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Short-term generation scheduling of a remote area hybrid energy system using computational intelligence techniques

Fung, C.C., Iyer, V. and Maynard, C. (1998) Short-term generation scheduling of a remote area hybrid energy system using computational intelligence techniques. In: Proceedings of the 1998 International conference on Power Electronic Drives and energy Systems for Industrial growth, PEDES’98, 1 - 3 December, Perth, Western Australia pp. 365-370.

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Link to Published Version: http://dx.doi.org/10.1109/PEDES.1998.1330043
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Abstract

This paper presents a solution to the short term generation scheduling problem in a hybrid energy system, used in remote area power supply (RAPS). Instead of extending the main electricity grid, RAPS systems are economical alternatives for the supply of electrical energy to consumers in remote areas. A typical generation system consists of one or more diesel generators, a storage battery bank and renewable energy sources. In this paper, a fuzzy logic algorithm together with a genetic algorithm is used to determine the optimal short term scheduling which minimises the fuel consumption for a time horizon of 24 hours. The system considered in this study for the validation of the proposed method consists of two diesel generators, solar panel and a battery bank. Data from a remote site in the Northern Territory of Australia are used for simulation purpose. Results from the studies have demonstrated a maximum saving of up to 20% on some days.

Publication Type: Conference Paper
URI: http://researchrepository.murdoch.edu.au/id/eprint/22034
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