Article
Energy & Fuels
Remi Lauvergne, Yannick Perez, Mathilde Francon, Alberto Tejeda De La Cruz
Summary: This paper describes a methodology to study the technical and economic impacts of mass EV charging on power systems. The results show that smart charging can significantly reduce operational electricity system costs and carbon emissions. The study also compares different smart charging modes and identifies the parameters with the largest impact on EV flexibility.
Article
Energy & Fuels
Asad Tariq, Syed Ali Abbas Kazmi, Ghulam Ali, Ali Hussain Umar
Summary: This research paper introduces a hybrid technique for accurately modeling the charging load of plug-in electric vehicles (PEVs) through stochastic modeling and real-world dynamics. The methodology combines stochastic modeling of PEV driving behaviors with powertrain simulations to determine critical parameters and proposes grid reinforcement solutions to mitigate the impact of additional PEV charging load on grid voltage stability.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2023)
Article
Energy & Fuels
Mohammed Al-Saadi, Josu Olmos, Andoni Saez-de-Ibarra, Joeri Van Mierlo, Maitane Berecibar
Summary: Fast charging is crucial for the wider adoption of Electric Vehicles (EVs), but it can lead to degradation of Li-ion Batteries (LIBs), making it essential to understand how fast charging affects battery degradation in order to design appropriate infrastructure and powertrains. Research on Battery Electric Buses (BEBs) in European cities found that reducing charger size and increasing battery capacity are cost-effective measures to mitigate LIB degradation during fast charging processes.
Article
Engineering, Electrical & Electronic
Xuan Gong, Wenyi Li
Summary: A multi-objective capacity optimization allocation model was developed to reduce the cost of capacity allocation in AC/DC hybrid micro-grids and improve user satisfaction. The particle swarm optimization algorithm was used to address capacity optimization in EVs across scenarios, proving the rationality and effectiveness of the proposed model.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2021)
Article
Automation & Control Systems
Shenxi Zhang, Yichen Fang, Heng Zhang, Haozhong Cheng, Xu Wang
Summary: Photovoltaic generation plays a crucial role in achieving carbon neutralization. This article presents a two-stage robust optimization model that considers the integration of soft open point (SOP) and electric vehicles (EVs) to assess the maximum hosting capacity of photovoltaic generation in power distribution network (PDN). The results demonstrate the advantages of the proposed model and solving strategy.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Energy & Fuels
Ulrich Fretzen, Mohammad Ansarin, Tobias Brandt
Summary: The research introduces a simple coordination strategy to minimize the impact on EV availability for drivers while maximizing the absorption of PV electricity generation by EV batteries. Results show that this coordination can provide 71%-92% of EV charging load from solar panels in the summer and 13%-76% in the winter, offering benefits compared to uncoordinated charging patterns. The gains are generally highest in winter and vary based on PV and EV integration levels, with minimal impact on EV availability for drivers.
Article
Energy & Fuels
Ming Wei
Summary: This paper investigates the impact of large-scale implementation of plug-in hybrid electric vehicles in Australia on thermal power generation expansion decisions and wind power integration. The study also evaluates the potential cost savings of optimizing PHEV charging loads.
Article
Thermodynamics
Yuanyuan Zhang, Huiru Zhao, Bingkang Li
Summary: This paper proposes an evaluation method for the generation capacity adequacy of multi-types units and designs a unit capacity compensation mechanism suitable for the initial stage of Power Market construction. The results of the case study show that this mechanism can effectively guarantee the generation capacity adequacy of the system and help power generation enterprises recover costs.
Article
Energy & Fuels
Alberto Boretti
Summary: This study analyzes data on the energy economy and environmental friendliness of passenger cars, aiming to propose the necessary developments to reduce CO2 emissions by the end of this decade. The findings suggest that sharing battery capacity among many plug-in hybrid electric vehicles (PHEVs) rather than a few battery electric vehicles would effectively reduce CO2 emissions in the life cycle analysis of road transport until 2030. Suggestions are also provided to improve the energy efficiency of PHEVs and hydrogen fuel cell vehicles over certification cycles.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Mlungisi Ntombela, Kabeya Musasa
Summary: With the increasing popularity of electric vehicles, more electricity is needed for charging, which requires a range of grid transportation solutions and considerable transmission infrastructure changes. Strategic planning and control can reduce energy loss on the power network, and bidirectional charging of EVs can help transmission systems cope with EV allocation. The addition of EVs to the transmission network can solve power loss and voltage instability issues.
Article
Engineering, Electrical & Electronic
Mohamed Ben-Marzouk, Serge Pelissier, Guy Clerc, Ali Sari, Pascal Venet
Summary: The article presents a methodology for analyzing data from 10 electric vehicles to select representative profiles for battery aging tests. Mathematical methods were used to sort key variables and classify vehicle uses, resulting in a realistic profile for aging tests. The effectiveness of using a real-life type profile compared to a modified WLTC profile for aging tests in automotive applications is demonstrated.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Review
Computer Science, Hardware & Architecture
Khalid Khan, Fadzil Hassan, Jahwan Koo, Mazin Abed Mohammed, Yumna Hasan, Danish Shamsheela, Danish Muhammad, Bhawani Shankar Chowdhry, Nawab Muhammad Faseeh Qureshi
Summary: This paper introduces the concept of blockchain system and its applications in various fields, with a focus on the application of blockchain in electric vehicle management and charging. It also discusses the impact of different consensus mechanisms on the performance of blockchain.
COMPUTERS & ELECTRICAL ENGINEERING
(2023)
Article
Green & Sustainable Science & Technology
Modawy Adam Ali Abdalla, Wang Min, Gehad Abdullah Amran, Amerah Alabrah, Omer Abbaker Ahmed Mohammed, Hussain Alsalman, Bassiouny Saleh
Summary: This study proposes an energy utilization optimization strategy for charging electric vehicles in a smart home. The strategy utilizes a vehicle-to-home system and household energy storage system to improve energy utilization and reduce electricity bills. Different scenarios are examined to investigate the role of these technologies in reducing costs and smoothing the load curve.
Article
Energy & Fuels
Lubos Buzna, Pasquale De Falco, Gabriella Ferruzzi, Shahab Khormali, Daniela Proto, Nazir Refa, Milan Straka, Gijs van der Poel
Summary: This paper presents a methodology for probabilistic electric vehicle load forecasting for different geographic regions, using a hierarchical approach to decompose the problem at low-level regions and forecast the aggregate load at a high-level geographic region through an ensemble methodology. Experimental results show that hierarchical approaches increase the skill of probabilistic forecasts up to 9.5% compared with non-hierarchical approaches.
Article
Energy & Fuels
Cheng Huang, Zheyu Du, Tianyao Ji, Zhe Chen, Runze Liu, Zhaoxia Jing, Qian Zhou, Yongyong Jia
Summary: The design of the power generation capacity adequacy mechanism requires comprehensive consideration of political goals, power systems, power markets, and other factors. This paper proposes a novel power generation capacity adequacy mechanism based on revenue call options, which includes two processes: forward contract auction and short-term market settlement. The mechanism guarantees participants steady revenue and provides accurate price signals.
Article
Engineering, Electrical & Electronic
M. D. Kamruzzaman, Mohammed Benidris
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2020)
Article
Physics, Applied
M. A. Bennani, Z. Aziz, S. Terkhi, E. H. Elandaloussi, B. Bouadjemi, D. Chenine, M. Benidris, O. Youb, S. Bentata
Summary: In this study, the properties of half-Heusler alloys RhFeX (with X = Ge, Sn) were investigated using density functional theory. The results show that the compounds are mechanically stable and exhibit strong half-metallic ferromagnet behavior. Additionally, the thermoelectric properties indicate that RhFeGe and RhFeSn have the potential to be good candidates for thermoelectric applications at low temperatures.
JOURNAL OF SUPERCONDUCTIVITY AND NOVEL MAGNETISM
(2021)
Article
Engineering, Multidisciplinary
Michael Abdelmalak, Mohammed Benidris
Summary: The article proposes a generalized polynomial chaos (gPC) based approach to quantify the impacts of uncertainties from renewable energy sources and load variations on voltage magnitudes of distribution systems. The method propagates uncertainties in the system under study to achieve efficient and significantly reduced computation time compared to Monte Carlo simulation.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2021)
Article
Engineering, Multidisciplinary
Michael Abdelmalak, Mohammed Benidris
Summary: This article proposes a probabilistic proactive generation redispatch strategy to enhance the operational resilience of power grids during wildfires. The strategy uses a Markov decision process to provide generation redispatch strategies for different system states, considering component failure probabilities, wildfire spatiotemporal properties, and load variation. The results demonstrate the effectiveness of the proposed method in enhancing the resilience level of power grids during wildfires.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2022)
Article
Engineering, Multidisciplinary
Michael Abdelmalak, Mohammed Benidris
Summary: This article proposes a proactive generation redispatch strategy to enhance the operational resilience of power grids during hurricanes by minimizing load curtailments and operational costs. The strategy considers the unavailability and forced outages of renewable energy sources, as well as various constraints such as generation, transmission, and system limitations. The results show that the proactive and dynamic generation redispatch can significantly reduce load curtailments and improve power system resilience during hurricanes.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Md. Kamruzzaman, Jiajun Duan, Di Shi, Mohammed Benidris
Summary: This paper proposes a data-driven multi-agent framework based on a deep-reinforcement-learning algorithm to enhance power system resilience by overcoming limitations of existing methods and planning for voltage stability.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Energy & Fuels
Md Kamruzzaman, Xiaohu Zhang, Michael Abdelmalak, Di Shi, Mohammed Benidris
Summary: The paper proposes a neural network-based approach to develop a battery model that captures non-linear interactions between charging/discharging power and battery state of charge. By training neural networks and combining them with mixed integer linear programming, an accurate and computationally efficient battery model is developed and successfully applied in power system reliability evaluation to determine optimal battery locations.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Engineering, Electrical & Electronic
Mohammad MansourLakouraj, Mukesh Gautam, Hanif Livani, Mohammed Benidris
Summary: This paper presents a graph convolution-based method for event classification and region identification in distribution grids. The method utilizes time-synchronized voltage and current phasor data, combined with network edge features, to achieve event classification and region identification by aggregating PMU data.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Engineering, Multidisciplinary
Mohammad MansourLakouraj, Hadis Hosseinpour, Hanif Livani, Mohammed Benidris
Summary: This article proposes a fault location method in active distribution feeders using the Short-Time Matrix Pencil method (STMPM) and Graph Neural Network (GNN) based on Waveform Measurement Units (WMUs). The method includes two stages: STMPM captures the dominant modes of transient changes in WMUs' sinusoidal signals, and GNN uses the captured features to identify the fault location and type. The proposed method is tested on a modified IEEE network with distributed energy resource (DER) and shows advantages over conventional approaches in fault location accuracy.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Michael Abdelmalak, Jordan Cox, Sean Ericson, Eliza Hotchkiss, Mohammed Benidris
Summary: Catastrophic impacts caused by extreme weather events on power systems have increased significantly in the past decade. However, data capturing the performance of power systems during and after disruptive events is scarce. This paper proposes an assessment framework using EAGLE-I data to evaluate the performance aspects of the power grid during extreme outage events, providing a probabilistic representation of state-level outage behaviors for evaluating resilience enhancement techniques.
Article
Energy & Fuels
Mukesh Gautam, Narayan Bhusal, Jitendra Thapa, Mohammed Benidris
Summary: A cooperative game theory-based approach is proposed in this paper to distribute slack active power among different participating generators, resulting in reduced generation costs and power losses.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Computer Science, Information Systems
Mohammad Mansourlakouraj, Mukesh Gautam, Hanif Livani, Mohammed Benidris
Summary: This paper presents a risk-aware Volt/VAR support framework and a real-time reinforcement learning controller for three-phase distribution systems, which incorporates voltage regulation and power scheduling of intermittent renewable resources.
Review
Computer Science, Information Systems
Hadis Hosseinpour, Mohammad Mansourlakouraj, Mohammed Benidris, Hanif Livani
Summary: This paper presents a comprehensive review and critique of large-signal stability analysis methods for inverter-based AC microgrids. The study analyzes and compares existing stability assessment methods, identifies gaps, and presents challenges for further investigation. It also examines the impact of dynamic models on the accuracy of stability assessment.
Article
Computer Science, Information Systems
Narayan Bhusal, Mukesh Gautam, Mohammed Benidris
Summary: A two-stage machine learning-based approach is proposed in this paper to detect, locate, and distinguish coordinated data falsification attacks in coordinated voltage regulation schemes in distribution systems. By comparing forecasted voltage with measured voltage in real-time, the proposed method can effectively prevent voltage control algorithms from being disturbed and ensure voltage stability. The research shows that the proposed approach can accurately detect low margin attacks with up to 99% accuracy.
