POWER LOSS MITIGATION IN A DISTRIBUTED PHOTOVOLTAIC-BASED MICROGRID USING SMA-PSO DUAL-OPTIMIZATION TECHNIQUE

The renewed research interest in renewable energy generation has substantially reduced the cost of electricity production from these sources and has laid the strong foundation for competing with non-renewable sources. The optimum power flow (OPF) problem involves addressing the unpredictable limitation by determining appropriate values for the control variables and optimizing the objective functions. The main constraint faced in the conception and design of power systems is the propensity for voltage instability. This paper proposed a Slime mould algorithm (SMA) and Particle swarm optimization (PSO) in an SMA-PSO dual-optimization that dynamically adjusts the number of search agents in the same search space using the SMA's feedback capacity and the PSO's quick convergence mechanism. The suggested algorithms were tested on the IEEE 33 bus system. The result indicates a decrease in network real power loss of 49.64% with a significant redundancy stabilization power of 910.9771 kW. This substantial decrease is sufficient to stabilize the microgrid while integrating a 3,500 kW Photovoltaic (PV) generator at the optimal location bus 6. The SMA-PSO technique validates further efficacy when compared to previously published research works on either single or hybrid optimisation approaches. Future research may include adding more complex microgrids with more buses and exploring duality and hybridization optimisation techniques