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
Engineering, Multidisciplinary
Kratika Yadav, Mukesh Singh
Summary: Electric vehicles have laid the foundation for sustainable transportation and have increased the load on the grid, necessitating the implementation of vehicle-to-grid infrastructure. To accurately measure the energy exchange between the grid and the vehicle, a bidirectional DC measurement system is needed. This paper investigates the role of such a system in vehicle-to-grid operation and proposes a DC net meter that complies with relevant standards and provides accurate billing to end customers.
Article
Thermodynamics
Mathias Mueller, Yannic Blume, Janis Reinhard
Summary: Bidirectional charging of electric vehicles can contribute to the energy transition, but its impact on the electricity grid load needs to be considered. A study found that more than 42% of low voltage grids will require expansion. Optimization algorithms applied at a building level do not significantly reduce the number of affected grids. The application of variable market prices can lead to higher simultaneous charging powers and increased grid load, resulting in a higher need for grid expansion.
Article
Automation & Control Systems
Aakash Kumar Seth, Mukhtiar Singh
Summary: This paper presents the design and implementation of a bidirectional off-board plug-in Electric Vehicle (PEV) charger controller with effective harmonic compensation and computational efficiency. The use of a repetitive controller for inner current regulation, with sensitivity modification, improves the performance of the controller.
Article
Engineering, Electrical & Electronic
P. M. Sneha Angeline, M. Newlin Rajkumar
Summary: The escalating power demand worldwide has led to the emergence of a power crisis. Vehicle-to-grid technology offers a promising solution to mitigate this crisis. This paper presents a bidirectional SEPIC-Zeta converter and optimization techniques to address the challenges of integrating electric vehicles with the power grid.
ELECTRICAL ENGINEERING
(2023)
Article
Energy & Fuels
Rishabh Ghotge, Koen Philippe Nijssen, Jan Anne Annema, Zofia Lukszo
Summary: This study investigates the acceptance of Vehicle-to-Grid (V2G) charging among electric vehicle (EV) drivers. The findings suggest that clear communication, financial compensation, real-time insight, and user-friendly interface contribute to higher acceptance. However, uncertainty in battery state-of-charge, increased planning requirements, anxiety about reaching destinations, and restrictions on personal vehicle use are major barriers. The study also reveals that actual experience with V2G charging influences perceptions, with concrete factors carrying more weight than abstract concerns.
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
Energy & Fuels
Bijan Bibak, Hatice Tekiner-Mogulkoc
Summary: The implementation of vehicle to grid (V2G) technology can decrease power issues and improve network efficiency by utilizing the unused power in electric vehicle (EV) batteries. This paper proposes a novel methodology to comprehensively evaluate the impact of EVs and V2G on shaving the peak demand and filling the valley demand. The simulation results indicate that off-peak charging mode has better consequences in leveling the load curve.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Engineering, Electrical & Electronic
Anekant Jain, Krishna Kumar Gupta, Sanjay K. Jain, Pallavee Bhatnagar
Summary: A five-level rectifier topology with self-balanced switched capacitors is proposed for EV battery charging applications, showing advantages such as wide output regulation and bidirectional power flow for vehicle-to-grid systems. Experimental results validate the feasibility of the proposed topology and its advantages for electric vehicle battery charging.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2022)
Article
Engineering, Multidisciplinary
Hamid Reza Gholinejad, Jafar Adabi, Mousa Marzband
Summary: This article proposes a smart charging approach for off-board EVs chargers in home-energy-hub applications. The proposed method enables smart charging and discharging of EVs, focusing on vehicle-to-x and x-to-vehicle operations in domestic applications integrated with renewable and storage elements. The study presents a laboratory implementation of a hierarchical energy management system for HEHs. The simulation and experimental results validate the effectiveness of the proposed analysis.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2022)
Article
Green & Sustainable Science & Technology
Hang Yu, Songyan Niu, Yitong Shang, Ziyun Shao, Youwei Jia, Linni Jian
Summary: This paper discusses the challenges and solutions for integrating electric vehicles with distribution grids and V2G operation, evaluates the performance of different architectures in terms of charging demand compatibility, power quality, V2G availability, etc., and provides recommendations for optimal architecture selection.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Energy & Fuels
Hang Yu, Yitong Shang, Songyan Niu, Chong Cheng, Ziyun Shao, Linni Jian
Summary: This paper presents a pseudo hierarchical management architecture for effective energy management in a compact, cost-effective, and easy-to-build DC nanogrid. The proposed architecture incorporates a state-triggered droop strategy in the short-time scale local management level and a multi-mode power dispatching strategy in the power dispatching level to achieve real-time, autonomous, and stabilized power coordination in the nanogrid. The effectiveness of the architecture and operation strategy is verified through detailed simulation models and hardware-in-loop experiments, showing improved operation economy and satisfaction of EV charging demand.
Article
Engineering, Electrical & Electronic
Musa Khan, Haishun Sun, Yingmeng Xiang, Di Shi
Summary: This paper discusses the smart management of Electric Vehicles (EVs) for Load Frequency Control (LFC), evaluating uncertain capacity and delay, ensuring system stability with a robust mixed H-2/H-infinity controller, and providing better reference tracking. The study shows that EVs and the adopted controller can effectively respond to various scenarios, reducing the burden on Conventional Sources (CS) while paving the way for a pollution-free future grid.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Green & Sustainable Science & Technology
S. Gupta, A. Maulik, D. Das, A. Singh
Summary: This study focuses on the optimal coordinated operation of a grid-connected AC microgrid consisting of controllable and uncontrollable power sources, battery storage units, considering plug-in hybrid electric vehicles and demand response programs. Through a nested stochastic optimization algorithm, a coordinated optimal operating strategy is proposed, which effectively reduces operating costs and system losses.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Energy & Fuels
Jian-Tang Liao, Hao-Wei Huang, Hong-Tzer Yang, Desheng Li
Summary: This study proposed optimal charging and discharging scheduling strategies for EV charging stations, utilizing a distributed computation architecture to streamline the complexity of an optimization problem and maximize operational profits for each EV and BESS. Considerations for conversion efficiencies under different load conditions, driver behavior models, and BESS degradation costs were included to enhance practical applicability.
Article
Energy & Fuels
Chun Wei, Zhuzheng Shen, Dongliang Xiao, Licheng Wang, Xiaoqing Bai, Haoyong Chen
Summary: This paper proposes an optimal scheduling strategy for interconnected microgrids, aiming to minimize operation costs and generate profits through peer-to-peer energy trading. The use of robust optimization and Nash bargaining mechanism ensures fair benefit sharing, while the alternating direction method of multipliers protects the privacy of individual microgrids. Simulation results demonstrate the effectiveness and fairness of the proposed method.
Article
Engineering, Electrical & Electronic
Peijie Li, Xiaoqian Huang, Junjian Qi, Hua Wei, Xiaoqing Bai
Summary: This study incorporates network connectivity into the mixed-integer linear programming model to solve the optimal transmission switching problem, effectively reducing the number of constraints. Case studies validate the effectiveness of the proposed model.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Energy & Fuels
Danlei Chen, Xiaoqing Bai
Summary: This study proposes a mixed-integer nonlinear programming model that combines electrical, natural gas, and heating systems, as well as coupling components such as CHP and gas-fired generators. By using second-order cone and linearized techniques, the model transforms the non-convex fundamental matrix formulation of multi-energy network equations to a mixed-integer convex multi-energy flow model, significantly improving computational efficiency and avoiding potential convergence issues.
FRONTIERS IN ENERGY RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Bin Li, Mengru Yang, Zhineng Li, Xiaoqing Bai
Summary: This study proposes a direct control strategy for central air conditioning based on discrete Fourier transform, which can reduce the deviation between actual load and transaction results while absorbing photovoltaic power generation and improving the enterprise economy.
IET GENERATION TRANSMISSION & DISTRIBUTION
(2022)
Article
Energy & Fuels
Shangfu Wei, Xiaoqing Bai
Summary: In this study, a novel hybrid model SSA-CNNBiGRU is proposed for short-term building energy consumption forecasting. The model integrates singular spectrum analysis, convolutional neural network, and bidirectional gated recurrent unit neural network. By decomposing, feature extraction, and time series forecasting of the energy consumption data, the proposed model achieves more accurate and stable energy consumption prediction.
Article
Engineering, Electrical & Electronic
Yunyi Li, Xiaoqing Bai, Jianling Meng, Liqin Zheng
Summary: This paper proposes a data-driven method for analyzing and evaluating the operation modes of power systems. By integrating techniques such as preprocessing, dimensionality reduction, clustering, and data visualization, high-dimensional datasets of power system operation can be processed and analyzed. Qualitative and quantitative methods are used to evaluate and study different operation modes in order to improve the efficiency of power grid enterprise operation and planning.
IET GENERATION TRANSMISSION & DISTRIBUTION
(2022)
Article
Engineering, Electrical & Electronic
Guang Liu, Zhengfeng Qin, Tianyi Diao, Xinwen Wang, Puming Wang, Xiaoqing Bai
Summary: This paper proposes an economic dispatch method based on robust stochastic optimization to reduce the operational difficulty of the integrated energy system under the low-carbon background. The paper establishes an optimization model for the integrated energy microgrid, considering energy conversion, transfer, and storage, and comprehensively considering system operation cost, waste treatment cost, and carbon trading cost. The rationality and effectiveness of the system are verified through simulation calculations.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Green & Sustainable Science & Technology
Ge Zhang, Songyang Zhu, Xiaoqing Bai
Summary: This paper proposes a CNN-Attention-LSTM model based on federated learning to forecast the multi-energy load of IEMs. Experimental results demonstrate that the federated models can achieve accuracy comparable to the central model and have better precision than individual models. The study also shows that the FedAdagrad strategy maintains stability when attacked by false data injection.
Article
Engineering, Electrical & Electronic
Yujing Jia, Xiaoqing Bai, Liqin Zheng, Zonglong Weng, Yunyi Li
Summary: AC optimal power flow (AC-OPF) is a significant problem in the economic operation of power systems. Traditional AC-OPF calculation methods only consider a specific operation pattern, which has limitations. We propose ConvOPF-DOP, a novel data-driven approach based on Convolutional Neural Network (CNN), to solve the AC-OPF problem in different operation patterns. The effectiveness and superiority of ConvOPF-DOP are verified through 30-bus systems in four different operation patterns. ConvOPF-DOP brings 350x speed increase compared with the traditional method while ensuring high accuracy of generated optimal solutions.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Editorial Material
Green & Sustainable Science & Technology
Xiaoqing Bai, Chun Wei, Peijie Li, Dongliang Xiao
Article
Energy & Fuels
Xiaoqing Shi, Xiaoqing Bai, Puming Wang, Qinghua Shang
Summary: This paper proposes a multi-time-scale rolling optimal scheduling method for virtual power plants, which integrates various types of distributed energy resources and performs optimal self-scheduling plans across different time scales, showing better performance in economy and security operation.
Article
Energy & Fuels
Puming Wang, Liqin Zheng, Tianyi Diao, Shengquan Huang, Xiaoqing Bai
Summary: This paper focuses on optimizing the operation of the park integrated energy system (PIES) and proposes a robust bilevel optimal dispatch. By constructing a robust uncertainty set and a two-level dispatch model, the proposed method ensures stability while increasing operator profits and reducing consumers' energy costs.
Article
Computer Science, Information Systems
Hongbo Wei, Hua Wei, Zhongliang Lyu, Xiaoqing Bai, Junyang Tian
Summary: This paper proposes a faulty feeder detection method based on Deep Belief Network for neutral non-effectively grounded systems. The method achieves a high accuracy of 94.7% by using millisecond-level data directly from the power dispatching system for training.
Article
Engineering, Electrical & Electronic
Peijie Li, Yucheng Wei, Junjian Qi, Xiaoqing Bai, Hua Wei
Summary: This paper proposes a closed-form formulation for eigenvalue sensitivities based on matrix calculus, which can enhance the accuracy and efficiency of stability analysis in power systems with converter-based generators.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2021)
Article
Engineering, Electrical & Electronic
Xiaohui Zhao, Hua Wei, Junjian Qi, Peijie Li, Xiaoqing Bai
Summary: The paper introduces an OPF model which considers dynamic frequency response constraints for ensuring frequency stability during primary frequency regulation. A definition of primary reserve for each unit is proposed based on the solution, leading to partial frequency restoration. Simulation results confirm the effectiveness of the model and highlight the strong coupling between frequency dynamics and pre-disturbance generation.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
