摘要
在碳达峰碳中和目标下,以新能源为主体的新型配电网运行提出了更高的要求,迫使配电网兼顾绿色低碳和经济高效两个方面效益。基于配电网的不确定性以及对环境和经济效益的影响,提出一种改进沙猫群算法。在改进沙猫群算法中,采用高破坏性多项式突变策略初始化种群,提高初始阶段解的质量,为全局搜索奠定基础;引入计数切换机制,帮助可行解跳出局部最优。为应对分布式发电的随机性问题,构建基于蒙特卡洛模拟和k-means聚类的分布式发电出力典型日场景生成方法。将改进沙猫群算法应用到主动配电网优化调度,以配电网运行成本作为目标函数,在IEEE 33总线测试系统中进行验证,结果表明:清洁能源的有效利用与经济效益的高低密切相关,能够提高调度精益化水平,平均成本为383.8万元,最终实现了绿色低碳和节约成本的目的。
Under the objectives of'carbon peaking'and'carbon neutrality',the operation of new types of distribution networks,primarily based on new energy,poses higher requirements,forcing distribution networks to consider both green,low-carbon benefits and economic efficiency.Given the uncertainty of distribution networks and their impact on environmental and economic benefits,an improved sand cat swarm optimization is proposed.In this improved algorithm,a high-destructive polynomial mutation strategy is used to initialize the population,enhancing the quality of solutions in the initial stage and laying the foundation for global search;a counting switch mechanism is introduced to help feasible solutions escape local optima.To address the randomness issues in distributed generation,a method for generating typical daily scenarios of distributed generation output,based on Monte Carlo simulation and k-means clustering,is constructed.The improved sand cat swarm algorithm is applied to the optimization scheduling of active distribution networks,with the operating cost of the distribution network as the objective function.Verified in the IEEE 33-bus test system,the results show that the effective use of clean energy is closely related to economic benefits,can improve the level of scheduling precision,and the average cost is 3.918 million yuan,ultimately achieving the purpose of green,low-carbon,and cost-saving.
作者
管智峰
吴红冬
周欣荣
韦海波
樊荣
王韬
雷天
Guan Zhifeng;Wu Hongdong;Zhou Xinrong;Wei Haibo;Fan Rong;Wang Tao;Lei Tian(Ulanqab Power Supply Company,Inner Mongolia Power(Group)Co.,Ltd.,Ulanqab,Inner Mongolia 012000,China;School of Electrical and Control Engineering,Liaoning Technical University,Huludao,Liaoning 125105,China)
出处
《机电工程技术》
2024年第10期192-196,207,共6页
Mechanical & Electrical Engineering Technology
基金
国家自然科学基金(51974151,71771111)。
关键词
配电网
沙猫群算法
场景生成
IEEE33
绿色低碳
distribution network
sand cat swarm optimization
scene generation
IEEE33
green and low-carbon
