Short-term real-power scheduling considering fuzzy factors in an autonomous system using genetic algorithms

Abstract

Distributed generation has several advantages such as reducing required transmission capacity and real power losses, and in terms of traditional generation expansion etc. An autonomous system is an independent system that may include diesel generators, a wind park, solar photovoltaic (PV) modules and/or batteries etc. serving its loads. The paper presents a new method for dealing with short-term power scheduling of an autonomous system. The fuel cost of diesel units is required to be smaller than an expected value and all operational constraints are satisfied. In particular, wind and solar PV power generation with uncertainties are modelled by a fuzzy set. The genetic algorithm is used to solve this problem formulated as symmetrical fuzzy programming. Simulation results based on an autonomous system show the applicability of the proposed method.