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Erschienen in: Water Resources Management 7/2018

26.02.2018

Application Research of the Improved Overall Temporal and Spatial Economic Operation Model Based on Information Entropy in Large-Scale Hydropower Station

verfasst von: Liu Yang, Kan Yang, Lei Chen

Erschienen in: Water Resources Management | Ausgabe 7/2018

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Abstract

For the high dimensional and complex inner-plant economical operation problem of large hydropower station, an improved ant colony optimization with adaptive ability, inspiring ability and local search ability was proposed. Spatial optimal load distribution model and temporal unit commitment model was combined into an overall temporal and spatial economic operation model, in which an innovative ant colony model of multiple ant colonies, multiple outsets and multiple routes was adopted. Information entropy was applied to adjust the path selection strategy and pheromone updating strategy of ant colonies along with the change of its value during the iteration. Two inspiring factors were applied in the algorithm to guide the ant colonies to search for optimal paths in a more efficient and targeted way. Local search ability was guaranteed by local translation of unit start-stop points of the optimal solution in each iteration. In the optimal load distribution model, optimal distribution table was set in advance using dynamic programming, which only took account of the stable operation regions and avoided the cavitation and vibration areas for the security and stability of units. The proposed method is applied to the Three Gorges Hydroelectric plant. Compared with other methods under different water heads, this method shows optimized result under the premise of both calculation speed and stability.

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Metadaten
Titel
Application Research of the Improved Overall Temporal and Spatial Economic Operation Model Based on Information Entropy in Large-Scale Hydropower Station
verfasst von
Liu Yang
Kan Yang
Lei Chen
Publikationsdatum
26.02.2018
Verlag
Springer Netherlands
Erschienen in
Water Resources Management / Ausgabe 7/2018
Print ISSN: 0920-4741
Elektronische ISSN: 1573-1650
DOI
https://doi.org/10.1007/s11269-018-1938-0

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