Article
Environmental Studies
Sierra Spencer, Zhe Fu, Elpiniki Apostolaki-Iosifidou, Timothy E. Lipman
Summary: Effective management of electric vehicle charging is crucial for reducing peak electricity demand, increasing utilization of renewable energy resources, and lowering charging costs. Studies have shown that optimization measures can successfully shift charging load from high grid cost periods to low grid cost periods, and effectively relocate charging events across different time periods and locations.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2021)
Article
Green & Sustainable Science & Technology
Pannee Suanpang, Pitchaya Jamjuntr, Phuripoj Kaewyong, Chawalin Niamsorn, Kittisak Jermsittiparsert
Summary: This paper proposes an intelligent public-accessible charging station framework based on Spatio-Temporal Multi-Agent Reinforcement Learning (STMARL), considering long-term spatio-temporal parameters. The framework aims to reduce the overall charging wait time, average charging price, and charging failure rate for electric vehicles (EVs).
Review
Energy & Fuels
Omid Sadeghian, Arman Oshnoei, Behnam Mohammadi-Ivatloo, Vahid Vahidinasab, Amjad Anvari-Moghaddam
Summary: This review paper discusses the benefits and challenges of EV smart charging (EVSC) from various perspectives, including the role of EV aggregators, charging methods and objectives, and the required infrastructure. The paper also examines the integration of EVSC in energy systems and the environmental benefits of smart green charging solutions. Important findings and recommendations are provided for researchers and policymakers.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Green & Sustainable Science & Technology
Xinran Li, Wei Wang, Hao Gu
Summary: Electric vehicles have the potential to improve environmental sustainability, but the current charging infrastructures cannot keep up with the increasing demand. Sharing private charge posts during idle time is a proactive solution that benefits both charge post owners and non-owner EV drivers. To create a trusted environment, a blockchain-enabled sharing charging system with redesigned procedures and a non-myopic charge post match strategy is proposed. Test results on Ethereum show that the redesigned system can provide high quality services with affordable computational resource consumption and improve the overall matching successful rate of charging requests.
JOURNAL OF CLEANER PRODUCTION
(2023)
Review
Engineering, Electrical & Electronic
Zixuan Jia, Jianing Li, Xiao-Ping Zhang, Ray Zhang
Summary: The rapid development of electric vehicles (EVs) is due to the increased focus on clean energy and environmental protection by countries and regions. This paper focuses on the optimization of EV charging, which poses new challenges to local power systems. Uncoordinated EV charging increases peak-to-valley load differences, harmonic distortions, and affects auxiliary services. To stabilize power grids, studies have been conducted on EV charging forecasting and coordinated charging strategies. The paper reviews these studies and provides recommendations for addressing EV charging challenges.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2023)
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
Automation & Control Systems
Shuangqi Li, Pengfei Zhao, Chenghong Gu, Jianwei Li, Shuang Cheng, Minghao Xu
Summary: This article develops a novel V2G scheduling method for consuming local renewable energy in microgrids by using a mixed learning framework, aims to protect vehicle batteries from fast aging and deal with renewable energy volatility. The effectiveness of the developed models is verified on a U.K. microgrid with actual energy generation and consumption data. The article effectively enables V2G to promote local renewable energy with battery aging mitigated, benefiting EV owners and microgrid operators, and facilitating decarbonization at low costs.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Thermodynamics
Deok Hwan Jeon, Jae Yong Cho, Jeong Pil Jhun, Jung Hwan Ahn, Sinwoo Jeong, Se Yeong Jeong, Anuruddh Kumar, Chul Hee Ryu, Wonseop Hwang, Hansun Park, Cheulho Chang, Hyoungjin Lee, Tae Hyun Sung
Summary: This study presents a novel concept to enhance the energy generation performance of piezoelectric energy harvesters used as charging stations on roads, overcoming the limitations of low electrical output and durability under extremely low road displacement conditions. The proposed lever-type piezoelectric energy harvester achieved significantly higher electrical performance compared to previous studies, with 467% higher output power than vibration type road energy harvesters. The results demonstrate that the energy generated by the proposed harvester can potentially be used as a power source for electric vehicles on smart roads.
Article
Energy & Fuels
Shivam Singh, Binod Vaidya, Hussein T. Mouftah
Summary: In the coming years, the increase in the number of electric vehicles will significantly impact the electricity generation and supply infrastructure. The demand for electricity for charging these vehicles, especially during peak hours, poses challenges to the grid. However, the load shifting potential of electric vehicles can be utilized to alleviate the burden on the grid. Charging scheduling schemes that consider charging behaviors and time of use tariffs can effectively minimize charging costs.
FRONTIERS IN ENERGY RESEARCH
(2022)
Article
Chemistry, Multidisciplinary
Theron Smith, Joseph Garcia, Gregory Washington
Summary: The ARVF algorithm is an efficient real-time PEV charging control method that utilizes fuzzy logic to adjust charging rates. Research demonstrates that when there is a significant deviation between forecasted and actual baseloads, the real-time capability of ARVF is more advantageous.
APPLIED SCIENCES-BASEL
(2021)
Review
Computer Science, Information Systems
Sanchari Deb, Mikko Pihlatie, Mohammed Al-Saadi
Summary: Smart charging is crucial for both power systems and electric vehicle users, as it can meet their needs and provide ancillary services to the power grid during emergencies. It also offers significant financial benefits and is currently being piloted worldwide.
Review
Computer Science, Information Systems
Dominic Savio Abraham, Rajesh Verma, Lakshmikhandan Kanagaraj, Sundar Rajan Giri Thulasi Raman, Narayanamoorthi Rajamanickam, Bharatiraja Chokkalingam, Kamalesh Marimuthu Sekar, Lucian Mihet-Popa
Summary: The use of electric vehicles has been increasing due to the rise in fossil fuel prices and CO2 emissions. EV-charging stations powered by DC grid are more efficient than AC distribution. RES-generated power storage in local ESU is an alternative solution for managing utility grid demand, and energy management strategies must carefully power EV battery charging units to maintain EV charging demand at microgrid levels.
Article
Engineering, Civil
Tianyang Zhang, Xi Chen, Bin Wu, Mehmet Dedeoglu, Junshan Zhang, Ljiljana Trajkovic
Summary: This paper focuses on the interactions between electric vehicle fleets and charging stations/battery swapping stations, developing a stochastic model and deriving revenue boundaries through simulations. The findings are valuable for future studies in public transportation.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Energy & Fuels
Theron Smith, Joseph Garcia, Gregory Washington
Summary: This study investigates the impact of variable rate charging on PEV charging and proposes an integration plan for residential neighborhoods. The results demonstrate that variable rate chargers can enhance both uncontrolled and controlled PEV charging. The integration plan consists of four phases, gradually introducing smart chargers and control strategies to reduce overloading.
Article
Computer Science, Information Systems
Ashish Kumar Karmaker, Md. Alamgir Hossain, Hemanshu Roy Pota, Ahmet Onen, Jaesung Jung
Summary: This paper presents an energy management algorithm that considers techno-economic and environmental factors for a hybrid solar and biogas-based electric vehicle charging station. The proposed algorithm, designed for a 20-kW charging station, utilizes a fuzzy inference system in MATLAB SIMULINK to optimize real-time charging costs and renewable energy utilization by managing power generation, EV power demand, charging periods, and existing charging rates. The results demonstrate a 74.67% reduction in energy costs compared to existing flat rate tariffs, with lower charging costs on weekdays and weekends. The integration of hybrid renewables also leads to a significant decrease in greenhouse gas emissions, making the project profitable with short payback periods for charging station owners.
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.