Article
Engineering, Electrical & Electronic
Syed Muhammad Arif, Tek Tjing Lie, Boon Chong Seet, Soumia Ayyadi
Summary: This paper proposes a cost-efficient energy management system based on a double-sided auction mechanism for energy trading in the PEBDC ecosystem, addressing the impact of integrating PV and ESS on the LV feeder. The MILP model for Bus Depot Owner profit maximization was analyzed using IBM ILOG studio and CPLEX solver.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Article
Management
K. Gkiotsalitis, C. Iliopoulou, K. Kepaptsoglou
Summary: This study extends the multi-depot vehicle scheduling problem with time windows (MDVSPTW) to incorporate electric vehicles and proposes a mixed-integer nonlinear model for the electric bus multi-depot vehicle scheduling problem with time windows (EB-MDVSPTW). The model considers operational cost, waiting times, capacity of charging stations, and prohibits simultaneous charging of different vehicles at the same charger. Valid inequalities are introduced to improve the computational efficiency of the problem. Numerical experiments show the effectiveness of the approach and the reduction in computational time.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Engineering, Multidisciplinary
Yahong Liu, Xingquan Zuo, Xiaodong Li, Shaokang Nie
Summary: Bus scheduling problem is vital for service quality and cost-saving. However, electric bus scheduling problem is difficult due to limited driving range and charging requirements. This article proposes a genetic algorithm with trip-adjustment strategy (GA-TAS) to solve the multi-depot electric bus scheduling problem (MD-EBSP). Experiments show that GA-TAS outperforms other approaches on various driving tasks.
ENGINEERING OPTIMIZATION
(2023)
Article
Green & Sustainable Science & Technology
S. Rafique, M. S. H. Nizami, U. B. Irshad, M. J. Hossain, S. C. Mukhopadhyay
Summary: This paper proposes a novel energy management system for bus depot operators to trade energy in the market and reduce operational costs. Simulation studies validate the effectiveness of the proposed system, showing it can significantly reduce energy costs compared to other scheduling strategies.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Thermodynamics
Yaseen Alwesabi, Zhaocai Liu, Soongeol Kwon, Yong Wang
Summary: The study aims to optimize the fleet size of electric buses and dynamic wireless charging infrastructure planning, through the development of a Mixed Integer Linear Programming model. Results showed that considering bus purchase costs can save the total system cost.
Article
Green & Sustainable Science & Technology
Mengyan Jiang, Yi Zhang
Summary: This paper addresses the multi-depot e-bus scheduling problem with the consideration of the vehicle relocation constraint and partial charging. A mixed integer programming model is formulated to minimize the operational cost, and a Large Neighborhood Search (LNS) heuristic is devised to tackle the vehicle relocation constraint. Numerical experiments based on multi-route operation cases in Shenzhen verify the model and effectiveness of the LNS heuristic.
Article
Engineering, Civil
Tianwei Lu, Enjian Yao, Yongsheng Zhang, Yang Yang
Summary: This study proposes a joint optimal scheduling model for a mixed bus fleet under micro driving conditions, using estimation of bus trip time and buffer time setting methods to construct an optimization model for scheduling. A heuristic procedure based on the genetic algorithm is used to improve upon the conventional model.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Huayan Shang, Yanping Liu, Wenxiang Wu, Fangxia Zhao
Summary: The goal of this study is to reduce passenger crowding on buses without wasting bus capacity. A bi-objective integer programming model was created, considering the crowding cost due to different vehicle sizes. A vehicle scheduling algorithm was developed to find solutions that consider vehicle capacity constraints. Validation using a real-world transit network in Beijing showed that the proposed model and algorithm effectively reduced passenger crowding cost and avoided wasting transport capacity.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Transportation Science & Technology
Farzad Avishan, Ihsan Yanikoglu, Yaseen Alwesabi
Summary: The public transportation system is undergoing significant changes due to the expansion of electromobility infrastructure and operations. This paper proposes a novel linear programming model to tackle the scheduling and procurement problem of electric fleets under travel time and energy consumption uncertainty. The model is evaluated through Monte Carlo simulation and a case study on a college transport network.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Economics
Matias Alvo, Gustavo Angulo, Mathias A. Klapp
Summary: The study focuses on efficiently planning a bus dispatch operation within a public transport terminal with a mixed fleet and limited chargers, modeling the problem as an extension of the Vehicle Scheduling Problem and using a Benders' type decomposition approach to solve it. Feasibility cuts dynamically injected into the branch-and-bound tree help remove infeasible bus charging operations, with computational experiments showing the effectiveness of the approach over a single-stage model. Insights for planners include the marginal benefit of additional chargers or electric buses and the value added by a mixed fleet compared to a pure electric one.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2021)
Article
Environmental Studies
Yu-Ting Hsu, Shangyao Yan, Powei Huang
Summary: This study investigates the transition from diesel-consuming buses to electric ones, focusing on determining locations of bus depots, charging and maintenance stations. An optimization model and heuristic algorithm are developed, with a case study in Taiwan. Major cost components are evaluated to help operators/planners make informed decisions during the transition towards electric bus systems.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2021)
Review
Management
Shyam S. G. Perumal, Richard M. Lusby, Jesper Larsen
Summary: The electrification of bus fleets in cities has environmental benefits, but electric buses face limitations in terms of range, charging times, and infrastructure requirements. This study reviews the problems in electric bus planning, including fleet investment, placement of charging infrastructure, vehicle scheduling, and charging scheduling. The review also identifies the need for research on scheduling robustness and rescheduling of electric vehicles, as well as integrated approaches to improve the efficiency of electric bus transport systems.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Management
Heiko Diefenbach, Simon Emde, Christoph H. Glock
Summary: This paper addresses the electric vehicle scheduling problem in an in-plant logistics setting with multiple charging stations. It introduces an integer programming model and a branch-and-check solution procedure to minimize the required fleet size. The study considers different battery charging functions and shows that the branch-and-check approach outperforms the standard solver in terms of computational efficiency.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Chunlu Wang, Congcong Guo, Xingquan Zuo
Summary: This study focuses on the multi-depot electric vehicle scheduling problem in public transit and proposes a genetic algorithm based column generation approach. Experimental results show that this approach can effectively solve the problem with shorter computational time compared to other algorithms.
APPLIED SOFT COMPUTING
(2021)
Article
Thermodynamics
Shah Mohammad Mominul Islam, Arshad Adam Salema, Mohammed Zeehan Saleheen, Joanne Mun Yee Lim
Summary: A study was conducted on the techno-economic feasibility of using solar energy for an electric bus depot, with the conclusion that implementing a bus charging routine can significantly reduce operational costs and carbon emissions, providing an optimal energy-saving solution.
Article
Energy & Fuels
N. Ding, K. Prasad, T. T. Lie
Summary: This paper introduces a hybrid EMS system for PHEV, using a rule-based control strategy and genetic algorithm optimization technique to overcome battery limitations. Simulation studies have shown significant improvements in emissions control with the proposed system.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Energy & Fuels
Ifedayo Oladeji, Ramon Zamora, Tek Tjing Lie
Summary: This paper proposes a fast security monitoring model that includes security prediction and load shedding for security control, where the security of the grid is predicted by considering load level, inertia constant, fault location, and power dispatched from the renewable energy sources generator. The model can estimate the amount of load shed required and determine the optimal node for load shedding operation.
Review
Energy & Fuels
Zaid Hamid Abdulabbas Al-Tameemi, Tek Tjing Lie, Gilbert Foo, Frede Blaabjerg
Summary: This paper provides a comprehensive review of control strategies for DC MG clusters, including DC-link voltage control and power flow control between MGs. It discusses the architecture configuration of DC MG clusters, as well as the advantages and limitations of various control strategies, and proposes future research recommendations based on the reviewed studies.
Article
Computer Science, Information Systems
Asaad Mohammad, Ramon Zamora, Tek Tjing Lie
Summary: This article introduces a transactive energy management system for commercial parking lots to balance charging demand with supply and achieve cost savings up to 12.09% through a double-sided auction bidding mechanism.
IEEE SYSTEMS JOURNAL
(2021)
Article
Green & Sustainable Science & Technology
Nicholas Mukisa, Ramon Zamora, Tek Tjing Lie
Summary: This study presents a multi-criteria analysis of alternative energy technologies based on the sustainable livelihoods framework. It proposes a time bound development predicting model and compares it with a time unbound development predicting model. The results reveal that rooftop solar PV is the best-choice technology and predict a high level of development for Uganda in the next 50 years.
Review
Chemistry, Multidisciplinary
Kosala Gunawardane, Nisitha Padmawansa, Nihal Kularatna, Kasun Subasinghage, Tek Tjing Lie
Summary: This paper provides a comprehensive review of the evolution and research trends of linear-type DC-DC converters in power supply applications, including the development of LDO regulators and the design and application of supercapacitor-assisted low-dropout regulators.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Information Systems
Zaid Hamid Abdulabbas Al-Tameemi, Tek Tjing Lie, Gilbert Foo, Frede Blaabjerg
Summary: This study proposes a hierarchical control strategy to tackle the generation-load mismatch in clustered DC microgrids, and optimize the performance of the global layer using Grey Wolf Optimizer. Simulation results show that the optimized global layer outperforms the conventional ones in power-sharing, voltage regulation, and energy losses.
Article
Engineering, Marine
Sadegh Khaleghi, Tek Tjing Lie, Craig Baguley
Summary: In this paper, a novel system combining a windcatcher with a conventional oscillating water column (OWC) is proposed to increase airflow rate and output power. The hydrodynamic behavior of the proposed system is investigated using a nonlinear computational fluid dynamics (CFD) model. Results show a significant increase in airflow rate and consistent power generation in the proposed hybrid system compared to a conventional type.
Article
Energy & Fuels
Syed Muhammad Ahsan, Hassan Abbas Khan, Naveed-ul-Hassan
Summary: The study proposes a multi-objective optimization framework for maximizing the profit of multiple interconnected buildings and scheduling electric vehicles. The optimized charging using local resources provides economic, technological, and environmental advantages.
Article
Multidisciplinary Sciences
Mohammad Zohaib, Muhammad Ahsan, Mudassir Khan, Jamshed Iqbal
Summary: In this paper, a ROS-based efficient algorithm for constructing dynamic maps is proposed, which utilizes spatial-temporal locality for detecting and tracking moving objects without prior knowledge of their geometrical features. The algorithm efficiently decodes sensory data to estimate the time-varying object boundary and updates the dynamic environment through manipulating spatial-temporal locality, achieving lower time-complexity. The algorithm is validated through simulations and experiments, demonstrating accurate detection and tracking of objects under low sensor noise and acceptable speed limits.
Review
Green & Sustainable Science & Technology
Nicholas Mukisa, Ramon Zamora, Tek Tjing Lie
Summary: This study provides an overview of the adoption extent of energy business models worldwide, showing that developed countries have widely embraced renewable energy initiatives, while developing countries face challenges in this area. It also discusses the shift in developing countries from customer-owned to community-shared energy business initiatives and analyzes existing billing schemes and store-on grid schemes applicable to energy business models.
Article
Energy & Fuels
Ifedayo Oladeji, Ramon Zamora, Tek Tjing Lie
Summary: This paper proposes a decision tree classification approach for determining the optimal placement of multiple photovoltaic DG units in an unbalanced distribution network, considering security indices such as risk index and power loss. The proposed technique outperforms existing methods in reducing power loss and enhancing voltage.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Review
Energy & Fuels
Hussam Almukhtar, Tek Tjing Lie, Wisam A. M. Al-Shohani, Timothy Anderson, Zaid Al-Tameemi
Summary: This study provides a comprehensive review of the impact of dust characteristics on PV systems and emphasizes the need for further research to improve efficiency and lifespan.
Article
Computer Science, Information Systems
Carlos A. Reusser, Ramon Herrera Hernandez, Tek Tjing Lie
Summary: This work proposes a hybrid drive controlled configuration that minimizes CO2 emissions by controlling the power flow direction of the Electric Machine (EM) using a minimum emissions search algorithm. The power flow is controlled by a bi-directional Model Predictive Control (MPC) scheme based on an emissions optimization algorithm. The proposed drivetrain configuration ensures the Minimum Emission Operating Point (MEOP) of the ICE regardless of the mechanical demand at the drivetrain. The simulation and validation results using a Hardware in the Loop (HIL) virtual prototype validate the proposed overall optimization strategy.
Article
Computer Science, Information Systems
Umer Ayub, Syed M. Ahsan, Shavez M. Qureshi
Summary: Advancements in sensor technology have led to the production of a huge amount of video and image data. However, the use of low-performance hardware and resource-heavy image processing approaches poses a bottleneck in extracting actionable insights. In this paper, a data pipeline system is proposed that utilizes open-source tools and commodity hardware for video stream processing and image processing in a distributed environment.
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS
(2022)
