Strategic interaction to reduce customer fatigue in load aggregation. (November 2021)

• Record Type: Journal Article
• Authors: Chen, Xinyi; Xu, Xiaochun; Dai, Xin; Hu, Qinran; Quan, Xiangjun; Yang, Shengzhe
• Is Part Of: Energy reports. Volume 7(2021)Supplement 6
• Page Start: 339
• Page End: 348
• Publication Date: 2021-11
• Subjects: Customer fatigue -- Load aggregation -- Online learning -- Fatigue-aware MAB; Power resources -- Periodicals; Energy industries -- Periodicals; Power resources; Periodicals; Electronic journals; 621.04205
• DOI: 10.1016/j.egyr.2021.08.039
• Languages: English
• ISSNs: 2352-4847

Abstract

Abstract: In demand response programs, the load aggregator would send requests to customers to confirm whether they are willing to participate in the demand response events later, making sure that there is sufficient capacity to meet the load adjustment requirement of the power grid in real-time. However, sending requests frequently to the customers would lead to customer fatigue effect, which dampens customers' enthusiasm for demand response. Motivated by this dilemma, an optimization problem of scheduling customers considering fatigue based on the MAB framework is proposed, and the online learning and ranking method: fatigue-aware MAB is presented to solve it. Finally, the numerical simulation demonstrates that the proposed method outperforms the traditional method under different parameter settings. Detailed analysis of how those settings affect the performance of our proposed method is also provided.