Quantum PSO-based power demand and supply management algorithm for Micogrids

Abstract

In this paper, we formulate a day-ahead dispatch problem of microgrids with distributed generation (DG) subject to the non-convex cost function. An operational frame- work is proposed to address the DGs 'valve-point' loading effect and optimize its performance. The valve-point effect induces a ripple in a 'fuel-cost' curve. The impact of demand side management (DSM) on convex and non-convex energy management system (EMS) problems with different load participation levels is investigated. Further, the DA scheduling horizon of a fifteen-minute resolution time is considered to examine the effect of load dynamics in the MG. The new optimization algorithm, Quantum Particle Swarm Optimization (QPSO), is employed to solve the non-convex DGs cost optimization problem. It is demonstrated that the algorithm efficiently solves the EMS problem. Simulation results point to a 5% reduction in OPEX costs with a minimal penalty on customer satisfaction or Utility.