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基于预测控制的含风电滚动优化调度 被引量:21

A Rolling Dispatch Model for Wind Power Integrated Power System Based on Predictive Control
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摘要 在预测控制理论的基础上建立了含风电的滚动优化调度模型,将常规火电机组、风电机组的有功出力视为预测控制的状态量,常规火电机组的出力调整量视为输入量,以状态空间的形式描述状态量和输入量之间的关系。通过对目标函数和约束条件进行状态空间转换,使滚动调度问题转变为矩阵形式的优化问题,建立了一种多机组多预测时段的滚动优化调度数学模型。并根据矩阵的特性对目标函数进行了化简,使优化问题转换为二次规划形式,推导了全矩阵约束时的内点法增量矩阵,便于应用内点法进行模型求解。此外,还对滚动优化的决策稳定性问题进行了理论分析。仿真算例表明,相比传统的单时刻优化,基于预测控制的含风电滚动优化模型在整体优化水平和调度决策前瞻性方面具有优势。 Based on predictive control,a new rolling dispatch model for wind power integrated power system was proposed.The power output from thermal units and wind farms were treated as a series of system states,and the adjustment power output of thermal units as the system inputs.The state space theory,by which the traditional objective function and constraints can be transformed into matrix forms,was used to describe the relationship between system states and inputs.The multiple power units and predictions optimization problem can be described by a series of matrixes,according the above transformation.With the objective matrix simplification and incremental matrix derivation,the original model was converted into a standard quadratic programming problem,which can be easily solved by interior point method.Finally,the stability of rolling dispatch was discussed.The numerical examples show that the proposed model has less total running cost than the traditional single-time optimization,and the rolling schedules are more proactive.
出处 《电工技术学报》 EI CSCD 北大核心 2017年第17期75-83,共9页 Transactions of China Electrotechnical Society
基金 国家自然科学基金资助项目(51607091)
关键词 风电 电力调度 滚动模型 预测控制 优化调度 Wind power power dispatch rolling model predictive control optimal dispatch
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  • 1杨莳百,丁明.大型电力系统可靠性技术(四)[J].电力系统自动化,1994,18(1):58-62. 被引量:2
  • 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周劼英,张伯明,尚金成,何南强,姚佳,范斗,程满,王丹,李予州,刘明松.河南电网实时调度系统若干功能与算法[J].电力系统自动化,2006,30(2):99-104. 被引量:25
  • 4周家启 任震译.电力系统可靠性评估[M].重庆:科学技术文献出版社重庆分社,1986..
  • 5SHEN Wei, WU Wenchuan, SUN Hongbin, et al. A wave filtering based electric load curve decomposition method for AGC[C]// Proceedings of 2010 International Conference on Power System Technology, October 24 -28, 2010, Hangzhou,.
  • 6MIRANDA M S, DUNN R W. One-hour-ahead wind speed prediction using a Bayesian methodology[C]// Proceedings of IEEE Power Engineering Society General Meeting, June 18-22, 2006, Montreal, Canada.
  • 7EI-FOULY T H M, EI-SAADANY E F, SALAMA M M A. One day ahead prediction of wind speed using annual trends [C]// Proceedings of IEEE Power Engineering Society General Meeting, June 18-22, 2006, Montreal, Canada.
  • 8SENJYU T, YONA A, URASAKI N, et al. Application of recurrent neural network to long-term-ahead generating power forecasting for wind power generator[C]// Proceedings of IEEE Power Systems Conference and Exposition, October 29- November 1, 2006, Atlanta, GA, USA: 1260-1265.
  • 9LI S. Wind power prediction using recurrent multilayer perceptron neural networks[C]// Proceedings of IEEE Power Engineering Society General Meeting, July 13-17, 2003, Toronto, Canada: 2325 -2330.
  • 10FAN S S, LIAO J J R, YOKOYAMA R R, et al. Forecasting the wind generation using a two-stage network based on meteorological information [ J ]. IEEE Trans on Energy Conversion, 2009, 24(2): 474-482.

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