Collaborators: The University of Tennessee, Fisk University, Commonwealth Edison, Tennessee Valley Authority
Sponsors: EPRI, DoD
The collaborators are forming a multidisciplinary Consortium for the Intelligent Management of the Electric Power Grid (CIMEG). CIMEG's broad aims are to develop intelligent monitoring, diagnostic and management concepts to promote the performance, health and longevity of the grid. CIMEG will advance and demonstrate innovative approaches to anticipatory grid control and self-healing, whereby the grid can defend itself by anticipating global contingencies and act locally on the basis of such anticipations. A number of methodological tools will be brought to bear towards achieving these goals. These will include, but will not be limited to: highly reliable predictive neural networks for short and long-term forecasting, multiagent modeling of loads transmission entities, generators and corporate entities; and high-performance simulations, visualizations and online stability analyses to achieve robust and efficient anticipatory control. The Consortium will demonstrate the developed methodologies through a prototype called TELOS (Transmission Entities with Learning-capabilities and On-line Self-healing), which is expected to operate off-line at the end of the third year. Professors Elmagarmid and Houstis are responsible for the data mining and agent-based technology tasks.