Techno-Economic Analysis of Grid-Connected Hydrogen
Production via Water Electrolysis
Pengcheng

Z h u *,

Masahiro

Mae, Ryuji

Matsuhashi

Abstract
As the global energy landscape transitions towards a more sustainable future, hydrogen has emerged as a promising energy
carrier due to its potential to decarbonized various sectors. However, the economic competitiveness of hydrogen production bywater electrolysis strongly depends on the availability of renewable energy sources (RESs). Thus, it is necessary to overcome
the challenges related to the intermittent nature of RESs. This paper presents a comprehensive technoeconomic analysis ofcomplementing green hydrogen production with grid electricity. An evaluation model for the levelized cost of hydrogen(LCOH) is proposed considering both CO2 emissions and the influence of RES fluctuations on electrolyzers. A minimum load
restriction is required to avoid crossover gas. Moreover, a new operation strategy is developed for hydrogen production plants
to determine optimal bidding in the grid electricity market to minimize the LCOH. Simulation results demonstrate that the
proposed strategy can reduce the LCOH and increase hydrogen productivity, without significantly increasing CO 2 emissions.
Key words : Hydrogen production, Water electrolysis, Renewable energy, CO2 emission, Levelized cost of hydrogen(LCOH).

1. Introduction

Therefore, it is necessary to overcome these issues related to the

Nowadays, the high levels of greenhouse gas emissions resulting

intermittent nature of RESs.

in global warming are regarded as one of the major issues

Regarding water electrolysis technologies for hydrogenworldwide [1]. Green hydrogen, produced through waterproduction, we focus on the alkaline technology and proton

electrolysis using renewable energy sources (RESs), has gained

membrane electrolysis (PEM) technology in this study. Alkalinesignificant attention in recent years as a promising solution toelectrolysis is the most mature and commercial technology withaddress global energy and climate challenges. Its potential

over 100 years of history [6]. It is highly durable, and alreadyapplications span across various sectors, including transportation,

available at large scale, with relatively low capital cost [7].

power generation, and industrial processes, making it a versatile

However, this conventional technology is not designed to be

and attractive energy carrier [2]. However, despite theoperated with fluctuating power sources, and it shows a very poorconsiderable progress made in the development of green

performance when the power supply is switched off [5]. PEM

hydrogen production technologies, its large-scale deployment still

electrolysis is relatively resistant to fluctuating power due to its

faces several barriers, primarily due to the intermittent nature offast response and flexible operation, which allows it to provide a

RESs and the high costs associated with electrolysis processes.

service with a larger load range than alkaline electrolysis,Among all RESs, the most used are photovoltaic (PV) and windespecially in the low load range, and to take advantage of dynamic

power generation, which mainly depend on weather conditions

electricity prices [8]. Moreover, PEM electrolysis shows less[3]. Thus, the availability of electricity from RESs is uncertain,

performance degradation when power interruption occurs [5].

affecting both the economy and the safety of water electrolysis.

Thus, it is beneficial in operations with intermittent power sources

On the one hand, a hydrogen production plant cannot work whenlike RESs. However, the high cost of precious metal electrodethe input power is unavailable, which will reduce the operating

catalysts and the shorter lifetime of PEM electrolyzers hinder thehours of the plant and increase total production costs [4]. On thewide deployment of this technology [9].

other hand, the direct use of fluctuating power from RESs will

Theoretically, the influence of RES power fluctuations oncause several problems such as crossover gas and electrolyzer

electrolyzers should be considered when modeling to avoid

degradation, challenging the normal operation of electrolysis [5].

security risks. However, the existing literature usually ignores thisissue to simplify the model [7], or just advocates for PEM
technology by highlighting the limits of alkaline technology*Department of Electrical Engineering and Information Systems
The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
E-mail : zhu@enesys.t.u-tokyo.ac.jp

without a specific techno-economic analysis [10], leading tomisestimation of the actual benefits brought by alkaline1electrolysis [11]. Few authors explicitly model the impacts offluctuating power supply. Thus, how to model the influences offluctuations in electrolyzers remains a challenge.
This paper aims to analyze the techno-economic benefits ofcomplementing green hydrogen production with grid electricity.
An evaluation model for levelized cost of hydrogen (LCOH) is
proposed, including the CO2 penalty, under a wholesale electricity

Fig.1 Grid-connected hydrogen production system.

market. Different capital expenditures (CAPEX) and different

only H2 but also O2. Crossover gas is a mix of H2 and O2, which

operating expenses (OPEX) are evaluated in the proposed model.

can easily explode. From [12], we know that crossover gas

An optimal operation strategy is developed to solve this nonlinear

reaches relatively high concentrations in an alkaline electrolyzer

evaluation model.

when power generation is relatively low, sometimes even more

The main contributions of this paper compared with the existing

than 1% in the experimental simulations, which is dangerous.

literature are as follows:•

Therefore, to keep the crossover gas concentration under control,

An evaluation model for LCOH is proposed, including CO2

it is necessary to set a minimum load restriction for alkaline

emission costs in a wholesale electricity market. It considers bothelectrolyzers. As for PEM electrolyzers, since they can operate

the economic and environmental impacts of grid-connectedwith fluctuating power, there are no minimum load requirements.

systems and can take advantage of dynamic electricity prices.
•

The electrolyzer must stop operating when the power falls below

The influences of RES fluctuations on alkaline and PEM

the operating range. During shutdown, RESs cannot be utilized,

electrolyzers are considered. A minimum load restriction isleading to a reduction in overall energy efficiency.

required to avoid explosion due to high crossover gas

One potential solution is using grid electricity to complement theconcentrations.
•power supply to the electrolyzer. This situation is presented in

A novel operation strategy for hydrogen production plants is

Fig.1. In this case, the electrolyzer will use RES electricity

developed to determine optimal bidding in the grid electricity

whenever it is available and grid electricity when necessary.

market to minimize the LCOH. It can simplify the above

Although the electricity cost and emission cost of grid electricity

optimization problem and solve it without any complex

are higher than that of RES electricity, this method can extend thealgorithms.

operating hours of the electrolyzer, reaching a higher capacity

The remainder of this paper is organized as follows: Section 2

factor and higher hydrogen production. Thus, the electrolyzer inintroduces the grid-connected system for producing hydrogen.

this system is more productive than the only-RES case, reducing

Section 3 presents the LCOH model employed and the optimal

the CAPEX. Moreover, this method can also avoid crossover gas

operation strategy to minimize the LCOH. A case study in theand slow electrolyzer degradation. Thus, there exists a trade-off

Kyushu area is performed to illustrate hydrogen production with

between the unitary CAPEX and average electricity cost andalkaline and PEM electrolyzers. The simulation results are shownemission cost.

in Section 4 to evaluate the performance of the proposed LCOH
model. Finally, conclusions are drawn in Section 5.

3. ModelIn this paper, we perform the optimization in a wholesale

2. Hydrogen production via water electrolysis

electricity market, which is closer to the real situation in Japan.

Green hydrogen production by water electrolysis requires 100%

3.1 Evaluation model for LCOH

RES electricity, such as wind power or solar power, which can be

The objective function of the optimal LCOH can be defined as:

achieved with an off-grid production plant. However, directly

𝑚𝑖𝑛 𝐶𝐿𝐶𝑂𝐻 = 𝑚𝑖𝑛( 𝐶𝑒𝑙 + 𝐶𝐶𝐴𝑃𝐸𝑋 + 𝐶𝑂𝑃𝐸𝑋 + 𝐶𝑒𝑚 )using RES electricity may cause some problems. For RES(1)

where 𝐶𝐿𝐶𝑂𝐻 is the LCOH, 𝐶𝑒𝑙 is the average electricity cost,

electricity, since the RESs are not always available, the plant may

𝐶𝐶𝐴𝑃𝐸𝑋 stands for the CAPEX per unit (“unitary CAPEX”),

work only during certain hours in a day, reducing the operation

𝐶𝑂𝑃𝐸𝑋 represents the OPEX excluding the electricity cost per unit

hours. In this case, the CAPEX is relatively high, usually not at a(“unitary OPEX”), and 𝐶𝑒𝑚 means the average emission cost.

competitive cost. Moreover, for alkaline electrolyzers, theFor the electricity cost, it includes the basic electricity cost andfluctuating power input may lead to crossover gas andthe wheeling charge cost. Here, we assume that only grid

performance degradation [5]. Water electrolysis can produce not2

electricity requires a wheeling charge since the green hydrogendenominator of the equations. Thus, this optimization problem is

production plants are usually in the same place as the RES. Then,nonlinear, which is hard to solve directly. Another limitation isthe average electricity cost 𝐶𝑒𝑙 is as follows:that the electricity spot price cannot be available one year in

𝐶𝑒𝑙 =(𝐶𝑅𝐸𝑆 +𝐶𝑔𝑟𝑖𝑑 +𝐶𝑤ℎ )𝑃𝐻2advance. That is to say, we can only use the historical data to(2)analyze the techno-economic performance.

where

3.2 Operation Strategy in the Wholesale Market𝑡𝑡
𝐶𝑅𝐸𝑆 = ∑𝑡 𝐸𝑅𝐸𝑆
⋅ 𝑃𝑟𝑖𝑐𝑒𝑅𝐸𝑆(3)

In this section, an operation strategy is proposed to determine the𝑡𝑡
𝐶𝑔𝑟𝑖𝑑 = ∑𝑡 𝐸𝑔𝑟𝑖𝑑⋅ 𝑃𝑟𝑖𝑐𝑒𝑔𝑟𝑖𝑑(4)

electricity bidding process for a hydrogen production plant to𝑡
𝐶𝑤ℎ = ∑𝑡 𝐸𝑔𝑟𝑖𝑑⋅ 𝑃𝑟𝑖𝑐𝑒𝑤ℎ(5)𝑡𝑡
𝑃𝐻2 = 𝜂 ∑𝑡(𝐸𝑅𝐸𝑆+ 𝐸𝑔𝑟𝑖𝑑)(6)

minimize the LCOH in the wholesale electricity market.
In this paper, the time-step is set as 30 min, and the period T = 1
year. We can determine the threshold price by analyzing historical

where 𝐶𝑅𝐸𝑆 and 𝐶𝑔𝑟𝑖𝑑 are the total electricity cost of RES anddata. Firstly, we calculate the LCOH at different initial threshold

grid. 𝐶𝑤𝑙 is the total wheeling charge cost. 𝑃𝐻2 means theprices using last year’s electricity prices. Then, we plot a graph of𝑡𝑡amount of hydrogen production. 𝐸𝑅𝐸𝑆
and 𝐸𝑔𝑟𝑖𝑑
stand forthe LCOH against the threshold price, and the threshold price is𝑡electricity used from RESs and the grid in time-step t. 𝑃𝑟𝑖𝑐𝑒𝑅𝐸𝑆

obtained by identifying the point on the figure with the lowest𝑡and 𝑃𝑟𝑖𝑐𝑒𝑔𝑟𝑖𝑑
represent RES and grid electricity prices in time-

LCOH value. The threshold price is determined in a one-year

step t. 𝑃𝑟𝑖𝑐𝑒𝑤𝑙 is the wheeling charge price. η is the efficiency

version, considering the grid price fluctuations throughout theof hydrogen production.

whole year. Next, by comparing the current grid electricity priceTo ensure the total load within the operating range, the above

with the threshold price, the operation state of an electrolyzer isequations are subject to the following constraint:𝑡𝑡
𝐸 𝑡 = (𝐸𝑅𝐸𝑆+ 𝐸𝑔𝑟𝑖𝑑) ∈ [𝐸𝑚𝑖𝑛 , 𝐸𝑚𝑎𝑥 ]

where

𝐸𝑡

𝑡
determined from two scenarios. If 𝑃𝑟𝑖𝑐𝑒𝑔𝑟𝑖𝑑≤ 𝑇𝑃 , the(7)electrolyzer is set as the maximum load to produce more hydrogen.

means the total electricity used in time-step t. 𝐸𝑚𝑖𝑛𝑡
Otherwise (𝑃𝑟𝑖𝑐𝑒𝑔𝑟𝑖𝑑> 𝑇𝑃), hydrogen production will return toand 𝐸𝑚𝑎𝑥 represent the minimum and maximum load for thethe required minimum load. In this case, grid electricity is only

electrolyzers. For an alkaline electrolyzer, the minimum load

used to make up the difference from the minimum load. So, if

restriction here is set to be 10% of the capacity [6]. In the case of𝑡
𝐸𝑅𝐸𝑆≥ 𝐸𝑚𝑖𝑛 , there is no need to consume additional power froma PEM electrolyzer, the minimum load is set as zero.

𝑡
the grid. Finally, the LCOH can be calculated with 𝐸𝑔𝑟𝑖𝑑. The

The unitary CAPEX can be calculated as the quotient between
the annualized CAPEX,

𝑎𝑛𝑛𝑢𝑎𝑙
𝐶𝐶𝐴𝑃𝐸𝑋

procedure is applied for every time-step within the period.

and the annual production ofhydrogen, 𝑃𝐻2𝑎𝑛𝑛𝑢𝑎𝑙 , as follows:
𝐶𝐶𝐴𝑃𝐸𝑋 =4. Case study
𝑎𝑛𝑛𝑢𝑎𝑙
𝐶𝐶𝐴𝑃𝐸𝑋

𝑃𝐻2𝑎𝑛𝑛𝑢𝑎𝑙(8)

4.1 Data source
The proposed model is general and can be applied to any area

The unitary OPEX can be obtained as:(9)with significant RES potential. To illustrate the proposed model,

where 𝑂𝑃𝐸𝑋𝑓𝑖𝑥𝑒𝑑 is the fixed cost, such as the maintenance cost

we choose the Kyushu area to perform the case study due to theand employee salaries, and 𝑂𝑃𝐸𝑋𝑣𝑎𝑟 is the variable cost

relatively high penetration rate of RESs, especially PV installation.

depending on total hydrogen production volume, for example, theThe simulation data used in this paper come from previous

water consumption cost.

literature and real data from the Japan electricity market [6,13,14].

We assumed that there is no CO2 emission related to RES

The LCOH of hydrogen production adopting the proposed

electricity. Thus, the average emission cost can be calculated as

operation strategy is simulated in the following four cases:

follows:

Case 1: alkaline electrolyzer using solar power.

𝐶𝑂𝑃𝐸𝑋 = 𝑂𝑃𝐸𝑋𝑓𝑖𝑥𝑒𝑑 + 𝑂𝑃𝐸𝑋𝑣𝑎𝑟

𝐶𝑒𝑚 =

𝑡
𝜆⋅𝜇𝑡𝑎𝑥 ⋅∑𝑡 𝐸𝑔𝑟𝑖𝑑

𝑃𝐻2

Case 2: alkaline electrolyzer using wind power.

(10)

Case 3: PEM electrolyzer using solar power.

where 𝜆 is the emission factor, which presents the CO2 emission

Case 4: PEM electrolyzer using wind power.

related to the grid electricity used, and 𝜇𝑡𝑎𝑥 is the CO2 tax.

There are three scenarios as follows:

Finally, the LCOH can be obtained by adding the result of (2),Scenario 1: using only RES electricity.

(8), (9), and (10). However, regarding the evaluation models, theScenario 2: using both RES and grid electricity in a wholesale𝑡𝑡
𝑃𝐻2 , which can be calculated by 𝐸𝑅𝐸𝑆
and 𝐸𝑔𝑟𝑖𝑑, is in theelectricity market.
3

Scenario 3: using both RES and grid electricity under the

restriction for alkaline electrolyzers. Fig.4 also shows the CO2

average pricing scheme [13].

emission levels for the four cases. The emission levels are affected

4.2 Optimization resultsby both the grid electricity proportion and electrolyzer efficiency.

Based on data FY2020, we have obtained the threshold prices

Moreover, compared to directly using coal (20 kg CO2/kgH2) orfor different cases. Then, based on data FY2021 and the thresholdnatural gas (8.5 kgCO2/kgH2) [6], CO2 emissions when either

prices, we can obtain the optimization results of the LCOH in

using alkaline or PEM electrolysis are always lower than those

FY2021 for each case. The results are presented in Fig.2. Amongproduced by fossil-fueled hydrogen production. Therefore,

the three scenarios, the proposed method has the lowest LCOH,

complementing green hydrogen production with grid power can

proving its effectiveness. In particular, when the electricity supply

reduce the LCOH, increase hydrogen productivity, and keep CO2

is supplemented with grid electricity in a wholesale electricity

emissions within an acceptable range.

market, the LCOH decreases by 11% to 33% in the four cases,
which is much lower than the only-RES scenario. This is because
the hydrogen production increase impacts more than the rise ofelectricity and emission costs. However, the average pricescenario shows poor performance in the alkaline cases, and the
LCOH is even higher than the only-RES scenario. On the other
hand, in the PEM cases, although the LCOH is still higher thanscenario 2, it is lower than the only-RES scenario. This is because
using the average electricity price means dynamic electricity
prices cannot be taken advantage of, resulting in an increase inaverage electricity costs.
Fig.3 Hydrogen productivity for the four cases.
⬇30%
⬇33%
⬇11%
⬇30%

Fig.2 Optimal LCOH for 4 cases.
Hydrogen productivity and emission cost are presented in Fig.3.

Fig.4 Hydrogen productivity and emissions for scenario 2.

Here, hydrogen productivity means the amount of hydrogen

4.3 Sensitivity Analyses

production per year and per unit capacity of the electrolyzers. We

It is necessary to illustrate the effectiveness of the threshold pricecan observe that, for all cases, hydrogen productivity connecting

used in this paper, as it is calculated using historical data.

to the grid increases by 86% to 140% compared with the only-

Meanwhile, as electrolysis technology continues to develop, theRES electricity scenario. It may be reasonable for a hydrogen

CAPEX and efficiency are expected to change to reachplant to choose to inject grid power to increase hydrogencommercial maturity. In addition, the CO2 tax will be increased

production and gain more profits. However, the CO2 emissions

by the Japanese government to further emphasize the importance

related to hydrogen production will increase. Fig.4 presents theof carbon neutrality. Therefore, in order to analyze how these

specific hydrogen productivity and emissions for scenario 2.

changes will affect the LCOH, sensitivity analyses are applied toWhen compared to scenario 1, the production from RES

the above variations. For simplicity, these sensitivity analyses areelectricity in alkaline cases increases, while that in PEM cases

only presented for case 1, but similar qualitative results can beremains the same. This is because more RES electricity can beobtained in the other cases.

utilized by injecting grid power to meet the minimum load
4

The threshold price sensitivity is shown in Fig.5. We can observethat each component of the LCOH is strongly affected by thethreshold price. When the threshold price is relatively low, there
is a decrease in the LCOH as shown. This situation occurs because
the reductions in the CAPEX and other OPEX are higher than theincreases in electricity cost and emission cost with the cheap
electricity prices. On the other hand, when the threshold price isrelatively high, the increase in electricity cost is much higher than
the reductions in the CAPEX and other OPEX, resulting in an
increase in the LCOH. In addition, the reference threshold pricebased on last year’s data is the threshold price used in previous

Fig.6 Sensitivity analysis for the CAPEX.

analyses. It can be observed that the LCOH related to thereference threshold price is approaching the lowest point of the
LCOH. That is to say, we can decrease the LCOH to close to theminimum value. Therefore, the operation strategy we used canobtain an approximate optimal result, proving its effectiveness.

Fig.7 Sensitivity analysis for the efficiency
slightly raise the LCOH. This is because the tax penalty imposed
on CO2 emissions is currently low in Japan, at only 289 JPY/t CO2.
The low CO2 tax also has a minimal effect on determining thethreshold price. The Japanese government is planning to increase
Fig.5 Sensitivity analysis for the threshold price.

the CO2 tax, which means that in the future, the cost of CO2

The result of the sensitivity analysis for the CAPEX is shown inemissions will have a more significant impact on the LCOH. To

Fig.6. It can be observed that as the CAPEX increases, the LCOH

further analyze the influence of CO2 emission costs, we chose thealso increases proportionally. However, when the CAPEX is

CO2 reduction credit offered by the J-credit Institution, which

relatively high, the impact on the LCOH becomes less significant.

equals 1500 JPY/t CO2, for the sensitivity analysis. The results areThis is because cheap grid electricity can offset the effects of aillustrated in Fig.9. After the CO2 price increases compared to thehigh CAPEX to a certain extent. Based on the sensitivity analysis

current CO2 tax, we observe a larger impact on the LCOH. In

for electrolyzer efficiency presented in Fig.7, the LCOH willother words, environmental factors will have a more significant

decrease when the electrolyzer efficiency increases. This is

impact on the economy with higher CO2 prices.

because the higher efficiency means more hydrogen production

5. Conclusion

with the same energy input, leading to a lower LCOH. However,This paper analyzes

it is necessary to note that diminishing returns occur when thecomplementing green hydrogen production with grid electricity.

efficiency is relatively high. In general, both the CAPEX and the

A model is proposed to evaluate the LCOH, including CO2

efficiency of the electrolyzer have a significant impact on theemissions, to minimize the LCOH in the wholesale electricity

LCOH. To reduce hydrogen production costs in the future, it may

market. The proposed model considers the influence of power

be more effective to concentrate on improving electrolyzer

fluctuations from RESs on water electrolysis, especially thetechnologies, such as reducing capital costs and enhancing

minimum load restriction of alkaline electrolyzers to avoid

electrolysis efficiency.

crossover gas. Moreover, an optimal operation strategy is

In Fig.8, the results of the sensitivity analysis for the CO2 tax aredeveloped to solve the above nonlinear optimization problem. By

presented. It can be observed that an increase in the CO2 tax will

injecting grid electricity, the LCOH decreases by 11% to 33%,
5

thetechno-economic benefits of

compared to using an only-RES supply. Hydrogen productivity

5)

increases by 86% to 140%, while CO2 emission levels are

Kojima, H.; Nagasawa, K.; Todoroki, N.; Ito, Y.; Matsui, T.;
Nakajima, R. Influence of renewable energy power

maintained within an acceptable range.

fluctuations on water electrolysis for green hydrogenproduction. Int. J. Hydrogen Energy 2023, 48, 4572–4593.
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Available online: https://www.iea.org/reports/the-future-ofhydrogen (accessed on 10 December 2022).

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Schmidt, O.; Gambhir, A.; Staffell, I.; Hawkes, A.; Nelson,
J.; Few, S. Future cost and performance of waterelectrolysis: An expert elicitation study. Int. J. Hydrogen
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Kumar, S.S.; Himabindu, V. Hydrogen production by PEM
water electrolysis—A review. Mater. Sci. Energy Technol.
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