A multi-region distributed state assessment method for power system

Abstract

The present invention proposes a multi-region distributed state evaluation method for a power system. The invention divides a power system into a plurality of non-overlapping areas, each area is equipped with a state estimator, performs local state estimation according to the measurement data provided by its own SCADA system, and obtains global information through an average consistency algorithm to perform system-level state estimation . The estimation process of each state estimator is parallel and divided into an initialization phase and an iterative calculation phase. In the initialization phase, the initial value of the state estimation is given, and the internal measurement vector and boundary measurement vector are obtained; in the iterative calculation phase, the internal measurement update amount of the state quantity is calculated, and the boundary of the state quantity is calculated after obtaining the global information through the average consistency algorithm Measure the update amount, calculate the total update amount of the state quantity according to the internal measurement update amount and the boundary measurement update amount, and end the iterative calculation process when the total update amount is less than the preset threshold. The invention has high precision, fast estimation speed, high reliability and small amount of exchanged information.

Description

technical field [0001] The invention belongs to the technical field of smart grids, and in particular relates to a multi-regional distributed state evaluation method of a power system. Background technique [0002] With the continuous expansion of power grid interconnection, the structure of power system is becoming more complex and the volume of measurement data is larger. The traditional centralized state estimation method needs to collect all information and perform estimation calculation by a centralized estimator. The system has low computational efficiency and reliability. not tall. Methods that can realize parallel state estimation have become a current research hotspot. [0003] At present, most parallel state estimation algorithms adopt a two-layer structure of "coordination center-sub-area", in which each area estimator performs state estimation of its own area in parallel, and the coordination center estimates the overall state according to the estimation results...

AI Technical Summary

Problems solved by technology

Some studies have proposed a distributed robust state estimation method based on the alternating direction multiplier method, which can obtain similar results to the centralized estimation method when the sub-region is not completely observable, but the sub-region estimator exchanges a large amount of information

Overall, the distributed estimation mode further improves the reliability of the state estimation system, but how to effectively obtain the global information required for state estimation in each region in a distributed manner is an unsolved problem

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