Analysis of the blackout risk reduction when segmenting large power systems using lines with controllable power flow
| Autor: | D. Gomila, B.A. Carreras, J.M. Reynolds-Barredo, P. Colet, O. Gomis-Bellmunt |
|---|---|
| Přispěvatelé: | Ministerio de Ciencia e Innovación (España), Agencia Estatal de Investigación (España), European Commission, Ministerio de Ciencia, Innovación y Universidades (España), ICREA Acadèmia, Agència de Gestió d'Ajuts Universitaris i de Recerca, Ministerio de Economía y Competitividad (España), Universitat Politècnica de Catalunya. Departament d'Enginyeria Elèctrica, Universitat Politècnica de Catalunya. CITCEA-UPC - Centre d'Innovació Tecnològica en Convertidors Estàtics i Accionaments |
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: |
Energia elèctrica--Transmissió
History Telecomunicaciones Polymers and Plastics Enginyeria elèctrica [Àrees temàtiques de la UPC] HVDC lines Física Energy Engineering and Power Technology Blackout risk control Industrial and Manufacturing Engineering Grid segmentation Grid resilience Stochastic processes OPA model Power transmission grid Electric power transmission Electrónica Business and International Management Electrical and Electronic Engineering |
| Popis: | Large electrical transmission networks are susceptible to undergo very large blackouts due to cascading failures, with a very large associated economical cost. In this work we propose segmenting large power grids using controllable lines, such as high-voltage direct-current lines, to reduce the risk of blackouts. The method consists in modifying the power flowing through the lines interconnecting different zones during cascading failures in order to minimize the load shed. As a result, the segmented grids have a substantially lower risk of blackouts than the original network, with reductions up to 60% in some cases. The control method is shown to be specially efficient in reducing blackouts affecting more than one zone. DG and PC acknowledge funding from project PACSS RTI2018-093732-B-C22 and APASOS PID2021-122256NB-C22 of the MCIN/AEI/10.13039/501100011033/ and by EU through FEDER funds (A way to make Europe), from the Maria de Maeztu program MDM-2017-0711 of the MCIN/AEI/10.13039/501100011033/, and also from the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 957852, VPP4Islands). B.A.C. and J.M.R.-B. acknowledge access to Uranus, a supercomputer cluster located at Universidad Carlos III de Madrid (Spain) funded jointly by EU FEDER funds and by the Spanish Government via the National Research Project Nos. UNC313- 4E-2361, ENE2009-12213-C03-03, ENE2012-33219, and ENE2012-31753. OGB was supported in part by FEDER/Ministerio de Ciencia, Innovacion y Universidades - Agencia Estatal de Investigacion, Project RTI2018-095429-B-I00 and in part by FI-AGAUR Research Fellowship Program, Generalitat de Catalunya . The work of OGB is supported by the ICREA Academia program . |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|