Vestas Wind Systems has been granted a patent for a method that uses historical weather predictions and power flow information to generate power flow predictions and identify areas that may experience reverse power flows. The method involves correcting historical weather predictions, training power flow models, and comparing predictions to thresholds to determine the significance of reverse power flows. A report is then generated with predictions and the identified geographic distribution area. GlobalData’s report on Vestas Wind Systems gives a 360-degree view of the company including its patenting strategy. Buy the report here.

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According to GlobalData’s company profile on Vestas Wind Systems, aerial inspection drones was a key innovation area identified from patents. Vestas Wind Systems's grant share as of June 2023 was 1%. Grant share is based on the ratio of number of grants to total number of patents.

The patent is granted for a method of predicting reverse power flow

Source: United States Patent and Trademark Office (USPTO). Credit: Vestas Wind Systems AS

A recently granted patent (Publication Number: US11689154B2) describes a method and system for predicting reverse power flows in a geographic distribution area based on meso-scale numerical weather predictions (NWP) and power flow information. The patent outlines a computer-readable medium containing executable instructions that can be performed by processors to carry out the method.

The method involves receiving historical meso-scale NWP and power flow information for a specific time period in a geographic distribution area. To improve accuracy, the historical NWP predictions are corrected for overfitting, reducing correlations within the predictions. The corrected historical NWP predictions are then used to train power flow models for the distribution area.

Next, current meso-scale NWP for a future time period are received, and the trained power flow models are applied to generate power flow predictions within or from different parts of the distribution area. These power flow predictions are compared to predefined thresholds to determine the significance of reverse power flows. Based on this comparison, a report is generated that includes predictions of reverse power flow and identifies the geographic distribution area that may be impacted by these predictions.

The patent also describes additional features, such as identifying specific portions of the distribution area and the electrical assets that distribute power to those portions. Alerts can be generated and sent to digital devices authorized to receive alerts for the identified electrical assets. The patent further discusses the scalability of model creation and the use of reduced parameters in the NWP predictions to improve scalability.

Overall, this patent presents a method and system for predicting reverse power flows in a geographic distribution area using historical and current meso-scale NWP and power flow information. By applying power flow models and comparing predictions to thresholds, the system can generate reports and alerts to help identify areas that may be impacted by reverse power flows. The patent highlights the importance of correcting for overfitting and reducing correlations within NWP predictions to improve accuracy.

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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.

GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.