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- W4328104180 abstract "This paper concentrates on using electric water heaters with the aim of demanding response. This is so as this method is considered most efficient when it comes to ensuring the safety and stabilization of power grids through the maintenance of balance between the demand and supply of the power grid. For this reason, the article investigates the overshoot temperature and the impact it has on demand response as well as to ensure the comfort and pricing variables as it happened in previous publications. The demand response process utilizing electric water heaters is explored as well as the impact of the physical parameters and the settings of the water heaters. In addition, a model is developed which puts into consideration the demand response requirements, the comfort of these water heater equipment, the power supply price in a simultaneous manner. Also, the effect of these factors on the end results of demand response is addressed. Experimental data is further used to demonstrate the efficiency of the suggested strategy." @default.
- W4328104180 created "2023-03-22" @default.
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- W4328104180 date "2023-02-22" @default.
- W4328104180 modified "2023-09-25" @default.
- W4328104180 title "Cloud Computing Based Demand Response Management Using Deep Reinforcement Learning; Review" @default.
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- W4328104180 doi "https://doi.org/10.14293/s2199-1006.1.sor-.ppfi6ov.v1" @default.
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