Including Dynamic Security Constraints in Isolated Power Systems Unit Commitment/Economic Dispatch: a Machine Learning-based Approach

• Type: Article in International Conference Proceedings Book
• Date: 2023

Authors

de Sousa, RP (Author) Other; C. L. Moreira (Author) FEUP; Leonel Carvalho (Author) FEUP; Manuel Matos (Author) FEUP

Conference proceedings International

Title: 2023 IEEE BELGRADE POWERTECH

IEEE Belgrade PowerTech Conference

Belgrade, SERBIA, JUN 25-29, 2023

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

Other information

Authenticus ID: P-00Y-T83

DOI: 10.1109/powertech55446.2023.10202690

Abstract (EN): Isolated power systems with high shares of renewables can require additional inertia as a complementary resource to assure the system operation in a dynamic safe region. This paper presents a methodology for the day-ahead Unit Commitment/ Economic Dispatch (UC/ED) for low-inertia power systems including dynamic security constraints for key frequency indicators computed by an Artificial Neural-Network (ANN)-supported Dynamic Security Assessment (DSA) tool. The ANN-supported DSA tool infers the system dynamic performance with respect to key frequency indicators following critical disturbances and computes the additional synchronous inertia that brings the system back to its dynamic security region, by dispatching Synchronous Condensers (SC) if required. The results demonstrate the effectiveness of the methodology proposed by enabling the system operation within safe frequency margins for a set of high relevance fault type contingencies while minimizing the additional costs associated with the SC operation.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6