NREL is a national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

Operated by the Alliance for Sustainable Energy, LLC

This report is available at no cost from the National Renewable Energy

Laboratory (NREL) at www.nrel.gov/publications.

Contract No. DE-AC36-08GO28308

Economic Assessment of 

Hydrogen Technologies 

Participating in California 

Electricity Markets

Joshua Eichman, Aaron Townsend, and 

Marc Melaina

National Renewable Energy Laboratory

Technical Report

NREL/TP-5400-65856

February 2016
NREL is a national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

Operated by the Alliance for Sustainable Energy, LLC

This report is available at no cost from the National Renewable Energy

Laboratory (NREL) at www.nrel.gov/publications.

Contract No. DE-AC36-08GO28308

National Renewable Energy Laboratory

15013 Denver West Parkway

Golden, CO 80401

303-275-3000 • www.nrel.gov

Economic Assessment of 

Hydrogen Technologies 

Participating in California 

Electricity Markets

Joshua Eichman, Aaron Townsend, and 

Marc Melaina

National Renewable Energy Laboratory

Prepared under Task No. HT12.2A15

Technical Report

NREL/TP-5400-65856

February 2016
NOTICE

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or favoring by the United States government or any agency thereof. The views and opinions of authors 

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Acknowledgements

The authors thank Dr. Susan Schoenung (Longitude 122 West, Inc.) and Mike Penev (National 

Renewable Energy Laboratory) for their reviews and comments during the publication process. 

This work was supported by the U.S. Department of Energy under Contract No. DE-AC36-

08GO28308 with the National Renewable Energy Laboratory. Funding was provided by the U.S. 

Department of Energy’s Fuel Cell Technologies Office in the Office of Energy Efficiency and 

Renewable Energy.
iv

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List of Abbreviations and Acronyms

CAISO California Independent System Operator

FOM fixed operation and maintenance

FC fuel cell

NREL National Renewable Energy Laboratory

SMR steam methane reformer

VOM variable operation and maintenance
v

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Executive Summary

As the electric sector evolves and increasing amounts of variable renewable generation are 

installed on the system, there are greater needs for system flexibility and sufficient capacity, and 

greater concern for overgeneration from renewable sources not well matched in time with 

electric loads. Hydrogen systems have the potential to support the grid in each of these areas. 

However, limited information is available about the economic competitiveness of hydrogen 

system configurations. 

This paper quantifies the value for hydrogen energy storage and demand response systems to 

participate in select California wholesale electricity markets using 2012 data. For hydrogen 

systems and conventional storage systems (e.g., pumped hydro, batteries), the yearly revenues

from energy, ancillary service, and capacity markets are compared to the yearly cost to establish 

economic competitiveness. 

Hydrogen systems can present a positive value proposition for current markets. Three main 

findings include: 

1. For hydrogen systems participating in California electricity markets, producing and 

selling hydrogen was found to be much more valuable than producing and storing 

hydrogen to later produce electricity; therefore systems should focus on producing and 

selling hydrogen and opportunistically providing ancillary services and arbitrage. 

2. Tighter integration with electricity markets generates greater revenues (i.e., systems that 

participate in multiple markets receive the highest revenue). 

3. More storage capacity, in excess of what is required to provide diurnal shifting, does not 

increase competitiveness in current California wholesale energy markets. 

As more variable renewable generation is installed, the importance of long duration storage may 

become apparent in the energy price or through additional markets, but currently, there is not a 

sufficiently large price differential between days to generate enough revenue to offset the cost of 

additional storage. Future work will involve expanding to consider later year data and multiple 

regions to establish more generalized results. 
vi

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Table of Contents

1 Introduction........................................................................................................................................... 1

2 Previous Studies on Grid Revenue Calculation and Hydrogen Flexibility..................................... 2

3 Hydrogen System Configurations ...................................................................................................... 4

4 Modeling Approach and Data Sources .............................................................................................. 6

4.1 Revenue Optimization................................................................................................................... 7

4.2 Cost Calculations......................................................................................................................... 11

4.3 System Configurations................................................................................................................ 12

5 Results................................................................................................................................................. 14

6 Conclusions ........................................................................................................................................ 18

7 Future Work......................................................................................................................................... 19

8 References .......................................................................................................................................... 20
vii

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List of Figures

Figure 1. Hydrogen technology configurations....................................................................................... 5

Figure 2. Example of optimized operation for an electrolyzer and fuel cell storage system for two 

consecutive days.................................................................................................................................. 9

Figure 3. Comparison of cost versus electricity market revenue for conventional and hydrogen 

technologies ($3–$10/kg represents a range of potential sale prices for hydrogen).................. 15

Figure 4. Breakdown of electricity market revenues with a hydrogen sale price of $3/kg ............... 16

Figure 5. Storage capacity sensitivity analysis for “FC-EY All” from 3 to 168 hours of storage ..... 17

List of Tables

Table 1. Historical Energy, Ancillary Service, and Natural Gas Prices for CAISO in 2012a ................ 6

Table 2. Technology Assumptions............................................................................................................ 8

Table 3. List of System Configurations .................................................................................................. 12
1

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1 Introduction

Hydrogen is a versatile element that can be used in a variety of applications including chemical 

and industrial processes (Bourgeois 2007; Ramachandran and Menon 1998), as a transportation 

fuel (Green et al. 2008), and as a heating fuel for heating, cooking, power generation, etc. (De 

Vries et al. 2007; Gahleitner 2013). Traditionally, hydrogen technologies focus on providing 

services to only one sector; however, because of the versatility of hydrogen, it has the ability to 

enable multi-sector interactions between transportation, electricity, commercial, and industrial

sectors. There are a variety of challenges in each sector: for example, clean and inexpensive fuels 

are needed for the transportation sector, grid balancing and renewable integration are needed for 

the electricity sector, and clean and inexpensive feedstocks are needed for chemical and 

industrial uses. By engaging multiple sectors, hydrogen has the potential to provide benefits to 

each sector and increase its revenue streams.

There is a strong interest in exploring opportunities to supplement revenue while supporting the 

electric grid; however, there are limited studies that explore the economic value of hydrogenbased energy systems, and even fewer that focus on North America. The goal of this study is to 

explore promising configurations for hydrogen systems that can interact with the electric grid 

and sell hydrogen. System configurations include both energy storage and demand response.

Several conventional energy storage technologies are included in this study for comparison. This 

comparison is essential to facilitate a discussion of wider implementation of hydrogen 

technologies. Revenues are calculated by co-optimizing energy, ancillary services, and hydrogen 

production to maximize operational profits.

To determine economic competitiveness, revenues from providing grid services and the sale of 

hydrogen are compared to the capital cost and operating expenses over the lifetime of the 

equipment. Results focus on the achievable value from several selected current electricity 

markets in California and include energy and ancillary services for grid balancing and reliability,

as well as capacity for resource adequacy.
2

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2 Previous Studies on Grid Revenue Calculation and 

Hydrogen Flexibility

Several studies have analyzed the concept of using electrolyzers both with and without fuel cells 

to smooth renewable generation, provide grid services, and benefit from the price difference in 

on-peak and off-peak electricity (Kroposki et al. 2006; Saur and Ramsden 2011; Steward et al. 

2009; EY et al. 2013). These studies establish that there are opportunities for electrolyzers to 

access lower cost electricity for hydrogen production by making use of different electricity 

markets and rate structures as well as utilizing curtailed renewable energy. The potential of 

integrating renewables with hydrogen technologies was demonstrated in projects at the National 

Renewable Energy Laboratory (NREL) (Harrison et al. 2009) and the University of North 

Dakota (Rebenitsch et al. 2009), among others. These projects demonstrate how renewable 

generation can be combined with electrolyzers to generate renewable hydrogen that can be used 

for a variety of applications. One application receiving growing interest, particularly in 

Germany, is injection of hydrogen or methanized hydrogen into the natural gas pipeline

(Gahleitner 2013; EPRI 2014; Grond et al. 2013). Methanation is the process by which carbon 

oxides are combined with hydrogen to form methane. This idea, also called power-to-gas, could 

enable greater uptake of curtailed renewables by providing supply-side flexibility for the 

electricity sector while reducing carbon dioxide emissions for systems using the natural gas grid.

The technical feasibility for hydrogen technologies to participate in electricity markets has been 

explored by Eichman et al. (2014), Hydrogenics (2011), and ITM Power (2014). It was found 

that electrolyzers are sufficiently responsive to provide grid services including operating 

reserves, frequency regulation and load-following. These studies show that there is both interest 

and potential for hydrogen technologies to participate in wholesale electricity markets and 

opportunity to enhance their revenue.

For this study, an operations optimization model is used to calculate the revenue from 

participation in one or more markets. The model optimizes revenue from electricity, ancillary 

service, and hydrogen production markets using historical price data to determine the maximum 

achievable revenue under the assumption that the equipment is not large enough to impact the 

electricity and hydrogen market prices. This “price-taker” approach has been used extensively 

for optimization within energy markets (Sioshansi et al. 2009; Spisto 2014) and also for cooptimization of both energy and ancillary services markets (Cutter et al. 2014; Drury et al. 2011; 

Kirby 2012). More detail on the model is provided in the following sections. In addition to 

exploring value from different services, those other studies explore the differences in the value of 

storage for different sizes, locations (California Independent System Operator [CAISO],

Pennsylvania-New Jersey-Maryland Interconnection, New York Independent System Operator,

and Italy), years (2002–2013), and technologies (pumped hydro, combustion turbine, compressed 

air energy storage, and conventional battery). Those studies also look at the importance of 

uncertainty in optimal dispatch. Storage revenue values ranged from $12/kW-yr to $94/kW-yr 

for systems providing only energy and from $33/kW-yr to $143/kW-yr for systems providing 

both energy and ancillary services.

To the authors’ knowledge the present work represents the first time that this strategy has been 

applied to hydrogen technologies. The goal of this work is to assess the economic viability of 

hydrogen storage systems and determine the revenue potential for participating in selected 
3

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electricity markets. This study includes an assessment of the day-ahead energy market and 

several ancillary services: frequency regulation up and down, spinning reserve, and non-spinning 

reserve. The prices are all drawn from the day-ahead markets. This study does not consider realtime market prices or potential future market products including flexible ramping and reactive 

power.
4

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3 Hydrogen System Configurations

Three hydrogen technologies were analyzed: electrolyzers (EY), hydrogen fuel cells (FC), and 

steam methane reformers (SMR). While there are many different types of fuel cells and 

electrolyzers, generally, a fuel cell electrochemically combines oxygen and hydrogen to generate 

electricity and water. Similarly, an electrolyzer electrochemically converts electricity and water 

to hydrogen and oxygen. A steam methane reformer splits methane through a series of chemical 

reactions to produce hydrogen and carbon dioxide.

Figure 1 provides a schematic for how each piece of equipment interacts with the electricity and 

natural gas grids. Electrolyzers and hydrogen fuel cells interact with the electric grid and produce 

or consume hydrogen while providing grid services. The steam methane reformer and pipeline 

injection, either directly or using methanation, interact with the natural gas grid and produce or 

consume hydrogen. In this way produced hydrogen, particularly from electrolyzers, can be stored 

in the natural gas grid. While not considered in this work, it is also possible to selectively remove 

injected hydrogen from the natural gas system at some downstream location (Melaina et al. 

2013). That pathway could be especially appropriate for large penetrations of hydrogen injection.

Hydrogen or natural gas on the gas grid can be used by fuel cells or conventional combustionbased generation equipment to generate electricity. Additionally, by using a renewable source of 

electricity electrolyzers can produce renewable hydrogen. Hydrogen made from the electrolyzer 

or reformer can be used in any of the output equipment including a fuel cell for power 

generation, fuel cell vehicles, chemical and industrial processes, or for pipeline injection. This 

work includes explicit modeling of the electrolyzer, stationary hydrogen fuel cell, and steam 

methane reformer, but it does not differentiate on the downstream uses of hydrogen for vehicles, 

pipeline injection, or industrial processes; rather it assumes a price that hydrogen is sold 

independent of the market.

The flexibility of hydrogen systems creates many opportunities for system design. Different 

combinations of equipment can enable interactions with different sectors; however, not all 

pathways represent viable business cases in the near-term. The purpose of the following analysis 

is to establish which configurations are economically viable and discuss which configurations

offer unique opportunities with current near-term market conditions. System configurations for 

this analysis are discussed in a later section and involve a variety of combinations of the 

hydrogen equipment presented in Figure 1.
5

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Figure 1. Hydrogen technology configurations

Photos by: (from top left by row) Warren Gretz, NREL 10926; Matt Stiveson, NREL 12508; Keith Wipke, 

NREL 17319; Dennis Schroeder, NREL 22794; NextEnergy Center, NREL 16129; Warren Gretz, NREL 

09830; David Parsons, NREL 05050; and Bruce Green, NREL 09408
6

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4 Modeling Approach and Data Sources

To explore the value of hydrogen systems the maximum achievable revenue is calculated using 

an optimization model (section 4.1) and compared to the annualized system cost from a cost 

model (section 4.2) to determine economic competitiveness for twelve scenarios (section 4.3).

Revenue streams include energy, ancillary service, and capacity markets as well as the sale of 

hydrogen at a range of prices to reflect different products. Not all electricity market products are 

modeled herein. This analysis uses day-ahead historical data for California electricity markets. A 

variety of end uses for hydrogen can be considered and this study focuses on the highest valued 

products, which are presently sale as a transportation fuel or as an industrial product.

The ancillary service markets explored for this analysis include regulation up and down, spinning 

reserve, and non-spinning reserve. Flexible ramping products are not included in this analysis. 

Regulation up and regulation down are used to maintain grid frequency by balancing energy 

imbalances. Regulation up means adding power from a generation source (or decreasing load), 

while regulation down means reducing input power or increasing load. Spinning and nonspinning reserves are used in contingency events where regulation and other responsive markets 

are not able to sufficiently correct an energy imbalance, for example in the event of a generator 

failure. As their names suggest, spinning reserve is capacity available for dispatch immediately 

while non-spinning reserve is capacity that is not online but can rapidly turn on.

Hourly day-ahead electrical energy and ancillary service prices for 2012 are taken from CAISO’s

Open Access Same-Time Information System (CAISO 2015). Monthly natural gas prices for 

California are drawn from the Energy Information Administration (EIA 2014). The historical 

average and range of CAISO prices for 2012 are shown in Table 1. The average price of energy 

is the highest, followed by regulation up and down, then spinning reserve and non-spinning 

reserve. While provision of energy is compensated for each unit of energy provided ($/MWh), 

ancillary services are typically offered as capacity products ($/MW) and called upon as 

necessary, and capacity value is a yearly payment based on the capacity provided ($/MW-yr).

Systems that are held for reserves receive the reserve price and if they are called to provide 

energy, they receive the energy price.

Table 1. Historical Energy, Ancillary Service, and Natural Gas Prices for CAISO in 2012a

Electricity 

($/MWh)

Reg. Up 

($/MW)

Reg. 

Down 

($/MW)

Spin 

Res. 

($/MW)

Non-Spin

Res.

($/MW)

Nat. Gas 

($/MMBtu)

Capacity 

Value

($/MW-yr)b

Average 30.0 5.7 4.4 3.3 0.9 3.6 150

Maximum 179.4 129.7 25.6 129.7 129.7 4.4 150

Minimum -59.4 0.0 0.0 0.0 0.0 3.0 150

a CAISO (2015); EIA (2014)

b Pfeifenberger et al. (2012)
7 

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4.1 Revenue Optimization

For this analysis, a variety of revenue streams are evaluated: energy revenues, ancillary service 

revenues, capacity revenues, and hydrogen sales. Revenues are maximized using an operations 

optimization model. These streams are described below.

Energy services include the purchase and sale of electricity. Ancillary services for this analysis 

include regulation up and down, spinning reserve, and non-spinning reserve. The value of 

providing capacity resources varies based on the type of capacity provided. New capacity to 

support resource adequacy within California can be valued at $150–$300/kW-yr according to 

Pfeifenberger et al. (2012). A value of $150/kW-yr is selected as the capacity revenue based on 

the cost for new market entry. 

The last revenue stream is from the sale of hydrogen produced at a facility. This analysis only 

includes the cost of production and not compression or delivery costs for sale to customers. A

range of hydrogen production prices from $3/kg to $10/kg are explored. This range represents 

the range of potential prices at which hydrogen can be sold from a production facility. The low 

value represents the U.S. Department of Energy target of $2–$4 per gallon gasoline equivalent 

without tax (DOE 2012). Because one gallon of gasoline contains the same energy content as one 

kilogram of hydrogen on a lower heating value basis (33.3 kWh), the target of $2–$4 per gallon 

gasoline equivalent can be translated to $2–$4 per kilogram hydrogen for production only (which 

does not include compression or delivery). The high value of $10/kg is selected for comparison. 

Depending on the market where hydrogen is sold, the sale price of hydrogen will be different. 

For example, selling hydrogen as a heating fuel in North America returns a lower value than

does selling it as a transportation fuel or industrial product. Using a range enables the reader to 

select a value for hydrogen and judge its competitiveness. 

The objective of the model is to maximize the operational profits of the candidate system. The 

operational profits are the sum of its revenues (including net revenues from electricity 

[ ], ancillary services [ ], capacity [ ] and hydrogen [ ]) less the sum of 

its costs (including assumed cost of natural gas [ ], variable operations and maintenance costs 

[ ], and startup costs [ ]) as shown in Equation 1. 

Operational Profits = + + + Eq. 1

In general, the system can earn revenue by performing price arbitrage (buying electricity when 

the electricity price is low and storing the energy until the electricity price is high), providing 

ancillary services to the grid, providing system capacity, or, for hydrogen technologies, 

producing and selling hydrogen. The operations optimization model determines which of these 

operations the system should pursue at each time step in order to maximize its operational profit. 

This optimization takes into account system parameters including efficiency, power capacity, 

energy capacity, and minimum part-load (i.e., maximum turndown) as shown in Table 2. Sources 

for the values in Table 2 are listed in the notes below the table. The first two technologies, 

pumped hydro and lead acid batteries, provide a comparison to conventional energy storage. 

Hydrogen technologies include a stationary hydrogen fuel cell, an electrolyzer, and a steam 

methane reformer. Many of the sources for cost values are not specific about the type of fuel cell 

or electrolyzer. Based on the assumed minimum part load and efficiencies in Table 2, this study 
8

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most closely reflects a proton exchange membrane fuel cell but also could be extended to an 

alkaline fuel cell or electrolyzer.

Table 2. Technology Assumptions

Properties Pumped 

Hydro

Lead Acid 

Battery

Stationary

H2 Fuel Cell

Electrolyzer Steam Methane 

Reformer

Rated power capacity 

(MW) 1.0 1.0 1.0 1.0 400 kg/day

Energy capacity 

(h at rated capacity) 8 4 8 8 8

Capital cost ($/kW) 1,500a–2,347b 2,000a–4,600a 1,500c–5,918b 430c–2121d 427–569 $/kg/daye

Fixed O&M ($/kW-yr) 8a–14.27b 25a–50a 75–296

(5% of capital) 42e 5.14–5.92% of capitale

H2 storage cost ($/kg) - - 623f–1000 623f–1000 623f–1000

Installation cost 

multiplier 1.2 1.2 1.2e 1.2e 1.92e

Lifetime (yr) 30 12a (4,400 h) 20 20e 20e

Interest rate 7% 7% 7% 7% 7%

Efficiency 80% AC/ACa 90% AC/ACa 40% LHV 70% LHV 0.156 MMBtu/kge

0.6 kWh/kge

Minimum part-load 30%g 1% 10% 10%h 100%i

a EPRI (2010).

b EIA (2012).

c DOE (2012).

d Saur (2008).

e DOE (2015).

f Steward et al. (2009).

g Levine (2003).

h Eichman et al. (2014).

i SMR unit power can be modulated but because the electric consumption for SMR is minimal and this 

study is focused on assessing electric grid impacts, for this study it is assumed that SMR operates 

baseload.

Based on the input prices and values in Table 2, the model can calculate the maximum revenue 

from operating each system. Figure 2 shows an example operation of a hydrogen energy storage 

system consisting of an electrolyzer, storage container, and fuel cell for two consecutive days. 

The top left figure shows the power level for the hydrogen fuel cell and electrolyzer. Negative 

values represent electricity consumption by the electrolyzer and positive values represent 

electricity generation by the fuel cell. The top right figure shows inputs (electrolyzer) and 

outputs (fuel cell and sale of hydrogen) from the storage system. The bottom two figures show 

the ancillary services that can be provided. Notice the mixture of services. In each time step the 

system might do one or more of the following: sit idle; buy electricity and store or sell hydrogen; 

use hydrogen to generate and sell electricity; provide one or more ancillary services; or any 

combination of these activities. For this analysis, time steps are hourly for an entire year, based 

on the availability of pricing data; however, the process is the same for data with higher temporal 

resolution.
9

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For generators, electricity production and provision of ancillary service is more straightforward 

to describe. A device can generate electricity for energy markets with part of its capacity (down 

to its minimum part-load point) and provide ancillary services with the remaining capacity. A 

generator can provide upward reserve products (regulation up and spinning reserve) with the 

remaining unused capacity and downward products (regulation down) with the capacity that it is 

provided to energy markets. The generator must be off or idle to provide non-spinning reserve. 

The principle is similar for demand response devices (e.g., electrolyzers) but in reverse. An 

electrolyzer can reduce its electricity consumption to reduce demand on the grid and act as a 

virtual power plant while also providing ancillary services. A demand response device can direct 

unused capacity to provide downward reserve products and can provide upward products with 

the capacity that is consuming electricity.

Figure 2. Example of optimized operation for an electrolyzer and fuel cell storage system for two 

consecutive days

The modeled system is subject to several constraints. Constraints include the minimum and 

maximum output and input power levels for the electrolyzer and fuel cell, minimum and 

maximum storage levels, maximum ancillary service provision,

1 minimum operation conversion 

 1 Maximum ancillary service provision establishes the range of capacity that a system can bid into the ancillary 

service markets. This depends on both the storage system and the market in which it is operated. For this analysis we 

assume that storage systems can offer their full capacity to ancillary service markets as long as the minimum power 

levels are respected.
10 

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efficiency, and hydrogen sales requirements. All these constraints are preserved during model 

operation. Apart from the maximum ancillary service provision constraint, it is assumed that 

there are no limitations on operational flexibility (i.e., each system can handle ramp rates greater 

than its maximum power per interval length of one hour [Eichman et al. 2014]). 

The model accepts as inputs the electricity and ancillary services prices, hydrogen prices, and 

operational characteristics of the candidate system and returns the maximum achievable 

operating profits that the system could earn. The model has perfect knowledge of all prices in the 

year, and therefore the optimization achieves the maximum possible operational profits. 

Additionally, this model assumes that the systems are sufficiently small such that their operation 

does not affect any of the system prices. Revenue calculations are shown below and additional 

details on the price-taker formulation are shown in Townsend (2013).

The net revenues from electricity can be expressed as follows:

= Eq. 2

where is the price of electricity at any time t, is the output device power (e.g., fuel 

cell, turbine, other generator) and is the input device power (e.g., electrolyzer, SMR, 

compressor, other charging device). In the case of batteries the output and input devices are the 

same. The net revenue for electricity is the sum of all intervals from time, i=1, to the end of the 

simulation, n (i.e., one year in hourly time steps). 

Revenues for ancillary services are calculated as follows:

= + + ( + ) + + +

+

Eq. 3

where is the price, is the output device, is the input device, and the superscripts refer to 

each ancillary service product. RU is regulation up, RD is regulation down, SP is spinning 

reserve, and NS is non-spinning reserve. Devices can generate or consume electricity while also 

providing reserves as long as the operational parameters are not violated (e.g., minimum and 

maximum power level and the maximum ancillary service provision).

Resource adequacy capacity revenue ( ) is the product of the assumed capacity value 

(e.g., $150/kW-yr for new market entry) and the equipment power capacity (e.g., 1 MW). The 

result is a fixed payment for technologies that can provide dispatchable capacity.

For devices that use natural gas for fuel (only the SMR in this study), the cost of fuel must also 

be considered as follows:

= + Eq. 4

where is the price of natural gas and and refer to the heat rate (i.e., thermal energy 

in divided by electrical energy out) for the output and the input devices, respectively. 
11 

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The model has the ability to include the impact of variable operation and maintenance (VOM) on 

the revenues. Currently, hydrogen systems deployed to date have a relatively flat operating 

profile and are not dispatched to provide ancillary services. As a result, an empirical basis for the 

VOM price ( ) is not available. For this analysis the VOM price for both the input and 

output devices is assumed to be zero. As dynamic operation of hydrogen equipment increases 

and these values become available, they can be included in the analysis as follows:

= , + ,

Eq. 5

Similarly, the ability to implement a startup cost is integrated into the model (Equation 6), but a 

representative cost for a startup ( ) has not yet been identified from operational systems. 

Therefore, until more data are available for hydrogen systems the startup cost is assumed to be 

negligible. 

= , + ,

Eq. 6

The last revenue stream is from the sale of hydrogen and is expressed as follows: 

= Eq. 7

where is the price of hydrogen and is the amount of hydrogen sold from storage. For 

this analysis a fixed hydrogen price, which does not change with time, is used. 

The storage level is maintained using the following equation at every time step:

= / + Eq. 8

where is the storage level and and are the efficiency for the output and input 

devices, respectively. 

Outputs from the model include, most notably, the time-resolved operating profiles for the output 

and input devices, storage level, and each revenue stream. The model is written in GAMS 

(Rosenthal 2014) and is based on the model described in Townsend (2013). 

4.2 Cost Calculations

System cost comprises capital cost, fixed operation and maintenance (FOM) costs, and a cost 

multiplier for installation. The total system cost is annualized over the equipment lifetime with 

an assumed 7% interest rate as shown in Equation 9. For this analysis it is assumed that there is 

no initial equity investment and taxes are not included. This analysis does not require a specific 

chemistry for the stationary hydrogen fuel cell or electrolyzer to be selected; however, cost and 

performance values are most similar to proton exchange membrane systems.

= + (1 + ) 1

Eq. 9
12 

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Net Present Cost is the summation of all capital costs and FOM costs over the lifetime of the 

equipment, is the interest rate, and is the lifetime of the equipment.

Electricity markets and natural gas prices represent 2012 values for California. It is assumed that 

the price profiles are the same for each year for the lifetime of the equipment. The authors 

recognize that the prices will change from year to year. However, with additional renewables and 

changes to markets within California, it is unclear how the prices will be affected (Hummon et 

al. 2013; Weron 2014), so for this study price profiles are assumed to be the same from year to 

year.

The capital cost and FOM costs in the results represent a range from current costs to more 

optimistic future costs. Power rating for each technology is 1 MW and the steam methane 

reformer is sized to produce the same amount of hydrogen that is sold by the other systems (400 

kg/day).

2 Default values for energy storage capacity are shown in Table 2; however, a sensitivity 

analysis is performed on the energy storage capacity to explore the value of additional storage 

for hydrogen systems. Additionally, the cost of hydrogen storage is only applied once for 

systems combining an electrolyzer and a fuel cell because they share the same storage system.

4.3 System Configurations

Twelve unique configurations are analyzed for cost competitiveness. A summary of the 

configurations is shown in Table 3. Multiple technologies, multiple operating strategies (i.e., 

energy markets only and providing both energy and ancillary services), and multiple uses (e.g., 

electricity markets and sale of hydrogen) are explored. 

Table 3. List of System Configurations

Technologies Short Name Grid Services Provided Hydrogen Sold

1 Pumped Hydro HYPS Eonly Energy markets only No

2 Pumped Hydro HYPS All Energy and ancillary services No

3 Lead Acid Battery Batt Eonly Energy markets only No

4 Lead Acid Battery Batt All Energy and ancillary services No

5 Fuel Cell and Electrolyzer FC-EY Eonly Energy markets only No

6 Fuel Cell and Electrolyzer FC-EY All Energy and ancillary services No

7 Fuel Cell and Electrolyzer FC-EY Eonly Energy markets only Yes, 400 kg/day (80%)

8 Fuel Cell and Electrolyzer FC-EY All Energy and ancillary services Yes, 400 kg/day (80%)

9 Steam Methane Reformer SMR Baseload No services 

(baseload operation) Yes, 400 kg/day (100%)

10 Electrolyzer EY Baseload No services 

(baseload operation) Yes, 400 kg/day (80%)

11 Electrolyzer EY Eonly Energy markets only Yes, 400 kg/day (80%)

12 Electrolyzer EY All Energy and ancillary services Yes, 400 kg/day (80%)

 

2 The 1 MW electrolyzers can produce close to 500 kg/day and are operated with an 80% capacity factor for the year 

resulting in 400 kg/day actual output. The SMR system can produce 400 kg/day and operates with a 100% capacity 

factor. 
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Participation in only energy markets relies on price arbitrage to achieve value. Participating in 

both energy and ancillary service markets means that some energy is used for arbitrage—when 

the on-peak/off-peak price split is sufficiently high to provide more revenue than providing 

ancillary services—but the majority of the time, power is used for providing ancillary services.

The optimization determines when the system should focus on participating in energy markets, 

providing ancillary services, or both.

Currently, most electrolyzer facilities do not offer flexible demand to the grid and operate with a 

relatively flat electrical consumption and hydrogen production profile; however, these systems

can respond very rapidly and provide a variety of grid services, which are not presently utilized. 

For electrolyzers that provide demand response, participating in only energy markets essentially 

means purchasing electricity when it is the least expensive to lower the total feedstock cost.

Participating in both energy and ancillary service markets involves modulating consumption to 

pursue low cost electricity and providing ancillary service support whenever possible.

It is assumed that for the scenarios that allow for the sale of hydrogen, a fixed amount must be 

produced (i.e., 400 kg/day) and the demand for hydrogen is constant. This creates a situation 

where the hydrogen storage tank provides a buffer between when the hydrogen is produced and 

when it is consumed. That allows the electrolyzer to change its electricity consumption profile to 

provide ancillary services while also meeting any contractual hydrogen production requirements.

The authors have explored the impacts of variable hydrogen demand profiles based on fueling 

station data. Using the available data, the impacts on operational revenue were less than 1% 

compared to constant demand and, as a result, are not included below. Lastly, while steam 

methane reformers can ramp up and down to meet hydrogen demand, because the natural gas 

price is constant and their electricity consumption is two orders of magnitude lower than that of 

the electrolyzers, the reformers maintain a constant operating profile and do not modulate 

production.
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5 Results

The operations optimization model was run using a variety of technologies and operating 

strategies as presented in Table 3. The cost for each case is compared to the maximum 

achievable revenue in Figure 3. The cost model was described in the previous section and the 

yearly revenue is calculated as the revenue from the provision of ancillary services and the sale 

of hydrogen, less the electricity or gas feedstock cost.

The figure is separated into two sections. The first six technologies from Table 3 do not include 

the sale of hydrogen and only take in electricity, store energy, and output it at a later time (i.e., 

electricity-in, electricity-out systems). Technologies 7 to 12 from Table 3 assume that 400 kg of 

hydrogen per day is sold, which amounts to 80% of the potential hydrogen production for 

electrolyzers and 100% of the hydrogen production for SMR systems. The hydrogen can be 

produced at any time and drawn from the storage tank when needed. This assumption ensures 

there is a steady supply of hydrogen for customers and capacity for systems to shift when 

hydrogen is produced and provide ancillary services. Technologies 7 and 8 can operate as

storage systems while technologies 9 to 12 operate as demand response systems. Electrolyzers 

and SMR units can operate as demand response devices when a fuel cell or combustion device is 

not attached. They consume electricity or gas to produce and store hydrogen and provide 

demand-side flexibility, but they do not re-generate electricity.

The range of revenue for the configurations that sell hydrogen represents a range of potential sale 

prices for hydrogen from $3/kg to $10/kg. The future market value for hydrogen is likely 

dependent on which markets are targeted so a range is used, allowing the reader to see the impact 

on revenue from different hydrogen sale prices. Similarly, the high end of the system cost range 

represents a current case and the low end represents a more optimistic future case. See Table 2

for more details.

As shown in Figure 3, hydrogen systems that do not sell hydrogen have a lower revenue and 

higher cost than conventional storage technologies. This is due to a lower round trip efficiency 

and higher capital cost for the fuel cell. As a result, when providing strictly electrical energy 

storage, it is challenging for hydrogen technologies to compete against conventional technologies

using the selected California electricity markets. Hydrogen produced by an electrolyzer or SMR 

and sold at $3–$10/kg as a fuel is more valuable than the electricity generated using a fuel cell.

Consequently, systems that can sell hydrogen should sell as much as possible, while providing 

ancillary services and on occasion selling electricity if the price differential is sufficiently high. 

For hydrogen storage systems, a 1 MW fuel cell is assumed, which increases the cost while only 

operating a few hours each year during periods of high price differentials, and only marginally 

increasing the value. For this analysis the same capacity of fuel cell and electrolyzer are 

installed; however, there may be opportunities to reduce the cost while still providing the 

increased system flexibility that comes with adding a fuel cell by installing a smaller fuel cell.

In all cases, systems providing both energy and ancillary services (i.e., “All”) generate more 

revenue than systems only participating in energy markets (i.e., “Eonly”). This is because 

providing additional services creates additional revenue streams that were previously not 

accessible. The last four cases are particularly promising for hydrogen technologies. These cases 

sell all of the hydrogen and do not re-generate any electricity. SMR is currently the most widely 
15

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used technology for hydrogen production and, as expected, shows the greatest revenue margin.

Electrolyzers are currently operated most often in baseload mode; however, there is significant 

value to capture from participating in electricity markets. By participating in energy markets and 

modulating operating load to minimize its electricity cost, the electrolyzer can increase revenues 

by $23/kW-yr; providing both energy and ancillary services increases that value to $57/kW-yr 

and, if the system is eligible, a capacity payment can provide additional revenue (i.e., $150/kWyr for this analysis).

Figure 3. Comparison of cost versus electricity market revenue for conventional and hydrogen 

technologies ($3–$10/kg represents a range of potential sale prices for hydrogen)

In addition to looking at systems that produce 80% of the potential hydrogen (400 kg/day), an 

analysis was performed that looked at producing only 20% or 100 kg/day to understand the 

potential for oversizing equipment to focus on revenues from provision of grid services. The 

results show similar behavior as the 400 kg/day cases, except for two things:

1. The revenues are significantly lower because less hydrogen is sold. The value for 

hydrogen is greater than electricity even at $3/kg, resulting in much less revenue than for 

the 400 kg/day scenarios.

2. The 100 kg/day systems focused more on regulation down (a lower value product) than 

on regulation up. This is because electrolyzers are only able to provide regulation up 

when they are producing hydrogen, which for 100 kg/day represents only 20% of the 

time, which will be much less than 80% for the 400 kg/day scenarios. 

A breakdown of revenue streams is shown in Figure 4. The capacity payment value is $150/kWyr. All technologies except the “SMR baseload” and “EY baseload” receive this payment. These 

do not receive a payment because they are not modulated to respond to grid needs.
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For the technologies that do not sell hydrogen (i.e., first six), the resulting revenue received from 

energy and/or ancillary services (not including capacity payment) ranges from $0/kW-yr to 

$107/kW-yr. For the technologies that sell hydrogen (i.e., last six), the resulting revenue from 

hydrogen and energy and/or ancillary services ranges from $255/kW-yr to $368/kW-yr, mainly 

from the sale of hydrogen. Energy market revenues include both the purchase and sale of

electricity so the value can be negative, particularly for technologies that sell hydrogen. When 

considering the selected California wholesale electricity markets, the main business for hydrogen 

equipment should be producing and selling hydrogen. Providing services to the grid can 

supplement that revenue.

Figure 4. Breakdown of electricity market revenues with a hydrogen sale price of $3/kg

Hydrogen systems are able to scale the energy storage capacity independently of the power 

capacity. This allows for systems with very high energy-to-power ratios (i.e., long duration 

storage). A sensitivity analysis was performed on the additional value for increasing the energy 

storage capacity at rated power from 3 hours to 168 hours (1 week) to determine the current 

market value for long term storage within California. This case is interesting because variable 

renewable generation may experience extended periods of low or no generation during events 

where the sky is cloudy or when there is insufficient wind for several days at a time. There are 

several options to mitigate this challenge including maintaining sufficient backup fossil 

generation, greatly increased demand-side management, and long duration storage. Long 

duration storage offers the opportunity to mitigate extended periods of limited renewable 

generation while not using fossil fuels and without the potential to impact customer usage and 

behavior.

Two cases were explored: (1) a fuel cell and electrolyzer storage system capable of providing 

energy and ancillary services that sells 400 kg/day of hydrogen and (2) the same system that 

cannot sell hydrogen. Figure 5 presents results for the system that can sell hydrogen. The 
17

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horizontal dotted line is positioned at the maximum revenue value for the 3 hour storage device 

and provides a reference for all of the subsequent items. Above-ground tanks are used for storage 

so the cost increases linearly as the required storage capacity increases. The use of underground 

hydrogen storage has been shown to dramatically reduce the cost for high volume storage

(Steward et al. 2009). That would reduce the increase in cost for the system; however, the 

expected revenue values are independent of the type of storage technology used.

The revenue slightly increases with additional capacity (i.e., $17,500/year when increasing from 

3 hours to 168 hours of storage). The horizontal dotted line in Figure 5 is used for reference to 

see the relative difference in yearly revenue. The maximum revenue-to-cost ratio occurs for 4 

hours of storage and is very similar for storage durations between 3 and 8 hours. However, for 

durations greater than 16 hours of storage, using above ground storage tanks, the revenue-to-cost 

ratio falls below 1 and continues to fall for all higher durations of storage. While the exact 

optimal value for storage operation is specific to the assumptions in this study, this result reflects 

the importance of targeting diurnal price differences in current markets. This exercise was 

repeated with a fuel cell and electrolyzer system that cannot sell hydrogen and even less of a 

revenue increase was seen (i.e., $2,700/year increase in revenue for a 56 times increase in 

storage capacity). This shows that more storage capacity is not necessarily more valuable in 

California’s current energy and ancillary service markets.

Based on select markets in California, the only mechanism to compensate users for long-term 

storage is the energy price differential from arbitrage and, potentially, capacity payments.

However, the price differential and demand follow a diurnal pattern, which means that the 

majority of value is achievable with less than one day of storage. High penetration of renewables

is causing concern with system flexibility and overgeneration. These challenges reinforce the 

importance of diurnal storage but also should encourage mechanisms to value longer-duration 

storage in the future.

Figure 5. Storage capacity sensitivity analysis for “FC-EY All” from 3 to 168 hours of storage
18 

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6 Conclusions

Hydrogen technologies offer unique system flexibility that can enable interactions between 

multiple energy applications including electricity, transportation, heating fuel, and industrial

processes. Previous research established that hydrogen technologies, and in particular 

electrolyzers, can respond fast enough and for sufficient duration to participate in electricity 

markets. To date, there has been little work done to assess the potential economic value of 

electricity market participation for hydrogen systems. The present work explores the value from 

a subset of California electricity markets including energy, regulation, spinning reserve, and nonspinning reserve. This work recognizes that participation in electricity markets can enhance the 

revenue streams available for hydrogen storage systems and quantifies the economic 

competitiveness of these systems compared to conventional energy storage technologies. 

The value of participation in energy, ancillary service, and capacity markets is explored and the 

key results are as follows.

Hydrogen systems should focus on selling hydrogen. Using historical wholesale 

electricity prices in California, a system that can produce hydrogen is more competitive if 

it sells its hydrogen than if it is used to generate electricity. This is largely due to a low 

round-trip efficiency for “electricity-in, electricity-out” hydrogen storage systems and the 

increase in system cost from the addition of a fuel cell. 

Participation in energy, ancillary service, and capacity markets yields the greatest 

revenue. Hydrogen systems capable of providing ancillary services achieve higher 

revenues than systems engaging in only energy markets, which in turn can receive greater 

revenue than systems operating with typical baseload or constant output profiles. 

More storage capacity is not necessarily more competitive in current energy and 

ancillary service markets. Current electricity markets in California do not have a 

specific mechanism for valuing long-term storage and rely on the energy price 

differential. Consequently, revenues only slightly increase for systems with a day or even 

a week of storage—not enough to overcome the costs of adding additional storage

capacity beyond that required to manage diurnal variations. 
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7 Future Work

The current study used CAISO 2012 historical data, but there are differences in the markets

available and prices for each region and from year to year. Future work will focus on expanding 

the list of markets explored to include flexible ramping and other new services as they develop, 

updating the analysis to current-year values, and expanding the regions considered beyond 

California. 

As mentioned in the approach, the operations optimization model assumes that systems are not 

large enough to impact market prices. However, with widespread roll-out of hydrogen 

technologies and especially electrolyzers to support renewable integration and provide 

transportation fuel, there are concerns about impacts on electricity markets of introducing such a 

large flexible load on the system. Those impacts are not captured in this effort. It is difficult to 

predict how market prices will be affected by changes to the system (Hummon et al. 2013; 

Weron 2014) or whether the ancillary service markets are deep enough to support significant 

increases in energy storage and dispatchable demand-side resources (Denholm et al. 2015). 

Integrating hydrogen technologies into production cost models would allow for the system 

impacts of energy storage and large dispatchable loads to be assessed. This work could quantify 

the difference in value for the price-taker methodology, presented here, and full system 

production runs where market prices can be impacted.
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