Mixed‐integer second‐order cone programming framework for optimal scheduling of microgrids considering power flow constraints. Issue 14 (24th September 2019)

• Record Type: Journal Article
• Authors: Fu, Long; Meng, Ke; Liu, Bin; Dong, Zhao Yang
• Is Part Of: IET renewable power generation. Volume 13:Issue 14(2019)
• Page Start: 2673
• Page End: 2683
• Publication Date: 2019-09-24
• Subjects: linear programming -- power generation dispatch -- power generation scheduling -- scheduling -- optimisation -- integer programming -- load flow -- distributed power generation -- distribution networks; mixed integer second‐order cone programming framework -- dynamical properties -- optimal energy scheduling problem -- microgrids -- optimal scheduling -- power flow constraints -- promising but challenging research topics -- tertiary level control -- existing centralised distributed scheduling models -- logical feature -- dynamical feature -- nonlinear power flow constraint -- appropriate unit commitment requirements -- applying decomposition -- iteration technics -- complex scheduling problems -- mixed integer linear reformulation -- different controllable devices; Renewable energy sources -- Periodicals; 333.79405
• DOI: 10.1049/iet-rpg.2019.0305
• Languages: English
• ISSNs: 1752-1416

Abstract

Abstract : Microgrids have been recognised as one of the most promising but challenging research topics over the last decade. The optimal energy scheduling problem is regarded as the most essential aspect in the tertiary level control in microgrids. However, most existing centralised or distributed scheduling models only focus on the logical and dynamical feature of microgrids' operation or the non‐linear power flow constraint, which would overact the system performance without considering appropriate unit commitment requirements. Moreover, applying decomposition and iteration technics to complex scheduling problems would encounter convergence issues. To address this concern, this study presents a mixed integer linear reformulation to characterise the operation of different controllable devices and convex relaxation techniques to cope with non‐linear power flow constraints, leading to a mixed integer second‐order cone programming framework in a concordant yet computationally efficient pattern, capturing non‐linear, logical and dynamical properties of the optimal energy scheduling problem in microgrids. The effectiveness of the proposed framework is validated on the IEEE 33‐bus distribution network with both grid‐connected and islanded modes.