A multi-objective metaheuristic framework for reactive power market optimization in distributed renewable systems
Abstract
The increasing integration of renewable energy sources into the electrical grid demands specific ancillary services, particularly for reactive power supply and voltage control. This study introduces an optimization framework integrated with a reactive power market under a high penetration of distributed generation (DG). The methodology formulates a multi-objective optimization problem with five technical and economic objective functions, solved using a multi-objective metaheuristic algorithm (MOPSO) and selecting the operating point from the Pareto front through TOPSIS. It also integrates a VCG auction mechanism to allocate the reactive power demanded by the system operator, promoting truthful bidding under the usual VCG assumptions. Validation is performed on a modified IEEE-30 test system with 50 MW DG units at buses 19, 21 and 30 and a stressed load condition at the same buses. The TOPSIS selected operating point under scenario S3 achieves active power losses of 2.382 MW, voltage deviation of 0.194 p.u., and conventional generation cost of 7648 $, while the S3 Pareto front reaches a hypervolume of 0.823. In the reactive power auction based on 20.2 MVAr demand, VCG allocates 100 % of the procurement to renewable units for total payments of 60.71 $. The results confirm that the proposed model significantly improves the technical operation of the system while providing an economically viable framework for the integration of reactive power ancillary services into electricity distribution, supporting the transition towards more efficient, stable and sustainable electrical networks.