This paper proposes a comparison of new evolutionary multi agent based particle swarm optimization algorithms for solving optimal power flows with security constraints (line flows and bus voltages). These methods combine the multi agents in two dimensional and cubic lattice structures with particle swarm optimization (PSO) to form two new algorithms. In both Two Dimensional Lattice Structured Multi Agent based Particle Swarm Optimization (TDLSMAPSO) and Cubic Lattice Structured Multi Agent based Particle Swarm Optimization (CLSMAPSO), an agent represents a particle in cubic lattice structure to PSO, and a candidate solution to the OPF problem. All agents live in a square and cubic lattice like environments, with agents fixed on a lattice point in the ascending order of their fitness value. In order to obtain the optimal solution, each agent in cubic and square lattice competes and cooperates with its neighbors. Making use of these agent-agent interactions, CLSMAPSO and TDLSMAPSO realizes the purpose of minimizing the objective function value. CLSMAPSO and TDLSMAPSO realizations were applied to IEEE 30 bus system. Simulation results show that proposed approaches gives better solution than earlier reported approaches in quick time.
Distribution System Reconfiguration for Loss Minimization and Voltage Profile Enhancement by using Discrete – Improved Binary Particle Swarm Optimization Algorithm