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Firefly algorithm-based cascade reservoir group scheduling optimization method

A firefly algorithm and cascade reservoir technology are applied in the field of hydropower station optimization in water conservancy projects to achieve the effects of improving the comprehensive utilization of water resources and the economic benefits of power generation enterprises, enriching the optimal scheduling method for cascade reservoir groups, and improving the level of joint operation.

Active Publication Date: 2018-01-19
XIAN UNIV OF TECH
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Problems solved by technology

[0004] As a novel and efficient search algorithm, foreign countries have begun to apply it to reservoir optimization scheduling problems in recent years, and there are few applications in China.

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  • Firefly algorithm-based cascade reservoir group scheduling optimization method
  • Firefly algorithm-based cascade reservoir group scheduling optimization method
  • Firefly algorithm-based cascade reservoir group scheduling optimization method

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Embodiment Construction

[0048] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0049] A kind of cascade reservoir group scheduling optimization method based on firefly algorithm of the present invention comprises the following steps:

[0050] Step 1: Taking the maximum power generation of the cascade reservoirs as the optimization goal during the dispatching period, and taking the hydraulic and electric constraints of the cascade reservoirs as constraints, an optimization model of the cascade reservoirs is established. The objective function of the cascade reservoir optimization model is:

[0051]

[0052] In the formula (1): E is the generating capacity of cascade power stations, 100 million kW h; m and n are the total number of power stations and the total number of dispatching periods; K i is the output coefficient of the i-th power station; Q i,j is the power generation flow of the i-th power station in the j-th...

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Abstract

The invention discloses a firefly algorithm-based cascade reservoir group scheduling optimization method. The method comprises the following steps of 1: by taking maximum generated energy of cascade reservoirs in a scheduling period as an optimization target, and taking waterpower constraints and electricity constraints of the cascade reservoirs as constraint conditions, building a cascade reservoir optimization model; and 2: performing optimization calculation on the cascade reservoir optimization model obtained in the step 1 by adopting an improved firefly algorithm to obtain the maximum generated energy and an optimal reservoir water level corresponding to the maximum generated energy, and outputting the optimal reservoir water level. The firefly algorithm-based cascade reservoir groupscheduling optimization method has important practical significance and application values for enriching cascade reservoir group optimization scheduling methods, improving the joint operation level ofa cascade reservoir group and improving comprehensive utilization benefits of water resources and economic benefits of power generation enterprises.

Description

technical field [0001] The invention belongs to the technical field of optimization methods for water conservancy engineering and hydropower stations, and in particular relates to an optimization method for cascade reservoir group scheduling based on a firefly algorithm. Background technique [0002] Cascade reservoir group scheduling is a nonlinear, high-dimensional, dynamic complex optimization problem, which is more complex and difficult to solve than general nonlinear constrained optimization. Currently, there are two main methods for solving reservoir scheduling problems: traditional optimal scheduling methods and swarm intelligence optimization algorithms. Traditional methods such as linear programming, dynamic programming, and step-by-step optimization algorithms have defects such as long calculation time, dimensionality disaster, and slow convergence speed, while swarm intelligence algorithms are widely used in reservoir optimization and scheduling due to their simpl...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06N3/00
Inventor 白涛杨旺旺赵梦龙黄强武连洲麻蓉哈燕萍马旭马盼盼
Owner XIAN UNIV OF TECH
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