Forecasting River Water Levels Influenced by Hydropower Plant Daily Operations using Artificial Neural Networks
Конференцијски прилог (Објављена верзија)
Метаподаци
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Multipurpose water systems are used to deal with multiple objectives related to the usage of water for daily human activities. These activities are often conflicted which creates a challenging water management task. To provide reliable water resources management decision support tools for successful forecasting of hydraulic data (river flows and water levels) are essential. This research presents an approach for forecasting river water levels influenced by hydropower plant operations using artificial neural networks. This approach estimates hourly water level fluctuations at the control location using the water levels and hydropower plant discharge data as input. This tool can be used for fast assessment of different hydropower plant operation plans and help in choosing the optimal one. This water level forecasting procedure is applied and tested on the Iron Gate water system, placed on the Danube River, to deal with multiple objectives in water system management (hydropower production..., flood protection, and inland navigation) and shows promising results.
Кључне речи:
River water level / Artificial Neural Networks / Danube River / Iron GateИзвор:
2nd Serbian International Conference on Applied Artificial Intelligence (SICAAI), Kragujevac, Serbia, May 19-20, 2023, 2023Колекције
Институција/група
GraFarTY - CONF AU - Milašinović, Miloš AU - Marjanović, Dušan AU - Prodanović, Dušan AU - Milivojević, Nikola PY - 2023 UR - https://grafar.grf.bg.ac.rs/handle/123456789/3120 AB - Multipurpose water systems are used to deal with multiple objectives related to the usage of water for daily human activities. These activities are often conflicted which creates a challenging water management task. To provide reliable water resources management decision support tools for successful forecasting of hydraulic data (river flows and water levels) are essential. This research presents an approach for forecasting river water levels influenced by hydropower plant operations using artificial neural networks. This approach estimates hourly water level fluctuations at the control location using the water levels and hydropower plant discharge data as input. This tool can be used for fast assessment of different hydropower plant operation plans and help in choosing the optimal one. This water level forecasting procedure is applied and tested on the Iron Gate water system, placed on the Danube River, to deal with multiple objectives in water system management (hydropower production, flood protection, and inland navigation) and shows promising results. C3 - 2nd Serbian International Conference on Applied Artificial Intelligence (SICAAI), Kragujevac, Serbia, May 19-20, 2023 T1 - Forecasting River Water Levels Influenced by Hydropower Plant Daily Operations using Artificial Neural Networks UR - https://hdl.handle.net/21.15107/rcub_grafar_3120 ER -
@conference{ author = "Milašinović, Miloš and Marjanović, Dušan and Prodanović, Dušan and Milivojević, Nikola", year = "2023", abstract = "Multipurpose water systems are used to deal with multiple objectives related to the usage of water for daily human activities. These activities are often conflicted which creates a challenging water management task. To provide reliable water resources management decision support tools for successful forecasting of hydraulic data (river flows and water levels) are essential. This research presents an approach for forecasting river water levels influenced by hydropower plant operations using artificial neural networks. This approach estimates hourly water level fluctuations at the control location using the water levels and hydropower plant discharge data as input. This tool can be used for fast assessment of different hydropower plant operation plans and help in choosing the optimal one. This water level forecasting procedure is applied and tested on the Iron Gate water system, placed on the Danube River, to deal with multiple objectives in water system management (hydropower production, flood protection, and inland navigation) and shows promising results.", journal = "2nd Serbian International Conference on Applied Artificial Intelligence (SICAAI), Kragujevac, Serbia, May 19-20, 2023", title = "Forecasting River Water Levels Influenced by Hydropower Plant Daily Operations using Artificial Neural Networks", url = "https://hdl.handle.net/21.15107/rcub_grafar_3120" }
Milašinović, M., Marjanović, D., Prodanović, D.,& Milivojević, N.. (2023). Forecasting River Water Levels Influenced by Hydropower Plant Daily Operations using Artificial Neural Networks. in 2nd Serbian International Conference on Applied Artificial Intelligence (SICAAI), Kragujevac, Serbia, May 19-20, 2023. https://hdl.handle.net/21.15107/rcub_grafar_3120
Milašinović M, Marjanović D, Prodanović D, Milivojević N. Forecasting River Water Levels Influenced by Hydropower Plant Daily Operations using Artificial Neural Networks. in 2nd Serbian International Conference on Applied Artificial Intelligence (SICAAI), Kragujevac, Serbia, May 19-20, 2023. 2023;. https://hdl.handle.net/21.15107/rcub_grafar_3120 .
Milašinović, Miloš, Marjanović, Dušan, Prodanović, Dušan, Milivojević, Nikola, "Forecasting River Water Levels Influenced by Hydropower Plant Daily Operations using Artificial Neural Networks" in 2nd Serbian International Conference on Applied Artificial Intelligence (SICAAI), Kragujevac, Serbia, May 19-20, 2023 (2023), https://hdl.handle.net/21.15107/rcub_grafar_3120 .