Bi‐level optimiseddispatch strategy of electric supply–demand balance considering risk–benefit coordination. Issue 4 (14th November 2018)

• Record Type: Journal Article
• Authors: Xu, Qingshan; Ji, Yongli; Huang, Qifeng; Sheng, Yehong
• Is Part Of: IET smart grid. Volume 1:Issue 4(2018)
• Page Start: 169
• Page End: 176
• Publication Date: 2018-11-14
• Subjects: optimisation -- power generation economics -- demand side management -- smart power grids -- decision making -- power markets -- power generation dispatch; level optimised dispatch strategy -- electric supply–demand balance -- risk–benefit coordination -- smart grid -- electricity market -- schedulable resources -- great concern -- power supply -- bi‐level system -- bi‐level programming -- ISO -- load aggregator -- bidding plans -- improved step‐wise bidding method -- risk attitudes -- upper level -- chance‐constrained programming method -- bi‐level optimised strategy -- decision makers -- decentralised schedulable resources; B0260 Optimisation techniques -- B8110B Power system management, operation and economics; Smart power grids -- Periodicals; Computer science -- Periodicals; Energy industries -- Periodicals; Broadcasting -- Periodicals; 333.79110285
• DOI: 10.1049/iet-stg.2018.0003
• Languages: English
• ISSNs: 2515-2947

Abstract

Abstract : With the development of smart grid and electricity market, schedulable resources of demand‐side attract great concern. To implement the balance between power supply and demand by utilising demand‐side schedulable resources, a bi‐level system is established and a bi‐level programming between independent system operator (ISO) and load aggregator (LA) is proposed in this study. LA in the lower level integrates decentralised schedulable resources and makes bidding plans by adopting the improved step‐wise bidding method in view of its risk attitudes, realising the unification of low risk and high profit. ISO in the upper level introduces the chance‐constrained programming method to make risk–benefit coordinated decisions considering uncertainties on the basic of bidding information and power supply–demand prediction. The simulation analyses show that the proposed bi‐level optimised strategy is effective for obtaining satisfactory decision schemes based on decision makers' risk preferences.