Multi-Time Scale Optimization Scheduling Strategy for Combined Heat and Power System Based on Scenario Method
The wind–heat conflict and wind power uncertainty are the main factors leading to the phenomenon of wind curtailment during the heating period in the northern region of China. In this paper, a multi-time scale optimal scheduling strategy for combined heat and power system is proposed. Considering th...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/7/1599 |
| _version_ | 1797571761938628608 |
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| author | Yunhai Zhou Shengkai Guo Fei Xu Dai Cui Weichun Ge Xiaodong Chen Bo Gu |
| author_facet | Yunhai Zhou Shengkai Guo Fei Xu Dai Cui Weichun Ge Xiaodong Chen Bo Gu |
| author_sort | Yunhai Zhou |
| collection | DOAJ |
| description | The wind–heat conflict and wind power uncertainty are the main factors leading to the phenomenon of wind curtailment during the heating period in the northern region of China. In this paper, a multi-time scale optimal scheduling strategy for combined heat and power system is proposed. Considering the temporal dependence of wind power fluctuation, the intra-day wind power scenario generation method is put forward, and both day-ahead and intra-day optimization scheduling models based on the scenario method are established to maximize the system’s revenue. The case analyzes the impacts of the initial heat storage capacity of a heat storage device and different scheduling strategies on system revenue. It is verified that the scheduling strategy can better adapt to wind power uncertainty and improve the absorption capacity of wind power, while ensuring the safety and economical efficiency of system operation. |
| first_indexed | 2024-03-10T20:45:07Z |
| format | Article |
| id | doaj.art-a49c71931a4f437dba945377431136e8 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T20:45:07Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-a49c71931a4f437dba945377431136e82023-11-19T20:21:27ZengMDPI AGEnergies1996-10732020-04-01137159910.3390/en13071599Multi-Time Scale Optimization Scheduling Strategy for Combined Heat and Power System Based on Scenario MethodYunhai Zhou0Shengkai Guo1Fei Xu2Dai Cui3Weichun Ge4Xiaodong Chen5Bo Gu6College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443000, ChinaCollege of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443000, ChinaDepartment of Electrical Engineering, Tsinghua University, Beijing 100000, ChinaJinzhou Power Supply Company, Liaoning Electric Power Co., Ltd., Shenyang 100084, ChinaJinzhou Power Supply Company, Liaoning Electric Power Co., Ltd., Shenyang 100084, ChinaJinzhou Power Supply Company, Liaoning Electric Power Co., Ltd., Shenyang 100084, ChinaJinzhou Power Supply Company, Liaoning Electric Power Co., Ltd., Shenyang 100084, ChinaThe wind–heat conflict and wind power uncertainty are the main factors leading to the phenomenon of wind curtailment during the heating period in the northern region of China. In this paper, a multi-time scale optimal scheduling strategy for combined heat and power system is proposed. Considering the temporal dependence of wind power fluctuation, the intra-day wind power scenario generation method is put forward, and both day-ahead and intra-day optimization scheduling models based on the scenario method are established to maximize the system’s revenue. The case analyzes the impacts of the initial heat storage capacity of a heat storage device and different scheduling strategies on system revenue. It is verified that the scheduling strategy can better adapt to wind power uncertainty and improve the absorption capacity of wind power, while ensuring the safety and economical efficiency of system operation.https://www.mdpi.com/1996-1073/13/7/1599combined heat and power systemwind power uncertaintyscenario methodtemporal dependenceoptimization scheduling |
| spellingShingle | Yunhai Zhou Shengkai Guo Fei Xu Dai Cui Weichun Ge Xiaodong Chen Bo Gu Multi-Time Scale Optimization Scheduling Strategy for Combined Heat and Power System Based on Scenario Method Energies combined heat and power system wind power uncertainty scenario method temporal dependence optimization scheduling |
| title | Multi-Time Scale Optimization Scheduling Strategy for Combined Heat and Power System Based on Scenario Method |
| title_full | Multi-Time Scale Optimization Scheduling Strategy for Combined Heat and Power System Based on Scenario Method |
| title_fullStr | Multi-Time Scale Optimization Scheduling Strategy for Combined Heat and Power System Based on Scenario Method |
| title_full_unstemmed | Multi-Time Scale Optimization Scheduling Strategy for Combined Heat and Power System Based on Scenario Method |
| title_short | Multi-Time Scale Optimization Scheduling Strategy for Combined Heat and Power System Based on Scenario Method |
| title_sort | multi time scale optimization scheduling strategy for combined heat and power system based on scenario method |
| topic | combined heat and power system wind power uncertainty scenario method temporal dependence optimization scheduling |
| url | https://www.mdpi.com/1996-1073/13/7/1599 |
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