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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Vydané v:Energy conversion and management Ročník 84; s. 363 - 373
Hlavní autori: Li, Chunlong, Zhou, Jianzhong, Ouyang, Shuo, Ding, Xiaoling, Chen, Lu
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Kidlington Elsevier Ltd 01.08.2014
Elsevier
Predmet:
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
Yangtze River
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
ISSN:0196-8904, 1879-2227
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Shrnutí:•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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ISSN:0196-8904
1879-2227
DOI:10.1016/j.enconman.2014.04.065