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基于教与学算法的风力发电系统区间优化调度 被引量:2

Interval Optimal Dispatch of Wind Power System Based on Teaching and Learning Algorithms
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摘要 针对风电并网后环境效益提高的同时总发电成本相应增加的问题,在发电成本中引入弃风系数,并且定义弃风系数的有效区间,建立了风力发电系统区间优化调度模型,兼顾风功率的接纳能力和系统发电总成本。采用新型算法教与学算法对模型进行求解,并对教与学算法的不足之处进行改进,有效地解决了算法寻优后期容易陷入局部最优的问题。仿真实验结果表明,弃风成本的引入平衡了风电并网后的经济效益,同时验证了教与学算法求解此类问题的有效性。 Aiming at the problem that the environmental benefit of wind power Grid-connected increases while the total cost of power generation increases accordingly,the abandonment coefficient is introduced into the generation cost,and the effective interval of abandoned wind coefficient is defined,and the optimal dispatching model of wind power system is established,which takes into account the wind power acceptance capacity and the total cost of this system.A new algorithm for teaching and learning is used to solve the model,and the shortcomings of the teaching and learning algorithm are improved,which effectively solves the problem that the algorithm is easy to fall into local optimum in the later stage of optimization.
出处 《工业控制计算机》 2019年第12期34-36,共3页 Industrial Control Computer
关键词 风电并网 弃风系数 区间优化 教与学算法 总发电成本 wind power grid connection abandoned wind coefficient interval optimization teaching and learning algorithms total generation cost
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  • 1丁伟,袁家海,胡兆光.基于用户价格响应和满意度的峰谷分时电价决策模型[J].电力系统自动化,2005,29(20):10-14. 被引量:163
  • 2陈海焱,陈金富,段献忠.含风电场电力系统经济调度的模糊建模及优化算法[J].电力系统自动化,2006,30(2):22-26. 被引量:217
  • 3胡福年,汤玉东,邹云.需求侧实行峰谷分时电价策略的影响分析[J].电工技术学报,2007,22(4):168-174. 被引量:26
  • 4徐玖平,吴巍.多属性决策的理论与应用[M].北京:清华大学出版社,2006:45-48.
  • 5Hetzer J, Yu D, Bhattarai K. An economic dispatch model incorporating wind power[J]. 1EEE Transactions on Power Systems, 2005, 20(4): 2143-2145.
  • 6Basu M. Dynamic economic emission dispatch using evolutionary programming and fuzzy satisfying method[J]. International Journal of Emerging Electric Power Systems, 2007, 8(4): 1-15.
  • 7Pandit N, Tripathi A, Tapaswi S, et al. An improved bacterial foraging algorithm for combined static/dynamic environmental economic dispatch[J]. Applied S0ttComputing, 2012, 12(11)~ 3500-3513.
  • 8Basu M. Dynamic economic emission dispatch using nondominatedsorting genetic algorithm-II[J]. Intemational Journal of Electrical Power & Energy Systems, 2008, 30(2): 140-149.
  • 9Jiang X, Zhou J, Wang H, et al. Dynamic environmental economic dispatch using multiobjective differential evolution algorithm with expanded double selection and adaptive random restart[J]. International Journal of Electrical Power & Energy Systems, 2013, (49): 399-407.
  • 10Guo C X, Zhan J P, Wu Q H. Dynamic economic emission dispatch based on group search optimizer with multiple producers[J]. Electric Power Systems Research, 2012(86): 8-16.

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