Peak Reduction and Long Term Load Forecasting for Large Residential Communities Including Smart Homes with Energy Storage
Domestic load profiles in the residential sectors are being modified with the adoption of smart home management systems and solar generation. In addition, houses with rooftop PV behave like local generators, contributing to the growth of the penetration of PV energy. Hence, the demand for power is declining day by day. However, the increasing PV penetration causes technical challenges for the power system, such as the “duck curve”. This can be addressed through home energy management (HEM) techniques including peak shaving, load shifting with smart home devices. In this regard, electric water heaters (EWH), with high thermal mass and being ubiquitous, are attractive and low-cost energy storage systems. In this article, a case study for one of the largest rural field smart energy technology demonstrators involving business, industries, and more than 5,000 residences, located in Glasgow, KY, US, is presented. Furthermore, a HEM system, which aims to minimize the total energy usage and peak demand by regulating the heating, ventilation, and air-conditioning (HVAC) systems, water heaters, and batteries, thereby benefiting both the utility and the consumer is proposed. This work also demonstrates the ability of EWH to provide ancillary services while maintaining customer comfort. The minimum participation rates for EWH and batteries are calculated and compared with respect to different peak reduction targets. Long term load prediction by considering different fractions of smart homes for the utility is also provided.
Digital Object Identifier (DOI)
Gong, Huangjie; Rallabandi, Vandana; McIntyre, Michael L.; Hossain, Eklas; and Ionel, Dan M., "Peak Reduction and Long Term Load Forecasting for Large Residential Communities Including Smart Homes with Energy Storage" (2021). Power and Energy Institute of Kentucky Faculty Publications. 52.
Published in IEEE Access, v. 9.
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