Optimal Smart Inverters Volt-VAR Curve Selection with a Multi-Objective Volt-VAR Optimization using Evolutionary Algorithm Approach

Abstract

Voltage optimization on distribution networks is of uttermost importance to Distribution System Operators (DSO). The performance of the entire distribution network depends on the voltage profile of the system. With the current increase in the penetration of Distributed Energy Resources (DERs) on the distribution network, the challenges of optimized voltage profiles become aggravated. For PV connected systems, smart inverters can be used to partake in the voltage regulation and optimization process using their capability of reactive power injection and absorption. This is often referred to as Volt-VAR Optimization (VVO). Choosing the optimal Volt-VAR Curve (VVC) for the smart inverters often becomes challenging. This paper formulates 4 objective functions, and also proposes the use of Genetic Algorithm (GA) for VVC selection with the integration of a high-level penetration of PV smart inverter. The algorithm was tested on the standard IEEE 13 node distribution test feeder without the use of traditional voltage regulating devices such as Voltage regulators and capacitor banks. The result showed that the overall system active power losses can be minimized by carefully selecting the optimal VVC for the scenarios under study. Also, the results show the different dependencies of the minimization of the active power losses in the network on the VVC reactive power absorption and injection axis.