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Volume 13
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10.3390/pr13030680
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Article

Optimized Dispatch of Integrated Energy Systems in Parks Considering P2G-CCS-CHP Synergy Under Renewable Energy Uncertainty

by
Zhiyuan Zhang
1,
Xiqin Li
1,
Lu Zhang
2,
Hu Zhao
3,
Ziren Wang
4,*,
Wei Li
4 and
Baosong Wang
5
1
State Grid Beijing Mentougou Power Supply Company, Mentougou, Beijing 102300, China
2
Research Institute of Electric Power Science, State Grid Beijing Electric Power Company, Fengtai, Beijing 100075, China
3
State Grid Beijing Electric Power Company, Xicheng, Beijing 100075, China
4
Department of Economics and Management, North China Electric Power University, Baoding 071000, China
5
School of Electrical and Electronic Engineering, North China Electric Power University, Changping, Beijing 102206, China
*
Author to whom correspondence should be addressed.
Processes 2025, 13(3), 680; https://doi.org/10.3390/pr13030680
Submission received: 22 January 2025 / Revised: 23 February 2025 / Accepted: 26 February 2025 / Published: 27 February 2025
(This article belongs to the Special Issue Modeling, Simulation and Control in Energy Systems)
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Abstract

To enhance low-carbon economies within Park Integrated Energy Systems (PIES) while addressing the variability of wind power generation, an innovative optimization scheduling strategy is proposed, incorporating a reward-and-punishment ladder carbon trading mechanism. This method effectively mitigates the unpredictability of wind power output and integrates Power-to-Gas (P2G), Carbon Capture and Storage (CCS), and Combined Heat and Power (CHP) systems. This study develops a CHP model that combines P2G and CCS, focusing on electric-heat coupling characteristics and establishing constraints on P2G capacity, thereby significantly enhancing electric energy flexibility and reducing carbon emissions. The carbon allowance trading strategy is refined through the integration of reward and punishment coefficients, yielding a more effective trading model. To accurately capture wind power uncertainty, the research employs kernel density estimation and Copula theory to create a representative sequence of daily wind and photovoltaic power scenarios. The Dung Beetle Optimization (DBO) algorithm, augmented by Non-Dominated Sorting (NSDBO), is utilized to solve the resulting multi-objective model. Simulation results indicate that the proposed strategy increases the utilization rates of renewable energy in PIES by 28.86% and 19.85%, while achieving a reduction in total carbon emissions by 77.65% and a decrease in overall costs by 36.91%.
Keywords: integrated energy systems; renewable energy consumption; P2G-CCS-CHP; reward-penalty ladder carbon trading; uncertainty in wind power output; dung beetle optimization algorithm under non-dominated sequencing integrated energy systems; renewable energy consumption; P2G-CCS-CHP; reward-penalty ladder carbon trading; uncertainty in wind power output; dung beetle optimization algorithm under non-dominated sequencing

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MDPI and ACS Style

Zhang, Z.; Li, X.; Zhang, L.; Zhao, H.; Wang, Z.; Li, W.; Wang, B. Optimized Dispatch of Integrated Energy Systems in Parks Considering P2G-CCS-CHP Synergy Under Renewable Energy Uncertainty. Processes 2025, 13, 680. https://doi.org/10.3390/pr13030680

AMA Style

Zhang Z, Li X, Zhang L, Zhao H, Wang Z, Li W, Wang B. Optimized Dispatch of Integrated Energy Systems in Parks Considering P2G-CCS-CHP Synergy Under Renewable Energy Uncertainty. Processes. 2025; 13(3):680. https://doi.org/10.3390/pr13030680

Chicago/Turabian Style

Zhang, Zhiyuan, Xiqin Li, Lu Zhang, Hu Zhao, Ziren Wang, Wei Li, and Baosong Wang. 2025. "Optimized Dispatch of Integrated Energy Systems in Parks Considering P2G-CCS-CHP Synergy Under Renewable Energy Uncertainty" Processes 13, no. 3: 680. https://doi.org/10.3390/pr13030680

APA Style

Zhang, Z., Li, X., Zhang, L., Zhao, H., Wang, Z., Li, W., & Wang, B. (2025). Optimized Dispatch of Integrated Energy Systems in Parks Considering P2G-CCS-CHP Synergy Under Renewable Energy Uncertainty. Processes, 13(3), 680. https://doi.org/10.3390/pr13030680

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