Article
Automation & Control Systems
Shafkat Islam, Shahriar Badsha, Shamik Sengupta, Ibrahim Khalil, Mohammed Atiquzzaman
Summary: The electric vehicle charging ecosystem requires adaptive data-driven cyber-defense mechanisms to tackle cyber-physical system attacks. We propose a federated learning framework based on differential privacy for building a collaborative network intrusion detection system for EV charging stations. We use utility optimized local differential privacy to protect the privacy of local network traffic data at each charging station. Moreover, we propose a reinforcement learning-based intelligent privacy allocation mechanism. The experimental results confirm the efficacy of our proposed mechanism with a privacy provisioning accuracy of approximately 95%.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Mathematics, Interdisciplinary Applications
Wanxing Sheng, Qing Duan, Haoqing Wang, Guanglin Sha, Chunyan Ma
Summary: This paper presents a new microgrid energy management model to address the impact of electric vehicle charging stations on the grid, considering economics and stability, and utilizes an evolutionary multiobjective optimization algorithm to handle constraints.
DISCRETE DYNAMICS IN NATURE AND SOCIETY
(2021)
Article
Economics
Catherine Ledna, Matteo Muratori, Aaron Brooker, Eric Wood, David Greene
Summary: Supporting the adoption of zero-emission vehicles, particularly electric vehicles, is a priority for governments due to their potential to reduce petroleum demand, improve air quality, and lower carbon emissions. This study uses a consumer choice model to simulate vehicle adoption and emissions in California, and demonstrates the effectiveness of public charging infrastructure and vehicle purchase subsidies in promoting EV sales and reducing CO2 emissions under different scenarios.
Article
Engineering, Civil
Syed Muhammad Danish, Kaiwen Zhang, Hans-Arno Jacobsen, Nouman Ashraf, Hassaan Khaliq Qureshi
Summary: The Intelligent Transportation System (ITS) plays an essential role in the economic and technological development of a country, especially with the rise of green ITS research opportunities driven by communication technology maturity and the integration of smart grids and electric vehicles (EVs). However, the untrusted centralized nature of energy markets and EV charging infrastructures poses privacy and security threats to EV user’s private information, leading to the proposal of BlockEV as a blockchain-based solution to address these issues.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Engineering, Civil
Alan Jenn
Summary: With recent policies and announcements, the electrification of vehicles on ride-hailing platforms is inevitable. This study examines the infrastructure deployment required to meet the demand from electric vehicles on Uber and Lyft platforms using actual trip data. A model is developed to analyze case studies and sensitivity scenarios, revealing important findings about charger types, charging behaviors, and charger requirements for ride-hailing EVs compared to the general public.
Article
Energy & Fuels
Qilong Huang, Li Yang, Cangqi Zhou, Lizi Luo, Puyu Wang
Summary: Current research shows that the rapid growth of electric vehicles (EVs) can have a significant impact on the power grid, particularly on directly-connected EV charging stations. To mitigate this impact, a combined scheduling approach of pricing and power management for EVs in the charging station is considered. The problem is formulated as a Markov decision process and solved using a bilevel optimization framework, with the outer optimization solved by rollout method and the inner optimization solved by mixed-integer programming. The effectiveness of this approach is demonstrated through comparisons of turnover and power management under different policies.
Article
Environmental Studies
Zhiyan Yi, Xiaoyue Cathy Liu, Ran Wei
Summary: This paper presents a novel data-driven approach to optimize public charging for electric vehicles (EVs). The study develops a modified geographical PageRank (MGPR) model to estimate EV charging demand based on trip origin-destination (OD) and social dimension features. The results are used to optimize the spatial layout of public charging stations using the capacitated maximal coverage location problem (CMCLP) model. The study demonstrates that the MGPR model effectively quantifies EV charging demand and the optimized charging stations address the spatial mismatch issue. The developed framework can be applied to other regions for EV charging demand estimation and optimal charging infrastructure siting.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2022)
Review
Energy & Fuels
Muhammad Shahid Mastoi, Shenxian Zhuang, Hafiz Mudassir Munir, Malik Haris, Mannan Hassan, Muhammad Usman, Syed Sabir Hussain Bukhari, Jong-Suk Ro
Summary: This paper discusses key factors in planning electric vehicle charging infrastructure, provides information and technological developments for improving the design and implementation of charging station infrastructure.
Article
Engineering, Electrical & Electronic
Yujie Qin, Mustafa A. Kishk, Mohamed-Slim Alouini
Summary: This paper analyzes a strategy for sharing wireless charging infrastructure in UAV and EV networks. By charging UAVs in EV charging stations and paying for the sharing fee, the EV sharing infrastructure can earn extra profit but may slightly reduce service quality. For UAVs, if renting EV charging stations can achieve acceptable system performance, they may not need to build their dedicated charging stations.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Transportation Science & Technology
Dingtong Yang, Navjyoth J. S. Sarma, Michael F. Hyland, R. Jayakrishnan
Summary: The demand for electric vehicles and EV charging has significantly increased in the past decade. This study aims to develop a stochastic dynamic simulation modeling framework for a regional system of EV fast-charging stations, investigating the impact of dynamic demand-responsive price adjustment (DDRPA) schemes on charging demand. The results show that DDRPA strategies are effective in balancing charging demand across fast-charging stations.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Engineering, Electrical & Electronic
Tao Qian, Chengcheng Shao, Xuliang Li, Xiuli Wang, Zhiping Chen, Mohammad Shahidehpour
Summary: In this paper, a multi-agent deep reinforcement learning (MA-DRL) method is proposed to model the pricing game and determine the optimal charging prices for electric vehicle charging stations (EVCSs) in urban transportation networks (UTNs). By analyzing the charging demand and formulating the price competition problem as a game with incomplete information, the MA-DRL approach is used to learn the charging pricing strategies and approximate the Nash Equilibrium (NE) of the pricing game.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Economics
Anant Atul Visaria, Anders Fjendbo Jensen, Mikkel Thorhauge, Stefan Eriksen Mabit
Summary: This paper analyzes user preferences related to electric vehicle charging decisions through qualitative and quantitative assessments. The findings identify the factors influencing charging decisions and highlight the preference for all-inclusive/flat fee pricing structures and interoperability between charging networks. The study also reveals barriers in the charging context.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2022)
Article
Economics
Felix Baumgarte, Matthias Kaiser, Robert Keller
Summary: Investments in public fast charging infrastructure are necessary for the widespread adoption of electric vehicles, but current profitable opportunities are limited to specific locations, leading to a lack of charging facilities in most areas. Various support measures are needed to enhance the profitability of fast charging networks and promote nationwide investments.
Article
Environmental Studies
Tai-Yu Ma, Simin Xie
Summary: A new online vehicle-charging assignment model is proposed to reduce charging delays in electrified shared mobility services, showing promising results in minimizing charging operation time with an efficiency optimization approach.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2021)
Article
Engineering, Electrical & Electronic
Francisco J. Marquez-Fernandez, Joschka Bischoff, Gabriel Domingues-Olavarria, Mats Alakula
Summary: This article proposes a new approach using agent-based simulations to assess the impact of different parameters on the electric transportation system. By analyzing five scenarios for charging infrastructure deployment, it is found that electric road systems offer the lowest system cost while potentially increasing overall energy consumption.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2022)
Review
Computer Science, Interdisciplinary Applications
Divya J. Navamani, Jagabar M. Sathik, A. Lavanya, Dhafer Almakhles, Ziad M. Ali, Shady H. E. Abdel Aleem
Summary: This article reviews three main reliability assessment models, compares their advantages and disadvantages in DC-DC power converters, proposes an optimal assessment tool, and discusses reliability calculation tools and fault identification methods. The importance of reliability study in applications is emphasized, and a comparative analysis of statistical approaches is provided for researchers to choose appropriate methods.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2023)
Article
Thermodynamics
Martin Calasan, Shady H. E. Abdel Aleem, Hany M. Hasanien, Zuhair M. Alaas, Ziad M. Ali
Summary: In this study, a new mathematical expression of PEMFC current as a voltage function is derived and solved using the iterative Lambert W function for the first time. The root-mean-square error (RMSE) and sum-of-squares error (SSE) between the measured and estimated current and voltage values are calculated, analyzed, and discussed. The results validate the effectiveness of the new mathematical model and show that the solutions obtained using ChERWCA outperformed those obtained by other methods presented in the literature.
Article
Green & Sustainable Science & Technology
Hassan Yousif Ahmed, Ziad M. Ali, Mohamed M. Refaat, Shady H. E. Abdel Aleem
Summary: This paper proposes a multi-objective planning framework for EV charging stations in power networks that move towards green transportation electrification. The model combines the planning models of renewable energy systems, energy storage systems, thyristor-controlled series compensators, and transmission lines. The objectives include maximizing EVs' penetration, reducing carbon dioxide emissions, and meeting financial requirements. The proposed model is solved using the multi-objective version of the Gazelle optimization algorithm. The results demonstrate the superiority of the MGOA in solving multi-objective optimization problems and the importance of energy storage systems in improving the EV's hosting capacity.
Article
Green & Sustainable Science & Technology
Mohamed S. Hashish, Hany M. Hasanien, Haoran Ji, Abdulaziz Alkuhayli, Mohammed Alharbi, Tlenshiyeva Akmaral, Rania A. Turky, Francisco Jurado, Ahmed O. Badr
Summary: This paper proposes a new metaheuristic optimization technique called Artificial Gorilla Troops Optimization (GTO) for solving the probabilistic optimum power flow (POPF) issue in a hybrid power system with photovoltaic (PV) and wind energy (WE) sources. The proposed algorithm was evaluated and compared with other algorithms using standard test systems, and it was proven to be efficient in providing optimal solutions. Furthermore, the results showed that the integration of PV and WE sources significantly reduces the total cost of the system.
Article
Energy & Fuels
Ahmed M. Taher, Hany M. Hasanien, Shady H. E. Abdel Aleem, Marcos Tostado-Veliz, Martin Calasan, Rania A. Turky, Francisco Jurado
Summary: This study presents a novel application of transient search optimization (TSO) in combination with model predictive control (MPC) to solve the load frequency control (LFC) problem in multiple zone power networks with renewable generators and storage devices. The TSO-MPC controller outperforms other optimization techniques by >10% in transient specifications and significantly enhances the transient response of the power system.
JOURNAL OF ENERGY STORAGE
(2023)
Editorial Material
Energy & Fuels
Josep M. Guerrero, M. Jagabar Sathik, Rasoul Shalchi Alisha, Dhafer Almakhles
FRONTIERS IN ENERGY RESEARCH
(2023)
Article
Automation & Control Systems
Mihailo Micev, Martin Calasan, Milovan Radulovic, Shady H. E. Abdel Aleem, Hany M. Hasanien, Ahmed F. Zobaa
Summary: This article discusses the use of artificial neural networks (ANN) for black-box modeling of synchronous generators. The ANN is employed to establish the relationship between excitation and terminal generator voltage values, determined using the Levenberg-Marquardt algorithm. The proposed ANN model is found to be accurate, providing a high degree of matching with experimental results and outperforming other nonlinear models.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Mathematics, Applied
Mohamed Metwally Mahmoud, Basiony Shehata Atia, Yahia M. Esmail, Sid Ahmed El Mehdi Ardjoun, Noha Anwer, Ahmed I. Omar, Faisal Alsaif, Sager Alsulamy, Shazly A. Mohamed
Summary: This study proposes the use of a whale optimization algorithm (WOA) based on a fractional-order proportional-integral controller (FOPIC) for unified power quality conditioner (UPQC) and STATCOM tools to address the issues faced by renewable energy systems (RESs) and nonlinear loads when connected to the electricity grid. By improving the control system, the proposed approach enhances system reliability, dynamic response speed, and reduces total harmonic distortion (THD) to improve power quality (PQ). Three different configurations are studied and assessed, and the results show significant improvements in PQ and system performance compared to the base case.
Article
Energy & Fuels
Mahmoud F. Elmorshedy, Umashankar Subramaniam, Jagabar Sathik Mohamed Ali, Dhafer Almakhles
Summary: This article proposes a hybrid DC microgrid (HDCMG) with different levels of DC bus voltages to cater to various types of loads. The HDCMG utilizes wind generating systems (WGSs), photovoltaic (PV) systems, battery banks, and the AC grid for emergencies. The controller is crucial in achieving the desired DC bus voltage levels and extracting maximum power from the WGS and PV systems. An energy management strategy (SEMS) is developed to ensure power continuity for critical loads and optimize system performance. The HDCMG is evaluated using MATLAB/Simulink under different scenarios, demonstrating its capabilities and good performance.
Article
Engineering, Electrical & Electronic
Nourhan A. Maged, Hany M. Hasanien, Essamudin A. Ebrahim, Marcos Tostado-V, Rania A. Turky, Francisco Jurado
Summary: Distributed power grid systems need intelligent and adaptable control management to maintain optimal performance. This research compares an autonomous microgrid system controlled by fuzzy logic and proportional-integral controller, using optimization algorithms based on African vulture and gorilla troops. The proposed control techniques are validated in a MATLAB/Simulink environment.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Multidisciplinary Sciences
Mohamed Awad, Mohamed Metwally Mahmoud, Z. M. S. Elbarbary, Loai Mohamed Ali, Shazly Nasser Fahmy, Ahmed I. Omar
Summary: This paper compares the efficiency and performance of PV and WT systems as sources of RESs for powering a PEMEL under different conditions. The study evaluates the input/output power, MPPT controller efficiency, green hydrogen production rate, and system efficiency for both PV and WT. Results show that WT produces twice the PEMEL capacity compared to the PV system. The study provides valuable insights for designing PV or WT systems to power an electrolyzer. MATLAB is used to validate the proposed configurations and control schemes.
Article
Mathematics, Interdisciplinary Applications
Muhyaddin Rawa, Sultan Alghamdi, Martin Calasan, Obaid Aldosari, Ziad M. Ali, Salem Alkhalaf, Mihailo Micev, Shady H. E. Abdel Aleem
Summary: This paper introduces a novel approach to design AVR systems as 6ISO systems and compares generator voltage responses for different structural configurations and regulator parameter choices. The effectiveness of various controllers is investigated, leading to a proposed improvement in regulator parameter design using the PSO-AVOA algorithm.
FRACTAL AND FRACTIONAL
(2023)
Article
Engineering, Multidisciplinary
Nor Hidayah Abdul Kahar, Ahmed F. Zobaa, Rania A. Turky, Ahmed M. Zobaa, Shady H. E. Abdel Aleem, Bazilah Ismail
Summary: Harmonic pollution has become a significant problem in power networks, and this paper presents an optimal design strategy for passive power filters using the MIDACO solver. The design criteria include minimizing active power losses, maximizing the true power factor, and maximizing the transmission efficiency. Constraints such as quality factors, harmonic resonance damping, power factor range, and voltage harmonic distortion are considered. The effectiveness of the MIDACO solver is validated through comparison with other optimization algorithms.
AIN SHAMS ENGINEERING JOURNAL
(2023)
Article
Computer Science, Information Systems
M. Jagabar Sathik, Mahmoud F. Elmorshedy, Dhafer J. Almakhles
Summary: This paper proposes a single-dc-source, seven-level (7L) inverter scheme with a dynamic voltage gain for solar applications. The proposed circuit combines two DC-DC boost converters in series for discharging and parallel for charging. The finite set model predictive controller is used to maximize power delivery to the load. The mathematical expression of volt-ampere balances is provided. Experimental validation demonstrates a 96.7% improvement in power quality and efficiency, considering variables such as load fluctuation and modulation index variation.
