Reliability constrained decision model for energy service provider incorporating demand response programs. (1st December 2016)

• Record Type: Journal Article
• Authors: Mahboubi-Moghaddam, Esmaeil; Nayeripour, Majid; Aghaei, Jamshid
• Is Part Of: Applied energy. Volume 183(2016)
• Page Start: 552
• Page End: 565
• Publication Date: 2016-12-01
• Subjects: Energy service provider (ESP) -- Demand response (DR) -- Day-ahead market -- Smart distribution network -- Reliability -- Robust optimization; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2016.09.014
• Languages: English
• ISSNs: 0306-2619

Abstract

Graphical abstract: Highlights: The operation of Energy Service Providers (ESPs) in electricity markets is modeled. Demand response as the cost-effective solution is used for energy service provider. The market price uncertainty is modeled using the robust optimization technique. The reliability of the distribution network is embedded into the framework. The simulation results demonstrate the benefits of robust framework for ESPs. Abstract: Demand response (DR) programs are becoming a critical concept for the efficiency of current electric power industries. Therefore, its various capabilities and barriers have to be investigated. In this paper, an effective decision model is presented for the strategic behavior of energy service providers (ESPs) to demonstrate how to participate in the day-ahead electricity market and how to allocate demand in the smart distribution network. Since market price affects DR and vice versa, a new two-step sequential framework is proposed, in which unit commitment problem (UC) is solved to forecast the expected locational marginal prices (LMPs), and successively DR program is applied to optimize the total cost of providing energy for the distribution network customers. This total cost includes the cost of purchased power from the market and distributed generation (DG) units, incentive cost paid to the customers, and compensation cost of power interruptions. To obtain compensation cost, the reliability evaluation of the distribution network is embedded into the framework using some innovative constraints. Furthermore, to consider the unexpected behaviors of the other market participants, the LMP prices are modeled as the uncertainty parameters using the robust optimization technique, which is more practical compared to the conventional stochastic approach. The simulation results demonstrate the significant benefits of the presented framework for the strategic performance of ESPs.