Fiche individuelle

To face environmental issues, SNCF, the French railway, has chosen to improve the energy efficiency of its electrical power system by investigating solutions for regenerative braking. With the contribution of Railenium, a research and test center in railway activities, they aim to recover the braking energy by setting up a reversible inverter in a DC substation “Masséna”. The issue is to test, implement and compare various control solutions to increase the energy efficiency with minimum impacts on the railway operation. In this paper, a simulation model for studying a reversible power substation is addressed by considering AC and DC equivalent electrical sources. The proposed model provides a reliable tool for analyzing the behavior of the railway electrical network during specially braking mode. In order to validate this model, its simulation results are compared with the ones obtained from Esmeralda, the SNCF professional software. A first configuration is led without the inverter and gives certified Esmeralda results and validates the proposed model despite some gaps in powers and voltages due to differences in input data and models. A second comparison with inverter is presented to highlight the main difference between the proposed model and Esmeralda. In addition, laboratory experimental activities are put forward to investigate the proposed model by using power-hardware-in-the-loop simulations. Finally, a simulation test under MATLAB software with fifty train’s traffic is presented to estimate the energy saving thanks to the installed inverter. For this latter case study, the system sent back to the national AC grid around 6.9% of the total energy consumed by all trains.

The growing use of electric vehicles (EVs) is key to reducing greenhouse gas emissions and promoting sustainable transportation. However, this rapid growth creates challenges, such as managing peak charging demand, maintaining power grid stability, and ensuring efficient use of charging stations. This study examines EV charging behavior within a potential local energy community in France, using data from September 2021 to August 2023 from 23 charging terminals. The analysis explores patterns in charging times, session durations, and energy consumption, uncovering trends and inefficiencies that impact power grid management. To improve energy planning, the study uses three machine learning models to forecast day-ahead EV charging demand. Gradient Boosting outperformed the others, achieving the lowest errors and highest R² (0.664), demonstrating the potential of advanced forecasting techniques for optimizing energy management systems. The results show how accurate forecasts can help balance energy demand and supply, making charging more efficient. This study demonstrates the value of integrating advanced forecasting techniques into energy management systems to support the growing adoption of EVs, reduce energy costs and improve power grid stability.

This work is focalized on the topical issue of improving the energy efficiency of train in braking mode. The improvement is explored by integration and control of a reversible inverter in a DC power substation to inject the braking power from the DC side to the AC power grid. This solution makes the substation reversible. The objective of this study is to investigate a control strategy by adjustment of the DC voltage for the inverter in order to recover the maximum of electric braking energy by keeping the DC voltage of the substation stable with a reference value. A comparative study of simulation results of the suggested control scheme with a droop control technique for the railway substation “Massena” in Paris is presented.

This article presents the modeling, control design and simulation of a variable speed Wind Energy Conversion System (WECS). The WECS contains a wind turbine that drives a permanent magnet synchronous generator (PMSG). The wind turbine and the PMSG are connected to a DC bus voltage through AC/DC converter. The power at the DC bus voltage is injected to the power grid through an inverter and RL (resistance and inductance) filter. The purpose of the modeling is to apply a control design able to ensure the operation of the wind generator in the maximum power point, to keep the DC bus voltage stable in its reference value, and to independently control the active and reactive powers injected to the grid. In addition, a simulation test of the detailed WECS is presented to demonstrate the concepts discussed.