Final Report Summary - BUILDNET (Smart Building Networks) The BuildNet project focuses on the use of a collection of commercial buildings to provide ancillary services, or balancing energy, to the smart grid. Our goal is to develop optimization and control methods for this purpose, and then to demonstrate their practical and economic efficacy. A website detailing the activities of the project can be found at https://sites.google.com/site/buildnetproject/__ Simulation of Building Networks __openBuildNet is a co-simulation platform that provides a framework for large-scale distributed control and simulation of complex multi-agent systems. The platform is capable of coupling and synchronizing different external computation agents, which can include simulation and control software processes running on separate processors, as well as hardware components, allowing parallel computations and hardware in the loop integration. A supervisor maintains a global clock to manage the progress of all agents and ensures the correctness of the co-simulation. A modeling and simulation environment, openBuild, has been developed that automatically produces optimization appropriate models from detailed building physics simulations, and couples this with financial and environmental data to form an accurate representation of the physics and economics of a European building participating in an energy market. openBuildNet is available on the project website.__ Distributed Control of Smart Building Networks __The team has developed novel distributed optimization methods that are best suited to the control of large collections of buildings. Methods have been developed that accelerate the large-scale convex optimization problems that we observe during the planning phase and deployment of ancillary service provision. Such developments are critical to enable the use of distributed optimization methods for control with tight real-time deadlines, such as for higher-frequency demand-response services (e.g. primary and/or secondary ancillary services). Distributed optimization methods for non-convex problems have been developed, which are required for managing the virtual storage represented by a collection of commercial buildings in a distribution grid, which can be used to control power flow. We have developed non-convex parametric optimization techniques, that are ideal for managing large-scale fast-changing systems, and have demonstrated their efficacy in power-system simulations.__ Optimal Utilization of Network Assets __A key question that the team has been examining is that of the "bidding problem", or the question of how flexible a building can be in terms of power consumption, without causing discomfort for the occupants. A novel approach based on concepts from robust optimization and predictive control has been developed, that allows the mathematical reduction of a building system to a simple battery, which can then be sold on the open market, or used to manage a distribution grid.__ Analysis of the BuildNet Concept __The team has analyzed the concept of using commercial buildings for demand-response using the simulation environment and techniques developed. Findings indicate that accurate control of the thermal state of buildings can act as a strong 'force multiplier' taking charge of the minutes-to-hours storage range when combined with high-frequency battery storage and efficient long-term storage. In addition, we have found the surprising result, that it is possible to significantly improve the comfort of occupants at a significantly reduced cost, when offering services to the grid by modulating power consumption. Experimental studies have been undertaken on the EPFL campus, which compile all of the developed results and prove the concept of high-frequency demand response using occupied commercial buildings. Results are reported on the project website.
