Multi-objective day-ahead localized reactive power market clearing model using HFMOEA

In this paper, a multi-objective localized day-ahead reactive power market clearing model named as multi-zone DA-RPMC is proposed. The proposed model is based on the zonal uniform price auction by separating the whole market into various voltage control areas/zones. Two objective functions such as total payment function (TPF) for reactive power support services from generators/synchronous condensers and total real transmission loss (TRTL) are minimized simultaneously using a hybrid fuzzy multi-objective evolutionary algorithm (HFMOEA) satisfying all the power system constraints. The proposed multi-zone DA-RPMC model is tested and compared with single-zone DA-RPMC model on standard IEEE 24 bus reliability test system. For both the single-zone and multi-zone DA-RPMC models, the performance of HFMOEA is also compared with NSGA-II in terms of various performance metrics such as spacing, spread and hypervolume. Further, both the single-zone and multi-zone DA-RPMC models are also analyzed on the basis of market power owned by any generator/any generating company. The simulation results obtained confirm the superiority of HFMOEA based multi-zone DA-RPMC model to take better day-ahead reactive power market clearing decisions.

► A multi-zone day-ahead reactive power market clearing model (DA-RPMC) is proposed.
► It includes two objectives such TPF and TRTL with various system operating constraints.
► The proposed multi-zone DA-RPMC model is compared with single-zone DA-RPMC model.
► HFMOEA and NSGA-II are compared for solving the multi-objective DA-RPMC models.
► The market power is also investigated in different gaming scenarios for both the models.