Improved decomposition–coordination and discrete differential dynamic programming for optimization of large-scale hydropower system
•Optimization of large-scale hydropower system in the Yangtze River basin.•Improved decomposition–coordination and discrete differential dynamic programming.•Generating initial solution randomly to reduce generation time.•Proposing relative coefficient for more power generation.•Proposing adaptive b...
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| Published in: | Energy conversion and management Vol. 84; pp. 363 - 373 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier Ltd
01.08.2014
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| ISSN: | 0196-8904, 1879-2227 |
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| Abstract | •Optimization of large-scale hydropower system in the Yangtze River basin.•Improved decomposition–coordination and discrete differential dynamic programming.•Generating initial solution randomly to reduce generation time.•Proposing relative coefficient for more power generation.•Proposing adaptive bias corridor technology to enhance convergence speed.
With the construction of major hydro plants, more and more large-scale hydropower systems are taking shape gradually, which brings up a challenge to optimize these systems. Optimization of large-scale hydropower system (OLHS), which is to determine water discharges or water levels of overall hydro plants for maximizing total power generation when subjecting to lots of constrains, is a high dimensional, nonlinear and coupling complex problem. In order to solve the OLHS problem effectively, an improved decomposition–coordination and discrete differential dynamic programming (IDC–DDDP) method is proposed in this paper. A strategy that initial solution is generated randomly is adopted to reduce generation time. Meanwhile, a relative coefficient based on maximum output capacity is proposed for more power generation. Moreover, an adaptive bias corridor technology is proposed to enhance convergence speed. The proposed method is applied to long-term optimal dispatches of large-scale hydropower system (LHS) in the Yangtze River basin. Compared to other methods, IDC–DDDP has competitive performances in not only total power generation but also convergence speed, which provides a new method to solve the OLHS problem. |
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| AbstractList | With the construction of major hydro plants, more and more large-scale hydropower systems are taking shape gradually, which brings up a challenge to optimize these systems. Optimization of large-scale hydropower system (OLHS), which is to determine water discharges or water levels of overall hydro plants for maximizing total power generation when subjecting to lots of constrains, is a high dimensional, nonlinear and coupling complex problem. In order to solve the OLHS problem effectively, an improved decomposition-coordination and discrete differential dynamic programming (IDC-DDDP) method is proposed in this paper. A strategy that initial solution is generated randomly is adopted to reduce generation time. Meanwhile, a relative coefficient based on maximum output capacity is proposed for more power generation. Moreover, an adaptive bias corridor technology is proposed to enhance convergence speed. The proposed method is applied to long-term optimal dispatches of large-scale hydropower system (LHS) in the Yangtze River basin. Compared to other methods, IDC-DDDP has competitive performances in not only total power generation but also convergence speed, which provides a new method to solve the OLHS problem. •Optimization of large-scale hydropower system in the Yangtze River basin.•Improved decomposition–coordination and discrete differential dynamic programming.•Generating initial solution randomly to reduce generation time.•Proposing relative coefficient for more power generation.•Proposing adaptive bias corridor technology to enhance convergence speed. With the construction of major hydro plants, more and more large-scale hydropower systems are taking shape gradually, which brings up a challenge to optimize these systems. Optimization of large-scale hydropower system (OLHS), which is to determine water discharges or water levels of overall hydro plants for maximizing total power generation when subjecting to lots of constrains, is a high dimensional, nonlinear and coupling complex problem. In order to solve the OLHS problem effectively, an improved decomposition–coordination and discrete differential dynamic programming (IDC–DDDP) method is proposed in this paper. A strategy that initial solution is generated randomly is adopted to reduce generation time. Meanwhile, a relative coefficient based on maximum output capacity is proposed for more power generation. Moreover, an adaptive bias corridor technology is proposed to enhance convergence speed. The proposed method is applied to long-term optimal dispatches of large-scale hydropower system (LHS) in the Yangtze River basin. Compared to other methods, IDC–DDDP has competitive performances in not only total power generation but also convergence speed, which provides a new method to solve the OLHS problem. |
| Author | Zhou, Jianzhong Chen, Lu Ouyang, Shuo Li, Chunlong Ding, Xiaoling |
| Author_xml | – sequence: 1 givenname: Chunlong surname: Li fullname: Li, Chunlong – sequence: 2 givenname: Jianzhong surname: Zhou fullname: Zhou, Jianzhong email: jz.zhou@mail.hust.edu.cn – sequence: 3 givenname: Shuo surname: Ouyang fullname: Ouyang, Shuo – sequence: 4 givenname: Xiaoling surname: Ding fullname: Ding, Xiaoling – sequence: 5 givenname: Lu surname: Chen fullname: Chen, Lu |
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| Keywords | Decomposition–coordination Discrete differential dynamic programming Long-term optimization The Yangtze River basin Improvement strategies Large-scale hydropower system Hydroelectric power plant Hydraulic power Improvement Electric power production Dynamic programming Decomposition-coordination Optimization |
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| Snippet | •Optimization of large-scale hydropower system in the Yangtze River basin.•Improved decomposition–coordination and discrete differential dynamic... With the construction of major hydro plants, more and more large-scale hydropower systems are taking shape gradually, which brings up a challenge to optimize... |
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| SubjectTerms | Applied sciences Decomposition Decomposition–coordination Discrete differential dynamic programming Dynamic programming Dynamical systems Energy Energy of waters: ocean thermal energy, wave and tidal energy, etc Energy. Thermal use of fuels Exact sciences and technology Hydroelectric power Hydroelectric power plants Improvement strategies Installations for energy generation and conversion: thermal and electrical energy Large-scale hydropower system Long-term optimization Natural energy Nonlinear dynamics Optimization Power generation Power plants The Yangtze River basin water power watersheds Yangtze River |
| Title | Improved decomposition–coordination and discrete differential dynamic programming for optimization of large-scale hydropower system |
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