Distribution Systems Resilience Improvement Utilizing Multiple Operational Resources

• Type: Article in International Conference Proceedings Book
• Date: 2021

Authors

Ortiz, JMH (Author) Other; Melgar-Dominguez, OD (Author) Other; Javadi, MS (Author) Other; Santos, SF (Author) Other; Mantovani, JRS (Author) Other; Catalao, JPS (Author) FEUP

Conference proceedings International

Title: 2021 21ST IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2021 5TH IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC/I&CPS EUROPE)

21st IEEE International Conference on Environment and Electrical Engineering / 5th IEEE Industrial and Commercial Power Systems Europe (EEEIC/I and CPS Europe)

Politecnico Bari, Bari, ITALY, SEP 07-10, 2021

Indexing

ISI Web of Knowledge - 4 Citations

Scopus - 5 Citations

Other information

Authenticus ID: P-00W-BCP

DOI: 10.1109/eeeic/icpseurope51590.2021.9584831

Abstract (EN): This paper presents a strategy based on mixedinteger linear programing (MILP) model to improve the resilience in electric distribution systems (EDSs). The restoration process considers operational resources such as the optimal coordination of dynamic switching operations, islanding operation of distributed generation (DG) units, and displacement of mobile emergency generation (MEG) units. In addition, the benefits of considering a demand response (DR) program to improve the recoverability of the system are also studied. The switching operations aim to separate the in-service from the out-of-service part of the system keeping the radiality of the grid. The proposed MILP model is formulated as a stochastic scenario-based problem where the uncertainties are associated with PV-based power generation and demand consumption. The objective function minimizes the amount of energy load shedding after fault, and the generation curtailment of the PV-based DG. To validate the proposed strategy, a 33-bus EDS is analyzed under different test cases. Results show the benefits of coordinating the dynamic switching operations, the optimal scheduling of MEG units, and a demand response program during the restoration process.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 6