Abstract
The operation efficiency of the power station mainly depends on power generation. Therefore, under the constraints of water level, water amount, and output of hydropower station, generation flow in each period can be reasonably controlled according to the initial operating conditions of reservoir and inflow runoff, maximize the power generation of cascade power station within the operation cycle. Grey wolf algorithm (GWO) is easy to implement, simple in structure, requires few parameters to be changed, and has a simple operating principle. The gray wolf algorithm’s solution process simulated wolves’ hunting behavior, and the prey was regarded as the optimal global solution. All the candidate solutions were regarded as a gray wolf population. As shown from the above results, the GWOs algorithm has a more vital exploration ability and development ability to optimize single-peak and multi-peak functions better than the other two algorithms.
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Chen, RF. et al. (2021). Optimal Operation of Reservoir Power Generation Based on Improved Grey Wolf Algorithm. In: Hassanien, AE., Chang, KC., Mincong, T. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2021. Advances in Intelligent Systems and Computing, vol 1339. Springer, Cham. https://doi.org/10.1007/978-3-030-69717-4_92
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DOI: https://doi.org/10.1007/978-3-030-69717-4_92
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