Artificial Neural Network-based Methodology for Short-Term Electric Load Scenario Generation

• Type: Article in International Conference Proceedings Book
• Date: 2015

Authors

Vagropoulos, SI (Author) Other; Kardakos, EG (Author) Other; Simoglou, CK (Author) Other; Bakirtzis, AG (Author) Other; Catalao, JPS (Author) FEUP

Conference proceedings International

Title: 2015 18th International Conference on Intelligent System Application to Power Systems (ISAP)

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 5 Citations

Other information

Authenticus ID: P-00K-C5A

DOI: 10.1109/isap.2015.7325540

Abstract (EN): In this paper a novel scenario generation methodology based on artificial neural networks (ANNs) is proposed. The methodology is able to create scenarios for various power system-related stochastic variables. Scenario reduction methodologies can then be applied to effectively reduce the number of scenarios. An application of the methodology for the creation of short-term electric load scenarios for one day up to seven days ahead is presented. Test results on the real-world insular power system of Crete present the effectiveness of the proposed methodology.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6