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Big-M based milp method for SCUC considering allowable wind power output interval and its adjustable conservativeness

2021-05-14

文章导读

伴随“双碳”目标下可再生能源的大力发展，未来十年我国大量风电资源将接入电网，当高比例风电资源接入电网时，风电的随机性和波动性加剧了系统调度运行的不确定性。如何处理风电的不确定性，且统筹协调多区域的风电和火电等资源，实现风电资源的跨区消纳已成为系统优化调度需要解决的关键问题。分析系统的调峰需求并且制定合理的机组优化调度方案,能够对系统接纳风电起到良好的促进作用,并保障含风电系统的安全经济运行。本章提出了基于大M法的MILP的风电区间可优化和可调节的安全约束机组组合。含大规模风电接入的电网，其所能消纳的风电出力区间受到电网备用容量和线路传输功率两方面约束。本文提出的鲁棒安全约束机组组合能够获得置信水平与风电出力不确定集间的关系，降低鲁棒调度策略的保守性，实现系统运行经济性和安全性的折中。

Big-M based milp method for SCUC considering allowable wind power output interval and its adjustable conservativeness

基于大M法的MILP的风电区间可优化和可调节的安全约束机组组合

Liudong Zhang, Qibing Zhang, Haifeng Fan, Haiwei Wu, Chunlei Xu

（State Grid Jiangsu Electric Power Company, LTD., Nanjing 210024, P.R. China）

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Abstract

、、In contrast to most existing works on robust unit commitment (UC), this study proposes a novel big-M-based mixed-integer linear programming (MILP) method to solve security-constrained UC problems considering the allowable wind power output interval and its adjustable conservativeness. The wind power accommodation capability is usually limited by spinning reserve requirements and transmission line capacity in power systems with large-scale wind power integration. Therefore, by employing the big-M method and adding auxiliary 0-1 binary variables to describe the allowable wind power output interval, a bilinear programming problem meeting the security constraints of system operation is presented. Furthermore, an adjustable confidence level was introduced into the proposed robust optimization model to decrease the level of conservatism of the robust solutions. This can establish a trade-off between economy and security. To develop an MILP problem that can be solved by commercial solvers such as CPLEX, the big-M method is utilized again to represent the bilinear formulation as a series of linear inequality constraints and approximately address the nonlinear formulation caused by the adjustable conservativeness. Simulation studies on a modified IEEE 26-generator reliability test system connected to wind farms were performed to confirm the effectiveness and advantages of the proposed method.

Keywords

Big-M method, Security-constrained unit commitment, Robust optimization, Mixed-integer linear programming, Allowable wind power output interval, Adjustable conservativeness.

Fig.1 Predicted wind power output interval

Fig.2Impact of wind power output limit on the allowable wind power output interval

Fig.3 Four cases of the determination of the uncertainty set

Fig.4Proposed robust dispatch framework of a two-level hierarchical dispatch system

Fig.5 Comparison of predicted and allowable interval upper/ lower bounds of wind power output

Fig.6 Comparison of conventional and proposed interval upper/lower bounds of wind power output

Fig.7 Comparison of operational schedules of conventional units between the proposed and conventional robust UC models

Fig.8 Comparison of proposed and conventional up/down spinning reserve amounts

本文引文信息

Zhang L, Zhang Q, Fan H, Wu H, Xu C J (2021) Big-M based MILP method for SCUC considering allowable wind power output interval and its adjustable conservativeness, 4(2): 193-203

张刘冬，张琦兵，樊海锋，吴海伟，徐春雷 (2021) 基于大M法的MILP的风电区间可优化和可调节的安全约束机组组合. 全球能源互联网（英文），4(2): 193-203

Biographies

Liudong Zhang

Liudong Zhang received the B.S. degree and Ph.D. degree in electrical engineering from Nanjing University of Science and Technology, Nanjing, China in 2009 and 2015, respectively. He currently works in State Grid Jiangsu Electric Power Company, Nanjing, China. His research interests include robust optimization on power system operation and planning with renewable energy.

Qibing Zhang

Qibing Zhang received the B.S. degree in Electrical Engineering from Zhejiang University, Hangzhou, China, in 2007, and the M.S. degree in Electrical Engineering from Shanghai Jiao Tong University, Shanghai, China, in 2010. He currently works in State Grid Jiangsu Electric Power Company, Nanjing, China. His research interests include power system operation and control and relay protection.

Haifeng Fan

Haifeng Fan received the B.S. degree in Electrical Engineering from Xi’an Jiao Tong University, Xi’an, China, in 2009, and the M.S. degree in Electrical Engineering from Zhejiang University, Hangzhou, China, in 2012. He currently works in State Grid Jiangsu Electric Power Company, Nanjing, China. His research interests include power system operation and electricity market.

Haiwei Wu

Haiwei Wu received the B.S. degree in Electrical Engineering from Hefei University of Technology, Hefei, China, in 2008, and the M.S. degree in Electrical Engineering from Zhejiang University, Zhejiang, China, in 2011. He currently works in State Grid Jiangsu Electric Power Company, Nanjing, China. His research interests include power system automation.

Chunlei Xu

Chunlei Xu received the B.S. degree in Electrical Engineering from Shanghai Jiao Tong University, Shanghai, China, in 1999. He currently leads the Dispatching Automation Department at Jiangsu Electrical Power Company in China. His research interests include power system operation and control and WAMS.

编辑：王闻昊王彦博

审核：王伟

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