Many-objective optimized scheduling method for combined operation of cascade hydropower stations

Abstract

The invention discloses a many-objective optimized scheduling method for combined operation of cascade hydropower stations, and aims at solving main problems in engineering application of standard quantum-behaved particle swarm optimization and problems in solving single-objective optimized scheduling. A multi-population evolution strategy is realized by external file set, advantageous individual selection and a chaotic mutation operator strategies, diversity of individuals is ensured, calculation of the method is accelerated, and an approximate Pareto optimal leading edge with sound distribution is obtained. An external file set is introduced to store elite individuals, dynamic update and maintenance of the file set are realized via non-inferior layered ordering and crowd distance, and distribution of the individual is kept uniform; and a chaotic mutation operator is used to carry out local disturbance on a non-control solution, and the neighborhood exploration capability of the individuals is enhanced. According to the invention, the particle swarm optimization is improved, and effectively applied to making the many-objective optimized scheduling scheme of combined operation of the cascade hydropower stations, and a feasible and high efficiency calculating method is provided for many-objective optimized scheduling of the cascade hydropower stations.

Description

technical field [0001] The invention relates to the field of dispatching of hydropower generation in electric power systems, in particular to a multi-objective optimization dispatching method for joint operation of cascade hydropower station groups. Background technique [0002] With the successive commissioning and operation of giant hydropower stations in major river basins in my country and the steady and orderly advancement of the national interconnected smart grid, cascade hydropower station groups have gradually become operating units that carry the demands of multiple stakeholders. The single-objective scheduling model such as the maximum power generation (power generation benefit) can only consider the maximization of the overall power generation benefit of the cascade from one aspect, and fails to effectively take into account the characteristics of the difference between peak and valley periods of high and low seasons, which can easily lead to unbalanced distributio...

AI Technical Summary

Problems solved by technology

The cascade hydropower station dispatching operation considering multiple objective functions is a typical multi-objective complex decision-making problem, which is usually transformed into a single-objective problem by using constraint method, weight method, ideal solution method, etc., and then using traditional nonlinear programming, dynamic programming, etc. Although the single-objective optimization method can reduce the difficulty of solving the problem, it is inevitably affected by the subjective factors of the decision-maker during the conversion process, which affects the objectivity of the scheduling results and the fairness of the plan; at the same time, the results obtained by dynamic programming and other methods As a result, the information capacity is relatively limited, and it is difficult to scientifically respond to multi-objective-oriented cascade scheduling decisions, and the application of large-scale hydropower scheduling problems is restricted by problems such as dimensionality disaster.

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