Article
Computer Science, Information Systems
Shiyao Zhang, James J. Q. Yu
Summary: This article proposes a multistage system framework for an integrated EV dynamic wireless charging system in a smart city. It develops an optimal placement strategy for power tracks based on city traffic information and EV energy demand, and formulates a dynamic V2G scheduling scheme to coordinate the schedules of EVs with V2G ancillary services.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Green & Sustainable Science & Technology
S. Gupta, A. Maulik, D. Das, A. Singh
Summary: This study focuses on the optimal coordinated operation of a grid-connected AC microgrid consisting of controllable and uncontrollable power sources, battery storage units, considering plug-in hybrid electric vehicles and demand response programs. Through a nested stochastic optimization algorithm, a coordinated optimal operating strategy is proposed, which effectively reduces operating costs and system losses.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Energy & Fuels
Bijan Bibak, Lihui Bai
Summary: Recently, the migration from internal combustion cars to electric vehicles (EVs) has gained attention as a viable solution for energy sustainability. However, the short lifespan of EV batteries poses a challenge. This paper proposes an optimal model for a commercial and industrial electric fleet system to reduce total electricity costs by coordinating various energy sources and usage.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2023)
Article
Engineering, Multidisciplinary
Mei Li, Yusef Ahad
Summary: With the development of smart grids, optimizing the performance of response programs in the distribution system is of great importance. This paper proposes an optimized method for demand response management in smart grids using real-time pricing, and validates its effectiveness through testing under different scenarios. The study also investigates the impact of PHEVs and compares the proposed method with other methods, demonstrating its advantages.
ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH
(2023)
Article
Chemistry, Physical
Meiye Wang, Michael T. Craig
Summary: Vehicle-to-grid (V2G) technology can increase electric vehicle (EV) revenues and grid flexibility, with V2G-enabled EVs generating $32-$48 more annual net revenues compared to smart-charging EVs. Future V2G revenues may decrease, highlighting the importance of a co-optimization framework.
JOURNAL OF POWER SOURCES
(2021)
Article
Energy & Fuels
Yitong Shang, Man Liu, Ziyun Shao, Linni Jian
Summary: The paper proposes a centralized V2G scheme with distributed computing capability using internet of smart charging points (ISCP). The scheme is successfully verified under the distribution grid of the SUSTech campus, achieving load peak-shaving and valley-filling effects.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Environmental Studies
Polina Alexeenko, Eilyan Bitar
Summary: We conducted a real-world pilot study to investigate a new pricing and control mechanism for coordinating residential EV charging loads. The mechanism offers EV owners a range of pricing options based on their willingness to delay their charging completion times. By optimizing the real-time power drawn by EVs, a smart charging system minimizes strain on the grid while ensuring all EVs are charged by user-requested deadlines. Our findings show that, on average, customers were willing to delay their charging by over eight hours, allowing the smart charging system to flatten the aggregate load curve and eliminate demand spikes. Importantly, customer participation rates remained stable throughout the study, indicating the viability of this mechanism as a non-wires alternative to meet the increasing electricity demand from EVs.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2023)
Article
Green & Sustainable Science & Technology
Atefeh Alirezazadeh, Masoud Rashidinejad, Peyman Afzali, Alireza Bakhshai
Summary: The study proposes a new method for joint power and reserve scheduling, which can enhance system flexibility and resiliency while reducing system costs by managing responsive loads and incorporating fast resources.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2021)
Article
Chemistry, Multidisciplinary
Eduardo Garcia-Martinez, Jesus Munoz-Cruzado-Alba, Jose F. Sanz-Osorio, Juan Manuel Perie
Summary: The rapid adoption of Electric Vehicle (EV) technology has led to the urgent need for a wide network of fast Vehicle-to-Grid (V2G) charging stations, which must work properly with every manufacturer and provide reliable designs and validation processes. The development of power electric vehicle emulators with V2G capability is critical for this progress, and this paper presents a complete design and experimental testbench for validation.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Electrical & Electronic
Ona Egbue, Charles Uko, Ali Aldubaisi, Enrico Santi
Summary: This paper proposes a unit commitment model for a vehicle-to-grid (V2G) system, investigating the application of plug-in electric vehicles (PEVs) in a smart power grid. The results show that optimizing the scheduling of PEVs can reduce generation cost and have an impact on load balancing.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Energy & Fuels
Alicia Blatiak, Federica Bellizio, Luis Badesa, Goran Strbac
Summary: This study quantifies the potential revenues that commercial EV fleet operators can gain from simultaneously scheduling their trips and charging, and explores the impact of this approach on the present and future British electricity system. It is found that optimal trip scheduling can significantly increase commercial fleet revenue, with flexible trip scheduling being more valuable in the summer and leading to carbon savings.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Transportation Science & Technology
Hossein Nasr Esfahani, Zhaocai Liu, Ziqi Song
Summary: As EVs become more prevalent, the use of bidirectional charging lanes can optimize transportation and power systems by utilizing EVs as additional energy storage sources. This study introduces a new user equilibrium model to depict the equilibrium conditions in a road network with bidirectional charging lanes. By formulating the optimization problem, the study demonstrates that bidirectional charging lanes have the potential to reduce peak load and charging costs associated with EVs. The developed meta-heuristic solution algorithm based on gray wolf optimizer and manifold suboptimization efficiently solves the model and provides numerical evidence for the effectiveness of this approach.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Computer Science, Information Systems
Xi Chen, Haihui Wang, Fan Wu, Yujie Wu, Marta C. Gonzalez, Junshan Zhang
Summary: This article presents a model of the electric vehicle (EV) charging network as a cyber-physical system that is coupled with transportation networks and smart grids. An EV charging station recommendation algorithm is proposed to create synergy between transportation networks and smart grids and utilize EV charging activities as a load-balancing tool to transfer energy between unbalanced distribution grids.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Green & Sustainable Science & Technology
Ehsan Azad-Farsani, Saeed Abedini, Iman Goroohi Sardou
Summary: The existing models for coordinating plug-in electric vehicles (PEV) based on uniform price methods neglect important network operation indexes and do not efficiently coordinate with distributed generations (DG). This paper introduces a new viewpoint based on locational marginal price (LMP) for effective coordination of PEVs and DGs in electricity day-ahead markets.
JOURNAL OF CLEANER PRODUCTION
(2021)
Review
Energy & Fuels
Kamran Taghizad-Tavana, As'ad Alizadeh, Mohsen Ghanbari-Ghalehjoughi, Sayyad Nojavan
Summary: With the rapid expansion of electric vehicles, they are expected to be a major contributor to transportation. The increasing use of fossil fuels has led to greenhouse gas emissions, making it crucial to achieve sustainable transportation. Countries around the world are implementing long-term plans and policies to replace internal combustion vehicles with EVs and generate electricity using renewable energy sources, resulting in an increase in charging stations.
Article
Energy & Fuels
Yitong Shang, Man Liu, Ziyun Shao, Linni Jian
Summary: The paper proposes a centralized V2G scheme with distributed computing capability using internet of smart charging points (ISCP). The scheme is successfully verified under the distribution grid of the SUSTech campus, achieving load peak-shaving and valley-filling effects.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Construction & Building Technology
Yanchong Zheng, Ziyun Shao, Linni Jian
Summary: The user-oriented V2G scheme with multiple operation modes is proposed to increase EVs' participation in coordinated charging, which varies depending on individual users' preferences and charging urgency.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Automation & Control Systems
Songyan Niu, Shuangxia Niu, Cheng Zhang, Linni Jian
Summary: This article proposes a field-oriented design of sensing coils for metal object detection, aiming to eliminate blind zones while maintaining high sensitivity and cost-effectiveness. By modulating coil size and adding an extra patch coil, the axial blind zones and central blind spot in the system are successfully removed.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Yujun Shi, Linni Jian, T. W. Ching
Summary: This article introduces a partial-analytical-method (PAM) to quantitatively identify field harmonics that have a negative impact on back electromotive force (EMF) in dual-permanent-magnet-excited (DPME) machines, and applies it to a 12/10 DPME machine, revealing that two types of harmonics are responsible for negative contribution to back EMF.
IEEE TRANSACTIONS ON MAGNETICS
(2022)
Article
Engineering, Electrical & Electronic
Hang Yu, Songyan Niu, Ziyun Shao, Linni Jian
Summary: Microgrid clusters are effective in increasing the utilization of renewable energy resources and improving power system reliability and stability. The proposed scalable and reconfigurable hybrid microgrid clustering architecture, along with a decentralized control method, enables flexible interconnection between microgrids and autonomous power exchange among neighboring microgrids.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Energy & Fuels
Yanchong Zheng, Ziyun Shao, Xiang Lei, Yujun Shi, Linni Jian
Summary: Electric vehicles (EVs) provide an alternative solution for sustainable and low-emission traffic system when combined with renewable energy sources. EVs can serve as distributed energy storage devices to offer V2G services for power grids. With decreasing battery costs, EV aggregators have the potential to profit in electricity markets.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Hang Yu, Yitong Shang, Songyan Niu, Chong Cheng, Ziyun Shao, Linni Jian
Summary: This paper presents a pseudo hierarchical management architecture for effective energy management in a compact, cost-effective, and easy-to-build DC nanogrid. The proposed architecture incorporates a state-triggered droop strategy in the short-time scale local management level and a multi-mode power dispatching strategy in the power dispatching level to achieve real-time, autonomous, and stabilized power coordination in the nanogrid. The effectiveness of the architecture and operation strategy is verified through detailed simulation models and hardware-in-loop experiments, showing improved operation economy and satisfaction of EV charging demand.
Article
Engineering, Electrical & Electronic
Yujun Shi, T. W. Ching, Junwen Zhong, Linni Jian
Summary: This paper proposes a dual-stator high-temperature-superconducting modular linear vernier motor (DS-HTS-MLVM) with the advantages of simple structure, conflict-free slot space, easy installation, and flexible excitation field and air-gap flux control. Finite element analysis shows that the proposed motor significantly improves thrust force density and power density, while suppressing force ripple.
IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY
(2022)
Article
Automation & Control Systems
Yitong Shang, Yimeng Shang, Hang Yu, Ziyun Shao, Linni Jian
Summary: This article proposes a distributed edge computing framework for vehicle-to-grid (V2G) technology, which aims to improve the dispatching performance and prediction accuracy using techniques such as long short-term memory network, attention mechanism, and data clustering.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Green & Sustainable Science & Technology
Yanchong Zheng, Yubin Wang, Qiang Yang
Summary: This study develops a two-phase coordinated charging scheduling solution in the energy market environment to optimally schedule EV charging loads for profit maximization from the perspective of EV aggregators. The proposed solution was implemented and assessed using the Guangdong energy market as a case study through extensive simulation experiments, and the numerical results confirmed its effectiveness.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2023)
Article
Thermodynamics
Yubin Wang, Yanchong Zheng, Qiang Yang
Summary: This paper presents a collaborative energy management strategy for the regional integrated energy system (RIES) to address operational uncertainties and electricity market transaction rules.
Article
Thermodynamics
Yanchong Zheng, Yubin Wang, Qiang Yang
Summary: This study proposes a risk-averse bidding strategy for electric vehicle aggregators (EVA) to handle the uncertainties in the day-ahead market. By minimizing the conditional value-at-risk, the strategy aims to reduce the energy transaction risk of the EVA. The model is transformed into a linear programming problem for efficient computation.
Article
Computer Science, Information Systems
Yujun Shi, Junwen Zhong, Linni Jian
Summary: This paper establishes a purely analytical magnetomotive force model for quantitatively analyzing back-EMF, revealing that only AFDHs meeting specific conditions can generate back-EMF and not all AFDHs play a positive role in its generation.
Article
Energy & Fuels
Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou
Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.
Article
Energy & Fuels
Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan
Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.
Article
Energy & Fuels
Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender
Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.
Article
Energy & Fuels
Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado
Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.
Article
Energy & Fuels
Duan Kang
Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.
Article
Energy & Fuels
Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang
Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.
Article
Energy & Fuels
Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi
Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.
Article
Energy & Fuels
Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong
Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.
Article
Energy & Fuels
Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song
Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.
Article
Energy & Fuels
Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz
Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.
Article
Energy & Fuels
Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He
Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.
Article
Energy & Fuels
Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang
Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.
Article
Energy & Fuels
Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung
Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.
Article
Energy & Fuels
Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu
Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.
