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
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
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
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
Thermodynamics
Liqin Zheng, Yunyi Li, Chun Wei, Xiaoqinq Bai
Summary: This paper proposes a data-driven method to identify operation patterns of an integrated energy microgrid, which is shown to be effective and superior through verification.
ENERGY CONVERSION AND MANAGEMENT-X
(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
Multidisciplinary Sciences
Yi Zheng, Xiaoqing Bai
Summary: The paper proposes a dynamic economic dispatch model considering AC optimal power flow based on CVaR, utilizing the wind-storage combined system and employing the MISOCP model. By analyzing dispatching costs at different confidence levels, it is determined that the CVaR method can adequately estimate dispatching risk, assisting decision-makers in formulating reasonable dispatching schedules.
SN APPLIED SCIENCES
(2021)
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)
