Computational Acquisition of Meteorological Data for Applications in Electric Power Systems

摘要

Humans heavily rely on mother nature for hospitable living conditions, plentiful harvests, and energy generation, yet have no control. The best humans can do is plan and predict. Climatological statistics and forecasts provided by public weather services serve as traditional methods for obtaining meteorological information. However, through Numerical Weather Prediction models, one can simulate climate fluctuations with high spatial resolution over long periods. Uses for Numerical Weather Prediction models include analyzing the energy flux of smart homes, smart grid technology, impact on power transmission infrastructure, and energy production through wind and photovoltaic farms. The efficiency of these technologies is dependant on the surrounding weather phenomena. The optimization of these systems to the environment upon which they exist can both reduce wasted resources and the economic impact on consumers and organizations. This paper outlines the methods used for the acquisition of weather data through computer simulations at a spatial resolution of 1.2 km in 15-minute intervals with an accuracy of 2%.