This paper describes a fuzzy logic-based demand-side management (DSM) strategy to shift the peaks of the average residential electric water heater power demand profile from periods of high demand for electricity to off-peak hours. The DSM strategy is achieved by dividing the distribution area water heaters into several blocks and controlling each by a different fuzzy controller. Simulation results are presented to show the effectiveness of the proposed DSM strategy to shift the average electric water heater peak demand to off-peak periods and to level utility distribution demand profile.
Abstract-This paper reports the development of a computer approach for evaluating the general performance of stand-alone wind/photovoltaic generating systems. Simple models for different system components are developed, integrated, and used to predict the behavior of generating systems based on available wind/solar and load data. The model is useful for evaluating the performance of stand-alone generating systems and gaining a better insight in the component sizes needed before they are built. Simulation results are presented for performance evaluation of a stand-alone generating system that has been previously designed to supply the average power demand of a typical residential house [1].An electric water heater model is used as a dump load, and the excess available wind/solar-generated power is used to heat the water. The heated water is used as the inlet water to the main house water heater, which is assumed to be nonelectric. It is shown that this strategy can be effective in reducing the amount of fuel used by the main residential water heater.Index Terms-Computer modeling, electric water heater dump load, wind/PV generation.
With the impending deregulation of electric utility industry, customer satisfaction with utility services will be crucial. Utilities will need to place a greater emphasis on their customers' preferences and desires. This would include the recognition and inclusion of customer comfort and satisfaction into utility demand side management programs. This paper presents a fuzzy logic-based water heater and air conditioner direct load controller recognizing several important customer preferences and desires. Study results show that the proposed controller successfully shifts the average power demand of customer loads and thus improves utility's load factor.
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