Quantifying the impact of electricity pricing on electric vehicle user behavior: a V2G perspective for smart grid development

ABSTRACT

This research introduces an innovative analytical framework for studying the behavior of electric vehicles (EVs) in power grids. The approach primarily examines the dynamic State of Charge (SOC) and energy reserves of EV batteries. By thoroughly examining patterns of EV charging demand and operational states (charging, discharging, idling, and waiting) across various time intervals, including day and night periods, this study aims to provide a comprehensive understanding of EV dynamic behavior in power networks. The proposed model goes beyond traditional assessments by incorporating human behavioral patterns and responsiveness to economic signals, specifically investigating the impact of electricity pricing on user behavior. The core analysis centers on exploring the Vehicle-to-Grid (V2G) concept, viewing EVs not only as energy consumers but also as potential contributors to grid stability and efficiency. The study delves into how the interplay of dynamic EV behavioral characteristics and owner responses to pricing influences the overall energy consumption curve of the grid, thereby shaping the capability of EVs in providing grid support services. To quantitatively validate the effectiveness of the model, a detailed case study is conducted, offering empirical evidence of its practical utility. The research findings are quantified, highlighting the significant implications for decision-makers, grid managers, and stakeholders in the energy sector. The paper emphasizes the main outcomes, demonstrating how the proposed analytical framework can empower stakeholders in making informed decisions about policy and infrastructure development. The robust methodological approach presented in this paper serves as a valuable tool for evaluating the impacts of adopting V2G, providing strategic insights for a more sustainable and economically viable paradigm.

KEYWORDS:

• Electric vehicles
• V2G
• demand response
• smart grids
• renewable energy
• energy efficiency

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Mohammad Hassan Bahmani

Mohammad Hassan Bahmani, He holds a PhD in electric power systems from Tarbiat Modares University in Tehran, Iran. He holds an M.Sc. from the University of Tehran, and a B.Sc. from Shahid Bahonar University, Kerman. With a strong background in microgrids, and smart grid technologies, Bahmani is proficient in coding languages and numerical modeling.

Mostafa Esmaeili Shayan

Mostafa Esmaeili Shayan, He holds a PhD in Renewable Energy Engineering from Tarbiat Modares University in Iran, where he also received his M.Sc. and B.Sc. degrees in Renewable Energy Engineering and Mechanical and Biosystems Engineering, respectively. His research interests include renewable energies, solar thermal energy, waste heat utilization, electric grid integration, and novel energy storage technologies.

Dillip Kumar Mishra

Dillip Kumar Mishra, He holds a PhD in Electrical Engineering from the University of Technology Sydney, Australia. With an M.Tech in Energy System Engineering and a B.Tech in Electrical Engineering, he brings a strong background in power systems. Currently, he serves as a Postdoctoral Fellow focusing on innovative solutions in the automotive sector.