Optimization-based reliability of a multipurpose reservoir by Genetic Algorithms: Jebba Hydropower Dam, Nigeria. Issue 1 (1st January 2018)

• Record Type: Journal Article
• Authors: Olukanni, D.O.; Adejumo, T.A.; Salami, A.W.; Adedeji, A.A.
• Editors: Alavi, Amir H.
• Is Part Of: Cogent engineering. Volume 5:Issue 1(2018)
• Publication Date: 2018-01-01
• Subjects: reservoir operation -- Jebba Hydropower Dam -- flood management -- optimization -- Genetic Algorithm -- LINGO; Engineering -- Periodicals; Technology -- Periodicals; Engineering; Technology; Periodicals; 620
• DOI: 10.1080/23311916.2018.1438740
• Languages: English
• ISSNs: 2331-1916

Abstract

Abstract: This study is focused on the application of Genetic Algorithm (GA) as an effective tool for modeling the operation of a multi-purpose reservoir with specific emphasis on Jebba Hydropower Dam, Nigeria. The specific objectives are to study the reservoir operation rule; model the reservoir parameters such as inflow, elevation, turbine release, generating head, energy generation, tailrace water level and plant coefficient. Available Data for 27-year period (1984–2011) was obtained from the Dam Station for statistical analysis. MATLab software for GA was used, and for comparison and check, another similar optimization software (LINGO) was utilized. The optimal solution obtained at operating performance of 50% reservoir inflow reliability has total annual energy generation of 42, 105.63MWH. GA for the total annual energy generation at operation performance of 95, 90 and 75% reservoir inflow reliability are 15, 964.48 MWH, 21, 009.53 MWH and 20, 798.58 MWH, respectively. The application of GA will lead to a more realistic and reliable optimal value for the improvement of hydroelectric power generation and flood management, which would guide decision makers in the hydropower sector.