摘要
分布式光伏发电在配电网中渗透率不断提高,使馈线中的传输功率减少,导致节点过电压情况严重,网损较大。本文提出一种含光伏输出功率短期预测的光伏配电网智能调压策略。首先,对光伏发电数据进行异常点检测后进行相似日聚类,应用深度神经网络(DNN)进行光伏输出功率预测;其次在大规模光伏发电中,依据改进的电气距离,选择可控光伏的安装并网点;最后,应用新型NSGA-III调控可控光伏设备的有功出力和无功出力,以达到调节配电网节点电压、降低网损的目标。在安徽省某县域配电网系统进行试验分析,证明了所提出的调压策略可以精细化解决电压越限问题,并且降低了总网损。
The continuous increment of permeability of distributed photovoltaic(PV)power generation in distribution network leads to reduction of transmission power in feeders,which causes serious overvoltage conditions at the nodes and large network loss.Therefore,an intelligent voltage regulation strategy for photovoltaic power distribution network with PV output power short-term prediction is proposed.Firstly,a deep neural learning network(DNN)is applied to predict photovoltaic output power after the anomaly detection and similar day clustering.Secondly,in large-scale photovoltaic power generation,a controllable photovoltaic installation and grid connection point is selected based on the advanced electrical distance.Finally,the new NSGA-III is used to regulate the active and reactive power output of the controllable photovoltaic equipment to adjust the voltage of the distribution node and reduce the network loss.A regional distribution network in Anhui province is analyzed.The experimental result demonstrates that the proposed voltage regulation strategy is able to solve the problem of voltage over-limit finely and reduce the total network loss.
作者
黄少雄
王璨
孔庆竹
马金辉
张金金
HUANG Shaoxiong;WANG Can;KONG Qingzhu;MA Jinhui;ZHANG Jinjin(State Grid Anhui Electric Power Co.,Ltd,Hefei 230073,China;School of Electrical Engineering and Automation,Anhui University,Hefei 230601,China)
出处
《热力发电》
CAS
北大核心
2020年第7期21-27,共7页
Thermal Power Generation
基金
国家电网安徽电力有限公司研究项目(5212001700)。