Electric Power Systems Research最新文献_第8页

A distributionally robust optimization approach of multi-park integrated energy systems considering shared energy storage and Uncertainty of Demand Response 考虑共享储能和需求响应不确定性的多园区综合能源系统分布式稳健优化方法

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

Electric Power Systems Research

Pub Date : 2024-10-05 DOI: 10.1016/j.epsr.2024.111116

Zechen Wang, Zhao Liu, Yuchong Huo

To enhance the economic efficiency and renewable energy integration capacity of multi-park integrated energy systems (MPIES) and address the issue of insufficient consideration of demand response uncertainty in existing studies, this paper proposes a distributionally robust optimization approach for multi-park integrated energy systems, considering shared energy storage and the uncertainty of demand response. First, models of the shared energy system and demand response are established. Based on these models, a deterministic optimization scheduling model for MPIES is developed, aiming to minimize system costs while considering constraints such as grid power balance. To address uncertainty in demand response, this paper employs Interval Type-2 Fuzzy Theory to construct uncertainty sets and considers system reliability constraints. The original optimization problem is then transformed into an equivalent robust counterpart model, and the optimal distributionally robust solution is obtained through parameter domain decomposition methods. Finally, the proposed method is validated using the IEEE 33-bus system. The results show that considering shared energy storage and demand response individually can reduce total system costs by 4.86 % and 26.46 %, respectively. After accounting for the uncertainty in demand response, the total system cost increases only slightly by 4.36 %, but this improves the system's robustness.

为提高多园区综合能源系统（MPIES）的经济效益和可再生能源集成能力，并解决现有研究中对需求响应不确定性考虑不足的问题，本文提出了一种考虑共享储能和需求响应不确定性的多园区综合能源系统分布式稳健优化方法。首先，建立了共享能源系统和需求响应模型。在这些模型的基础上，为 MPIES 开发了一个确定性优化调度模型，旨在最大限度地降低系统成本，同时考虑电网功率平衡等约束条件。为了解决需求响应中的不确定性问题，本文采用了区间-2 型模糊理论来构建不确定性集，并考虑了系统可靠性约束。然后将原始优化问题转化为等效鲁棒对应模型，并通过参数域分解方法获得最优分布式鲁棒解决方案。最后，利用 IEEE 33 总线系统验证了所提出的方法。结果表明，单独考虑共享储能和需求响应可将系统总成本分别降低 4.86 % 和 26.46 %。在考虑需求响应的不确定性后，系统总成本仅略微增加了 4.36%，但这提高了系统的鲁棒性。

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引用次数: 0

Preventive primary frequency response control of energy storage systems for a high renewable penetrated power grid 可再生能源渗透率高的电网中储能系统的预防性一次频率响应控制

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

Electric Power Systems Research

Pub Date : 2024-10-05 DOI: 10.1016/j.epsr.2024.111109

Heng Wang , Xinyan Zhang , Yiqian Sun , Qing Li

Low inertia in power grids with high renewable penetration may lead to severe frequency concerns after disturbances. Meanwhile, fluctuations of renewable generation can make the frequency deviation even worse, due to their large proportion in total generation capacity. Energy storage system (ESS) is a promising solution to relief the frequency issues, taking advantages of its fast response and relatively low cost compared with hydro or thermal generations with similar frequency support capability. However, ESS commonly responses to frequency deviation following a droop control with preset droop rate and deadband width, such constant primary frequency response parameter (PFRP) setting is insufficient for a system with various renewable fluctuation patterns and possible contingencies. In order to overcome this issue, this work proposes a preventive control scheme to determine PFRP of ESS, which is able to dynamically adjust droop rate and deadband width along with day-ahead dispatch using a multi-period scenario-based optimal power flow (OPF) formulation. The effectiveness of the proposed approach is verified using the test cases from a real-world province-level power grid with high renewable penetration in China. Numerical results show that the proposed approach is able to achieve required post-disturbance frequency performance by only increasing less than 3% operating cost.

在可再生能源渗透率较高的电网中，低惯性可能会导致扰动后出现严重的频率问题。同时，由于可再生能源发电在总发电量中所占比例较大，其波动会使频率偏差更加严重。与具有类似频率支持能力的水力或火力发电相比，储能系统（ESS）具有响应速度快、成本相对较低的优势，是缓解频率问题的一种有前途的解决方案。然而，ESS 通常采用预设下垂率和死区宽度的下垂控制来响应频率偏差，这种恒定的主频率响应参数（PFRP）设置对于具有各种可再生能源波动模式和可能的突发事件的系统来说是不够的。为了克服这一问题，本研究提出了一种预防性控制方案来确定 ESS 的 PFRP，该方案能够在使用基于多期情景的最优功率流 (OPF) 配方进行日前调度的同时，动态调整下垂率和死区宽度。利用中国可再生能源渗透率较高的实际省级电网的测试案例，验证了所提方法的有效性。数值结果表明，所提出的方法只需增加不到 3% 的运营成本，就能实现所需的扰动后频率性能。

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引用次数: 0

Robust wind power capacity planning under fuel price uncertainty using conic duality theory and piecewise McCormick relaxation 利用圆锥对偶理论和片断麦考密克松弛法，在燃料价格不确定的情况下进行稳健的风电容量规划

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

Electric Power Systems Research

Pub Date : 2024-10-04 DOI: 10.1016/j.epsr.2024.111127

Fawzy A. Bukhari , Khalid A. Alnowibet , Abdelatty E. Abdelgawad

Increasing the proportion of renewable energy sources (RESs) in power generation is crucial due to fossil fuel depletion and rising environmental pollution. In this regard, identifying the most lucrative sites and sizes for installing wind farms, as one of the fastest-growing types of RESs, is imperative. This paper presents a robust profit-oriented wind power capacity planning (WPCP) considering long- and short-term uncertainty. The model forms a two-stage min-max-min hierarchical structure. The first stage minimizes the investment cost plus maximum regret, while the second stage maximizes the profit under the worst-case uncertainty realization. Unlike the existing approaches where uncertainty in fossil fuel prices is neglected, we model fuel price uncertainty using both polyhedral and ellipsoidal uncertainty sets. In this respect, the third level is formulated as a bi-level program, with the upper level being the profit maximization and the lower level being the locational marginal price (LMP) calculation. In the case of the ellipsoidal set, the conic duality theory is employed to dualize the lower level. The piecewise McCormick relaxation (PMR) technique linearizes the bilinear terms. The nested column-and-constraint generation (NCCG) technique solves the formulated problem. A clarifying case study is employed to demonstrate the efficacy of the proposed model.

由于化石燃料枯竭和环境污染加剧，提高可再生能源（RES）在发电中的比例至关重要。在这方面，风力发电场是增长最快的可再生能源之一，确定安装风力发电场最有利可图的地点和规模势在必行。本文提出了一种考虑到长期和短期不确定性的稳健的以利润为导向的风电容量规划（WPCP）。该模型采用两阶段最小-最大-最小的分层结构。第一阶段最小化投资成本和最大遗憾，第二阶段最大化最坏情况下不确定性实现的利润。与忽略化石燃料价格不确定性的现有方法不同，我们使用多面体和椭圆体不确定性集来模拟燃料价格的不确定性。在这方面，第三层被表述为一个双层程序，上层是利润最大化，下层是本地边际价格（LMP）计算。在椭圆集的情况下，采用圆锥对偶理论对下层进行对偶。片式麦考密克松弛（PMR）技术使双线性项线性化。嵌套列约束生成（NCCG）技术解决了所提出的问题。为了证明所提模型的有效性，我们采用了一个说明性案例研究。

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引用次数: 0

Optimized wide area backup for distance relay tele-protection with security adjustment 优化的广域备份，用于远距离中继远程保护，可进行安全调整

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

Electric Power Systems Research

Pub Date : 2024-10-04 DOI: 10.1016/j.epsr.2024.111111

Seyed Ali Esmaeilzadeh Mousavi , Reza Mohammadi Chabanloo , Hossein Askarian Abyaneh , Hatem H․ Zeineldin

Tele-protection schemes efficiently clear faults at line ends, but failures in the telecommunication link or relay malfunction can cause delayed fault clearance, network instability and significant power loss. Hence, this paper presents a reliable protection method as a backup for tele-protection schemes which is designed based on nearby distance relays zone pickup. The proposed protective method introduces a novel ability to adjust sensitivity to fault events through a security factor index. This method can adapt to network uncertainties or changes in topology, using one-step calculation of optimal values based on the least square error method and provides the fast adaptation to network changes. In addition, it enables the fault detection even if a relay fails at one of the faulted line terminals. Performance evaluation of the proposed method has been done based on the reliability indices through a wide simulation of fault scenarios on the IEEE 9-bus system. Considering the possible uncertainties, the test results have shown that the proposed method is more efficient with 98.5 % dependability compared to the conventional tele-protection schemes. While this index is evaluated at 90 % and 92.5 % in the PUTT and POTT schemes, respectively.

远动保护方案能有效清除线路末端的故障，但电信链路故障或继电器故障会导致故障清除延迟、网络不稳定和重大电力损失。因此，本文提出了一种可靠的保护方法，作为远动保护方案的后备方案。所提出的保护方法引入了一种新的能力，即通过安全系数指数来调整对故障事件的敏感性。这种方法可以适应网络的不确定性或拓扑结构的变化，使用基于最小平方误差法的一步计算最佳值，并提供对网络变化的快速适应。此外，即使故障线路终端的继电器发生故障，它也能进行故障检测。通过对 IEEE 9 总线系统故障情况的广泛模拟，根据可靠性指数对所提方法进行了性能评估。考虑到可能存在的不确定性，测试结果表明，与传统的远程保护方案相比，建议的方法更有效，可靠性达到 98.5%。而 PUTT 和 POTT 方案的这一指数分别为 90% 和 92.5%。

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引用次数: 0

Anomaly detection of photovoltaic power generation based on quantile regression recurrent neural network 基于量子回归递归神经网络的光伏发电异常检测

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

Electric Power Systems Research

Pub Date : 2024-10-04 DOI: 10.1016/j.epsr.2024.111132

Chengcheng Yi , Yu Peng , Sheng Su , Bin Li , Xiaoqian Wang , Wenqing Zhou , Xin Guo , Hongming Yang , Wenchuan Meng

Distributed photovoltaic (PV) power generation systems are widely spread. Moreover, due to the randomness of meteorological conditions and the complexity of installation environments, it is difficult to eliminate the interference of factors such as meteorological fluctuations in the monitoring of abnormal states of PV equipment. Based on this, this paper proposes a PV power generation anomaly detection method based on Quantile Regression Recurrent Neural Network (QRRNN). First, the characteristics of solar irradiance on clear days are analyzed, and the clear day masking method is used to eliminate the interference of cloudy and rainy weather. Then, the output correlation of different power stations is analyzed to obtain PV stations with high output correlation as the horizontal reference, which is used to exclude interferences such as permanent faults at the power stations. At the same time, vertical comparison of the output curves of the station under test on different clear days is conducted to eliminate interference factors such as weather and environmental conditions. Subsequently, the metered active power output data, which is free from interference, is input into the QRRNN model to obtain the normal active power output range of the PV. The power threshold of the normal output range is utilized to identify anomalies in PV power generation. Finally, simulation analysis of actual PV system data is conducted, and the results show that the method can effectively identify PV power generation anomalies and has high accuracy in PV fault detection.

分布式光伏（PV）发电系统广泛普及。此外，由于气象条件的随机性和安装环境的复杂性，光伏设备异常状态监测难以排除气象波动等因素的干扰。基于此，本文提出了一种基于量回归递归神经网络（QRRNN）的光伏发电异常检测方法。首先，分析晴天的太阳辐照度特征，并采用晴天遮蔽法排除阴雨天气的干扰。然后，分析不同电站的输出相关性，获得输出相关性高的光伏电站作为横向参考，用于排除电站永久故障等干扰。同时，对被测电站在不同晴天的输出曲线进行纵向比较，以排除天气和环境条件等干扰因素。随后，将不受干扰的有功功率输出计量数据输入 QRRNN 模型，得出光伏正常有功功率输出范围。利用正常输出范围的功率阈值来识别光伏发电的异常情况。最后，对实际光伏系统数据进行了仿真分析，结果表明该方法能有效识别光伏发电异常，在光伏故障检测中具有较高的准确性。

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引用次数: 0

Scheduling and assessment of multi-area virtual power plant including flexible resources using swarm intelligence technique 利用蜂群智能技术对包括灵活资源在内的多区域虚拟发电厂进行调度和评估

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

Electric Power Systems Research

Pub Date : 2024-10-04 DOI: 10.1016/j.epsr.2024.111139

Anubhav Kumar Pandey, Vinay Kumar Jadoun, Jayalakshmi Narayana Sabhahit

A virtual power plant (VPP) makes the distributed energy resources (DERs) visible to support grid services, promoting clean energy use by offering an alternative to reduce reliance on conventional sources. This paper proposes optimized operation and scheduling of VPP by forming a group of flexible resources that includes renewables i.e., solar, wind power, fuel cell, and co-generation units along with storage facilities to form a holistic network in a multi-area interconnected system framework. Initially, the scheduling is performed for a single area system in which a comparison is made with the available work relevant to the proposed formulation. In addition, the scheduling is further extended to the proposed multi-area based virtual power plant (MAVPP) performed on a day-ahead (DA) basis and the target objective(s) i.e., net profit and emission are optimized. Furthermore, a recently developed marine predator optimization algorithm (MPOA) is employed to solve the proposed problem formulation and the results are compared and discussed extensively with conventional techniques. Also, the analysis pertaining to MAVPP is carried out which is beneficial in terms of economic and environmental perspective. The result reveals that the maximum value of net profit for MAVPP is converging to an optimum value of 59,351.88 $ followed by the attained value of minimum emission of 51,700.73 Kg by consuming an elapsed time of 92.96 and 104.76 s., respectively in 200 iterations. The outcomes are promising and upon comparison with the available literature work, the superiority of the selected technique is evident in terms of computational time, improvement of net profit and reduction in emission followed by the ease of convergence behaviour in fewer iterations.

虚拟发电厂（VPP）使分布式能源资源（DERs）显性化，以支持电网服务，通过提供替代能源来减少对传统能源的依赖，从而促进清洁能源的使用。本文提出了虚拟发电厂的优化运行和调度方法，即在多区域互联系统框架内，将可再生能源（即太阳能、风能、燃料电池和热电联产机组）与储能设施组成一组灵活的资源，形成一个整体网络。起初，调度是针对单个区域系统进行的，在此过程中，我们对与拟议方案相关的现有工作进行了比较。此外，调度还进一步扩展到基于提前日（DA）的拟议多区域虚拟发电厂（MAVPP），并对目标（即净利润和排放）进行了优化。此外，还采用了最近开发的海洋捕食者优化算法（MPOA）来解决提出的问题，并将结果与传统技术进行了广泛的比较和讨论。此外，还对 MAVPP 进行了分析，从经济和环境角度来看，MAVPP 都是有益的。结果表明，MAVPP 的最大净利润值趋近于最佳值 59,351.88 美元，随后在 200 次迭代中分别耗时 92.96 秒和 104.76 秒，达到最小排放值 51,700.73 公斤。结果很有希望，与现有文献相比，所选技术在计算时间、提高净利润和减少排放量方面优势明显，而且迭代次数更少，更容易收敛。

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引用次数: 0

Ampacity derating factors for submarine transmission cables in J-tubes J 型管海底输电电缆的载流量降额系数

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

Electric Power Systems Research

Pub Date : 2024-10-04 DOI: 10.1016/j.epsr.2024.111118

Zhiye Du , Gen Li , Guohua Yue , Chao Peng , Yu Zhan , Yongqing Deng

With the development of deep-sea wind power, the temperature hotspots of submarine cables in J-tubes are getting increasing attention. Currently, the relevant standards do not provide a thermal rating method for such cable sections, and the only studies are difficult to apply in practice. This study derived an analytical solution for calculating the derating in ampacity of submarine cables within J-tubes. The proposed approach is efficient and readily integrated with IEC-related standards. Initially, an indoor experiment was conducted to validate the correctness of the analytical model. Subsequently, a numerical example utilizing an actual HVDC submarine cable is presented, demonstrating increased cable conductor temperature within the J-tube and a corresponding reduction in ampacity. A derating factor is employed to quantify the extent of ampacity reduction, which is a function of the J-tube length, outer diameter, ambient temperature, wind speed, and solar radiation intensity. It turns out that once the J-tube air section's length exceeds approximately 60 times the cable outer diameter, the transmission circuit ampacity can be based on the value installed in the infinite J-tube. Furthermore, factors resulting in substantial cable ampacity reduction, such as high solar radiation intensity, may yield a derating factor approaching 0.6.

随着深海风电的发展，J 型管海底电缆的温度热点问题日益受到关注。目前，相关标准并未提供此类电缆截面的热额定值方法，仅有的研究也难以应用于实际。本研究为计算 J 型管内海底电缆的安培力降额得出了一种分析解决方案。所提出的方法不仅高效，而且易于与 IEC 相关标准相结合。首先，进行了一次室内实验来验证分析模型的正确性。随后，介绍了一个利用实际高压直流海底电缆的数值示例，该示例显示了 J 型管内电缆导体温度的升高和相应的载流量降低。采用降额系数来量化载流量降低的程度，该系数是 J 型管长度、外径、环境温度、风速和太阳辐射强度的函数。结果表明，一旦 J 型管空气部分的长度超过电缆外径的约 60 倍，输电回路的安培力就可以按照无限大 J 型管中安装的数值来计算。此外，导致电缆载流量大幅降低的因素（如高太阳辐射强度）可能会产生接近 0.6 的降额系数。

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引用次数: 0

An enhanced algorithm for detection of HIAF in active distribution networks and real-time analysis 主动配电网络中 HIAF 检测和实时分析的增强算法

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

Electric Power Systems Research

Pub Date : 2024-10-04 DOI: 10.1016/j.epsr.2024.111108

Fanidhar Dewangan, Monalisa Biswal

Identifying a downed conductor in distribution is challenging due to the insignificant variations in the current signal. Most of the distribution system faults are identified using overcurrent and earth fault protection. Fault path resistance decides the current magnitude while high resistance path may create timely issues in identifying a fault. Downed conductor and high resistance faults create arc in between the ground and conductor. Due to this the fault at the location is highly nonlinear with reduced magnitude. These faults are known as high impedance arcing fault (HIAF). Such faults can be identified effectively by conducting harmonic analysis of the signals. But in a modern distribution system apart from other renewable sources, the integration of electric vehicle (EV) may create HIAF detection challenges due to the inclusion of inverters and switching harmonics associated with EV. Considering the available advanced architecture of modern microgrid system, an effective solution is proposed in this work to securely detect HIAFs. The method is robust and highly reliable for HIAFs. The system stability and continuity can be unaffected with the help of the proposed method in case of various non-fault or transient/switching conditions. Comparison with other profound techniques is done to show the superiority of the proposed method.

由于电流信号的变化微乎其微，因此在配电系统中识别停电导线具有挑战性。大多数配电系统故障都是通过过流保护和接地故障保护来识别的。故障路径电阻决定了电流的大小，而高电阻路径可能会给及时识别故障带来问题。击穿导体和高电阻故障会在接地和导体之间产生电弧。因此，该位置的故障是高度非线性的，且量级减小。这些故障被称为高阻抗电弧故障（HIAF）。通过对信号进行谐波分析，可以有效识别此类故障。但在现代配电系统中，除其他可再生能源外，电动汽车（EV）的集成可能会带来高阻抗电弧故障检测方面的挑战，因为其中包含了逆变器和与电动汽车相关的开关谐波。考虑到现代微电网系统现有的先进架构，本研究提出了一种有效的解决方案来安全地检测 HIAF。该方法对 HIAFs 具有鲁棒性和高可靠性。在各种非故障或瞬态/开关条件下，系统的稳定性和连续性都不会受到拟议方法的影响。通过与其他先进技术的比较，可以看出所提方法的优越性。

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引用次数: 0

Hybrid quantum annealing decomposition framework for unit commitment 单位承诺的混合量子退火分解框架

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

Electric Power Systems Research

Pub Date : 2024-10-04 DOI: 10.1016/j.epsr.2024.111121

Jiajie Ling, Quan Zhang, Guangchao Geng, Quanyuan Jiang

Quantum computing is an emerging and promising technology that has overwhelming quantum advantages compared to its classical counterparts. Unit commitment (UC) is a critical issue in the power system, and it becomes more challenging with the integration of intermittent renewable energy. Therefore, this paper proposes an innovative decomposition and coordination optimization framework to accelerate the solution of UC, in which the interaction between an adiabatic quantum computer and a classical computer is designed to harness the immense computational power of quantum computers effectively. First, decomposition methods considering the requirements of quantum computers are introduced to decompose UC into small-scale models. Then, the paper presents a quadratic unconstrained binary optimization modeling method to transform UC problems into the form of quantum computing. Furthermore, due to the limitations of quantum computing resources, a reductive variable technique is proposed to reduce the number of slack variables in the optimization model and ensure that it remains feasible for quantum computers. Case studies conducted in test systems with a quantum annealing simulator and a real quantum annealing computer illustrate the feasibility and effectiveness of the method and demonstrate its potential in the era of quantum computing.

量子计算是一项新兴且前景广阔的技术，与经典计算相比，它具有压倒性的量子优势。机组承诺（UC）是电力系统中的一个关键问题，随着间歇性可再生能源的整合，它变得更具挑战性。因此，本文提出了一种创新的分解和协调优化框架来加速解决 UC，其中设计了绝热量子计算机和经典计算机之间的交互，以有效利用量子计算机的巨大计算能力。首先，介绍了考虑量子计算机需求的分解方法，将 UC 分解为小规模模型。然后，论文提出了一种二次无约束二元优化建模方法，将 UC 问题转化为量子计算的形式。此外，由于量子计算资源的限制，本文还提出了一种还原变量技术，以减少优化模型中的松弛变量数量，确保优化模型在量子计算机上仍然可行。利用量子退火模拟器和真实量子退火计算机在测试系统中进行的案例研究说明了该方法的可行性和有效性，并展示了其在量子计算时代的潜力。

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引用次数: 0

A long-term power system state calculation method using sequential power and holomorphic embedding 利用顺序功率和全态嵌入的长期电力系统状态计算方法

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

Electric Power Systems Research

Pub Date : 2024-10-03 DOI: 10.1016/j.epsr.2024.111125

Hongzhong Li , Yihao Huang , Fuxin Luo , Xiaolu Li , Luo Li

Traditional Power Flow (PF) calculations struggle to support the data analysis requirements as the power system develops. Therefore, this paper introduces a non-sequential and non-iterative PF calculation method to enhance the computational speed and analytical efficiency of power system state variables over long time scales. Firstly, a Power Sequential Division (PSD) method is proposed, representing the power curve using hierarchical energy with temporal characteristics. Next, based on the Fast and Flexible Holomorphic Embedding (FFHE) method, the paper explores the incremental properties of Voltage Power Series Coefficients (VPSC) and proposes an Incremental Holomorphic Embedding (IHE) method. Finally, by combining PSD and IHE, this study introduces a Power Sequential Flow (PSPF) method for rapid computation of power system state variables over long time scales. Unlike traditional PF methods, PSPF method shifts away from time-series calculations and instead analyzes the distribution of power system state variables over long time scales from an energy perspective. Various test cases are set up to analyze the performance characteristics of IHE and PSPF from multiple perspectives. The results indicate that the proposed methods significantly outperform traditional PF methods in terms of computational speed, adaptability to test cases, and analytical efficiency.

随着电力系统的发展，传统的功率流 (PF) 计算难以满足数据分析的要求。因此，本文介绍了一种非序列和非迭代的 PF 计算方法，以提高长时间尺度上电力系统状态变量的计算速度和分析效率。首先，本文提出了一种功率序列划分（PSD）方法，利用具有时间特性的分层能量来表示功率曲线。接着，基于快速灵活的全形态嵌入（FFHE）方法，本文探索了电压功率序列系数（VPSC）的增量特性，并提出了增量全形态嵌入（IHE）方法。最后，通过结合 PSD 和 IHE，本研究介绍了一种用于快速计算长时间尺度电力系统状态变量的功率序列流 (PSPF) 方法。与传统的 PF 方法不同，PSPF 方法不再进行时间序列计算，而是从能量角度分析电力系统状态变量在长时间尺度上的分布。为从多个角度分析 IHE 和 PSPF 的性能特点，我们设置了各种测试案例。结果表明，所提出的方法在计算速度、对测试案例的适应性和分析效率方面都明显优于传统的 PF 方法。

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引用次数: 0