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作 者:李碧桓 李知艺 鞠平 LI Bihuan;LI Zhiyi;JU Ping(College of Electrical Engineering,Zhejiang University,Hangzhou 310027,Zhejiang Province,China)
机构地区:[1]浙江大学电气工程学院,浙江省杭州市310027
出 处:《中国电机工程学报》2023年第3期878-888,共11页Proceedings of the CSEE
基 金:国家自然科学基金项目(U2066601,52007164,51837004)。
摘 要:在新型电力系统中,高比例新能源出力的不确定性对系统频率安全造成了严峻挑战,中低压配电网负荷参与频率控制成为趋势。然而,配电网负荷量测普遍存在时标异步的问题,给在线负荷准确估计带来了困难,对开展精细化频率控制造成影响。鉴于此,该文提出一种基于软同步的配电网负荷量测联合校正方法。首先,通过分析量测数据矩阵的秩增特性,采用低秩矩阵恢复的思路构建目标函数;在此基础上,采用数据驱动的思路,根据用户用电行为的周期平稳性提出相关约束;以上模型与传统的配电网物理约束和电量平衡约束共同构成了模型–数据联合驱动的凸优化问题。仿真结果验证了该文方法的独特优势,即无需各量测设备误差的概率分布等先验信息,且结果相比传统方法有更高的估计精度。In the new power system,the uncertainty of the high proportion of new energy brings serious challenges to power system frequency security.It becomes a tendency for loads in integrated medium-and low-voltage distribution networks to participate in frequency control.However,the asynchronous measurements limit the estimation accuracy of online load,and affect refined frequency control.This paper proposes a joint correction method of load measurements based on soft synchronization.First,the objective function is conducted using the low rank matrix recovery method.On this basis,data-driven constraints are proposed by analyzing the period stationarity of users’behavior.The above models,together with the traditional distribution network physical constraints and power balance constraints,constitute a model-data-driven convex optimization model.The simulation further verifies the advantages of the proposed method:on the one hand,the proposed method has high estimation accuracy;on the other hand,the proposed method does not need prior information such as the probability distribution of asynchronous measurements error and the detailed sampling time error of measuring devices.
关 键 词:配电网 负荷估计 异步数据 软同步 低秩矩阵恢复
分 类 号:TM93[电气工程—电力电子与电力传动]
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