Article
Thermodynamics
Mahmoud M. Gamil, Tomonobu Senjyu, Hasan Masrur, Hiroshi Takahashi, Mohammed Elsayed Lotfy
Summary: This study introduces a multi-objective power scheduling and energy management techniques to address the growing burden of electric vehicles on the electrical grid. By comparing different sizing scenarios of residential microgrids and introducing control techniques for charging and discharging battery energy storage systems, the effectiveness of the control techniques in reducing total system cost and CO2 emissions is demonstrated.
ENERGY CONVERSION AND MANAGEMENT
(2022)
Article
Energy & Fuels
Muhammad Aurangzeb, Ai Xin, Sheeraz Iqbal, Muhammad Zeshan Afzal, Hossam Kotb, Kareem M. AboRas, Yazeed Yasin Ghadi, Bello-Pierre Ngoussandou
Summary: This research study investigates the use of a droop-ANN model to enhance power quality in vehicle-to-grid (V2G) systems. Simulation results demonstrate that the droop-ANN model significantly improves power quality across various battery states of charge and charging/discharging scenarios, highlighting its potential to enhance stability and reliability in V2G systems.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Mohammadali Kargar, Chen Zhang, Xingyong Song
Summary: This article studies the problem of autonomous hybrid electric vehicles following a leader, integrating the external dynamics and powertrain dynamics for optimization. A customized control strategy based on Approximate Dynamic Programming and neural networks is proposed, and the accuracy of the optimization solution is improved by applying the concept of reachable sets. Three case studies demonstrate that the examined integrated control strategy significantly improves fuel consumption compared to the separated optimization method.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Energy & Fuels
Zhang Xiaoxin, Chen Qigong, Ge Yuan
Summary: This paper optimizes the spatial scheduling of electrolytic hydrogen centers (HECs) and electric vehicles (EVs) in integrated energy systems (IES) to minimize network loss while ensuring safe operation of the power grid. The proposed method is validated using a simulation instance, showing its effectiveness in reducing network loss and providing reference for HEC optimization.
ENERGY SCIENCE & ENGINEERING
(2023)
Article
Energy & Fuels
Zhang Xiaoxin, Chen Qigong, Ge Yuan
Summary: This paper proposes a collaborative optimal energy scheduling method, which converts electrical energy into chemical energy by adding electrolysis to hydrogen production, to meet the needs of HFCVs and EVs, and improve the economy of the integrated energy system.
ENERGY SCIENCE & ENGINEERING
(2023)
Article
Energy & Fuels
Zhao Huang, Zhiwei Guo, Pengbo Ma, Mengmeng Wang, Yonghong Long, Ming Zhang
Summary: This research presents a two-stage optimization strategy for the microgrid (MG) scheduling problem considering the integration of electric vehicles (EVs) into buildings. The first stage establishes a model for coordinated charging/discharging of EVs, and dynamically divides the peak and valley hours to minimize the peak-to-valley difference (PVD) of the load curve. In the second stage, the daily optimal scheduling of MG generators is calculated efficiently considering the tradeoff between generation cost and pollutant emission. The proposed method is validated using two cases from a residential MG system, showing the relief of power supply pressure and cost saving achieved through coordinated vehicle-to-grid (V2G) service and power planning of MG components.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Energy & Fuels
Wenjun Yang, Jia Guo, Aris Vartosh
Summary: The present paper proposes a comprehensive multi-objective optimization model for energy management in local multi-energy systems with plug-in electric vehicles. The model aims to maximize the operators' profit and minimize CO2 emission by coordinating multiple energy carriers and optimizing the charging and discharging strategies of PEVs. The effectiveness test showed that the proposed framework can achieve the set objectives through optimal coordination and effective management of energy flexibility. Furthermore, numerical analysis in different scenarios demonstrated the impact of the optimization strategies on the operators' profit and CO2 emission reduction.
Article
Engineering, Electrical & Electronic
Mohammadali Kargar, Tohid Sardarmehni, Xingyong Song
Summary: This article focuses on the control of powertrain energy management for an autonomous HEV and introduces a new control strategy based on flexible power demand. The power flexibility is incorporated into the Approximate Dynamic Programming (ADP) framework. An example is provided to demonstrate the feasibility of the proposed method.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Review
Environmental Sciences
Kevin Pinto, Hari Om Bansal, Praveen Goyal
Summary: This study conducted a bibliometric analysis on 10,426 publications related to electric vehicles (EVs) from 1989 to 2020. By analyzing citations and co-citations, key research areas in the field of EVs over the last three decades were identified, providing insights for stakeholders. The results highlight the importance of EVs in addressing environmental issues and accelerating adoption by end-users.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Thermodynamics
Zia Ullah, Shaorong Wang, Guan Wu, Hany M. Hasanien, Anis Ur Rehman, Rania A. Turky, Mohamed R. Elkadeem
Summary: The integration of Electric Vehicles (EVs) and Photovoltaics (PVs) into the electric power distribution system is increasing worldwide. However, the simultaneous integration of EVs and PVs poses challenges that require suitable control design and optimization strategies. This paper proposes a solar-based grid-tied charging station (SGTCS) that maximizes PV power utilization for EV charging. The proposed model considers seasonal variation effects and was implemented using HOMER Grid, including a case study in Islamabad. The results show the relevance and applicability of the study.
Article
Green & Sustainable Science & Technology
Xiaosong Hu, Zhongwei Deng, Xianke Lin, Yi Xie, Remus Teodorescu
Summary: This paper addresses the challenges of current battery management systems and proposes solutions, including introducing the concept of multi-physics coupled battery modeling and utilizing machine learning to improve battery life prediction and fault diagnosis.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Thermodynamics
Yajun Wang, Jidong Wang, Man Cao, Xiangyu Kong, Bouchedjira Abderrahim, Long Yuan, Aris Vartosh
Summary: This paper proposes a power-pollution dynamic load dispatch method based on electric vehicles, aiming to simultaneously reduce fuel costs and pollution emissions by adding electric vehicles. A scenario-based probabilistic method is used to handle the uncertainty in wind farms, and the problem is considered dynamically using various factors. A novel multi-objective optimization algorithm based on harmony search is proposed, and a sorting model and fuzzy theory are employed for solution selection. The efficiency of the proposed model and method is demonstrated through different test systems.
Article
Computer Science, Artificial Intelligence
Subhamay Basu, Mousumi Basu
Summary: Day-ahead scheduling of isolated nanogrid using horse herd optimization algorithm (HOA) is proposed in this paper. The simulation results show that HOA outperforms other optimization algorithms in solving fuel-constrained scheduling problems for nanogrids.
APPLIED ARTIFICIAL INTELLIGENCE
(2021)
Article
Chemistry, Physical
Liange He, Zihan Gu, Yan Zhang, Haodong Jing, Pengpai Li
Summary: This study proposes an Auxiliary Power Unit (APU) control strategy C that considers battery SOC, vehicle power, and battery temperature in order to improve the range of REEV at high temperatures while meeting the cooling requirements of the battery and cabin. Experimental results show that strategy C not only reduces fuel consumption, but also increases the cooling rate of the battery and cabin.
SUSTAINABLE ENERGY & FUELS
(2023)
Article
Energy & Fuels
Mohamed Lotfi, Tiago Almeida, Mohammad S. Javadi, Gerardo J. Osorio, Claudio Monteiro, Joao P. S. Catalao
Summary: This study proposes and models the coordination between home energy management systems (HEMSs) and EV parking lot management systems (PLEMS), achieving optimal energy management through partially sharing individual EV schedules and without sharing private information. The results show that this coordination framework is both technically and economically beneficial for power grids and EV owners.
Article
Engineering, Electrical & Electronic
Tu A. Nguyen, M. L. Crow
IEEE TRANSACTIONS ON POWER SYSTEMS
(2016)
Article
Energy & Fuels
Mohammad Rasoul Narimani, Maigha, Jhi-Young Joo, Mariesa Crow
Article
Engineering, Electrical & Electronic
Keyou Wang, Xin Huang, Bo Fan, Qinmin Yang, Guojie Li, Mariesa L. Crow
IEEE TRANSACTIONS ON SMART GRID
(2018)
Article
Green & Sustainable Science & Technology
Maigha, M. L. Crow
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2017)
Article
Engineering, Electrical & Electronic
Lisa L. Grant, Mariesa L. Crow, Maggie X. Cheng
IEEE TRANSACTIONS ON POWER SYSTEMS
(2018)
Article
Green & Sustainable Science & Technology
Maigha, Mariesa L. Crow
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2018)
Article
Green & Sustainable Science & Technology
Chen Qi, Keyou Wang, Qinmin Yang, Guojie Li, Xin Huang, Jidong Wu, Mariesa L. Crow
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2019)
Article
Green & Sustainable Science & Technology
Xin Huang, Keyou Wang, Bo Fan, Qinmin Yang, Guo-Jie Li, Da Xie, Mariesa L. Crow
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2020)
Article
Energy & Fuels
Fahd Hariri, Mariesa Crow
Summary: The paper discusses the challenges faced by traditional protection schemes due to the integration of distributed generation resources, proposing new methods to estimate fault distance in the presence of infeeds without requiring communication links. The performance of the proposed methods is demonstrated using a radial distribution system model in PSCAD(TM)/EMTDC(TM).
Article
Engineering, Electrical & Electronic
Mohammad Rasoul Narimani, Daniel K. Molzahn, Mariesa L. Crow
Summary: This paper investigates two improvements to convex relaxation methods for optimal power flow problems, one using polar representation of branch admittances and the other based on a coordinate transformation via complex per unit base power normalization. These improvements make the QC envelopes tighter, enhancing the accuracy of the convex relaxation approach.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Hiva Nasiri, Shay Bahramirad, Mohammad Shahidehpour, Aleksi E. Paaso, Nayeem Mohammad Abdullah, Daniel Kushner
IEEE TRANSACTIONS ON SMART GRID
(2020)
Proceedings Paper
Energy & Fuels
Sri Raghavan Kothandaraman, Ahmadreza Malekpour, Maigha Maigha, Aleksi Paaso, Amin Zamani, Farid Katiraei, Muhidin Lelic
CONFERENCE RECORD OF THE THIRD IEEE INTERNATIONAL WORKSHOP ON ELECTRONIC POWER GRID (EGRID)
(2018)
Proceedings Paper
Energy & Fuels
Maigha Maigha, Johan H. Enslin
2018 9TH IEEE INTERNATIONAL SYMPOSIUM ON POWER ELECTRONICS FOR DISTRIBUTED GENERATION SYSTEMS (PEDG)
(2018)
