The broader impact/commercial potential of this I-Corps project is in addressing a substantial challenge in energy systems. The future electric power grid, commonly referred to as the smart grid, is expected to differ from the current system by the increased integration of distributed generation, demand response and sensing and communication technologies. As distributed energy resources become more prevalent and shape the future of the electric power grid, the overall operational flexibility of the grid increases. This also means that more control decisions need to be made. This project provides an optimal coordination solution for coordinating geographically scattered energy resources. A commercially viable optimal coordination solution for ever increasing energy resources is crucial for cost efficient generation and dispatch of electricity and ensuring the reliability of the power grid. Specially, focusing on cold chain technologies, this project addresses scalable and flexible control and coordination of distributed refrigeration systems; it is envisioned that the proposed solution and software would turn end-users' pre-installed refrigerators and freezers into an integrated intelligent refrigeration system and significantly improve their energy efficiency.

This I-Corps project provides a novel distributed control method that addresses a significant operational challenge of the distribution electric grid. Control of energy systems today is largely performed by centralized computing and control solutions run at central units. Increased infeed measurements (sensing data) result in growing stress and extended time for computations. Thus, centralized control solutions may not be feasibly computed and applied in real-time. This project contributes to fundamentally new methodologies and software for distributed computation of control decisions in real-time. Our research provides a promising solution for the intelligent control of distributed energy resources, which enables the efficient interaction and coordination of a variety of components with and by a central unit. The key premise in this research is that if coordinated in an intelligent, predictive and scalable way, operation of numerous energy resources can be optimized in real-time, thereby resolving the issue of scalability. In addition to extending the proposed distributed control methodology toward achieving reliable and cost effective energy and demand side management, this project focuses on commercializing a more target specific extension of the proposed approach directed at minimizing the operational cost of refrigeration systems in cold chain industries through enhanced distributed coordination.

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Carnegie-Mellon University
United States
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