Firm level optimisation strategies for sustainable and cost effective electric vehicle workplace charging.

npj Sustainable Mobility and Transport Pub Date : 2025-01-01 Epub Date: 2025-03-17 DOI:10.1038/s44333-025-00032-w
Marcel Seger, Christian Brand, Christoph Clement, James Dixon, Charlie Wilson
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Abstract

Expanding electric vehicle (EV) charging infrastructure is essential for transitioning to an electrified mobility system. With rising EV adoption rates, firms face increasing regulatory pressure to build up workplace charging facilities for their employees. However, the impact of EV charging loads on businesses' specific electricity consumption profiles remains largely unknown. Our study addresses this challenge by presenting a mathematical optimisation model, available via an open-source web application, that empowers business executives to manage energy consumption effectively, enabling them to assess peak loads, charging costs and carbon emissions specific to their power profiles and employee needs. Using real-world data from a global car manufacturer in South East England, UK, we demonstrate that smart charging strategies can reduce peak loads by 28% and decrease charging costs and emissions by 9% compared to convenience charging. Our methodology is widely applicable across industries and geographies, offering data-driven insights for planning EV workplace charging infrastructure.

公司层面的可持续和成本效益的电动汽车工作场所充电优化策略。
扩大电动汽车(EV)充电基础设施对于向电气化交通系统过渡至关重要。随着电动汽车采用率的不断提高,企业面临着越来越大的监管压力,必须为员工建立工作场所充电设施。然而,电动汽车充电负荷对企业具体用电情况的影响在很大程度上仍是未知数。为了应对这一挑战,我们的研究通过开源网络应用程序提出了一个数学优化模型,使企业高管能够有效地管理能源消耗,使他们能够评估峰值负荷、充电成本和碳排放,以满足其用电情况和员工需求。通过使用英国英格兰东南部一家全球汽车制造商的真实数据,我们证明了与便捷充电相比,智能充电策略可将峰值负荷降低 28%,充电成本和排放量降低 9%。我们的方法广泛适用于各个行业和地区,为电动汽车工作场所充电基础设施的规划提供了数据驱动的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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