Aduama Prince, Al-Sumaiti Ameena S, Al-Hosani Khalifa H, El-Shamy Ahmed R
Department of Electrical Engineering and Computer Science, Khalifa University, Shakhbout Bin Sultan St Zone 1, Abu Dhabi, United Arab Emirates.
Advanced Power and Energy Center, Department of Electrical Engineering and Computer Science, Khalifa University, Shakhbout Bin Sultan St Zone 1, Abu Dhabi, United Arab Emirates.
Heliyon. 2024 Jul 23;10(15):e34857. doi: 10.1016/j.heliyon.2024.e34857. eCollection 2024 Aug 15.
This paper presents a mathematical optimization framework for the strategic placement of quasi-dynamic wireless charging (QWC) stations within road networks to address the charging needs of battery electric buses (BEBs). This study evaluates two scenarios for powering the buses. In the first scenario, a grid-connected system is considered. The optimization aims to minimize annual costs related to capital, operation, and energy losses of the electric bus fleet. This involves determining the optimal locations for QWC stations, the length of power transmitters, and the corresponding battery capacities for the BEBs. Using MATLAB-based optimization tools Casadi and Yalmip, with solvers Bonmin and Fmincon, the optimal configuration includes a 13 kWh battery capacity and a 300 m power transmitter distributed across five bus stop areas. The second scenario employs a chance-constrained optimization approach for an isolated solar photovoltaic (PV) and battery energy storage system (BESS). This system is designed to reliably meet the BEBs' energy requirements throughout the day, considering different seasonal data (winter, summer, all seasons/year-round). The optimization results for the PV and BESS capacities vary with the seasons: 394.247 kW and 2012.6 kWh using summer data, 1762.1 kW and 2738.2 kWh using winter data, and 1610.8 kW and 2741.9 kWh using year-round data. Additionally, the paper examines the impact of varying bus fleet sizes on the optimal battery size and power transmitter combination using a real-world example of the bus route between Khalifa City and Abu Dhabi Downtown in the UAE. The findings suggest that larger batteries with fewer or no charging stations are more economical for smaller fleets. Conversely, as the fleet size increases, a combination of smaller battery sizes and a greater number (and length) of QWC (power transmitters) becomes more cost-effective. This research offers significant insights into the efficient deployment of QWC stations and the integration of renewable energy and energy storage for sustainable urban electric bus networks. The proposed optimization models provide a systematic approach to designing and operating charging infrastructure, contributing to sustainable urban transportation systems. Moreover, the study highlights the influence of seasonal data on PV system sizing and costs.
本文提出了一种数学优化框架,用于在道路网络中对准动态无线充电(QWC)站进行战略布局,以满足电动公交(BEB)的充电需求。本研究评估了为公交车供电的两种方案。在第一种方案中,考虑了一个并网系统。优化的目标是使与电动公交车队的资本、运营和能量损失相关的年度成本最小化。这涉及确定QWC站的最佳位置、功率发射器的长度以及电动公交相应的电池容量。使用基于MATLAB的优化工具Casadi和Yalmip以及求解器Bonmin和Fmincon,最优配置包括13千瓦时的电池容量和分布在五个公交站点区域的300米功率发射器。第二种方案采用机会约束优化方法来设计一个孤立的太阳能光伏(PV)和电池储能系统(BESS)。该系统旨在考虑不同季节数据(冬季、夏季、全年),可靠地满足电动公交全天的能量需求。光伏和电池储能系统容量的优化结果随季节而变化:夏季数据下为394.247千瓦和2012.6千瓦时,冬季数据下为1762.1千瓦和2738.2千瓦时,并使用全年数据下为1610.8千瓦和2741.9千瓦时。此外,本文以阿联酋哈利法城和阿布扎比市中心之间的公交线路为例,研究了不同公交车队规模对最佳电池尺寸和功率发射器组合的影响。研究结果表明,对于较小的车队,配备较少或没有充电站的较大电池更经济。相反,随着车队规模的增加,较小电池尺寸与更多数量(和长度)的QWC(功率发射器)相结合会变得更具成本效益。这项研究为QWC站的高效部署以及可再生能源和储能的整合以实现可持续城市电动公交网络提供了重要见解。所提出的优化模型为充电基础设施的设计和运营提供了一种系统方法,有助于实现可持续城市交通系统。此外,该研究突出了季节数据对光伏系统规模和成本的影响。