Abstract The optimal power flow (OPF) problem is of paramount interest and challenge for researchers in Electrical power systems. The problem becomes more challenging when Renewable Energy Sources (RES) like solar wind, etc. are integrated with the traditional interconnected network The main goal of this paper is the cost reduction of a hybrid system comprising both conventional and RES with the integration of Flexible AC transmission Systems (FACTs), considering system limitations in emission loss, in transmission line, to cater voltage fluctuations such that the overall system stability is improved. The classic problem of OPF itself is extremely complex and nonlin-ear, coupled with convex, intermittent constraints. The issue’s complexity increases when the unpredictable behaviour of solar and wind energy is considered. Using solar and wind power in traditional thermal power generations in the particular test system, this research suggests an analysis of the OPF problem by using a metaheuristic optimization technique Chaotic African Vulture Optimization Algorithm (CAVOA.) The suggested method was tested using a modified IEEE 30-bus system and executed using MATLAB in sixteen cases via multi-objective functions. The proposed problem is mitigated by computational intelligence tools to solve OPF problems like tuning grid voltages, transformer tap setting, allocation and sizing of FACTs devices, capacitor bank rating, etc. Compared to the outcomes of the (insert full form) FDBAGDE methods and those found in the literature, the simulation outcomes obtained through the suggested approach successfully identified the best solution. Additionally, the suggested algorithm’s superiority is assessed using a statistical method known as the one-way analysis of variance (ANOVA) test.
No takes yet. Share an insight, caveat, or question.
Mondal et al. (2024) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: