Article
Energy & Fuels
S. J. Sultanuddin, R. Vibin, A. Rajesh Kumar, Nihar Ranjan Behera, M. Jahir Pasha, K. K. Baseer
Summary: Electric vehicles (EV) have become the preferred option in transportation due to their environmental and energy sustainability. However, uncontrolled EV charging can increase consumer costs and overload the grid. This research proposes an improved reinforcement learning charging management system to prevent grid overload. Under realistic operating conditions, the proposed approach provides an adjustable, scalable, and flexible strategy for an electric car fleet. Compared to an uncontrolled charging strategy, the proposed reinforcement learning technique reduces the variance of the overall load by 68%.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Morteza Azimi Nasab, Mohammad Zand, Amir Ali Dashtaki, Mostafa Azimi Nasab, Sanjeevikumar Padmanaban, Frede Blaabjerg, Q. Juan C. Vasquez
Summary: This article addresses the issue of uncertainty in the use of new energies by solving the flexibility planning of electric vehicle charging and discharging with the help of the CPLEX solver. It aims to coordinate with wind and solar production and compensate for the uncertainty of these resources. The results show that considering uncertainties can reduce costs through optimal planning for electric vehicles, which is also profitable for the operator.
Article
Green & Sustainable Science & Technology
Felipe Gonzalez Venegas, Marc Petit, Yannick Perez
Summary: This study examined the challenges and opportunities of integrating EVs into distribution grids, highlighting key technical and economic issues while addressing the impact of the lack of regulatory frameworks on flexibility value assessment.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
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)
Review
Energy & Fuels
Anna Auza, Ehsan Asadi, Behrang Chenari, Manuel Gameiro da Silva
Summary: This paper reviews the techniques and dynamics of uncertainty modelling in electric grids with vehicle-to-grid integration for electric vehicles. The most frequently used uncertainty modelling approaches are Monte Carlo, probabilistic scenarios, stochastic, point estimate method, and robust optimization. The findings show that probabilistic techniques, specifically Monte Carlo and scenario analysis, are the most widely applied. Early articles tend to use robust optimization due to the lack of historical data, while more recent articles favor Monte Carlo simulation. The uncertainty handling techniques depend on the type of uncertainty and the availability of human resources, and are unrelated to the generation type.
Article
Energy & Fuels
Ricardo Reibsch, Philipp Blechinger, Julia Kowal
Summary: It is necessary to transform the energy system towards renewable energies and the electrification of the transport and heating sectors. The increasing load on low-voltage grids can be alleviated by battery storage systems and flexible operation of consumers.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Bahman Ahmadi, Elham Shirazi
Summary: This paper presents an innovative multi-objective optimization framework for EV smart charging (EVSC) using the Dynamic Hunting Leadership (DHL) method, aiming to improve the voltage profile, eliminate voltage violations and energy not supplied (ENS) in the network. The proposed approach considers both residential EV chargers and parking stations, takes constant current charging into account, and solves the problem as a mixed integer non-linear programming (MINLP) problem. The results demonstrate the effectiveness of the DHL algorithm in minimizing conflicting objectives and improving the grid's voltage profile while considering operational constraints.
Article
Engineering, Electrical & Electronic
Lou Wei, Chen Yi, Jin Yun
Summary: This paper presents a novel reinforcement learning based approach for energy drive and management in smart grids, utilizing Q-learning technique and dragonfly optimization algorithm for power dispatch optimization and cost minimization.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Construction & Building Technology
Yubin Lin, Chenbing Cheng, Fen Xiao, Khalid Alsubhi, Hani Moaiteq Abdullah Aljahdali
Summary: This paper introduces a new framework based on directed acyclic graph (DAG) and distributed multi-layer cloud-fog computing for optimizing the energy management of smart grids with high penetration of PHEVs. Simulation results demonstrate the effectiveness of the proposed scheme.
SUSTAINABLE CITIES AND SOCIETY
(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
Computer Science, Information Systems
Naheel Faisal Kamal, Abdulla Khalid Al-Ali, Abdulaziz Al-Ali, Sertac Bayhan, Qutaibah M. Malluhi
Summary: Smart meters are deployed worldwide to modernize the power grid, offering advantages such as automated consumption reporting and demand-based power generation. However, there are privacy concerns as detailed reporting can reveal consumer behavior. This study proposes a protocol that ensures privacy while maintaining the benefits of smart grids, using techniques like randomization, masking, and differential privacy. The method outperforms previous approaches in terms of efficiency and communication overhead, as demonstrated through implementation, simulation, and analysis using real-life smart meter data.
Article
Computer Science, Information Systems
Hwei-Ming Chung, Sabita Maharjan, Yan Zhang, Frank Eliassen, Kai Strunz
Summary: This article proposes a computational architecture combining energy trading and demand responses based on cloud computing for managing virtual power plants (VPPs) in smart grids. EVs can be charged rapidly by purchasing energy in the cloud, while users with storage devices can sell surplus energy to the market. By modeling the interactions between EV owners and VPPs as a non-cooperative game, a Nash equilibrium is sought to maximize revenue and minimize charging costs.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
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
Soomin Woo, Zhe Fu, Elpiniki Apostolaki-Iosifidou, Timothy E. Lipman
Summary: This research estimated the maximum potential gains in economic and environmental performance of utility grid operation by optimizing the time and location of EV charging, using actual EV operational data and grid-operation data. The results showed the potential for reducing operational costs, marginal emissions, and increasing renewable energy use in the utility grid by rescheduling EV charging load.
Article
Energy & Fuels
Stavros Sykiotis, Christoforos Menos-Aikateriniadis, Anastasios Doulamis, Nikolaos Doulamis, Pavlos S. Georgilakis
Summary: This study proposes a residential smart EV charging framework that prioritizes solar PV power self-consumption for charging electric vehicles, aiming to accelerate the transition to a carbon neutral passenger vehicle fleet. The results show that compared to uncontrolled EV charging, the proposed method can increase the average self-consumption of solar energy for EV charging by 19.66%, reduce network stress by 7%, and decrease electricity bills by 10.3%.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2023)
Article
Energy & Fuels
Stefani Freitas, Luis Carlos Oliveira, Priscila Oliveira, Bruno Exposto, Jose Gabriel Pinto, Joao L. Afonso
Summary: In order to reduce harmonic content in electrical power systems and improve power quality levels, filters and other harmonic compensation devices are widely used. This paper introduces a new hybrid arrangement of harmonic compensation that incorporates both active and passive filtering for four-wire electrical systems feeding single-phase, non-linear loads. The effectiveness of this hybrid arrangement is demonstrated through simulations and experimental tests, showing significant improvement in power factor and reduction in harmonic distortions.
Article
Computer Science, Information Systems
Joao D. C. Sousa, Tiago J. C. Sousa, Vitor Monteiro, Joao L. Afonso
Summary: This study focuses on the traction system based on a synchronous reluctance permanent magnet (SRPM) machine in electric vehicles (EVs). The developed prototype integrates bidirectional AC-DC and DC-DC converters, allowing for regenerative braking, and the SRPM machine is controlled using a maximum torque per ampere (MTPA) algorithm. Computer simulations and experimental results demonstrate the relevance and effectiveness of the SRPM machine for EV applications.
Article
Social Issues
Paula Ferreira, Ana Rocha, Madalena Araujo, Joao L. Afonso, Carlos Henggeler Antunes, Marta A. R. Lopes, Gerardo J. Osorio, Joao P. S. Catalao, Joao Pecas Lopes
Summary: This paper analyzes the potential societal impacts of research projects with low technology readiness level, using the case of the ESGRIDS project as an example. The study highlights the influence of individual perceptions and organizational contexts on future developments. The analysis is translated into a technology roadmap, which outlines the time dimension for technology maturity evolution and implementation impacts.
TECHNOLOGY IN SOCIETY
(2023)
Editorial Material
Energy & Fuels
Vitor Monteiro, Jose A. Afonso, Joao L. Afonso
Review
Energy & Fuels
Joao P. D. Miranda, Luis A. M. Barros, Jose Gabriel Pinto
Summary: Electric vehicles (EVs) are gaining popularity due to their environmental friendliness and energy efficiency. The energy storage and management system, especially the battery management system (BMS), plays a critical role in EVs. Active cell equalization circuits have been developed to balance individual cell voltage and state of charge (SoC), ensuring the safety and longevity of the energy storage system. This paper provides a comprehensive overview of research on active cell equalization circuits, highlighting their importance, advantages, disadvantages, and specifications.
Article
Energy & Fuels
Luis A. M. Barros, Antonio P. Martins, Jose Gabriel Pinto
Summary: The current railway system has some weaknesses due to increasing demand, which requires an increase in power supply for longer trains and faster locomotives. This paper proposes a control algorithm to minimize the power imbalance in each traction power substation. Excess energy from regenerative braking can be used to assist the traction of another locomotive, increasing the overhead line capacity. Computer models using a modular multilevel converter topology were used to analyze different consumption events and their responses.
Editorial Material
Energy & Fuels
Jose A. Afonso, Vitor Monteiro, Joao L. Afonso
Article
Computer Science, Information Systems
Nuno Rodrigues, Jose Cunha, Vitor Monteiro, Joao L. Afonso
Summary: With the increasing demand and price of electricity, there is a need for more reliable and efficient electrical energy conversion systems. The modular multilevel converter (MMC) based on submodules has emerged as a solution, offering higher performance levels and compact design. The modularity concept allows for voltage and current scalability through series and parallel connection of submodules. The MMC has various applications, including HVDC power transmission systems, solid-state transformers, renewable energy interfaces, and railway power systems. This paper focuses on the development and experimental validation of a single-phase MMC for a railway static converter, with emphasis on AC side control and using half-bridge submodules.
Article
Computer Science, Information Systems
Vitor Monteiro, Catia F. Oliveira, Joao L. Afonso
Summary: This paper presents a bidirectional multilevel dc-dc power converter for electric vehicle battery charging. The power converter ensures continuous charging operation for EV batteries, regardless of the occurrence or absence of open-circuit failures in the bipolar dc grid. The proposed control algorithms and topology were validated through simulation and experimental results, analyzing different states of power semiconductors and considering various conditions of operation.
Article
Engineering, Electrical & Electronic
Wandry R. Faria, Gregorio Munoz-Delgado, Javier Contreras, Benvindo R. Pereira Jr
Summary: This paper proposes a new bilevel mathematical model for competitive electricity markets, taking into account the participation of distribution systems operators. A new pricing method is introduced as an alternative to the inaccessible dual variables of the transmission system.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Chao Zhang, Liwei Zhang, Dong Wang, Kaiyuan Lu
Summary: The load disturbance rejection ability of electrical machine systems is crucial in many applications. Existing studies mainly focus on improving disturbance observers, but the speed response control during the transient also plays a significant role. This paper proposes a sliding mode disturbance observer-based load disturbance rejection control with an adaptive filter and a Smith predictor-based speed filter delay compensator to enhance the transient speed response.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Arif Hussain, Arif Mehdi, Chul-Hwan Kim
Summary: The proposed scheme in this research paper is a communication-less islanding detection system based on recurrent neural network (RNN) for hybrid distributed generator (DG) systems. The scheme demonstrates good performance in feature extraction, feature selection, and islanding detection, and it also performs effectively in noisy environments.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Zonghui Sun, Xizheng Guo, Shinan Wang, Xiaojie You
Summary: This paper presents a status pre-matching method (SPM) that eliminates the iterative calculations for resistance switch model, and simulates all operation modes of PECs through a more convenient approach. Furthermore, a FPGA implementation scheme is proposed to fully utilize the multiplier units of FPGA.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Rui Zhou, Shuheng Chen, Yang Han, Qunying Liu, Zhe Chen, Weihao Hu
Summary: In power system scheduling with variable renewable energy sources, considering both spatial and temporal correlations is a challenging task due to the complex intertwining of spatiotemporal characteristics and computational complexity caused by high dimensionality. This paper proposes a novel probabilistic spatiotemporal scenario generation (PSTSG) method that generates probabilistic scenarios accounting for spatial and temporal correlations simultaneously. The method incorporates Latin hypercube sampling, copula-importance sampling theory, and probability-based scenario reduction technique to efficiently capture the spatial and temporal correlation in the dynamic optimal power flow problem. Numerical simulations demonstrate the superiority of the proposed approach in terms of computational efficiency and accuracy compared to existing methods.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Juan Manuel Mauricio, J. Carlos Olives-Camps, Jose Maria Maza-Ortega, Antonio Gomez-Exposito
Summary: This paper proposes a simplified thermal model of VSC, which can produce accurate results at a low computational cost. The model consists of a simple first-order thermal dynamics system and two quadratic equations to model power losses. A methodology is also provided to derive the model parameters from manufacturer data.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Jae-Kyeong Kim, Kyeon Hur
Summary: This paper investigates the relationship between the accuracy of finite difference-based trajectory sensitivity (FDTS) analysis and the perturbation size in non-smooth systems. The study reveals that the approximation accuracy is significantly influenced by the perturbation size, and linear approximation is the most suitable method for practical applications.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Yuan Si, Amjad Anvari-Moghaddam
Summary: This paper investigates the impact of geomagnetic disturbances on small signal stability in power systems and proposes the installation of blocking devices to mitigate the negative effects. Quantitative evaluation reveals that intense geomagnetic disturbances significantly increase the risk of small signal instability. Optimal placement of blocking devices based on sensitivity scenarios results in a significant reduction in the risk index compared to constant and varying induced geoelectric fields scenarios.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Xuejian Zhang, Wenxin Kong, Nian Yu, Huang Chen, Tianyang Li, Enci Wang
Summary: The intensity estimation of geomagnetically induced currents (GICs) varies depending on the method used. The estimation using field magnetotelluric (MT) data provides the highest accuracy, followed by the estimation using 3D conductivity models and the estimation using a 1D conductivity model. The GICs in the North China 1000-kV power grid have reached a very high-risk level, with C3 and C4 having a significant impact on the geoelectric field and GICs.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Yue Pan, Shunjiang Lin, Weikun Liang, Xiangyong Feng, Xuan Sheng, Mingbo Liu
Summary: This paper introduces the concept and model of offshore-onshore regional integrated energy system, and proposes a stochastic optimal dispatch model and an improved state-space approximate dynamic programming algorithm to solve the model. The case study demonstrates the effectiveness and high efficiency of the proposed method in improving economic and environmental benefits.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Mohammad Eydi, Reza Ghazi, Majid Oloomi Buygi
Summary: Proportional current sharing, voltage restoration, and SOCs balancing in DC microgrid control algorithms are the leading challenges. This paper proposes a novel communication-less control method using a capacitor and a DC/DC converter to stabilize the system and restore the DC bus voltage. The method includes injecting an AC signal into the DC bus, setting the current of energy storage units based on frequency and SOC, and incorporating droop control for system stability. Stability analysis and simulation results validate the effectiveness of the proposed method.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Xiangjian Meng, Xinyu Shi, Weiqi Wang, Yumin Zhang, Feng Gao
Summary: With the increasing penetration of photovoltaic power generation, regional power forecasting becomes critical for stable and economical operation of power systems. This paper proposes a minute-level regional PV power forecasting scheme using selected reference PV plants. The challenges include the lack of complete historical power data and the heavy computation burden. The proposed method incorporates a novel reference PV plant selection method and a flexible approach to decrease the accumulated error of rolling forecasting.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Huabo Shi, Yuhong Wang, Xinwei Sun, Gang Chen, Lijie Ding, Pengyu Pan, Qi Zeng
Summary: This article investigates the dynamic stability characteristics of the full size converter variable speed pumped storage unit and proposes improvements for the control strategy. The research is important for ensuring the safe and efficient operation of the unit.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Firmansyah Nur Budiman, Makbul A. M. Ramli, Houssem R. E. H. Bouchekara, Ahmad H. Milyani
Summary: This paper proposes an optimal harmonic power flow framework for the daily scheduling of a grid-connected microgrid, which addresses power quality issues and ensures effective control through demand side management.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Cong Zeng, Ziyu Chen, Jizhong Zhu, Fellew Ieee
Summary: This paper introduces a distributed solution method for the multi-objective OPF problem, using a coevolutionary multi-objective evolutionary algorithm and the idea of decomposition. The problem is alleviated by decomposing decision variables and objective functions, and a new distributed fitness evaluation method is proposed. The experimental results demonstrate the effectiveness of the method and its excellence in large-scale systems.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
