A composite sensitivity factor based method for networked distributed generation planning

Abstract

Distributed generation (DG) can provide multiple benefits to distribution networks such as power loss reduction and voltage stability enhancement. Today's distribution networks are designed with an increased penetration level of DG. In this paper, a novel composite sensitivity factor based method (CSFBM) is proposed for optimizing locations and sizes of network owned DG units to decrease the losses and to improve the voltage stability simultaneously in a distribution network. CSFBM prioritizes the buses which are more sensitive to the losses and the voltage stability and then applies sensitivity factors to settle DG units iteratively. Besides, uncertainties of renewable resource DG outputs are fully considered with a discrete Monte Carlo simulation. CSFBM is tested on two radial distribution systems with different scenarios including single stage and multi-stage planning. In comparison to a multi-objective genetic algorithm, the DG allocations performed by CSFBM are unique satisfying optimization solutions with a much higher efficiency.