Raquel Martínez Torre

R.Martinez

RAQUEL MARTÍNEZ TORRE

 

Raquel Martinez received her Industrial Engineer Degree and her Master in Research in Industrial Engineering from University of Cantabria, Spain in 2011 and 2012, respectively. In 2011 she joined the Department of Electrical and Energy Engineering and GTEA. She received her PhD in Industrial Engineering from University of Cantabria in 2016 with a work about dynamic management in overhead lines. As a result of this research line has one publication in journal, 7 publications in international conferences and 2 patents.


icono-mail raquel.martinez@unican.es

molumen_phone_icon+34 942 200956

474487-icono-ubicacion School of Industrial and Telecommunications Engineering. Floor: -2. Office: S2-53



PROJECTS

  • REDACTIVA: Innovation on Isolated Neural Distribution Grid Automation

  • Development Model of Dynamic Capacity of Overhead Lines

  • PROFIT DYNELEC: Dynamic Calibration of Electrical Lines

  • Data Capture and Sustainable Energy in Edification

PUBLICATIONS

  • Study of Different Mathematical Approaches in Determining the Dynamic Rating of Overhead Power Lines and a Comparison with Real Time Monitoring Data

  • Comparison between IEEE and CIGRE Thermal Behaviour Standards and Measured Temperature on a 132-kV Overhead Power Line

  • Methodology for the Low-Cost Optimisation of Small-Wind Turbines

  • Operational Aspects of Dynamic Line Rating. Application to a Real Case of Grid Integration of Wind Farms

  • A Comparison of Different Methodologies for Rating Definition in Overhead Lines

  • Aspectos Operativos de la Gestión Dinámica de Capacidad en Líneas Aéreas de Distribución. Aplicación al Caso Real de la Integración en Red de Parques Eólicos

  • Analysis of a Real Case of Ampacity Management in a 132 kV Network Integrating High Rates of Wind Energy

  • Preliminary Results of a Power Quality Survey in a Distribution Network Based on No-Gap PQ Meters

  • Indirect Estimation of Overhead Line Ampacity in Overhead Lines Integrating Wind Farms

  • Ampacity Forecasting Using Neural Networks

  • Increasing Grid Integration of Wind Energy by using Ampacity Techniques

  • Methodology for Dynamic Capacity Management in High Voltage Overhead Lines Based on Multiple Discrete Measures of Environmental Conditions

PATENTS

  • Methodology for the Calculation and Prediction of Ampacity on Overhead Power Lines According to the Choice of Crtitical Sites

  • Method and System for Direct Measurement and no Contact of Surface Temperature in a Cable