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A regional wind-solar resource assessment method based on K-means clustering

A technology of k-means clustering and wind power generation, applied in resources, electrical digital data processing, instruments, etc., can solve the problems of difficult application of regional wind power resource complementarity evaluation results, lack of widely used methods, and regional wind power resource evaluation problems Insufficient richness and in-depth research

Active Publication Date: 2019-01-25
ELECTRIC POWER RESEARCH INSTITUTE OF STATE GRID SHANDONG ELECTRIC POWER COMPANY +1
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Problems solved by technology

[0005] At present, the research on resource assessment of regional wind power generation is not rich and in-depth enough, and there is a lack of a widely used method
Existing methods can not take into account the requirements of high-dimensional data calculation and visualization, and the evaluation results of regional wind power resource complementarity are difficult to apply to actual projects, which reduces the practicability

Method used

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  • A regional wind-solar resource assessment method based on K-means clustering
  • A regional wind-solar resource assessment method based on K-means clustering
  • A regional wind-solar resource assessment method based on K-means clustering

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Embodiment Construction

[0082] With reference to the accompanying drawings, the K-means clustering-based regional wind power resource evaluation method of the present invention includes the following steps:

[0083] Step 1) Use the virtual power generation system model to preprocess the original scenery data sequence, and convert the original wind speed and light intensity data into capacity coefficients;

[0084] Step 2) Construct the index of regional resource synergy coefficient, quantify the complementarity between different locations and types of power generation resources, and form a new data set;

[0085] Step 3) Utilize PCA method to process new data collection, reduce new data collection dimension;

[0086] Step 4) Using the K-means clustering method to extract the complementarity pattern of regional wind and wind power generation resources, and visualize the results.

[0087] In step 1):

[0088] The scenery data sequence is measured or meteorological reanalysis wind speed and light inten...

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Abstract

The invention relates to a method for regional wind-solar power generation resource assessment method based on K-means clustering, comprising the following steps: pre-processing original wind-photovoltaic data sequence by using a virtual power generation system model, and converting the original wind speed and light intensity data into capacity coefficient; constructing the index of regional resource coordination coefficient, quantifying the complementarity among different kinds of power generation resources in different locations, and forming a new data set; using a PCA method to deal with anew data set and reducing the dimension of a new data set; and using a K-means clustering method to extract the complementary pattern of the regional wind-solar power generation resources and visualizes the result. The invention reduces the dimension of the original data set of the regional wind-solar power generation resource assessment, takes into account the requirements of high-dimensional data calculation and visualization, and has high engineering practical application value and advancement; and comprehensive considers the complementarity of regional power generation resources, can guidethe planning of a regional complementary power generation system and improves the resource utilization efficiency.

Description

technical field [0001] The invention relates to the field of new energy power generation, in particular to a method for evaluating regional wind power generation resources based on K-means clustering. Background technique [0002] In recent years, wind power generation technology has developed rapidly, and the installed capacity of wind power and photovoltaic units has continued to increase. Wind power generation has irreplaceable advantages such as cleanliness and pollution-free. However, due to the inherent randomness of resources, the output of wind and solar power generation is volatile, which poses new challenges to the safe operation of the power grid. At the same time, wind and wind power resources also have inherent complementarity. Making full use of wind and wind complementarity can smooth the output curve after aggregation, reduce the overall output volatility, reduce the dependence of wind and wind power generation on power grid climbing backup and energy storag...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/06G06F16/2458G06K9/62
CPCG06Q10/0639G06Q50/06G06F18/23213
Inventor 杨冬慈文斌陈博邢鲁华麻常辉王昕郑天茹周宁赵康马欢蒋哲李山李文博牛凯吴彬邓丽刘文学
Owner ELECTRIC POWER RESEARCH INSTITUTE OF STATE GRID SHANDONG ELECTRIC POWER COMPANY
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