A Comprehensive Review on the Integration of Renewable Energy Through Advanced Planning and Optimization Techniques

Carlos Barrera-Singaña (), María Paz Comech and Hugo Arcos
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Carlos Barrera-Singaña: Department of Electrical Engineering, Universidad Politécnica Salesiana, Quito EC170702, Ecuador
María Paz Comech: Research Institute for Energy and Resource Efficiency of Aragón (Energaia), University of Zaragoza, Campus Río Ebro, Mariano Esquillor Gómez, 15, 50018 Zaragoza, Spain
Hugo Arcos: Faculty of Electrical Engineering, Escuela Politécnica Nacional, Quito EC170525, Ecuador

Energies, 2025, vol. 18, issue 11, 1-23

Abstract: The expanding integration of wind and photovoltaic (PV) energy is disrupting the power system planning processes. Their incorporation poses limitations to forecasting due to their inherent variability. This review compiles a total of ninety studies conducted and published between 2019 and 2025, presenting for the first time an integrated approach that simultaneously optimizes the generation, transmission, storage, and flexibility of resources given high ratios of renewable generation. We present a systematic taxonomy of conflicting optimization approaches—deterministic, stochastic, robust, and AI-enhanced optimization—outlining meaningful mathematical formulations, real-world case studies, and the achieved trade balance between optimality, scale, and runtime. Emerging international cooperation clusters are identified through quantitative bibliometric analysis, and method selection in practice is illustrated using a table with concise snapshots of case study excerpts. Other issues analyzed include long-duration storage, centralized versus decentralized roadmap delineation, and regulatory and market drivers of grid expansion. Finally, we identified gaps in the literature—namely, resilience, sector coupling, and policy uncertainty—that warrant further investigation. This review provides critical insights for researchers and planners by systematically integrating methodological perspectives to tackle real-world, application-oriented problems related to generation and transmission expansion models amid significant uncertainty.

Keywords: energy storage systems; power system planning; renewable energy integration; stochastic optimization; transmission expansion planning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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