Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal Units
The deep peak regulation of thermal units is an important measure for coping with significant wind power penetration. In this paper, based on interval optimization, a novel multi-objective unit commitment method is proposed considering the deep peak regulation of thermal units. In the proposed metho...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-03-01
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| Series: | Energies |
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| Online Access: | http://www.mdpi.com/1996-1073/12/5/922 |
| _version_ | 1798005070084702208 |
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| author | Yinping Yang Chao Qin Yuan Zeng Chengshan Wang |
| author_facet | Yinping Yang Chao Qin Yuan Zeng Chengshan Wang |
| author_sort | Yinping Yang |
| collection | DOAJ |
| description | The deep peak regulation of thermal units is an important measure for coping with significant wind power penetration. In this paper, based on interval optimization, a novel multi-objective unit commitment method is proposed considering the deep peak regulation of thermal units. In the proposed method, a thermal power cost model was developed to accurately determine the economic performance of three different peak regulation scenarios, particularly of the deep peak regulation scenario. The midpoint and width of the cost interval are simultaneously considered in the optimization process. The non-dominated sorting GA-II (NSGA-II) algorithm was incorporated into the model for a coordinated control of the midpoint and width of the obtained cost interval for further optimization. Considering that significant wind penetration results in greater nodal variations, the affine arithmetic was employed to solve nodal uncertainties, so that all system variations can be addressed. The method proposed in this paper was validated by a modified IEEE-39 bus system. The results showed that it serves as a useful tool for power dispatchers to obtain robust and economic solutions at different wind power prediction accuracies. |
| first_indexed | 2024-04-11T12:33:29Z |
| format | Article |
| id | doaj.art-7cab2dd29e8f46cebb7b128ff14b9c35 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T12:33:29Z |
| publishDate | 2019-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-7cab2dd29e8f46cebb7b128ff14b9c352022-12-22T04:23:41ZengMDPI AGEnergies1996-10732019-03-0112592210.3390/en12050922en12050922Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal UnitsYinping Yang0Chao Qin1Yuan Zeng2Chengshan Wang3Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, ChinaThe deep peak regulation of thermal units is an important measure for coping with significant wind power penetration. In this paper, based on interval optimization, a novel multi-objective unit commitment method is proposed considering the deep peak regulation of thermal units. In the proposed method, a thermal power cost model was developed to accurately determine the economic performance of three different peak regulation scenarios, particularly of the deep peak regulation scenario. The midpoint and width of the cost interval are simultaneously considered in the optimization process. The non-dominated sorting GA-II (NSGA-II) algorithm was incorporated into the model for a coordinated control of the midpoint and width of the obtained cost interval for further optimization. Considering that significant wind penetration results in greater nodal variations, the affine arithmetic was employed to solve nodal uncertainties, so that all system variations can be addressed. The method proposed in this paper was validated by a modified IEEE-39 bus system. The results showed that it serves as a useful tool for power dispatchers to obtain robust and economic solutions at different wind power prediction accuracies.http://www.mdpi.com/1996-1073/12/5/922deep peak regulationunit commitmentinterval numberoptimization methods |
| spellingShingle | Yinping Yang Chao Qin Yuan Zeng Chengshan Wang Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal Units Energies deep peak regulation unit commitment interval number optimization methods |
| title | Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal Units |
| title_full | Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal Units |
| title_fullStr | Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal Units |
| title_full_unstemmed | Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal Units |
| title_short | Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal Units |
| title_sort | interval optimization based unit commitment for deep peak regulation of thermal units |
| topic | deep peak regulation unit commitment interval number optimization methods |
| url | http://www.mdpi.com/1996-1073/12/5/922 |
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