Conference paper
An intelligent approach of achieving demand response by fuzzy logic based domestic load management
Plant breeding for the 11th millenium [electronic resource] : proceedings of the 12th Australasian Plant Breeding Conference : Perth, Western Australia, 15-20 September 2002
Australasian Universities Power Engineering Conference (AUPEC2014) (Perth, Western Australia, 28/09/2014–01/10/2014)
2014
Abstract
Demand response is an important demand-side resource that allows consumers to consume less electricity when the system is under stress. Existing demand response mechanism reduces power consumption by forcefully shutting down the consumers’ loads or punishing the consumers with high consumption prices during high peak hours without considering their comfort level. This paper presents a methodology to design a model for domestic load management based on fuzzy logic techniques where three optimization parameters – comfort, cost and demand response are taken into account. Furthermore a comparative analysis for the power consumption and cost saving performance is carried out to show the benefit of using renewable energy sources along with a fuzzy logic based load controller. Simulation results show that the proposed controller successfully limits the power consumption during the peak hours and concurrently maximizes the savings of energy consumption cost without violating consumers’ comfort level.
Details
- Title
- An intelligent approach of achieving demand response by fuzzy logic based domestic load management
- Authors/Creators
- M.M. Rahman (Author/Creator)S.N. Hettiwatte (Author/Creator)S. Gyamfi (Author/Creator)
- Contributors
- J.A. McComb (Editor)
- Publication Details
- Plant breeding for the 11th millenium [electronic resource] : proceedings of the 12th Australasian Plant Breeding Conference : Perth, Western Australia, 15-20 September 2002
- Conference
- Australasian Universities Power Engineering Conference (AUPEC2014) (Perth, Western Australia, 28/09/2014–01/10/2014)
- Identifiers
- 991005542620507891
- Murdoch Affiliation
- School of Engineering and Information Technology
- Language
- English
- Resource Type
- Conference paper
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