Abstract
An application of computational intelligence techniques to the optimisation of a hybrid energy system operational cost is reported in this paper. The hybrid energy system is an example of the Remote Area Power Supply (RAPS) systems used in many countries in the Pacific Rim. A hybrid energy system typically comprises of a diesel generator, solar panels and a battery bank. It is used in areas where then main electricity supply grids are unavailable. In this study, a fuzzy logic algorithm is used to determine the initial generator operational schedule and the battery discharge-charge schedules for the next 24-hour period. A genetic algorithm is then used to find an optimum solution with minimal generation cost. Simulation of the algorithm has been carried on a system operating at a remote site in the Northern Territory, Australia. An average saving of 10% in fuel cost was demonstrated in the case study.
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Fung, C., Iyer, V., Maynard, C. (1998). Computational intelligence techniques for short term generation scheduling in a hybrid energy system. In: Lee, HY., Motoda, H. (eds) PRICAI’98: Topics in Artificial Intelligence. PRICAI 1998. Lecture Notes in Computer Science, vol 1531. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095276
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DOI: https://doi.org/10.1007/BFb0095276
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