MILP-based customer-oriented E-Fleet charging scheduling platform

Abstract

Conventional road transport is a significant contributor to greenhouse gas emissions and air pollution. Electric mobile assets (E-buses, E-trucks, E-taxis, and even E-ferries) are an efficient, low noise, low emission alternative which could—if operated alongside significant renewable energy capacity—help to improve air quality and avoid catastrophic global warming. In this study, a Mixed Integer Linear Programming-based solution for operating a fleet of E-mobile assets has been proposed, considering technical and operational characteristics of different fleet elements. It takes into account customer (E-fleet operator) objectives, such as load balancing and charging cost minimization. Furthermore, the E-depot charging capacity increase achieved through integrating an energy storage system has been studied and discussed. The results of the optimization have been discussed and reported using a case study (demonstrating peak reduction of up to 50% and total charging reduction of 27%) and the benefits of operating an E-fleet using the proposed solution have been discussed from economic and technical perspectives.