Economical Optimization of Grid Power Factor Using Predictive Data

作     者：Chaojiong Huang Jason Gu Haiying Liu Yuansheng Lu Jun Luo 

作者机构：IEEE the School of Electrical Engineering and AutomationShanghai University the Department of Electrical and Computer EngineeringDalhousie University 

出 版 物：《IEEE/CAA Journal of Automatica Sinica》 (自动化学报（英文版）)

年 卷 期：2019年第6卷第1期

页      面：258-267页

核心收录：

学科分类：0810[工学-信息与通信工程] 1205[管理学-图书情报与档案管理] 080802[工学-电力系统及其自动化] 0808[工学-电气工程] 08[工学] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：ECE Department of Dalhousie University Green Power Labs Company 

主　　题：Grid optimization GridLAB-D inverter power factor predictive data control shunt capacitor 

摘      要：We present an electrical grid optimization method for economical benefit. After simplifying an IEEE feeder diagram, we build a compact smart grid system including a photovoltaic-inverter system, a shunt capacitor, an on-load tapchanger(OLTC) and transmission lines. The system power factor(PF) regulation and reactive power dispatching are indispensable to improve power quality. Our control method uses predictive weather and load data to decide engaging or tripping the shunt capacitor, or reactive power injection by the photovoltaic-inverter system, ultimately to keep the system PF in a good range. From the perspective of economics, the economical model is considered as a decision maker in our predictive data control ***-only control strategy is a common photovoltaic(PV)regulation method, which is treated as a baseline case. Simulations with GridLAB-D on profiled loads and residential loads have been carried out. The comparison results with baseline control strategy and our predictive data control method show the appreciable economical benefit of our method.