4.7 Article

Low-carbon power dispatch with wind power based on carbon trading mechanism

Journal

ENERGY
Volume 170, Issue -, Pages 250-260

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2018.12.126

Keywords

Low-carbon; Power dispatch; Wind power; Carbon trading

Funding

  1. National Natural Science Foundation of China [71603135, 71804190, 71704095, 71573121, 71573186]
  2. National Science Fund for Distinguished Young Scholars [71625005]
  3. China Postdoctoral Science Foundation [2017M621743]
  4. MOE (Ministry of Education in China) Project of Humanities and Social Sciences [15YJC630048, 18YJC630043]

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Low-carbon power dispatching with wind power has been attracting increasing attention recently, whereas it also encounters some difficulties under carbon trading mechanism, such as the resistance to carbon emission reduction, the fairness of carbon trading, and the disturbance of wind power uncertainty. For harmonizing these contradictions, this paper presents a stochastic dynamic economic dispatch model focusing on wind power uncertainty and carbon emission rights simultaneously, which tries to minimize total electrical energy costs under uncertainty, and to meet the specific requirement of carbon emission reductions. Moreover, several traditional allocation methods for initial carbon emission rights emphasizing the equality are introduced, and the uncertainty characterizations of wind power are discussed through the scenario-generation technique. The simulation results eventually demonstrate that the operating cost for non-cooperative mode cannot be optimized as the ratio of carbon emission reductions rises; carbon trading mechanism is beneficial for lower cost under the pressure of carbon emission reduction; carbon price ranges that suit both carbon trading parties could be deduced. Synthesizing wind power uncertainty and carbon emission rights, this study is helpful for allocating the load demand of wind power integrated system to each generating unit more scientifically and reasonably based on carbon trading mechanism. (C) 2018 Elsevier Ltd. All rights reserved.

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