Abstract
This study suggests a solution to the optimal reservoir operation's typical nonlinear optimization problem by an improved Bat algorithm (IBA). The reservoir operations issue is modeled as the objective function according to the runoff data and comprehensive utilization requirements dealing with IBA’s optimization method. The IBA is implemented by introducing adaptive weight into the bat algorithm (BA) for updating mechanism. The bat's position is adjusted dynamically according to the actual situation to improve the bat's searching performance. The mechanism Tabu search (TS) diversity is also used to enhance the bat population diversity for preventing the situation that circuitous search does not leap out of the local optimum. The simulation results show that IBA can obtain a better reservoir operation scheme with higher operating efficiency than other algorithms, which offers a new way to maximize reservoir power generation operation.
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Dao, TK., Chang, KC., Chu, KC., Nguyen, TTT., Ngo, TG., Nguyen, TT. (2021). A Solution for Cascade Hydropower Station Reservoirs Optimal Operation Based on Improved Bat 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_91
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