A day-ahead market clearing mechanism for nodal carbon intensity control using the flexibility of charging stations. (May 2023)

• Record Type: Journal Article
• Authors: Ligao, Junjie; Yang, Jun; Li, Huiying; Shao, Lizheng; Xiao, Yi; Qin, Shaoming; Zhu, Xu; Wu, Fuzhang
• Is Part Of: International journal of electrical power & energy systems. Volume 147(2023)
• Publication Date: 2023-05
• Subjects: Electric vehicles -- Generalized energy storage -- Carbon intensity control -- Energy market -- ADMM; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2022.108907
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A data-model hybrid driven approach is used to model the flexibility of the charging stations. An ADMM-based clearing mechanism considering the carbon intensity control is proposed. The flexibility of the charging stations is verified to be used to control the carbon intensity. Abstract: A large number of high-capacity charging stations are being built and will enter the wholesale electricity market as independent entities. Energy storage is considered to be an effective means of mitigating carbon emissions. When a large number of charging stations with storage capacity enter the market, how to make full use of their flexibility in the wholesale market to control the carbon intensity of the power system is an urgent problem to be solved. To address this problem, in this paper, a day-ahead market clearing mechanism for nodal carbon intensity control using the flexibility of charging stations is proposed, and a distributed clearing algorithm based on the alternating direction method of multipliers is designed. The local distribution network operators are used as intermediate coordinators, through which the market operator and the local charging station operators transmit system flexibility demands and energy schedules, respectively. Market clearing is completed through several iterations. This reduces the complexity of the unified clearing model. Moreover, based on the data-model hybrid driven approach, the generalized energy storage model of the charging stations and the linear nodal carbon intensity constraints of the power system are established. The locational marginal price considering the carbon emission cost is derived. The simulation verifies that using the flexibility of the charging stations to improve the power flow distribution of the power system can control the nodal carbon intensity with only 0.11% cost increase. The distributed algorithm has good convergence.