Toward coordinated look‐ahead reactive power optimisation for distribution networks with minimal control. Issue 11 (24th April 2018)

• Record Type: Journal Article
• Authors: Ding, Min; Chiang, Hsiao‐Dong; Li, Peng
• Is Part Of: IET generation, transmission & distribution. Volume 12:Issue 11(2018)
• Page Start: 2707
• Page End: 2717
• Publication Date: 2018-04-24
• Subjects: power distribution control -- reactive power control -- integer programming -- nonlinear programming -- minimisation -- power transformers -- power capacitors -- distributed power generation -- pattern clustering -- load flow -- power generation control; distribution network -- coordinated look‐ahead reactive power optimisation method -- mixed integer nonlinear programming problem -- MINLP problem -- transformer tap -- capacitor bank -- reactive power output -- distributed generator -- DG -- day‐ahead load demand -- active power output -- assessment stage method -- time‐period‐partitioning stage method -- coordinated reactive power optimisation stage method -- time‐period‐partitioning stage -- clustering algorithm -- power‐flow solution -- modified IEEE13 case study -- IEEE123 case study -- time 24 h; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2017.1367
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : A coordinated look‐ahead reactive power optimisation method is proposed to minimise the required number of operating control devices for a time horizon of 24 h. The aim is to determine, via solving a mixed integer non‐linear programming (MINLP) problem, optimum value settings of transformer taps, capacitor banks and reactive power output of distributed generators (DGs) based on the day‐ahead load demand and active power output of DGs satisfying the engineering and operational constraints. The proposed method employs a three‐stage method: assessment stage, time‐period‐partitioning stage, and coordinated reactive power optimisation stage. The first stage assesses the hourly voltage profile and available delivery capability margin of the system, while the time‐period‐partitioning stage uses clustering algorithm based on power‐flow solution to partition time periods into coherent time durations. The MINLP problem is solved in the proposed coordinated optimisation stage. A modified IEEE13 case and IEEE123 case are used to verify the effectiveness of the proposed three‐stage method.