Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/150949
Title: A piecewise-affine decision rule based stochastic AC optimal power flow approach
Authors: Isuru, Mohasha
Foo, Eddy Yi Shyh 
Gooi, Hoay Beng 
Keywords: Engineering::Electrical and electronic engineering::Electric power
Issue Date: 2020
Source: Isuru, M., Foo, E. Y. S. & Gooi, H. B. (2020). A piecewise-affine decision rule based stochastic AC optimal power flow approach. 2020 IEEE Power & Energy Society General Meeting (PESGM), 2020-August, 1-5. https://dx.doi.org/10.1109/PESGM41954.2020.9281413
Project: 2018-T1-002-093
Abstract: This paper proposes a piecewise-affine decision rule based stochastic optimal power flow approach for reserve dispatch of generators under uncertain demand and renewable energy source generation. The ambiguity set comprises a predefined set of scenarios to capture the plausible uncertain realizations. The objective is to minimize the expected generation cost under those scenarios. A piecewise-affine decision rule is established with auxiliary control parameters to compute the optimal participation of generators depending on the amounts of reserve requirements. Such a reserve dispatch rule would be less conservative compared to the traditional affine decision rule. The results illustrate that the proposed piecewise-affine generation redispatch rule improves the optimality of operation via efficient resource utilization for reserve support.
URI: https://hdl.handle.net/10356/150949
ISBN: 9781728155081
DOI: 10.1109/PESGM41954.2020.9281413
Rights: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/PESGM41954.2020.9281413
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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