Multicore Parallel Dynamic Programming Algorithm for Short-Term Hydro-Unit Load Dispatching of Huge Hydropower Stations Serving Multiple Power Grids

Short-term hydro-unit load dispatching (SHULD) refers to the determination of the power output of each unit within a hydropower station over a planning horizon to minimize the operational cost or maximize the power-generation profit while satisfying hydraulic and electrical constraints. In China, hu...

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Veröffentlicht in:Water resources management Jg. 34; H. 1; S. 359 - 376
Hauptverfasser: Liao, Shengli, Liu, Jie, Liu, Benxi, Cheng, Chuntian, Zhou, Lingan, Wu, Huijun
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Dordrecht Springer Netherlands 01.01.2020
Springer Nature B.V
Schlagworte:
Algorithms
Atmospheric Sciences
Canyons
case studies
China
Civil Engineering
Computation
computers
Dry season
Dynamic programming
Earth and Environmental Science
Earth Sciences
Electric power grids
Environment
Geotechnical Engineering & Applied Earth Sciences
Hydroelectric power
Hydroelectric power stations
Hydrogeology
Hydrology/Water Resources
Operating costs
Parallel processing
power generation
Rainy season
Receiving waters
Unit loads
Vibration
water power
China
Xiluodu hydropower station
Multicore parallel dynamic programming
Multiple power grids
Fork/join framework
Short-term hydro-unit load distribution
ISSN:0920-4741, 1573-1650
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Zusammenfassung:Short-term hydro-unit load dispatching (SHULD) refers to the determination of the power output of each unit within a hydropower station over a planning horizon to minimize the operational cost or maximize the power-generation profit while satisfying hydraulic and electrical constraints. In China, huge hydropower stations, such as the Three Gorges (TG) and Xiluodu (XLD) stations, are composed of a large number of hydro units, which feature a high installed capacity and a high water head. SHULD models of these stations are more complex and difficult to solve compared with those of traditional stations, especially when the stations serve multiple power grids. This study develops a practical method for optimizing SHULD models by considering the XLD hydropower station as a case study. First, a SHULD model for huge hydropower stations with multiple vibration zones and multiple receiving power grids is presented. Second, classical and sophisticated dynamic programming (DP) is applied to the SHULD model, and a practical strategy is proposed to balance the available water in a reservoir’s left and right banks to satisfy their load demands. Finally, the Fork/Join framework is used to parallelize DP to reduce the computation time and fully utilize the computer resources. The wet and dry season results demonstrate that the approach is efficient and suitable for huge hydropower stations with a high water head and multiple receiving power grids, thereby demonstrating its potential practicability and validity for solving the SHULD problem.
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ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-019-02455-w