报告题目：Joint Control of Manufacturing and Onsite Microgrid System via Markov Decision Processes and Reinforcement Learning
报告人：胡文清（密苏里州罗拉市密苏里科技大学）
报告时间：2022年6月10日9:00-10:30
报告地点：腾讯会议ID:602 612 928
摘要：Onsite microgrid generation systems with renewable sources are considered a promising complementary energy supply system for manufacturing plant, especially when outage occurs during which the energy supplied from the grid is not available. Compared to the widely recognized benefits in terms of the resilience improvement when it is used as a backup energy system, the operation along with the electricity grid to support the manufacturing operations in non-emergent mode has been less investigated. In this talk, we propose a joint dynamic decision-making model for the optimal control for both manufacturing and onsite microgrid generation systems via delicate Markov Decision Process (MDP) modeling. The proposed MDP model is then solved using various neural-network integrated reinforcement learning algorithms. Real-data experiments for a manufacturing system with an onsite microgrid with renewable sources have been implemented to identify optimal control actions for both manufacturing system and microgrid components towards cost optimality. The presentation is based on joint works with Zeyi Sun, Yunchao Zhang, Yu Li, Jiaojiao Yang and Louis Steimeister.
报告人简介：
胡文清博士于2008年获得中国北京大学应用数学学士学位，2013年获得美国马里兰州大学帕克分校数学博士学位。他目前是美国密苏里州罗拉市密苏里科技大学数学与统计系的数学副教授。主要研究方向是概率论和统计方法。他一直致力于数据科学、统计机器学习和优化领域的问题。
