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Email

airam.perezguillen@unimelb.edu.au

Credentials


Position
Research Fellow - Research Focussed
Department of Electrical and Electronic Engineering
Education
PhD
The University of Manchester
Bachelor (Honours)
The University of Manchester
ORCID

0000-0002-0171-5716

Airam Perez Guillen

Research Fellow - Research Focussed
Department of Electrical and Electronic Engineering

9 Scholarly works
0 Projects

HIGHLIGHTS

  • 2026

    Journal article

    Machine Learning-Based Long-Term Forecasting of Load Composition Considering Exogenous Variables
    DOI: 10.1109/TSG.2026.3660327
  • 2026

    Thesis / Dissertation

    Long-Term Forecasting of Demand Flexibility and Models in Sustainable Power Networks
  • 2025

    Conference Proceedings

    Sensitivity of the accuracy of long-term load forecasting to exogenous variables
    DOI: 10.1049/icp.2025.1619
  • 2025

    Conference Proceedings

    Very Long Term Load Forecasting at Grid Supply Points with Limited Historical Load Data Availability
    DOI: 10.1109/ISGTEurope64741.2025.11305326
  • 2025

    Conference Proceedings

    The Influence of Exogenous Variables on Accuracy of Demand Forecasting over Different Time Scales
    DOI: 10.1109/PowerAfrica65840.2025.11289083
  • 2024

    Conference Proceedings

    The Impacts of the Effective Load Data Preprocessing in Long-Term Load Forecasting
    DOI: 10.1109/ISGTEUROPE62998.2024.10863353
  • 2023

    Conference Proceedings

    The Influence of Load Growth Scenarios on Distribution Network Operation
    DOI: 10.1109/ISGTEUROPE56780.2023.10407958
Airam Perez Guillen

Latest Honours,
Awards and Fellowships


2025
Fellow of the Higher Education Academy (UK) (FHEA)
Member of the Institute of Electrical and Electronic Engineers (IEEE)

RECENT SCHOLARLY WORKS

  • 2023

    Conference Proceedings

    The Impacts of Spatially Distributed Demand Growth and Load Modelling on Distribution Network Operation
    DOI: 10.1109/ISGTEUROPE56780.2023.10408126
  • 2023

    Conference Proceedings

    The Impacts of the Uncertainty in Demand Growth and Load Models on Distribution Network Operation
    DOI: 10.1109/ISGTEUROPE56780.2023.10408708

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