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Review

Optimal Operation of Combined Cooling, Heating, and Power Systems with High-Penetration Renewables: A State-of-the-Art Review

1
School of Electronic Information and Electrical Engineering, Huizhou University, Huizhou 516007, China
2
School of Automation, Guangdong University of Technology, Guangzhou 510006, China
*
Authors to whom correspondence should be addressed.
Processes 2025, 13(8), 2595; https://doi.org/10.3390/pr13082595 (registering DOI)
Submission received: 20 July 2025 / Revised: 11 August 2025 / Accepted: 15 August 2025 / Published: 16 August 2025
(This article belongs to the Special Issue Distributed Intelligent Energy Systems)

Abstract

Under the global decarbonization trend, combined cooling, heating, and power (CCHP) systems are critical for improving regional energy efficiency. However, the integration of high-penetration variable renewable energy (RE) sources introduces significant volatility and multi-dimensional uncertainties, challenging conventional operation strategies designed for stable energy inputs. This review systematically examines recent advances in CCHP optimization under high-RE scenarios, with a focus on flexibility-enabled operation mechanisms and uncertainty-aware optimization strategies. It first analyzes the evolving architecture of variable RE-driven CCHP systems and core challenges arising from RE intermittency, demand volatility, and multi-energy coupling. Subsequently, it categorizes key flexibility resources and clarifies their roles in mitigating uncertainties. The review further elaborates on optimization methodologies tailored to high-RE contexts, along with their comparative analysis and selection criteria. Additionally, it details the formulation of optimization models, model formulation, and solution techniques. Key findings include the following: Generalized energy storage, which integrates physical and virtual storage, increases renewable energy utilization by 12–18% and reduces costs by 45%. Hybrid optimization strategies that combine robust optimization and deep reinforcement learning lower operational costs by 15–20% while strengthening system robustness against renewable energy volatility by 30–40%. Multi-energy synergy and exergy-efficient flexibility resources collectively improve system efficiency by 8–15% and reduce carbon emissions by 12–18%. Overall, this work provides a comprehensive technical pathway for enhancing the efficiency, stability, and low-carbon performance of CCHP systems in high-RE environments, supporting their scalable contribution to global decarbonization efforts.
Keywords: combined cooling, heating, and power systems; high-penetration renewables; uncertainty optimization; multi-energy complementarity; operation optimization; flexibility resources combined cooling, heating, and power systems; high-penetration renewables; uncertainty optimization; multi-energy complementarity; operation optimization; flexibility resources

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MDPI and ACS Style

Mao, Y.; Yuan, J.; Jiao, X. Optimal Operation of Combined Cooling, Heating, and Power Systems with High-Penetration Renewables: A State-of-the-Art Review. Processes 2025, 13, 2595. https://doi.org/10.3390/pr13082595

AMA Style

Mao Y, Yuan J, Jiao X. Optimal Operation of Combined Cooling, Heating, and Power Systems with High-Penetration Renewables: A State-of-the-Art Review. Processes. 2025; 13(8):2595. https://doi.org/10.3390/pr13082595

Chicago/Turabian Style

Mao, Yunshou, Jingheng Yuan, and Xianan Jiao. 2025. "Optimal Operation of Combined Cooling, Heating, and Power Systems with High-Penetration Renewables: A State-of-the-Art Review" Processes 13, no. 8: 2595. https://doi.org/10.3390/pr13082595

APA Style

Mao, Y., Yuan, J., & Jiao, X. (2025). Optimal Operation of Combined Cooling, Heating, and Power Systems with High-Penetration Renewables: A State-of-the-Art Review. Processes, 13(8), 2595. https://doi.org/10.3390/pr13082595

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