A Computationally Intelligent Power Transmission Expansion Strategy in a Deregulated Energy System


This paper aims to simulate a computationally intelligent electrical power transmission expansion system and study the factors affecting power transmission expansion in a deregulated energy system to improve on the current economic conditions. The main problem facing most power system transmission is the failure to actually forecast the load expansion accurately this leads to failure in the transmission expansion design. a hybrid algorithm for the ac/dc transmission expansion planning (HTEP) and  multi algebraic formulation of the stochastic TEP model in a multi-stage planning framework will be used to analyze the  transmission expansion system, optimization problem will considers a weighted  sum of multiple objectives including cost of operation and maintenance, emission, load shedding and line investments, simulation method would consider random outages of generating units and ac/dc transmission lines as well as load forecast .The independent system operator would utilize the proposed method to select the optimal set of ac/dc transmission lines for satisfying TEP criteria. The proposed set of dc transmission system may use either current source converters or voltage source converters. The proposed algorithms are simulated on IEEE 24-bus reliability test system (RTS) and Gerner’s 6 bus system   to compare optimal plans between the original and equivalent system. Further assumptions and adjustments are searched and tested to get more accurate optimal plans. results obtained showed that the hybrid model was capable of handling future generation and load patterns in deregulated, unbundled, and competitive electricity system. the results of the study showed the hybrid model was tested in the Gerner’s 6 bus system and the expansion model after a load forecast. On the IEEE 24-bus system showed that the hybrid expansion model was able to take care of the load forecast for future expansion.

  1. A. Jager-Waldau, and H. Ossenbrink, “Progress of Electricity from Biomass, Wind and Photovoltaics in the European Union,†Renewable and Sustainable Energy Review, vol. 8, no. 2, pp. 157-182, 2004.  |   Google Scholar
  2. Energy Commission of Nigeria. Nigeria Energy Demand and Power Planning Study for the Period 2000-2030. Technical Report no. ECN/EPA/04/01 on Energy Masterplan Development, Abuja, 2004.  |   Google Scholar
  3. Energy Commission of Nigeria. Renewable Energy Masterplan. Executive Report, Abuja, 2005.  |   Google Scholar
  4. The Grid Code for the Nigerian Electricity Transmission System, Version 1. Grid Code, Abuja: Nigerian Electricity Regulatory Commission, 2010.  |   Google Scholar
  5. N. Newman. “Power system investment planning using stochastic dual dynamic programming.†PhD Thesis, University of Canterbury, New Zealand, 2008.  |   Google Scholar
  6. G.C. Oliveria, A. P. Costa and S. Binato, “Large Scale Transmission Network Planning using Optimization and Heuristic Techniques,†IEEE Trans, on Power System, vol. 10, no. 4, pp. 1828-1834, 1995.  |   Google Scholar
  7. G. A. Orfanos, P. S. Georgilakis and N. D. Hatziargyriou, “Transmission Expansion Planning in Deregulated Electricity Markets for Increased Wind Power Penetration,†European Market Conf., 2001.  |   Google Scholar
  8. L. U. Miao, D. Z. Yang and R. S. T. Kuma, “A Framework for Transmission Planning in a Competitive Electricity Market,†IEEE/ PES, Transmission and Distribution Conference Exhibition, Asia and Pacific Dalian China, 2005.  |   Google Scholar
  9. M. O. Buygi, H. M. Shanechi, G. Balzer, and M. Shahidehpour, "Transmission Planning Approaches in Restructured Power Systems," IEEE Powertech, June 2006.  |   Google Scholar
  10. A. H, Escobar, R. A. Gallego, and R. Romero, “Multistage and Coordinated Planning of the Expansion of Transmission Systems," IEEE Transactions on Power Systems, vol.19, no.2, pp. 735-744, 2004.  |   Google Scholar
  11. F. Ibitoye and A. Adenikinju, “Future Demand for Electricity in Nigeria,†Applied Energy, vol. 84, pp. 492-504, 2007.  |   Google Scholar
  12. J. Ignacio, J. Perez-Arriga and L. Pedro, “Market vs Regulation, a Role for Indicative Energy Planning,†2008.  |   Google Scholar
  13. M. R. Hesamzadeh, N. Hosseinzadeh and P. J. Wolfs, “Economic assessment of transmission expansion project in competitive market: an analytical review,†43rd Universities Power Engineering Conference International, 1-4 Sept. 2008, Padova, Italy.  |   Google Scholar
  14. E. Bueren, E. H. Klijn, and J. Koppenjan, “Dealing with Wicked Problems in Networks: Analyzing an Environmental Debate from a Network Perspective," Journal of Public Administration Research and Theory, vol. 13, no. 2, pp.193-212, 2003.  |   Google Scholar
  15. A. M. Geoffrion, “Generalized Benders Decomposition,†Journal of Optimization Theory Applications, vol. 10, pp. 237-260, 1972.  |   Google Scholar
  16. A. J. Conejo, E. Castillo, and R. Minquez, Decomposition Techniques in Mathematical Programming: Engineering and Science Applications; Berlin Heidelberg: Springer, ISBN 3-540-27685-8, 2006.  |   Google Scholar
  17. A. O. Ekwue, “Investigations of the transmission system expansion problem,†International Journal of Electrical Power and Energy Systems, vol. 6, no. 3, pp. 139-142, 1984.  |   Google Scholar
  18. A. M. Costa, “A survey on benders decomposition applied to fixed-charge network design problems,†Computer and Operations Research, vol. 32, pp.1429-1450, 2005.  |   Google Scholar
  19. H. M. Chebbo and M.R. Irving, “Application of Genetic Algorithms to Transmission Planning,†2nd International Conference on Genetic Algorithms in Engineering Systems: Innovations and  |   Google Scholar
  20. Applications, 2-4 Sept. 1997, Glasgow, UK.  |   Google Scholar
  21. R. D. Dunlop, R Gutman, and P.P Marchenko. "Analytical Development of Loadability Characteristics for EHV and UHV Transmission Lines," IEEE Transactions on Power Apparatus and Systems, vol. PAS-98, No. 2, 1979.  |   Google Scholar
  22. S. Cerisola, and A. Ramos, “Benders Decomposition for Mixed Integer Hydrothermal Problems by Lagrangean Relaxation,†IEEE 14th Power System Computation Conference, Seville, 2002.  |   Google Scholar
  23. Y. P. Dusonchet and A. EL-Abiad, “Transmission Planning using Discrete Dynamic Optimization. IEEE Transactions on Power Apparatus and Systems, vol. PAS-92, no. 4, 1973  |   Google Scholar
  24. L. L. Garver, "Transmission Network Estimation using Linear Programming," IEEE Transactions on Power Analysis System, vol. PAS-89, no. 7, pp.1688–1687, 1970.  |   Google Scholar
  25. L. G. Bayona, and I. T. Perez-Arriga, “A Heuristic Model for Long Term Transmission Expansion Planning,†IEEE Transmissions Power System Planning, vol. 9, pp. 1886-1894, 1994.  |   Google Scholar


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Ahiakwo, C.O., Orike, S. and Obioma, A.O. 2018. A Computationally Intelligent Power Transmission Expansion Strategy in a Deregulated Energy System. European Journal of Electrical Engineering and Computer Science. 2, 4 (May 2018). DOI:https://doi.org/10.24018/ejece.2018.2.4.22.

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 Christopher O. Ahiakwo
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 Sunny Orike
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 Ahuruezemma O. Obioma
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