HybridGA‐MCSbased optimization for integration of DG, DVR, and DSTATCOM planning in distribution networks

Abstract

The integration of distributed generations (DGs), dynamic voltage restorer (DVR), and distribution static compensator (DSC) plays an important role in the context of environmental problems and sustainable development throughout the world. The traditional DG, DVR, and DSC locating and sizing methods are based on a fixed network structure, which is assumed to be unchangeable during the planning period. The research presented here discusses a hybrid approach working on genetic algorithm (GA) and Monte Carlo simulation (MCS) which can be used for enhancement of system power factor (SPF) and voltage profile (VP) by the integration of DG, DVR, and DSC planning in distribution networks with constant impedance (Z), constant current (I), constant power (P) load models (ZIP-LMs) from the minimization of total real power loss of the system viewpoint. The proposed methodology is applied to a 75-bus distribution network. This article is useful for researchers as well as practitioners who are working in the fields of integration of DG, DVR, and DSC for the improvement of system performances such as SPF and voltage profile from the minimization of total real power loss of the system viewpoint.