Optimal Power Flow Management Strategies in AC Microgrid using Soft Computing Techniques

Abstract

The thesis delves into applying a modified Flower Pollination Algorithm (FPA) version to optimize power distribution systems (PDS). FPA is a cutting-edge optimization algorithm that takes inspiration from the pollination process of flowers. In contrast, the Golden Search Algorithm (GSA) is a traditional optimization technique. Both algorithms have been utilized separately to address various optimization problems, such as numerical, scheduling, local search, and combinational optimization problems. newlineThe research aims to merge GSA and FPA with tangent flight. This hybrid approach can solve a single-objective problem, such as minimizing losses by restructuring PDS, and it can also integrate the Pareto probability factor to tackle multi-objective problems. The proposed hybrid methodology minimizes PDS power losses (PLs) and balances the load through the load balancing index (LBI). The efficacy of this methodology is measured with existing optimization techniques. newlineThe proposed methodology is evaluated using widely used power system test cases, including IEEE 33, 69, 119, and Indian 52-bus test systems. The findings from the initial tests demonstrate that the proposed methodology can effectively minimize power losses in the PDS. The proposed method is also utilized to optimize PDS through network reconfiguration, which is a challenging problem. Using the Tangent Golden Flower Pollination Algorithm (TGFPA) with other optimization techniques showcases the versatility and effectiveness of the proposed methodology. newlineMoreover, the proposed methodology aims to significantly reduce LBI through a multi-objective golden flower pollination algorithm (MOGFPA) incorporating the Pareto probability factor. MATLAB, a widely used tool for power system analysis, is employed to analyze the data. It enhances the credibility of the results obtained using the proposed methodology. The successful application of the TGFPA and MOGFPA is exhibited in PDS optimization problems. The proposed method effectively minimizes power losses and can be app