Wind power base booster station site selection method

Abstract

The invention discloses a wind power base booster station site selection method. A GIS three-dimensional wind power model is used as a research scene. The method comprises steps of using layout of thefan as input data; introducing an economic cost investment model in combination with engineering and geographical limiting factors, taking the minimum investment cost of the booster station of the wind power base as an optimization target, designing an optimization algorithm for the layout and the electrical structure of the wind power base, and solving the economic cost investment model to obtain an optimal wind power base booster station site selection result. The optimal design of the layout and the electrical structure of the wind power base is as follows: fans of each wind power plant are preliminarily classified; the wind power plant is divided into a plurality of small areas; equivalently, addressing of a plurality of booster stations is carried out on the whole wind power base atthe same time; in this way, the situation that fans of different wind power plants are classified into the same group when the fans of the whole wind power base are clustered can be avoided, and the situation that optimal results are difficult to search due to the fact that multiple populations are used for conducting booster station site selection on all the wind power plants is avoided.

Description

technical field [0001] The invention relates to the technical field of site selection for booster stations of wind power bases, in particular to a method for site selection of booster stations for wind power bases. Background technique [0002] Investment cost and later income issues have always been key issues in wind power construction projects. Optimizing the design scheme of wind power construction projects to reduce investment costs and improve wind power revenue has become a key task in the wind power industry. [0003] As an important link that affects the economic cost of wind power construction projects, the site selection of booster stations in wind farms is the key work of the project. The site selection of traditional wind farm booster stations mostly relies on engineering experience and artificial comprehensive analysis of topographical maps. Select suitable points within the scope of the wind farm as alternatives for booster station site selection, and then ev...

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Problems solved by technology

[0012] In order to achieve the above purpose, the technical solution provided by the present invention is: a wind power base step-up station site selection method, using the GIS three-dimensional wind power model as the research scene, taking the layout of the wind turbine as the input data, combining engineering and geographical constraints, and introducing The economic cost investment model applicable to the site selection of wind power base booster stations takes the minimum investment cost of wind power base booster stations as the optimization goal, and designs an optimization algorithm based on differential evolution algorithm for the layout and electrical structure of wind power bases. The investment model is solved to obtain the optimal site selection result of the wind power base booster station; wherein, the differential evolution algorithm is based on population variation evolution and is used to solve the global optimization problem of continuous variables. The wind power base is composed of multiple wind farms Composition, the optimal design for the layout and electrical structure of the wind power base is to divide the wind farm into multiple small areas by initially classifying the wind turbines of each wind farm, which is equivalent to performing multiple booster stations on the entire wind power base at the same time. This can avoid the situation that the wind turbines of different wind farms are in the same group when clustering the wind turbines of the entire wind power base, and avoid using multiple populations to select the location of the booster station for each wind farm, which will lead to the search for the most optimal location. Situations where optimal results are difficult;

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