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典型工业负荷参与频率响应的最优申报容量确定及其控制策略设计OA北大核心CSTPCD

Optimal Declared Capacity Model and Operation Control Strategy for Typical Industry Load Participating in Frequency Response

中文摘要英文摘要

作为负荷侧的潜力控制资源,典型工业负荷可有效弥补由于常规机组被新能源替代所导致的系统频率响应(frequency response,FR)能力缺失.然而由于其能力与运行工况密切相关,故需要对其能力进行准确刻画,并据此确定参与调频服务的最优申报调节容量.结合我国调频辅助服务技术规定,提出了典型工业负荷在系统大功率缺失场景下参与频率响应控制的基本原则;考虑奖惩风险,构建了相应的最优申报调节容量优化模型;以年为时间尺度,提出了其参与频率响应的随机生产模拟方法;针对其运行特性,设计了参与频率响应的实时控制策略.仿真算例表明:所提方法能准确模拟工业负荷的生产过程,合理实现工业负荷的运行控制,优化所得到的申报容量为风险意义下的最佳值.

As a potential control resource for the load side,a typical industry load can effectively compensate for the loss of the frequency response capacity of a system in which conventional units are replaced by new energy sources. However,the capacity of the industrial load is closely related to operating conditions. It is necessary to characterize this capacity accurately and determine the optimal declared capacity to participate in the frequency response service. According to the technical regulations of the frequency response service,the load participates in the frequency response control in the case of high-power loss. An optimal declaring capacity optimization model was established considering the risks of reward and punishment. Taking a year as the timescale,a stochastic production simulation method involving a frequency response service is proposed. A real-time control strategy was designed based on the operating characteristics. Simulation examples show that the proposed method can accurately simulate the production process of the industry load,reasonably realize the operation control,and optimize the declared capacity considering the risk of reward and punishment.

贾依霖;郝睿;郭力滔;高雷;孙永超;李卫东

辽宁省电力有限公司鞍山供电公司,辽宁省鞍山市 114000大连理工大学电气工程学院,辽宁省大连市116024

动力与电气工程

频率响应(FR)典型工业负荷最佳申报容量随机生产模拟模糊评价理论

frequency response(FR)typical industry loadoptimal declared capacitystochastic production simulationfuzzy evaluation theory

《电力建设》 2024 (009)

89-99 / 11

国家自然科学基金项目(U22A20223);国家电网有限公司科技项目(2022YF-11)This work is supported by the National Natural Science Foundation of China(No.U22A20223)and State Grid Corporation of China Research Program(No.2022YF-11).

10.12204/j.issn.1000-7229.2024.09.008

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