Optimizing Nodal Demand Response in the Day-Ahead Electricity Market within a Smart Grid Infrastructure

• Type: Article in International Conference Proceedings Book
• Date: 2018

Authors

Neda Hajibandeh (Author) Other; Miadreza Shafie khah (Author) Other; Mehdi Ehsan (Author) Other; João P. S. Catalão (Author) FEUP

Conference proceedings International

Title: Proceedings - IEEE 16th International Conference on Industrial Informatics, INDIN 2018

Pages: 972-977

16th IEEE International Conference on Industrial Informatics, INDIN 2018

18 July 2018 through 20 July 2018

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

INSPEC

Other information

Authenticus ID: P-00P-TE7

DOI: 10.1109/indin.2018.8472049

Abstract (EN): Developments of the smart grid infrastructure can facilitate the upsurge of Demand Response (DR) share in power system resources. This paper models the effects of Demand Response Programs (DRPs) on the behavior of the electricity market in the Day-Ahead (DA) session. Decision makers look for the best DR tariff to employ it as a tool to obtain a flexible and sustainable energy market. Employing the most effective DRP is of crucial importance. An optimized DR model and the optimum rates for each DRP are found to meet the decision makers' requirements. Optimizing the nodal tariff and incentive values of different DRPs are proposed in the electricity market. In such environment, market interactions are considered by means of a security constrained unit commitment problem. Both types of Price-Based Demand Response (PBDR) and Incentive-Based Demand Response (IBDR) are modeled. The numerical results presented indicate the effectiveness of the proposed model.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6