Optimal Real-Time Operation Strategy for Microgrid: An ADP-Based Stochastic Nonlinear Optimization Approach
Document Type
Article
Date of Original Version
4-1-2019
Abstract
This paper proposes an approximate dynamic programming (ADP) based algorithm for the real-time operation of the microgrid under uncertainties. First, the optimal operation of the microgrid is formulated as a stochastic mixed-integer nonlinear programming (MINLP) problem, combining the ac power flow and the detailed operational character of the battery. For this NP-hard problem, the proposed ADP based energy management algorithm decomposes the original multitime periods MINLP problem into single-time period nonlinear programming problems. Thus, the sequential decisions can be made by solving Bellman's equation. Historical data is utilized offline to improve the optimality of the real-time decision, and the dependency on the forecast information is reduced. Comparative numerical simulations with several existing methods demonstrate the effectiveness and efficiency of the proposed algorithm.
Publication Title, e.g., Journal
IEEE Transactions on Sustainable Energy
Volume
10
Issue
2
Citation/Publisher Attribution
Shuai, Hang, Jiakun Fang, Xiaomeng Ai, Jinyu Wen, and Haibo He. "Optimal Real-Time Operation Strategy for Microgrid: An ADP-Based Stochastic Nonlinear Optimization Approach." IEEE Transactions on Sustainable Energy 10, 2 (2019): 931-942. doi: 10.1109/TSTE.2018.2855039.