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Optimal Determination for Cost of Electric Power Generation and Plant Capacity of Utilities

Ighravwe, D.E and Oke, Sunday Ayoola (2017) Optimal Determination for Cost of Electric Power Generation and Plant Capacity of Utilities. Walailak Journal of Science & Technology, 14 (6). pp. 463-484.

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Optimisation of power generation and plant capacity are of primary significance for the improvement of power supplies, cost decisions and economics. This paper develops a robust predictive model for electric power generation and capacity utilisation and integrates the output from predictive models into a multi-objective model. The optimal solution was determined after comparing the performance of a Real Coding Genetic Algorithm (RCGA), Particle Swarm Optimisation (PSO) and Big- Bang Big-Crunch Algorithm (BB-BC). Testing of the proposed model was carried out using data from a Nigerian electric power generation plant with a capacity of about 5 million Megawatt Hours (MWH) to test the presented methodology. Our findings indicate that the Auto-Regressive Integrated Moving average (ARIMA) model adequately predicts the power generation variables and compares favorably with literature results. The RCGA performed better than the BB-BC and PSO algorithms in terms of the quality of solutions for the proposed model. The outcome of this study suggests that computational complexity can be reduced in the evaluation of variables, yet producing a practical, simple and robust model.

Item Type: Article
Uncontrolled Keywords: ARIMA, robust regression, electricity, meta-heuristics, fuzzy logic
Subjects: T Technology > T Technology (General)
T Technology > TJ Mechanical engineering and machinery
Divisions: Faculty of Engineering, Science and Mathematics > School of Engineering Sciences
Depositing User: Mrs Patricia Nwokealisi
Date Deposited: 12 May 2017 09:51
Last Modified: 12 May 2017 09:51

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