Symbiotic organisms search-based multi-objective optimal placement of distributed generators considering source and load uncertainty

Integration of Distributed Generation (DG) into a distribution network reduces the costs of network expansion and increases the network reliability by reducing the voltage magnitude deviations. This study proposes a Symbiotic Organisms Search (SOS)-based technique for determining the best size and position of DG in radial distribution networks to improve their voltage profile and voltage security state. The objective is to minimize the bus voltage variation and maximize Voltage Stability Index (VSI) of the network as a multi-objective optimization problem in the presence of source and load uncertainties. In addition, the uncertainty regarding the solar power, wind power, and load is modeled using 2m point estimate method along with SOS algorithm. To better illustrate the effect of the DG placement on the voltage security state of the distribution system, the system was classified into three states depending on the VSI values. The simulation results obtained from two standard (IEEE) radial distribution networks confirm the efficiency and accuracy of the proposed SOS method. The results of the SOS-based method are compared with those obtained by some other techniques proposed in recent literature based on which it can be concluded that the SOS algorithm outperforms other standard optimization techniques. (c) 2023 Sharif University of Technology. All rights reserved.