Power optimization scheduling method and device, computer equipment and storage medium

Abstract

The invention relates to a power optimization scheduling method and device, computer equipment and a storage medium. The method comprises the following steps that computer equipment ,; initializes a primary population and algorithm parameters of a power system based on a decision variable and an optimization target of the power system; and performs crossover mutation processing on the primary population by adopting a differential operator and a levy flight dynamic adaptation search strategy to obtain a target optimization population so as to obtain a target solution set of the decision variable corresponding to the optimization target of the power system, and completes power scheduling operation according to the target solution set of the decision variable. In the method, since when crossover mutation processing is performed on the primary population of the power system, crossover variation is carried out on the primary population by adopting the differential operator and the levy flight dynamic adaptation search strategy, the obtained filial generation population has better convergence, the number and quality of optimal individuals of the population are ensured while the diversityand distributivity of the population are improved, and therefore the complex requirement for multi-target power scheduling of a power system is met.

Description

technical field [0001] The present application relates to the field of electric power technology, and in particular, relates to an electric power optimal scheduling method, device, computer equipment and storage medium. Background technique [0002] With the continuous expansion of the power system scale and the rise of power market operations, the objective functions of various optimization problems in the power system show a trend of diversification, especially in power system reactive power optimization, economic dispatch, load modeling optimization and distribution network rebalancing. In the field of structure and other fields, it has gradually developed into a multi-objective optimization problem that comprehensively considers various operating indicators such as economy, environmental protection benefits, voltage safety margin and power quality, so the trade-off problem has become increasingly prominent. [0003] Existing multi-objective optimization algorithms includ...

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Problems solved by technology

[0004] However, with the complexity of the actual application requirements of the power system, the existing optimization methods cannot meet the needs of multi-objective complex optimal scheduling of the power system

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