Smart Energy Systems: Control, Communications, and Optimization

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The next generation of energy systems will harness the latest ICT technologies including broadband wireline and wireless networks, sensors, data collection and processing. They will reduce our carbon footprint, improve infrastructure cost efficiency, integrate disruptive technologies such as distributed generation, demand side management, energy storage elements, and flexible loads (e.g., buildings and electrical vehicles), and place the customers more 'in the loop'. This will be done by converting the existing grid which is 'energy rich, control poor, and information poor' into an 'energy frugal, control rich, and information rich' system. The result will be a large scale heterogeneous distributed system, made of hundreds of thousands intermittent sources, two way flows, and a set of elastic loads and storage elements.  This system will have a lot of similarities (and some striking differences) to the Internet. This proposal aims to address several of the fundamental challenges and system issues facing the next generation of energy systems by taking full advantage of the experiences (successes and failures) drawn from the Internet. As an example, the Internet's robustness comes from its simple layered architecture and the use of distributed control mechanisms to prevent congestion. Internet researchers have had to design for the unknown, both the 'generation' of content and the demands are random, and new applications regularly emerge to test the robustness of the Internet design. The next generation of energy systems has similar characteristics, i.e., it will be highly distributed and will contain many more sources of randomness making the need for a robust design a necessity. Our long-term objective is to propose a legacy-compatible control and communication architecture and design the related protocols and algorithms that enable the efficient integration of renewables and energy storage in a distribution network while taking advantage of the flexibility of some loads (e.g., buildings and electrical vehicles).  We will do that by: (a) Modeling and analyzing energy storage technologies in different application areas (e.g., ancillary services, improving power quality, solar/wind firming). (b) Characterizing, quantifying and managing load flexibility. (c) Proposing and evaluating different control and communication architectures. The outcomes of the proposal will be new tools and mechanisms to size, study, and operate the next generation of distribution networks. They will significantly advance the state of the art on energy systems in general and will be key to the development of Smart Grids in Canada and elsewhere. They will help Canadian policy makers make informed decisions when selecting incentive programs or when subsidizing technologies. The proposal will also provide excellent HQP training opportunities at the PhD levels.