A simplified multi-objective planning approach for allocation of distributed PV generators in unbalanced power distribution systems

Abstract

Uneven distribution of loads in three-phase power networks causes voltage unbalances and reduces system’s efficiency. Adding PV generation that is intermittent only makes issues more challenging. Taking into account seasonal changes in both load demand and PV generation, this study presents a new method for the precise placement of PV systems inside unbalanced networks in order to enhance system performance. The most efficient PV hosting is accomplished with the help of a novel value-adaptive weight-aggregated (VAWA) grey-wolf optimizer (GWO) within a multi-objective problem framework. The use of the VAW aggregation strategy may effectively mitigate the limitations associated with the linearization problem with multiple objective functions. This approach is suitable for combining several objectives into a single aggregated objective. Two diverse unbalanced radial distribution systems (URDSs) are considered for the investigation in order to examine and validate the recommended method. Voltage unbalance factor (VUF), voltage security factor (VSF), and active power loss (APL) are three distinctive objectives that are considered to be key contributors to the distribution system performance parameter on an annual basis. The yearly average VSF, VUF, and APL of the Indian 19-bus URDS test network improved by 0.62%, 12.97%, and 38.81% once the PV system was included. Compared to before PV allocation, the modified IEEE 123-bus test network's annual average VSF and APL are improved by 0.081% and 13.42%, respectively. GWO convergence data from the obtained results reveals that it outperforms PSO by reaching the global optimum solution on multiple occasions with regard to test runs.