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Smart Power Systems of the Future: Foundations for Understanding Volatility and Improving Operational Reliability

Co-PIs M. A. Dahleh, M. Roozbehani, S. Mitter (MIT), A. Dominguez-Garcia (UIUC), and S. Meyn (UF)

$? (approx.) 2012 – 2015

Project Summary The current power grid is expected to evolve rapidly in the next decade to incorporate new and exiting innovations in power generation as well as distributed control. This project addresses the impact of the integration of renewable intermittent generation and the integration of sophisticated sensing, communication, and actuation capabilities into the future grid on the system’s reliability, price volatility, and economic efficiency.

Intellectual Merit The future power grid, characterized by a substantial increase in renewable generation and a powerful cyber layer that allows for collection and communication of large amounts of data and distributed decision making at the level of generation, transmission, distribution, and consumption, is cursed by a substantial increase in uncertainty and complexity. Without careful crafting of its architecture, the future smart grid may suffer from a decrease of reliability and robustness, an increase of price volatility, and an increase of undetectable strategic policies by market players that reduce the market efficiency. In order to address this challenging problem, a project is proposed that relies on the following components: (a) the development of tractable cross-layer models; physical, cyber, and economic, that capture the fundamental tradeoffs between reliability, price volatility, and economic efficiency, (b) the development of computational tools for quantifying the value of information on decision making at various levels, (c) the development of tools for performing distributed robust control design at the distribution level in the presence of information constraints, (d) the development of dynamic economic models that can address the real-time impact of consumer’s feedback on future electricity markets, and finally (e) the development of cross-layer design principles and metrics that address critical architectural issues of the future grid.

Broader Impact The broader impacts of the proposed project are summarized as follows:

• Socioeconomic Impact: The social, economic, and environmental impacts of this project are profound. Not only do power interruptions result in enormous financial losses, but also they have a substantial social impact on consumers. Even local outages can lead to loss of life and capital with detrimental consequences on our society. While the public will value the environmental benefits of renewable generation, the investments in these technologies will depend on the ability to mitigate the induced uncertainties. This project aims at providing a clear understanding of the sources of uncertainty in the smart grid and the limitations and capabilities of control in supplying reliable power in the face of such uncertainty, and thus, promotes modernization of the grid by reducing the system-level barriers for integration of new technologies.

• Industrial and Policy Impact: Fundamental issues such as pricing renewable resources, design of dynamic market mechanisms for fair and balaced integration of these volatile resources, control and operation of a safety-critical system with hard constraints in the presence of stochastic uncertainties, and the implications of different system architectures on volatility, reliability, economic efficiency, and computational complexity are unresolved. The outcome of this research will substantially influence the architecture, market design, and system operation for future power systems. This research is timely and valuable to industries involved at all levels of the electricity supply chain. Moreover, understanding the fundamental limits is indispensable to policymakers that are currently engaged in revamping the infrastructure of our energy system.

• Educational Impact: Research in this project brings together a broad set of expertise in the following fields: power systems engineering, distributed control and optimization, sensor networks and characterization of ”optimal information for decisions”, and finally, economics and market design. Students supervised under this project will be trained in the majority of these fields. Addressing the fundamental problems concerning integration of the renewable resources, and formulation of canonical problems concerning the interaction of multi-layer multi-rate networks will lead to many opportunities for master’s and doctoral theses in engineering and mathematics. New developments will be integrated in our curriculum and will be disseminated through MIT’s OpenCourseWare as well as our regular interactions with the MIT Energy Initiative that has targeted the industry, policy makers, and students and researchers all around the world. Given the increasing international interest in the topic, it is expected that the educational impact of the new developments would be substantial.

 

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