Day-ahead multi-objective procurement of voltage control ancillary service in dynamic wind-solar incorporated deregulated power system

The ancillary services are becoming more important due to the increasing integration of non-dispatchable and intermittent renewable energy sources. Such behavior under deregulation necessitates the procurement of these services suitably. This paper presents the multi-objective procurement of voltage control ancillary service in a dynamic pool deregulated system that is contingent to wind and solar power generation uncertainties. The shunt capacitors bid to supply this service and their switchings, although restricted due to life expectancy, depend on locational marginal prices. An improved multi-objective artificial electric field algorithm, which adopts the concept of Pareto-based non-dominated sorting, is presented to co-optimize total cost and voltage deviation. The particle’s positions are updated through randomly picked Pareto solution to enhance exploitation capability. The sign and reorder mutation operations are employed to maintain diversity in the population, improve exploration, and evade local optima trap. The performance is investigated for different levels of wind and solar penetration on IEEE 30-bus and IEEE 118-bus test systems. The convergence of presented algorithm is analyzed and compared with other algorithms through statistical metrics and associated boxplots.