DRO-MPC-based data-driven approach to real-time economic dispatch for islanded microgrids

Lyu，Cheng1,2; Jia，Youwei1; Xu，Zhao2,3

2020-12-18

10.1049/iet-gtd.2020.0849

IET Generation Transmission & Distribution   影响因子和分区

1751-8687

1751-8695

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.

power generation control secondary cells distributed power generation optimisation power generation dispatch battery storage plants power generation economics energy storage predictive control numerical analysis battery energy storage systems novel degradation cost model online auction algorithm Wasserstein ambiguity set DRO-MPC-based data-driven approach real-time economic dispatch islanded microgrids rechargeable battery banks real-time management two-stage distributionally robust optimisation problem model predictive control numerical results

SCI ; EI

英语

第一 ; 通讯

High-level University Fund[G022360002] ; National Natural Science Foundation of China[71971183]

Engineering

Engineering, Electrical & Electronic

WOS:000596021500002

INST ENGINEERING TECHNOLOGY-IET

20205009615096

Predictive control systems ; Digital storage ; Electric load dispatching ; Secondary batteries ; Scheduling ; Battery storage ; Combinatorial optimization ; Real time systems

Energy Storage:525.7 ; Secondary Batteries:702.1.2 ; Electric Power Transmission:706.1.1 ; Data Storage, Equipment and Techniques:722.1 ; Digital Computers and Systems:722.4 ; Control Systems:731.1 ; Management:912.2 ; Combinatorial Mathematics, Includes Graph Theory, Set Theory:921.4 ; Optimization Techniques:921.5

2-s2.0-85097355009

Scopus

1.Department of Electrical and Electronic Engineering,Southern University of Science and Technology,Shenzhen,China
2.Department of Electrical Engineering,Hong Kong Polytechnic University,Hong Kong,Hong Kong
3.Shenzhen Research Institute,Hong Kong Polytechnic University,Hong Kong,Hong Kong

Lyu，Cheng,Jia，Youwei,Xu，Zhao. DRO-MPC-based data-driven approach to real-time economic dispatch for islanded microgrids[J]. IET Generation Transmission & Distribution,2020,14(24):5816-5822.

Lyu，Cheng,Jia，Youwei,&Xu，Zhao.(2020).DRO-MPC-based data-driven approach to real-time economic dispatch for islanded microgrids.IET Generation Transmission & Distribution,14(24),5816-5822.

Lyu，Cheng,et al."DRO-MPC-based data-driven approach to real-time economic dispatch for islanded microgrids".IET Generation Transmission & Distribution 14.24(2020):5816-5822.