A comparative techno-economic assessment of bidirectional heavy duty and light duty plug-in electric vehicles operation: A case study

Abstract

The proliferation of electric vehicles (EVs) all around the world offers both challenges and opportunities to build a sustainable city and transportation system. Bidirectional charging capabilities at workplace charging facilities (e.g., as part of a microgrid) have made the overall economic optimization more attractive on one hand, but also more complex on the other hand. This paper investigates the cost optimization problem for bidirectional charging at a workplace microgrid connected to two different buildings to determine the optimal framework for a combination of both heavy-duty and light-duty electric vehicles (HDEV and LDEV). A deep learning-based model has been developed to forecast the 15-minute solar generation and building power consumption. Real-time travel profile data has been used to represent the temporal uncertainty of electric vehicle charging. The cost optimization problem is formulated as a Mixed Integer Programming (MIP) model which also addresses battery life degradation. Furthermore, a comprehensive economic analysis has been carried out to analyze the payback period, peak reduction, and cost savings for two different buildings at the same workplace with both on-board and off-board charger configurations. It has been found that HDEV is a better cost-effective solution in comparison to LDEV in terms of energy cost reduction and payback periods. Net metering capability leads to higher energy savings and peak reductions in most cases.