Cross-Sector Asset Management: Applying Real Estate Portfolio Optimization Models to Renewable Energy Infrastructure

Abstract

Renewable energy infrastructure such as solar farms, wind parks, hydropower assets, and battery-storage facilities has emerged as a critical investment class in global energy transitions. However, despite its long-term strategic value, the sector often lacks standardized asset management frameworks comparable to those used in commercial real estate, where investors routinely apply structured valuation metrics and risk-adjusted portfolio optimization models. This review examines how established real estate based methodologies including net present value (NPV) techniques, capitalization rate analysis, riskreturn mapping, diversification modeling, and asset lifecycle forecasting can be adapted to enhance the financial and operational decision-making processes for renewable energy portfolios. By comparing asset characteristics across the two sectors, the study highlights synergies in valuation modeling, cash-flow stabilization strategies, and hedging approaches while accounting for the unique uncertainties in renewable assets such as policy volatility, intermittency, and technology degradation. The review further evaluates how portfolio optimization models, including Modern Portfolio Theory (MPT), real options analysis, sensitivity modeling, and discounted cash-flow (DCF) forecasting, can be recalibrated to improve investment resilience in renewable infrastructure. Ultimately, this paper proposes a cross-sector asset management framework that integrates real estate portfolio logic with renewable energy performance metrics to support investors, policymakers, and asset managers in achieving long-term sustainability, profitability, and risk mitigation in the evolving clean energy economy.