基于贝叶斯网络的智能电网现货交易负荷需求响应优化  

Demand Response Optimization of Spot Trading Load for Smart Grid Based on Bayesian Networks

作　　者：夏稀渊 许宏 何栋 XIA Xiyuan;XU Hong;HE Dong(State Grid Gansu Comprehensive Energy Service Co.,Ltd.,Lanzhou 730070,Gansu,China)

机构地区：[1]国网甘肃综合能源服务有限公司,甘肃兰州730070

出　　处：《电气传动自动化》2024年第6期41-45,共5页Electric Drive Automation

摘　　要：智能电网现货交易在极端天气条件下,电力需求可能会急剧增加,电力供应受到限制,导致负荷功率较高。因此,设计一种基于贝叶斯网络的智能电网现货交易负荷需求响应优化方法。收集智能电网现货交易的负荷需求数据,这些数据涵盖了实时电力需求和价格波动。运用贝叶斯网络建立了精确的负荷需求响应模型,利用该模型对智能电网现货交易负荷需求响应进行优化,通过精准匹配供需关系、合理调度电力资源,实现电网运行效率的提升。实验结果表明,所提方法在高峰时段,智能电网负荷功率为1320kW,比优化前减少了580 kW,能够有效降低智能电网负荷功率、促进电力市场竞争,实现供需的高效匹配。Under extreme weather conditions,power demand may increase sharply,and power supply is limited,resulting in high load power.Therefore,a smart grid spot trading load demand response optimization method based on Bayesian network is designed.Collect load demand data for smart grid spot transactions that covers real-time power demand and price fluctuations.Using Bayesian network,an accurate load demand response model is established,which is used to optimize the load demand response of spot trading of smart grid.By accurately matching the supply and demand relationship and rationally dispatching power resources,the operation efficiency of the power grid is improved.The experimental results show that the load power of the smart grid is 1320kW,which is 580 kW less than before optimization,which can effectively reduce the load power of the smart grid,promote the power market competition,and realize the efficient matching of supply and demand.

关 键 词：贝叶斯网络 智能电网 现货交易 负荷需求 响应优化 

分 类 号：TM732[电气工程—电力系统及自动化]