Data-Driven Portfolio Optimization for Utility-Scale Solar, Wind, and Battery Energy Storage Systems (BESS): Integrating Performance Analytics with Investor EBITDA Targets

Abstract

The accelerating global shift toward renewable energy underscores the importance of data-driven investment frameworks that connect operational performance with financial objectives. This study examines portfolio optimization for utility-scale solar, wind, and battery energy storage systems (BESS), integrating performance analytics with investor earnings before interest, taxes, depreciation, and amortization (EBITDA) targets. Findings reveal that portfolios optimized through data-driven analytics achieve higher financial stability, improved EBITDA margins, and reduced exposure to market volatility compared to conventional investment strategies. The study also finds that hybrid portfolios combining solar, wind, and BESS assets yield more consistent revenue streams due to complementary energy generation and storage dynamics. Furthermore, the integration of predictive analytics enhances asset reliability, optimizes energy dispatch, and increases investor confidence by improving transparency in performance forecasting. Based on these findings, the study recommends that investors and energy managers adopt advanced data analytics platforms to guide capital allocation, strengthen financial planning, and enhance operational efficiency. It also recommends incorporating real-time monitoring systems and digital performance dashboards to support adaptive decision-making and long-term profitability. Overall, the research highlights that a data-centric approach to renewable energy portfolio management can simultaneously maximize investor returns and promotes sustainable energy transition.