Electric power unit combination method based on grey prediction evolution algorithm

Abstract

The invention relates to an electric power unit combination method based on a grey prediction evolution algorithm. The method comprises the steps of setting constraint conditions of an electric powerunit; establishing a binary matrix representing the on-off state of each population individual and a real number matrix of output power; generating a binary matrix of a switch state by adopting a binary genetic algorithm, generating a real number matrix of output power in a unit power range by adopting a gray prediction evolution algorithm, and ensuring that the binary matrix and the real number matrix meet constraint conditions; and selecting the optimal population individual to enter the next generation until the maximum number of iterations is reached, and outputting a binary matrix and a real number matrix as the on-off state and the output power of the power unit. The two meta-heuristic algorithms are operated in parallel to solve the two sub-problems of unit on-off state and power dispatching, the respective advantages of the two algorithms are effectively embodied, a good effect can be achieved on a large-scale unit, the cost of a power system is remarkably saved, input parameters are few, and operation of an operator is facilitated.

Description

Technical field [0001] The invention relates to the field of electric power systems, and in particular to a method for power unit combination based on grey prediction evolution algorithm. Background technique [0002] The problem of power unit combination refers to the reasonable arrangement of the start and stop status and output of each unit under the condition of satisfying user load requirements and various unit constraints within a dispatch period, so as to minimize the system operation cost. The methods to deal with the power unit commitment problem can be roughly divided into three categories: classic numerical optimization techniques, meta-heuristic algorithms and hybrid techniques. [0003] Decision techniques have the advantages of simple expression, strong robustness, non-iteration, and fast convergence speed, but they consume a lot of calculation time while obtaining good solutions, and are not suitable for large-scale unit commitment problems. In order to solve this p...

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Problems solved by technology

[0006] Aiming at the technical problems existing in the prior art, the present invention provides a combination method of electric power units based on the gray prediction evolution algorithm, which solves the problem of the two aspects of power combination that cannot be solved at the same time in the prior art. The quality of the balanced solution and the calculation time The problem

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