Dynamic pricing for decentralized energy trading in micro-grids. (15th October 2018)

• Record Type: Journal Article
• Authors: Liu, Youbo; Zuo, Kunyu; Liu, Xueqin (Amy); Liu, Junyong; Kennedy, Jason M.
• Is Part Of: Applied energy. Volume 228(2018)
• Page Start: 689
• Page End: 699
• Publication Date: 2018-10-15
• Subjects: Micro-grids -- Aggregator -- Dynamic pricing -- Decentralized energy trading -- Multi-agent system -- JADE; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2018.06.124
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: The marginal cost of renewable generation is deduced by generation uncertainty. Value of single charging/discharging action for energy storage can be quantified. A three-tiered optimization maximizes profits for participants within micro-grids. The profits for owners and aggregators are cleared through a win-win framework. Abstract: The fast deployment of distributed energy resources in the electric power system has highlighted the need for an efficient energy trading transactive model, without the need for centralized dispatch. In this field, a particular challenge is the determination of an effective pricing scheme that is able to produce benefits for all participants. In this paper, a novel dynamic pricing methodology is presented, offering a market-oriented means to drive decentralized energy trading and to optimize financial benefits for owners of distributed energy resources. Firstly, a price-responsive model for each type of distributed energy resource is investigated. Particularly, the decoupled State of Charge function is proposed to calculate the value of a single charging/discharging action for energy storage systems. In addition, an adaptable three-tiered framework is designed, including micro-grid balancing, aggregator scheduling, and trading optimization. By launching Tier I, II, and III, the spot prices for participants are iteratively updated and optimized in inner-micro-grid, inner-aggregator, and inter-aggregators level. The framework is able to maximize the financial savings from renewable energy, and meanwhile, provide a dynamic price signal to assist stakeholders in determining response actions and trading strategies. A realistic case is simulated using Java Agent Development framework based multi-agent modeling. The results indicate that the presented methodology enables decentralized energy trading and permits easier marketization of micro-grids with a high share of distributed energy resources.