Combined fuzzy-logic and genetic algorithm technique for the scheduling of remote area power system

Abstract

Remote area power supply (RAPS) systems are commonly used at isolated locations where the mains grid connection is unavailable. Majority of the RAPS systems consist of either single or multiple diesel generators. Efficiencies of such systems however are low due to the variations in the load demands. To improve the system efficiency, hybrid energy systems consist of diesel generator, solar generator, storage battery bank and inverter have been developed. Optimal operation of such systems however depends on the scheduling of the battery charge/discharge cycle and load settings of the diesel generator. This paper proposes a new approach based on fuzzy logic (FL) and genetic algorithm (GA) techniques for the scheduling of the battery and the diesel generator of a RAPS system. Two methods have been developed. One was based on a pure genetic algorithm (PGA) approach, and the other was based on a combined fuzzy-logic and genetic algorithm (FGA) approach. Simulation studies have been carried out with both methods for single and multiple generators connected to a typical RAPS system. In terms of efficiency and charge/discharge cycles, the FGA method is found to be capable of providing a better result.