Journal of Guangdong University of Technology ›› 2017, Vol. 34 ›› Issue (01): 50-54,64.doi: 10.12052/gdutxb.160087

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Unit Commitment Optimization Based on Chance-constrained Programming in Wind Power Integrated System

Chen Jing-hua1, Liang Li-li1, Ding Lin-jun1, Zhou Jun2, Liu Guo-xiang3   

  1. 1. School of Automation, Guangdong University of Technology, Guangzhou, 510006, Guangdong Province, China;
    2. State Grid Pingxiang City Anyuan District Electric Power Supply Branch, Pingxiang, 337000, Jiangxi Province, China;
    3. State Grid Power Jiangxi Pingxiang Supply Branch Company, Pingxiang, 337000, Jiangxi Province, China
  • Received:2016-06-20 Online:2017-01-09 Published:2017-01-09

Abstract:

Because of the random nature of wind power output, a unit commitment optimization model with wind farm based on chance-constrained programming is proposed. The constraints of both power system and generator are considered. Chaos Discrete Particle Swarm Optimization algorithm (CDPSO) is used to arrange thermal unit commitment startup and shutdown and cultural chaos particle swarm optimization algorithm (CCPSO) is proposed to solve economic load dispatch. Based on it, Multi-objective optimization unit commitment optimization problem in wind power integrated system under the energy saving and lower emission is considered. The Monte Carlo stochastic simulation techniques verified opportunity constraints and the superiority of opportunities constraints coordination programs profit and risk under different confidence level are analyzed. It provides a new way of thinking to coordinating profit, risk and environment benefits. A system with one wind power farm and 10 coal-fired plants was taken as a study example and the results show that the model is correct.

Key words: energy conservation, unit commitment optimization, chaos cultural particle swarm optimization, chance-constrained programming

CLC Number: 

  • TM731

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