Year: 2025
Type: conference-paper
Abstract: An e-taxi fleet consumes a significant amount of energy daily, making it a substantial electricity consumer. Unlike traditional consumers, such as factories and buildings, a fleet coordinates charging activities across both times and locations, offering considerable flexibility in its energy demand. This allows a fleet to achieve substantial reductions in energy consumption in response to demand response requests while maintaining transportation service quality. To better understand and control this intrinsic energy flexibility, we propose the eFlx framework for managing e-taxi fleets for demand response. In the eFlx framework, we establish a model to characterize the energy flexibility upon receiving a real-time demand response request. We then investigate the energy flexibility provisioning problem, formulated as a bi-level optimal control problem, which aims to optimize and maintain the energy flexibility of the fleet for potential demand response requests that could arise at any time. To achieve real-time flexibility provisioning, we develop an efficient iterative algorithm to solve this problem. Data-driven evaluations with NYC datasets demonstrate that eFlx achieves a 19. 98% greater reduction in energy demand compared to existing solutions, without requiring extra charging or compromising the quality of taxi service.
Authors: Liangkai Zhou, Yue Zhao, Yukun Yuan, Ce Xu, Shan Lin
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
Awards: G1915844967, Collaborative Research: CISE MSI: RDP: CPS: Enhancing Efficiency and Sustainability in Electric Transportation and Power Systems through Interaction-Aware Management, Collaborative Research: Learning for Faster Computations to Enhance Efficiency and Security of Power System Operations
OpenAlex ID: W4410140556