Interval Optimization-Based Unit Commitment for Deep Peak Regulation of Thermal Units

Yinping Yang, Chao Qin, Yuan Zeng and Chengshan Wang
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Yinping Yang: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Chao Qin: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Yuan Zeng: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Chengshan Wang: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China

Energies, 2019, vol. 12, issue 5, 1-21

Abstract: 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.

Keywords: deep peak regulation; unit commitment; interval number; optimization methods (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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