Work

Short-term scheduling optimization of battery electric buses in the context of sustainable energy resources under uncertainty

Year: 2025

Type: article

Abstract: With growing emphasis on sustainability goals, particularly in adopting electric vehicles (EVs) as a public transportation mode, battery electric buses (BEBs) have attained significant market attention. However, a critical obstacle lies in efficiently assigning BEBs to suitable charging stations (CSs) during daily transit operations, which still need enough space to be filled. The aim is to address this issue by leveraging diverse input parameter models in a context that seamlessly integrates services to the grid and passengers' needs. The primary goal is to allocate BEB to the best charging stations while focusing on increasing overall profit by serving the grid and passenger needs effectively. To solve this issue, several factors are considered, including transit hours, sustainable energy resources, state-of-charge (SOC), vehicle-to-grid (V2G) and grid-to-vehicle (G2V) service trading, bus, charging station capacity, data-sharing, and route dynamics. A novel methodology is proposed, utilizing energy network flows and operational-level information to optimize short-term scheduling. A mixed-integer linear programming (MILP) model is developed due to the large-scale nature of the problem, metaheuristic algorithms are used to solve the model instead of exact solution methods. Enabling the transportation company (TC) which owns both CSs and BEBs, to schedule suitable CS selection for its en-routed buses while simultaneously considering the peak hours of energy capacities and its transactions to maximize revenue. To enhance realism, the model is extended to robust counterpart formulation, accounting for uncertainties in key parameters including demand, price, and capacity. This model provides sufficient insights to facilitate short-term charging scheduling during regular operations to optimize income effectively.

Source: International Journal of Electrical Power & Energy Systems

DOI: 10.1016/j.ijepes.2025.110715

Authors: Muhammad Ahmad Iqbal, Ismail I. Almaraj

Institution: King Fahd University of Petroleum and Minerals

Language: English

Topic: Electric Vehicles and Infrastructure

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $3,920