Optimal Hybrid Power Filter Compensator Design Using Multi-Objective Particle Swarm Optimization (MOPSO)

The paper presents a novel discrete search optimization and approach to solve the problem of the hybrid power filter compensator with design a C-type filler and fixed capacitor bank using Discrete Multi Objective Particle Swarm Optimization MOPSO method. This is to ensure both loss reduction and harmonic current mitigation on electrical utility grid. This novel optimization approach, a Multi Objective Particle Swarm Optimization MOPSO method is implemented to tackle a number of conflicting search goals that define the complex optimal filter design problem. The paper presents the following conflicting objective functions and a compromising selection criterion: 1. Minimum feeder current for maximum AC system grid capacity release, 2. Minimum dominant harmonic current penetration into the host electric grid system, 3. Maximum harmonic current absorption by the hybrid harmonic power filler with the fixed capacitor bank, Throughout the iterative optimization process, all power filler parameters are being treated as either continuous type or discrete variables. The hybrid shunt power filler design with compensator and optimization is performed over a specified set of discrete dominant offending low order harmonics.