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考虑CHP-P2G-CCS的综合能源系统鲁棒优化调度策略研究OACSTPCD

Robust optimal dispatch strategy of integrated energy system considering CHP-P2G-CCS

中文摘要英文摘要

综合能源系统能提高能源利用率,减少碳排放,是实现"双碳"目标的重要手段.本文针对电-热-气-冷综合能源系统,研究了考虑P2G和碳捕集系统的CHP模型相关特性,建立了两阶段鲁棒优化模型.首先,建立了考虑P2G和碳捕集系统的CHP模型,推导该模型的电热耦合特性、P2G容量约束,证明该模型可以改善电热耦合特性,提高电功率调节范围,降低碳排放.然后,构建了综合能源系统两阶段鲁棒优化调度模型,日前调度阶段以启停成本最小为目标函数,实时调度考虑多重不确定性,以设备运行成本、碳排放成本、弃风和弃光成本最小为目标函数.最后,采用ψ-piecewise对目标函数线性化后,基于C&CG算法对模型进行求解.仿真结果显示,本文模型可有效消纳可再生能源,降低系统总成本.

Integrated energy systems(IESs)can improve energy efficiency and reduce carbon emissions,essential for achieving peak carbon emissions and carbon neutrality.This study investigated the characteristics of the CHP model considering P2G and carbon capture systems,and a two-stage robust optimization model of the electricity-heat-gas-cold integrated energy system was developed.First,a CHP model considering the P2G and carbon capture system was established,and the electric-thermal coupling characteristics and P2G capacity constraints of the model were derived,which proved that the model could weaken the electric-thermal coupling characteristics,increase the electric power regulation range,and reduce carbon emissions.Subsequently,a two-stage robust optimal scheduling model of an IES was constructed,in which the objective function in the day-ahead scheduling stage was to minimize the start-up and shutdown costs.The objective function in the real-time scheduling stage was to minimize the equipment operating costs,carbon emission costs,wind curtailment,and solar curtailment costs,considering multiple uncertainties.Finally,after the objective function is linearized with a ψ-piecewise method,the model is solved based on the C&CG algorithm.Simulation results show that the proposed model can effectively absorb renewable energy and reduce the total cost of the system.

张彬;夏益辉;彭晓涛

电热联产电转气碳捕集系统综合能源系统鲁棒优化

Combined heat and powerPower-to-gasCarbon capture systemIntegrated energy systemRobust optimization

《全球能源互联网(英文)》 2024 (001)

14-24 / 11

This study was supported by the National Natural Science Foundation of China(Grant number 51977154).

10.1016/j.gloei.2024.01.002

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