基于智能电网技术的电力负荷预测与优化调度研究  

Research on Power Load Prediction and Optimal Dispatching Based on Smart Grid Technology

作　　者：潘华颖 PAN Huaying

机构地区：[1]广州市电力工程有限公司,广东广州510260

出　　处：《电力系统装备》2023年第10期66-68,共3页Electric Power System Equipment

摘　　要：随着能源需求的不断增长和环境保护意识的日益增强,电力负荷预测与优化调度成为智能电网技术中的重要研究领域。文章以智能电网技术为基础,围绕电力负荷预测与优化调度展开研究,重点采用粒子群算法构建电力负荷预测模型,以实现对电力系统负荷的精确预测。同时针对负荷优化调度问题,提出基于模型预测控制和强化学习的策略,旨在最大程度地满足电力供需平衡的要求,并优化电力系统运行效率,减少碳排放。With the increasing energy demand and the increasing awareness of environmental protection,power load forecasting and optimal dispatching have become an important research field in smart grid technology.Based on the smart grid technology,this paper conducts research on the power load prediction and optimal scheduling,focusing on the particle swarm algorithm to build the power load prediction model,so as to realize the accurate prediction of the power system load.At the same time,for the problem of load optimization scheduling,this paper puts forward a strategy based on model prediction control and reinforcement learning,aiming to meet the requirements of power supply and demand balance to the greatest extent,optimize the operation efficiency of power system,and reduce carbon emissions.

关 键 词：智能电网技术 电力负荷预测 优化调度 粒子群算法 

分 类 号：TM71[电气工程—电力系统及自动化]