钢铁企业电网中光伏发电的智能管控研究  

Research on the Intelligent Control of Photovoltaic Power Generation in Power Grids of Steel Enterprises

作　　者：李宏伟[1] LI Hongwei(MCC Capital Engineering&Research Incorporation Limited,Beijing 100176,China)

机构地区：[1]中冶京诚工程技术有限公司,北京100176

出　　处：《冶金动力》2024年第3期1-4,41,共5页Metallurgical Power

摘　　要：光伏发电的建设有力推动了钢铁企业的经济发展,钢铁企业光伏电站宜采用“自发自用”的运行方式进行设计和消纳。光伏发电接入厂区电气系统后,控制系统需自动识别出在不同运行方式下各用电负荷所对应的电源点,也就是负荷与电源点之间的拓扑关系。为了实现该功能,对基于改进型深度优先搜索算法(DFS算法)的快速动态拓扑识别技术进行了研究,实现了任意电网架构下的最优拓扑路径检索。根据拓扑识别出来的实际运行方式,电网智能管控系统可对光伏发电进行功率实时调控和功率预测调控,以实现综合利用厂内余能、余热以及新能源的目的。The construction of photovoltaic power generation strongly promotes the economic development of iron and steel enterprises,and those photovoltaic power stations should adopt the"self-generated and self-consumption"mode of operation for the design and power consumption.Af-ter photovoltaic power generation is connected to the electrical system of the plant,the control sys-tem needs to automatically identify the power point corresponding to each electrical load under dif-ferent operating modes,that is,the topological relationship between the load and the power point.To realize this function,a fast dynamic topology identification technique based on an improved depth-first search algorithm(DFS algorithm)is investigated to achieve optimal topology path retrieval under arbitrary grid architecture.Based on the actual operation mode identified by the topology,the grid in-telligent control system can carry out real-time power regulation and power prediction and control of photovoltaic power generation to realize the purpose of comprehensive utilization of residual energy,heat and new energy in the plant.

关 键 词：光伏发电 拓扑识别 智能管控 功率预测 深度优先搜索算法 

分 类 号：TM615[电气工程—电力系统及自动化]