Sustainable Energy Grids & Networks最新文献_第3页

A method for configuring hybrid electrolyzers based on joint wind and photovoltaic power generation modeling using copula functions 基于使用 copula 函数的风力和光伏联合发电建模的混合电解槽配置方法

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2024-10-16 DOI: 10.1016/j.segan.2024.101539

Yuan Liang , Haoyuan Ma , Zhonghao Liang , Hongqing Wang , Jianlin Li

Considering the specific wind and photovoltaic power characteristics of a certain region, this study investigates the optimal ratio of Alkaline Electrolysis Cells (AEL) to Proton Exchange Membrane (PEM) electrolyzers in a hybrid electrolysis system for hydrogen production. A flexible model for configuring the hybrid electrolysis system is proposed, based on a copula function for joint wind and solar power modeling. This model generates wind and photovoltaic power generation scenarios using the copula function, incorporating a selection mechanism to ensure that the output scenarios are more representative of the actual data characteristics of wind and photovoltaic power output. Consequently, considering both the fluctuation and amplitude, the wind and photovoltaic power data are decomposed using the Ensemble empirical mode decomposition method. The decomposed components are then allocated to the two types of electrolyzers. Furthermore, the optimal configuration of the hybrid electrolysis system is determined by minimizing the costs associated with wasted power, electricity purchases, and other expenses. Finally, a case study of a 100 MW wind farm and a 50 MW photovoltaic power station in Northwest China is presented, concluding that the optimal configuration ratio of AEL to PEM electrolyzers is 2:1. In a Matlab/Simulink platform, the performance metrics of the hybrid electrolysis system were validated. It was found that the hydrogen production rate of the hybrid electrolyzer is comparable to that of the PEM electrolyzer, but with a lower required cost. Additionally, the hydrogen production rate and volume of the optimal configuration for the hybrid electrolyzer determined by the model proposed in this paper are higher than those obtained through the optimization algorithm's optimal configuration.

考虑到某一地区特定的风能和光伏发电特性，本研究探讨了制氢混合电解系统中碱性电解槽（AEL）与质子交换膜（PEM）电解槽的最佳比例。基于风能和太阳能联合建模的 copula 函数，提出了一个用于配置混合电解系统的灵活模型。该模型利用 copula 函数生成风力和光伏发电情景，并结合了选择机制，以确保输出情景更能代表风力和光伏发电输出的实际数据特征。因此，考虑到波动性和振幅，使用集合经验模式分解法对风电和光伏发电数据进行分解。然后将分解后的组件分配给两种类型的电解槽。此外，混合电解系统的最佳配置是通过最大限度地降低与浪费电力、电力采购和其他费用相关的成本来确定的。最后，通过对中国西北地区一个 100 兆瓦风电场和一个 50 兆瓦光伏电站的案例研究，得出 AEL 与 PEM 电解槽的最佳配置比例为 2:1。在 Matlab/Simulink 平台上，对混合电解系统的性能指标进行了验证。结果发现，混合电解槽的制氢率与 PEM 电解槽相当，但所需成本更低。此外，本文提出的模型确定的混合电解槽最佳配置的制氢率和体积均高于优化算法最佳配置的制氢率和体积。

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引用次数: 0

A study of electricity sales offer strategies applicable to the participation of multi-energy generators in short- and medium-term markets 适用于多能源发电机参与中短期市场的售电报价战略研究

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2024-10-16 DOI: 10.1016/j.segan.2024.101553

Boyu Wang , Xiaofeng Xu , Genzhu Li , Hang Fan , Ning Qiao , Haidong Chen , Dunnan Liu , Tongtao Ma

Due to the increasing proportion of renewable energy, a multi-layered and multi-timescale energy market has emerged in many countries such as China. In the meanwhile, power generation companies must develop more intelligent and dynamic offer strategies to adapt to today's intricate energy trading. Because of the difficulty in describing the dynamic trading environment caused by the uncertainty of renewable energy, previous studies have not fully explored the offer strategy especially in both short-term and medium-term electricity markets. In response to this challenge, this research introduces a novel biding strategy framework leveraging a Asynchronous Advantage Actor-Critic (A3C) algorithm, which can effectively address the decision making in dynamic and uncertain energy markets. The framework focuses on intra-monthly transaction clearing mechanisms with the aim of optimally enhancing earnings. The research formulates an offer model both for thermal and renewable power generation enterprises, which is applicable to medium-term monthly and intra-monthly trading. The study then validates this framework through three distinct analyses: the returns of various bid methods under standard scenarios, the offer strategies return of power generation companies with diverse cost profiles, and the impact of varying renewable energy proportions. The multi-angle simulations confirm that the model presented in this paper offers a scientific basis for the development of offer strategies for power generation companies and enable power generating firms to effectively adopt to the current power market.

随着可再生能源比例的不断提高，中国等许多国家出现了多层次、多时段的能源市场。与此同时，发电企业必须制定更加智能和动态的报价策略，以适应当今错综复杂的能源交易。由于难以描述可再生能源的不确定性所导致的动态交易环境，以往的研究并没有充分探讨特别是短期和中期电力市场的报价策略。为了应对这一挑战，本研究利用异步优势行为批判者（A3C）算法引入了一个新颖的出价策略框架，该框架能有效解决动态和不确定能源市场中的决策问题。该框架重点关注月内交易清算机制，旨在优化提高收益。研究为火力发电企业和可再生能源发电企业制定了一个报价模型，该模型适用于中期月度交易和月内交易。研究随后通过三项不同的分析验证了这一框架：标准情景下各种投标方法的收益、不同成本状况下发电企业的报价策略收益以及不同可再生能源比例的影响。多角度模拟证实，本文提出的模型为发电公司制定报价策略提供了科学依据，使发电公司能够有效地适应当前的电力市场。

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引用次数: 0

Flexibility potential quantification of electric vehicle charging clusters 电动汽车充电集群的灵活性潜力量化

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2024-10-16 DOI: 10.1016/j.segan.2024.101547

Simone Striani, Tim Unterluggauer, Peter Bach Andersen, Mattia Marinelli

A significant obstacle to providing flexibility services with electric vehicles (EVs) is the uncertainty surrounding the profitability and flexibility potential of charging clusters when utilized as a flexible load. Currently, there is a lack of comprehensive and easily applicable methods for quantifying flexibility in the literature. This paper introduces an evaluation tool and a set of flexibility indexes to assess the capability of charging clusters to deliver flexibility services. The method is designed to evaluate and quantify the flexibility potential of charging clusters in terms of short-term and long-term power adjustments and charge scheduling. Through sensitivity analysis, we examine how connection capacity, EV battery capacities, power capabilities, and the number of daily charging sessions influence the flexibility potential of charging clusters. Our findings highlight a direct relationship between the grid connection capacity of clusters and their ability to perform short-term power adjustments. Moreover, while larger batteries tend to reduce energy and time flexibility, their increased storage capability facilitates managing and scheduling a larger energy volume. Furthermore, for the days analysed, the flexibility potential showed minimal sensitivity to the number of daily charging sessions. Instead, the amount of energy requested and connection patterns emerge as key determinants of overall flexibility. In summary, this research provides valuable insights that can inform the design, monitoring, and assessment of EV charging clusters when evaluating their suitability for various flexibility services.

利用电动汽车（EV）提供灵活性服务的一个重大障碍，是充电集群作为灵活负载使用时的盈利能力和灵活性潜力的不确定性。目前，文献中缺乏全面且易于应用的灵活性量化方法。本文介绍了一种评估工具和一套灵活性指数，用于评估充电集群提供灵活性服务的能力。该方法旨在评估和量化充电集群在短期和长期电力调整以及充电调度方面的灵活性潜力。通过敏感性分析，我们研究了连接容量、电动汽车电池容量、供电能力和每日充电次数对充电集群灵活性潜力的影响。我们的研究结果表明，集群的电网连接能力与其执行短期功率调整的能力之间存在直接关系。此外，虽然大型电池往往会降低能量和时间的灵活性，但其存储能力的提高有助于管理和调度更大的能量。此外，在所分析的日子里，灵活性潜力对每日充电次数的敏感性极低。相反，所需的能源量和连接模式成为整体灵活性的关键决定因素。总之，这项研究为电动汽车充电集群的设计、监控和评估提供了有价值的见解，有助于评估其是否适合各种灵活性服务。

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引用次数: 0

Comparative analysis of online voltage stability indices based on synchronized PMU measurements 基于同步 PMU 测量的在线电压稳定性指数比较分析

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2024-10-16 DOI: 10.1016/j.segan.2024.101544

Valéria Monteiro de Souza, Hugo Rodrigues de Brito, Kjetil Obstfelder Uhlen

The need for reliable real-time information on voltage stability margins of electrical power systems is an increasingly relevant concern within the current trend of electrification and deployment of power electronics-based devices. This paper conducts the assessment and comparison of four Voltage Stability Indices (VSIs) proposed for this application and based exclusively on synchronized phasor measurements. The robustness and accuracy of each method in identifying the point of maximum power transfer are evaluated as the correlation between load characteristics and consistent estimation of voltage stability margins is explored. In addition, the likelihood inherent to each VSI formulation of triggering false alarms under certain system dynamics is addressed in detail. The comparative analyses are derived from dynamic simulation data of a 3-bus test system, the IEEE 9-bus network and the IEEE 39-bus network, all modelled in the open-source Python-based power system simulator DynPSSimPy. Case studies cover placement of monitoring device, different load types, line disconnection events and presence of measurement noise. The results presented serve as a reference point for the development and/or enhancement of VSIs suitable for real-time applications, highlighting their most significant advantages and drawbacks and providing insights on potential trade-offs that need to be considered when employing such approaches within control centre settings.

在当前电气化和部署基于电力电子设备的趋势下，对电力系统电压稳定裕度可靠实时信息的需求日益增长。本文评估和比较了针对这一应用提出的四种电压稳定指数（VSI），它们完全基于同步相量测量。在评估每种方法在确定最大功率传输点时的稳健性和准确性的同时，还探讨了负荷特性与电压稳定裕度的一致估计之间的相关性。此外，还详细讨论了每种 VSI 方案在特定系统动态下触发误报的可能性。比较分析来自 3 总线测试系统、IEEE 9 总线网络和 IEEE 39 总线网络的动态模拟数据，所有数据均在基于 Python 的开源电力系统模拟器 DynPSSimPy 中建模。案例研究包括监控设备的放置、不同的负载类型、线路断开事件和测量噪声的存在。所提供的结果可作为开发和/或增强适合实时应用的 VSI 的参考点，突出了其最显著的优点和缺点，并为在控制中心环境中采用此类方法时需要考虑的潜在权衡问题提供了见解。

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引用次数: 0

Optimising green hydrogen injection into gas networks: Decarbonisation potential and influence on quality-of-service indexes 优化向天然气网络注入绿色氢气：脱碳潜力及对服务质量指数的影响

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2024-10-16 DOI: 10.1016/j.segan.2024.101543

João Fontoura, Filipe Joel Soares, Zenaida Mourão, António Coelho

This paper introduces a mathematical model designed to optimise the operation of natural gas distribution networks, considering the injection of hydrogen in multiple nodes. The model is designed to optimise the quantity of hydrogen injected to maintain pressure, gas flows, and gas quality indexes (Wobbe index (WI) and higher heating value (HHV)) within admissible limits. This study also presents the maximum injection allowable of hydrogen correlated with the gas quality index variation. The model has been applied to a case study of a gas network with four distinct scenarios and implemented using Python. The findings of the case study quantify the maximum permitted volume of hydrogen in the network, the total savings in natural gas, and the reduction in carbon dioxide emissions. Lastly, a sensitivity analysis of injected hydrogen as a function of the Wobbe index (WI) and Higher Heating Value (HHV) limits relaxation.

本文介绍了一个数学模型，旨在优化天然气输配网络的运行，其中考虑了在多个节点注入氢气的问题。该模型旨在优化氢气注入量，使压力、天然气流量和天然气质量指标（沃伯指数（WI）和高热值（HHV））保持在允许范围内。本研究还提出了与气体质量指数变化相关的最大允许氢气注入量。该模型应用于一个天然气网络的案例研究，包含四种不同的情况，并使用 Python 实现。案例研究的结果量化了网络中允许的最大氢气量、节省的天然气总量以及减少的二氧化碳排放量。最后，对注入氢气作为沃伯指数（WI）和高热值（HHV）限制松弛函数的敏感性进行了分析。

引用次数: 0

Optimal operation of multi-energy carriers considering energy hubs in unbalanced distribution networks under uncertainty 不确定性条件下不平衡配电网络中考虑能源枢纽的多能源载体优化运行

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2024-10-15 DOI: 10.1016/j.segan.2024.101538

Fernando García-Muñoz , Andrés Felipe Cortés-Borray

This article presents a two-stage stochastic programming model to address the dispatching scheduling problem in an energy hub, considering an unbalanced active low-voltage (LV) network. A three-phase version of the second-order cone relaxation of DistFlow AC optimal power flow (AC-OPF) is employed to incorporate unbalanced network constraints, while the objective minimizes the Local Energy Community (LEC) operational cost. The model results have been validated using OpenDSS, encompassing energy losses, voltage levels, and active/reactive power. Likewise, a comparative analysis between the three-phase model and the traditional single-phase model, using a modified version of the IEEE European LV Test Feeder as a case study, reveals interesting differences, such that the single-phase model underestimates voltage limits during photovoltaic (PV) system operation and overestimates energy purchased from the main grid, compared with the three-phase model. Similarly, the comparison results reveal that discrepancies between the single and three-phase models intensify as the power injected from PV systems rises. This notably impacts the total energy purchased from the grid, battery operation, and the satisfaction of thermal consumption through electricity. Finally, while the three-phase model offers valuable insights into security levels for voltage and grid energy purchase, its longer computational time makes it more suitable for strategic use rather than daily operational frameworks.

本文提出了一种两阶段随机编程模型，用于解决能源枢纽中的调度调度问题，该模型考虑了不平衡的有源低压（LV）网络。该模型采用了 DistFlow 交流最优功率流 (AC-OPF) 二阶圆锥松弛的三阶段版本，以纳入不平衡网络约束，同时目标最小化本地能源社区 (LEC) 运营成本。模型结果已通过 OpenDSS 验证，包括能量损失、电压水平和有功/无功功率。同样，以修改版的 IEEE 欧洲低压试验馈线为案例，对三相模型和传统单相模型进行了比较分析，发现了有趣的差异，例如，与三相模型相比，单相模型低估了光伏（PV）系统运行期间的电压限制，并高估了从主电网购买的能源。同样，比较结果表明，随着光伏系统注入功率的增加，单相和三相模型之间的差异也会加剧。这明显影响了从电网购买的总能量、电池运行以及通过电力满足热能消耗。最后，虽然三相模型为电压和电网能源购买的安全等级提供了有价值的见解，但其较长的计算时间使其更适用于战略用途，而非日常运行框架。

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引用次数: 0

Optimal design model for a public-private Renewable Energy Community in a small Italian municipality 意大利小城市公私可再生能源社区的优化设计模型

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2024-10-15 DOI: 10.1016/j.segan.2024.101545

Bruno Laurini , Barbara Bonvini , Stefano Bracco

Energy communities (ECs) are currently seen as an important pathway to increase the participation of citizens in the energy transition. The present work proposes a mixed integer linear programming (MILP) optimization model that provides the optimal design of a renewable energy community (REC) in terms of best technologies and chosen members. Different objective functions are investigated so that the REC’s design can be studied from different perspectives. The first objective is related to the minimization of total annualized costs (TAC) while the second one regards the maximization of the shared energy. The model considers one year as time horizon with a timestep of one hour. A case study is defined by considering the municipality of Plodio, located in the northwest of Italy, as the host of a potential REC. A total of 11 possible users are introduced, including municipality and residential users. In cost-optimized scenarios, the REC design is characterized by fewer users but has the maximum installation of PV modules. However, most of the revenues are obtained due to the selling of electricity and not due to its sharing. When the shared energy is maximized, all the candidate members are chosen and technologies such as wind turbines and batteries are exploited to increase the number of periods characterized by the injection of electricity into the grid. It is also noted that higher electricity prices increase the profitability of the investment. Finally, it is shown that the inclusion of an industrial user positively influences energy-sharing indicators.

能源社区（EC）目前被视为提高公民参与能源转型的重要途径。本研究提出了一个混合整数线性规划（MILP）优化模型，从最佳技术和所选成员的角度对可再生能源社区（REC）进行优化设计。研究了不同的目标函数，以便从不同角度研究可再生能源社区的设计。第一个目标与总年化成本（TAC）最小化有关，第二个目标则与共享能源最大化有关。该模型的时间跨度为一年，时间步长为一小时。案例研究将位于意大利西北部的普洛迪奥市作为潜在 REC 的所在地。共引入了 11 个可能的用户，包括市政用户和居民用户。在成本优化方案中，REC 设计的特点是用户较少，但光伏组件安装量最大。然而，大部分收入是通过出售电力获得的，而不是通过分享电力获得的。当共享能源最大化时，选择所有候选成员，并利用风力涡轮机和电池等技术，增加向电网注入电力的时段。此外，我们还注意到，较高的电价会提高投资的盈利能力。最后，研究表明，工业用户的加入会对能源共享指标产生积极影响。

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引用次数: 0

Acquiring better load estimates by combining anomaly and change point detection in power grid time-series measurements 结合电网时间序列测量中的异常点和变化点检测，获取更好的负荷估计值

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2024-10-15 DOI: 10.1016/j.segan.2024.101540

Roel Bouman , Linda Schmeitz , Luco Buise , Jacco Heres , Yuliya Shapovalova , Tom Heskes

In this paper we present novel methodology for automatic anomaly and switch event filtering to improve load estimation in power grid systems. By leveraging unsupervised methods with supervised optimization, our approach prioritizes interpretability while ensuring robust and generalizable performance on unseen data. Through experimentation, a combination of binary segmentation for change point detection and statistical process control for anomaly detection emerges as the most effective strategy, specifically when ensembled in a novel sequential manner. Results indicate the clear wasted potential when filtering is not applied. The automatic load estimation is also fairly accurate, with approximately 90% of estimates falling within a 10% error margin, with only a single significant failure in both the minimum and maximum load estimates across 60 measurements in the test set. Our methodology’s interpretability makes it particularly suitable for critical infrastructure planning, thereby enhancing decision-making processes.

在本文中，我们提出了自动过滤异常和开关事件的新方法，以改进电网系统中的负荷估算。通过利用无监督方法和有监督优化，我们的方法优先考虑了可解释性，同时确保了在未见数据上的稳健性和通用性。通过实验，二进制分割法检测变化点和统计过程控制法检测异常点的组合成为最有效的策略，特别是以新颖的顺序方式进行组合时。结果表明，如果不使用过滤功能，显然会浪费潜力。自动负载估计也相当准确，约 90% 的估计值误差在 10% 以内，在测试集中的 60 次测量中，只有一次在最小和最大负载估计中出现重大失误。我们的方法具有可解释性，因此特别适用于关键基础设施规划，从而加强决策过程。

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引用次数: 0

Distributed photovoltaic power forecasting based on personalized federated adversarial learning 基于个性化联合对抗学习的分布式光伏发电功率预测

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2024-10-14 DOI: 10.1016/j.segan.2024.101537

Fangming Deng, Jinbo Wang, Lei Wu, Bo Gao, Baoquan Wei, Zewen Li

Existing distributed photovoltaic (PV) power forecasting methods fail to address the impact of sample scarcity and heterogeneity in PV power data. Moreover, training a single prediction model proves challenging to meet the personalized forecasting needs of different PV stations in distributed environments. This paper proposes a personalized federated generative adversarial network (PFedGAN)-based DPV power forecasting method. Leveraging the federated learning (FL) framework, it achieves collaborative training of prediction models among DPV stations while preserving data privacy. y introducing generative adversarial networks (GAN) and personalized strategy optimization into the FL training process, it alleviates data scarcity issues and reduces the impact of data heterogeneity. A TimesNet-DeepAR (TNE-DeepAR) power prediction model is designed, where the TimesNet module extracts correlations between PV power data from different time periods, and the DeepAR module facilitates PV power prediction, mitigating the effects of meteorological factors' multi-periodic variations on PV power. Experimental results show that the proposed hybrid prediction model reduces the average mean absolute percentage error (MAPE) by 30–40 % compared to single models. The proposed approach reduces the MAPE by 9.79 % compared to traditional methods and by 49.62 % for PV stations with scarce data.

现有的分布式光伏（PV）功率预测方法未能解决光伏功率数据中样本稀缺性和异质性的影响。此外，要满足分布式环境中不同光伏电站的个性化预测需求，训练单一预测模型具有挑战性。本文提出了一种基于联合生成对抗网络（PFedGAN）的个性化 DPV 功率预测方法。它利用联合学习（FL）框架，在保护数据隐私的同时，实现了 DPV 站之间预测模型的协同训练。在 FL 训练过程中引入生成对抗网络（GAN）和个性化策略优化，缓解了数据稀缺问题，降低了数据异质性的影响。设计了 TimesNet-DeepAR（TNE-DeepAR）功率预测模型，其中 TimesNet 模块提取了不同时间段光伏功率数据之间的相关性，DeepAR 模块促进了光伏功率预测，减轻了气象因素多周期变化对光伏功率的影响。实验结果表明，与单一模型相比，所提出的混合预测模型可将平均绝对百分比误差 (MAPE) 降低 30-40%。与传统方法相比，所提出的方法可将 MAPE 降低 9.79%，对于数据稀缺的光伏电站，可将 MAPE 降低 49.62%。

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引用次数: 0

Operational reliability and non-deterministic resilience estimation of active distribution network incorporating effect of real-time dynamic hosting capacity 包含实时动态托管能力影响的主动配电网运行可靠性和非确定弹性估计

IF 4.8 2区工程技术 Q2 ENERGY & FUELS

Sustainable Energy Grids & Networks

Pub Date : 2024-10-11 DOI: 10.1016/j.segan.2024.101541

Sourav Kumar Sahu , Sonal , Debomita Ghosh , Dusmanta Kumar Mohanta , Soham Dutta

Active distribution networks are increasingly recognized essential for achieving sustainable development goals. Traditionally, hosting capacity was considered as a static measure for planning distributed energy resources integration. This work introduces the concept of dynamic hosting capacity, which recurrently re-evaluates hosting capacity in response to erratic modern grid conditions. The introduction of dynamic hosting capacity facilitated testing variations of power injection from minimum to 100 %, sustaining power system governing parameter limits. This embarked the need of operational reliability assessment and enhancing situational awareness for optimum power injection and balance. To achieve operational reliability analysis based on dynamic hosting capacity, hybrid probability distribution function-based Monte Carlo simulation is proposed. This resulted in 85–90 %. improvisation of solar photovoltaic generation and load alignment, as this methodology provides comprehensive and accurate assessment of system performance under diverse uncertainties. The framework's validation includes projection of time-varying operational reliability indices, over time independent reliability indices i.e., dynamic loss of load probability, dynamic loss of load expectation, dynamic loss of load duration, dynamic loss of load frequency, dynamic grid margin, and dynamic grid dependency. This resulted in 30 % improvement in assessment of grid margin, facilitating reliable uncertainty handling competence. Additionally, expectation maximization algorithm is proposed to evaluate non-deterministic resilience due to ambiguities associated with solar photovoltaic distributed energy resources. The non-deterministic resilience assessment testified 80 % bounce-back rate, demonstrating better adaptability and robustness. The entire analysis is conducted in MATLAB, validated using Typhoon Hardware-in-Loop real-time platform, and compared with existing literatures to demonstrate its effectiveness.

人们日益认识到，主动配电网络对实现可持续发展目标至关重要。传统上，托管容量被认为是规划分布式能源资源整合的静态措施。这项工作引入了动态寄存容量的概念，即根据不稳定的现代电网条件，反复重新评估寄存容量。动态托管容量的引入有助于测试从最小到 100 % 的功率注入变化，维持电力系统的管理参数限制。这就需要对运行可靠性进行评估，并提高态势感知能力，以实现最佳的功率注入和平衡。为实现基于动态托管能力的运行可靠性分析，提出了基于概率分布函数的混合蒙特卡罗模拟。由于该方法可在各种不确定因素下对系统性能进行全面、准确的评估，因此太阳能光伏发电和负载调整的改善率达到 85-90%。该框架的验证包括预测随时间变化的运行可靠性指数，以及与时间无关的可靠性指数，即动态负载损失概率、动态负载损失预期、动态负载损失持续时间、动态负载损失频率、动态电网裕度和动态电网依赖性。这使得电网裕度的评估结果提高了 30%，促进了可靠的不确定性处理能力。此外，由于太阳能光伏分布式能源资源的不确定性，还提出了期望最大化算法来评估非确定弹性。非确定性弹性评估测试了 80% 的反弹率，显示了更好的适应性和鲁棒性。整个分析在 MATLAB 中进行，使用台风硬件在环实时平台进行了验证，并与现有文献进行了比较，以证明其有效性。

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引用次数: 0