Quantum-based PSO applied to hour-ahead scheduling in the context of smart grid management

This paper presents a Quantum Particle Swarm Optimization (QPSO) applied to hour-ahead scheduling in Smart Grid (SG). The unforeseen events not considered in day-ahead scheduling, must be overcome when approaching intraday operation. This implies new constraints in hour-ahead formulation. The developed methodology aims to complement the day-ahead scheduling tools already available on the literature. The unforeseen events in the hour-ahead can include change of forecasted load demand, market prices and availability of renewable generation. The QPSO solves the problem in adequate execution time under the hour-ahead time scale. This is demonstrated using a scenario with high penetration of distributed generation and gridable vehicles. Furthermore, a comparison with GAMS is presented.