Multi-Objective Coupled Energy and Reactive Power Market Clearing Model using HFMOEA

This paper presents a new multi-objective coupled energy and reactive power market clearing model namely the MO-CERPMC model in day-ahead competitive market environment. In proposed model, both the active and reactive power markets are considered as coupled markets and cleared in a same time frame. The multi-objective optimization problem involves the minimization of total payment functions for active power and reactive power support services respectively. Minimization of both objectives are subject to various system operating constraints such as generators capability curve limits, uniform price auctions for both the markets, zonal/localized reactive power market structure etc. The MO-CERPMC model is solved using two multi-objective optimization techniques such as a hybrid fuzzy multi-objective evolutionary algorithm (HFMOEA) and a non-dominated sorting genetic algorithm (NSGA-II) and the results are compared. KeywordsCoupled energy and reactive power market clearing, uniform price auction, multi-objective optimization, Pareto-optimal front, hybrid fuzzy evolutionary algorithm.