EconPapers    
Economics at your fingertips  
 

Novel sensitivity models for electromechanical oscillations analysis in active distribution networks considering electrical vehicles optimal charging

Augusto C. Rueda-Medina, Rodrigo Fiorotti, Helder R.O. Rocha and Domingos S.L. Simonetti

Renewable Energy, 2024, vol. 232, issue C

Abstract: The integration of distributed generators (DGs) from renewable sources and electric vehicles (EVs) poses challenges, notably in the optimal management of these resources to exploit all the advantages they can bring to the electrical network. This paper proposes three novel sensitivity models for dynamic analysis of low-frequency electromechanical oscillations in active distribution networks, considering a centralized and decentralized frequency control strategy. Additionally, a novel linear formulation has been devised to leverage the flexibility inherent in DGs in the EVs optimal charging, in which the DGs generation uncertainties are reduced by using a novel forecasting system combining the Monte Carlo method and Markov models. To carry out validation analysis, in-depth and extensive comparisons have been conducted through the definition of several study cases in a modified IEEE 37-bus distribution test system, taking into account the presence of EVs. Moreover, Fourier transforms and Wavelet methods were utilized to conduct response signals spectral and time series analysis, showing that integrating the proposed models into active distribution networks offers valuable insights for transient response studies, since these models provide a range of dynamic analysis options that can be selected based on the runtime speeds and the required level of results accuracy.

Keywords: Distributed generation; Frequency control; Electrical vehicles; Generation uncertainty; Monte Carlo method; Markov models (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148124011741
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:232:y:2024:i:c:s0960148124011741

DOI: 10.1016/j.renene.2024.121106

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:renene:v:232:y:2024:i:c:s0960148124011741