DRO‐MPC‐based data‐driven approach to real‐time economic dispatch for islanded microgrids. Issue 24 (29th October 2020)

• Record Type: Journal Article
• Authors: Lyu, Cheng; Jia, Youwei; Xu, Zhao
• Is Part Of: IET generation, transmission & distribution. Volume 14:Issue 24(2020)
• Page Start: 5704
• Page End: 5711
• Publication Date: 2020-10-29
• Subjects: 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; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2020.0849
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : 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.