Power distribution network layering and partitioning state estimation system based on hybrid measurement

Abstract

The invention relates to a power distribution network layering and partitioning state estimation system based on hybrid measurement, and the system comprises an input unit which obtains node data in a power distribution network, power distribution network branch data, PMU configuration data and other measurement device configuration data; the power distribution network layering and partitioning unit is used for dividing the power distribution network into a plurality of sub-regions based on the data input by the input unit, delimiting a tie line region by boundary nodes and tie line nodes, and establishing a power distribution network layering and partitioning model; the measurement data fusion unit is used for fusing state estimation values and estimation variances of the sub-regions processed by the layering and partitioning unit of the power distribution network by taking the phase angle information measured by the PMU nodes in the partitions as partition phase angle reference; the dynamic state estimation unit is used for carrying out mutual fusion on the sub-regions to realize whole-network dynamic state estimation in a parallel computing mode; and the output unit stores the processing data and outputs a global dynamic state estimation result of the power distribution network. Compared with the prior art, the method has the advantages of high precision, high operation speed and the like.

Description

technical field [0001] The invention relates to the technical field of distribution networks, in particular to a hybrid measurement-based hierarchical and partitioned state estimation system for distribution networks. Background technique [0002] With the construction and development of smart grid, the scale of power system network is expanding day by day, and the number of nodes is increasing dramatically. Advanced, flexible, intelligent and safe active distribution network has become an important direction for the development of distribution network planning and operation mode. At the same time, the interconnection between large-scale integrated distributed generation (Distributed Generation, DG) and flexible and changeable loads (such as electric vehicles) connected to the power grid, and regional power grids continues to increase. The computational efficiency and estimation of traditional centralized state estimation Accuracy and dynamic real-time bring great challenges...

AI Technical Summary

Problems solved by technology

In view of the coexistence of multiple measurement devices, uneven distribution of measurement configuration, asynchronous measurement sampling time scale, and differential measurement accuracy in the actual distribution network, it is necessary to effectively carry out mixed measurement data such as PMU and SCADA. fusion

[0003] At present, some scholars or researchers have proposed some real-time state estimation technologies, for example, using a variety of data fusion strategies to improve the accuracy of linear state estimation and shorten the period, and using branch current-based measurement transformation technology to analyze the distribution network. The state estimation of the single partition of the single partition, the weighted minimum absolute value method with strong tolerance to the state estimation of the AC-DC distribution network considering the three-phase unbalance, the robustness state estimation algorithm based on the least square and the sum of one multiplication Solve the state estimation of the measurement data after RTU and PMU fusion, etc. However, these methods are mainly based on SCADA measurement, and less consideration is given to data completion and fusion in the case of PMU high-frequency measurement

However, due to the small time scale and strong volatility of the dynamic process in the smart distribution network, the complexity of the distribution network is greatly increased. Therefore, in order to fully mine high-frequency measurement data and complement the problem of incomplete distribution of PMU measurement space, it is necessary A data fusion and completion strategy for different sampling frequency bands and measurement types is proposed to improve the redundancy of measurement

In addition, the existing state estimation mainly focuses on the algorithm research, lacks the in-depth mining of the parallel computing structure of the distribution network topology, and ignores the transmission efficiency of system measurement data and the fusion boundary of local measurement data in high-frequency state estimation. importance and feasibility

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