Understanding the costs associated with producing green hydrogen from renewable sources is essential to evaluate its large-scale viability in a global energy context. From this perspective, Enertis Applus+ conducted a comparative analysis of green hydrogen production costs to analyze the levelized cost of hydrogen (LCOH) across ten international locations with different levels of solar and wind resources, using off-grid electrolyzers powered exclusively by renewable electricity generation systems.
Through a rigorous approach, with more than 4,000 simulations and a detailed analysis of each scenario, the study offers a solid roadmap for understanding where, how, and under what conditions green hydrogen can be produced at competitive costs.
The study analyzed a wide range of hybrid configurations of solar photovoltaic plants, wind farms, and battery energy storage systems (BESS) to identify the most efficient and economically competitive combinations. The analysis model kept the electrolyzer power constant, varying only the composition of the generation sources and energy storage capacity of the system. This approach enabled comparable scenarios across all locations to be obtained.
A precise evaluation of system performance in a variety of Production, energy costs and prices Scenarios
The system architecture is based on an off-grid electrolysis station that is powered exclusively by a solar plant, a wind farm, and a BESS system, all newly installed. With 100 MW of electrolysis power, any excess energy not consumed by the electrolyzer is stored in the battery system, if its state of charge allows it. This design mitigates curtailment, enables a more efficient use of renewable production and provides an opportunity to study the strategic role of storage in energy management and its impact on costs.
Figure 1 shows the general scheme on which the different iterations were performed:
Figure 1: System architecture. Source: own elaboration
Based on the variability in wind and solar resources, suitable locations were identified in Spain (five locations), Romania, Chile (two locations), Australia, and the United States. The analysis methodology determined a common base case that allowed for precise evaluation of system performance under different combinations of renewable technologies. The base case structure included 100 MW of electrolysis, 100 MWac of solar photovoltaic, 99 MW of wind, and no storage capacity. From this starting point, 240 iterations were carried out per location, combining different renewable powers and storage capacities while keeping the electrolyzer capacity constant.
The analysis of gross and net available energy was a key part of the study. Initially, hourly simulations were obtained to determine the gross energy amount and the total potential energy production without restrictions. Subsequently, for each scenario, curtailments, losses, and actual performance were calculated using in-house developed simulation systems. Based on the net available energy and the operating conditions of the electrolyzers, the annual hydrogen production was determined for each analyzed configuration.
The economic calculations were organized based on two scenarios and the estimation of investment costs (Capex) and operation costs (Opex). On one hand, a model with standard prices, independent of location, was defined. In this scenario, the same cost values were used to calculate the levelized cost of energy (LCOE) and LCOH in all locations, therefore the variability of results was directly related to the availability of renewable energy resources. On the other hand, a second scenario was defined in which variable prices – adjusted according to economic estimates and the financial situation of each country – were introduced. In total, 4,800 simulations were performed: 2,400 with standard prices and an equal number with variable prices.
The identification of scenarios for the optimization of electricity and hydrogen production costs was one of the key aspects of the analysis. For this, two reference frameworks were defined: a base scenario, which allowed for a homogeneous comparison between locations; and an optimal scenario, in which the LCOH was minimized at each location through system architecture. This approach highlighted that the configuration that produced the most hydrogen was not always the one that achieved the lowest LCOH. In this sense, the balance between energy curtailment and the capacity factor of the electrolyzer proved decisive. In locations with a low LCOE, it was more viable to oversize renewable generation, even if a certain level of curtailment was involved, in order to ensure a higher capacity factor of the electrolysis system. In contrast, in locations with a higher LCOE, the economic penalty for curtailments forced greater efficiency in the renewable power/electrolysis power ratio.
Resource, Electrolyzer Capacity Factor, and Financial Conditions: Determining Factors
One of the key findings of the study is that the availability of renewable resources at each site directly determines its hydrogen production potential. In this regard, locations that benefit from a complementary mix of renewable sources—such as photovoltaic solar and wind—demonstrate significant advantages. This complementarity enables higher capacity factors for the electrolyzer, resulting in a lower LCOH and greater overall system efficiency.
The study shows that the configurations where the electrolyzer operation is maximized —through well-managed renewable generation, presented substantially lower LCOH. This was the case, for example, of locations such as Texas (USA) or Cádiz (Spain), where the complementarity between solar and wind resources allowed for achieving high-capacity factors and a significant reduction in LCOH, below $3.6/kg in the standard scenario. In contrast, the same configuration deployed in regions such as Romania, where electrolyzer capacity factors are significantly lower, achieves LCOH values of up to $5.5/kg.
Conversely, sites with limited availability of one energy resource exhibited markedly lower electrolyzer capacity factors, translating into higher LCOH values. For example, locations such as northern Chile, with low wind availability, showed very reduced electrolyzer capacity factors, which translated into LCOH values above $5/kg. in the standard architecture However, even in these cases, optimized configurations could be identified. By eliminating the wind component and reinforcing solar generation, the LCOH was reduced to $4.1/kg, demonstrating that system optimization depends not only on the gross availability of renewable resources but also—critically—on the design strategy and generation architecture employed.
The study also highlights the decisive impact of local economic conditions. Factors such as Capex, Opex, and project evaluation rates can significantly influence final costs, so it is essential to consider them in the planning and economic analysis of projects. Thus, locations with good resources can lose competitiveness in scenarios with variable prices due to unfavorable investment costs or inflation rates. Therefore, the high availability of resources, although a necessary condition, is not enough to guarantee a competitive LCOH. For example, locations such as Texas may experience an increase in their LCOH of more than $1/kg due to the higher Capex associated with transitioning from the standard pricing scenario to a location-adjusted pricing scenario. These variations can be also observed when changing the return rates of the financial model, with differences exceeding $1.5/kg in some locations.
The following table summarizes the behavior of the mentioned variables in the different architecture and price scenarios:
Table 1: Summary of LCOE & LCOH. Source: own elaboration.
In addition, in the following figure, the behavior of the itemized LCOH can be observed in the different concepts that comprise them, and the evolution of each of them can be observed.
Table 2. Itemized LCOH. Source: own elaboration.
As a conclusion, the levelized cost of hydrogen depends on a complex interaction between technical, operational, and economic variables. A high-capacity factor of the electrolyzer, a reduced LCOE, and favorable financial conditions are the three pillars on which any strategy for green hydrogen production should be based. None of these factors is enough taken independently, but their effective combination, and adaptation to each location, determines the difference between a viable project and an economically unfeasible one.
Enertis Applus+ is a Spain-based full-range engineering consultancy firm with extensive expertise in the renewable energy and storage sectors. As pioneers in testing and quality control and specialists in technical advisory services, it offers an integrated understanding of solar PV, wind and BESS projects covering technical, environmental, financial, and contractual project phases.
The views and opinions expressed in this article are the author’s own, and do not necessarily reflect those held by pv magazine.
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