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Decentralized energy production, particularly from photovoltaic (PV) systems, is becoming increasingly prevalent, leading to a rise in the number of energy producers and consumers, or ”prosumers”. These prosumers, equipped with their own energy generation and storage systems, are not just passive consumers but active participants in the energy market. They generate their own electricity, often from renewable sources, and can feed excess power back into the grid, store it for later use, or share it within a local energy community. This evolving energy paradigm presents new opportunities and challenges in terms of energy management and optimization, necessitating innovative approaches to ensure efficient and sustainable use of energy resources. This paper introduces an innovative storage management method for grid-connected photovoltaic (PV) systems. The method is designed to minimize either the economic or ecological cost, or to find an optimal balance between the two, under various tariff scenarios. This is achieved while adhering to a full self-consumption constraint imposed by the distribution system operator. The control strategy is underpinned by forecasts of electrical consumption, production, and CO2 emissions, which are developed using feedforward neural network models. These models are trained on data from a real-scale smart-grid demonstrator at the Catholic University of Lille, France. The results of the study offer a comparative analysis of the economic and ecological benefits of the three proposed strategies, demonstrating that the best compromise is achieved when considering the off-peak tariff option. Furthermore, a real-time controller was implemented on the Energy Management System (EMS) of the demonstrator and tested over a 24-hour period, yielding satisfactory results. This paper, therefore, presents a significant advancement in the field of storage management for grid-connected PV systems.

The deployment of DC fast charging stations (DCFCSs) in cities requires costlyrein-forcement of low‐volt age (LV) distribution grids, due to the high power required. It results in high investments for the station operator as well as for the distribution system operatorand profitability of such projects. In this study, a novel concept of fast charging station which reduces the connection to the grid is presented.This station uses Vehicle‐to‐vehicle (V2V) power transfer from a fleet of car sharing electric vehicles to provide a high charging power while mitigating the power demand on the grid. Based on data from a car sharing operator in the city of Paris, a simulation model of a combined carsharing/V2V fast charging system is proposed, allowing to simulate car sharing trips and V2Vtransfers. The reduction of the grid connections required to provide fast charging is evaluated and the impact of the repeated discharges on the level of service ofthe car sharing system is discussed. Moreover, simulation of LV distribution grids allows to compare the grid losses of the V2V system with conventional DCFCSs.

In this paper, a reliable methodology is proposed in order to implement and validate a Model Predictive Control (MPC) scheme on an actual Voltage Source Converter (VSC) integrated in a scale-down multi-terminal DC grid. The objective of the investigated MPC controller is to enable AC frequency support among two asynchronous AC areas through a High Voltage Direct Current (HVDC) grid, while considering physical constraints, such as maximum and minimum DC voltage. A systematic and accurate implementation strategy is proposed, based mainly on the Hardware In the Loop (HIL) and Power Hardware In the Loop (PHIL), leading to the real-life testing on VSC, controlled by a classical microcontroller. The technical problems during the implementation process, as well as the proposed solutions, are described in detail through this paper. This procedure is deemed valuable to bridge the gap between offline simulation and the actual implementation of such advanced control scheme on experimental test rig.

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.

This paper presents a DC-bus signaling (DBS) control method for a smart grid with a PV plant and multiple electric vehicle charging stations (EVCS). The proposed DBS method aims to maximize self-consumption and reduce greenhouse gases (GHG) intensity of the EVCS.The proposed DBS system uses the DC bus voltage as a signal to modulate the EVs charging power, to adapt to PV production in real-time. Therefore, the need for a communication infrastructure is minimized, thus increasing the system’s robustness. Moreover, a minimal charging power is set to still be able to provide a charging service in the case of a low PV production.Real-world data from the smart grid demonstrator at the Catholic University of Lille in northern France are used for PV production and EV consumption. The system is modelled using MATLAB/Simulink and simulated to be compared with actual data from a chosen day. The simulations results show that the DBS control system allows an increase in the self-consumption and lower GHG emissions, while keeping a satisfactory charging service.

To meet the high transport demand in the urban areas, railway companies are required to increase train traffic and particularly the feeder power that supplies the trains. Increasing DC power leads to rising fault currents in the substations that can exceed 110 kA. The main purpose of this study is to limit fault current and optimise rectifier diode (I 2 t) in the DC substation for railway networks. This limitation will enable to reduce the oversize of the network components, to minimise their investment and maintenance costs. A resistive superconducting fault current limiter is used. First, the DC substation with and without faults current is modelled using EMPTP-RV software. A detailed model of the superconducting limiter based on REBCO tapes is then modelled using Matlab software. Results from REBCO models are integrated into the substation under faults conditions and then optimised to achieve the required limitation. A case study is carried out using the SNCF network in Paris. Results show 50% faults limitation and 23.75% I 2 t optimisation of rectifier diode in transient regime.

To support the mass market adoption of battery electric vehicles (BEVs), an appropriate charging infrastructure is necessary, and DC fast chargers (DCFCs) are expected to play a key role. However, their deployment requires costly reinforcements of the distribution grid. This paper investigates a novel concept of fast charging station. It uses the batteries of a fleet of carsharing electric vehicles (CEVs) able to be partially discharged to provide a high charging power to private electric vehicle (PEVs) owners, thanks to a vehicle-to-vehicle (V2V) conductive energy transfer. Based on data from a carsharing operator in the city of Paris, a simulation model of a V2V fast charging infrastructure is built. The impact on the carsharing system and on the required reinforcements of the distribution grid are evaluated.

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.

The efficiency of a regenerative braking energy operation is discussed in this paper. Sending recovered energy back to the grid is possible using a reversible converter installed in a DC railway power substation. The strategy of such converter impacts the efficiency of the recovered energy because of coupling between the converter strategy and the regenerative braking strategy of the train. This coupling is highlighted in this paper and results on real time simulation test bench of a specific railway section in Paris are discussed.

Known for being a reliable alternative, microgrids have been widely deployed recently in power distribution field in order to guarantee a constant power supply especially in isolated zones. Moreover, microgrids have increasingly known the penetration of renewable energy as environmentally friendly energy sources. However, the intermittency of these sources oblige specialists to think about tools allowing determining their potential, over a predetermined time interval, in order to ensure energy security. For this reason, renewable energy forecasting is crucial. Thus, in this paper, a feed forward back-propagation neural network is used to forecast next 24 hours photovoltaic (PV) power of one of the catholic university buildings "îlot RIZOMM". The accuracy of the model built is evaluated with some performance metrics. Thereafter, prediction results of PV power are compared to those provided by SteadySat, an industrial solution developed by the company SteadySun. It is shown that the prediction Mean Absolute Errors (MAEs) of the model are of 3.05% in a clear sky day, 4.95% in a cloudy day and 5.98% in a partly cloudy day.

The subject of this paper is the experimental validation of a recently proposed advanced control scheme for Voltage Source Converters (VSC) based on Model Predictive Control (MPC). The main purpose of the investigated advanced controller is the frequency support from an AC grid to another after significant disturbance through HVDC Grid. The paper reports on the implementation methodology on a small-scale 3-terminal DC mock-up grid consisting of several physical low-scale VSCs, actual DC cables. These components are coupled with realtime simulation tools simulating the adjacent AC grids. The different steps for the validation process of the MPC strategy are illustrated, starting from offline simulation based on a model of the DC grid, up to the actual implementation of the controller in the mock-up of the DC grid.

The frequency support provided by a DC grid to an interconnected AC grid and integrated in VSC-HVDC controller is studied in this paper. The advantages of a combined control of voltage droop and frequency droop are investigated on a hybrid AC/DC system for the case of a sudden loss of large generation unit in the AC grid. The coupling between both droops control and the correction factor of the frequency droop coefficient are discussed. An experimental validation on VSC converter prototypes and under realistic operation conditions is conducted using Power-Hardware-In-the-Loop simulation. The practical results showed a good match with the theoretical calculation and confirmed the offline simulation results presented in previous work.