Planning of DGs’ generated electricity energy in day-ahead markets, in order to get more profit, with GA and PSO algorithms

سال انتشار: 1393
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 699

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شناسه ملی سند علمی:

ETEC04_381

تاریخ نمایه سازی: 19 تیر 1394

چکیده مقاله:

Day-ahead market is one of the methods that Generation companies (GENCOS) use it for planning electricity market bidding strategies for days ahead. In this paper calculations of costs and profits are dynamically and separately in different periods called segments. Some of features of this paper are: uncertainty of GENCO’s offering price for selling power of all GENCOS and fuel’s price, maximum profitability of suggesting amount of energy for selling by GENCOS in the critical situation of competitive electricity market, including emission penalty and it’s influence on the costs and using exact relation between output power and fuel price. Genetic algorithm is used in this paper for suggesting the best amount of power for selling in each segment in order to gain the maximum available profit. Normal distribution is used for modeling the uncertainty of offering power of other GENCOS and fuel cost. Objective of the critical situation of market is when the all other rival GENCOS are at their most profitability.

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  • A. Azadeh, S.F. Gadri, B.Pourvalkhan Nokhandan, M. Sheikhalishahi, A new ...
  • X. Maa, F.Wena, Y.Nia, J.Liub, Towards the deveopment of risk ...
  • H.Kita, E.Tanaka, J.Hasegawa, Price forecasting in the day-ahead electricity market. ...
  • P. Atta virianpap, H.Kita, E.Tanaka, J.Hasegwa, New bidding strategy formulation ...
  • D.Rodrigo, Optimal operational strategies for a day-ahead electricity market in ...
  • and Computer Engineering College of Engineering Kansas State Unversity, Manhattan, ...
  • A.K. David, Competive bidding in electricity supply, Transmission and Distribution, ...
  • K. Bhattacharya, Strategc bidding and generation scheduling in electricity spot-markets, ...
  • G.B. Sheble, Agent based economics. In I. Marja, G. Francisco, ...
  • G. Xiong, T. Hashiyama, S. Okuma, An evolutionary computation for ...
  • S. Kouhi, F. Keinya, A new cascade NN based method ...
  • M. Shafie-khah, M. Parsa Moghaddam, M.K. Sheikh -El-Eslami, Price forecasting ...
  • P. Attaviryanup ap _ H. Kita, E.Tanaka, J. Hasegawa, New ...
  • A.D. Yacekaya, J. Vaenzuela, G. Dozier, Strategic bidding in electricity ...
  • A. Borghetti, S. Massuccob, F. Silvestro, Influence of feasibility constrains ...
  • L.Wang, C.W. Yu, F.S Wen, The impacts of differemt bidding ...
  • S. Fan, C. Mao, L. Chen, Next-day electricity-price forecasting using ...
  • J. Zhang, Bidding strategy based _ adaptive particle SWarm optimzation ...
  • N. Domingues, V.Mendes, Strategic Bids in Liberalized Markets, IEEE comference ...
  • Using Distributed Energy Resources, Department of Energy .Federal EnergyMana gement ...
  • R. Noroozian, H. Vahedi, Optimal Management of MicroGrid Using Bacterial ...
  • [Online]. Available :Www. cummispower. c om/Commerc iall/D iesel/S- 12 15.pdf." ...
  • H.A. Shayanfar, A. Salimiia Lahjji, J. Aghaei, A. Rabiee, Generation ...
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