Deliverable D2.2 Control Strategies for V2X Integration in Buildings

Charalampos Ziras, Jan Martin Zepter, Jan Engelhardt, Mattia Marinelli, António Furtado, Carlos Martins, Tarcísio Silva, Francisco Branco, João Mateus, Samuel Matias, Herbert Amezquita, Cindy Paola Guzman Lascano, Hugo Morais, Manuel Pereira, Filipe Lopes, Rui Martins, Liliana Matos, Catarina Rocha, Miguel Quinto

Research output: Book/ReportReportCommissioned

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Abstract

The Control Strategies for V2X Integration in Buildings deliverable presents decision-making models capable of integrating Vehicle-to-Everything (V2X) in the optimal energy management of buildings with local generation capabilities. The developed control methods will be considered in the Portuguese demonstrator of the EV4EU project, in São Miguel Island, Azores, and the Danish demonstrator, in the island of Bornholm, Denmark, to test the benefits of smart charging techniques.

Both developed control frameworks rely on collecting and utilizing historical data (on building load, photovoltaic (PV) production and Electric Vehicle (EV) data) for forecasting purposes. The Danish framework utilizes a forecasting-assisted rolling-horizon optimisation approach, while the Portuguese framework utilizes a daily planning stage (which determines a predefined goal), followed by the real-time operation stage.

The control objective in the Danish case is to optimally manage EV charging for minimizing energy costs while respecting a reduced line limit for the aggregated EV charging power, while for the Portuguese case various scenarios are considered, whose objective, apart from minimizing energy costs, is the activation of grid services, specifically targeting smaller islanded systems, such as the one in Azores.

The developed strategies were tested on a number of simulation scenarios which relied on historical data from the sites and a few available sources to replace the missing EV data because during the execution of the task the demonstration sites were not yet operational. Simulation results showed that the inclusion of forecasts and an optimisation-based control approach can bring substantial economic benefits and reduce peak power, thus reducing the required grid connection size for the chargers. Additionally, those preliminary results indicate that the added benefit of using sophisticated forecasting techniques is rather low, pointing at the use of simple and easy-to-implement methods which strike a better balance between simplicity and performance.

It should be noted that the economic benefit largely relies on the amount of installed chargers, the share of EV load compared to the building’s consumption and the tariff/price structure. Longer plug-in durations and higher EV power capacity lead to higher potential cost savings by employing the developed control strategies, and a more realistic quantification will be carried out during the demonstration phase of the project.
Original languageEnglish
PublisherTechnical University of Denmark
Number of pages53
Publication statusPublished - 2023

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