Adaptive Predictive Algorithms for Renewables Integration

A robust software algorithm is needed to monitors the conditions of the electricity grid in real time and use historical statistical data to predict behavior under various future conditions. The algorithm could be used release additional capacity, and improve the reliability and economic efficiency of the nation¿s transmission and distribution corridors. This project will develop and field-test a prototype software package that receives data from line sensors and uses credible contingency scenarios to predict ampacity one, two, and four hours into the future, while assigning probabilities to the outcomes. Phase I will involve the development of an adaptive, predictive algorithm. Because the environmental data needed for the computations has in the past proven to be relatively expensive, an inexpensive method of acquiring local environmental information also will be developed. Phase II will focus on the deployment of the algorithm for use by independent system operators. Commercial Applications and other Benefits as described by the awardee In addition to improving the reliability and efficiency of the electric power transmission grid, the technology would enable the successful integration of distributed energy generation, especially wind power, into the grid.