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About

I'm graduated in Electrical Engineering from the University of Trás-os-Montes e Alto Douro (UTAD), Portugal in 1991. I have obtained the M.Sc. degree in Power Electronics in 1997 from UTAD and the Ph.D. degree in Electrical Engineering (Harmonic distortion analysis on the LV distribution networks) in 2007 from UTAD. Presently, I'm an Auxiliar Professor in the Department of Electrical Engineering, UTAD and also a INESCTEC researcher in power quality, electrical machines and renewables. My main interest areas are power quality, electrical machines and renewables.

Interest
Topics
Details

Details

  • Name

    José Ribeiro Baptista
  • Cluster

    Power and Energy
  • Role

    Affiliated Researcher
  • Since

    01st October 2012
Publications

2022

Wind Energy Assessment for Small Wind Turbines in Different Roof Shapes Based on CFD Simulations

Authors
Oliveira, C; Cerveira, A; Baptista, J;

Publication
SUSTAINABLE SMART CITIES AND TERRITORIES

Abstract

2022

State of the Art of Wind and Power Prediction for Wind Farms

Authors
Puga, R; Baptista, J; Boaventura, J; Ferreira, J; Madureira, A;

Publication
INNOVATIONS IN BIO-INSPIRED COMPUTING AND APPLICATIONS, IBICA 2021

Abstract
There are different clean energy production technologies, including wind energy production. This type of energy, among renewable energies, is one of the least predictable due to the unpredictability of the wind. The wind prediction has been a deeply analysed field since has a considerable share on the green energy production, and the investments on this sector are growing. The efficiency and stability of power production can be increased with a better prediction of the main source of energy, in our case the wind. In this paper, some techniques inspired by “Biological Inspired Optimization Techniques” applied to wind forecast are compared. The wind forecast is very important to be able to estimate the electric energy production in the wind farms. As you know, the energy balance must be checked in the electrical system at every moment. In this study we are going to analyse different methodologies of wind and power prediction for wind farms to understand the method with best results. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

2022

Supraharmonic and Harmonic Emissions of a Bi-Directional V2G Electric Vehicle Charging Station and Their Impact to the Grid Impedance

Authors
Grasel, B; Baptista, J; Tragner, M;

Publication
ENERGIES

Abstract
Bidirectional electric vehicle supply equipment and charging stations (EVSE) offer new business models and can provide services to the electrical grid. The smart grid lab in Vienna gives unique testing possibilities of future smart grids, as different type of electrical equipment can be operated at a reconstructed, well-known distribution grid. In this work the harmonic and supraharmonic emissions of a bidirectional EVSE are measured according to IEC61000-4-7 and IEC61000-4-30 Ed3 standard as well as the high-frequency grid impedance. In addition, the efficiency and the power factor are determined at various operating points. Although THDi at nominal power (10 kW) is very low and the efficiency and power factor is very high, at low power levels the opposite situation arise. Supraharmonic emissions remain stable independent of the charging/discharging power, and both wideband and narrowband emissions occur. The additional capacitance when connecting the EVSE impacts the high-frequency grid impedance substantially and generates resonance points.

2022

Power Quality of Renewable Energy Source Systems: A New Paradigm of Electrical Grids

Authors
Baptista, J; Faria, P; Canizes, B; Pinto, T;

Publication
ENERGIES

Abstract
The power quality delivered by the distribution companies to consumers has always been a relevant issue, especially to industrial consumers, where power quality is directly related to productivity [...]

2022

Dynamic remuneration of electricity consumers flexibility

Authors
Ribeiro C.; Pinto T.; Vale Z.; Baptista J.;

Publication
Energy Reports

Abstract
This paper proposes a decision support model to define electricity consumers’ remuneration structures when providing consumption flexibility, optimized for different load regimes. The proposed model addresses the remuneration of consumers when participating in demand response programs, benefiting or penalizing those who adjust their consumption when needed. The model defines dynamic remuneration values with different natures for the aggregator (e.g. flexibility aggregator or curtailment service provider) and for the consumer. The preferences and perspective of both are considered, by incorporating variables that represent the energy price, the energy production and the flexibility of consumers. The validation is performed using real data from the Iberian market, and results enable to conclude that the proposed model adapts the remuneration values in a way that it is increased according to the consumers’ elastic, while being reduced when the generation is higher. Consequently, the model boosts the active consumer participation when flexibility is required, while reaching a solution that represents an acceptable g tradeoff between the aggregators and the consumers. © 2022 The Authors

Supervised
thesis

2021

Adaptação de um robô colaborativo para a função de suporte de aquisição de imagens numa clínica dentária

Author
Bruno da Costa Rocha

Institution
UP-FEUP

2021

Automatic analysis of UAS-based multi-temporal data as support to a precision agroforestry management

Author
Luís Filipe Machado Pádua

Institution
UTAD

2019

Actuação Cooperativa de Conversores em Redes Eléctricas Inteligentes

Author
Amaro Miguel Ferreira Antunes

Institution
UTAD

2019

Remuneration and Tariffs in the Context of Virtual Power Players

Author
Ana Catarina Silva Ribeiro

Institution
UTAD

2018

Remuneration and Tariffs in the Context of Virtual Power Players

Author
Ana Catarina Ribeiro

Institution
UTAD