Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Agent-Based Modelling of Charging Behaviour of Electric Vehicle Drivers
Journal of Artificial Societies and Social Simulation ( IF 3.506 ) Pub Date : 2019-01-01 , DOI: 10.18564/jasss.4133
Mart van der Kam , Annemijn Peters , Wilfried van Sark , Floor Alkemade

The combination of electric vehicles (EVs) and intermittent renewable energy sources has received increasing attention over the last few years. Not only does charging electric vehicles with renewable energy realize their true potential as a clean mode of transport, charging electric vehicles at times of peaks in renewable energy production can help large scale integration of renewable energy in the existing energy infrastructure. We present an agent-based model that investigates the potential contribution of this combination. More specifically, we investigate the potential effects of different kinds of policy interventions on aggregate EV charging patterns. The policy interventions include financial incentives, automated smart charging, information campaigns and social charging. We investigate how well the resulting charging patterns are aligned with renewable energy production and how much they affect user satisfaction of EV drivers. Where possible, we integrate empirical data in our model, to ensure realistic scenarios. We use recent theory from environmental psychology to determine agent behaviour, contrary to earlier simulation models, which have focused only on technical and financial considerations. Based on our simulation results, we articulate some policy recommendations. Furthermore, we point to future research directions for environmental psychology scholars and modelers who want to use theory to inform simulation models of energy systems.

中文翻译:

基于智能体的电动汽车驾驶员充电行为建模

电动汽车(EV)与间歇性可再生能源的结合在过去几年中受到越来越多的关注。用可再生能源给电动汽车充电不仅可以实现清洁交通方式的真正潜力,而且在可再生能源生产达到高峰时给电动汽车充电还可以帮助将可再生能源大规模整合到现有能源基础设施中。我们提出了一个基于代理的模型,该模型调查了这种组合的潜在贡献。更具体地说,我们调查了各种政策干预措施对总电动汽车收费模式的潜在影响。政策干预措施包括经济激励措施,自动智能收费,信息运动和社交收费。我们调查了由此产生的充电模式与可再生能源生产的协调程度以及它们对电动汽车驾驶员的用户满意度有多大影响。在可能的情况下,我们将经验数据整合到我们的模型中,以确保符合实际情况。我们使用环境心理学的最新理论来确定代理商的行为,这与早期的仿真模型相反,后者仅关注技术和财务方面的考虑。根据我们的模拟结果,我们阐明了一些政策建议。此外,我们为希望使用理论为能源系统的仿真模型提供指导的环境心理学学者和建模人员指出了未来的研究方向。确保现实的情况。我们使用环境心理学的最新理论来确定代理商的行为,这与早期的仿真模型相反,后者仅关注技术和财务方面的考虑。根据我们的模拟结果,我们阐明了一些政策建议。此外,我们为希望使用理论为能源系统的仿真模型提供指导的环境心理学学者和建模人员指出了未来的研究方向。确保现实的情况。我们使用环境心理学的最新理论来确定代理商的行为,这与早期的仿真模型相反,后者仅关注技术和财务方面的考虑。根据我们的模拟结果,我们阐明了一些政策建议。此外,我们为希望使用理论为能源系统的仿真模型提供指导的环境心理学学者和建模人员指出了未来的研究方向。
更新日期:2019-01-01
down
wechat
bug