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Key Technologies and Prospects for Electric Vehicles Within Emerging Power Systems: Insights from Five Aspects 新兴电力系统中电动汽车的关键技术与前景:从五个方面透视
IF 7.1 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-02-14 DOI: 10.17775/CSEEJPES.2024.00190
Yalun Li;Minggao Ouyang;C. C. Chan;Xueliang Sun;Yonghua Song;Wei Cai;Yilin Xie;Yuqiong Mao
The energy revolution requires coordination in energy consumption, supply, storage and institutional systems. Renewable energy generation technologies, along with their associated costs, are already fully equipped for large-scale promotion. However, energy storage remains a bottleneck, and solutions are needed through the use of electric vehicles, which traditionally play the role of energy consumption in power systems. To clarify the key technologies and institutions that support EVs as terminals for energy use, storage, and feedback, the CSEE JPES forum assembled renowned experts and scholars in relevant fields to deliver keynote reports and engage in discussions on topics such as vehicle-grid integration technology, advanced solid-state battery technology, high-performance electric motor technology, and institutional innovation in the industry chain. These experts also provided prospects for energy storage and utilization technologies capable of decarbonizing new power systems.
能源革命要求协调能源消费、供应、储存和机构系统。可再生能源发电技术及其相关成本已完全具备大规模推广的条件。然而,能源储存仍然是一个瓶颈,需要通过使用电动汽车来解决,因为电动汽车传统上在电力系统中扮演着能源消耗的角色。为了明确支持电动汽车作为能源使用、存储和反馈终端的关键技术和制度,CSEE JPES 论坛召集了相关领域的知名专家学者,就车网一体化技术、先进固态电池技术、高性能电机技术、产业链制度创新等议题进行了主题报告和讨论。这些专家还对能够实现新电力系统去碳化的能源储存和利用技术进行了展望。
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引用次数: 0
Hybrid Modular Smart Transformer for Asymmetrically Bidirectional Power Flow Operation 用于非对称双向功率流运行的混合模块化智能变压器
IF 6.9 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-02-14 DOI: 10.17775/CSEEJPES.2022.05650
Kangan Wang;Youngjong Ko;Rongwu Zhu;Siyu Wu;Weimin Wu;Marco Liserre
The presence of renewable energy resources in LV distribution networks may lead to a distribution transformer, also known as a Smart Transformer (ST), experiencing the bidirectional power flow. Therefore, the ST must have the capability to operate in both directions. However, the reverse power is less as compared to the forward power, thus the design of ST with the same capacity in both directions increases the hardware cost and decreases the system efficiency. This paper proposes a Hybrid-modular-ST (H-ST), composed of a mixed use of single active bridge-based series resonant converter and dual active bridge instead of complete use of uni-or bi-directional converter adopted in the conventional solid-state-transformer. Based on the proposed H-ST, the impacts of power imbalance among cascaded modules in reverse operation mode are analyzed and then an effective solution based on reactive power compensation combined with the characteristics of the proposed architecture is adopted. The simulation and experimental results clearly validate the effectiveness and feasibility of the theoretical analyses.
低压配电网络中可再生能源的存在可能会导致配电变压器(也称为智能变压器(ST))出现双向电力流动。因此,智能变压器必须具备双向运行的能力。然而,与正向功率相比,反向功率较小,因此设计双向容量相同的 ST 会增加硬件成本并降低系统效率。本文提出了一种混合模块化 ST(H-ST),由基于单有源桥的串联谐振转换器和双有源桥混合使用组成,而不是完全使用传统固态变压器中采用的单向或双向转换器。基于所提出的 H-ST 架构,分析了反向运行模式下级联模块间功率不平衡的影响,并结合所提出的架构特点,提出了基于无功功率补偿的有效解决方案。仿真和实验结果清楚地验证了理论分析的有效性和可行性。
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引用次数: 0
Reinforcement Learning-Empowered Graph Convolutional Network Framework for Data Integrity Attack Detection in Cyber-Physical Systems 用于网络物理系统数据完整性攻击检测的强化学习驱动图卷积网络框架
IF 7.1 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-02-14 DOI: 10.17775/CSEEJPES.2023.01250
Edeh Vincent;Mehdi Korki;Mehdi Seyedmahmoudian;Alex Stojcevski;Saad Mekhilef
The massive integration of communication and information technology with the large-scale power grid has enhanced the efficiency, safety, and economical operation of cyber-physical systems. However, the open and diversified communication environment of the smart grid is exposed to cyber-attacks. Data integrity attacks that can bypass conventional security techniques have been considered critical threats to the operation of the grid. Current detection techniques cannot learn the dynamic and heterogeneous characteristics of the smart grid and are unable to deal with non-euclidean data types. To address the issue, we propose a novel Deep-Q-Network scheme empowered with a graph convolutional network (GCN) framework to detect data integrity attacks in cyber-physical systems. The simulation results show that the proposed framework is scalable and achieves higher detection accuracy, unlike other benchmark techniques.
通信和信息技术与大规模电网的大规模集成提高了网络物理系统的效率、安全性和经济性。然而,智能电网开放和多样化的通信环境面临着网络攻击。可以绕过传统安全技术的数据完整性攻击被认为是对电网运行的严重威胁。目前的检测技术无法了解智能电网的动态和异构特性,也无法处理非欧几里得数据类型。为解决这一问题,我们提出了一种新颖的深度 Q 网络方案,该方案采用图卷积网络(GCN)框架,用于检测网络物理系统中的数据完整性攻击。仿真结果表明,与其他基准技术不同,所提出的框架具有可扩展性,并能实现更高的检测精度。
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引用次数: 0
Detection Method for Cascading Failure of Power Systems Based on Epidemic Model 基于流行病模型的电力系统级联故障检测方法
IF 7.1 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-02-14 DOI: 10.17775/CSEEJPES.2022.07410
Jian Xu;Zhonghao He;Siyang Liao;Yuanzhang Sun;Liangzhong Yao;Deping Ke;Jun Yang
The early detection of cascading failure plays an important role in the safe and stable operation of the power system with high penetration of renewable energy. This paper proposes a fault propagation dynamic model based on the epidemic model, and further puts forward a method to detect the development of cascading failures. Through the simulation of the IEEE 39-bus and 118-bus systems, this model is proven to be valid and capable of providing practical technical support for the prevention of cascading failures in power systems with high penetration of renewable energy. This paper also provides an analysis method for the choice of different protection and control measures at each stage of cascading failure, which has critical significance and follow-up value.
在可再生能源渗透率较高的情况下,早期发现级联故障对电力系统的安全稳定运行具有重要作用。本文提出了一种基于流行病模型的故障传播动态模型,并进一步提出了一种检测级联故障发展的方法。通过对 IEEE 39 总线和 118 总线系统的仿真,证明该模型是有效的,能够为可再生能源高渗透率电力系统中级联故障的预防提供实用的技术支持。本文还提供了在级联故障各阶段选择不同保护和控制措施的分析方法,具有关键意义和后续价值。
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引用次数: 0
Observability Analysis of Integrated Electricity and Heating Systems with Thermal Quasi-Dynamics in Pipelines 管道热准动力学综合电力和供热系统的可观测性分析
IF 7.1 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-02-14 DOI: 10.17775/CSEEJPES.2022.04860
Zhigang Li;Wenjian Zheng;Junbo Zhao;J. H. Zheng;Q. H. Wu
Observability analysis (OA) is vital to obtaining the available input measurements of state estimation (SE) in an integrated electricity and heating system (IEHS). Considering the thermal quasi-dynamics in pipelines, the measurement equations in heating systems are dependent on the estimated results, leading to an interdependency between OA and SE. Conventional OA methods require measurement equations be known exactly before SE is performed, and they are not applicable to IEHSs. To bridge this gap, a scenario-based OA scheme for IEHSs is devised that yields reliable analysis results for a predefined set of time-delay scenarios to cope with this interdependency. As its core procedure, the observable state identification and observability restoration are formulated in terms of integer linear programming. Numerical tests are conducted to demonstrate the validity and superiority of the proposed formulation.
可观测性分析(OA)对于获得综合电力和供热系统(IEHS)中状态估计(SE)的可用输入测量值至关重要。考虑到管道中的热准动力学,供热系统中的测量方程取决于估计结果,从而导致 OA 和 SE 之间的相互依存关系。传统的 OA 方法要求在执行 SE 之前准确知道测量方程,因此不适用于 IEHS。为了弥补这一缺陷,我们为 IEHS 设计了一种基于情景的 OA 方案,该方案可为一组预定义的时延情景提供可靠的分析结果,以应对这种相互依赖关系。作为其核心程序,可观测状态识别和可观测性恢复是通过整数线性规划来实现的。为证明所提方案的有效性和优越性,进行了数值测试。
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引用次数: 0
Distributed Energy and Reserve Scheduling in Local Energy Communities Using L-BFGS Optimization 利用 L-BFGS 优化本地能源社区的分布式能源和储备调度
IF 7.1 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-02-14 DOI: 10.17775/CSEEJPES.2023.06270
Mohammad Dolatabadi;Alireza Zakariazadeh;Alberto Borghetti;Pierluigi Siano
Encouraging citizens to invest in small-scale renewable resources is crucial for transitioning towards a sustainable and clean energy system. Local energy communities (LECs) are expected to play a vital role in this context. However, energy scheduling in LECs presents various challenges, including the preservation of customer privacy, adherence to distribution network constraints, and the management of computational burdens. This paper introduces a novel approach for energy scheduling in renewable-based LECs using a decentralized optimization method. The proposed approach uses the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method, significantly reducing the computational effort required for solving the mixed integer programming (MIP) problem. It incorporates network constraints, evaluates energy losses, and enables community participants to provide ancillary services like a regulation reserve to the grid utility. To assess its robustness and efficiency, the proposed approach is tested on an 84-bus radial distribution network. Results indicate that the proposed distributed approach not only matches the accuracy of the corresponding centralized model but also exhibits scalability and preserves participant privacy.
鼓励公民投资小型可再生资源对于向可持续和清洁能源系统过渡至关重要。地方能源社区有望在这方面发挥重要作用。然而,LEC 中的能源调度面临着各种挑战,包括保护客户隐私、遵守配电网络限制以及管理计算负担。本文介绍了一种在基于可再生能源的 LEC 中使用分散优化方法进行能源调度的新方法。所提出的方法采用了有限内存 Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) 方法,大大减少了解决混合整数编程 (MIP) 问题所需的计算量。它纳入了网络约束条件,评估了能源损失,并使社区参与者能够向电网公用事业公司提供辅助服务,如调节储备。为了评估该方法的稳健性和效率,我们在一个 84 总线的径向配电网络上对所提出的方法进行了测试。结果表明,所提出的分布式方法不仅与相应的集中式模型的准确性相匹配,而且还具有可扩展性,并能保护参与者的隐私。
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引用次数: 0
Resilient Smart Power Grid Synchronization Estimation Method for System Resilience with Partial Missing Measurements 针对部分缺失测量的系统弹性智能电网同步估计方法
IF 7.1 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-02-14 DOI: 10.17775/CSEEJPES.2023.06900
Yi Wang;Yanxin Liu;Mingdong Wang;Venkata Dinavahi;Jun Liang;Yonghui Sun
With the increasing demand for power system stability and resilience, effective real-time tracking plays a crucial role in smart grid synchronization. However, most studies have focused on measurement noise, while they seldom think about the problem of measurement data loss in smart power grid synchronization. To solve this problem, a resilient fault-tolerant extended Kalman filter (RFTEKF) is proposed to track voltage amplitude, voltage phase angle and frequency dynamically. First, a three-phase unbalanced network's positive sequence fast estimation model is established. Then, the loss phenomenon of measurements occurs randomly, and the randomness of data loss's randomness is defined by discrete interval distribution [0], [1]. Subsequently, a resilient fault-tolerant extended Kalman filter based on the real-time estimation framework is designed using the time-stamp technique to acquire partial data loss information. Finally, extensive simulation results manifest the proposed RFTEKF can synchronize the smart grid more effectively than the traditional extended Kalman filter (EKF).
随着对电力系统稳定性和恢复能力的要求越来越高,有效的实时跟踪在智能电网同步中发挥着至关重要的作用。然而,大多数研究都侧重于测量噪声,而很少考虑智能电网同步中的测量数据丢失问题。为解决这一问题,本文提出了一种弹性容错扩展卡尔曼滤波器(RFTEKF)来动态跟踪电压幅值、电压相位角和频率。首先,建立了三相不平衡电网的正序快速估计模型。然后,随机发生测量丢失现象,数据丢失的随机性由离散区间分布 [0]、[1] 定义。随后,利用时间戳技术获取部分数据丢失信息,设计了基于实时估计框架的弹性容错扩展卡尔曼滤波器。最后,大量仿真结果表明,与传统的扩展卡尔曼滤波器(EKF)相比,所提出的 RFTEKF 能更有效地同步智能电网。
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引用次数: 0
Self-Sustaining of Critical Park Microgrids Integrating Mobile Emergency Generators Subjective to Major Outage 集成移动应急发电机的重要园区微电网在大停电情况下的自我维持能力
IF 6.9 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-02-14 DOI: 10.17775/CSEEJPES.2023.01670
Quan Sui;Lei Zhang
In the event of a major power outage, critical park microgrids (PMGs) could be self-sustaining if mobile emergency generators (MEGs) are stationed to share energy. However, the need for privacy protection and the value of flexible power support on minute-time scales have not been given enough attention. To address the problem, this paper proposes a new self-sustaining strategy for critical PMGs integrating MEGs. First, to promote the cooperation between PMG and MEG, a bi-level benefit distribution mechanism is designed, where the participants' multiple roles and contributions are identified, and good behaviors are also awarded. Additionally, to increase the alliance benefits, three loss coordination modes are presented to guide the power exchange at the minute level between the MEG and PMG, considering the volatility of renewable generation and load. On this basis, a multi-time scale power-energy scheduling strategy is formulated via the alternating direction method of multipliers (ADMM) to coordinate the PMG and MEG. Finally, a dimensionality reduction technology is designed to equivalently simplify the optimization problem to facilitate the adaptive-step-based ADMM solution. Simulation studies indicate that the proposed strategy achieves the self-sustaining of PMGs integrating MEGs while increasing the economy by no less than 3.1%.
在发生重大停电事件时,如果移动应急发电机(MEG)能够共享能源,关键园区微电网(PMGs)就能自我维持。然而,隐私保护的需求和分钟级灵活电力支持的价值尚未得到足够重视。为解决这一问题,本文提出了一种新的关键永磁发电机整合移动应急发电机的自我维持策略。首先,为促进 PMG 与 MEG 之间的合作,本文设计了一种双层利益分配机制,即对参与者的多重角色和贡献进行识别,并对良好行为进行奖励。此外,考虑到可再生能源发电和负荷的波动性,为提高联盟效益,提出了三种损耗协调模式,以指导 MEG 和 PMG 在分钟级的电力交换。在此基础上,通过乘法交替方向法(ADMM)制定了多时间尺度的电力-能源调度策略,以协调 PMG 和 MEG。最后,设计了一种降维技术来等效简化优化问题,以促进基于自适应步长的 ADMM 求解。仿真研究表明,所提出的策略实现了永磁发电机与多元气体发电机的自我维持,同时提高了不少于 3.1% 的经济效益。
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引用次数: 0
Conjugate Vectors Method Applied to Asymmetrical Fault Analysis of Power Electronized Power Systems 共轭矢量法在电力电子化系统非对称故障分析中的应用
IF 6.9 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-02-14 DOI: 10.17775/CSEEJPES.2023.04790
Yingbiao Li;Xing Liu;Jiabing Hu;Jianhang Zhu;Jianbo Guo
With the wide application of power electronized resources (PERs), the amplitude and frequency of voltages show significant time-varying characteristics under asymmetrical faults. As a result, the traditional phasor model, impedance model, and symmetrical components method based on the constant amplitude and frequency of voltages are facing great challenges. Hence, a novel asymmetrical fault analysis method based on conjugate vectors is proposed in this paper which can meet the modeling and analysis requirements of the network excited by voltages with time-varying amplitude/frequency. Furthermore, asymmetrical fault characteristics are extracted. As an application, a faulted phase identification (FPI) strategy is proposed based on the fault characteristics. The correctness and superiority of the asymmetrical fault analysis method and FPI strategy are verified in time-domain simulations and a real-time digital simulator.
随着电力电子资源(PER)的广泛应用,在非对称故障情况下,电压的幅值和频率表现出明显的时变特性。因此,传统的相量模型、阻抗模型和基于电压恒定幅值和频率的对称分量法面临着巨大挑战。因此,本文提出了一种基于共轭矢量的新型非对称故障分析方法,可满足由时变幅值/频率电压激发的网络的建模和分析要求。此外,还提取了非对称故障特征。作为应用,根据故障特征提出了故障相位识别(FPI)策略。时域仿真和实时数字仿真器验证了非对称故障分析方法和 FPI 策略的正确性和优越性。
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引用次数: 0
Optical Sensor with Wide Range and High Sensitivity for Internal Magnetic Field Detection of Transformer 用于变压器内部磁场检测的宽范围、高灵敏度光学传感器
IF 6.9 2区 工程技术 Q2 ENERGY & FUELS Pub Date : 2024-02-14 DOI: 10.17775/CSEEJPES.2022.07270
Meng Huang;Wei Zheng;Tong Ji;Mao Ji;Tianjiao Pu;Bo Qi
The deterioration of winding defects is one of the important causes of power transformer fires and even explosion failures. The change of leakage magnetic field distribution is the most direct response to winding defects. Currently there are few sensors suitable for online measurement of the internal magnetic field of transformers. Based on the Faraday magneto-optical effect, a magnetic field sensor with wide range and high sensitivity is proposed in this paper, which is suitable for the interior use of transformers. The straight-through optical structure with interior polarizer is adopted, and the sensor has a measurement range of 1.5 T and a sensitivity of 1 mT. It also possesses a small size, with a length of about 30 mm after encapsulation. The influence mechanism of vibration and temperature is revealed through theoretical analysis and numerical simulation. It is proposed to filter out the interference of vibration by characteristic frequency analysis and to compensate for temperature by a two-probe structure. An anti-interference test verifies the effectiveness of this method, and it can reduce the error from 80.56% to 2.63% under the combined interference of vibration and temperature.
绕组缺陷的恶化是电力变压器起火甚至爆炸故障的重要原因之一。漏磁场分布的变化是对绕组缺陷最直接的反应。目前,适合在线测量变压器内部磁场的传感器很少。本文基于法拉第磁光效应,提出了一种适用于变压器内部的宽量程、高灵敏度磁场传感器。该传感器采用带内部偏振片的直通式光学结构,测量范围为 1.5 T,灵敏度为 1 mT。该传感器体积小,封装后长度约为 30 毫米。通过理论分析和数值模拟,揭示了振动和温度的影响机理。建议通过特征频率分析滤除振动干扰,并通过双探头结构补偿温度。抗干扰试验验证了该方法的有效性,在振动和温度的共同干扰下,该方法可将误差从 80.56% 降至 2.63%。
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引用次数: 0
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CSEE Journal of Power and Energy Systems
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