Optimized Electric Power Generation Expansion Planning Using Decomposition Technique

Ngang Bassey Ngang, Bakare Kazeem, Ude Kinsley Okechukwu and Akaninyene Michael Joshua
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Ngang Bassey Ngang: Enugu State University of Science and Technology (ESUT), Enugu, Nigeria.
Bakare Kazeem: Enugu State University of Science and Technology (ESUT), Enugu, Nigeria.
Ude Kinsley Okechukwu: Enugu State University of Science and Technology (ESUT), Enugu, Nigeria
Akaninyene Michael Joshua: Enugu State University of Science and Technology (ESUT), Enugu, Nigeria

International Journal of Science and Business, 2021, vol. 5, issue 6, 94-116

Abstract: The decrease in power supply in the country has caused economic problems to small scale industries; one major problem attributed to this is inadequate planning mechanism that will forecast the required amount of power that will be needed to feed the entire population .Power system engineers had used all the conventional methods improve power supply. This issue of not having adequate forecasting mechanism in power generation network that will adequately serve the entire public is overcome by optimized electric power generation expansion planning using decomposition technique, It is achieve in this manner, characterizing the existing output power capacities of the electric power generating plants under study, Forecasting of the load demand of the power generating plants under study, exterminating of percentage power generating capacity contribution and power generating capacity projected contribution to the National Grid, developing a Model for Decomposition Technique, Integrating SIMULINK Model in the Decomposition Technique. The results obtained are in 2009 the residential power demand by numerous consumers is 8075.00MW and the power demand in ten years is 10214.03MW and the commercial power demand is 2009 is 3865.50MW while the forecast power demand by this sector in ten years’ time when decomposition technique is introduced in the system is 5481.65MW.With these results, it shows that the power demand in ten years’ time is 41.9% generation power expansion.

Keywords: optimized; electric power generation; power planning; cost saving; decomposition technique (search for similar items in EconPapers)
Date: 2021
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