Autonomous Energy Consumption Management and Load Control in the Smart Grid: a Control-Theoretic Perspective

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This research program aims at developing strategies for autonomous energy consumption management (ECM) and load control (LC) from costumer's side (demand side) in the context of the smart grid. In recent years, an extremely important effort from the scientific community, industry, and public sectors has been devoted to the development of the paradigm of smart grids aiming at upgrading electric power networks to ensure an efficient and reliable energy production and delivery in the next century while minimizing and postponing massive investments on infrastructures. It is known that the concept of the Smart Grid is concerned with a wide variety of elements in electric power networks, from power generation to its transmission, distribution, and consumption. This research program will focus on the segment of consumption, despite the strong interactions between different segments in an electric power network. To this aim, the research will be carried out in the framework of Demand-Side Management (DSM). The proposed research will be based on a layered architecture for energy consumption management and load control developed in our recent research on the related topics. This architecture can encapsulate the functionality of demand-side energy management, assure the interoperability between various components, allow for the integration of different energy sources, ease system maintenance and upgrading, and provide a convenient means for the interaction of utilities and consumers in the context of the Smart Grid. In the proposed research program, we will apply the method of Model Predictive Control (MPC) to the operation of thermostatically controlled loads (TCLs) and HVAC (heating, ventilation, and air-condition) systems. We will then develop algorithms for the scheduling of different type of loads and the integration of energy storage and renewable energy sources. To provide a comprehensive solution, we will address the issues related to handling, in particular, Demand-Response (DR) to enable a dynamic interaction between utilities and end-use consumers. We will also address issues related to the concerns raised in practical applications, in particular performance guarantees in the presence of nonlinearity, modeling errors, parametric uncertainties, and communication imperfection. For this purpose, we will consider the application of robust and adaptive MPC and Lyapunov theory. Another research venue of this program is the modeling and control of aggregated large population of TCLs. As this problem may lead to models described by partial differential equations (PDEs), a particular effort will be put on the application of PDE control theory and techniques to achieve optimal distributed control schemes. Finally, we plan to build software platforms for the validation of the developed solutions and to conduct experimentations with real-life systems via industrial collaborations.