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As the penetration of renewable energy resources increases, their intrinsic uncertainty and randomness raise significant concerns about the grid&#x2019;s reliability. With the development of information technologies, residential air-conditioners serve increasing services, including secondary frequency regulation, peak load shaving, and capacity reserve. However, these resources can hardly be allocated economically and reliably. On the one hand, it is unrealistic to provide advanced and expensive control modes for all AC units due to the limited investment cost. On the other hand, the uncertainty of residents&#x2019; behavior varying with control modes affects the reliability. Few previous works effectively make a trade-off between economics and reliability, which restricts the value of residential air-conditioners. Thus, this paper proposed an economical and reliable allocation method based on a real survey dataset and the online learning multi-armed bandits framework. This method explores the inherent relationship between the allocation plan&#x2019;s economics and reliability. We also propose an allocation model which enables system operators to design an economic and reliable plan for each residential area considering ancillary services requirements. A case study in a modified IEEE 9 nodes system illustrates the effectiveness of the proposed method.

Optimal Allocation Method of Residential Air-Conditioners: Trade-Off Solutions Between Economic Costs and Aggregation Reliability