Green hydrogen through electrolysis: Deployment of supplementary batteries to smoothen electricity input for electrolyzers

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Green hydrogen through electrolysis:

Deployment of supplementary batteries to smoothen

electricity input for electrolyzers

Supply Chain Management

Msc thesis

University of Groningen, Faculty of Economics and Business

Author: Krijn Wermenbol (S2781778) Supervisor: Dr. M.J. (Martin) Land

Second supervisor: Prof. dr. ir. J.C. (Hans) Wortmann

Date: 22.06.2020

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Acknowledgement:

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Abstract: Many countries are building PV arrays and wind turbines in order to reduce harmful

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1. Introduction

The energy sector is facing some major challenges in order to reach a sustainable future. Fossil fuels face depletion and alternatives have to be developed to secure the energy supply, and emission of

greenhouse gasses have to be reduced to mitigate environmental effects (Kaygusuz, 2012). A large number of countries have signed the Paris Agreement, in which governments state the intention to reduce emission of CO2 (UNFCCC, 2016). One of the major sources of CO2 emission is fossil energy production (Sirikunpitak et al., 2017). Therefore, the energy sector is facing a transition from fossil energy sources to renewable energy (RE) sources such as photovoltaic (PV) systems and wind energy. However, RE faces several difficulties. For instance, the production pattern of RE is unpredictable and weather dependent (Bajaj & Singh, 2020; Denholm & Hand, 2011; Krishan & Suhag, 2019; Weidner, 2018). The unpredictable production pattern of RE sources demands a way of storage in order to supply electricity during periods without energy production (Weidner, 2018). Moreover, PV arrays and wind turbines are mostly installed in rural areas since they require a lot of space. Rural areas tend to have older electricity infrastructures which have insufficient capacity to handle peak production (Crabtree et al., 2011). A method to handle the excess supply of electricity is to store it in the form of hydrogen. Green hydrogen production can help to store energy over time and relieve local grids from congestion (Leeuwen & Mulder, 2018).

Hydrogen is considered a promising and emission free method to store energy (Leeuwen & Mulder, 2018; Weidner, 2018). However, electrolyzers for green hydrogen production require enormous capital expenditures (Schmidt et al., 2017). Several studies have researched the coupling of an electrolyzer to PV systems (Clarke et al., 2009; Morico et al., 2019), to wind energy systems (Kroniger & Madlener, 2014) or to both (Muralikrishna & Lakshminarayana, 2008; Turner et al., 2008). The problem of these systems is that the electrolyzers can only operate during RE production. Therefore, the burden of the capital expenditures of the electrolyzer is to be earned back over a relatively small amount of operating hours. To increase operating hours, a buffer for temporarily electricity storage could be integrated to feed the electrolyzer during times without RE production. Research has found that batteries perform well in short-term electricity storage (Heymans et al., 2014). This study proposes to combine the use of batteries and electrolyzers to process electricity surpluses into hydrogen, wherein the batteries

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5 This research will study a system using RE, battery storage, electrolyzers and hydrogen storage that will be used to feed a hydrogen demand for industry, mobility and a hydrogen based heating system in a rural town in the Netherlands. As this innovative system is currently not applied anywhere, this study gives valuable insights to both researchers and practitioners in the trade-offs between electricity production capacity, battery capacity, electrolyzer capacity and hydrogen storage. This research reveals groundbreaking insights on the impact that batteries can have on hydrogen production patterns over the year. This will in turn have a large effect on the required seasonal hydrogen storage. The system will be simulated based on real-life data of energy supply and hydrogen demand. Based on the above, this research aims to contribute to the effective use of excess electricity production from RE sources. More precisely, this research aims to find the best configurations for a system using a buffering approach with short term battery storage to smoothen electricity supply for an electrolyzer.

The next chapter will consist of a literature research to clarify the concepts used in this research. Thereafter, an outline of the used methods will be described. The fourth chapter will consist of the findings of this research. The last chapter will contain a discussion and conclusion, where the findings are discussed and compared with existing literature as well as limitations and suggestions for future research.

2. Theoretical framework

Currently, the Netherlands is struggling to meet their greenhouse gas emission reduction targets (at 15% in 2018, with the target of 25% in 2020, and 49% in 2030 (CBS, 2019)). Therefore, the need for drastic measures to reduce harmful emissions rises. To drive a sustainable and emission-free energy economy, green hydrogen can become increasingly important to store energy over time (Ehsan & Wahid, 2016; Mulder & Perey, 2019). Before going in depth on the hydrogen project in a rural town in the

Netherlands, we review prior literature and theory on RE, energy storage possibilities and the role of buffering in energy systems.

2.1. Renewable energy sources

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6 Studies found that the intermittent nature of RE leads to a mismatch in production and consumption (e.g. Muenzel et al., 2015; Orioli & Gangi, 2013). For example, PV has its highest production in the middle of the day, while an average household consumes most electricity in the morning and evening (Muenzel et al., 2015). Moreover, electricity demand in the Netherlands is higher in the winter than in the summer (NEDU, 2019), while PV generates the bulk of its electricity in the summer (Muralikrishna & Lakshminarayana, 2008). Electricity networks with a high penetration of PV will therefore have a challenge to achieve sufficient storage capacity to accommodate for the seasonal energy mismatch (Pfenninger & Staffell, 2016).

The output of wind energy varies with the strength of the wind (Burton et al., 2011). When wind energy production is higher than projected, the grid can get overloaded which may cause blackouts (Schenk et al., 2007). Because many conventional power plants cannot quickly adjust power output to the variable production of wind energy and solar energy, oversupply of electric energy is high during peak

production of RE (Denholm & Hand, 2011; Schenk et al., 2007).

Given the intermittent nature of PV and wind, a higher penetration of RE in the energy mix will, without storage options, lead to a higher oversupply of electricity (Denholm & Hand, 2011). However, until now electrical energy storage has been difficult to sell in the market due to high costs and difficulties on quantifying value (Denholm et al., 2010). Due to declining feed-in-tariffs, exporting electricity to the main grid becomes less attractive, and ways to store electricity have to be sought (Muenzel et al., 2015). An energy carrier that is widely researched is hydrogen (Mulder & Perey, 2019).

2.2. Hydrogen

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7 fossil energy to RE, electrolysis has gained much attention due to its coupling ability with RE (Turner et al., 2008). A study of Clarke et al. (2009) observed that coupling an PV array with a PEM electrolyzer showed promising aspects, as the PEM electrolyzer was able to respond to variable electricity input as well as temperature changes.

Hydrogen can be stored on a large scale in depleted salt caverns, which would be suitable for seasonal storage (Mulder & Perey, 2019). However, this is not used as of yet. Otherwise, hydrogen is mostly stored under high pressure in tanks or tubes. This storage can conserve the hydrogen for a long period, even for a season-to-season basis, and can be designed to have a long lifetime (Gray et al., 2011). As these hydrogen storage tubes and tanks are very expensive (Kharel & Shabani, 2018), installing them for seasonal storage requires enormous investments. Even though green hydrogen production shows promising aspects, it is not deployed on a large scale yet (Leeuwen & Mulder, 2018).

Prior research has stated that in order for large scale green hydrogen production to get off the ground, either the price of hydrogen has to increase or the investment costs for hydrogen production have to decrease (Kopp et al., 2017; Leeuwen & Mulder, 2018). Due to the relatively low prices of electricity and low operating costs of electrolyzers, practitioners are mostly interested in reducing capital expenditures of the electrolyzer (Schmidt et al., 2017). The reduction of capital costs can be realized in two ways, 1) by decreasing capital costs through technological improvement and, 2) decreasing capital costs by decreasing the capacity of an electrolyzer. The first method is dependent on future development of electrolyzers and can be seen as an external factor that cannot be influenced in the context of this research. The second method would, ceteris paribus, lead to a bigger oversupply of RE and lower hydrogen production. However, when excess energy can be temporarily stored until production of RE sources falls (e.g. no sun for PV, no wind for wind energy), smaller electricity surpluses and increased hydrogen production levels may be realized by increasing operating hours compared to a situation without temporary electricity storage. For example, a battery storage system can be used to store electricity as it is able to allow for electricity to be consumed in a later stage (Hassan et al., 2017).

2.3. Battery storage

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8 Østergaard, 2009). Electrical storage in the form of many different batteries can have efficiencies from 70 up to 100% (Kroniger & Madlener, 2014). A battery that achieves high efficiency and is commercially available is the lithium ion (li-ion) battery. Research of Divya et al. (2009) has found lithium ion batteries have great potential due to their high energy density and storage efficiency close to 100%. Some

drawbacks on li-ion batteries are its high cost and the detrimental effects that charging below 20% and above 80% has on its lifetime (Divya & Østergaard, 2009). Therefore, this study will only consider the useful capacity of li-ion batteries between 20 and 80% of its capacity.

Batteries have shown to be effective in storing electrical energy generated by solar PV (Hassan et al., 2017), wind turbines (Housseini et al., 2018) or a combination of PV and wind (Merabet et al., 2017). Therefore, this study will investigate the possibility of using batteries to capture electricity from RE production peaks to store it for a short time.

2.4. Congestion management

As aforementioned, a high penetration of RE can lead to curtailment of electricity (Denholm & Hand, 2011). Without congestion management, the grids will get overloaded and electricity curtailment will be necessary (Schermeyer et al., 2018). Therefore, ways to decrease the electricity supply to the grid during peak production of RE have to be sought. The electrolyzer and battery are additional demand centers for electricity produced by PV and wind. Previous study has found that an electrolyzer can be best placed close to the RE production in order to prevent grid congestion and electricity curtailment due to limited cable capacities in rural areas (Keizer, 2019). An electrolyzer and battery can be placed close by RE production to process oversupply of electricity before its enters the grid, and thus reduce the peak load, can be identified as a form of peak clipping as introduced by Gellings (1985).

2.5. Buffering

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9 falls. Linked to the hydrogen production, battery storage can be used as an inventory buffer against variability of electricity supply.

3. Methodology

This research analyses the configurations of a hypothetical energy system containing production, storage and consumption of energy. An overview of the system is depicted in figure 1. As there is no such infrastructure in place as of now, observation of different configurations of the system is not possible and modelling is an appropriate option. This research will have a predictive and exploratory character regarding the different scenarios that will be deployed, in order to develop insights for renewable energy infrastructures with hydrogen integration. Simulation research is a good approach for research with an exploratory and predictive nature in combination with a complex infrastructure (Karlsson, 2016). This simulation will present scenario outcomes that provide insights in the concepts that are important in an hydrogen infrastructure, which fits the class of simulation research (Meredith et al., 1989). The model will require many calculations and large amounts of data, i.e., RE production patterns, electricity demand pattern and the hydrogen demand pattern. Therefore, the selected simulation model will be built as a spreadsheet model in excel. The methodology that is proposed is influenced by Keizer (2019), who has done research with a comparable modelling approach. This research will extend and adapt the methodology of Keizer (2019).

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10 3.1. Situation description

This study will deploy a model based on real-life data from a small town located in a rural province of the northern part of the Netherlands. In line with the energy transition from fossil energy to RE, an initiative for a local hydrogen economy is planned. The local hydrogen economy contains 1) renewable electricity production by wind turbines and PV arrays, 2) hydrogen production through electrolysis, 3) temporary electricity storage in batteries, 4) hydrogen storage, 5) hydrogen sales and purchase, and finally, 6) hydrogen demand for mobility, industry and residential heating for 112 newly built houses.

The supply of local RE production will not always be equal to the local electricity demand. In the case of an electricity shortage, electricity has to be imported from the main grid. During oversupply of

electricity, electricity has to be converted into hydrogen, stored in batteries or exported to the main grid. In order to capture all electricity during peak production, enormous electrolyzer and battery capacities have to be installed. Due to the high capital expenditures of electrolyzers and batteries this will be infeasible. Therefore, part of the electricity surplus will be exported to the main grid. The aim of the simulation is to analyze combinations of multiple battery and electrolyzer capacities coupled to PV arrays and wind turbines. The analysis will be conducted under different combinations of PV and wind energy. The performance analysis will contain the utilization of the battery, the utilization of the electrolyzer and the required hydrogen storage based on the hydrogen demand for residential heating, mobility and industry. Part of the analysis will consider a restricted hydrogen storage capacity, where hydrogen has to be purchased and sold.

3.2. The system

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11 considered due to the low roundtrip efficiency of about 50%. The third state is the most interesting state of the system, because decisions have to be made about the destination of the electricity surplus.

The priority rules during excess electricity production are as follows. The first priority of produced electricity is to supply local electricity demand. The second priority is to produce hydrogen through electrolysis. The third priority is to store electricity in batteries. The fourth priority is to export electricity to the main grid.

3.3. Simulation model

The simulation model (see figure 2) consists of four input variables which result in six model outputs through five simulation variables. The input variables are defined as follows, hourly local electricity demand in kWh, hourly hydrogen demand in kWh, hourly PV production in kWh and hourly wind production in kWh. The simulation variables are defined as the electrolyzer capacity in kW, the battery capacity in kWh, the allocation between PV and wind generation in percentages, the PV and wind capacity in kW and lastly the restrictions on hydrogen storage capacity in kg. The actual data of the input variables will be presented in section 3.4.

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12 Figure 2. Overview of the simulation model

The model outputs are analyzed by several performance indicators per output, which are shown in table 1. Electricity supply and demand matching was analyzed based on the ability of the local RE to match the local demand. The ability to match local supply and demand is measured by on-site energy fraction (OEF), on-site energy matching (OEM) (Cao et al., 2013), and grid dependency as a percentage of electricity demand that has to be imported from the main grid. The OEF represents the fraction of local electricity demand that is met by locally produced electricity. The OEM represents the fraction of locally produced electricity that is used for local electricity demand. The electrolyzer utilization is measured by the operational hours in a year, utilization as a percentage of total capacity and utilization as a percentage of the capacity during operational hours. Battery utilization is measured by the

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13 Table 1. output performance indicators

3.4. Model inputs

All model inputs are based on the year 2016, as this was the most recent year with all necessary data available.

3.4.1. Local electricity demand

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14 Figure 3. Hourly electricity demand over the year

Figure 4. Hourly electricity demand zoomed into a week in July

3.4.2. Hydrogen demand

No real hydrogen demand data could be found. Therefore, the assumption was made that the hydrogen demand for the residential heating had similar demand pattern as demand for natural gas for residential heating. The data of the demand for natural gas was obtained from Rendo. The yearly hydrogen demand of an individual house was 8125 kWh (244 kg). This added up to a total yearly hydrogen demand for residential heating of 0,9 GWh (27302 kg). The hydrogen demand for residential heating in the

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15 constant over the year. The yearly demand for industry added up to 1,5 GWh (45450 kg) hydrogen. The yearly demand for mobility added up to 1,3 GWh (40000 kg) hydrogen. Figure 5 depicts the hourly hydrogen demand in kWh.

Figure 5. Hydrogen demand profile over the year

3.4.3. PV production pattern

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16 Figure 6. PV generation profile (hourly output for 1 year)

Figure 7. Zoomed in PV generation profile for 1 week in July

3.4.4. Wind production pattern

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17 Figure 8. Wind generation profile over the year

3.4.5. Electrolyzer

Studies have shown various efficiencies for PEM electrolyzers ranging from 70 to 85%, (Schenk et al., 2007), 67 to 82% (Carmo et al., 2013) and 72% (Mulder & Perey, 2019). The choice was made to be conservative with an electrolyzer efficiency of 70%. The electrolyzer capacity in the scenarios without a battery is minimized to the point where it was able to produce same amount of hydrogen as is

demanded. The scenarios that include a battery have an electrolyzer capacity of 1000 kW. In order to fulfill the hydrogen demand, a 1000 kW electrolyzer would have to run at 61,4% of its capacity. Given the intermittent nature of PV and wind, enormous battery capacities would have to be installed in order to produce sufficient hydrogen with an electrolyzer capacity smaller than 1000 kW. A system with only PV would only be able to supply electricity to the electrolyzer for 30,1% of the time, and a system with only wind would be able to supply electricity to the electrolyzer for 40,2% of the time.

3.4.6. Battery capacity

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3.4.7. Hydrogen storage

Part of the scenarios assumed an unlimited storage capacity for hydrogen, and another part of the scenarios assumed a limited hydrogen storage capacity of 1000 kg and 5000 kg. In the scenarios with a limited storage capacity, hydrogen had to be imported and exported. In absence of a connection to an external hydrogen pipeline network, hydrogen had to be exported and imported with tube trailers. Tube trailers are able transport 500 kg hydrogen in one full truckload. As the chosen electrolyzer capacities are able to produce more than 500 kg hydrogen per day, it was deemed inappropriate to buy and sell hydrogen in smaller amounts than a full truckload. Very little is known about the hydrogen market and its lead times, as it hardly available for these small scale parties as of now. Therefore, the assumption was made that the scenarios with limited storage capacity assume that 500 kg hydrogen is bought when the hydrogen inventory falls below 100 kg, and 500 kg hydrogen is sold when the remaining storage capacity is under 100 kg. Moreover, it was assumed that hydrogen buyers as well as sellers are always available.

3.5. Scenarios

The 12 scenarios are shown in table figure 9. The scenarios are based on 5 different electricity

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19 Figure 9. Scenario visualization

4. Results

4.1. Supply and demand matching

The following section presents the results for the supply and demand matching of electricity. Based on the local electricity demand profile and the production profile of PV and wind, the OEF, OEM and grid dependency are calculated. The yearly electricity output of PV and wind is equal to 125% of the yearly local electricity demand. However, since there is a mismatch in time of production and consumption of electricity, it is not possible to use all locally produced electricity for local electricity demand. Therefore, the local grid is dependent on the main grid to import and export electricity.

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20 interpreted as an indication that large electricity surpluses occur, which is an opportunity for green hydrogen production.

The grid dependency is at its highest in the scenario with 100% PV with a dependency of 64%. It gradually decreases until 44% grid dependency at the scenario around scenarios with 50% PV and 50% wind and 25% PV and 75% wind. Then, it increases to 50% at the scenario with 100% wind. To

summarize, all performance measures indicate that the supply and demand matching of electricity is optimized at scenarios with 50% PV and 50% wind and 25% PV and 75% wind.

Figure 10. Supply and demand matching under different electricity generation scenarios 4.2. 100% PV

4.2.1. Electrolyzer and battery

Within the base cases, the electrolyzer for hydrogen production is powered by a PV array. The electrolyzer and battery capacities along with some operational findings can be seen in table 2. The minimum electrolyzer capacity, in absence of a battery, to fulfil hydrogen demand is 2310 kW (scenario 1). When the electrolyzer capacity is restricted to 1000 kW, a battery capacity of 9425 kWh is required to fulfil the hydrogen demand (scenario 2). This means that a fully charged battery is able to supply the 1000 kW electrolyzer for 9.425 hours. The battery mostly supplies electricity to the electrolyzer during the night. The restriction on the electrolyzer capacity has implications for its operations. When

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21 5622 per year, which is an increase of 33.2% operating hours. Because the capacities are optimized to produce a fixed amount of hydrogen, the increase in utilization of the electrolyzer in the scenario with a battery is a logical consequence. The utilization of available electrolyzer capacity increases by 34.8%, from 26.5% in scenario 1 to 61.3% in scenario 2. The battery in scenario 2 is operational in 5487 hours of the year, which is 62.6% of the available time. The battery is charged at an average of 41.5% of its useful capacity. The presence of a battery increases the amount of operating hours of the electrolyzer, because it ensures a more stable electricity supply. Also, the battery allows for an increased utilization during operating hours. When the electricity surplus from the PV array is not sufficient to let the electrolyzer run at 100%, the battery can support the electrolyzer with extra electricity. The electrolyzer utilization during operating hours increases from 88.1% in scenario 1 to 95.6% in scenario 2.

Table 2. Required capacities, electrolyzer- and battery utilization

4.2.2. Hydrogen production

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22 battery allows for more than half of the hydrogen production in scenario 2. Both scenarios result in a total output of 3.76 GWh hydrogen, which is equal to around 112,700 kg.

Table 3. Hydrogen production details

Figure 11 shows the hydrogen production per month. Scenario 1, without the battery, is able to produce more hydrogen than scenario 2 in the period from April to September. Scenario 2, with the battery, is able to produce more hydrogen from January to March and from October to December. Compared to the hydrogen demand per month, the hydrogen production in scenario 2 is closer to the hydrogen demand than the hydrogen production in scenario 1 in every month.

Electricity production from PV arrays is highest during the summer. This period has a higher amount of hours between sunrises and sunset and the sun is stronger, which leads to a more constant electricity supply. The electrolyzer in scenario 1 has a capacity that is 1310 kW larger than the electrolyzer in scenario 2. The electrolyzer in scenario 1 has to run at full capacity for at least 7.19 hours a day to make up for the electricity that the battery can provide. The high hydrogen production from April to

September indicates that the electrolyzer in scenario 1 is better able to process the large supply of electricity over a longer period, compared to a scenario with a smaller electrolyzer supported by a battery. During this period, the electrolyzer in scenario 1 is, on average, able to benefit from its larger capacity for longer than 7.19 operational hours. From the supply side, the small electrolyzer capacity along with a battery in scenario 2 can be identified as bottlenecks for hydrogen production. However, a higher production in this period will only lead to excessive hydrogen inventories, given the low hydrogen demand in this period.

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23 produces a large amount of electricity for a small number of hours in the winter months. This results in huge electricity surpluses during these hours. The combination of a small electrolyzer with a battery is able to process these electricity surpluses better than a larger electrolyzer without a battery is able to. The electrolyzer in scenario 1 can benefit from its larger capacity for less than 7.19 hours a day due to the unstable supply of electricity and the limited hours between sunrise and sunset in this period. The possibility to store electricity in scenario 2 greatly benefits the hydrogen production in periods were electricity surpluses are scarce.

Figure 11. Hydrogen production and demand per month

4.2.3. Unrestricted hydrogen storage

This section elaborates on the behavior of the hydrogen buffer. Table 4 shows the required storage capacities and starting inventories for scenario 1 and 2 when the model does not set any restrictions on the storage capacity. Both scenarios start with a positive hydrogen inventory, which is set at a level that the inventory is completely empty at its lowest point. The hydrogen inventory at the end of the year will be at the same level as the starting inventory. The buffer has to end at the same level as the starting inventory, since supply and demand of hydrogen is a cyclic process. For simplicity, the presence of a safety stock is ignored. However, in reality inventory may deplete at a slower or faster rate due to divergent weather patterns. In this case, hydrogen could be imported or exported.

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24 Scenario 1 requires a storage capacity of 1.11 GWh (33200 kg), which is 29.6% of the yearly hydrogen production. The required storage capacity for scenario 2 is substantially lower at 0.85 GWh (25494 kg), which is 22.8% of the yearly hydrogen production. The course of the hydrogen buffer over the year is displayed in figure 12.

Due to lower hydrogen production and higher hydrogen demand in the winter months, the buffer depletes during this period. In the summer months, hydrogen production is higher and hydrogen demand is low, which results in a growing inventory. The production pattern of scenario 2 has a better match with the demand pattern for hydrogen than scenario 1 as discussed in section 4.2.2.. This leads to a lower starting inventory and total capacity requirement in scenario 2 compared to scenario 1.

Table 4. Hydrogen buffer details

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4.2.4. Restricted hydrogen storage

The previous section explained what would happen with access to large scale hydrogen storage. However, without access to large scale storage such as depleted salt caverns it is very costly to realize seasonal hydrogen storage. Therefore, the next section studies scenario 1 and 2 under more feasible assumptions of 1000 kg and 5000 kg hydrogen storage capacity. The inventory starts and ends at 500 kg. Table 5 shows the amount of hydrogen in kg and truckloads (500 kg) had to be bought and sold in one year. Compared to a 1000 and 5000 kg hydrogen storage capacity, buying and selling 500 kg hydrogen seems like a large amount. During the summer period, there are days where more than 500 kg hydrogen is produced, and multiple trucks would have to drive every day if the trucks would ship much less than 500 kg hydrogen.

In scenario 1 with a storage capacity of 1000 kg, 34500 kg (69 truckloads) of hydrogen had to be bought and sold. In scenario 2 with a storage capacity of 1000 kg, 25500 kg (51 truckloads) of hydrogen had to be bought and sold. Thus, the better match between production and consumption in scenario 2 creates less dependability on importing and exporting hydrogen.

When the hydrogen storage capacity is increased to 5000 kg, 28500 kg (57 truckloads) had to be bought and sold in scenario 1. In scenario 2, 21000 kg (42 truckloads) had to be bought and sold over the year. The hydrogen bought and sold decreases by a larger amount than the hydrogen storage capacity is increassed. This will be explained in the next paragraph.

Table 5. Hydrogen bought and sold

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26 Figure 14 shows the points in time where hydrogen has to be bought and sold when the hydrogen storage capacity is 5000 kg. The four occasions were hydrogen is “wrongfully” bought and sold is reduced to zero. Apart from that, is not able to fulfill seasonal storage capacities. After the buffer is either full or empty, the scenario with 5000 kg hydrogen storage follows the same buying and selling pattern as the scenario with 1000 kg hydrogen storage. The hydrogen storage capacities of 1000 and 5000 kg both can store two and ten days of the average hydrogen production in the summer period respectively. Therefore, the restricted hydrogen storage does act as a transit center for hydrogen sales and purchases, instead of a seasonal storage. Therefore, it does not seem a wise investment to increase the hydrogen storage capacity from 1000 kg to 5000 kg under these conditions.

Figure 13. Buying and selling points scenario 1 with a storage capacity of 1000 kg

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27 Figure 15 shows the points were hydrogen has to be sold and bought in scenario 2 with 1000 kg storage capacity. It roughly follows the same pattern as scenario 1 with 1000 kg storage capacity. One difference is that event of buying and selling hydrogen occurs less frequently. Moreover, the event of “wrongfully” selling or buying hydrogen has decreased to one in March. This reduction is negligible compared to the total hydrogen import and export.

When the storage capacity is increased to 5000 kg in figure 16, the occasion of “wrongfully” selling or buying hydrogen decreased from one to zero. Even though scenario 2 produces more hydrogen during the winter than scenario 1, the 5000 kg storage capacity is still acting as a transit center and is not able to act as a seasonal buffer. Even in the presence of a battery, it does not seem a wise investment to increase the hydrogen storage capacity to 5000 kg.

Figure 15. Buying and selling points scenario 2 with a storage capacity of 1000 kg

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28

4.2.5. Doubling the electricity supply

Doubling the size of the solar park will affect the supply of electricity. Table 6 showcases the

consequences for several outputs in the system. The yearly produced electricity is 70.4 GWh, which is 247% of the yearly 28.5 GWh electricity demand.

The supply and demand matching of electricity is affected by the increase in electricity supply. The OEF, the percentage of local consumption that is from local electricity supply, increased from 36.0% to 40.0%. Increasing the electricity supply leads to electricity surpluses that cannot be used locally. This can also be seen in the OEM, which is the percentage of local electricity production that can be consumed locally. The OEM decreasds drastically from 28.9% to 16.0%, which resulted in large amounts of electricity that had to be fed back to the main grid or curtailed. The dependency from the grid fell from 64.0% to 60.0%. To summarize, doubling the size of the PV array does lead to large electricity amounts that cannot be consumed locally and it does not lead to significantly less dependency from the grid. This is caused by the mismatch over time in supply and demand of electricity.

However, the electrolyzer does benefit from the oversupply of electricity. When comparing the scenarios (1 and 3) with only an electrolyzer, significant differences are seen. Doubling the electricity supply results to a 5.9% increase in operational hours. The used capacity based on the yearly available capacity increases with 7.1% and the used capacity during operational hours increases by 7.5%. This indicates that under a doubled electricity supply, the hydrogen demand could be fulfilled with a smaller electrolyzer capacity.

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29 Table 6. Doubling the electricity supply

The amount of electricity that can be used for hydrogen production increases when the electricity supply is doubled. In the scenario with only an electrolyzer, doubling the electricity supply results in a 26.4% (1.42 GWh) increase in electricity that can be used for hydrogen production. This leads to an additional 26.4% (0.99 GWh;29891 kg) hydrogen production.

In the scenario with the combination of electrolyzer and battery, the electricity that can be used for hydrogen production increases by 0.84 GWh (15.6%), which leads to an additional 0.59 GWh (15.6%; 17624 kg) hydrogen production. The electricity that is first stored in the battery increases in quantity by 0.27 GWh. However, the electricity first stored in batteries decreases by 2.8% as a share of total

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30 electricity supply to the electrolyzer, which leads to a larger share of electricity being fed to the

electrolyzer directly.

Doubling the electricity supply leads to an oversupply of hydrogen in both the scenario with only an electrolyzer and the scenario that combines the electrolyzer with the battery. As the hydrogen oversupply is larger in the scenario with only the electrolyzer, a larger number of hydrogen truckloads has to be sold than in the scenario that combines the electrolyzer with the battery. In the scenario with only the electrolyzer and 1000 kg hydrogen storage capacity, the number of truckloads hydrogen that has to be bought decreases by 23 truckloads (-33.3%). With 5000 kg hydrogen storage capacity, it decreases by 21 truckloads (-36.9%). In the scenario with 1000 kg hydrogen storage capacity which combines the electrolyzer and battery, the number of hydrogen truckloads that has to be bought decreases by 18 truckloads (-35.3%). With 5000 kg storage capacity, it decreases by 17 truckloads (-40.5%).

In both scenarios the amount of hydrogen that has to be bought decreases when the electricity supply doubles. Hence, both scenarios increase their hydrogen production in the winter. The increase in hydrogen production is larger in the scenario with only an electrolyzer. An increase in hydrogen storage capacity does not strongly affect the amount of hydrogen that has to be bought. Hence, the hydrogen storage remains to be a transit center when its capacity is increased from 1000 kg to 5000 kg.

4.3. Electricity generation scenarios

The following section elaborates on the effect that different combinations of PV and wind have on the hydrogen economy.

4.3.1. Hydrogen production

The minimal electrolyzer and battery capacity requirements to fulfill hydrogen demand vary under different electricity generation scenarios. These requirements are shown in table 7. There is a trade-off in the allocation between PV with wind energy, and the required electrolyzer and battery capacities. In the scenarios excluding a battery, the minimum electrolyzer capacity requirement decreases when PV is partly substituted by wind energy until it reaches its lowest point at 25% PV and 75% wind. The

electrolyzer capacity requirement has a small increase when the electrolyzer is powered by 100% wind energy.

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31 little at 25% PV and 75% wind. The minimal battery requirement is highest of all scenarios in the

scenario with 100% wind, which is caused by the long periods of intermittency whom require a battery that can feed the electrolyzer for a longer time. The complementarity of PV and wind energy result in the lowest capacity requirements of both electrolyzer and battery in the scenarios with 50% PV and 50% wind, and 25% PV and 75% wind.

Table 7. Capacity requirements under different generation scenarios

The electrolyzer utilization in table 8 show the importance of the complementarity of the generation patterns of PV and wind. The scenarios with only an electrolyzer show an increase in the amount of operating hours when the PV capacity is partly substituted by wind capacity. Due to the more stable electricity supply, the number of operating hours increases from 2639 (30.1%) at 100% PV to its peak at 25% PV and 75% wind with 3851 (44.0%) operating hours. Due to the complementarity of PV and wind that generates a more constant electricity supply, the electrolyzers are able to achieve a higher utilization rate.

The amount of hours that the battery is (partly) charged is relatively similar along all generetion scenarios. The batteries are charged between 41.5% and 44.7% under all generation scenarios. On first glance, there are no big differences in the battery utilization. However, it can be seen that the largest amount of electricity is fed from the battery in the scenario with 100% PV. This amount decreases until the scenario with 25% PV and 75% wind. Thereafter, the amount of electricity fed from the battery to the electrolyzer increases again in the scenario with 100% wind.

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32 Table 8. Hydrogen production details under different generation scenarios

4.3.2. Hydrogen storage

The effects for the hydrogen storage, unrestricted as well as restricted, can be seen in table 9. First, the scenarios with just the electrolyzer are compared. The required hydrogen storage capacity is highest under 100% PV, due to high hydrogen production during the summer. Due to the more evenly distributed electricity generation by wind energy over the year, the hydrogen storage requirement decreases when PV is partly substituted by wind. The lowest capacity requirement are at 0.45 GWh (13461 kg) at 25% PV and 75% wind, and 0,46 GWh (13905 kg) at 100% wind. These hydrogen storage requirements are significantly lower than under 100% PV, due to the better match of wind electricity generation and hydrogen demand.

The inclusion of a battery results in a decrease of required hydrogen storage capacity under all electricity generation scenarios. The influence of a battery on required hydrogen storage capacity diminishes in the scenarios with 50% PV and 50% wind, and 25% PV and wind. These scenarios have less need for a battery because these scenarios are able to provide a relatively stable electricity supply for the electrolyzer.

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33 hydrogen storage capacity would not be able to provide hydrogen during long periods of intermittency. This results in many hydrogen sales and purchases, which could be avoided by an increase in storage capacity. Due to the complementarity of PV and wind, hydrogen purchase and sales are lowest under the scenarios with 50% PV and 50% wind, and 25% PV and 75% wind.

When the hydrogen storage capacity is increased to 5000 kg, the scenario with 100% PV and excluding a battery remains to be the scenario with the highest amount of hydrogen bought and sold. This amount decreases by a bit in the scenario with 75% PV and 25% wind without a battery. These scenarios benefit by the inclusion of a battery, as the hydrogen purchases and sales decrease by significant amount. In these scenarios, the hydrogen storage acts as a transit center. Therefore, increasing the storage capacity to 5000 kg does not seem appropriate.

The scenarios with at least 50% wind have the lowest amounts of hydrogen bought and sold over the year. The hydrogen sales and purchases decrease by a lot with the hydrogen storage capacity of 5000 kg, compared to the scenarios with 1000 kg storage capacity. The 5000 kg storage capacity is able to handle the long periods of wind intermittency better than a storage capacity of 1000 kg. The influence of a battery diminishes in the scenarios with at least 50% wind and 5000 kg hydrogen storage capacity, when the goal is to minimize the hydrogen purchases and sales. When the hydrogen storage capacity is increased from 1000 to 5000 kg, its role changes from a transit center to a buffer to get through long periods of wind intermittency. Therefore, increasing the hydrogen storage capacity seems appropriate in these scenarios.

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5. Discussion and conclusion

Several challenges arise with the increasing number of PV arrays and wind turbines. Due to the intermittent nature of PV and wind, it is challenging to use the produced electricity effectively. Also, electricity grids have to be relieved from the congestion that is induced by RE production peaks. This study analyzed how a local hydrogen infrastructure could be deployed in order to use renewable electricity effectively, and relieve the grid from congestion. However, there are many barriers for the green hydrogen economy to get off the ground. The main issue are the costs that are involved with producing and storing hydrogen (Kopp et al., 2017; Leeuwen & Mulder, 2018). This study has analyzed the influence that the inclusion of a battery can have in a local hydrogen economy. The deployment of a battery which could supply electricity to an electrolyzer in a later stage resulted in several benefits.

This study has found that a supplementary battery allowed for increased hydrogen production, as it allowed for a higher utilization of an electrolyzer. A priori, it was expected that the use of a battery would mostly smoothen hydrogen production on a daily level in scenarios only concerning PV as the battery would allow to sustain hydrogen production during the night. In addition to smoothened hydrogen production on a daily level, this study has found that batteries enabled effective use of occasional electricity surpluses during the winter. Thus, the inclusion of a supplementary battery smoothens the hydrogen production over the year.

The smoothened hydrogen production over the year resulted in lower seasonal hydrogen buffer requirements. As long as large scale hydrogen storage in is salt caverns is inaccessible, hydrogen may have to be bought and sold over the year, due to small local hydrogen storage capacities. When hydrogen production is fed from a PV array, local hydrogen storages would act as a transit center for hydrogen sales and purchases. The inclusion of a battery reduced the amount of hydrogen that had to be bought and sold. In these scenarios, increasing the hydrogen storage did not change the role of the storage as a transit center for buying and selling hydrogen. Therefore, investments to install large hydrogen storage (but not sufficient to get through the winter) are unnecessary in a hydrogen economy powered by PV.

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35 When PV and wind energy were combined, their complementary generation pattern was able to

generate a more stable electricity supply to the electrolyzer than either PV or wind could do as a standalone electricity supplier. Therefore, the required electrolyzer and battery capacities decreased when part of the PV was substituted by wind in the RE generation mix. All the combinations of PV and wind benefited from the inclusion of a battery, as the battery reduced the seasonal hydrogen storage capacity. A restricted storage capacity of 1000 kg resulted in large amounts of hydrogen sales and purchases in scenarios with a large share of wind, due to the long periods of wind intermittency. The amount of hydrogen that had to be bought and sold decreased drastically when the storage capacity increased to 5000 kg. The increased hydrogen storage capacity had sufficient inventory to get through these periods of wind intermittency. Therefore, when the share of wind energy increases, the need for a large local hydrogen storage rises. This will prevent unnecessary hydrogen sales and purchases and supports the independency of the local hydrogen economy.

To sustain hydrogen production over the year, there is a need for a stable electricity supply. Previous study have found that the complementarity of PV and wind result in lower energy storage requirements (Heide et al., 2011). This study confirms this finding by the lower hydrogen storage requirements in the scenarios with a combination of PV and wind. Moreover, the required battery capacities to fulfill the hydrogen demand were lower in these scenarios. The supplementary battery resulted in more constant production of hydrogen. The hydrogen production pattern in the scenarios that used a battery had a better fit with the hydrogen demand pattern. The latter resulted in lower seasonal buffer requirements for hydrogen.

Studies have stated that in order for large scale hydrogen production to come off the ground, investment costs have to be lowered (Kopp et al., 2017; Leeuwen & Mulder, 2018). This research showcases that the implementation of a battery allows for lower capacity requirements of electrolyzers and hydrogen storage under different combinations of PV and wind. Herein, financial trade-offs

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5.1. Limitations and further research

This study has only observed the production and demand patterns of one year. As these patterns can slightly differ in other years, the outcomes can be a bit different when other years are studied. However, the overall tendency will be similar. In order to strengthen the generalizability of the findings, future research could extend this research by running this simulation over multiple years.

Also, the RE generation supplied electricity to about 10,000 households and the hydrogen demand for residential heating only consisted of 112 households. The results found in this study should be

interpreted with caution regarding future projects where all households would have demand for both electricity and hydrogen. Further research could investigate a setting where all households demand both electricity and hydrogen.

This research minimized electrolyzer and battery capacities in order to produce a set amount of hydrogen. This approach gave valuable insights on the course of the hydrogen buffer over the year. A downside of this approach is inability to compare e.g. the hydrogen production under set electrolyzer and battery capacities under different electricity generation scenarios. Future research carefully think about the limitations and opportunities that these decisions bring.

Moreover, this study assumed that demand for residential heating is fulfilled only by hydrogen. It would also be possible to use a combination of heat pumps and hydrogen boilers to fulfill heating demand. Future research could investigate this combination.

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