Optimal control method for power system reactive power management considering real‐time uncertainties

Abstract

This article investigates multi-objective reactive power management while accounting for real-time generation and load uncertainties. The primary goal of this research is to investigate the effects of uncertainties on reactive power dispatch, while taking into account multiple objectives at the same time and keeping operational constraints in mind. The optimal reactive power dispatch (ORPD) problem is solved using an "indicator-based evolutionary technique" called "ISDE+," which considers two different goal functions: real power loss minimization and voltage deviation minimization. IEEE 30 and IEEE 57 bus test systems are taken into account in the simulation. ISDE+ generates a set of non-dominated optimal solutions, from which the best compromise solution is extracted using the "S" shaped fuzzy membership function. A hyper-volume indicator is used to evaluate the optimizer's performance. In addition, this work proposes a stochastic ORPD problem for tri-objective optimization with load demand and wind power uncertainty. The Weibull probability distribution function was used to model stochastic wind power using real-time wind speed data gathered from the National Institute of Wind Energy. Furthermore, to obtain a generalized wind speed set, a scenario-based reduction technique based on the Python programming language is developed. The outcomes of simulations in deterministic and stochastic instances were studied and compared using ISDE+, which outperforms other methods documented in the literature.