The project will research, develop, and demonstrate technology that enables the modulation of controllable household loads, to provide multiple grid services, including peak capacity management, ramp support, and frequency regulation.\u00a0 We will show how the fusion of data from multiple sources, including communicating thermostats, smart appliances, weather forecasts, utility bills, solar production data, and interval electric meter data can be used as inputs to a grey-box model of household net load to increase the accuracy of generation and load forecasts.\u00a0 Model predictive control (MPC) will be used to plan the electricity use by flexible resources at individual dwellings while accounting for factors such as occupant comfort and resource availability.\u00a0 Responsive loads will be aggregated and used to offer demand response in a globally optimal fashion according to pre-defined policy objectives, using pricing as a feedback signal to coordinate the behavior of individual nodes.<\/p>\n
The work in Paschalidis\u2019 Network Optimization and Control (NOC) laboratory will focus on designing a methodology for coordinating decisions at individual homes through the use of a coordination agent<\/em> that receives information about predicted behavior for individual nodes and determines optimal aggregated response based on the specific combination of services on offer.\u00a0 For this component, we will use a pricing feedback signal to induce coordinated, yet distributed, load balancing among individual nodes, while taking into account inferred comfort preferences using an inverse optimization methodology we have developed in earlier work.\u00a0 The proposed approach will decentralize<\/em> these decisions; designing a mechanism with which detailed load-scheduling decisions are made locally and the information exchanged between the individual homes and the coordination agent reduces to a pricing signal communicated to individual homes and a response communicated to the coordination agent.<\/p>\n PI<\/strong>: Dr. Michael Zeifman, (Fraunhofer Center for Manufacturing Innovation,<\/span>\u00a0U.S.A<\/a>.)<\/p>\n Other Senior Personnel:<\/strong> Dr. Kurt Roth (Fraunhofer), Matt Kromer (Fraunhofer), Professor Yannis Paschalidis<\/a> (Boston University), Dr. George Zavaliagkos\u00a0 (Sense Labs<\/a>), Mr. Chris Micali (Sense Labs), Mr. Michael Phillips (Sense Labs).<\/p>\n