Power grid optimal power flow problem solving method based on distributed crisscross algorithm

Abstract

The invention discloses a power grid optimal power flow problem solving method based on a distributed crisscross algorithm, and the method employs a local area network computer group system as a distributed computing environment of the crisscross algorithm, and aims at realizing high parallelism of population crisscross operation and fitness calculation by using the advantages of parallel computing of the crisscross algorithm and the interactivity and mobility of a multi-agent system . According to each evolution of the original crisscross algorithm population, a new population is generated through alternation of transverse crossover and longitudinal crossover, and then the current optimal value of an individual is reserved according to a greedy principle, so that reduction of communication overhead is facilitated, the calculation efficiency is improved, and meanwhile, the possibility is provided for enhancing the flexibility of distributed parallel calculation of the crisscross algorithm. The multi-agent parallel computing platform based on the crisscross algorithm is developed by combining the characteristics of non-global control of the crisscross algorithm and the advantage ofmulti-agent system distribution.

Description

technical field [0001] The invention relates to a method for solving the optimal power flow problem of a power grid, in particular to a method for solving the optimal power flow problem of a power grid based on a distributed criss-cross algorithm. Background technique [0002] With the rapid development of the motherland, the scale of the power grid has expanded rapidly, which has brought huge challenges to the regulation and control of the power grid company. In the past two decades, the swarm intelligence optimization algorithm has become a research hotspot for solving the optimal power flow problem of the power grid due to its simple structure and no excessive restrictions on the objective function and constraints. There are problems of large amount of calculation and slow speed, so constructing parallel calculation is an effective way to improve its calculation efficiency. However, since most swarm intelligence optimization algorithms such as particle swarm optimization...

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Problems solved by technology

[0003] The purpose of the present invention is to provide a solution to the optimal power flow problem of the power grid based on the distributed vertical and horizontal cross algorithm for the problem that the above-mentioned intelligent optimization algorithm takes a long time to optimize

The present invention proposes a parallel computing method suitable for the non-global control characteristics of the vertical and horizontal cross algorithm, obtains a fully parallelized population update iteration framework and computing mechanism in a distributed computing environment, and realizes a flexible and efficient multi-agent distributed optimization system for the vertical and horizontal cross algorithm. So as to solve the calculation time bottleneck problem faced by the optimal dispatching problem of large-scale power grid

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