The price at whichH2 is sold to each customer must cover, at least, energy expenses related to its production and compression. In that case, the minimum prices for each customer can be determined by:
πHCHP min2 = πeB ηELEC
·HHVH2 (4.1)
πHFL min2 = πeB ηELEC
·HHVH2+πeB·PCPFL (4.2)
πHT RSP min
2 = πeB
ηELEC
·HHVH2+πeB·PCPT RSP (4.3)
whereπeBis the average price of electricity.
However, to cover other expenses such as the costs (CAPEX and OPEX) of equipment, main-tenance, depreciation, and loan interest, among others, and to make the plant profitable, the prices obtained using Equations4.1,4.2and4.3have to be further increased, as demonstrated up ahead.
Nevertheless, the ratio between them is kept constant, unless otherwise specified.
Table 4.15: List and description of the six main simulation scenarios.
Scenario Description
Grey17-20
H2PP participates in the MIBEL to buy and sell electricity Consumes electricity at any hour of the day
Uses electricity prices data from 2017 to 2020 Green17-20
H2PP participates in the MIBEL to buy and sell electricity
Consumes electricity when production in the Portuguese hub is from RES only Uses electricity prices data from 2017 to 2020
PPA17-20
H2PP acquires electricity through a PPA with a wind farm H2PP sells electricity at MIBEL’s price
Uses energy prices data from 2017 to 2020 Grey21
H2PP participates in the MIBEL to buy and sell electricity Consumes electricity at any hour of the day
Uses electricity prices data from 2021 Green21
H2PP participates in the MIBEL to buy and sell electricity
Consumes electricity when production in the Portuguese hub is from RES only Uses electricity prices data from 2021
PPA21
H2PP acquires electricity through a PPA with a wind farm H2PP sells electricity at MIBEL’s price
Uses energy prices data from 2021
two parts are bounded by long-term conditions, which can be disadvantageous for one of them:
if the electricity price rises the producer loses revenue and if the price falls it is the customer that fails to benefit [145]. There is not much information available regarding the agreed electricity price for these contracts, so it adopted a value close to that of the Feed-In Tariff (FIT). In 2013, the Portuguese Government published the Decree Law 35/2013, starting the possibility for voluntary changes of the FIT and offering wind power producers different remuneration schemes. One of those schemes, chosen by multiple organizations, defines this tariff as the average market price of the previous twelve months and has a floor of 74 C/MWh and a cap of 98 C/MWh [146]. Based on this information, the price of electricity for this fictitious PPA is set to the average of those two values: 86 C/MWh.
The Grey, Green and PPA scenarios are also split in accordance with time spans. When the suffix 17-20 is used, the operation of theH2PP is simulated in the years from 2017 to 2020. The results of those 4 years are then combined, creating an "average year" to be replicated 20 times, covering the plant’s entire lifetime. Conversely, when the suffix 21 is used, the operation of the H2PP is simulated for the year 2021, using the corresponding data regarding energy prices and
usage of renewable and non-renewable sources (needed for the Green scenarios). To cover the project’s lifetime this year is, as before, replicated 20 times.
There are two main reasons to split the year 2021 from the others. First, due to the global ongoing energy crisis, the price of electricity in the MIBEL suffered a substantial increase. In fact, in the last trimester of 2021, the price of electricity in the Iberian market was over three times higher than in the last quarter of 2018 [147]. Secondly, with the decommissioning of a large coal-fired power plant in January 2021 [148] (the Sines coal-coal-fired power plant, preceded by a reduction in its production in the years before [149]) the number of hours available to generate greenH2 significantly increased. This is supported by the data provided in Table4.16, where the average price of electricity in MIBEL and the number of hours with no production from large CCGT or coal power plants in Portugal are presented.
Table 4.16: Average price of electricity in Portugal and number of green hours [150].
Year Average price [ C/MWh] Green hours [h]
2017 52.48 41
2018 57.45 593
2019 47.87 436
2020 34.03 1161
2021 112.1 1471
4.3.1 Simulation results of base case scenarios
The described scenarios were simulated, and an economic analysis was carried out for each one. The required prices to reach a payback period of 13 years are shown in Table4.17.
Table 4.17:H2prices for each customer, to reach a 13 years payback.
Scenarios πHCHP
2 [ C/kg] πHFL2 [ C/kg] πHTRSP
2 [ C/kg]
Grey17-20 5.092 5.337 5.243
Green17-20 31.79 33.32 32.73
PPA17-20 7.357 7.711 7.575
Grey21 7.336 7.689 7.553
Green21 13.93 14.60 14.34
PPA21 7.349 7.703 7.567
Regarding the 17-20 scenarios, the most favourable one is Grey17-20, with H2 prices close to 5-5.4 C/kg. This result was expected because, in this situation, energy costs are low (when compared to 2021), and the electrolyser is not restricted to hours of only renewable production.
Meanwhile, in Green17-20,H2prices are considerably higher, surpassing 30 C/kg, since the hours
for the plant to produceH2 are quite limited. In the PPA17-20 scenario,H2 prices are closer to those of Grey17-20, but still higher, around 7-8 C/kg.
For the 2021 scenarios, like before, the production of greyH2 leads to the lowest prices in Grey21, between 7-8 C/kg, but higher than those of Grey17-20 due to the rise in electricity costs.
Contrastingly, the renewable scenario experienced a positive evolution due to the decrease in non-renewable sources, with Green21 presenting prices from 13-15 C/kg. In the PPA scenario, the production is not affected by energy costs, and, as such, prices did not face major changes, staying within 7-8 C/kg.
The variation of the payback period with the price ofH2 for each customer, across these six different settings, is presented in Figures 4.4, 4.5 and 4.6. It can be seen how, in all the given scenarios, as the prices increase the payback period drops at a decreasing rate.
Figure 4.4: Grey scenarios - Relation between payback period andH2price for each customer.
To complement the price analysis, it is considered the possibility of a more uncertain payback period, varying between 11 and 15 years, that is, 13±2 years. A situation like this could arise from uncertain factors, such as sudden changes in a hypothetical hydrogen market, which would lead to a need to adjustH2prices to ensure thisH2PP remains competitive.
The prices leading to a payback of 11 and 15 years are also marked in Figures4.4,4.5and4.6 and listed in Table4.18.
For the prices conducting to a payback of 13 years, a set of economic metrics used to assess the performance of the investment were computed, namely: Net Present Value (NPV), Internal Return Rate (IRR) and Levelised Cost of Hydrogen (LCOH). The LCOH is calculated in accordance with [119]. The results, given in Table4.19, line up with the aforesaid analysis.
Like before, Grey17-20 is the most beneficial setting and Green17-20 is the least promising.
The main differences are in the LCOH, which varies substantially between scenarios. The NPV
reaches similar values, close to 315,000 C in all scenarios bar the Green ones, where it is lower.
The difference in return rates is negligible.
Figure 4.5: Green scenarios - Relation between payback period andH2price for each customer.
Figure 4.6: PPA scenarios - Relation between payback period andH2price for each customer.
The average yearly values of hydrogen produced by the electrolyser and consumed by the fuel cell and the customers are provided in Table4.20. The results show how the increase in energy prices from Grey17-20 to Grey21 led to a decrease inH2generation and commercialization. Also, the lack of production in Green17-20 and its significant boost in Green21 are evidenced. The PPA scenarios show similar results, with the difference being that, since production costs do not change but the price at which the fuel cell sells energy increases from PPA17-20 to PPA21, it injects more power into the grid.
Also, Table4.20shows how the fuel cell, which was set to sell energy to the grid at market price, is barely activated. This situation, worsen by its low efficiency (50%), can be solved by increasing the energy selling price. This solution, implemented further ahead in this work, can be triggered by the H2PP operator, who shall control this price to boost the competitiveness of the fuel cell.
Table 4.18:H2prices for each customer to reach a payback period of 11 years and 15 years.
Scenarios πHCHP
2 [ C/kg] πHFL
2 [ C/kg] πHTRSP
2 [ C/kg]
11 years 15 years 11 years 15 years 11 years 15 years Grey17-20 5.220 4.991 5.471 5.231 5.375 5.139 Green17-20 33.27 30.74 34.83 32.22 34.21 31.65
PPA17-20 7.479 7.259 7.838 7.606 7.701 7.474
Grey21 7.508 7.197 7.869 7.543 7.730 7.411
Green21 14.45 13.52 15.14 14.19 14.88 13.93
PPA21 7.469 7.249 7.828 7.598 7.692 7.464
Table 4.19: Economic metrics corresponding to a 13 years payback.
Scenarios NPV [ C] IRR [%] LCOH [ C/kg]
Grey17-20 315,075 15.99 4.72 Green17-20 253,426 15.29 21.7
PPA17-20 312,990 15.95 7.59
Grey21 313,611 15.96 6.88
Green21 252,662 15.28 10.6
PPA21 314,818 15.99 7.57
Table 4.20: Average yearlyH2production and consumption, for a 13 years payback.
Scenarios
Electrolyser Fuel cell CHP Forklift fleet Tube trailer production consumption consumption consumption consumption
[kg] [kg] [kg] [kg] [kg]
Grey17-20 156,259 0 6796 40,102 109,200
Green17-20 11,955 0 635 4606 6675
PPA17-20 157,575 0 7962 40,113 109,500
Grey21 111,313 245 5429 31,238 74,400
Green21 31,496 41.6 1646 11,208 18,600
PPA21 159,315 1820 7882 40,113 109,500