Comparative Assessment of Thermal Power Systems Performance Under Uncertainty


  •   Anthony Kpegele Le-ol

  •   Sidum Adumene

  •   Kenneth Israel


This work presents a comparative analysis of the thermo-economic performance of a simple, retrofitted and built-in combined cycle power plants within the Delta. The data were obtained from a 25MW gas turbine plant-based engine, retrofitted and MATLAB software was used to model the thermodynamic performance of the plants. The economic prediction of the plants was done using a developed net present value(NPV), internal rate of return (IRR), cost of investment (COR) and payback period (PBP).  The economic concept for plants performance was analysed under uncertainty constraints of energy need, operating conditions, energy cost and energy supply variability. Three plants configuration; simple gas turbine (SGT), retrofitted combined cycle (RCC) and Built-in combined cycle (BCC) was analysed based on these economic performance indicators. The three configurations show a positive NPV, PBP and IRR, with the BCC showing the optimum return on investment. Although the RCC show minimum initial cost on investment compare to BCC, the BCC demonstrates greater overall return with an NPV of $30,755,454.18, IRR of 17.1% and PBP of 6.3years for the period of 20years. The analysis shows cash flow of 34.1% and 52.6% for the RCC and BCC respectively. The result also showed that the plant performs better at a lower ambient temperature and higher relative humidity with a higher return on investment. This research provides great insight into the thermo-economic analysis, and benefits of combined cycle power plant and will aid energy system investors on the choice of the power plant for power generation in the Niger Delta.

Keywords: Net-Present-Value, Internal Rate of Return, Payback Period, Simple-Gas-Turbine, Combined-Cycle


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How to Cite
Kpegele Le-ol, A., Adumene, S. and Israel, K. 2018. Comparative Assessment of Thermal Power Systems Performance Under Uncertainty. European Journal of Engineering Research and Science. 3, 7 (Jul. 2018), 50-57. DOI: