Energy Management as a Service (EMaaS)

Smart grid enables the two-way communication between the electricity utility and its customers and adopts new technologies such as electric vehicle and distributed energy resources (e.g., solar, wind). The heterogeneous environment in smart grid with the emerging role as “prosumer” (consumer and producer) and the employed new technologies need sophisticated energy management tools to optimize the operations. Recent advances in cloud computing bring infrastructure, platform, and software as services to all users. Scalable and on-demand computing services are provisioned and released efficiently with minimal management effort to users. The service-oriented cloud computing provides an opportunity for building energy management tools to be shared by the smart grid community. We propose an extensive cloud-based framework to provide energy management as a service (EMaaS). Various purposes and types of the energy management services can be efficiently adopted in the cloud-based framework. In this talk, we will focus on the customer-oriented EMaaS for the distributed renewable owners and the realization of fair demand response with electric vehicle charging scheduling on EMaaS.

This talk will first introduce the smart grid and the cloud computing. Secondly, we will present the design of customer-oriented EMaaS that provides financial incentives to customers and enhance the renewable energy integration. Then we will illustrate the realization of fair demand response with EV charging scheduling on EMaaS. The analysis will also be discussed to evaluate the performance. The talk will be concluded with a brief discussion on my current work and future research directions.

Bio:

Dr. Chen is an Assistant Professor in Department of Computer Systems Technology at New York City College of Technology. She received her Ph.D. degree from Electrical and Computer Engineering department at Iowa State University under the supervision of Prof. Morris Chang. She received her B.S. degree in Communication Engineering from the National Central University in Taiwan, and M.S. degree in Electrical Engineering from Columbia University in New York City with her research advised by Prof. Nicholas Maxemchuk. Her Ph.D. works have covered the cloud-based energy management, demand response, and electric vehicle charging scheduling, and have been published in IEEE Transaction on Smart Grid. Her research interests lie within the scope of Smart Grid, large-scale data analysis, cloud computing, optimization, communication networking, security, and Internet of Thing. She received Best Student Award from National Central University. She is a member of IEEE, a member of IEEE- HKN, and Tau Beta Pi-The Engineering Honor Society.