A centralized fuzzy controller for aggregated control of domestic water heaters
Khalid Elgazzar, Howard Li, Liuchen Chang
Abstract
Khalid Elgazzar, Howard Li, Liuchen Chang
Abstract
Utilizing aggregated electric loads as system resources has several benefits. It can provide ancillary services for power systems. At the same time, it can provide demand management for electricity customers. It is necessary to develop integrated control strategies for aggregated electric loads. Most domesticwater heaters (DWHs) are electric and they consume much power especially in winter. DWHs represent a substantial share of the residential electricity consumption. Due to the energy storage capability of DWHs they are the best candidates for load control strategies. In this paper, we propose a novel centralized fuzzy controller for peak shaving of the power demand profiles. The proposed centralized controller does not sacrifice customers' convenience level. Simulation results show that the proposed centralized control strategy is effective in shaving the aggregated DWHs load demands while filling valleys of the aggregated load profile.
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Utilizing aggregated electric loads as system resources has several benefits. It can provide ancillary services for power systems. At the same time, it can provide demand management for electricity customers. It is necessary to develop integrated control strategies for aggregated electric loads. Most domesticwater heaters (DWHs) are electric and they consume much power especially in winter. DWHs represent a substantial share of the residential electricity consumption. Due to the energy storage capability of DWHs they are the best candidates for load control strategies. In this paper, we propose a novel centralized fuzzy controller for peak shaving of the power demand profiles. The proposed centralized controller does not sacrifice customers' convenience level. Simulation results show that the proposed centralized control strategy is effective in shaving the aggregated DWHs load demands while filling valleys of the aggregated load profile.
Key concepts: Peaking power plant, Peak demand, Controller (irrigation), Electricity, Load management, Fuzzy logic, Computer science, Demand response