Demand Side Response with Optimized Economic Load Dispatch using Particle Swarm Algorithm

Abstract

Electrical power systems are designed and operated to meet the continuous variation of the required load demand. The literature surveyed mostly reported optimized demand response with economic dispatch without considering customer incentives for power transferred to the grid. This study seeks to explore the efficacy of evolutionary swarm optimization technique, the particle swarm optimization (PSO) to validate the optimum choice of distributed energy sources in microgrid demand side response with customer incentive-based economic load dispatch (ELD). The results indicate the cost of the grid power is directly proportional to the energy supplied and inversely proportional to the transferred energy, energy received and the customer incentives. The solar energy (P_s) and wind (P_w) supplied for hours complemented the grid supply and increased the customer incentives from $5.5 to $36 per kWh representing over 18% improvement and reduced the corresponding grid intake from 360 kWh to 317 kWh representing about 14% decrease. Future work on this demand side response with ELD should include additional optimization techniques and larger solar PV and wind energy powers to validate the efficiency in a more complex microgrid.