Risk-Based Decision Support Model for the Optimal Operation of a Smart Energy Distribution Company for Enabling Emerging Resources

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

S. Muhammad Bagher Sadati (Author) Other; Jamal Moshtagh (Author) Other; Miadreza Shafie-khah (Author) Other; João P. S. Catalão (Author) FEUP

Conference proceedings International

Title: 52nd Hawaii International Conference on System Sciences, HICSS 2019, Grand Wailea, Maui, Hawaii, USA, January 8-11, 2019

Pages: 1-8

Indexing

Scopus - 1 Citation

Other information

Authenticus ID: P-00S-AZ3

Abstract (EN): In this paper, a risk-based decision support model is developed for a smart energy distribution company, enabling emerging resources like renewable energy sources, electric vehicles and demand response programs in a holistic approach. Because of the inherent uncertainties of these emerging resources, the conditional value-at-risk (CVaR) method is adopted to restrict the distribution company's risk. A risk aversion parameter sensitivity analysis is also provided on the optimal operation of the smart energy distribution company. The proposed model is thoroughly tested on a 15-bus distribution grid system, and the numerical results prove the effectiveness of the model in risk management.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7