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作 者:华昊辰 吴浩星 陈星莺[1] 吴星辰 余昆[1] HUA Haochen;WU Haoxing;CHEN Xingying;WU Xingchen;YU Kun(School of Electrical and Power Engineering,Hohai University,Nanjing 210098,Jiangsu Province,China)
机构地区:[1]河海大学电气与动力工程学院,江苏省南京市210098
出 处:《电网技术》2024年第10期4174-4184,I0065-I0067,I0064,共15页Power System Technology
基 金:国家重点研发计划项目(2022YFE0140600);国家自然科学基金项目(52107089)。
摘 要:在含氢能区域综合能源系统参与碳交易的能量协同优化过程中,用户经济性和满意度目标一致性动态变化,给含多决策变量的区域综合能源系统能量协同优化带来了挑战。为此,该文构建了包含氢能梯级利用的冷热电联产系统模型,提出了基于预测平均投票数指标的用户综合需求响应策略,具体地,以上层综合能源运营商为领导者和下层用户聚合商为跟随者构建了主从双层博弈均衡模型,并采用基于成功历史的自适应差分进化算法嵌套CPLEX求解双方收益均衡化的交互策略。仿真结果表明该文所提策略提升了双方收益,且该文采用基于成功历史的自适应差分进化算法的求解时间分别比差分进化算法、遗传算法、自适应遗传算法减少了15.6%,8.6%,4.8%。In the energy collaborative optimization of the hydrogen-bearing regional integrated energy system participating in carbon emission trading,the dynamic changes in the consistency of user-side economic and satisfaction goals have challenged the energy collaborative optimization of the regionally integrated energy system multiple decision variables.For this reason,a combined cooling,heating,and power system model,including hydrogen cascade utilization,is constructed,and a user-integrated demand response strategy based on the predicted mean vote index is proposed.Specifically,with the upper-level integrated energy service providers as the leader and the lower-level user aggregators as the follower,a master-slave bi-level game equilibrium model is constructed,and the success-history-based adaptive differential evolution(SHADE)is nested with CPLEX to solve the interaction strategy under the balance of both parties’benefits.The simulation demonstrates that the proposed strategy improves both parties'profits.In addition,compared to the differential evolution algorithm,genetic algorithm,and adaptive genetic algorithm,the SHADE algorithm significantly reduced the execution time by 15.6%,8.6%,and 4.8%,respectively.
关 键 词:区域综合能源系统 能量协同 碳交易 基于成功历史的自适应差分进化
分 类 号:TM721[电气工程—电力系统及自动化]
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