TY - JOUR
T1 - DRO-MPC-based data-driven approach to real-time economic dispatch for islanded microgrids
AU - Lyu, Cheng
AU - Jia, Youwei
AU - Xu, Zhao
N1 - Funding Information:
This paper was supported in part by High-level University Fund G022360002, and the National Natural Science Foundation of China (71971183).
Publisher Copyright:
© The Institution of Engineering and Technology 2020
PY - 2020/12/18
Y1 - 2020/12/18
N2 - Rechargeable battery banks have been widely utilised in islanded microgrids as energy storage systems to complement the instant power imbalance in real-time. However, the cycle degradation becomes an unavoidable concern of the battery energy storage systems (BESSs) in achieving microgrid economic dispatch (ED). In this study, a novel degradation cost model based on an online auction algorithm is proposed for real-time management of BESS. To settle the intermittent distributed sources in real-time operation, a Wasserstein ambiguity set is adopted to characterise the uncertainties. Meanwhile, the authors newly reformulate the real-time microgrid ED as a two-stage distributionally robust optimisation (DRO) problem. To improve the tractability and scalability of the DRO problem, a model predictive control (MPC)-based data-driven approach is proposed, in which a novel affine policy namely extended event-wise affine adaption is properly employed. Through extensive case studies, the numerical results demonstrate the effectiveness of the proposed approach.
AB - Rechargeable battery banks have been widely utilised in islanded microgrids as energy storage systems to complement the instant power imbalance in real-time. However, the cycle degradation becomes an unavoidable concern of the battery energy storage systems (BESSs) in achieving microgrid economic dispatch (ED). In this study, a novel degradation cost model based on an online auction algorithm is proposed for real-time management of BESS. To settle the intermittent distributed sources in real-time operation, a Wasserstein ambiguity set is adopted to characterise the uncertainties. Meanwhile, the authors newly reformulate the real-time microgrid ED as a two-stage distributionally robust optimisation (DRO) problem. To improve the tractability and scalability of the DRO problem, a model predictive control (MPC)-based data-driven approach is proposed, in which a novel affine policy namely extended event-wise affine adaption is properly employed. Through extensive case studies, the numerical results demonstrate the effectiveness of the proposed approach.
UR - http://www.scopus.com/inward/record.url?scp=85097355009&partnerID=8YFLogxK
U2 - 10.1049/iet-gtd.2020.0849
DO - 10.1049/iet-gtd.2020.0849
M3 - Journal article
AN - SCOPUS:85097355009
SN - 1751-8687
VL - 14
SP - 5704
EP - 5711
JO - IET Generation, Transmission and Distribution
JF - IET Generation, Transmission and Distribution
IS - 24
ER -