Substation capacity optimal configuration method based on mixed quantum evolutionary algorithm

Abstract

The invention relates to the technical field of electric power system configuration and discloses a substation capacity planning method based on the mixed quantum evolutionary algorithm. According to the technical scheme, the substation capacity planning method comprises steps of substation data collection, substation capacity configuration and result output. The substation capacity configuration comprises the steps that firstly, a system is initialized; secondly, the state of a population Q (t) is observed and an observation state population P (t) is produced; thirdly, local search is performed on individuals in the observation state population P (t); fourthly, decoding is performed, and a variable optimal solution is obtained; fifthly, fitness evaluation is performed on an objective function; sixthly, the optimal individual and relevant information are stored; seventhly, end conditions are judged; eighthly, the population is updated. According to the substation capacity planning method based on the mixed quantum evolutionary algorithm, the advantages of strong capacity in global optimization and a fast convergence rate of the quantum evolutionary algorithm and the advantage of strong capacity in local search of the tabu search algorithm are combined, therefore, an optimized capacity configuration scheme of a substation can be fast and accurately obtained, and an output result can be fast and accurately obtained.

Description

technical field [0001] The invention relates to the technical field of power system configuration, in particular to a substation capacity optimization configuration method based on a hybrid quantum evolutionary algorithm. Background technique [0002] Substation planning is an important part of distribution network planning. Its planning content includes: substation optimal capacity allocation, optimal transformer combination scheme and substation optimal location, etc. It is essentially a multi-constraint complex combination optimization problem. As an indispensable and important part of distribution network planning, the results of substation capacity planning directly affect the power network structure, grid investment, power supply reliability and operation economy. The rapidly growing demand for electricity in recent years has further promoted the upgrading of urban power grids, and the voltage levels of major substations will continue to be upgraded. Therefore, in ord...

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Problems solved by technology

[0004] At present, the use of evolutionary algorithms to solve the combinatorial optimization problem of substation planning has become the main research direction in this field, but the existing optimization methods still have some shortcomings in finding the optimal solution under the premise of ensuring the convergence and performance of the algorithm, so it is difficult to propose The most ideal plan

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