Power distribution network state estimation method based on firefly algorithm

Abstract

The invention provides a power distribution network state estimation method based on a firefly algorithm. The method comprises steps as follows: Step 1, generating a power distribution network node admittance matrix; Step 2, initializing fluorescein and dynamic decision domains of fireflies; Step 3, updating the fluorescein of the fireflies; Step 4, calculating the distance between the fireflies to acquire neighborhoods; Step 5, calculating the movement probability of the fireflies; Step 6, updating positions of the fireflies; Step 7, updating the dynamic decision domains of the fireflies; Step 8, judging whether a convergence condition is satisfied or not, if the convergence condition is satisfied, ending the process, executing Step 9, and otherwise, executing Step 3; Step 9, outputting an optimal solution. According to the method, node voltage is used as a state variable, the node injection power is calculated, an objective function value of the least square method is taken as a firefly fitness function value and converted into the fluorescein of the fireflies, the state variable is updated continuously, and the firefly position with the highest fluorescein is taken as the optimal state estimation result. Experiments indicate that the method has good accuracy and adaptability.

Description

technical field [0001] The invention relates to an estimation method, in particular to a distribution network state estimation method based on a firefly algorithm. Background technique [0002] Distribution network state estimation is a method that uses the correlation and redundancy of measurement data, applies computer processing technology, and adopts mathematical processing methods to predict and correct errors in distribution network operating parameters, thereby improving the reliability and integrity of data. It can effectively obtain the real-time operation status information of the distribution network. [0003] With the development requirements of power grid dispatching automation level, the power grid dispatching center must comprehensively and accurately grasp various data of power grid operation, so high-quality state estimation is required as a guarantee for real-time data; the distribution network has significant characteristics different from the transmission...

AI Technical Summary

Problems solved by technology

[0003] With the development requirements of power grid dispatching automation level, the power grid dispatching center must comprehensively and accurately grasp various data of power grid operation, so high-quality state estimation is required as a guarantee for real-time data; the distribution network has significant characteristics different from the transmission network. Many transmission network state estimation algorithms cannot be directly applied to distribution network state estimation, and there are few real-time measurement configurations and insufficient data redundancy in distribution network. Therefore, in-depth research on distribution network state estimation is needed.

[0004] At present, there are many distribution network state estimation methods, among which the weighted least squares method is the most commonly used state estimation method. The solution of the square method can be regarded as an optimization problem for an objective function. The traditional solution methods include the Newton iterative method, the gradient method, etc., and the Newton method is generally used to solve the problem, but the solution of the Newton method has higher requirements for the initial value of the iteration. If the initial value is given If the value is too far from the correct value, it will not be able to converge accurately, and even cause iterative divergence.

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