Power system multi-region distributed state estimation method

Abstract

The invention discloses a power system multi-region distributed state estimation method. According to the invention, one power system is divided into a plurality of non-overlapped regions; a state estimator is configured in each region; local state estimation is carried out according to measurement data provided by an SCADA system of each state estimator; and by an average consistency algorithm, global information is acquired to carry out system-level state estimation. The estimation process of each state estimator is parallel and is divided into an initialization stage and an iterative computation stage. In the initialization stage, a state estimation initial value is given out, and a region internal measurement vector and a boundary measurement vector are acquired; in the iterative computation stage, an internal measurement update quantity of a state quantity is computed, a boundary measurement update quantity of the state quantity is computed after the global information is acquiredby the average consistency algorithm, a total update quantity of the state quantity is computed according to the internal measurement update quantity and the boundary measurement update quantity, andwhen the total update quantity is smaller than a preset threshold, the iterative computation process is ended. The power system multi-region distributed state estimation method is high in accuracy, high in estimation speed, high in reliability and small in exchange information quantity.

Description

technical field [0001] The invention belongs to the technical field of smart grids, and in particular relates to a multi-area distributed state evaluation method of a power system. Background technique [0002] With the continuous expansion of the scale of grid interconnection, the structure of the power system is becoming more and more complex and the volume of measurement data is larger. The traditional centralized state estimation method needs to collect all the information and perform estimation calculations by the centralized estimator. The calculation efficiency of the system is low and the reliability is low. 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-region", in which each region estimator performs state estimation for each region in parallel, and the coordination center performs overall stat...

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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