A Computer Engineering Approach to the Smart Grid

点击翻译按钮获取中文摘要

The concept of the Smart Grid is born from the convergence of electrical energy systems and the latest Information and Communications technologies including broadband wireline and wireless networks, sensors, data collection and processing. The objectives are to reduce our carbon footprint, improve the infrastructure cost efficiency (in particular by reducing peaks) and put the customers in the loop by integrating disruptive technologies such as distributed generation, demand side management, energy storage elements, and new loads (e.g., electrical vehicles). The purpose is to convert 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 of intermittent sources, two way flows, and a set of elastic loads and storage elements which has a lot of similarities (and some striking differences) with the Internet. This proposal aims to address several of the fundamental challenges and system issues facing the Smart Grid by taking full advantage of the experiences (successes and failures) drawn from the Internet. As an example, the Internet robustness comes from its simple layered architecture and the use of distributed control mechanisms to prevent congestion and these mechanisms are high potential candidates for enabling demand side management. Internet researchers have had to design for the unknown, both the 'generation' of content and the demands are random, and new applications come regularly to test the robustness of the Internet design. The existing grid is relatively centralized and predictable, while the Smart Grid will be highly distributed and stochastic making the design for the unknown a necessity. In the existing grid, the electric utility controls the supply so that it follows the (quasi-uncontrolled) loads. One of the main paradigm shifts linked to the Smart Grid is supply following, i.e., the fact that due to the high penetration of new intermittent energy sources (e.g., wind and solar) and the need for cost efficiency, loads will need to be controlled to match variable generation while minimizing the impact on the consumers (by taking advantage of their inherent flexibility) or 'impedance matching' via energy storage will need to be performed. Our long term objective is to address the challenge of supply following by considering two (complementary) approaches, one based on energy storage and one based on characterizing and taking advantage of load flexibility. More specifically, we will address the following 5 medium-term objectives: a) Characterizing and quantifying load flexibility using techniques from stochastic calculus. b) Defining mechanisms and protocols to manage load flexibility using techniques from distributed algorithms, control, and convex analysis. c) Fast time-scale supply following using an energy storage aggregator using optimization and real-time distributed algorithms techniques. d) Studying a realistic supply following scenario involving several energy storage aggregators using optimization and real-time distributed algorithms techniques. e) A clean-slate approach to the smart grid: from new service models to an enhanced architecture. The outcome of this research will significantly advance the state of the art on supply following and the Smart Grid in general. It will be key to the development of Smart Grids in Canada and elsewhere. It will help Canadian industries (which are already important global players in the power sector) to continue to lead in this area that is critical to our economy. The projects will also provide excellent HQP training opportunities at the PhD and Master's levels.