CAREER: Stochastic Multiple Time-Scale Co-Optimized Resource Planning of Future Power Systems with Renewable Generation, Demand Response, and Energy Storage

A recent NSF Career award was given to Dr.Wu in Clarkson University in the area of smart grid, combining optimization and power system planning and scheduling.


This PI will develop co-optimized generation, transmission, and DR planning solutions to cope with the impacts of short-term variability and uncertainty of renewable generation (RG) and demand response (DR) as well as hourly chronological operation details of energy storage (ES) and generators. The approach is to (1) propose a stochastic multiple time-scale co-optimized planning model that explicitly integrates short-term variability and uncertainty as well as hourly chronological operation into long-term planning; (2) develop efficient solution methodologies and implement on high performance parallel computing facilities. Intellectual Merit: The interaction among variability, uncertainty, and constraints from long-term planning and hourly chronological operation will be quantified for enhancing security and sustainability of power systems with significant RG, DR, and ES. This research can be used to evaluate effective load carrying capability (ELCC) of variable energy sources, and to study policies on portfolios of energy production and storage techniques. This study is of practical importance since RG, DR, and ES are being implemented worldwide and their distinctive contributions to energy security and sustainability need to be well understood.

Broader Impacts: This project has profound impacts on the sound deployment of RG, DR, ES, and smart grid. For example, it allows better treatment of investment options which require transmission and generation together, in order to exploit favorable sites for wind or solar. The research and educational findings would help educate engineers to meet challenges of the secure and sustainable electricity infrastructure. The project will increase public awareness and understanding of the complexity of power system planning, and appeal to researchers and educators with interests in power systems-based research and education.