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)
Article
Environmental Studies
Frans Libertson
Summary: The future energy systems need to balance supply and demand more effectively due to the electrification of various sectors and the growing role of volatile energy production. The increasing use of electric vehicles poses both challenges and opportunities for energy systems. Smart electric vehicle charging and user flexibility have been suggested as potential solutions, but their success relies on close collaboration between users and system operators. This study investigates the implementation of supplier-managed charging and its impact on user attitudes and flexibility. The results show that although participants have a positive view of smart charging, they also associate it with uncertainty and anxiety. The capacity for flexible energy use is influenced by factors beyond users' direct control, such as working patterns, financial resources, and access to charging stations. To optimize smart charging schemes, it is crucial to consider not only user attitudes but also factors that can facilitate user flexibility and prevent unfair flexibility markets.
ENERGY RESEARCH & SOCIAL SCIENCE
(2022)
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
Energy & Fuels
Ahmet Mandev, Patrick Plotz, Frances Sprei, Gil Tal
Summary: This study investigated the charging behavior of plug-in hybrid electric vehicles (PHEV) and found that most users do not charge their vehicles overnight and engage in additional charging on 20-26% of driving days. The study also indicated that the utility factor should not be the sole measure of PHEV environmental performance.
Article
Energy & Fuels
Ahmet Mandev, Patrick Ploetz, Frances Sprei, Gil Tal
Summary: The study investigated the daily charging behavior of over 10,000 Chevrolet Volt PHEVs and found that a percentage of users do not charge overnight, while additional charging occurs on 20-26% of driving days. It also concluded that the utility factor should not be the sole measure of environmental performance for PHEVs.
Article
Computer Science, Hardware & Architecture
Yanru Zhang, Feng Hong, Yan Wang, Zhi Liu, Yingjie Zhou, Zheng Chang, George Chen
Summary: This article discusses the potential of using edge intelligence to optimize PEV charging pricing strategies, aiming to address issues such as poor operation of charging stations, degraded user experience, and enable service providers to generate decent profits.
Article
Automation & Control Systems
Satadru Dey, Munmun Khanra
Summary: This article addresses the cybersecurity challenges associated with the large scale deployment of plug-in electric vehicles (PEVs) by exploring control-oriented approaches. Two algorithms for detecting cyberattacks on PEV battery packs during charging are discussed, including a static detector and a dynamic detector. A filter-based design approach for the dynamic detector is proposed to consider stability, robustness, and attack sensitivity as multiobjective criteria. Theoretical analysis and simulation studies show the effectiveness of the algorithms in detecting denial-of-charging (DoC) and overcharging attacks, indicating the superiority of the dynamic detector.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Review
Energy & Fuels
Emilia M. Szumska
Summary: This paper analyzes the availability of existing charging infrastructure equipped with fast charging points for electric vehicles in European Union countries and discusses EU policy on zero-emission vehicles and technical issues related to charging infrastructure. Based on a review of the current state of charging infrastructure and development plans in light of the EU Green Deal, it is concluded that the fast charging infrastructure for electric cars is still insufficiently developed in many regions. Due to the economic diversity of EU countries, the development of charging infrastructure varies, highlighting the importance of locating fast charging points primarily along the TEN-T network and highways.
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.
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
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
Engineering, Electrical & Electronic
Karl Schwenk, Stefan Meisenbacher, Benjamin Briegel, Tim Harr, Veit Hagenmeyer, Ralf Mikut
Summary: Smart charging of Electric Vehicles reduces operating costs, promotes electric mobility, but uncoordinated charging is still common. The impact of future smart charging applications needs further exploration, requiring precise thermal models for high-power charging and estimation of battery aging costs to enhance the profitability of V2G services.
IEEE TRANSACTIONS ON SMART GRID
(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).
Article
Energy & Fuels
Muhammet Deveci, Nuh Erdogan, Dragan Pamucar, Sadik Kucuksari, Umit Cali
Summary: As the transition to electric mobility accelerates, the expansion of charging infrastructure, known as electric vehicle supply equipment (EVSE), is crucial for promoting the transition and alleviating charger access anxiety among electric vehicle (EV) users. This study introduces a multi-criteria decision-making (MCDM) framework that combines a new MCDM model with an optimal public charging station model to determine the best performing public EVSE type from multiple EV user perspectives. The proposed model is tested using real charging data and user evaluations, and it identifies DCFC EVSE as the best performing option.
Article
Computer Science, Information Systems
Joaquim Perez, Filipe Quintal, Lucas Pereira
Summary: We propose a user-friendly and intuitive simulation tool to evaluate the integration of electric vehicle charging processes into power grids. The decoupled and flexible architecture achieved through open design and containerized microservices has been successfully validated.
Article
Chemistry, Multidisciplinary
Hanif Tayarani, Hamidreza Jahangir, Razieh Nadafianshahamabadi, Masoud Aliakbar Golkar, Ali Ahmadian, Ali Elkamel
APPLIED SCIENCES-BASEL
(2019)
Article
Green & Sustainable Science & Technology
Hamidreza Jahangir, Masoud Aliakbar Golkar, Falah Alhameli, Abdelkader Mazouz, Ali Ahmadian, Ali Elkamel
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2020)
Article
Automation & Control Systems
Hamidreza Jahangir, Hanif Tayarani, Saleh Sadeghi Gougheri, Masoud Aliakbar Golkar, Ali Ahmadian, Ali Elkamel
Summary: The study introduces a precise forecasting method based on deep learning concept and microclustering task, which effectively handles a high volume of data in smart grids.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Energy & Fuels
Saleh Sadeghi Gougheri, Hamidreza Jahangir, Mahsa A. Golkar, Ali Ahmadian, Masoud Aliakbar Golkar
Summary: This study presents an optimal bidding strategy for virtual power plants to address the uncertainty of renewable energy and electric vehicles' stochastic behaviors.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2021)
Article
Engineering, Electrical & Electronic
Hamidreza Jahangir, Saleh Sadeghi Gougheri, Behzad Vatandoust, Mahsa A. Golkar, Masoud Aliakbar Golkar, Ali Ahmadian, Amin Hajizadeh
Summary: Electric Vehicle (EV) demand modeling is essential for integrating EVs into the power system. The complexity arises from the different characteristics and correlation of EV demand. Previous methods fail to preserve the correlation between EV demand characteristics. This study proposes a novel semi-supervised approach using Generative Adversarial Networks (GANs) with a 3D convolutional structure for effective EV demand modeling.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Green & Sustainable Science & Technology
Hanif Tayarani, Aditya Ramji
Summary: Hydrogen fuel cells are crucial for decarbonizing the transportation sector globally and in California. However, the environmental impact of the hydrogen supply chain raises concerns. This study compares three hydrogen production methods and evaluates the life cycle impacts of truck and pipeline transportation in gaseous form.
Article
Engineering, Electrical & Electronic
Hossein Khoun Jahan, Mehdi Abapour, Kazem Zare, Seyed Hossein Hosseini, Frede Blaabjerg, Yongheng Yang
Summary: This paper proposes a switched-capacitor (SC)-based cascaded half-bridge multilevel inverter to address the issues of the cascaded H-bridge multilevel inverter (CMI) in photovoltaic (PV) applications. The proposed topology only requires one dc source and achieves the minimum number of switches, spontaneous capacitor charging, voltage boosting, and continuous input current. The feasibility and effectiveness of the proposed topology are validated through simulations and experimental tests.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Hamidreza Jahangir, Saleh Sadeghi Gougheri, Behzad Vatandoust, Masoud Aliakbar Golkar, Ali Ahmadian, Amin Hajizadeh
IEEE TRANSACTIONS ON SMART GRID
(2020)
Proceedings Paper
Energy & Fuels
Ferinar Moaidi, Masoud Aliakbar Golkar
2019 IEEE MILAN POWERTECH
(2019)
Proceedings Paper
Energy & Fuels
Ferinar Moaidi, Masoud Aliakbar Golkar
2019 IEEE MILAN POWERTECH
(2019)
Article
Green & Sustainable Science & Technology
Lars odegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro, Paal Engelstad
Summary: This study investigates uncertainty modeling in wind power forecasting using different parametric and non-parametric methods. Johnson's SU distribution is found to outperform Gaussian distributions in predicting wind power. This research contributes to the literature by introducing Johnson's SU distribution as a candidate for probabilistic wind forecasting.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Xing Liu, Qiuchen Wang, Yunhao Wen, Long Li, Xinfang Zhang, Yi Wang
Summary: This study analyzes the characteristics of process parameters in three lean gas ethane recovery processes and establishes a prediction and multiobjective optimization model for ethane recovery and system energy consumption. A new method for comparing ethane recovery processes for lean gas is proposed, and the addition of extra coolers improves the ethane recovery. The support vector regression model based on grey wolf optimization demonstrates the highest prediction accuracy, and the multiobjective multiverse optimization algorithm shows the best optimization performance and diversity in the solutions.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Cairong Song, Haidong Yang, Xian-Bing Meng, Pan Yang, Jianyang Cai, Hao Bao, Kangkang Xu
Summary: The paper proposes a novel deep learning-based prediction framework, aTCN-LSTM, for accurate cooling load predictions. The framework utilizes a gate-controlled multi-head temporal convolutional network and a sparse probabilistic self-attention mechanism with a bidirectional long short-term memory network to capture both temporal and long-term dependencies in the cooling load sequences. Experimental results demonstrate the effectiveness and superiority of the proposed method, which can serve as an effective guide for HVAC chiller scheduling and demand management initiatives.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Zhe Chen, Xiaojing Li, Xianli Xia, Jizhou Zhang
Summary: This study uses survey data from the Loess Plateau in China to evaluate the impact of social interaction on the adoption of soil and water conservation (SWC) technology by farmers. The study finds that social interaction increases the likelihood of farmers adopting SWC, and internet use moderates this effect. The positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Chenghua Zhang, Yunfei Yan, Kaiming Shen, Zongguo Xue, Jingxiang You, Yonghong Wu, Ziqiang He
Summary: This paper reports a novel method that significantly improves combustion performance, including heat transfer enhancement under steady-state conditions and adaptive stable flame regulation under velocity sudden increase.
JOURNAL OF CLEANER PRODUCTION
(2024)
