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An Optimization Method for Wind Turbine Site Selection and Type Selection Applicable to Complex Constraints

A technology of wind turbines and constraint conditions, applied in data processing applications, forecasting, instruments, etc., can solve the problems that are not suitable for the practical use of micro-site selection, do not consider the influence of wake between wind turbines, and do not consider the globality of optimization algorithms, etc. Achieve the effects of strong practicability, satisfying the safety distance restriction conditions, and good global optimality

Active Publication Date: 2020-01-21
ZHEJIANG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

At the same time, in the process of micro-site selection of wind farms, there are also various restrictions, such as the need to meet the safety distance and the minimum power generation of wind farms in normal years, etc.
[0004] Among the documents and patents related to this patent, the document Castro Mora, J et al. published the paper "An evolutive algorithm for wind farm optimal design" in Neurocomputing in 2007, and proposed the problem of multi-model fan arrangement optimization and gave A solution, but the optimization does not take into account the wake effect between fans
The patent "A Genetic Algorithm-based Optimal Arrangement Scheme for Multi-model Wind Turbines in Wind Farms" (Application Publication No.: CN103793566A) proposes the use of genetic algorithms to solve the problem of multi-model wind turbine arrangement, but the optimal algorithm for fan model selection adopted It does not consider the globality of the optimization algorithm, which is relatively rough and not accurate enough
These studies do not consider complex constraints or assume very simple assumptions, which are not suitable for use in micro-site selection practice

Method used

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  • An Optimization Method for Wind Turbine Site Selection and Type Selection Applicable to Complex Constraints
  • An Optimization Method for Wind Turbine Site Selection and Type Selection Applicable to Complex Constraints
  • An Optimization Method for Wind Turbine Site Selection and Type Selection Applicable to Complex Constraints

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Embodiment

[0051] In this embodiment, the arrangement and selection of the wind turbines before the construction of the generators are optimized for 8 wind turbines in a wind farm. The optional fans are two ex-factory models A (rated power of 1.5MW) and B (rated power of 2MW). There are two installation heights for each ex-factory model (1.5MW has two heights of 65 meters and 80 meters, 2MW There are two heights of 80 meters and 90 meters), that is, there are 4 types of wind turbines. The wind farm area is the abscissa [0,2000] (meter), and the ordinate is the range of [0,2000] (meter). In this embodiment, complex terrain is not considered. The number of wind turbines is 7, the safety distance between the wind turbines is 5 times the diameter of the wind wheel, which is 550 meters, and the minimum annual power generation of the wind farm is 8MW. The optimization goal is the lowest cost per kilowatt-hour of wind farms. The implementation steps are as follows:

[0052] 1) According to the...

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Abstract

The invention discloses a method for optimizing the site selection and the model selection of wind driven generators suitable for a complex constraint condition. For an optimization problem of the site selection and the model selection of the wind driven generators, when nonlinear constraint conditions exist such as minimum annual power generation and shortest distance between wind driven generators, a genetic algorithm is used for site selection of the wind driven generators and a particle swarm optimization (PSO) algorithm is used for acquiring the optimal scheme of the model selection of the wind driven generators at such site. The method sets the objective function of the PSO algorithm, adds a penalty function in order to add a minimum power generation limiting condition thereto, and is in nested use with a genetic algorithm as a wind driven generator model selection optimization algorithm. In the genetic algorithm, the objective function of the genetic algorithm is set, and the penalty function is added to the shortest wind driven generator distance, that is, a safe distance limiting condition is added in order to achieve position model optimization of mixed installation of multiple models of wind driven generators in a wind power plant. The method can solve the optimization problem with the complex nonlinear constraint condition, achieves a better performance index, a more accurate model selection scheme, and better practicality.

Description

Technical field [0001] The invention relates to an optimization method for the arrangement of multi-model wind power generators in a wind farm, in particular to a wind power generator site selection optimization method suitable for complex constraint conditions. Background technique [0002] Wind energy is a pollution-free and renewable new energy. In a modern society where energy is scarce and traditional energy is seriously polluting the environment, the wind power industry has become one of the new energy industries that are vigorously developed. Micro-site selection of wind farms is a necessary step for the rational planning of the wind power industry. The micro-site selection of wind farms before the construction of wind farms can effectively improve wind energy utilization efficiency, increase the service life of wind turbines, reduce wind farm operation and maintenance costs and wind power costs, so as to achieve reasonable decision-making and scientific development of the...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/043G06Q50/06
Inventor 唐晓宇杨秦敏陈积明孙优贤
Owner ZHEJIANG UNIV
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