Techno-economic analysis and optimal sizing of wind–PV–hydropower–biomass hybrid energy systems for hydrogen production in Finland

To achieve sustainable hydrogen production, systems powered by renewable energy must replace conventional fossil fuel-based routes. This study evaluates the techno-economic feasibility and optimal sizing of seven distinct hybrid renewable energy system configurations—comprising wind, solar, biomass, and pumped hydro energy storage (PHES)—for producing one ton of green hydrogen per day in Finland. The energy systems are modelled by Aspen Plus and MATLAB and analyzed within tax-based and non-tax-based frameworks concerning biogenic CO 2 emissions from biomass combustion. Four multi-objective optimization problems use the non-dominated sorting genetic algorithm II (NSGA-II) to determine the Pareto set for four scenarios that minimize the levelized cost of hydrogen (LCOH) and capital expenditure (CAPEX). A decision-making method is then employed to choose the best solutions. In addition, the net present value (NPV) and payback period are evaluated to assess system profitability. The findings indicate that biomass-based systems can compete with wind and solar in green hydrogen production, although policy instruments—particularly biogenic CO 2 taxation—significantly influence system design and cost. The results show that wind-PHES and solar-PHES systems can produce hydrogen at costs of about $3.2/kg and $3.6/kg, respectively. PHES contributes roughly 11% of the total CAPEX in the wind-based system, compared to 31% in the solar-based configuration. The exclusive use of biomass coupled with a Rankine cycle to power the electrolyzer results in an LCOH of $7.3/kg under biogenic CO 2 taxation, compared to $3.6/kg in the absence of such a tax. The study highlights the importance of incorporating storage or complementary energy systems, such as PHES or biomass, to support configurations relying primarily on wind and solar resources. • Optimal sizing of renewables to steadily produce one tonne of hydrogen per day. • The system is modeled by Aspen Plus and MATLAB and assessed in seven scenarios. • Four multi-objective optimization problems based on the NSGA-II are carried out. • Carbon taxation heavily impacts the system design and hydrogen pricing. • Biomass can produce hydrogen at low LCOH and CAPEX.