A data-driven hybrid interval reactive power optimization based on the security limits method and improved particle swarm optimization

The integration of renewable power generation introduces randomness and uncertainties in systems, the reactive optimization with interval uncertainty (RPOIU) problem has been constructed to acquire voltage control strategy. However, large amount uncertain data coexistence discrete continuous variables increase difficulty solving RPOIU problem. This paper proposes a data-driven hybrid based on security limits method (SLM) improved particle swarm (IPSO) solve In this method, historical is processed by obtain boundary optimal set. variable decomposed into optimization. are optimized applying SLM fixed, IPSO fixed. two processes applied alternately, values obtained each used as fixed other method. Based simulations carried out for IEEE 30-bus system three methods, we verified that strategy could ensure state intervals satisfied constraints. Meanwhile, real losses proposed were smaller than those IPSO. simulation results demonstrated effectiveness value