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Research Publications (Engineering and Built Environment)

Permanent URI for this collectionhttp://ir-dev.dut.ac.za/handle/10321/215

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Author: search.filters.author.Olofintoye, Oluwatosin OnaopemipoHas files: Yes

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    Maximization of hydropower generation from Hazelmere Dam in South Africa
    (Business Perspectives, 2015) Mashiyane, Thulasizwe Innocent; Olofintoye, Oluwatosin Onaopemipo; Adeyemo, Josiah
    Harnessing more energy from existing water sources within the frontier of the country is germane in capacitating the South African Government’s commitment to reduction of the country’s greenhouse gas emissions and transition to a low-carbon economy while meeting a national target of 3 725 megawatts by 2030. This study aims to determine the amount of energy that can be generated from Hazelmere Dam on the Mdloti River, South Africa. Behavioral analyses of the Hazelmere reservoir were performed using plausible scenarios. Feasible alternative reservoir operation models were formulated and investigated to determine the best operating policy and power system configuration. The optimi-zation models were formulated to maximize hydropower generation while keeping within the limits of existing irriga-tion demands. Differential evolution algorithm was employed to search feasible solution space for the best policy. Findings suggest that if the water resource in the dam is properly managed, about 558.54 MWh of annual energy may be generated from the reservoir under medium flow condition without system failure.
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    Evaluation of combined Pareto multiobjective differential evolution on tuneable problems
    (SIMM, 2014) Adeyemo, Josiah; Olofintoye, Oluwatosin Onaopemipo
    Many optimization problems in engineering involve the satisfaction of multiple objectives within the limits of certain constraints. Methods of evolutionary multi-objective algorithms (EMOAs) have been proposed and applied to solve such problems. Recently, a combined Pareto multi-objective differential evolution (CPMDE) algorithm was proposed. The algorithm combines Pareto selection procedures for multi-objective differential evolution to implement a novel selection scheme. The ability of CPMDE in solving unconstrained, constrained and real optimization problems was demonstrated and competitive results obtained from the application of CPMDE suggest that it is a good alternative for solving multi-objective optimization problems. In this work, CPMDE is further tested using tuneable multi-objective test problems and applied to solve a real world engineering design problem. Results obtained herein further corroborate the efficacy of CPMDE in multi-objective optimization.