The adoption of Electric Vehicles (EVs) is rapidly increasing, positioning this technology at the forefront of transportation decarbonization efforts. However, this transition also brings challenges to grid stability, including unmanaged peak loads, the mismatch between peak generation from Renewable Energy Sources (RES) and peak consumption by EVs, energy imbalances, and the intermittency of RES production, among others. If these issues are not effectively addressed, they could undermine the advantages of RES and EV adoption, potentially causing energy shortages or leading to overproduction that cannot be stored or utilized.
The shift to electric vehicles (EVs) requires smarter energy management for efficient charging and grid stability.
As part of the European OPEVA project, partners are exploring these strategies by developing a demonstrator focused on optimizing the scheduling of electric vehicle charging. This approach aims to minimize energy costs, balance production with consumption, and maximize renewable energy self-consumption, whether within a renewable energy community or a single building.
The demo 09 of OPEVA project focuses on developing a solution to schedule the EV charging in a way that addresses these challenges.
The core concept of the demonstrator involves the flexibility scheduling algorithm that optimizes EV charging schedules, considering factors such as renewable production, energy prices and local demand.
Data-Driven Charging with Secure Communication
The project integrates advanced AI-driven algorithms developed by ISEP to dynamically schedule EV, these algorithms rely on real data from charging EVs, PV production and other loads consumption. Integration with Cleanwatts Cloud platform and my-icharging cloud platform was achieved to obtain data from real scenarios.
The CarLink Connect module, also developed by ISEP, allows real-time tracking of an EV’s state of charge (SoC), enhancing the accuracy of the scheduling algorithm.
Secure data exchange is another critical aspect of the project. Communication between EV chargers, local controllers, and cloud platforms follows established protocols such as OCPI, OCPP, Modbus, and REST APIs, ensuring reliability and cybersecurity in the charging process.
Real-World Scenarios for Smarter Charging
Demo 9 explores various real-world scenarios where smart scheduling can make a difference:
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- Scenario 1 – to recharge the battery when arriving home from work: the battery can be charged any time during the night (when the price is usually lower) and be fully charged before going to work in the next morning.
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- Scenario 2 (simulated) – using the car as battery: if the car is stopped and connected with the charger, then the car battery can also be used to store energy from local production Photovoltaic (PV) cells, or other sources, and sell it to the grid (simulated) when required.
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- Scenario 3 – to recharge a car during its trip: the charging station where to stop is calculated and reserved according to the travel plan of the driver, considering among others the charging tariff, the existence of Energy Community members within the traveling routing, etc.
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- Scenario 4 – to charge the battery of the EV when connected to a building fleet charging network, with automatic prioritization according to the EV/user needs and performing building load balancing policies, RES management and Demand Response activities.
Deployment site – Cleanwatts Living Lab and I-charging facilities
The Flexibility Scheduling Algorithms will be tested in a residential environment, Cleanwatts Living Lab, and in a corporate setting, I-Charging São Mamede Factory and I-Charging Marechal Headquarters.
The Cleanwatts Living Lab in Portugal, primarily concentrated in the Coimbra region, consists of a network of participants engaged in various energy roles, including consumers, flexsumers (offering flexibility through remote equipment control), prosumers, and producers that together form a simulated energy community.
An energy community is a group that produces its own energy, typically from renewable sources like solar, and shares it among its members. This model promotes collective self-consumption, allowing participants to use the energy they generate and distribute any excess within the community.
As part of the Living Lab expansion, 4 small AC chargers were supplied by i-Charging and installed. These chargers will contribute to the existing assets and support the implementation of various use cases.
As the Living Lab consists of homes belonging to real families, any interaction with their energy assets for testing the OPEVA solution must be conducted carefully to minimize disruption to their daily routines. Therefore, only the four houses equipped with new EV chargers from i-charging will have active control over their EV chargers, BESS and other loads. Meanwhile, 13 houses will solely provide energy flow data for the scheduling algorithms. Together, these 17 houses represent the energy community for this project.
The I-charging S. Mamede Factory site includes one 50 kW DC charger, two AC chargers, and PV panels. The objective here is to provide balancing to the energy consumed by charging and minimizing disruptions and minimizing costs while adhering to the EV driver’s comfort.
The I-charging Marechal Headquarters site includes one 50 kW DC charger and eighteen 22 kW AC chargers. This installation will be used to test the users’ flexibility and energy optimization according to the power limits and other loads consumption.
Demo 9 presents a simple solution for optimizing EV charging costs and maximizing the use of renewable energy, suitable for both family homes and corporate settings.
Authors:
Luis Lino Ferreira, ISEP
Paulo Rodrigues, i-charging
Pedro Paiva, Cleanwatts
Tiago Fonseca, ISEP