Article
Engineering, Electrical & Electronic
Erdem Guemruekcue, Jonatan Ralf Axel Klemets, Jon Are Suul, Ferdinanda Ponci, Antonello Monti
Summary: This study introduces a decentralized management concept for urban charging hubs, where electric vehicles can access multiple charger clusters controlled by aggregators. The provided day ahead schedules and peak power limits of the aggregators can restrict energy supply. A suitable energy management concept is required to mitigate the impact on EV users. In the proposed approach, an electromobility operator allocates incoming EVs into charger clusters using a smart routing algorithm that optimizes cluster allocations and charging schedules. Real-time charging control is achieved through an optimization problem solved by each aggregator. The results demonstrate the effectiveness of the proposed concept in reducing deviations from schedules and violations of power limits, while decreasing unfulfilled charging demand and unscheduled discharge from EV batteries.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2023)
Article
Automation & Control Systems
Si Lv, Sheng Chen, Zhinong Wei
Summary: With the increasing use of electric vehicles, the coordination between power and transportation networks becomes crucial for maximizing the benefits. This article proposes a Nash-Stackelberg-Nash game framework to model the interactions between drivers and network operators. A subsidy-based method is introduced to address the upper bounding issue in the existing tariff-based incentive scheme. The effectiveness of the noncooperative operation and the subsidy-based scheme is demonstrated through numerical experiments.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Civil
Mahsa Ghavami, Mohammad Haeri, Hamed Kebriaei
Summary: In this paper, the problem of managing traffic and Charging Stations (CSs) crowdedness in the context of Electric Vehicles (EVs) is addressed. The authors propose a non-cooperative game model and a linear pricing policy to optimize the efficiency of EVs' decision strategies. The model considers a hierarchical game between a Smart City Coordinator (SCC) and EVs, where the SCC designs optimal price functions for CSs and Traffic Coordinator (TC) to maximize social profits. The proposed method enables simultaneous and global-optimum management of traffic and CSs' crowdedness, and a decentralized algorithm is introduced to preserve the privacy of EVs.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Thermodynamics
Peter Makeen, Saim Memon, M. A. Elkasrawy, Sameh O. Abdullatif, Hani A. Ghali
Summary: This paper presents a smart charging decision-making criterion for enhancing the scheduling of electric vehicles during the charging process, utilizing genetic algorithm and water cycle optimization algorithm for decision-making algorithms development. The proposed criterion aims to optimize charging time, select charging methodology, maximize charging capacity, and minimize queuing delay to improve efficiency.
INTERNATIONAL JOURNAL OF GREEN ENERGY
(2022)
Article
Computer Science, Information Systems
Michela Moschella, Pietro Ferraro, Emanuele Crisostomi, Robert Shorten
Summary: This article introduces a stochastic decentralized algorithm for recommending charging stations to plug-in electric vehicles, utilizing different cost functions and IoT architecture with distributed ledger technology to ensure compliance and reduce driver misbehaviors. Extensive simulations conducted in city-wide networks validate the effectiveness of the proposed algorithm for PEV assignment.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Automation & Control Systems
Oliver Frendo, Nadine Gaertner, Heiner Stuckenschmidt
Summary: Smart charging involves assigning charging capacities between vehicles in limited infrastructures and can now be found in both commercial and open source solutions. This article introduces an open source package with a smart charging algorithm and presents implementation aspects and field test results showing its effectiveness. By scheduling vehicles for charging while ensuring fair share, the smart charging algorithm has demonstrated real-time applicability and scalability to large fleet sizes.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Green & Sustainable Science & Technology
Amrit Paudel, Syed Asad Hussain, Rehan Sadiq, Hamidreza Zareipour, Kasun Hewage
Summary: The deployment of electric vehicles poses challenges to power system planning and operation. This study presents a decentralized cooperative approach for charging electric vehicles, incorporating a consensus-based iterative algorithm to protect user privacy and address charging urgency. The proposed strategy allows multiple electric vehicles to be charged simultaneously without a central decision-maker, maximizing user satisfaction while respecting constraints.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Engineering, Electrical & Electronic
Mauro Zucca, Paolo Squillari, Umberto Pogliano
Summary: This article describes a new traceable measurement system designed for the characterization of inductive charging stations for electric vehicles, focusing on static charging. The system can accurately measure the performance and efficiency of charging stations and converters, improving the ability to characterize wireless charging stations both in field and laboratory environments.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2021)
Article
Computer Science, Interdisciplinary Applications
Yeming Dai, Yao Qi, Lu Li, Baohui Wang, Hongwei Gao
Summary: This paper proposes a dynamic pricing scheme for EV charging stations based on a Stackelberg game model to optimize the charging strategy of PV charging stations and implement EV user demand response. Through analyzing the probability properties of model constraints, the game model with uncertainty is transformed into a convex game.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Aastha Kapoor, Viresh S. Patel, Ankush Sharma, Abheejeet Mohapatra
Summary: This paper proposes three novel pricing schemes for the day-ahead optimal scheduling of Electric Vehicles (EVs) based on the centralized and decentralized architectures. These schemes effectively address the issues of load valley-filling and rebound peak occurrence while fulfilling the objectives of multiple players.
IEEE TRANSACTIONS ON SMART GRID
(2022)
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
Green & Sustainable Science & Technology
Yan Zhang, Bak Koon Teoh, Limao Zhang
Summary: The paper proposes a hybrid approach integrating GIS and BN to deal with the location selection problem of charging stations for EVs. The transportation efficiency is identified as the most important factor in the location selection, more important than social and economic efficiency.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Energy & Fuels
Runzi Lin, Zhenhui Xu, Xiaoliang Huang, Jinwu Gao, Hong Chen, Tielong Shen
Summary: This paper proposes an optimal scheduling management and decentralized charging control strategy for EVs in parking lots, and verifies its effects on charging cycle control and electricity price fluctuations through numerical simulations.
Article
Engineering, Electrical & Electronic
Kai Ma, Xiaoyan Hu, Jie Yang, Zhiyuan Yue, Bo Yang, Zhixin Liu, Xinping Guan
Summary: This paper investigates the charging problem in intelligent transportation system and proposes a model that helps taxis reduce operating costs by selecting charging stations with the lowest charging cost and increases revenues for charging stations by adjusting charging prices. Simulation results show that the model effectively ensures the operational effectiveness of taxis.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Automation & Control Systems
Mohammad Ali Hosseinzadeh, Maryam Sarebanzadeh, Cristian F. Garcia, Ebrahim Babaei, Jose Rodriguez, Ralph Kennel
Summary: This article introduces a generalized topology for multisource inverters (MSIs) and discusses their advantages in reducing the battery capacity requirements of electric vehicles. The feasibility of the proposed approach is validated through simulation results, and experimental results are presented to verify the correct operation of the system under static load.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Computer Science, Information Systems
Xiaojun Yu, Muhammad Zulkifal Aziz, Muhammad Tariq Sadiq, Ke Jia, Zeming Fan, Gaoxi Xiao
Summary: This study introduces a computer-aided broad learning EEG system (CABLES) for the classification of six distinct EEG domains. The proposed CABLES framework outperforms existing domain-specific methods in terms of classification accuracies and multirole adaptability.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2022)
Article
Engineering, Electrical & Electronic
Xinghua Liu, Xiang Li, Jiaqiang Tian, Yubo Wang, Gaoxi Xiao, Peng Wang
Summary: This paper presents an economic dispatching method for a large-scale wind-photovoltaic-hydro-battery system. The LSTM neural network is used to predict the output power of wind and photovoltaic power generation, and the LHS method and synchronous reduction algorithm are employed to obtain different scenarios. The integration of concentrated solar power, hydropower stations, batteries, and transferable loads effectively reduces the fluctuation and curtailment rates of wind and photovoltaic power generation.
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS
(2022)
Article
Automation & Control Systems
Yihan Lin, Jiawei Sun, Guoqi Li, Gaoxi Xiao, Changyun Wen, Lei Deng, H. Eugene Stanley
Summary: The number of control sources is a limiting factor in many network control tasks, but exploiting the temporal variation of network topology can overcome this limitation. The proposed spatiotemporal input control strategy reduces the required number of sources to 2, which is significant for complex network control problems.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2022)
Article
Engineering, Electrical & Electronic
Weixin Yin, Lei Xu, Wanli Liu, Zhicheng Cai, Yuwang Yang, Ping Wang
Summary: In this work, a method is proposed to address the joint video packet assignment, power control and user scheduling problem in cognitive multi-homing heterogeneous NOMA networks. By dividing the problem into subproblems and using corresponding algorithms, the video transmission quality and network throughput are improved.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Nguyen Quang Hieu, Dinh Thai Hoang, Dusit Niyato, Ping Wang, Dong In Kim, Chau Yuen
Summary: This research proposes an intelligent optimization framework based on Markov Decision Process (MDP) to assist autonomous vehicles in selecting optimal radar-communication functions in dynamic and uncertain environments. Through the use of deep reinforcement learning and transfer learning algorithms, the proposed framework shows significant reduction in obstacle miss detection probability, making it applicable in various autonomous driving scenarios.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Shufeng Li, Mingyu Cai, Libiao Jin, Yao Sun, Hongda Wu, Ping Wang
Summary: This paper designs a non-binary polar-coded SCMA system with a free order matching strategy to address the issues of delay and reliability. By proposing a new decoding method and detection algorithm, as well as optimizing the update method of the algorithm, the system achieves better BER performance and lower complexity.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Thermodynamics
Jiaqiang Tian, Xinghua Liu, Siqi Li, Zhongbao Wei, Xu Zhang, Gaoxi Xiao, Peng Wang
Summary: This study proposes a state-of-health (SOH) attenuation model considering driving mileage and seasonal temperature for battery health estimation, which is significant for battery pack management and maintenance. The variable forgetting factor recursive least square (VFFRLS) algorithm is used for battery model parameter identification and the extended Kalman-particle filter (EPF) algorithm is proposed for online capacity estimation. The proposed model and algorithm are verified using actual vehicle data over nine months. The experimental results demonstrate the accurate estimation of model parameters and capacity through the proposed algorithm, and the decrease in average capacity of the battery module with total mileage. The compensation of monthly driving mileage and ambient temperature factors effectively improves the accuracy of the SOH model.
Article
Engineering, Civil
Jiaqiang Tian, Xinghua Liu, Chaobo Chen, Gaoxi Xiao, Yujie Wang, Yu Kang, Peng Wang
Summary: In this study, a battery pack inconsistency evaluation method based on an improved GMM and feature fusion approach is proposed. The method accurately estimates battery parameters and quantifies inconsistency using the standard deviation coefficient approach.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Energy & Fuels
Zhengmao Li, Yan Xu, Peng Wang, Gaoxi Xiao
Summary: This paper proposes a coordinated restoration method for the renewable energy-integrated multi-energy distribution system (MDS) to address the threats of low-probability but high-impact extreme events, such as floods, earthquakes, and hurricanes, to the security of the energy system. The method comprehensively models the MDS restoration with coupled power and thermal network constraints, utilizing thermal inertia and smart buildings' thermal demand response as buffers to reduce post-disaster energy supply cost. Preparation and load recovery stage measures are employed for efficient and reliable system restoration. Multiple uncertainties are dealt with through a risk-averse two-stage stochastic programming approach. Simulation results validate the effectiveness and superiority of the method.
Article
Computer Science, Information Systems
Siwei Qiao, Xinghua Liu, Yuru Liang, Gaoxi Xiao, Yu Kang, Shuzhi Sam Ge
Summary: This paper proposes a sliding mode load frequency control (SMLFC) method for interconnected power systems under periodic denial-of-service (DoS) attacks. By designing a suitable sliding surface and event-triggered conditions, the stability and reachability of the power systems are achieved.
IEEE SYSTEMS JOURNAL
(2023)
Article
Automation & Control Systems
Min Meng, Gaoxi Xiao
Summary: This article investigates the state distribution of Markovian jump Boolean networks subject to stochastic disturbances based on the measured outputs. The considered disturbances are modeled as independent and identically distributed processes with known probability distributions. An iterative algorithm is proposed to compute conditional probability distributions of the current state and one-step predicted state based on the knowledge of the output measurements. The obtained conditional probability distributions can be applied to study the optimal state estimation, reconstructibility, and fault detection of Markovian jump Boolean networks.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Engineering, Electrical & Electronic
Qiuyang Huang, Hongfei Jia, Yuanbo Xu, Yongjian Yang, Gaoxi Xiao
Summary: In this paper, a deep-learning model called Limi-TFP is proposed for citywide traffic flow prediction. The model identifies a limited number of monitored roads and utilizes their historical traffic data. It captures spatial context and road attributes through embedding, and incorporates external factors for improved accuracy. Experimental results demonstrate superior performance and noise tolerance compared to existing baselines with only 5% roads being monitored.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Chemistry, Physical
Xinghua Liu, Yubo Wang, Jiaqiang Tian, Gaoxi Xiao, Peng Wang
Summary: This paper proposes a method to achieve a good balance between the capacity and cost of wind-hydrogen integrated energy systems (WHIES). It evaluates the aging status of the wind power generation system and the hydrogen production system, and develops an aging economic model for WHIES. The proposed model aims to maximize production capacity with the minimum cost by considering the actual operating conditions and the aging factor.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2023)
Article
Engineering, Electrical & Electronic
Guangyu Song, Xinghua Liu, Jiaqiang Tian, Gaoxi Xiao, Tianyang Zhao, Peng Wang
Summary: In this paper, a neural network improved dragon-fly algorithm (NNIDA) based approach is proposed to improve the performance of tracking the global maximum power point (GMPP) in photovoltaic systems. The approach can quickly and accurately locate the maximum power point, independent of the configuration of PV modules and the availability of irradiance and temperature sensors.
IEEE TRANSACTIONS ON POWER DELIVERY
(2023)
Article
Engineering, Electrical & Electronic
Ran Wang, Hui Wang, Kun Zhu, Changyan Yi, Ping Wang, Dusit Niyato
Summary: Electric vehicles (EVs) are important for sustainable transportation, but their limited battery capacity and long charging time hinder widespread adoption. To address this issue, mobile charging services (MCSs) using mobile charging vehicles (MCVs) are investigated as supplemental charging methods. This article examines the advantages of MCSs under different charging scenarios and discusses future research and possible methodologies.
IEEE VEHICULAR TECHNOLOGY MAGAZINE
(2023)
