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基于改进鲸鱼算法多元负荷下新型电力系统运行方案优化 被引量:1

Optimization of New Power System Operation Scheme under Multiple Load Based on Improved Whale Algorithm
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摘要 针对新能源大规模消纳带来的电网供需平衡难题,提出了一个兼顾多目标的电网优化运行方案。利用储能设备的充放电调节,建立了考虑最小化总运行成本、减少电能损耗、降低环境污染排放并最大化用户经济补偿收益的多目标优化模型,并采用线性加权法、理想点和反理想点法将其单目标化。在采用鲸鱼优化算法时,利用了群体智能优化的原理,对鲸鱼优化算法进行了改进;引入高斯变异算子增加种群多样性;结合自适应收敛因子策略加速算法收敛,在保证全局搜索能力的同时改进了局部搜索性能。以改进前后的鲸鱼优化算法对方案进行求解。实验结果表明,算法改进后,系统降低总运行成本26.9%,减少电能损耗10.3%,降低环境污染排放16.97%,用户经济补偿收益提高16.1%。以上结果表明,所提出的优化运行方案和改进算法合理有效。 Aiming at the problem of supply and demand balance in large-scale new energy absorption,a multi-objective optimal operation scheme is proposed.A multi-objective optimization model is established to minimize the total operation cost,reduce the power loss,reduce the environmental pollution emission and maximize the economic compensation benefit of the users by using the charge-discharge regulation of the energy storage equipment,and the methods of linear weighting,ideal point and anti-ideal point are used to make the single objective.In the whale optimization algorithm,the principle of swarm intelligence is used to improve the whale optimization algorithm,and Gauss mutation operator is introduced to increase the population diversity;the adaptive convergence factor strategy is combined to accelerate the convergence of the algorithm,and the local search performance is improved while the global search capability is guaranteed.The improved whale optimization algorithm was used to solve the scheme.The experiment results show that after the improvement,the total running cost of the system is reduced by 26.9%;the power loss is reduced by 10.3%,the environmental pollution discharge is reduced by 16.97%,and the economic compensation income of the users is increased by 16.1%.The results show that the proposed optimal operation scheme and improved algorithm are reasonable and effective.
作者 刘金鑫 马兆兴 刘硕 钱宝珊 王瑞华 LIU Jinxin;MA Zhaoxing;LIU Shuo;QIAN Baoshan;WANG Ruihua(School of Information and Control Engineering,Qingdao University of Technology,Qingdao 266520,China)
出处 《电力科学与工程》 2024年第1期18-30,共13页 Electric Power Science and Engineering
基金 国家自然科学基金资助项目(62203248) 山东省自然科学基金资助项目(ZR2020ME194) 智能电网保护和运行控制国家重点实验室项目(SGNR0000KJJ2302137)。
关键词 新型电力系统 智能运行调度 优化运行 多元负荷 充放电优化 鲸鱼优化算法 new power system intelligent operation scheduling optimal operation multi-loads charge and discharge optimization whale optimization algorithm
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