Treffer: Stochastic multi-objective optimization of hybrid distributed power generation with battery storage systems.

Hybrid energy projects are gaining global interest due to their potential to promote sustainable development. This study addresses a gap in the literature by proposing a stochastic model that assesses the economic feasibility of a hybrid energy system combining wind, photovoltaic generation, and battery storage. Unlike traditional deterministic approaches, the model incorporates uncertainties in key financial and operational variables, improving decision-making in real-world conditions. The optimization framework integrates Design of Experiments (DoE), Response Surface Methodology (RSM), and the Desirability function to balance economic return and financial risk. By maximizing the mean and minimizing the variance of the Net Present Value (NPV), the model identifies an optimal system configuration with 92% wind energy, a demand level of 230 kWh/month, and lithium-ion battery storage. This approach reduces computational complexity and enhances hybrid system viability in regions with strong wind resources, providing a valuable tool for investors and policymakers in sustainable energy planning. [ABSTRACT FROM AUTHOR]

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