Metaheuristic optimization of electrical distribution systems with energy storage and reactive compensators

This study, using the dynamic arithmetic optimization algorithm (DAOA), provides a solution for the optimal integration of renewable energy sources, reactive power compensators (RPCs), and battery energy storage systems (BESS) into electric power systems. To reduce annual energy dissipation and RPC operating costs as much as possible, the DAOA optimizes the BESS and RPC levels. Uncertain residential, commercial, and industrial demand is also factored into the analysis. Annual energy loss and reactive power compensation costs are reduced significantly after implementing optimal active and reactive power compensation allocations. The yearly cost of energy loss decreases from 2631.77 k$ to 27.21 k$ for residential demand, 3995.48 k$ to 40.65 k$ for commercial demand, and from 4838.24 k$ to 48.54 k$ for industrial demand. In addition to determining critical performance measures, including the voltage deviation from unity, system stability, and voltage profile during the simulation horizon, the capability of the DAOA algorithm to minimize the different costs of units while satisfying the problem and system restrictions is also outlined. The results confirm the efficient methodology adopted using the DAOA in controlling the BESS units' charging and discharging modes according to the system operating conditions.