基于预测控制的含风电滚动优化调度

doi:10.19595/j.cnki.1000-6753.tces.161373

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (1031 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract 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.

Key words： Wind power power dispatch rolling model predictive control optimal dispatch

Received: 26 August 2016 Published: 14 September 2017

PACS:

TM73

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Liu Liyang
	Wu Junji
	Meng Shaoliang

Cite this article:

Liu Liyang,Wu Junji,Meng Shaoliang. A Rolling Dispatch Model for Wind Power Integrated Power System Based on Predictive Control[J]. Transactions of China Electrotechnical Society, 2017, 32(17): 75-83.

URL:

https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.161373 OR https://dgjsxb.ces-transaction.com/EN/Y2017/V32/I17/75

[1] Bilil H,Aniba G,Maaroufi M. Probabilistic economic emission dispatch optimization of multi-sources power system[J]. Energy Procedia,2014,50:789-796.
[2] 于东,孙欣,高丙团,等. 考虑风电不确定出力的风电并网协调优化模型[J]. 电工技术学报,2016,31(9):34-41.
Yu Dong,Sun Xin,Gao Bingtuan,et al. Coordinated optimization model for wind power integration considering wind power uncertainty output[J]. Transactions of China Electrotechnical Society,2016,31(9):34-41.
[3] Hargreaves J J,Hobbs B F. Commitment and dispatch with uncertain wind generation by dynamic programming[J]. IEEE Transactions on Sustainable Energy,2012,3(4):724-734.
[4] 刘德伟,郭剑波,黄越辉,等. 基于风电功率概率预测和运行风险约束的含风电场电力系统动态经济调度[J]. 中国电机工程学报,2013,33(16):9-15.
Liu Dewei,Guo Jianbo,Huang Yuehui,et al. Dynamic economic dispatch of wind integrated power system based on wind power probabilistic forecasting and operation risk constraints[J]. Proceedings of the CSEE,2013,33(16):9-15.
[5] 杨天,王京波,宋少帅,等. 考虑风速相关性的电力系统动态经济调度[J]. 电工技术学报,2016,31(16):189-197.
Yang Tian,Wang Jingbo,Song Shaoshuai,et al. Dynamic economic dispatch of power system considering the correlation of the wind speed[J]. Transactions of China Electrotechnical Society,2016,31(16):189-197.
[6] 卢志刚,隋玉珊,冯涛,等. 考虑储热装置与碳捕集设备的风电消纳低碳经济调度[J]. 电工技术学报,2016,31(17):41-51.
Lu Zhigang,Sui Yushan,Feng Tao,et al. Wind power accommodation low-carbon economic dispatch considering heat accumulator and carbon capture devices[J]. Transactions of China Electrotechnical Society,2016,31(17):41-51.
[7] 胡国伟,别朝红,王锡凡. 考虑运行可靠性的含风电电力系统优化调度[J]. 电工技术学报,2013,28(5):58-65.
Hu Guowei,Bie Zhaohong,Wang Xifan. Optimal dispatch in wind integrated system considering operation reliability[J]. Transactions of China Electrotechnical Society,2013,28(5):58-65.
[8] 徐秋实,邓长虹,肖永,等. 风电时序动态修正的实时调度计划研究[J]. 华中科技大学学报(自然科学版),2014,42(3):73-77.
Xu Qiushi,Deng Changhong,Xiao Yong,et al. Study on real-time generation dispatch with wind power time series dynamic rectification[J]. Journal of Huazhong University of Science and Technology(Natural Science Edition),2014,42(3):73-77.
[9] 包宇庆,王蓓蓓,李扬,等. 考虑大规模风电接入并计及多时间尺度需求响应资源协调优化的滚动调度模型[J]. 中国电机工程学报,2016,36(17):4589-4599.
Bao Yuqing,Wang Beibei,Li Yang,et al. Rolling dispatch model considering wind penetration and multi-scale demand response resources[J]. Proceedings of the CSEE,2016,36(17):4589-4599.
[10]张伯明,吴文传,郑太一,等. 消纳大规模风电的多时间尺度协调的有功调度系统设计[J]. 电力系统自动化,2011,35(1):1-6.
Zhang Boming,Wu Wenchuan,Zhang Taiyi,et al. Design of a multi-time scale coordinated active power dispatching system for accommodating large scale wind power penetration[J]. Automation of Electric Power Systems,2011,35(1):1-6.
[11]Camacho E F,Bordons C. Model predictive control[M]. 2nd ed. London:Springer,2007.
[12]席裕庚. 预测控制[M]. 北京:国防工业出版社,2013.
[13]Zhang Jiangfeng,Xia Xiaohua. A model predictive control approach to the periodic implementation of the solutions of the optimal dynamic resource allocation problem[J]. Automatica,2011,47(2):358-362.
[14]Xia X,Zhang J,Elaiw A. An application of model predictive control to the dynamic economic dispatch of power generation[J]. Control Engineering Practice,2011,19(6):638-648.
[15]Del Real A J,Arce A,Bordons C. Combined environmental and economic dispatch of smart grids using distributed model predictive control[J]. International Journal of Electrical Power & Energy Systems,2014,54:65-76.
[16]Elaiw A M,Xia X,Shehata A M. Application of model predictive control to optimal dynamic dispatch of generation with emission limitations[J]. Electric Power Systems Research,2012,84(1):31-44.
[17]张伯明,陈建华,吴文传. 大规模风电接入电网的有功分层模型预测控制方法[J]. 电力系统自动化,2014,38(9):6-14.
Zhang Boming,Chen Jianhua,Wu Wenchuan. A hierarchical model predictive control method of active power for accommodating large-scale wind power integration[J]. Automation of Electric Power System,2014,38(9):6-14.
[18]杨冬锋,周苏荃,魏剑啸,等. 基于MPC的超短期优化调度策略研究[J]. 电力系统保护与控制,2015,43(11):21-26.
Yang Dongfeng,Zhou Suquan,Wei Jianxiao,et al. Ultra-short term optimal dispatch method based on MPC[J]. Power System Protection and Control,2015,43(11):21-26.
[19]陈宝林. 最优化理论与算法[M]. 北京:清华大学出版社,2005.
[20]Stephen B,Lieven V. 凸优化[M]. 北京:清华大学出版社,2013.
[21]Michalska H,Mayne D Q. Robust receding horizon control of constrained nonliner system[J]. IEEE Transactions on Automation Control,1993,38(11):1623-1633.