Fuel Cell Electric Vehicle as a Power Plant: Techno-Economic Scenario Analysis of a Renewable Integrated Transportation and Energy System for Smart Cities in Two Climates
Abstract
:Featured Application
Abstract
1. Introduction
2. Materials and Methods
2.1. Approach
- Location selection, system design and dimensioning, technological and economic characterization for the system components in two technology development scenarios (Section 2.2).
- Developing a calculation model for hourly simulation of all energy flows for multiple years and sizing of system components, for two different European climates zones in two technology development scenarios (Section 2.3).
- Calculating the cost of energy for the two technology development scenarios in two climate zones based on the sizing and economic characterization of the system components (Section 2.4).
- Inter-annual variability analysis of wind and solar energy production on the cost of energy (Section 2.5).
2.2. Location Selection, System Design and Dimensioning, System Components, and Scenarios
2.2.1. Location Selection
- Located in a region with underground salt formations suitable for underground gas storage [104].
- One location should have a relatively low annual precipitation compared to European measurements [105].
- All required statistical and hourly modeling data should be available for the selected locations (wind velocity, solar irradiation, precipitation, building energy consumption, etc.).
2.2.2. System Design and Dimensioning
- uses only electricity and hydrogen as energy carriers and is all-electric in end-use
- uses only hydrogen as seasonal energy storage and fuel to power all road vehicles
- can be applied to an average European city area and is a scalable design
- can be integrated into existing infrastructure and buildings
- is not dependent on an in-urban area underground hydrogen pipeline transportation network
- uses abundant renewable energy sources in Europe: local solar and large-scale wind only
- is independent of high and medium voltage electricity grids, natural gas, and district heating grids or the expansion of these.
- Local solar electricity and hydrogen production (orange): Local rooftop solar electricity and rainwater collection, purification, and storage systems (S1–S3) produce solar electricity (ES) and pure water (H2OS). A part of the solar electricity is directly consumed (EDC) in buildings and other sub-systems. The remaining surplus solar electricity (ES) is used with purified water (H2OS) in the hydrogen production, purification, and compression system (S4–S6) for filling tube trailers (TT1) with hydrogen (HS).
- Fuel cell electric vehicle-to-grid, building electricity consumption, and smart grid control (yellow): The smart electric grid is managed by a controller, which connects all buildings, grid-connected FCEVs (FCEV1and2), the hydrogen fueling station (HFS1-HFS4), solar electricity and hydrogen production (S1–S6), and the tube trailer filling station (SHS2) at the seasonal hydrogen storage (SHS1). The directly consumed solar electricity (EDC) is divided amongst the all-electric residential and services sector buildings (EB), HFS (EHFS), and SHS (ESHS) electricity consumption. Any shortage of electricity is met by the electricity produced from hydrogen (EV2G) through parked (at home or in public or commercial spaces) and V2G connected FCEVs (FCEV1and2).
- Hydrogen tube trailer transportation (grey): Tube trailers (TT1) towed by tube trailer tractors (TT2) transport hydrogen from either the local solar hydrogen production or the SHS to the HFS, or from the local solar hydrogen production to the SHS.
- Hydrogen fueling station (blue): Hydrogen from tube trailers is further compressed (HFS1) and stored at high pressure (HFS2). A chiller (HFS3) cools the dispensed hydrogen (HHFS), including sufficient dispensers (HFS4) to provide hydrogen for both road transportation (Hroad) and V2G (HV2G) use.
- Road transportation (purple): A fleet of road transportation FCEVs, namely passenger cars, vans, buses, trucks, and tractor-trailers.
- Large-scale and shared wind hydrogen production (green): A large-scale wind turbine park (W1) that is not located near or in smart city areas is shared with other smart city areas and renewable hydrogen hubs and consumers. All wind electricity (EW) is used with purified water (H2OW) from local surface water or seawater in hydrogen production (W4), purification (W5), and compression system (W6), which includes a water collection and purification system (W2 and W3). The hydrogen produced (HW) is stored in a large-scale underground seasonal hydrogen storage (SHS1).
- Large-scale and shared seasonal hydrogen storage (red): Large-scale underground seasonal hydrogen storage (SHS1), including a tube trailer filling and emptying station (SHS2).
2.2.3. Technological and Economic Characterization of System Components in Two Scenarios
- The Near Future scenario uses current state-of-the-art renewable and hydrogen technology and current energy demand for buildings and transportation. It is an all-electric energy system, which means space heating is done using heat pumps, meeting the present heat demand for houses and buildings. Only commercially available hydrogen technologies are used. For all systems, including hydrogen technologies, current technology characteristics and cost figures are used. The Near Future scenario presents a system that could be implemented in 2020–2025.
- In the Mid Century scenario, a significant reduction in end-use energy consumption is assumed. Hydrogen and fuel cell technologies have become mature with mass production and performing on the cost and efficiency targets projected for 2050. Also, for all the other technologies, such as solar, wind, and electrolyzers, the learning curves are taken into account.
2.3. Calculation Model and Hourly Simulation
- Electricity consumption and production (yellow; see description in Appendix B.1)
- Road transport hydrogen demand (blue; see description in Appendix B.2)
- Electricity and hydrogen hourly balance (red; see description in Appendix B.3)
- Hydrogen tube trailer and tractor fleet (grey; see description in Appendix B.4)
- Wind hydrogen production and seasonal storage balance (green; see description in Appendix B.5)
2.4. Calculating the Cost of Energy
- Smart city area total system cost of energy (TSCoESCA) in euros per year (Appendix C.1).
- System levelized cost of energy for electricity (SLCoEe) in euros per kWh and for hydrogen (SLCoEH) in euros per kg of hydrogen (Appendix C.2).
- Cost of energy for households (CoEhh) in euros per household per year (Appendix C.3).
2.4.1. Smart City Area Total System Cost of Energy
2.4.2. System Levelized Cost of Energy
2.4.3. Cost of Energy for Households (Without Taxes and Levies)
2.5. Inter-Annual Variability Analysis
3. Energy Balance Results and Discussion
3.1. Annual Energy Balance Results
- Reliable electricity supply can be realized at all times, as extreme FCEV2G peaks never exceed 50% of the car fleet. Maximums of 760 and 772 cars, 32% and 42% of the car fleet in Hamburg and Murcia in the Near Future scenario, are reduced to 391 and 275 cars, 17% and 15% of the car fleet in the Mid Century scenario. The above maximums are extreme outliers, and values close to these occur for only a few hours per year (Figure A1).
- In the Mid Century scenario, FCEV2G usage is comparable to driving. In the Near Future scenario, the fleet average FCEV2G hours are 880 h/year compared to 440 h in Mid Century scenario at 10 kW/car output for Hamburg. For Murcia, this is 670 h and 330 h. The Mid Century scenarios’ FCEV2G hours are similar to the average driving hours for passenger cars: 310 and 280 h/year for, respectively, Hamburg and Murcia.
- The 87% higher solar electricity output in the Mid Century scenario in both locations results in less required external wind-to-hydrogen production to close the energy balance. This, together with more than a 30% reduction in building and road transportation energy consumption, and improvements in energy conversion processes, results in reductions of 70% and 90% of wind electricity production for, respectively, Hamburg and Murcia.
- The 490% higher solar hydrogen production in the Mid Century scenario in both locations compared to the Near Future scenario. Due to lower building electricity consumption and higher solar electricity production, there is more solar surplus electricity for hydrogen production. In Hamburg, solar electrolyzer power consumption always peaks in the summer’s time, whereas, in Murcia, solar electrolyzer power consumption peaks in winter (Figure A2).
- The 40% and 56% higher coverage of electricity consumption with direct solar electricity production in the Mid Century scenario in, respectively, Hamburg and Murcia compared to the Near Future scenario. Due to higher solar radiation and lower building and system electricity consumption, a higher percentage can be met directly with solar electricity. Nighttime electricity consumption has to be met with FCEV2G electricity production.
- The 15%–25% lower seasonal hydrogen storage requirements in the Mid Century scenario due to a better match of higher solar electricity production and lower building electricity demand compared to the Near Future scenario. For Hamburg, the maximum storage content of hydrogen occurs in the fall for both scenarios, whereas, in Murcia, this period shifts from spring to fall. The minimum storage content occurs in winter for both locations and scenarios. In the Mid Century scenario, a typical salt cavern [104] (Table A3) could serve approximately 23 similarly operating smart city areas in Hamburg and 40 Murcia smart city areas.
- The 40% lower seasonal hydrogen storage and FCEV2G requirements in Murcia compared to Hamburg, in all scenarios. In the Mid Century scenario, solar electricity alone is almost able to supply all of Murcia’s energy needs for buildings and road transportation (despite its 21% higher consumption of road transportation hydrogen; Appendix B.2). If approximately 15% more solar panels were to be installed, either on facades, in public spaces, or nearby solar fields, the entire energy demand could be met with solar energy. The reason for the lower SHS and FCEV2G requirements in Murcia compared to Hamburg is the better match in time (daily and seasonal) between solar electricity production and building electricity consumption. In addition, Murcia also has a relatively higher solar electricity output and lower building demand compared to Hamburg. In the Mid Century scenario in Murcia, the same solar system produces 73% more electricity than in Hamburg.
- Relatively, 70% and 30% more seasonal hydrogen storage is needed in the Mid Century scenario for, respectively, Hamburg and Murcia. Even though absolute hydrogen and electricity production, energy consumption, and seasonal hydrogen storage decrease in the Mid Century scenario, the higher dependency on solar electricity production increases the seasonal effect. Hence, there is an increase in relative seasonal hydrogen storage compared to the annual hydrogen and electricity production in the Mid Century scenario.
3.2. FCEV2G Usage and Electricity Balance Discussion and Results
- Reliable electricity supply can be realized at all hours of the day, as extreme FCEV2G peaks never exceed 50% of the total car fleet. The number of cars needed to balance the system peaks in the morning (06:00–09:00) and the late afternoon/early evening (16:00–20:00) and correspond to driving rush hours. These peaks are extreme outliers, and values close to these occur for only a small number of hours per year (Figure A1).
- In Murcia, virtually no cars are required during daylight hours. This is valid in all scenarios and seasons, except for some moments. In Hamburg, this is only the case in the summer period, for both scenarios.
- Hamburg faces a greater seasonal, and Murcia a greater day-night storage challenge, particularly in the Mid Century scenario. In Hamburg, peak FCEV2G electricity production occurs in the winter period, whereas, in Murcia, the production is highest in both the summer and the winter period (see also Figure A2).
- On average, less than 22% and 13% of all cars are required during peak hours (17:00–19:00), in, respectively, the Near Future and the Mid Century scenario (black crosses).
- In Murcia, the mean FCEV2G usage is highest in summer. In Hamburg, the mean FCEV2G usage is highest in winter. Electricity demand in Murcia is dominated by space cooling, whereas, in Hamburg, it is dominated by space heating. In the Mid Century scenario, the mean daily FCEV2G usage in the winter period in Hamburg is 7.3% of all cars, whereas, in Murcia, the figure is 4.6%. In summer, this is 3% of all cars in Murcia and 2.7% of all cars in Hamburg.
- Relatively more FCEV2G electricity is produced outside regular driving hours (20:00–06:00) [129] than during regular driving hours (06:00–20:00). In the Mid Century scenario, up to 60% of all FCEV2G electricity production in Murcia takes place during the 10 night hours (20:00–06:00); the remaining 40% FCEV2G electricity is produced during the 14 regular driving hours (06:00–20:00). In Hamburg, in the Mid Century scenario, the figures are 50% during the 10 regular driving hours and 50% during the 14 regular driving hours.
4. Cost of Energy Results and Discussion
4.1. Total System Cost of Energy
- The 70% reduction in TSCoE in the Mid Century compared to the Near Future scenario for both locations. Higher efficiencies, lower final energy consumption, and increased favorable match between solar electricity production and final energy consumption significantly reduce installed capacities, thus costs. Economies of scale also reduce both installed capital and operation and maintenance costs.
- The 20–30% lower TSCoE for Murcia compared to Hamburg for both scenarios. For Murcia, the TSCoE is 1.9 million euros/year in the Mid Century scenario, whereas, for Hamburg, it is 2.6 million euros/year. The reason for this is the lower final transportation and building electricity demand and lower storage and reconversion requirements.
- Variations in TSCoE from year to year are very small, 2.2–4.0% (coefficient of variation CV in Table A7 in Appendix E). This can be explained by the variations in daily and annual wind and solar electricity production, as well as the varying mismatch between solar electricity production and consumption. Seasonal hydrogen storage has relatively higher cost variations (8–12%) in comparison to other components, as the SHS is responsible for coping with all the above-mentioned variations.
- The cost of hydrogen components in the Mid Century scenario drops up to 75%. For both locations, in the Near Future scenario, the hydrogen components represent about 70% of the TSCoE; this reduces to 63% on average. As hydrogen technology is relatively new, economies of scale have a bigger impact on future cost reductions than on solar and wind electricity technology. In addition, the increase in solar output reduces storage requirements.
- Hydrogen transportation, seasonal hydrogen storage, and the solar system are the only components that share in the total costs’ relative increase compared to all other components. This is because the cost reductions for these components are relatively lower compared to the other components. The relatively higher use of seasonal hydrogen storage in the Mid Century scenario compared to the annual hydrogen production (see Section 3.1) is another contributing factor.
4.2. System Levelized Cost of Energy
- The system levelized cost of energy of electricity (SLCoEe) is 239 and 176 €/MWh in the Near Future scenario for, respectively, Hamburg and Murcia, and 104 and 71 €/MWh in the Mid Century scenario. The SLCoEe is calculated by summing the costs of solar and FCEV2G electricity for buildings and dividing it by the total building electricity consumption. The total costs of solar electricity for buildings are calculated by multiplying the solar electricity consumption of buildings (Figure 4 and Figure 5) by the levelized cost of energy of solar electricity (LCoEe,S). The total FCEV2G electricity costs are calculated by multiplying the FCEV2G electricity for buildings by the system levelized cost of energy of FCEV2G electricity (SLCoEe,V2G).
- All SLCoEe reduce by approximately 60% in the Mid Century scenario compared to the Near Future scenario. Also, in Murcia, the SLCoEe is about 30% lower compared to Hamburg. In Murcia, a larger part of the building load can be directly covered by cheap and abundant solar electricity (even for hydrogen production) in both scenarios. As a result, less hydrogen production, storage, dispensing, and FCEV2G electricity are required.
- The levelized cost of energy of hydrogen from surplus solar electricity (LCoEH,S in €/kg H2) in this system is always higher than the levelized cost of energy of hydrogen from wind electricity (LCoEH,W in €/kg H2). The levelized cost of energy of hydrogen (LCoEH,W&S) before transportation and storage is based on hydrogen from both wind and solar. Even in Murcia, in the Mid Century scenario, the cost of solar electricity (LCoEe,S) is lower than the cost of wind electricity LCoEe,W. The reason for this is that a significantly higher capacity factor is achieved when the electrolyzer is connected to the wind turbine than to the solar electricity system, which only uses surplus solar electricity peaks.
- The system levelized cost of energy of hydrogen (SLCoEH) is 70–80% higher than the combined levelized cost of energy of hydrogen from solar and wind (LCoEH,W&S). The SLCoEH includes the costs of hydrogen transportation by tube trailers, seasonal and fueling station storage, and dispensing on top of the solar and wind electricity costs, and the electrolyzers and low-pressure compressors, which is only the case for the LCoEH,W&S.
4.3. LCoE and SLCoE Comparison with Other Studies
- Onshore wind electricity costs (LCoEe,W) are relatively low in comparison with other studies. Near Future scenario 24–27 €/MWh compared to 30–50 €/MWh for 2025 [131], and Mid Century scenario 16–18 €/MWh with 20–35 €/MWh for 2050 [131]. There are three reasons for this. First, the exclusion of grid connection costs of 11.5% [132,133] in this study, because of the direct coupling between the wind turbine and the electrolyzer. Second, the use of a lower WACC (3%) compared to other studies (3.5–10%) [131]. Third, the placement of wind turbines on sites with good wind conditions, resulting in good onshore wind capacity factors (33–38%).
- Rooftop solar electricity costs (LCoEe,S) are comparable to the average small rooftop and utility-scale solar electricity costs, also known as community-scale or large rooftop. Near Future scenario costs of 38–68 €/MWh are similar to 20–90 €/MWh [134,135] in 2025, and Mid Century scenario costs of 18–32 €/MWh to 15–44 €/MWh [134] in 2050. The aforementioned values from the literature have similar global horizontal irradiation, although higher WACC (4–5%) [134,135].
- Stored and dispensed hydrogen costs (SLCoEH) are similar or lower compared to other studies. Near Future scenario costs of 4.9–5.2 €/kg H2 are similar to the 4–7 €/kg H2 according to studies by the Fuel Cell Hydrogen Joint Undertaking (FCH JU) and United States Department of Energy (US DoE) [136,137,138,139]. The SLCoEH in the Mid Century scenario of 2.6–3.0 €/kg H2 is slightly lower than the US DoE targets of dispensed hydrogen (3.3–3.9 €/kg H2) [140]. The major reasons for this are the higher electricity and expensive electrolyzer costs assumed by the US DoE.
- System electricity costs (SCLoEe) are similar to or lower than those in other studies on 100% renewable energy systems, including energy and transportation. The Near Future scenario SCLoEe of 179–239 €/MWh is lower compared to the transportation and energy system of the United States National Renewable Energy Laboratory (NREL) [3]. The difference can be explained by the system’s smaller scale, higher, and older component cost figures, and the use of stationary fuel cells instead of FCEV2G technology. The Mid Century scenario SLCoE-e of 71–104 €/MWh is close to the SLCoEe of 88 €/MWh for an average European smart city area, excluding seasonal hydrogen storage [36]. Several hydrogen electricity reconversion pathways in the north of Germany have been designed and evaluated for the year 2050, including underground seasonal hydrogen storage [141]. The study reports higher values of 176–247 €/MWh, although it confirms that the costs are dominated in all pathways by the costs of purchasing electricity [141]. The authors of [102] and [142] report similar values of 75–85 €/MWh and 100 €/MWh for 100% renewable and self-sufficient energy systems in 2050. Although they have similar system electricity costs, there are several differences: [102] and [142] use different storage technologies simultaneously, include more sectors (industry, agriculture, fishing, and forestry) and renewable energy sources, and either simulate for entire countries (Germany and Spain) [102] or cities in a different continent (North America) [142].
4.4. Cost of Energy for Households (Without Taxes and Levies)
5. Discussion
- The city area is not connected to any national electricity or natural gas grid or a transportation fuel network. It is self-sufficient and stand-alone.
- Only the residential, services, and road transportation sectors have been taken into account as energy consumers (e.g., not industry, agriculture, rail, or air transportation sectors).
- Space heating and hot water production are all-electric.
- It uses a single set of technologies for road transportation, transportation fuel, energy storage, and balancing, namely hydrogen, hydrogen production, and fuel cells (FCEVs), (no batteries or Battery Electric Vehicles, BEVs).
- The city area is relatively small, based on approximately 5000 people.
5.1. Other System Designs
- A national electricity grid connection would make it possible to import electricity or export peaks of solar electricity to other cities or electricity consumers in different sectors, such as industry, for example, by importing lower-cost onshore or offshore wind electricity during periods of insufficient solar electricity production (e.g., at night). This would reduce the need for hydrogen storage and FCEV2G electricity. High solar output at midday in the Mid Century scenario results in high surplus peaks to be absorbed by the solar electrolyzer. Exporting these high peaks of solar electricity to, for example, industrial cooling warehouses would reduce solar electrolyzer installed capacity and costs. Using only one electrolyzer connected to the national grid and placed next to the hydrogen station could reduce hydrogen transportation. Smart placement of electrolyzers in the electricity grid could obviate electricity grid congestion and reduce or avoid the need for expensive capacity expansion [144].
- A hydrogen pipeline network [32,145,146,147,148,149] could reduce hydrogen transportation via tube trailers and fueling station capacity. Multiple electrolyzers and hydrogen fueling stations could be interconnected via a pipeline network [150]. In this way, tube trailer hydrogen transportation could be replaced, and hydrogen transportation costs reduced. Furthermore, the partial re-compression of hydrogen when emptying a tube trailer could also be reduced or avoided altogether. The compressor could even be omitted, provided the electrolyzer hydrogen output pressure is higher than the pipeline pressure. In the case of parked FCEVs delivering V2G electricity, the fuel cell could be connected directly to the hydrogen distribution pipeline network, instead of using hydrogen from the on-board hydrogen tank [151]. Not using hydrogen from the 700 bar tank eliminates the need for refueling for V2G purposes, which in turn reduces the required capacity of hydrogen fueling stations.
- Import of low-cost renewable hydrogen could partially replace, possibly costlier, local hydrogen production and seasonal hydrogen storage, and thus total system costs. Locally and at certain times of the year, there could be insufficient solar and onshore wind sources available to produce hydrogen. Regions with abundant and low-cost hydro, solar, or wind power [152,153,154,155,156,157,158] could produce low-cost hydrogen for export. This hydrogen could be imported at demand centers instead of being produced and stored on-site. Several ideas already exist, for example, producing hydrogen (far) offshore [159] from fixed or floating wind [32,160,161,162] and solar structures [163,164], or wave energy [165] and bringing the hydrogen onshore via existing natural gas or newly built pipelines [32] or ships [166,167]. The onshore pipeline network would then distribute the hydrogen to the consumers.
- Using a lower-cost mix of renewable energy sources. In this study, the rooftop solar surface area was kept equal in both locations, even though solar electricity is more expensive in Hamburg than in Murcia. Therefore, using the lowest cost renewable energy source locally available could reduce total system costs even further. For example, hydropower, offshore wind, biomass, concentrated solar power, by-product hydrogen, or tidal or wave energy could result in lower-cost electricity than onshore wind or solar Photovoltaic (PV).
- Tailor electricity mix and its supply pattern to local demand. In Murcia, solar electricity production has a better time match with electricity consumption on both a daily and a seasonal basis. During the day, solar electricity production in summer aligns well with electricity demand in buildings for space cooling. Therefore, a lower total system cost can be achieved by tailoring the renewable energy mix to allow for a better match between the production pattern and the demand pattern [61,63,65,102,142,168,169,170,171,172,173,174,175,176,177]. This would result in lower hydrogen production, storage, transportation, fueling, and FCEV electricity production costs.
5.2. Other Balancing Methods
- Using a mix of FCEVs, BEVs, or fuel cell plug-in hybrid electric vehicle (FCPHEV) and stationary batteries [84,87,178,179,180]. Instead of only using hydrogen and FCEV2G for both daily and seasonal energy balancing, other technologies could be used in parallel. For example, batteries in BEVs or FCPHEV, as well as stationary batteries, could be used for storing or releasing peak surplus or shortage of electricity [181] for day-to-day storage. Especially in Murcia, this could result in lower total system costs, as the day-to-day storage is more prevalent in Murcia [182]. Capacity factors of electrolyzers could be improved, and so decrease costs. FCEVs and hydrogen production and storage could subsequently be used for energy balancing for longer periods, up to entire seasons [182].
- Using other CO2-free hydrogen carriers for energy transportation, short and long-term energy storage. There are several other proven and available carriers today, such as liquefied hydrogen [183,184,185,186,187], ammonia (NH3) [188], or liquid organic hydrogen carriers (LOHC) [189,190]. Transporting liquid hydrogen can be less costly compared to compressed hydrogen when volumes and distances are larger. Ammonia storage and LOHC storage are becoming commercial applications at scale, and both represent reasonable alternatives in the absence of salt caverns.
- Increase passenger car FCEV2G power output, use other FCEVs and stationary fuel cells for combined heat and power. At the moment, only passenger cars with an output of 10 kW/car while having a 100 kW fuel cell system on-board are used for FCEV2G electricity. This limitation is mainly because of potential insufficient cooling radiator capacity when parked and providing FCEV2G electricity [38]. If V2G output could be increased by enhancing cooling capacity, then proportionally fewer passenger cars would be needed. Cooling capacity could be enhanced by installing, for example, a bigger radiator and cooling fans, or by using two-phase cooling fluids with a higher cooling capacity [191]. Commercial vehicles (vans, trucks, buses) are more widely used than passenger cars, although often not during the night. By also using commercial for V2G purposes [192], the number of passenger cars would be reduced. In the case of an underground hydrogen pipeline network, stationary fuel cells [193,194,195,196,197,198] could provide heat and power to buildings, and when necessary, FCEV2Gs could provide peak power.
- Internet Technology (IT) usage for demand response forecasting, scheduling, virtual power plants, and autonomous driving. Weather and electricity demand forecasting [199,200,201,202,203,204,205,206,207,208] in combination with demand response [21,26,209,210,211] could potentially avert peaks in temporal surplus or shortage of electricity. This would reduce installed capacity cost. Combining the output of thousands of grid-connected FCEVs would create so-called virtual power plants [212,213] with potentially large capacities. Similar to mobility as a service (MaaS) [214,215,216,217,218], power or electricity as a service (PaaS or EaaS) could be introduced. To create these markets, additional pricing structures, contract types, and aggregators scheduling and operating the cars will be required [219,220,221,222]. Upcoming technologies could facilitate the scheduling of cars, for example, self-driving, free-floating, cloud-connected car-sharing fleets [223,224,225], together with inductive (wireless) self-connecting V2G infrastructure [226,227,228,229,230]. As mentioned earlier, most FCEV2G electricity is required at night, whereas most people travel and work during the day. So, even if car-sharing spreads widely and the total number of cars decreases, at night, car-sharing fleets will be used less and, therefore, will be available to provide power.
6. Conclusions
- The city area is not connected to any national grid; it is self-sufficient and stand-alone.
- Only the residential, services, and road transportation sectors have been taken into account as energy consumers.
- Space heating and hot water production are all-electric.
- It uses a single set of technologies for road transportation, transportation fuel, energy storage, and balancing; hydrogen, hydrogen production, and fuel cells (FCEVs and no batteries or BEVs).
- The city area is relatively small, based on approximately 5000 persons.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A. Locations Selection, System Design, Dimensioning, and Components
Appendix A.1. Location Selection
Key Figures | Locations | |
---|---|---|
Hamburg, Germany | Murcia, Spain | |
No. of inhabitants of urban area (# x 1,000,000) [231,232,233] | 1.8 | 1.5 |
Climate zone (Köppen–Geiger) (-) [44,234,235,236,237] | temperate oceanic (Cfb) | hot semi-arid (BSh) |
Weather station data | ||
Weather station height above sea-level (m) 1 [238,239] | 11 | 61 |
Weather station location 1 [238,239] | 53°38′ N, 9°59′ E | 38°0′ N, 1°10′ W |
Weather data 2012–2016 means and standard deviations | µ (CV) | µ (CV) |
Wind speed at 10 m above ground (m/s) 1 [238,242] | 4.1 (4.3%) | 3.9 (4.3%) |
Solar global horizontal irradiation (kWh/m2/year) [238,240] | 1020 (4%) | 1855 (1.8%) |
Precipitation (l/m2/year) [238,240] | 735 (4.9%) | 255 (24%) |
Air temperature (°C) [238,240] | 9.9 (5.9%) | 19.1 (2.8%) |
Daily maximum air temperature (°C) [238,240] | 13.4 (5.1%) | 25.5 (2.2%) |
Daily minimum air temperature (°C) [238,240] | 6.3 (8.7%) | 13.7 (4.4%) |
Heating Degree Days (°C·day/year) 2 [238,240] | 3066 (6.5%) | 854 (16%) |
Cooling Degree Days (°C·day/year) 2 [238,240] | 101 (24%) | 1245 (6.9%) |
Appendix A.2. Technological and Economic Characterization of System Components in Two Scenarios
Label (See Figure 2 and Table 2) | Energy Conversion Processes | Specific Energy Consumption/Production (SEC/SEP) | |
---|---|---|---|
Near Future [kWhe/kg H2] | Mid Century [kWhe/kg H2] | ||
W4 and S4 | Alkaline water electrolysis [246,255,256,257,258,259] | 44.4–50.0 1,2 | 42.6–47.7 1,2 |
S5 and W5 | Hydrogen purification [260,261] | 1.3 | 1.1 |
S6 | Compressor at local solar (500 bar) [115,263,264,265,266] | 3.0 3 | 1.8 3 |
W6 | Compressor at wind turbine park to SHS (180 bar) [115,263,264,265,266] | 1.9 3 | 1.0 3 |
HFS1 | Compressor at HFS ([30–500]–875 bar) [115,263,264,265,266] | 0.5–3.1 1 | 0.4–2.5 1 |
SHS2 | Compressor at SHS (180–500 bar) [115,263,264,265,266] | 0.8 | 0.6 |
HFS3 | Chiller [277,278] | 0.20 | 0.15 |
S2 and W2 | Reverse Osmosis—rainwater/surface water [272,273,274] | 0.006 | 0.006 |
FCEV1 | FCEV hydrogen to electricity [275,276,279] | 20.3 | 23.6 |
Label | Subsystems and Components | Near Future | Mid Century | ||||
---|---|---|---|---|---|---|---|
ICi | OMi [%/year] | LTi [years] | ICi | OMi [%/year] | LTi [years] | ||
Solar and wind electricity production | |||||||
S1 | Solar electricity system [134,280,281] | 725 €/kWp | 2.8% | 25 | 440 €/kWp | 2.3% | 30 |
W1 | Wind turbine park [132,133,280,281,282,283,284] | 975 €/kW | 2% | 25 | 800 €/kW | 1% | 25 |
Hydrogen production and compression | |||||||
S4 and S5 | Alkaline electrolyzer, including H2 purification at solar system [136,285,286,287,288] | 575 1 €/kW | 2.5% 2 | 203 | 200 €/kW | 2.5% 2 | 30 3 |
W4 and W5 | Large-scale alkaline electrolyzer, including H2 purification at wind turbines [136,285,286,287,288] | 480 1 €/kW | 4.2% 2 | 203 | 200 €/kW | 4.4% 2 | 30 3 |
S6 | Compressor at solar system [267,289] | 10,030/9630 €/kg H2/h 4 | 4% | 15 | 3445/3325 €/kg H2/h 4 | 2% | 15 |
W6 | Compressor at wind turbine park to SHS [267,289] | 8250/8915 €/kg H2/h 4 | 4% | 15 | 3515/6260 €/kg H2/h 4 | 2% | 15 |
Hydrogen transport | |||||||
TT1 | Tube trailer storage [136,190,267] | 830 €/ kg H2 | 2% | 30 | 510 €/ kg H2 | 2% | 30 |
TT2 | Trailer tractors [136,190,267] | 160,000 €/ tractor | 61/65% 5 | 8 6 | 160,000 €/tractor | 63/62% 5 | 8 6 |
Hydrogen fueling station (HFS) | |||||||
HFS1 | Compressor at HFS [267,289] | 8375/8820 €/kg H2/h 4 | 4% | 10 | 3630/3670 €/kg H2/h 4 | 2% | 10 |
HFS2 | Storage HFS 875 bar [263,290,291] | 920 €/kg H2 | 1% | 30 | 575 €/ kg H2 | 1% | 30 |
HFS3 | Chiller units [263,289] | 143,875 €/kg H2/min | 2% | 15 | 118,520 €/kg H2/min | 2% | 15 |
HFS4 | Dispensers units [260,261,263,289] | 91,810 €/unit | 1.1% | 10 | 72,890 €/unit | 0.9% | 10 |
Fuel cell electric vehicle to grid (FCEV2G) | |||||||
FCEV1 | Replacement of fuel cell system in FCEV for V2G use [36,38,275,276,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307] | 3970 €/100 kW | 5% | 4100 h 7 | 2650 €/100 kW | 5% | 8000 h 7 |
FCEV2 | Smart grid, control, and V2G infrastructure [134] | 6400 €/4-point dischargers | 5% | 15 | 3200 €/4-point dischargers | 5% | 15 |
Seasonal hydrogen storage (SHS) | |||||||
SHS1 | SHS plant (3733 ton H2 cavern) [104] | 107,000,000 €/plant | 0.5% | 30 | 107,000,000 €/plant | 0.5% | 40 |
SHS2 | Compressor at SHS [267,289] | 3470/3825 €/kg H2/h 4 | 4% | 15 | 1560/1665 €/kg H2/h 4 | 2% | 15 |
Water purification and storage | |||||||
S2 and W2 | Water purification [272] | 1,200 €/m3/day | 4.8% | 25 | 1,200 €/m3/day | 4.8% | 25 |
S3 and W3 | Pure-water tank [121,122,123,124] | 120 €/m3 | 0.33% | 50 | 120 €/m3 | 0.33% | 50 |
Appendix B. Detailed Description and Background Data of the Calculation Model and Hourly Simulation
Appendix B.1. Electricity Consumption and Production
- Space heating
- Space cooling
- Water heating
- Cooking
- Lighting
- Electrical appliances
Energy Consumption Category | Specific Energy Consumption Buildings SECB [kWh/m2/Year] | |||||
---|---|---|---|---|---|---|
Hamburg, Germany | Murcia, Spain | |||||
Present Situation | Near Future | Mid Century | Present Situation | Near Future | Mid Century | |
Residential sector | ||||||
Space heating [54] | 131.1 1 | 29.2 | 6.6 | 13.8 1 | 2.7 | 0.7 |
Space cooling [51] | 0.9 b | 0.9 | 0.3 | 30.2 2 | 30.2 | 9.1 |
Water heating [54] | 32.3 1 | 24.5 | 16.2 | 16.4 1 | 13.7 | 8.2 |
Cooking [54] | 7.8 1 | 7.4 | 7.4 | 7.7 1 | 6.7 | 6.7 |
Lighting [54] | 2.9 2 | 2.3 | 0.6 | 4.9 2 | 3.9 | 1.0 |
Electrical appliances [54] | 18.9 2 | 18.9 | 18.9 | 25.7 2 | 25.7 | 25.7 |
Total | 194.0 | 83.2 | 49.8 | 98.6 | 82.9 | 51.3 |
Services sector | ||||||
Space heating [55] | 80.3 1 | 18.3 | 12.1 | 48.3 1 | 11.4 | 7.2 |
Space cooling [50] | 3.4 2 | 3.4 | 1.0 | 43.0 2 | 43.0 | 12.9 |
Water heating [55] | 8.3 1 | 7.3 | 4.1 | 7.7 1 | 6.4 | 3.8 |
Cooking [55] | 13.1 1 | 11.5 | 11.5 | 4.1 1 | 3.5 | 3.5 |
Lighting 3 [55] | 28.8 2 | 23.0 | 5.8 | 71.5 2 | 57.2 | 14.3 |
Electrical appliances [55] | 39.7 2 | 39.7 | 39.7 | 49.0 2 | 49.0 | 49.0 |
Total | 173.6 | 103.3 | 74.2 | 223.5 | 170.5 | 90.8 |
Total annual Energy consumption buildings EB [MWh/year] | ||||||
Hamburg | Murcia | |||||
Present Situation | Near Future | Mid Century | Present Situation | Near Future | Mid Century | |
Residential | 35,541 | 15,241 | 9127 | 18,105 | 15,225 | 9422 |
Services | 16,130 | 9597 | 6893 | 8567 | 6535 | 3479 |
Total | 51,671 | 24,838 | 16,020 | 26,672 | 21,760 | 12,901 |
Energy Consumption Category | Specific Energy Consumption Savings Compared to Present Situation | |
---|---|---|
Residential Sector | Near Future | Mid Century |
Space heating [309,310,311,312,313] | 71% 1 | 95% |
Space cooling [51,309,310,313] | 0% | 70% |
Water heating [54,55,127,311,313] | 24/16% 2 | 50%/50% 3 |
Cooking [54,55,127] | 5/13% 2 | 5/13% 2 |
Lighting [314] | 20% | 80% |
Electrical appliances [317,318,319] | 0% 4 | 0% 4 |
Services sector | ||
Space heating [309,310,311,312,313] | 71% 1 | 85% |
Space cooling [50,309,310,313] | 0% | 70% |
Water heating [54,55,127,313] | 12/17% 2 | 50%/50% 3 |
Cooking [54,55,127] | 12/15% 2 | 12/15% 2 |
Lighting [314,315,316] | 20% | 80% |
Electrical appliances [317,318,319] | 0% 4 | 0% 4 |
- Space heating SECB is multiplied by the normalized hourly profile of aggregated natural gas consumption profiles for space heating, only in the residential [321] and the services sector [322], and the daily HDD profile with base temperature 18 °C [323]. The natural gas consumption profiles for space heating only are made by subtracting the natural gas consumption for water heating from the total natural gas consumption profiles.
- Water heating SECB is multiplied by the normalized hourly profile of the aggregated gas consumption profiles for water heating only. The natural gas consumption for water heating is extracted from the total aggregated natural gas consumption profiles during the period of 3 summer weeks (day 205 of the year onwards) with ambient temperatures above 18 °C, where it is assumed no space heating is taking place [321,322]. As the profiles are based on aggregated values, it is assumed that holiday effects are excluded.
Appendix B.2. Road Transportation Hydrogen Demand
Specific Energy Consumption Transportation SECT [kg H2/100 km] | Average Annual Distance Driven d [km/year/vehicle] | |||
---|---|---|---|---|
Vehicle Type | Near Future [36] | Mid Century [36] | Hamburg, Germany [119,120] | Murcia, Spain [57] |
Passenger car | 1.0 | 0.6 | 13,728 | 12,535 |
Van | 1.3 | 0.9 | 19,388 | 17,704 a |
Truck | 4.6 | 3.7 | 31,870 b | 37,077 |
Tractor-trailer | 6.9 | 5.5 | 96,211 | 151,513 |
Bus | 8.6 | 6.9 | 55,883 | 147,398 |
Hamburg, Germany | Murcia, Spain | |||
Annual hydrogen consumption Hroad | Near Future | Mid Century | Near Future | Mid Century |
Hydrogen [kg H2 /year] | 479,909 | 316,129 | 545,192 | 381,732 |
Hydrogen Energy c [MWhHHV/year] | 18,913 | 12,459 | 21,486 | 15,044 |
Appendix B.3. Electricity and Hydrogen Hourly Balance
Appendix B.4. Hydrogen Tube Trailer and Tractor Fleet
Appendix B.5. Wind Hydrogen Production and Seasonal Hydrogen Storage Balance
Appendix C. Calculating Cost of Energy
Appendix C.1. Smart City Area Total System Cost of Energy
Appendix C.2. System Levelized Cost of Energy
Appendix C.3. Cost of Energy for Households (Without Taxes and Levies)
Appendix D. Energy Balance Figures
Appendix E. Total System Cost Table
Hamburg | Murcia | ||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Near Future | Mid Century | Near Future | Mid Century | ||||||||||||||
Label | Subsystems and Components | Qi | TCi | Qi | TCi | Qi | TCi | Qi | TCi | ||||||||
µ | CV [%] | µ [k€/yr] | CV [%] | µ | CV [%] | µ [k€/yr] | CV [%] | µ | CV [%] | µ [k€/yr] | CV [%] | µ | CV [%] | µ [k€/yr] | CV [%] | ||
Electricity production | |||||||||||||||||
S1 | Solar electricity system [MWp] | 11.20 | - | 690 | 18.67 | - | 600 | - | 11.20 | - | 690 | - | 18.67 | - | 600 | - | |
W1 | Wind turbines park share [MW] | 23.36 | 8.3 | 1760 | 8.3 | 7.26 | 10.1 | 390 | 10.1 | 18.60 | 6.5 | 1400 | 6.5 | 1.43 | 16.4 | 80 | 16.4 |
Hydrogen production and compression | |||||||||||||||||
S4 and S5 | Alkaline electrolyzer—solar [MW] | 6.20 | 5.7 | 330 | 4.5 | 14.63 | 4 | 220 | 3.7 | 6.97 | 4.8 | 360 | 3.8 | 16.23 | 5.5 | 240 | 4.9 |
W4 and W5 | Alkaline electrolyzer share—wind [MW] | 21.95 | 8.3 | 1150 | 8.3 | 6.95 | 10.1 | 130 | 10.1 | 17.48 | 6.5 | 920 | 6.5 | 1.36 | 16.4 | 30 | 16.4 |
S6 | Compressor—solar [kg H2/h] | 125 | 5.7 | 150 | 3.7 | 308 | 4 | 110 | 2.6 | 140 | 4.8 | 170 | 3.1 | 342 | 5.5 | 120 | 3.6 |
W6 | Compressor share—wind [kg H2/h] | 441 | 8.3 | 450 | 5.5 | 146 | 10.1 | 50 | 6.7 | 351 | 6.5 | 390 | 4.3 | 29 | 16.4 | 20 | 10.5 |
Hydrogen transport | |||||||||||||||||
TT1 | Tube trailer storage [kg H2] | 4620 | 9.5 | 270 | 9.5 | 4400 | 0 | 160 | 0 | 4400 | - | 260 | 0 | 4400 | - | 160 | - |
TT2 | Tractor-trailers [#] | 1.9 | 6.6 | 200 | 1.7 | 1.1 | 9.5 | 120 | 2.3 | 1.4 | 8.7 | 160 | 1.9 | 1.3 | - | 140 | 0.6 |
Hydrogen fueling station (HFS) | |||||||||||||||||
HFS1 | Compressor [kg H2/h] | 489 | 4 | 640 | 4.6 | 240 | 3.4 | 120 | 2.4 | 343 | 9.6 | 480 | 8.3 | 172 | 5.1 | 90 | 8.4 |
HFS2 | Stationary storage 875 bar [kg H2] | 5705 | 4.6 | 320 | 4.6 | 2715 | 3.2 | 100 | 3.2 | 4051 | 10.7 | 230 | 10.7 | 1954 | 5.5 | 70 | 5.5 |
HFS3 | Chiller capacity [kg H2/min] | 9.5 | 4.6 | 140 | 4.6 | 4.5 | 3.2 | 60 | 3.2 | 6.7 | 10.7 | 100 | 10.7 | 3.3 | 5.5 | 40 | 5.5 |
HFS4 | Dispensers units [#] | 29.2 | 4.6 | 340 | 4.6 | 4.5 | 3.2 | 40 | 3.2 | 20.7 | 10.7 | 240 | 10.7 | 3.3 | 5.5 | 30 | 5.5 |
FCEV2G | |||||||||||||||||
FCEV1 | Replacement of FC system in FCEV due to V2G use only [#100 kW systems] | 755 | 7.5 | 1190 | 1.2 | 389 | 3.3 | 230 | 0.8 | 774 | 4.3 | 750 | 1.7 | 265 | 2.2 | 140 | 1.2 |
FCEV2 | Smart grid, Control, and V2G infrastructure [# 4-point dischargers] | 189 | 7.5 | 160 | 7.5 | 97 | 3.2 | 40 | 3.2 | 193 | 4.3 | 170 | 4.3 | 66 | 2.2 | 30 | 2.2 |
Seasonal hydrogen storage (SHS) | |||||||||||||||||
SHS1 | Share of SHS plant (3733 ton H2 cavern) [%] | 4.1 | 14.7 | 250 | 14.7 | 3.8 | 7.9 | 200 | 7.9 | 3.9 | 12.9 | 230 | 12.9 | 2.1 | 12.2 | 110 | 12.2 |
SHS2 | Tube trailer filling (compressor) at SHS [kg H2/h] | 488 | 4.2 | 210 | 8.5 | 239 | 3.4 | 40 | 12.5 | 341 | 9.7 | 160 | 6.3 | 171 | 5 | 30 | 3.2 |
Water purification and storage | |||||||||||||||||
S2 | Reverse osmosis—solar [m3/day] | 95 | 8.3 | 12 | 8.3 | 31 | 10.1 | 4 | 10.1 | 75 | 6.4 | 10 | 6.4 | 6.2 | 16.4 | 1 | 16.4 |
W2 | Reverse osmosis—wind [m3/day] | 6.7 | 3.8 | 0.8 | 3.8 | 20 | 4.5 | 2.6 | 4.5 | 7.6 | 5.7 | 1 | 5.7 | 21 | 2.1 | 2.6 | 2.1 |
S3 | Pure-water tank—solar [m3] | 13 | 3.8 | 0.1 | 3.8 | 41 | 4.5 | 0.2 | 4.5 | 15 | 5.7 | 0.1 | 5.7 | 42 | 2.1 | 0.2 | 2.1 |
W3 | Pure-water tank—wind [m3] | 189 | 8.3 | 1 | 8.3 | 63 | 10.1 | 0.3 | 10.1 | 150 | 6.4 | 0.8 | 6.4 | 12 | 16.4 | 0.1 | 16.4 |
Total | 8290 | 4 | 2620 | 2.2 | 6710 | 3.7 | 1920 | 2.7 |
Appendix F. Background Figures Cost of Energy for a Household
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Label | Components | Label | Components |
---|---|---|---|
S | Local solar electricity and hydrogen production | TT | Hydrogen tube trailer transportation |
S1 | Solar electricity system | TT1 | Tube trailers |
S2 | Water purification (reverse osmosis) | TT2 | Trailer tractors |
S3 | Pure-water tank | FCEV | Fuel cell electric vehicle-to-grid (V2G) |
S4 | Electrolyzer | FCEV1 | Fuel cell in fuel cell electric vehicle (FCEV) for V2G use |
S5 | Hydrogen purifier | FCEV2 | V2G infrastructure |
S6 | Low-pressure compressor | Energy and water flows | |
W | Large-scale and shared wind hydrogen production | E | Electricity |
W1 | Shared wind turbine park | EW | Electricity from wind |
W2 | Water purification (reverse osmosis) | ES | Electricity from solar |
W3 | Pure water tank | EDC | Direct consumption solar electricity |
W4 | Electrolyzer | Esurp | Surplus solar electricity |
W5 | Hydrogen purifier | EB | Electricity consumption in buildings |
W6 | Low-pressure compressor to SHS | EV2G | Electricity from hydrogen via V2G |
HFS | Hydrogen fueling station (HFS) | EHFS | Electricity consumption HFS |
HFS1 | High-pressure compressor | ESHS | Electricity consumption SHS |
HFS2 | High-pressure stationary storage | H | Hydrogen |
HFS3 | Chillers | HW | Hydrogen from wind electricity |
HFS4 | Dispensers | HS | Hydrogen from surplus solar electricity |
SHS | Large-scale and shared seasonal hydrogen storage (SHS) | HHFS | Dispensed hydrogen at HFS |
SHS1 | Shared seasonal hydrogen storage (SHS) | HRoad | Hydrogen consumed by road vehicles |
SHS2 | Low-pressure compressor | HV2G | Hydrogen consumed for V2G electricity |
H2O | Water | ||
H2OW | Water for hydrogen production via wind | ||
H2OS | Water for hydrogen production via solar |
Characteristics | Quantity | |
---|---|---|
Hamburg, Germany | Murcia, Spain | |
Common parameters (based on European statistics) | ||
Gas stations (#) [114] | 1 | 1 |
Retail food shops (#) [112] | 1 | 1 |
Households and dwellings 1 in smart integrated city (#) [54] | 2000 | 2000 |
Local parameters (based on national statistics) | ||
People (#) [118] | 4310 | 5083 |
Passenger cars (#) [57,119,120] | 2364 | 1846 |
Vans (#) 2 [57,119,120] | 115 | 356 |
Trucks (#) [57,119,120] | 27 3 | 31 4 |
Tractor-trailers [57,119,120] | 10 | 12 4 |
Buses (#) [57,119,120] | 4.1 | 4.5 |
Floor area of residential buildings (m2) 5,6 [54] | 183,200 | 183,550 |
Floor area of services buildings (m2) 6 [55] | 92,940 | 38,330 |
Roof area available for solar electric modules (m2) [125,126] | 56,000 | 56,000 7 |
Location | Hamburg | Murcia | ||
---|---|---|---|---|
Scenario | Near Future | Mid Century | Near Future | Mid Century |
FCEV2G | ||||
Fleet average FCEV2G hours at 10 kW (hours/year) | 880 | 440 | 670 | 330 |
Annual electricity production (MWh) | 20,794 | 10,388 | 12,247 | 6112 |
Max. power (MW) | 7.60 | 3.91 | 7.72 | 2.75 |
Date max. power (dd-mm) | 3 January | 4 January | 12 June | 3 September |
Max. FCEV2Gs (#) / Max fleet percentage (%) | 760/32.1 | 391/16.5 | 772/41.8 | 275/14.9 |
FCEV Driving | ||||
Average driving time passenger car (hours/year) | 310 | 310 | 280 | 280 |
Solar electrolyzer | ||||
Capacity factor (%) | 4.1 | 8.6 | 7.8 | 15.5 |
Annual electricity consumption (MWh) | 2680 | 12,428 | 5658 | 7648 |
Max. absorbed power (MW) | 7.43 | 16.47 | 8.26 | 19.05 |
Date max. power (dd-mm) | 27 July | 27 July | 23 February | 23 February |
SHS | ||||
Max. H2 storage (×1000 kg H2) | 191 | 163 | 122 | 92 |
Max. H2 storage relative to typical SHS 3733 ton H2 (%) | 5.1 | 4.4 | 3.2 | 2.5 |
No. similar smart city areas served by one typical SHS (#) | 20 | 23 | 30 | 40 |
Date max. storage (dd-mm) | 4 September | 29 September | 29 May | 6 October |
Date min. storage (dd-mm) | 24 January | 15 March | 3 February | 17 February |
Annual hydrogen production (×1000 kg H2) | 1504 | 753 | 1149 | 640 |
Max. H2 storage relative to annual hydrogen production (%) | 13 | 22 | 11 | 14 |
Max. H2 storage relative to annual electricity production (%) | 8.9 | 15 | 6.7 | 9.3 |
Hamburg | Murcia | ||||
---|---|---|---|---|---|
Levelized Cost Parameter | Involved Cost (TCi) of Components (i) (Table A7 Appendix E) | Near Future | Mid Century | Near Future | Mid Century |
LCoEe,S [€/MWh] | S1 | 68 | 31.7 | 37.6 | 17.5 |
LCoEe,W [€/MWh] | W1 | 23.5 | 16 | 26.5 | 18.2 |
LCoEH,S [€/kg H2] | S1–6 | 13.7 | 2.9 | 6.5 | 1.5 |
LCoEH,W [€/kg H2] | W1–6 | 2.3 | 1.2 | 2.7 | 1.4 |
LCoEH,W&S [€/kg H2] | W1–6 and S1–6 | 2.7 | 1.7 | 3 | 1.5 |
System levelized cost parameter | |||||
SLCoEH [€/kg H2] | W1–6, S1–6 (surplus), TT1and2, SHS1and2, HFS1–4, | 4.9 | 3 | 5.2 | 2.6 |
SLCoEe,V2G [€/MWh] | W1–6, S1–6 (surplus), TT1and2, SHS1and2, HFS1–4, FCEV1and2 | 307 | 154 | 332 | 139 |
SLCoEe [€/MWh] | W1–6, S1–6, TT1and2, SHS1and2, HFS1–4, FCEV1and2 | 239 | 104 | 179 | 71.2 |
Hamburg | Murcia | |||||
---|---|---|---|---|---|---|
Annual Cost of Energy for Households (Without Taxes and Levies) | Present | Near Future | Mid Century | Present | Near Future | Mid Century |
Building CoEhh,B [€/hh/year] | 1050 | 1820 | 480 | 1120 | 1360 | 340 |
Transportation CoEhh,T [€/hh/year] | 460 | 790 | 290 | 350 | 570 | 180 |
Total CoEhh [€/hh/year] | 1510 | 2610 | 770 | 1470 | 1930 | 520 |
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Oldenbroek, V.; Smink, G.; Salet, T.; van Wijk, A.J.M. Fuel Cell Electric Vehicle as a Power Plant: Techno-Economic Scenario Analysis of a Renewable Integrated Transportation and Energy System for Smart Cities in Two Climates. Appl. Sci. 2020, 10, 143. https://doi.org/10.3390/app10010143
Oldenbroek V, Smink G, Salet T, van Wijk AJM. Fuel Cell Electric Vehicle as a Power Plant: Techno-Economic Scenario Analysis of a Renewable Integrated Transportation and Energy System for Smart Cities in Two Climates. Applied Sciences. 2020; 10(1):143. https://doi.org/10.3390/app10010143
Chicago/Turabian StyleOldenbroek, Vincent, Gilbert Smink, Tijmen Salet, and Ad J.M. van Wijk. 2020. "Fuel Cell Electric Vehicle as a Power Plant: Techno-Economic Scenario Analysis of a Renewable Integrated Transportation and Energy System for Smart Cities in Two Climates" Applied Sciences 10, no. 1: 143. https://doi.org/10.3390/app10010143