Real-Time Demand Side Management for a Microgrid Considering Uncertainties
Document Type
Article
Date of Original Version
5-1-2019
Abstract
Different from most existing studies that focus on offline demand side management (DSM) in microgrids (MGs) while neglecting forecasting errors of uncertain renewable generations, this paper studies online DSM. A two-stage real-time DSM method for an MG including different time scales, integrated with schedulable ability (SA) and uncertainties, is proposed. In the first stage, a novel internal pricing model is developed. On this basis, a model predictive control-based dynamic optimization is applied to minimize the operation cost and maintain the power balance considering the uncertainties imposed by both supply and demand sides in the MG system. In the second stage, we define the concept of SA for response executors (REs) and also establish an SA evaluation system taking the real-time and history information of the REs into account. In doing so, a faster-time scale online power allocation among REs is carried out in the framework of dynamic optimization to further compensate for the uncertainties in real-time, based on the evaluated SA values of the REs and the required compensation power. Numerical simulations on a residential MG show the reasonableness and effectiveness of the proposed method.
Publication Title, e.g., Journal
IEEE Transactions on Smart Grid
Volume
10
Issue
3
Citation/Publisher Attribution
Yang, Xiaodong, Youbing Zhang, Haibo He, Shuaijie Ren, and Guoqing Weng. "Real-Time Demand Side Management for a Microgrid Considering Uncertainties." IEEE Transactions on Smart Grid 10, 3 (2019): 3401-3414. doi: 10.1109/TSG.2018.2825388.