Optimal allocation of renewable energy resources in distribution systems using meta-heuristic algorithms

In recent decades, Distributed Generation (DG) has emerged as the most effective solution for Radial Distribution Systems (RDS) to reduce power losses, primarily due to the significant increase in energy consumption, while also improving the voltage profile. This paper discusses the application of two algorithms: the White Shark Optimizer (WSO) and the Exponential Distribution Optimizer (EDO). These algorithms are designed to determine the optimal distribution of Renewable Energy Resources (RERs) for Photovoltaic (PV) systems and Wind Turbine Generators (WTGs) within a distribution network. The main objectives are to minimize power losses and enhance the voltage profile of the distribution system. Simulations were conducted across various case studies, considering multiple scenarios to assess the impact of PV and WTG systems on power losses and the Voltage Deviation Index (VDI). The effectiveness of the proposed algorithms is demonstrated through a comprehensive performance analysis applied to the IEEE 33-bus system.Results indicate that, in the best scenario involving multi-objective functions, the WSO can reduce power losses and VDI by up to 90.7 % and 98.98 %, respectively, while improving the minimum voltage from 0.9131 to 0.9804 p.u. These findings were compared with other techniques, highlighting the superiority and effectiveness of the proposed algorithms. Overall, the results show that these algorithms effectively determine the ideal sizes and placements for PV and WTG units, leading to a significant reduction in active power loss and an improvement in the minimum bus voltage.