A Method of Prediction and Evaluation Considering Wind Resource Utilization Rate
A utilization rate and wind resource technology, applied in the field of monitoring of wind turbines, can solve problems such as the evaluation of wind energy utilization rate fluctuations, the monitoring and evaluation of the health status of wind turbines without wind resources, and the operating status of wind turbines in places where wind measurement is not fully considered.
Active Publication Date: 2022-03-22
HEBEI UNIV OF TECH
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Problems solved by technology
CN105005581A discloses a method and system for processing wind resource data in wind farms. This technology only monitors data such as wind speed and direction, but does not monitor and evaluate the utilization rate of wind resources and the health status of wind turbines; CN104331621B discloses a wind resource calculation method, this method does not fully consider the wind measuring location and the operating state of the wind turbine, but simply classifies the wind resource level according to a single index; CN103696913B discloses a method for real-time monitoring of wind energy utilization deviation when the wind turbine is running, and the utilization deviation The method of real-time monitoring of wind energy utilization deviation, but did not evaluate the degree of fluctuation of wind energy utilization
In short, the existing technical solutions do not predict and evaluate the fluctuation degree of wind resource utilization
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Embodiment
[0112] In this embodiment, a method for predicting and evaluating wind resource utilization is considered, and the technical parameters of the selected 2MW wind turbine are shown in Table 1 below:
[0113] Table 1. Technical parameters of 2MW wind turbines
[0114]
[0115] Count the actual wind speed v and the actual active power P of the wind turbine in the SCADA system of a typical wind farm for the whole year, perform data preprocessing, and draw a P-v scatter diagram, such as figure 1 Shown in the wind speed-power scatter diagram after processing in this embodiment. The filtered data is randomly divided into two subsets, both including training samples and testing samples. The first subset is used for wind turbine power model parameter identification and model evaluation, and the second subset is used for wind resource utilization prediction, error probability distribution statistics and confidence interval estimation.
[0116] In this embodiment, a method for foreca...
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The invention relates to a method for predicting and evaluating wind resource utilization rate, which relates to the field of wind engine monitoring. The steps of the method are: building a five-parameter model of wind turbine power; gray wolf optimization algorithm for power model parameter identification; dividing wind speed segments at equal intervals , using the non-parametric kernel density estimation method to establish the probability distribution of the wind resource utilization rate prediction error in each wind speed segment; to estimate the interval of the wind resource utilization rate, and obtain the confidence interval of the wind resource utilization rate of the wind turbine under a given confidence level ; Forecasting and evaluating the fluctuation degree of wind resource utilization rate, the present invention overcomes the defect in the prior art that there is no prediction and evaluation of the wind resource utilization rate fluctuation degree.
Description
technical field [0001] The technical solution of the present invention relates to the field of wind power engine monitoring, in particular to a method for forecasting and evaluating wind resource utilization. Background technique [0002] Wind resource utilization reflects the performance of wind turbines, and wind resource utilization prediction and evaluation is one of the effective means for wind turbine condition monitoring and wind power prediction. The intermittency, randomness and volatility of wind energy make the power generation performance of wind turbines deviate from the design index, and the stability of wind resource utilization is poor, which brings great challenges to the safe operation and economic dispatch of the power grid. [0003] At present, there are few literatures on the prediction and evaluation of wind resource utilization rate, and the general wind resource assessment methods rarely evaluate the wind resource utilization rate, and are limited to ...
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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06G06N3/00
CPCG06Q10/04G06Q10/0639G06Q50/06G06N3/006Y04S10/50Y02E40/70
Inventor 姚芳董超群刘明宇王晓鹏
Owner HEBEI UNIV OF TECH