology readiness levels. The roadmaps for the three technologies are articulated separately, in addition to roadmaps for hydrogen production. While these roadmaps implicitly refer to the other roadmaps, they separately set targets that do not guarantee the feasibility of the systems integrating each technology. The results from this study give an example of determining research targets rationally. Specifically, the target values of UCostH2 are found to be 30 JPY/Nm3 [78,79] or 20 JPY/Nm3 [80]. The results in this study show the possibility of achieving the target values of UCostH2 through the combination of technologies along with the individual technology development from the roadmaps for batteries, PV, and electrolyzers. Batteries have the potential to support the reduction in UCostH2 by increasing the operating ratio of electrolyzers. The thresholds of UCostbat to reduce UCostH2 are 1.00  104 to 6.50  104 JPY/kWh associated with UCostely . This indicates that greater development of electrolyzer technologies leads to lower Capbat to assist in hydrogen production. In other words, batteries can assist the reduction in UCostH2 even if electrolyzers cannot develop according to its technology roadmap. As shown in Fig. 4, the dominant component of UCostH2 is the electricity for electrolysis, which means that the sensitivity of an electrolyzer to battery assistance is low. The C-rate required for batteryassisted hydrogen production is ranges widely depending on Capbat , which are obtained through the optimization of UCostH2 with CapPV . We note that the C-rate for assisting hydrogen production in this study is much less than that for electric vehicles, i.e., 2.14 calculated from the battery roadmap of Japan [45]. Due to the significant demand for batteries for vehicles, the technology development of batteries has been directed for such usage. If this is shifted to assistance for hydrogen production, the required C-rate should be addressed by investigating irradiation patterns and the optimal CapPV .

Please cite this article as: Kikuchi Y et al., Battery-assisted low-cost hydrogen production from solar energy: Rational target setting for future technology systems, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2018.11.119

international journal of hydrogen energy xxx (xxxx) xxx

Conclusion A techno-economic analysis was conducted for off-grid hydrogen production from PV utilizing battery-assisted electrolyzers. A key finding is that battery assistance can contribute to lower-cost hydrogen production when a reasonably cheap battery cost is realized as well as when an appropriate system is configured. The ratios of installed capacities of the PV, battery, and electrolyzer determine whether the battery should be implemented. The realization of the future cost targets in the individual technology roadmaps of PV, electrolyzers, and batteries support cost-competitive hydrogen production in future energy markets. The battery-assisted hydrogen production from PV can become a solution for utilizing renewable energy in distributed systems free from the grid-connection restrictions to avoid an extreme instability induced by the intermittency of the installed PV outputs. The requirement for the C-rate range of batteries is also one of findings of this study. The C-rate of batteries for electric vehicle requires a rapid response for the changes in driving mode as well as the consumer need for quick charging. In contrast, the cycle rate for charging and discharging in battery-assisted hydrogen production are determined by solar irradiation and hydrogen production at the electrolyzer. In this case, the C-rate requirement for the batteries are found to be much slower than that for electric vehicles, while most of battery roadmaps aim to achieve higher C-rates for electric vehicle application. The Crate for batteries clarified in this study can be a rational target of research and development for battery applications in hydrogen production from PV. This study can be an example of rationally setting research and development targets for future advanced technology supported by simulation-based analysis.

Acknowledgements The authors thank Mr. Narihisa Sako for his support in the calculation of hydrogen production costs. Part of this study was financially supported by MEXT Program for Integrated Materials Development and JSPS KAKENHI [16H06126 (Young Scientists A)]. Activities of the Presidential Endowed Chair for “Platinum Society” in the University of Tokyo are supported by the KAITEKI Institute Incorporated, Mitsui Fudosan Corporation, Shin-Etsu Chemical Co., ORIX Corporation, Sekisui House, Ltd., and the East Japan Railway Company.

Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.ijhydene.2018.11.119.

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Please cite this article as: Kikuchi Y et al., Battery-assisted low-cost hydrogen production from solar energy: Rational target setting for future technology systems, International Journal of Hydrogen Energy, https://doi.org/10.1016/j.ijhydene.2018.11.119