Bi-Level Programming-Based Optimal Strategy to LSEs with Demand Response Bids. Issue 18 (8th November 2018)

• Record Type: Journal Article
• Authors: Ding, Tao; Yang, Qingrun; Jiang, Jiangfeng; Yang, Yongheng; Blaabjerg, Frede; Li, Yaohong; Ju, Yuntao
• Is Part Of: Electric power components and systems. Volume 46:Issue 18(2018)
• Page Start: 1926
• Page End: 1937
• Publication Date: 2018-11-08
• Subjects: demand response -- mixed integer second-order cone programming -- optimal strategy -- bi-level programming -- load serving entities (LSEs); Electric machinery -- Periodicals; 621.3104205
• DOI: 10.1080/15325008.2018.1528315
• Languages: English
• ISSNs: 1532-5008

Abstract

Abstract: As a profit-seeking market participant, load serving entities (LSEs) have been trying to apply demand response (DR) programs to induce the demand elasticity to further their profit. However, due to the different preference of DRs, it is difficult for LSEs to generate the optimal strategic bidding strategy in the ISO/RTO's market. Therefore, this paper proposed a bi-level optimization model considering DR bidding to maximize the total profit of LSEs: conceptually, the consumers participate DR through setting their bidding prices to LSEs with respect to their own preference and LSEs should determine the optimal reward value of DR as well as the amount of demanded electricity; technically, an original method has been implemented to solve the bi-level optimization model. The closed form of shadow price function with respect to the total load demand is derived to reduce the complexity. Hence, the proposed model is converted to a mixed integer second order cone programming and able to achieve the global optimality. It needs to be note that the closed form of shadow price introduced in this paper can also be applied to other bi-level programming models. Moreover, case studies have been performed to demonstrate the validity of the proposed method.