Optimal Reactive Power Planning Under Wind Power Uncertainties with Techno-Commercial Assessment

Abstract

Power systems have numerous issues arising from increased demand and advancements in technology. Among these challenges, the most major ones are the planning of reactive power and the enhancement of voltage stability. Previous studies focused on improving the voltage stability and lesser power losses with installation of renewable sources. Cost effective planning lacks the consideration of service provider’s benefits of buying the renewable power. This work is focused to reduce the cost on consumers with multiple reactive planning objectives like voltage stability and power losses. FACT device and Weibull modeled wind power plant are installed and sensitive installation location is identified by PTDF. Thus, formulated nonlinear multi-objective techno-economic problem is solved by a novel enhanced pareto front optimization algorithm which is uses the strength of a hypergraph network. The hypergraph network is modeled to solve the complex connections and locate the best solution in the search space. The results demonstrate that the proposed novel multi-objective hypergraph particle swarm optimization (MOHGPSO) effectively improves the voltage stability index by up to 30.10% when compared to MOPSO. The power loss and total cost decreased by 31.70% and 7.43%, respectively.