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Optimization Models for Vehicle-to-House (V2H) Technologies in Smart Grids: Real-Time Management and Price Fluctuation Adaptation

Giovanni Della Negra

Optimization Models for Vehicle-to-House (V2H) Technologies in Smart Grids: Real-Time Management and Price Fluctuation Adaptation.

Rel. Alessio Sacco, Simone Silvestri, Guido Marchetto. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2024

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Abstract:

The increasing use of electric vehicles (EVs) is revolutionizing the landscape of home energy management, offering new opportunities through Vehicle-to-Grid (V2G) technology and, in particular, the Vehicle-to-House (V2H) mode. This research explores the implementation of an intelligent V2H system, with the main objective of minimizing energy costs and reducing peak demand, thus contributing to a more sustainable, resilient, and efficient electrical system. The first part of the work provides a detailed overview of V2G and V2H technologies, illustrating the potential and challenges associated with their integration into home energy systems. The technical, economic, and environmental implications are analyzed, highlighting how these technologies can foster a transition to a greener and smarter energy model. The core of the research focuses on four linear optimization models. The first two models are offline and based on historical data and forecasts of load and energy production. These models are designed to optimize energy management over defined time periods, leveraging forecasts of energy availability and demand. The other two models are corrective and operate online, adapting energy management strategies in real-time in response to immediate variations in load and energy availability conditions. The key innovation of this research lies in the ability to consider the dynamic price of electricity, optimizing the energy flow between the vehicle and the house to maximize economic savings. Through intelligent management of the electric vehicle’s charging and discharging, the system can reduce energy costs, mitigate peak demand, and improve the overall efficiency of home energy use. The experimental results obtained demonstrate a significant reduction in energy costs and more efficient use of energy, confirming the effectiveness of the proposed models. The research concludes by emphasizing the potential of V2H as an essential strategy to address future energy challenges, promoting home energy management that is not only more sustainable but also smarter and more resilient. This research represents a significant contribution to the field of energy management, outlining a clear path toward a greener and smarter energy future.

Relators: Alessio Sacco, Simone Silvestri, Guido Marchetto
Academic year: 2024/25
Publication type: Electronic
Number of Pages: 88
Subjects:
Corso di laurea: Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica)
Classe di laurea: New organization > Master science > LM-25 - AUTOMATION ENGINEERING
Aziende collaboratrici: University of Kentucky
URI: http://webthesis.biblio.polito.it/id/eprint/33109
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