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Evaluating the Economic Feasibility of Utility-Scale Hybrid Power Plants Under Divergent Policy Environments: A Multi-Objective Approach

Author

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  • Shree Om Bade

    (Department of Energy and Petroleum Engineering, University of North Dakota, Grand Forks, ND 58202, USA)

  • Hossein Salehfar

    (School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, ND 58202, USA)

  • Olusegun Stanley Tomomewo

    (Department of Energy and Petroleum Engineering, University of North Dakota, Grand Forks, ND 58202, USA)

  • Johannes Van der Watt

    (College of Engineering & Mines, Research Institute, University of North Dakota, Grand Forks, ND 58202, USA)

  • Michael Mann

    (Professor Emeritus, University of North Dakota, Grand Forks, ND 58202, USA)

Abstract

This study presents a novel policy-integrated optimization framework for utility-scale hybrid power plants (HPP), including wind–solar–battery, addressing a critical gap in hybrid renewable energy system design by simultaneously evaluating technical, operational, and economic performance under dynamic policy environments. Unlike conventional approaches that treat these factors separately, this multi-objective optimization model uniquely combines (1) technical reliability assessment through Loss of Load Probability (LOLP) metrics, (2) operational efficiency analysis via curtailment minimization, and (3) economic viability evaluation using net present value (NPV) optimization—all while accounting for policy incentive structures. Applying this framework to comparative U.S. and India case studies reveals how tailored policy combinations can enhance project viability compared to single-incentive scenarios. The results indicate that HPPs are financially unviable without policy support, but targeted incentives like Investment Tax Credits (ITCs) and Production Tax Credits (PTCs) in the U.S. and Accelerated Depreciation (AD), Generation-Based Incentives (GBIs), and Viability Gap Funding (VGF) can improve their viability. The U.S. scenario sees a 197% increase in NPV and a reduction in LCOE to USD 0.055/kWh, while India achieves a 107% turnaround in NPV and an LCOE of USD 0.039/kWh. Sensitivity and breakeven analyses reveal that interest rates and consistent policy support are critical, especially in emerging markets. Specific policy thresholds are identified for feasibility, providing actionable benchmarks. By bridging the gap between technical optimization and policy analysis, this work provides both a methodological advance for HPP design and practical insights for policymakers seeking to accelerate HPP. While this study centers on incentive-driven feasibility, it also outlines key modeling limitations and future improvements, such as market participation, environmental constraints, and advanced system design that will support future HPP planning.

Suggested Citation

  • Shree Om Bade & Hossein Salehfar & Olusegun Stanley Tomomewo & Johannes Van der Watt & Michael Mann, 2025. "Evaluating the Economic Feasibility of Utility-Scale Hybrid Power Plants Under Divergent Policy Environments: A Multi-Objective Approach," Energies, MDPI, vol. 18(17), pages 1-24, August.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:17:p:4608-:d:1737979
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    References listed on IDEAS

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    1. Stanley, Andrew P.J. & King, Jennifer, 2022. "Optimizing the physical design and layout of a resilient wind, solar, and storage hybrid power plant," Applied Energy, Elsevier, vol. 317(C).
    2. Grant, Elenya & Clark, Caitlyn E., 2024. "Hybrid power plants: An effective way of decreasing loss-of-load expectation," Energy, Elsevier, vol. 307(C).
    3. Street, Alexandre & Prescott, Pedro, 2024. "On the regulatory and economic incentives for renewable hybrid power plants in Brazil," Energy Economics, Elsevier, vol. 140(C).
    4. Shree Om Bade & Olusegun Stanley Tomomewo & Ajan Meenakshisundaram & Maharshi Dey & Moones Alamooti & Nabil Halwany, 2025. "Multi-Criteria Optimization of a Hybrid Renewable Energy System Using Particle Swarm Optimization for Optimal Sizing and Performance Evaluation," Clean Technol., MDPI, vol. 7(1), pages 1-31, March.
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