A piecewise-affine decision rule based stochastic AC optimal power flow approach
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 realization...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/150949 |
| _version_ | 1826126737087397888 |
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| author | Isuru, Mohasha Foo, Eddy Yi Shyh Gooi, Hoay Beng |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Isuru, Mohasha Foo, Eddy Yi Shyh Gooi, Hoay Beng |
| author_sort | Isuru, Mohasha |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T06:57:14Z |
| format | Conference Paper |
| id | ntu-10356/150949 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:57:14Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | ntu-10356/1509492021-06-15T10:02:09Z A piecewise-affine decision rule based stochastic AC optimal power flow approach Isuru, Mohasha Foo, Eddy Yi Shyh Gooi, Hoay Beng School of Electrical and Electronic Engineering 2020 IEEE Power & Energy Society General Meeting (PESGM) Centre for system intelligence and efficiency (EXQUISITUS) Engineering::Electrical and electronic engineering::Electric power AC Optimal Power Flow Piecewise-affine Decision Rule 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. Ministry of Education (MOE) Accepted version Mohasha Isuru and Eddy Y. S. Foo acknowledge the support of the Singapore Ministry of Education Academic Research Fund Tier 1 Grant (MOE2018-T1-002-093). 2021-06-15T09:48:32Z 2021-06-15T09:48:32Z 2020 Conference Paper 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 9781728155081 https://hdl.handle.net/10356/150949 10.1109/PESGM41954.2020.9281413 2-s2.0-85099167378 2020-August 1 5 en 2018-T1-002-093 © 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 application/pdf |
| spellingShingle | Engineering::Electrical and electronic engineering::Electric power AC Optimal Power Flow Piecewise-affine Decision Rule Isuru, Mohasha Foo, Eddy Yi Shyh Gooi, Hoay Beng A piecewise-affine decision rule based stochastic AC optimal power flow approach |
| title | A piecewise-affine decision rule based stochastic AC optimal power flow approach |
| title_full | A piecewise-affine decision rule based stochastic AC optimal power flow approach |
| title_fullStr | A piecewise-affine decision rule based stochastic AC optimal power flow approach |
| title_full_unstemmed | A piecewise-affine decision rule based stochastic AC optimal power flow approach |
| title_short | A piecewise-affine decision rule based stochastic AC optimal power flow approach |
| title_sort | piecewise affine decision rule based stochastic ac optimal power flow approach |
| topic | Engineering::Electrical and electronic engineering::Electric power AC Optimal Power Flow Piecewise-affine Decision Rule |
| url | https://hdl.handle.net/10356/150949 |
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