• Home
  • Victor Adrian Jimenez
Victor Adrian Jimenez

Victor Adrian Jimenez
Universidad Tecnológica Nacional, Tucumán · Grupo de Investigación en Tecnologías Informáticas Avanzadas

Ph.D. in Information Systems

About

26
Publications
5,507
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
87
Citations
Citations since 2017
19 Research Items
86 Citations
20172018201920202021202220230510152025
20172018201920202021202220230510152025
20172018201920202021202220230510152025
20172018201920202021202220230510152025
Introduction
I am a Computer Engineer, received at the National University of Tucumán, Argentina, in 2013. Recently, I received a Ph.D. degree in Information Systems Engineering. Currently, I am a researcher member of GITIA, and my work focuses on intelligent data analysis applied to the management and optimization of energy.
Additional affiliations
April 2013 - present
National University of Technology
Position
  • Researcher
Description
  • My work focuses on intelligent data analysis applied to the management and optimization of energy. My research interests are Genetic and Evolutionary Algorithms and its applications to Climate and Energy, Data Science and Edge Computing.
April 2013 - October 2021
Independent Researcher
Independent Researcher
Position
  • PhD Student
Education
August 2014 - June 2020
National University of Technology
Field of study
  • Ph.D. in Information Systems
April 2006 - April 2013
National University of Tucuman
Field of study
  • Computer Engineer

Publications

Publications (26)
Article
Full-text available
Solar radiation is one of the most important parameters for applications, development and research related to renewable energy. However, solar radiation measurements are not a simple task for several reasons. In the cases where data are not available, it is very common the use of computational models to estimate the missing data, which are based ma...
Article
In this work we present a Distributed Demand-Side Management system based on the Artificial Immune Network algorithm. It implements an intelligent, distributed and autonomous control of the customer’s Air Conditioning devices in order to meet the desired demand. The system is particularly adapted to tackle the Peak Load problem that appears in Trop...
Article
One of the most common problems in the electricity sector is the lack of accurate information about the structure of the low-voltage distribution network, particularly the association between the customers and the substation’s phases. Identifying to which substation’s phase each customer is connected reduces the response time to contingencies, impr...
Article
Knowledge about the customers' phase connections is strategic and critical for utility companies. It allows them to optimize maintenance and repair operations, implement load balancing, and detect losses, among other benefits. However, this information may be incomplete or outdated due to the undocumented changes in the Low Voltage network. Several...
Article
Load balancing is one of the most widely used techniques to reduce losses and improve service quality in low-voltage networks. Many methods have been proposed, including the customer phase reassignment, which has multiple advantages. However, its application represents a real challenge if the data availability is limited (only a few variables from...
Experiment Findings
Seven field tests were conducted using data provided and validated by two electricity distribution companies: Discar SA. (Córdoba, Argentina), and EDET S.A. (Tucumán).
Article
Full-text available
Customer rephasing is one of the most efficient techniques for balancing loads, reducing losses, and improving electricity quality. Traditionally, phase changes were performed by an operator, interrupting the supply during the process. Instead, a more recent approach proposes using phase switching devices that dynamically and imperceptibly transfer...
Article
Full-text available
The Smart Grids paradigm emerged as a response to the need to modernize the electric grid and address problems related to the demand for better quality energy. However, there are no fully developed and implemented smart grids, but only some minor scale tests to prove the concepts. Centralized systems are still common, with a low granularity of cont...
Presentation
Full-text available
The pandemic has brought a lot of unexpected challenges and situations that very few organizations were prepared to handle. In particular, reconversion of Intermediate Care Units and other spaces into Intensive Care Units. Even stadiums and hotels were reconverted to Intensive Care Units worldwide, during the peaks of the pandemic. Among other chan...
Presentation
Full-text available
Monophasic customer phase connection determination in 3-phasic distribution transformer substation, is an international problem. Except for some Power Line Communications Technology, most but not all Smart Meters Technology can establish a customer to transformer relation. But identifying which phase a monophasic customer is connected to, or even i...
Presentation
Full-text available
Climate change is currently affecting weather patterns, producing more severe storms, harsher weather, and heat waves in places never seen before. In particular, it brings the so called Air Conditioning Trap Problem: Greenhouse gases produce more heat in the atmosphere and heat waves (warmer weather in places never seen before), that gets people ar...
Article
Full-text available
El modelado de datos es un problema fundamental en diversas áreas del conocimiento. La Regresión Simbólica es una técnica que permite encontrar una relación matemática para describir un conjunto de datos experimentales. A diferencia de los métodos tradicionales de modelado, la Programación Genética permite encontrar una expresión matemática suscept...
Presentation
Full-text available
La disponibilidad de datos brindados por las Redes Inteligentes permite a las empresas de distribución de energía aplicar diferentes técnicas para conseguir una mejor y más eficiente gestión del sistema eléctrico. Sin embargo, la implementación de estas técnicas es un verdadero desafío cuando la información disponible sobre la red y su estado actua...
Article
Full-text available
Durante décadas de investigación en problemas de optimización, se han desarrollado innumerables algoritmos, tanto determinísticos como heurísticos. Aun así, debido a este amplio abanico de posibilidades resulta una tarea compleja determinar cuál de ellos es más adecuado para un problema específico. Se propone en este trabajo una comparativa entre d...
Preprint
Full-text available
Variable selection problems generally present more than a single solution and, sometimes, it is worth to find as many solutions as possible. The use of Evolutionary Algorithms applied to this kind of problem proves to be one of the best methods to find optimal solutions. Moreover, there are variants designed to find all or almost all local optima,...
Patent
La presente invención pertenece al campo técnico de la medición de variables y análisis de datos en sistemas de provisión y distribución de energía eléctrica en general, en particular, enfocado a la identificación de fase y vinculación con la Subestación Transformadora de clientes en redes de distribución de baja tensión y Microgrids. La misma se r...
Article
Full-text available
Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations due to overload (since the margin for summer peaks is small). The advent of the Smart Grids allows electricity distribution...
Article
Full-text available
La radiación solar es uno de los parámetros más importantes para el desarrollo de aplicaciones e investigaciones relacionadas a energías renovables. Sin embargo, la adquisición de mediciones de radiación solar no siempre es posible por diferentes motivos y es necesario contar con modelos que permitan estimarla. Estos modelos en su mayoría utilizan...
Conference Paper
Full-text available
Load forecasting is a critical technique in the decision-making process for the proper management of different aspects of the electricity distribution network. Load Forecasting is a very complex problem, and there is a wide variety of techniques to address it. However, it is the data and local conditions that determine what technique is the best. I...
Conference Paper
Full-text available
El consumo de energía, específicamente de energía eléctrica ha crecido de manera sostenida en las últimas décadas. Debido a los nuevos requisitos de los usuarios consumidores y al surgimiento de nueva tecnología se nacimiento a las Redes Inteligentes o Smart Grids. En éste contexto, es que surge la propuesto de Demand-Side Management (DSM) como alt...
Patent
The present invention is referred to a disposition of electronic units and procedures to control and regulate the energy consumption of devices connected to the electric network in order to avoid blackouts generated by electric overloads or peak load, and to protect the providers and users electric installations in an autonomous and decentralized w...
Conference Paper
Short-Term Load Forecating (STLF), está tomando una mayor relevancia por el desarrollo de las microgrid y los sistemas Supervisory Control And Data Acquisition (SCADA). Existe una explosión de datos en esta área; para lograr que los sistemas sean prácticos y precisos se necesita seleccionar de manera adecuada las variables de entrada utilizadas por...
Article
Full-text available
La Programación Genética (PG) es un conjunto de técnicas de computación evolutiva basadas en Algoritmos Genéticos, que permiten resolver problemas mediante la generación automática de programas. La PG ha demostrado ser un método eficiente para encontrar soluciones a una gran variedad de problemas donde se cuenta con una función objetivo o tarea a...
Article
Full-text available
El problema de la predicción de consumo eléctrico a corto plazo o Short Term Load Forecasting (STLF), es un tema de capital importancia para las empresas de energía en la actualidad, ya que permite un manejo más eficiente, permitiendo un mejor aprovechamiento de los equipos y recursos. La predicción de la demanda es un problema complejo, ya que est...
Conference Paper
La programación genética (PG) es un conjunto de técnicas de computación evolutiva que permiten resolver problemas automáticamente y que están basadas en Algoritmos Genéticos (AG). La PG ha sido un método muy utilizado para encontrar y evolucionar nuevas e inesperadas maneras de resolver problemas, en particular problemas de Regresión Simbólica (RS)...
Conference Paper
Full-text available
La falta de datos en bases de datos climáticas es un problema común en todo el mundo. Debido a que los datos meteorológicos son un parámetro esencial para estudios y desarrollos de aplicaciones relacionados a clima y energía, es de vital importancia la utilización de técnicas para el relleno de datos faltantes. Esta tarea requiere conocimientos esp...

Network

Cited By

Projects

Projects (5)
Project
Determining the topology of the low-voltage grid in the electricity distribution network is problematic. In large cities, grid changes take time to be updated in the Geographic Information Systems (GIS), contain human errors, or produce other problems. Even more, using only one-phase connection in buildings with 3-phase energy is very common due to cost. In both cases, the information about phases and transformer substations is unknown or contains errors, increasing costs and decreasing service quality. In the case of old buildings like hospitals that have undergone several renovations over the years, the problem is worse because, usually, the blueprints do not match the reality of the circuits. The objective is to develop a system based on data analysis (PhID) that uses commercial smart meters data in order to detect the topology of the network. The system must work with very little data and be resilient and fully automated (no data cleansing or parameter adjustment of any kind).
Archived project
In the current project, tools based on Artificial Intelligence are used to tackle the Peak Load Problem, such as Multi-Agent Systems, Artificial Immune Systems, and Genetic Algorithms. From the energy viewpoint, the project uses a Demand-Side Management approach to control energy demand. This strategy is oriented to reduce the impact of the Peak Loads transparently or imperceptibly to the electric consumer.
Project
Data Analysis. Artificial Intelligence. Application to Energy Management and Optimization. Edge Computing.