Economic Load Dispatch of Egbin and Okpai Plants using PSO and GA: A Comparative Study with Quadratic Cost Function

Abstract

In this research, the Hybrid Optimization Technique (HOT) is applied to solve the economic dispatch problem using the Egbin and Okpai power plants in Nigeria. Power flow analysis using Newton Raphson was carried out using the Power System Analysis Toolbox PSAT. The voltages and phase angles obtained from each simulation was used to compute the loss coefficient through the formation of B-Matrix. The B-Matrix developed, Generators Operating Limits (GOL), Quadratic Cost Function (QCF) of the generating units in addition with the HOT namely; Particle Swam Optimization (PSO) and Genetic Algorithm (GA) were used to set up the optimum dispatch problem programmed in the Matlab 2020b environment. Results for the Economic Dispatch ED for Egbin Plant shows an average transmission loss and fuel cost of 7.31MW and ₦35,104.18 were obtained using PSO while that of GA was 8.74MW and ₦161, 840 respectively. For Okpai Plant, an average transmission loss and fuel cost of 9.44 MW and ₦367, 394.92 was obtained using PSO while that of GA gave 11.74 MW and ₦49,101,333.33. The summarised results showed that Egbin Plant with its higher power rating has lowest loss transmission loss and fuel cost while Okpai Plant has the highest fuel cost. The summarized result is an indication that Egbin Plant is more efficiently operated at dispatch level when compared to other plants. Also, from the HOT, it was observed that the PSO out performed GA ED related problems.

Keywords

• ELD
• GA
• Power Plant
• PSO

References

1. [1] A.E Airoboman, P.O Airoboman and F.A Airoboman “Clean Energy Technology for the Mitigation of Climate Change: African Traditional Myth”. In: Leal Filho W., Ogugu N., Adelake L., Ayal D., da Silva I. (eds) African Handbook of Climate Change Adaptation. Springer, Cham.
2. [2] A.E. Airoboman, A.O. Salau, and M. Chhabra, “Review of the Performance of the Power Sector in Some Selected African Countries”, IEEE Nigercon, 4th International Conference, 17th -19th May, Nile University Abuja, pp. 1-5, 2022.
3. [3] A.E Airoboman, “Reliability Assessment of Power System Network: A Detailed Review”, International Journal of Engineering Technologies, Vol. 7, Issue 4, pp. 90-103
4. [4]. D. Bisen, H. M. Dubey, M. Pandit and B. K. Panigrahi, “Solution of Large Scale Economic Load Dispatch Problem using Quadratic Programming and GAMS: A Comparative Analysis” Journal of Information and Computing Science, Vol. 7, Issue 3, pp. 200-211, 2012.
5. [5]. C. Niannian, T. T. N. Nguyen and J. Mitra, “Economic Dispatch in Micro grids Using Multi-agent System”, North American Power Symposium, pp. 1-5, 2012.
6. [6] H. M. Dubey, M. Pandit, B. K. Panigrahi and M. Udgir M., “Economic Load Dispatch by Hybrid Swarm Intelligence Based Gravitational Search Algorithm”, International Journal Intelligent Systems and Applications, Vol. 5, issue 8, pp. 21-32, 2013.
7. [7]. G. K. Babu and R. K. Samala, “Network and Generator Constrained Economic Dispatch Using Real and Binary Coded Genetic Algorithms”, International Journal of Engineering Research and Applications, Vol. 3, Issue 5, pp. 1185-1192, 2013.
8. [8]. V. Karthikeyan, S. Senthilkumar and V. J. Vijayalakshmi, “A New Approach to the Solution of Economic Dispatch Using Particle Swarm Optimization with Simulated Annealing”, International Journal on Computational Sciences and Applications, vol. 3, issue 3, pp. 37-49, 2013.

9. [9] O. O. Awodiji, G. A. Bakare, U. O. Aliyu, “Short-Term Economic Load Dispatch of Nigerian Thermal Power Plants Based on Differential Evolution Approach”, International Journal of Scientific & Engineering Research, Vol. 5, Issue 3, pp. 589-595, 2014.
10. [10]. K. Balamurugan, R. Muralisachithnndam, and S.R. Krishnan, “Differential Evolution Based Solution for Combined Economic and Emission Power Dispatch with Valve Loading Effect”, International Journal on Electrical Engineering and Informatics, vol. 6, issue 1, pp. 74-92, 2014.
11. [11] E. Buraimoh, T. O. Ejidokun and O. J. Ayamolowo, “Optimization of an expanded Nigeria electricity grid system economic using load dispatch”, ABUAD Journal of Engineering Research and Development, Vol. 1, Issue 1, pp. 61-66. 2017.
12. [12] C. Amos, S. Y. Musa and I. T. Thuku, “Particle Swarm Optimization based economic load dispatch of Nigeria hydrothermal considering hydro cost functions”, International Journal of Engineering Science and Computing, pp. 14690-14696, 2017.
13. [13]. M.N. Nwohu, and OsaremwindaOsarobo Paul, “Evaluation of Economic Load Dispatch Problem in Power Generating Stations by the Use of Ant Colony Search Algorithms”, International Journal of Research Studies in Electrical and Electronics Engineering, Volume3, Issue 1, pp. 20-29, 2017.
14. [14] R. Al-Nahhal, A. F., Naeim and Y. G., Hegazy, “Economic Load Dispatch Problem using Particle Swarm Optimization Technique Considering Wind Power Penetration”, IEEE, pp. 1-6, 2019.
15. [15] A. O. Odesola and T. O. Ale, “Overview Of Energy t Jebba Hydropower Station (2009-2016)”,Nigerian Journal of Technology, Vol. 38, No. 3, pp. 744 – 749, 2019 System considering Valve-Point Loading Effect through Interior point method”, ICEPT, pp. 1-9, 2022.
16. [16] M. Okafor and I. Adewale, “Electricity Sector Assessment in Nigeria: The Post-Liberalization Era.” Cogent Engineering, 9(1).