HOUSTON, July 27 (Xinhua) -- Texas A&M University researchers have developed an intelligent model that can predict a potential vulnerability to utility assets, according to a recent news release by the university.
Using the model based on big data, researchers can present a map of where and when a possible outage may occur, caused by high-speed winds during a thunderstorm.
High-speed winds during a thunderstorm may cause trees around an electric grid to crash into the distribution system feeders causing an outage in that area.
However, the predictive feature of the model allows the trees in the most critical areas with the highest risk to be trimmed first.
Predicting an optimal tree trimming schedule that would minimize the risk of vegetation-related outages is only one of the applications.
Mladen Kezunovic, Regents Professor and holder of the Eugene E. Webb professorship in the Department of Electrical and Computer Engineering, along with graduate students Tatjana Dokic and Po-Chen Chen, have developed the framework for a model that can predict weather hazards, vulnerability of electric grids and the economic impact of the potential damage.
Data such as a utility company's operational records, weather forecasts, altitude and vegetation around the power systems can be used to customize the applications of the model.
The model is flexible and can process a variety of data despite differing formats and data sources.
The researchers say processing such data is a demanding task they have been able to solve. Every source of data and its presentation is different and multifaceted.
Based on the goals, they select a large amount of input data from several sources and perform a risk analysis.
