E3S Web Conf.
Volume 167, 20202020 11th International Conference on Environmental Science and Development (ICESD 2020)
|Number of page(s)||7|
|Published online||24 April 2020|
- D. Kirschen, G. Strbac, Fundamentals of Power System Economics, University of Manchester Institute of Science and Technology, John Wiley & Sons, UK, 2004. [Google Scholar]
- (Chapter 1-3) S. Stoft, Power System Economics (Designing Markets for Electricity), Part 1, IEEE Press & Wiley, New York, NY, 2002. [Google Scholar]
- Jamasb T., Thakur T., Bag B., “Smart electricity distribution networks, business models, and application for developing countries”, 2018, Energy Policy 114, 22–29. [Google Scholar]
- Youfei Liu, Felix F. Wu. “Generator bidding in oligopolistic electricity markets using optimal control: fundamentals and application”. IEEE Transactions on Power Systems, vol. 21, no. 3, august 2006, pp 1050-61. [CrossRef] [Google Scholar]
- Shahdehpour M, Almoush M. Restructured Electrical Power Systems Operation, Trading and Volatility. Marcel Dekker, Inc.; 2001. [Google Scholar]
- David AK, Wen F. Strategic bidding in competitive electricity markets: a literature survey. In: Proceedings of IEEE power engineering society summer meeting, vol. 4; 2000. p. 2168–73. [Google Scholar]
- A.K. David, F. Wen, Market power in electricity supply, IEEE Trans. Energy Convers. 16 (No. 4) (2001) 352-360. [CrossRef] [Google Scholar]
- Kian Ashkan R, Cruz Jose B, Thomas Robert J. Bidding strategies in oligopolistic dynamic electricity double-sided auctions. IEEE Trans Power Syst 2005; 20(1):50–8. [Google Scholar]
- Srivastava Anurag K, Kamalasadan Sukumar, Patel Daxa, Sankar Sandhya, AlOlimat Khalid S. Electricity markets: an overview and comparative study. Int J Energy Sec Manage 2011; 5(2):169–200. [CrossRef] [Google Scholar]
- Shahidehpour M, Yamin H, Li Z. Market Operations in Electric Power Systems: Forecasting, Scheduling, and Risk Management. New York: IEEE Wiley-Inter Science; 2002. [Google Scholar]
- Gong Li, Jing Shi, Xiuli Qub, “Modeling methods for GenCo bidding strategy optimization in the liberalized electricity spot market A state-of-the-art review” Energy 36 (2011) 4686-4700. [CrossRef] [Google Scholar]
- S. Mathur, A. Arya, M. Dubey, “Optimal bidding strategy for price takers and customers in a competitive electricity market”, Cogent Engineering Taylor Francis online(2017) vol. 1 issue 4, pp. 1-15. [Google Scholar]
- S. Mathur, A. Arya, M. Dubey, “Impact of emission trading on optimal bidding of price takers in a competitive energy market” Advances in Intelligent System and computing, Springer (2018) Vol. 741, pp. 171-180. [CrossRef] [Google Scholar]
- J. Kennedy, R. Eberhart, Particle swarm optimization, in: Proc. IEEE Int. Conf. Neural Networks, IV, Perth, Australia, 1995, pp. 1942-1948. [Google Scholar]
- Kumar A., Pant S., and Singh S.B., “Reliability Optimization of Complex System by Using Cuckoos Search algorithm” Mathematical Concepts and Applications in Mechanical Engineering and Mechatronics, IGI Global, 2016, 95-112 [Google Scholar]
- Pant S and Singh SB, “Particle swarm optimization to reliability optimization in complex system” In: IEEE international conference on quality and reliability, Bangkok, Thailand, Sept 14–17, 2011, pp 211–215. [Google Scholar]
- Shi and R. Eberhart, “A modified particle swarm optimizer, ” In Proc. IEEE World Congr. Comput. Intell., 1998, pp. 69–73. [Google Scholar]
- I. J. Raglend; N. P. Padhy, “Solutions to Practical Unit Commitment Problems with Operational, Power Flow and Environmental Constraints” IEEE Power Engineering Society General Meeting, 2006, pp. 1-8. [Google Scholar]
- S. Soleymani, Bidding strategy of generation companies using PSO combined with SA method in the pay as bid markets, Int. J. Electr. Power Energy Syst. 33 (2011) 1272-1278. [CrossRef] [Google Scholar]
- A. Azadeh, S.F. Ghaderi, B. PourvalikhanNokhandan, M. Sheikhalishahi, A new genetic algorithm approach for optimizing bidding strategy viewpoint of profit maximization of a generation company, Expert Syst. Appl. 39 (No. 1) (2012) 1565-1574. [Google Scholar]
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