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Publicações

Publicações por José Ribeiro Baptista

2021

Optimization of Wind Turbines Placement in Offshore Wind Farms: Wake Effects Concerns

Autores
Baptista, J; Lima, F; Cerveira, A;

Publicação
Optimization, Learning Algorithms and Applications - First International Conference, OL2A 2021, Bragança, Portugal, July 19-21, 2021, Revised Selected Papers

Abstract

2023

Impact of Electric Vehicle Charging Stations on Distribution Grids with PV Integration

Autores
Silva, P; Cerveira, A; Baptista, J;

Publicação
International Conference on Electrical, Computer and Energy Technologies, ICECET 2023

Abstract
Electric mobility has been one of the big bets for the reduction of CO2 in the transport sector. But, the integration of electric vehicles on a large scale, especially the charging of their battery will bring some challenges in the distribution of electricity to avoid problems in their transport. In this paper, the impact of introducing electric vehicle charging stations and renewable energy sources in a 69-node IEEE network will be analysed. The integration of charging stations into the grid leads to high losses and voltage drops that harm the network. On the other hand, the installation of Photovoltaic (PV) panels, besides the advantage of energy production, improves the profile of the grid in terms of voltage drops. The choice of the best location for the charging stations, as well as the best location for the renewable sources, is made using two genetic algorithms. The results obtained show that the genetic algorithms can solve the problem efficiently. © 2023 IEEE.

2023

Modeling and Forecasting Photovoltaic Power Production

Autores
Ribeiro, D; Cerveira, A; Solteiro Pires, EJ; Baptista, J;

Publicação
International Conference on Electrical, Computer and Energy Technologies, ICECET 2023

Abstract
As the world's population grows, there is a need to find new sources of energy that are more sustainable. Photovoltaic (PV) energy is one of the renewable energy sources (RES) expected to have the greatest margin for growth in the near future. Given their intermittency, RES bring uncertainty and instability to the management of the power system, therefore it is essential to predict their behavior for different time frames. This paper aims to find the most effective forecasting method for PV energy production that could be applied to different time frames. PV energy production is directly dependent on solar radiation and temperature. Several forecasting approaches are proposed in this paper. A multiple linear regression (MLR) model is proposed to predict the monthly energy production based on the climatic parameters of the previous year. Different approaches are proposed based on first predicting the temperature and radiation and then applying the PV mathematical models to predict the produced energy. Three methods are proposed to predict the climatic parameters: using the average values, the additive decomposition, or the Holt-Winters method. Comparing the errors of the four proposed forecasting methods, the best model is the Holt-Winters, which presents smaller errors for radiation, temperature, and produced energy. This method is close to additive decomposition. © 2023 IEEE.

2023

Energy Sharing Models in Renewable Energy Communities

Autores
Araújo, I; Grasel, B; Cerveira, A; Baptista, J;

Publicação
International Conference on Electrical, Computer and Energy Technologies, ICECET 2023

Abstract
Renewable energy communities (REC) are an increasingly interesting solution for all energy market stakeholders. In RECs consumers and producers come together to form energy cooperatives with a strong incorporation of renewables in order to make the market and energy trading more advantageous for both sides. This growing trend has been followed by several studies aimed at understanding which are the best models for energy sharing within the community. This paper proposes different models of energy sharing within the community and evaluates their efficiency. Energy sharing can be based on constant coefficients or variable coefficients based on the net consumption of the self-consumers. This study proposes a new methodology based on a hybrid model. The results show the advantages and challenges of the individual energy-sharing models, showing that up to 41% of the energy imports from the grid can be reduced. © 2023 IEEE.

2023

Optimal Location of Electric Vehicle Charging Stations in Distribution Grids Using Genetic Algorithms

Autores
Gomes, E; Cerveira, A; Baptista, J;

Publicação
Optimization, Learning Algorithms and Applications - Third International Conference, OL2A 2023, Ponta Delgada, Portugal, September 27-29, 2023, Revised Selected Papers, Part I

Abstract

2024

The impact of V2G charging stations (active power electronics) to the higher frequency grid impedance

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

Publicação
SUSTAINABLE ENERGY GRIDS & NETWORKS

Abstract
Renewable energy generation technologies, heat pumps or electric vehicle (EV) charging stations use active power electronics such as IGBT or MOSFET for AC to DC conversion with the consequence of emissions in the higher frequency range above 2 kHz (non-intentional supraharmonic emissions) and with an impact to the higher frequency grid impedance. In this study the impact of active power electronics on the higher frequency grid impedance in the range up to 150 kHz is analyzed. As existing grid modelling solutions do not consider these technologies sufficiently, this study analyzes the impact of a vehicle to grid (V2G) chargers to a representative distribution grid considering different grid topologies and different types of V2G chargers. The study shows that the additional capacitance and inductance (LCL filter, DC link capacitor) introduced in the electrical grid causes parallel and series resonances in a wide frequency range starting from 500 Hz up to 50 kHz. The grid topology and the number of V2G chargers connected determines the frequency range and characteristics of resonances. Finally, the major contribution of this study is outlining the importance of considering the higher frequency grid impedance for characterization of supraharmonic emissions (primary vs. secondary emissions) and their propagation.

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