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基于模型预测控制的主动配电网多时间尺度有功无功协调调度 被引量:118

Multi-time Scale Active and Reactive Power Coordinated Optimal Dispatch in Active Distribution Network Based on Model Predictive Control
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摘要 随着大量可再生能源的接入,主动配电网在如何应对分布式电源出力不确定性以及负荷波动方面面临极大挑战,同时也对运行过程的经济性和安全性提出了更高要求。为解决上述问题,提出基于模型预测控制的主动配电网多时间尺度有功无功协调调度方法。基于模型预测控制实现主动配电网日前调度,日内滚动调度以及实时反馈校正,减少可再生能源间歇性以及负荷预测误差对配电网运行的影响。同时考虑配电网有功无功耦合特性,通过有功无功协调优化来降低网络损耗,减少无功设备频繁动作所产生的操作成本,在保证主动配电网安全运行的同时进一步实现运行效益最大化。通过仿真分析计算,证明了所提方法的可行性和有效性。 With increasing renewable energy resources integrated, how to deal with the energy uncertainty and load fluctuation has been a great challenge to the active distribution network. Meanwhile, the improvement of system security and economy capacities are also put forward. To solve these problems, an active and reactive power coordinated optimal dispatch of active distribution network based on model predictive control was proposed in this paper. The optimal dispatch was formed by day-ahead scheduling, intra-day rolling scheduling and real-time feedback correction, which can handle uncertainties in renewable energy and load. Also, the prosed approach used the active and reactive power coordinated optimal dispatch to reduce the operating losses and action times of control devices, so that the operational benefits of the network can be maximized while the security was also ensured. The results of the case study verify the effectiveness and feasibility of the proposed approach.
作者 任佳依 顾伟 王勇 嵇文路 刘海波 曹戈 REN Jiayi1, GU Wei1, WANG Yong2, JI Werdu2, LIU Haibo1, CAO Ge1(1.School of Electrical Engineering, Southeast University, Nanjing 210096, Jiangsu Province, China; 2. State Grid Nanjing Power Supply Company, Nanjing 210019, Jiangsu Province, Chin)
出处 《中国电机工程学报》 EI CSCD 北大核心 2018年第5期1397-1407,共11页 Proceedings of the CSEE
基金 国家重点研发计划(2016YFB0900400,2016YFB09004004) 国家自然科学基金项目(51477029) 江苏省电力公司科技项目资助(J2016040)~~
关键词 主动配电网 有功无功协调调度 模型预测控制 多时间尺度 二阶锥规划 active distribution network active and reactivepower coordinated optimal dispatch model predictive control(MPC) multi-time scale second-order cone programming
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