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Title: Virtual storage-based DSM with error-driven prediction modulation for microgrids
Authors: Lee, Xuecong
Yan, Mengxuan
Xu, Fang Yuan
Wang, Yue
Fan, Yiliang
Lee, Zekai
Wen, Yonggang
Mohammad Shahidehpour
Lai, Loi Lei
Keywords: Storage
Engineering::Computer science and engineering
Issue Date: 2019
Source: Lee, X., Yan, M., Xu, F. Y., Wang, Y., Fan, Y., Lee, Z., . . . Lai, L. L. (2019). Virtual storage-based DSM with error-driven prediction modulation for microgrids. IEEE Access, 7, 71109-71118. doi:10.1109/ACCESS.2019.2913898
Series/Report no.: IEEE Access
Abstract: Microgrids consider adjustable loads in demand-side management (DSM), which respond to dynamic market prices. A reliable DSM strategy relies on load forecasting techniques in day-ahead (DA) scheduling. This paper applies an error-driven prediction modulation to evaluate these differences. In addition, this paper creates two new DSM methods with an evaluation environment to utilize this modulation. The first method adds this modulation directly to traditional microgrid DSM with electrical storage. The second method creates two virtual sub-storages for behavior adjustment in both DA and real-time (RT) markets. The results of numerical studies indicate that the new DSM methods can reduce microgrid operation costs.
DOI: 10.1109/ACCESS.2019.2913898
Rights: Articles accepted before 12 June 2019 were published under a CC BY 3.0 or the IEEE Open Access Publishing Agreement license. Questions about copyright policies or reuse rights may be directed to the IEEE Intellectual Property Rights Office at +1-732-562-3966 or
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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