Dr. Yang Chen
Oak Ridge National Lab
Friday, September 7, 2018
2:30-3:30pm JDT 410
Recently, existing research has demonstrated that more benefits of energy cost saving, environmental sustainability and reliable power supply can be achieved by clustering micro-grids together to freely exchange information and energy. To enable efficient transactive operation among micro-grids in the cluster, both centralized and distributed decision approaches are developed in the past decades. However, most of the existing approaches are only applicable for small scale micro-grid clusters and/or the privacy of each stakeholder (e.g., micro-grid) is not well protected. To bridge these research gaps, we propose a swarm intelligence based bi-level distributed decision approach. A particle swarm optimizer is employed at the system level to coordinate the transactive operations among micro-grids, and a mixed integer programming model is developed for each micro-grid to simultaneously obtain operation decisions for its energy systems. The performance of the proposed decision approach in terms of accuracy, scalability, and robustness is evaluated using various micro-grid clusters with the number of micro-grids from 2 to 256. It is demonstrated that our proposed approach is very computationally efficient, scalable and robust, and the computational complexity is O(n) where n is the number of micro-grids in the cluster. To further decrease model complexity and utilize updated information, model predictive control approaches have also been embedded in the stochastic operation.
Dr. Yang Chen is a postdoc research associate in Environmental Science Division at Oak Ridge National Laboratory, start from April, 2018. Currently, he is involved in hydro value study and modular pump storage project where he has built an operation model to estimate the maximum potential revenue for a novel energy storage GLIDES system in different electricity market ISO/RTO. He can be contacted at firstname.lastname@example.org
Prior to ORNL, Yang was a doctoral student at University of Illinois at Chicago, majored in Industrial & System Engineering under supervision of Dr. Mengqi Hu. The title of his PhD thesis is “Uncertainty-Aware Transactive Operation Decisions for Grid-Friendly Building Clusters”. His research is focused on energy system operation in smart buildings, and developing efficient coordinating algorithms for building level micro-grids to exchange and trade energy in emerging local energy transaction market. He is particularly interested and has great passion in renewable energy technologies and smart grid optimization. His other research interests include EV-Building integration, swarm intelligence algorithms, distributed decision making.