Generation expansion planning

Generation expansion planning (also known as GEP) is finding an optimal solution for the planning problem in which the installation of new generation units satisfies both technical and financial limits.[1][2] GEP is a challenging problem because of the large scale, long-term and nonlinear nature of generation unit size.[3] Due to lack of information, companies have to solve this problem in a risky environment because the competition between generation companies for maximizing their benefit make them to conceal their strategies.[1] Under such an ambiguous condition, various nonlinear solutions have been proposed to solve this sophisticated problem.[4] These solutions are based on different strategies including: game theory[5], two-level game model[6], multi-agent system[1], genetic algorithm[4], particle swarm optimization[7] and so forth.

Software for generation expansion planning

GAP (Generation Analysis and Planning) Editor : Innovation Energie Développement Creation  : 1990 Last Version  : 4.1 (feb 2020) At the heart of the GAP lies a simulation and stochastic model of generation scenarios, calculating the technical and economic results of different hypotheses of expansion of the generation park. Various scenarios can be studied and compared in order to identify, through these sensitivity studies, the most technically and financially optimized options.

See also

References
  1. Kazemi, Hamidreza Moayed, Sahand Ghaseminejad Liasi, and Mohammadkazem Sheikh-El-Eslami. "Generation Expansion Planning Considering Investment Dynamic of Market Participants Using Multi-agent System." In 2018 Smart Grid Conference (SGC), pp. 1-6. IEEE, 2018.
  2. Chunyu Zhang; Ding, Yi; Ostergaard, Jacob; Wu, Qiuwei (2019-09-10). "Generation expansion planning considering integrating large-scale wind generation" (PDF). IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society. pp. 2051–2056. doi:10.1109/IECON.2013.6699447. ISBN 978-1-4799-0224-8.
  3. Jinxiang Zhu; Mo-Yuen Chow (2019-09-10). "A review of emerging techniques on generation expansion planning". IEEE Transactions on Power Systems. 12 (4): 1722–1728. doi:10.1109/59.627882.
  4. Park, Jong-Bae, Young-Moon Park, Jong-Ryul Won, and Kwang Y. Lee. "An improved genetic algorithm for generation expansion planning." IEEE Transactions on Power Systems 15, no. 3 (2000): 916-922.
  5. Y.Tohidi, L. Olmos, M. Rivier and M. Hesamzadeh, "Coordination of generation and transmission development through generation transmission charges - a game theoretical approach," IEEE Transactions on Power Systems, vol. 32, no. 2, pp. 1103 - 1114, 2017.
  6. V. Nanduri, T. K. Das and P. Rocha, "Generation capacity expansion in energy markets using a two-level game-theoretic model," IEEE trans. power sys, vol.24, no.3, pp.1165,1172, 2009.
  7. Kannan, S., S. Mary Raja Slochanal, P. Subbaraj, and Narayana Prasad Padhy. "Application of particle swarm optimization technique and its variants to generation expansion planning problem." Electric Power Systems Research 70, no. 3 (2004): 203-210.
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