Hybrid multi-objective optimisation for ancillary service procurement in renewable energy integrated deregulated environment

In this manuscript, the reactive power control ancillary services are procured in a thermal-wind-solar deregulated system with renewable energy generation uncertainties.This procurement is devised as a dynamic bi-objective optimisation problem to find the optimum switching schedule of the shunt capacitor for cost and voltage fluctuations minimisation.The capacitors participate in offering ancillary services, and their switching decisions, constrained by their operational lifespan, are influenced by marginal pricing.A particle swarm and electric field hybrid optimisation (PSEFHO) algorithm is presented in this paper utilising Pareto-based approach and non-dominance sorting.The convergence of algorithm is assessed using statistical performance measures.The effectiveness of developed algorithm is verified using IEEE 118-bus and IEEE 300-bus test system.Moreover, an analysis is undertaken to accommodate seasonal variations in solar irradiance.