基于多种群协同粒子群人工智能算法的电力系统负荷调度研究  

Research on Power System Load Dispatching Based on Multi group Collaborative Particle Swarm Optimization Artificial Intelligence Algorithm

作　　者：刘雁行 徐恺 乔如妤 梁楠 陈宇 李旭东 LIU YanHang;XU Kai;QIAO RuYu;LIANG Nan;CHEN Yu;LI XuDong(Inner Mongolia Power Marketing Service&Operation Management Branch,Hohhot 010010,China;Inner Mongolia Power(Group)Co.,Ltd.,Hohhot 010010,China)

机构地区：[1]内蒙古电力(集团)有限责任公司内蒙古电力营销服务与运营管理分公司,呼和浩特010010 [2]内蒙古电力(集团)有限责任公司,呼和浩特010010

出　　处：《自动化与仪器仪表》2024年第4期139-143,共5页Automation & Instrumentation

摘　　要：高效的电力系统负荷调度已成为解决电力供需平衡的新途径,对降低企业成本意义重大。通过对蒙西地区电力情况的分析,确定低污染排放与低成本发电两个调度目标,构建电力负荷调度模型。同时引入一种多种群协同粒子群模型求解电力负荷调度模型,采用协同策略分种群处理多个目标问题,避免模型陷入局部最优。在前沿性比较中,所提出的模型相比多目标进化与多目标粒子群性能提升18.65%与12.65%。在电力系统调度测试中,所提出的模型最优发电成本为30.4133×10^(4)元,最优污染排放量为1.8592×10^(4)1 b。在发电成本与污染排放上相比另外两种模型具有明显优势。由此可见,所提出的技术应用效果更好,研究技术为电网的调度优化与节能减排提供技术参考。Efficient power system load dispatch has become a new way to solve the balance between power supply and demand,It is of great significance for reducing enterprise costs.By analyzing the power situation in the western Mongolian region,two scheduling goals of low pollution emissions and low-cost power generation are determined,and a power load scheduling model is constructed.At the same time,a multi group collaborative particle swarm optimization model is introduced to solve the power load dispatch model,and a collaborative strategy is used to handle multiple objective problems in different groups to avoid the model falling into local optima.In the forefront comparison,the proposed model has improved performance by 18.65%and 12.65%compared to multi-objective evolution and multi-objective particle swarm optimization.In the power system scheduling test,the optimal generation cost of the proposed model is 30.4133×10^(4)yuan,with an optimal pollution discharge of 1.8592 yuan×10^(4)1b.Compared to the other two models in terms of power generation costs and pollution emissions,there are significant advantages.From this,it can be seen that the proposed technology has better application effects,and the research technology provides technical reference for the optimization of power grid scheduling and energy conservation and emission reduction.

关 键 词：电力 调度 蒙西 调度模型 粒子群 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]