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Yang Weng

Postdoctoral Research Fellow

Year Awarded: 2015

Research Lab: Ram Rajagopal


Yang Weng received a Ph.D. in August 2014 in electrical and computer engineering from Carnegie Mellon University, where he also earned an M.S. in machine learning. Prior to that, he received an M.S. in statistics from University of Illinois-Chicago, and a bachelor's degree in electrical engineering from Huazhong University of Science and Technology (HUST) in China. Weng's research focuses on the estimation and optimization of power systems, especially the link between physics and data. He won the Best Paper Award at the 2012 and 2013 International Conference on Smart Grid Communication. In 2014, his paper was named one of the best papers at the IEEE Power and Energy Society General Meeting. His work was also recognized by an ABB fellowship. Most recently, Weng has accepted a faculty offer from Arizona State University. He will likely start his faculty career in January 2017.

Consuming Renewable Power: Information and Reliability as a Resource

Increasingly utilities are integrating more renewable energy resources to meet the rapid growth in electricity consumption and energy-portfolio targets. However, reliable integration of renewable energy on the grid is challenging, because these resources are intermittent and variable. This generation uncertainty is a concern for system operators who try to balance supply and demand. A key strategy to address this challenge is demand-side management (DSM) or load management; examples include demand response, energy efficiency, or pricing programs. DSM strategies examine the potential of offering new services for managing customer load so that demand for energy can be tailored to meet the varying supply conditions at throughout the day and at different time scales. There are generally two types of DSM programs: event-based and intervention-based. Event-based programs involve the temporary management of electricity consumption over a period of time (minutes up to a few hours) in response to either emerging overload conditions or projected spikes in wholesale market prices. An intervention-based program, on the other hand, is a one-time commissioning that permanently changes a feature that affects energy consumption. Examples include installation of PV panels or implementation of a new electricity rate tariff (pricing) to manage consumption. Benefits of DSM programs may include long-term financial savings and managing supply and demand in transition to a sustainable grid. The most important measure of benefit is the estimated energy saving for each individual after an intervention or during a demand-response event. Thus, accurate saving estimates are crucial for ensuring high program enrollment.