Electric Power Systems Research最新文献_第10页

Energy management system for a workplace PV-EV charging station with active and reactive power dispatch of EVs considering transformer aging and uncertainties 考虑变压器老化和不确定性的工作场所光伏-电动汽车充电站能源管理系统与电动汽车有功和无功功率调度

IF 3.3 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2024-10-15 DOI: 10.1016/j.epsr.2024.111062

Rayaprolu.M. Raghuveer, Bhavesh Bhalja, Pramod Agarwal

This study presents a new energy management system (EMS) for a grid-tied photovoltaic (PV) – electric vehicle (EV) integrated workplace charging station. The proposed EMS is developed as a convex stochastic mixed-integer quadratically constrained problem (MIQCP) to minimize the expected apparent power demand while limiting the distribution transformer's accelerated aging and satisfying the EV driving needs. This is accomplished by scheduling real and reactive powers of EVs in real-time through Vehicle-to-grid (V2G) mode. The inherent diurnal uncertainties and seasonal variations associated with the workplace non-EV load, PV generation are incorporated using probabilistic and hierarchical clustering techniques, respectively. The implementation of the developed EMS under receding horizon model enables real-time operation by adapting to dynamic arrivals of EVs. The effectiveness of the proposed EMS is validated through numerous simulations from the view point of the distribution system operator (DSO), charging station owner (CSO), and EV prosumer. The results indicate a substantial reduction in the peak demand, minimized transformer's loss-of-life (LoL), and operating cost saving while satisfying the EV driving needs in comparison to uncoordinated charging method.

本研究为并网光伏（PV）-电动汽车（EV）一体化工作场所充电站提出了一种新的能源管理系统（EMS）。所提出的 EMS 是一个凸随机混合整数二次约束问题 (MIQCP)，旨在最小化预期视在功率需求，同时限制配电变压器的加速老化并满足电动汽车的行驶需求。实现这一目标的方法是通过车辆对电网（V2G）模式实时调度电动汽车的实际功率和无功功率。利用概率和分层聚类技术，分别纳入了与工作场所非电动汽车负载、光伏发电相关的固有昼夜不确定性和季节性变化。在地平线后退模型下实施所开发的 EMS，可通过适应电动汽车的动态到达实现实时运行。从配电系统运营商（DSO）、充电站所有者（CSO）和电动汽车消费者的角度出发，通过大量模拟验证了所建议的 EMS 的有效性。结果表明，与非协调充电方法相比，在满足电动汽车驾驶需求的同时，峰值需求大幅降低，变压器寿命损失（LoL）最小化，运营成本节约。

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引用次数: 0

Fault classification in distribution system utilizing imaging time-series, convolutional neural network and adaptive relay protection 利用成像时间序列、卷积神经网络和自适应继电保护进行配电系统故障分类

IF 3.3 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2024-10-15 DOI: 10.1016/j.epsr.2024.111143

Baraa Khabaz , Maarouf Saad , Hasan Mehrjerdi

This paper presents a fault classification model in the transmission lines and classify faults while keeping the coordination between the primary and the backup relays by adaptively changing the relay’s parameters accordingly. The problem to be addressed through this paper is the need for a protection system that can dynamically adjust the relay’s settings and operation to enhance their response to the fault. This model is based on convolutional neural network (CNN), by implementing Gramian Angular Field (GAF) to transform voltage and current signals into images for extracting temporal features. The coordination between primary and backup relays is optimized to minimize primary relay operating time. The proposed model was evaluated using a 9-bus test system to determine optimal relay coordination based on fault’s type. The proposed fault classifier’s achieves 100% accuracy in classifying the faults while achieving the optimal solution in 0.047 s.

本文提出了一种输电线路故障分类模型，通过自适应地相应改变继电器的参数，在对故障进行分类的同时，保持主继电器和备用继电器之间的协调。本文要解决的问题是，保护系统需要能够动态调整继电器的设置和运行，以增强其对故障的响应能力。该模型基于卷积神经网络 (CNN)，通过实施格兰角场 (GAF) 将电压和电流信号转换为图像，以提取时间特征。对主继电器和备用继电器之间的协调进行了优化，以最大限度地减少主继电器的运行时间。利用 9 总线测试系统对所提出的模型进行了评估，以确定基于故障类型的最佳继电器协调。所提出的故障分类器对故障分类的准确率达到 100%，同时在 0.047 秒内实现了最佳解决方案。

引用次数: 0

Integrating model-driven and data-driven methods for under-frequency load shedding control 整合模型驱动和数据驱动方法，实现欠频甩负荷控制

IF 3.3 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2024-10-15 DOI: 10.1016/j.epsr.2024.111103

Binghui Li , Huaiyuan Wang , Jian Li , Guoqiang Lu

With the access of a high percentage of new energy sources, power system frequency stability is challenged. Under-frequency load shedding (UFLS) is one of the primary measures to maintain frequency stability. Due to the mismatch between the amount of load shed by the traditional UFLS methods and the actual active power deficit, a new UFLS method needs to be designed. An approach utilizing a deep deterministic policy gradient (DDPG) algorithm for the problem is proposed. First, the DDPG algorithm is modified to adapt to the UFLS problem. Then, the idea of model-driven is introduced to improve the validity of the model. Thus, a novel UFLS method is proposed, which integrates data-driven and model-driven ideas. Furthermore, a structure called the dual experience pool is designed to accelerate training speed and improve stability. Based on the proposed method, a UFLS control framework is designed. Finally, the suggested methodology is validated using the IEEE-39 bus system and the Fujian power grid as test cases.

随着大量新能源的接入，电力系统的频率稳定性面临挑战。欠频甩负荷（UFLS）是维持频率稳定的主要措施之一。由于传统 UFLS 方法的甩负荷量与实际有功功率缺口不匹配，因此需要设计一种新的 UFLS 方法。本文提出了一种利用深度确定性策略梯度（DDPG）算法解决该问题的方法。首先，对 DDPG 算法进行修改，以适应 UFLS 问题。然后，引入模型驱动的思想来提高模型的有效性。因此，我们提出了一种融合了数据驱动和模型驱动思想的新型 UFLS 方法。此外，还设计了一种名为双经验池的结构，以加快训练速度并提高稳定性。根据提出的方法，设计了一个 UFLS 控制框架。最后，以 IEEE-39 总线系统和福建电网为测试案例，对所提出的方法进行了验证。

引用次数: 0

A privacy protection scheme to resist ring selection attack in peer-to-peer double auction V2V electricity transaction for charging stations 在充电站点对点双竞价 V2V 电力交易中抵御选环攻击的隐私保护方案

IF 3.3 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2024-10-15 DOI: 10.1016/j.epsr.2024.111155

Shaomin Zhang , Xu Wang , Baoyi Wang

With the development of Electric Vehicles (EVs), the number of public charging piles cannot meet the immediate charging needs of EV users sometimes. The charging stations provide flexible electricity transaction schemes for users by managing charging piles and Vehicle-to-Vehicle (V2V). Users can freely choose transaction partners and submit transaction plans to multiple charging stations. The mobility of EVs results in users randomly selecting rings multiple times, which may cause them to appear in different rings. Attackers can link multiple transaction plans and infer user privacy information. The leakage of transaction information may threaten the fairness of transactions. Aiming at the above situations, a privacy protection scheme to resist ring selection attack in Peer-to-Peer double auction V2V electricity transaction for charging stations is proposed. Firstly, the ring signcryption algorithm is improved to resist ring selection attack. Secondly, a real identity verification algorithm is designed to track malicious users. Theoretical analysis proves that the security of the proposed privacy protection scheme. The elliptic curve point multiplication is used in the scheme to improve computational efficiency. Experiments show that this scheme has low computational and communication costs. Verification cost increases slowly with the increase of the number of ring members.

随着电动汽车（EV）的发展，公共充电桩的数量有时无法满足电动汽车用户的即时充电需求。充电站通过管理充电桩和车对车（V2V），为用户提供灵活的电力交易方案。用户可以自由选择交易伙伴，并向多个充电站提交交易计划。电动汽车的流动性导致用户多次随机选择环，从而可能出现在不同的环中。攻击者可以链接多个交易计划并推断用户隐私信息。交易信息的泄露可能会威胁到交易的公平性。针对上述情况，本文提出了一种在充电站点对点双竞价 V2V 电力交易中抵御选环攻击的隐私保护方案。首先，改进了环形签名加密算法，以抵御环形选择攻击。其次，设计了一种真实身份验证算法来跟踪恶意用户。理论分析证明了所提隐私保护方案的安全性。方案中使用了椭圆曲线点乘法来提高计算效率。实验表明，该方案的计算和通信成本较低。验证成本随着环成员数量的增加而缓慢增加。

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引用次数: 0

Data-driven adaptive Lyapunov function based graphical deep convolutional neural network for smart grid congestion management 基于数据驱动的自适应 Lyapunov 函数图形深度卷积神经网络用于智能电网拥塞管理

IF 3.3 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2024-10-14 DOI: 10.1016/j.epsr.2024.111163

J Christy , Pandia Rajan Jeyaraj

Optimal power flow by leveraging network grid topology will ensure stable operation of the smart grid. Energy management in grid-connected systems aimed to reduce computational non-linearities and ensure reliable operation of the smart grid. The conventional method manages congestion with optimal scheduling for every 10–15 min. Hence congestion in the smart grid occurs during secured energy distribution. In smart grid, instant congestion and energy management are needed. This research, work is devoted to a novel data-driven adaptive Lyapunov function with a Graphical Deep Convolutional Neural Network (GDCNN) regulated optimal flow by accurate energy management. By employing novel Graph theory-based network, the congestion data are obtained to train the proposed GDCNN. A Comparison of obtained results with existing baseline methods has been carried for claiming the novelties of proposed GDCNN. It is observed, that compared to existing machine learning-based extended subspace identification techniques. Our method has better optimal power regulation within 1.8 s by controlling power sources. Also, numerical simulation on IEEE 68 bus system shows the proposed GDCNN have superior performance, reliability, and optimal energy management. This by integrating the benefits of adaptive Lyapunov function and graphical convolutional network.

利用网络电网拓扑结构优化电力流将确保智能电网的稳定运行。并网系统中的能量管理旨在减少计算非线性，确保智能电网的可靠运行。传统方法通过每 10-15 分钟的优化调度来管理拥塞。因此，智能电网中的拥塞发生在安全的能量分配过程中。在智能电网中，需要即时的拥塞和能源管理。这项研究致力于利用图形深度卷积神经网络（GDCNN）的新型数据驱动自适应 Lyapunov 函数，通过精确的能源管理调节最佳流量。通过采用基于图论的新型网络，获得了拥堵数据来训练所提出的 GDCNN。为了证明所提出的 GDCNN 的新颖性，将所获得的结果与现有的基线方法进行了比较。结果表明，与现有的基于机器学习的扩展子空间识别技术相比，我们的方法能更好地实现最优电力调节。我们的方法通过控制电源，在 1.8 秒内实现了更好的最佳功率调节。此外，在 IEEE 68 总线系统上进行的数值仿真表明，所提出的 GDCNN 具有卓越的性能、可靠性和最佳能源管理。这得益于自适应 Lyapunov 函数和图形卷积网络的综合优势。

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引用次数: 0

Multi-energy trading strategies for integrated energy systems based on low-carbon and green certificate 基于低碳和绿色证书的综合能源系统多能源交易战略

IF 3.3 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2024-10-14 DOI: 10.1016/j.epsr.2024.111120

Jin Gao , Zhenguo Shao , Feixiong Chen , Mohammadreza Lak

Nowadays, integrated energy systems (IESs) have become an influential approach in the backdrop of energy interconnection and low-carbon energy concepts. This paper proposes a multi-energy trading strategy for IESs that simultaneously considers carbon emissions transaction (CET) and tradable green certificate (TGC) to promote low-carbon energy development further. Firstly, a multi-stage robust optimization method addresses uncertainties in renewable energy, loads, and electricity prices to ensure stable operation of the IES. Secondly, a trading mechanism is proposed by integrating CET with TGC to establish a coupled electricity-heat-carbon-green certificate market. Accordingly, a cooperative game framework among multiple IESs is modeled, which considers different contribution allocations while promoting the economic and low-carbon operation of IES. Finally, the model is solved using the alternating direction method of multipliers (ADMM) algorithm. The proposed strategy’s effectiveness in improving the low-carbon economic operation of IESs has been proved through simulation studies.

如今，在能源互联和低碳能源概念的背景下，综合能源系统（IES）已成为一种颇具影响力的方法。本文提出了一种同时考虑碳排放交易（CET）和可交易绿色证书（TGC）的综合能源系统多能源交易策略，以进一步推动低碳能源的发展。首先，采用多阶段稳健优化方法解决可再生能源、负荷和电价的不确定性，确保 IES 的稳定运行。其次，通过将 CET 与 TGC 相结合，提出了一种交易机制，以建立一个电-热-碳-绿证书耦合市场。相应地，模拟了多个 IES 之间的合作博弈框架，在促进 IES 经济低碳运行的同时，考虑了不同的贡献分配。最后，利用交替乘法（ADMM）算法对模型进行求解。通过模拟研究，证明了所提策略在改善 IES 低碳经济运行方面的有效性。

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引用次数: 0

A novel frequency constrained unit commitment considering VSC-HVDC's frequency support in asynchronous interconnected system under renewable energy Source's uncertainty 考虑可再生能源不确定性下异步互联系统中 VSC-HVDC 频率支持的新型频率受限机组承诺

IF 3.3 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2024-10-12 DOI: 10.1016/j.epsr.2024.111098

Danyang Xu, Zhigang Wu, Lin Zhu, Lin Guan

The increasing share of renewable energy source (RES) poses a challenge to the frequency security of the power system. Frequency constrained unit commitment (FCUC) serves as an effective measure to address this challenge at the operational level. This paper introduces a novel FCUC model applicable to the asynchronous interconnected system connected by voltage source converter based HVDC (VSCHVDC), fully taking into account the frequency support capability of VSCHVDC in order to reduce the demand for synchronous generators' inertia and reserve while ensuring frequency security, thereby lowering operating costs. Additionally, the uncertainty of RES is also considered. The constraint expressions for three frequency indicators are derived based on a system frequency response model that includes frequency support from VSCHVDC. The proposed model optimizes unit commitment, generation and reserve dispatch and VSCHVDC transmission power and frequency response parameters, while addressing RES uncertainty using the distributionally robust chance constrained approach. In response to the highly nonlinear characteristics of the maximum frequency derivation (MFD) constraints, we propose an intelligent sampling-based support vector machine to convexify the MFD constraints and introduce a two-stage decomposition algorithm for solving the model. The effectiveness of the proposed model is demonstrated based on a modified IEEE RTS-79 system.

可再生能源（RES）份额的不断增加对电力系统的频率安全构成了挑战。频率约束单位承诺（FCUC）是在运行层面应对这一挑战的有效措施。本文介绍了一种适用于基于电压源换流器的高压直流（VSCHVDC）连接的异步互联系统的新型 FCUC 模型，充分考虑了 VSCHVDC 的频率支持能力，以便在确保频率安全的同时减少对同步发电机惯性和储备的需求，从而降低运营成本。此外，还考虑了可再生能源的不确定性。基于包含 VSCHVDC 频率支持的系统频率响应模型，得出了三个频率指标的约束表达式。提议的模型优化了机组承诺、发电和储备调度以及 VSCHVDC 输电功率和频率响应参数，同时使用分布稳健的机会约束方法解决可再生能源的不确定性问题。针对最大频率推导（MFD）约束的高度非线性特性，我们提出了一种基于智能采样的支持向量机来凸化 MFD 约束，并引入了一种两阶段分解算法来求解模型。基于修改后的 IEEE RTS-79 系统，演示了所提模型的有效性。

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引用次数: 0

Spatio-temporal graph attention network-based detection of FDIA from smart meter data at geographically hierarchical levels 基于时空图注意网络的智能电表数据的 FDIA 地理分层检测

IF 3.3 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2024-10-11 DOI: 10.1016/j.epsr.2024.111149

Md Abul Hasnat , Harsh Anand , Mazdak Tootkaboni , Negin Alemazkoor

The power consumption data from residential households collected by smart meters exhibit a diverse pattern temporally and among themselves. It is challenging to distinguish between regular consumer behavior and injected falsified measurements into the data stream with the intent of energy theft or compromising the security of the associated measurement infrastructure. This work identifies the challenges of detecting falsified measurements in smart meter data aggregated at geographically hierarchical levels and proposes a novel graph attention network (GAT)-based unsupervised learning framework to detect false data injection attacks (FDIA) from the moving statistics of the power consumption data in real-time, namely MOVSTAT-GAT. The proposed technique is capable of detecting falsified measurements at both 9-digit and 5-digit ZIP code labels in an unsupervised manner, solely from smart meter power consumption data with no additional meters. Moreover, the proposed technique offers a visualization technique to assist the operator in identifying the localization characteristics of the attack and proposes an automated localization strategy for localized FDIAs. Experiments suggest the effectiveness of the proposed framework, especially for localized FDIA or external anomalies, such as power outages and denial-of-service (DoS). Additionally, a detailed discussion regarding the implementation of MOVSTAT-GAT in the industrial environment has been provided.

智能电表收集的居民家庭用电数据在时间上和数据之间呈现出不同的模式。在数据流中区分正常的用户行为和以窃取能源或破坏相关测量基础设施的安全为目的而注入的伪造测量数据具有挑战性。本研究确定了在按地理层次聚合的智能电表数据中检测伪造测量值所面临的挑战，并提出了一种基于图注意网络（GAT）的新型无监督学习框架，即 MOVSTAT-GAT，用于从实时电能消耗数据的移动统计中检测虚假数据注入攻击（FDIA）。所提出的技术能够以无监督的方式检测出 9 位数和 5 位数邮政编码标签上的虚假测量数据，而且仅从智能电表的用电数据中检测，不需要额外的电表。此外，所提出的技术还提供了一种可视化技术，帮助操作员识别攻击的定位特征，并提出了一种针对定位 FDIA 的自动定位策略。实验表明，所提出的框架非常有效，尤其适用于局部 FDIA 或外部异常情况，如停电和拒绝服务（DoS）。此外，还详细讨论了 MOVSTAT-GAT 在工业环境中的实施情况。

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引用次数: 0

A voltage sensorless technique for a shunt active power filter adopting band pass filter under abnormal supply conditions 异常供电条件下采用带通滤波器的并联有源电力滤波器的无电压传感器技术

IF 3.3 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2024-10-11 DOI: 10.1016/j.epsr.2024.111133

Ahmed M.M. Nour , Ahmed A. Helal

Shunt active power filters (SAPFs) are effective in addressing power quality issues such as harmonics and voltage unbalance. During abnormal grid conditions, there will be a substantial variation in both the actual and reactive power of the system. Various SAPF control approaches were employed to address these issues. This paper presents an improved bandpass filter technique that serves multiple purposes: extracting the reference current harmonic for SAPF, providing reactive current for power factor correction, and functioning as a backup synchronization method in the event of a loss of bus voltage measurement. Furthermore, it should be minimally affected by the unbalance in supply voltage. The case study model and the proposed reference technique have been executed and validated using the MATLAB software environment.

并联有源电力滤波器（SAPF）可有效解决谐波和电压不平衡等电能质量问题。在异常电网条件下，系统的实际功率和无功功率都会出现大幅变化。为解决这些问题，人们采用了各种 SAPF 控制方法。本文介绍了一种改进的带通滤波器技术，它具有多种功能：为 SAPF 提取参考电流谐波，为功率因数校正提供无功电流，以及在母线电压测量丢失的情况下作为备用同步方法。此外，它还应尽量不受电源电压不平衡的影响。使用 MATLAB 软件环境执行并验证了案例研究模型和建议的参考技术。

引用次数: 0

Comparison of interfacial injected energy between simulated lightning return stroke experiment and common Joule heat & Arc heat model application 模拟闪电回击实验与普通焦耳热和弧热模型应用之间的界面注入能量比较

IF 3.3 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2024-10-10 DOI: 10.1016/j.epsr.2024.111034

Yutong Lin

A previous study has shown that the thermal damage of the Joule thermal arc heat transfer model is lighter than that of a natural lightning strike. Therefore, this paper focuses on the return stroke current and proposes an improved experimental method of simulated return damage without using arc-inducing wire. Combining the data with the inversion model of injected energy, the energy transfer characteristics of the samples are characterized. Furthermore, a data dimensionality reduction method based on multiple correlation coefficients is used to discuss the impact of the current peak/rise rate/wave tail time on the injected energy discrepancy. The results indicate a positive correlation between the current peak and current rise rate with the injected energy discrepancy. When the tail time exceeds 15 microseconds, the injected energy discrepancy decreases as the tail time increases. The thermal source characteristics of energy transfer during the return stroke process are determined. During the initial phase of the return stroke current, interfacial energy transfer includes contributions from ion enthalpy flux, Joule heating, and electronic enthalpy flux. When the tail time exceeds 15 microseconds, the contribution of ion enthalpy flux to the injected energy diminishes with increasing tail time.

之前的研究表明，焦耳热电弧传热模型的热损伤比自然雷击轻。因此，本文将重点放在回击电流上，并提出了一种改进的不使用引弧线模拟回击损伤的实验方法。将数据与注入能量的反演模型相结合，表征了样品的能量传递特性。此外，基于多重相关系数的数据降维方法用于讨论电流峰值/上升率/波尾时间对注入能量差异的影响。结果表明，电流峰值和电流上升率与注入能量差异呈正相关。当波尾时间超过 15 微秒时，注入能量差异会随着波尾时间的增加而减小。确定了返回冲程过程中能量传递的热源特性。在返回冲程电流的初始阶段，界面能量传递包括离子焓通量、焦耳加热和电子焓通量的贡献。当尾流时间超过 15 微秒时，离子焓通量对注入能量的贡献随着尾流时间的增加而减少。

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引用次数: 0