Aggregate demand response strategies for smart communities with battery-charging/switching electric vehicles. (February 2023)

• Record Type: Journal Article
• Authors: Lin, Junguang; Sun, Juwei; Feng, Yanhao; Zheng, Menglian; Yu, Zitao
• Is Part Of: Journal of energy storage. Volume 58(2023)
• Publication Date: 2023-02
• Subjects: Battery switching station -- Battery charging station -- Electric vehicles -- Community energy storage -- Demand response -- Redistribution time-of-use tariff; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2022.106413
• Languages: English
• ISSNs: 2352-152X

Abstract

Abstract: Demand response (DR) plays an important role in the peak shaving and load-shifting of a community, but the avalanche effect creates a huge obstacle in DR with uncoordinated usage of appliances and charging of electric vehicles (EVs). Recognizing the remarkably rising deployment of EVs, there is great potential to coordinate EVs' charging in a charging station or a battery switching station for providing DR. However, the potential benefits of the battery-switching EVs for providing DR and their impacts on the aggregate load of the community have not been fully studied. In this regard, the present study proposes two novel aggregate community-level DR strategies, i.e., a strategy employing battery-charging EVs and a strategy employing battery-switching EVs. The proposed strategies are compared with the conventional strategy that only incorporates community battery energy storage for enabling peak shaving. The cost optimization is conducted with optimization parameters including demand limits during different periods and the power and energy capacity of the battery energy storage system. A stochastic bottom-up demand model for households, a probabilistic model for predicting loads of EVs, and a redistribution time-of-use tariff are implemented in the optimization. A group with 20 households and 20 EVs in New York, USA is used in the case study. The results in the case study show that the total annual costs (electricity tariff cost and battery energy storage cost if any) are reduced by 63.3 %, 54.0 %, and 14.7 % under the battery-switching EV strategy, the battery-charging EV strategy, and the battery energy storage strategy compared to the base case (i.e., DR-free strategy), respectively. Additionally, the battery-switching EV strategy enables DR throughout the day with the maximum temporal flexibility. Last, the developed two EV strategies can provide a good stability of the household loads on the grid and avoid the avalanche effect. Highlights: Propose a cooperative DR strategy with battery energy storage and EVs Enable the participation of a community battery-switching station in DR Combine a redistribution time-of-use tariff and demand limit in DR strategy DR strategy smooths out demand profiles and reduces tariff cost of the community. Charging flexibility of batteries in battery-switching station further reduces peaks.