Optimal Participation of DR Aggregators in Day-Ahead Energy and Demand Response Exchange Markets - Technological Innovation for Collective Awareness Systems (DoCEIS 2014) Access content directly
Conference Papers Year : 2014

Optimal Participation of DR Aggregators in Day-Ahead Energy and Demand Response Exchange Markets

Abstract

Aggregating the Demand Response (DR) is approved as an effective solution to improve the participation of consumers to wholesale electricity markets. DR aggregator can negotiate the amount of collected DR of their customers with transmission system operator, distributors, and retailers in Demand Response eXchange (DRX) market, in addition to participate in the energy market. In this paper, a framework has been proposed to optimize the participation of a DR aggregator in day-ahead energy and intraday DRX markets. In this regard, the DR aggregator optimizes its participation schedule and offering/bidding strategy in the mentioned markets according to behavior of its customers. For this purpose, the customers’ participation is modeled using a Supply Function Equilibrium (SFE) model. In addition, due to uncertainties of market prices and the behavior of consumers, an appropriate risk measurement, CVaR, is incorporated to the optimization problem. The numerical results show the effectiveness of the proposed framework.
Fichier principal
Vignette du fichier
978-3-642-54734-8_39_Chapter.pdf (4 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01274797 , version 1 (16-02-2016)

Licence

Attribution

Identifiers

Cite

Ehsan Heydarian-Forushani, Miadreza Shafie-Khah, Maziar Yazdani Damavandi, João S. Catalão. Optimal Participation of DR Aggregators in Day-Ahead Energy and Demand Response Exchange Markets. 5th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Apr 2014, Costa de Caparica, Portugal. pp.353-360, ⟨10.1007/978-3-642-54734-8_39⟩. ⟨hal-01274797⟩
134 View
130 Download

Altmetric

Share

Gmail Facebook X LinkedIn More