Journal of Modern Power Systems and Clean Energy最新文献_第4页

Probabilistic Small-Signal Stability Assessment and Cooperative Control for Interconnected Microgrids via Back-to-Back Converters

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-09-19 DOI: 10.35833/MPCE.2024.000449

Yuhong Wang;Xinyao Wang;Jianquan Liao;Miaohong Su;Yongyue Liu

{"title":"Probabilistic Small-Signal Stability Assessment and Cooperative Control for Interconnected Microgrids via Back-to-Back Converters","authors":"Yuhong Wang;Xinyao Wang;Jianquan Liao;Miaohong Su;Yongyue Liu","doi":"10.35833/MPCE.2024.000449","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000449","url":null,"abstract":"The flexible interconnection of microgrids (MGs) adopting back-to-back converters (BTBCs) has emerged as a new development trend in the field of MGs. This approach enables larger-scale integration and higher utilization of distributed renewable energy sources (RESs). However, their stability characteristics are very different from single MG due to the control characteristics of flexible interconnection. Meanwhile, the uncertainty and stochastic dependence structures of RESs and loads create challenges for stability analysis and cooperative control. In this paper, a probabilistic small-signal stability assessment and cooperative control framework is proposed for interconnected MGs via BTBCs. First, a cooperative control architecture for MGs is constructed. Then, a small-signal model of interconnected MGs via BTBCs containing primary control and secondary control is developed. This model facilitates the analysis of the impacts of BTBCs and various control strategies on the system stability. Subsequently, Copula functions and polynomial chaos expansion (PCE) are combined to achieve the probabilistic small-signal stability assessment. On this basis, the parameters of the cooperative control are optimized, enhancing the robustness of interconnected MGs via BTBCs. Finally, a case of interconnected MGs via BTBCs are built in MATLAB/ Simulink to verify the accuracy and effectiveness of the proposed framework.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"552-563"},"PeriodicalIF":5.7,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684502","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Mix-Integer Programming Based Deep Reinforcement Learning Framework for Optimal Dispatch of Energy Storage System in Distribution Networks

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-09-19 DOI: 10.35833/MPCE.2024.000391

Shengren Hou;Edgar Mauricio Salazar;Peter Palensky;Qixin Chen;Pedro P. Vergara

{"title":"A Mix-Integer Programming Based Deep Reinforcement Learning Framework for Optimal Dispatch of Energy Storage System in Distribution Networks","authors":"Shengren Hou;Edgar Mauricio Salazar;Peter Palensky;Qixin Chen;Pedro P. Vergara","doi":"10.35833/MPCE.2024.000391","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000391","url":null,"abstract":"The optimal dispatch of energy storage systems (ESSs) in distribution networks poses significant challenges, primarily due to uncertainties of dynamic pricing, fluctuating demand, and the variability inherent in renewable energy sources. By exploiting the generalization capabilities of deep neural networks (DNNs), the deep reinforcement learning (DRL) algorithms can learn good-quality control models that adapt to the stochastic nature of distribution networks. Nevertheless, the practical deployment of DRL algorithms is often hampered by their limited capacity for satisfying operational constraints in real time, which is a crucial requirement for ensuring the reliability and feasibility of control actions during online operations. This paper introduces an innovative framework, named mixed-integer programming based deep reinforcement learning (MIP-DRL), to overcome these limitations. The proposed MIP-DRL framework can rigorously enforce operational constraints for the optimal dispatch of ESSs during the online execution. This framework involves training a <tex>${Q}$</tex>-function with DNNs, which is subsequently represented in a mixed-integer programming (MIP) formulation. This unique combination allows for the seamless integration of operational constraints into the decision-making process. The effectiveness of the proposed MIP-DRL framework is validated through numerical simulations, demonstrating its superior capability to enforce all operational constraints and achieve high-quality dispatch decisions and showing its advantage over existing DRL algorithms.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"597-608"},"PeriodicalIF":5.7,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684496","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Voltage Sag Monitor Placement for Fault Location Detection Based on Precise Determination of Areas of Vulnerability 基于精确确定易受影响区域的故障定位检测电压波动监测器安置方法

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-09-13 DOI: 10.35833/MPCE.2023.001022

Mojtaba Hajiahmadi;Rahmat-Allah Hooshmand;Arash Kiyoumarsi

{"title":"Voltage Sag Monitor Placement for Fault Location Detection Based on Precise Determination of Areas of Vulnerability","authors":"Mojtaba Hajiahmadi;Rahmat-Allah Hooshmand;Arash Kiyoumarsi","doi":"10.35833/MPCE.2023.001022","DOIUrl":"https://doi.org/10.35833/MPCE.2023.001022","url":null,"abstract":"The increase in the number of sensitive loads in power systems has made power quality, particularly voltage sag, a prominent problem due to its effects on consumers from both the utility and customer perspectives. Thus, to evaluate the effects of voltage sag caused by short circuits, it is necessary to determine the areas of vulnerability (AOVs). In this paper, a new method is proposed for the AOV determination that is applicable to large-scale networks. The false position method (FPM) is proposed for the precise calculation of the critical points of the system lines. Furthermore, a new method is proposed for the voltage sag monitor (VSM) placement to detect the fault locations. A systematic placement scheme is used to provide the highest fault location detection (FLD) index at buses and lines for various short-circuit fault types. To assess the efficiency of the proposed methods for AOV determination and VSM placement, simulations are conducted in IEEE standard systems. The results demonstrate the accuracy of the proposed method for AOV determination. In addition, through VSM placement, the fault locations at buses and lines are detected.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 1","pages":"228-240"},"PeriodicalIF":5.7,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10680315","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143184064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Clearing Mechanism with Reduced Computational Complexity for Spot Flexibility Markets

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-09-13 DOI: 10.35833/MPCE.2024.000264

Sameer Sabir;Sousso Kelouwani;Nilson Henao;David Toquica;Michaël Fournier;Kodjo Agbossou;Juan C. Oviedo

{"title":"A Clearing Mechanism with Reduced Computational Complexity for Spot Flexibility Markets","authors":"Sameer Sabir;Sousso Kelouwani;Nilson Henao;David Toquica;Michaël Fournier;Kodjo Agbossou;Juan C. Oviedo","doi":"10.35833/MPCE.2024.000264","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000264","url":null,"abstract":"The spot flexibility markets are before the real-time energy exchange, allowing demand-side management to reduce energy consumption during peak periods. In these markets, demand aggregators must quickly choose the customers' reduction bids that fulfill grid requirements. This clearing procedure is challenging due to the computational complexity of selecting the optimal bids. Therefore, developing a clearing mechanism that avoids searching the entire flexibility bid space while respecting grid constraints is essential for the smooth operation of the spot flexibility market. This paper presents a clearing mechanism with reduced computational complexity of the winner determination problem in spot flexibility market for demand aggregators carrying out reductions in energy consumption. The proposed approach transforms customers' flexibility bids into a reward-based function. Afterward, the gradient-based optimization solves the bid selection problem. This approach helps demand aggregators achieve satisfactory energy reductions within an appropriate delay for spot flexibility markets. A comparative study presents the effectiveness of the proposed approach against commonly used approaches: hybrid particle swarm optimization genetic algorithm and combinatorial search.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"650-662"},"PeriodicalIF":5.7,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10680316","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Resonance Assessment of Large-scale Wind Park Connected to Primary Distribution Network

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-09-02 DOI: 10.35833/MPCE.2024.000127

Andrés Argüello;Ricardo Torquato;Walmir Freitas

{"title":"Resonance Assessment of Large-scale Wind Park Connected to Primary Distribution Network","authors":"Andrés Argüello;Ricardo Torquato;Walmir Freitas","doi":"10.35833/MPCE.2024.000127","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000127","url":null,"abstract":"On-shore wind parks are typically connected to the high-voltage (HV) transmission system through a bulk transformer. However, wind generators may be connected directly at a medium-voltage (MV) level, such as a utility-owned primary distribution network, if the network is capable of sustaining the power flow and ensuring adequate power quality for its users. This paper presents the findings of a comprehensive study on the management of resonance in a utility-owned wind park in Costa Rica. The wind park is connected directly to the MV primary distribution network and has no shunt capacitor for power factor correction. The results demonstrate that such configuration has a higher immunity to resonances, as the total grid equivalent impedance perceived by the wind park is typically dominated by the absent HV/MV transformer and shunt capacitor bank. Moreover, the capacitance provided by the underground feeders of the wind park did not result in natural oscillation frequencies in the range of typical harmonic distortions observed in MV distribution networks that violated power quality standards.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 1","pages":"289-299"},"PeriodicalIF":5.7,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10663528","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

3D Data Scattergram Image Classification Based Protection for Transmission Line Connecting BESS Using Depth-Wise Separable Convolution Based CNN

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-09-02 DOI: 10.35833/MPCE.2023.001008

Yingyu Liang;Yi Ren;Xiaoyang Yang;Wenting Zha

{"title":"3D Data Scattergram Image Classification Based Protection for Transmission Line Connecting BESS Using Depth-Wise Separable Convolution Based CNN","authors":"Yingyu Liang;Yi Ren;Xiaoyang Yang;Wenting Zha","doi":"10.35833/MPCE.2023.001008","DOIUrl":"https://doi.org/10.35833/MPCE.2023.001008","url":null,"abstract":"The distinctive fault characteristics of battery energy storage stations (BESSs) significantly affect the reliability of conventional protection methods for transmission lines. In this paper, the three-dimensional (3D) data scattergrams are constructed using current data from both sides of the transmission line and their sum. Following a comprehensive analysis of the varying characteristics of 3D data scattergrams under different conditions, a 3D data scattergram image classification based protection method is developed. The depth-wise separable convolution is used to ensure a lightweight convolutional neural network (CNN) structure without compromising performance. In addition, a Bayesian hyperparameter optimization algorithm is used to achieve a hyperparametric search to simplify the training process. Compared with artificial neural networks and CNNs, the depth-wise separable convolution based CNN (DPCNN) achieves a higher recognition accuracy. The 3D data scattergram image classification based protection method using DPCNN can accurately separate internal faults from other disturbances and identify fault phases under different operating states and fault conditions. The proposed protection method also shows first-class tolerability against current transformer (CT) saturation and CT measurement errors.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"609-621"},"PeriodicalIF":5.7,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10663529","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Self-Organizing Energy Management Modeling for Multi-Microgrids in Contingencies

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-08-26 DOI: 10.35833/MPCE.2024.000007

Jiachen Chen;Zhong Chen;Qiang Xing

{"title":"Self-Organizing Energy Management Modeling for Multi-Microgrids in Contingencies","authors":"Jiachen Chen;Zhong Chen;Qiang Xing","doi":"10.35833/MPCE.2024.000007","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000007","url":null,"abstract":"Contingencies, such as behavior shifts of microgrid operators (MGOs) and abrupt weather fluctuations, significantly impact the economic operations of multi-microgrids (MMGs). To address these contingencies and enhance the economic and autonomous performance of MGOs, a self-organizing energy management modeling approach is proposed. A second-order stochastic dynamical equation (SDE) is developed to accurately characterize the self-organizing evolution of the operating cost of MGO incurred by contingencies. Firstly, an operating model of MMG relying on two random graph-driven information matrices is constructed and the order parameters are introduced to extract the probabilistic properties of variations in operating cost. Subsequently, these order parameters, which assist individuals in effectively capturing system correlations and updating state information, are incorporated as inputs into second-order SDE. The second-order SDE is then solved by using the finite difference method (FDM) within a loop-structured solution framework. Case studies conducted within a practical area in China validate that the proposed self-organizing energy management model (SEMM) demonstrates spontaneous improvements in economic performance compared with conventional models.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"574-584"},"PeriodicalIF":5.7,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10648973","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DistFlow Safe Reinforcement Learning Algorithm for Voltage Magnitude Regulation in Distribution Networks

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-08-26 DOI: 10.35833/MPCE.2024.000253

Shengren Hou;Aihui Fu;Edgar Mauricio Salazar Duque;Peter Palensky;Qixin Chen;Pedro P. Vergara

{"title":"DistFlow Safe Reinforcement Learning Algorithm for Voltage Magnitude Regulation in Distribution Networks","authors":"Shengren Hou;Aihui Fu;Edgar Mauricio Salazar Duque;Peter Palensky;Qixin Chen;Pedro P. Vergara","doi":"10.35833/MPCE.2024.000253","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000253","url":null,"abstract":"The integration of distributed energy resources (DERs) has escalated the challenge of voltage magnitude regulation in distribution networks. Model-based approaches, which rely on complex sequential mathematical formulations, cannot meet the real-time demand. Deep reinforcement learning (DRL) offers an alternative by utilizing offline training with distribution network simulators and then executing online without computation. However, DRL algorithms fail to enforce voltage magnitude constraints during training and testing, potentially leading to serious operational violations. To tackle these challenges, we introduce a novel safe-guaranteed reinforcement learning algorithm, the DistFlow safe reinforcement learning (DF-SRL), designed specifically for real-time voltage magnitude regulation in distribution networks. The DF-SRL algorithm incorporates a DistFlow linearization to construct an expert-knowledge-based safety layer. Subsequently, the DF-SRL algorithm overlays this safety layer on top of the agent policy, recalibrating unsafe actions to safe domains through a quadratic programming formulation. Simulation results show the DF-SRL algorithm consistently ensures voltage magnitude constraints during training and real-time operation (test) phases, achieving faster convergence and higher performance, which differentiates it apart from (safe) DRL benchmark algorithms.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 1","pages":"300-311"},"PeriodicalIF":5.7,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10648969","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Self-Adaptive Action and Parameter Optimization of DC Series-Parallel Power Flow Controller for Fault Current Limiting in Bipolar DC Distribution Systems

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-08-26 DOI: 10.35833/MPCE.2024.000212

Yangtao Liu;Jianquan Liao;Chunsheng Guo;Zipeng Tan;Qianggang Wang;Yuhong Wang;Niancheng Zhou

{"title":"Self-Adaptive Action and Parameter Optimization of DC Series-Parallel Power Flow Controller for Fault Current Limiting in Bipolar DC Distribution Systems","authors":"Yangtao Liu;Jianquan Liao;Chunsheng Guo;Zipeng Tan;Qianggang Wang;Yuhong Wang;Niancheng Zhou","doi":"10.35833/MPCE.2024.000212","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000212","url":null,"abstract":"DC series-parallel power flow controller (SP-PFC) is a highly efficient device to solve the problem of uncontrolled line current in the bipolar DC distribution system. However, its potential in fault current limiting is not fully explored. In this paper, a self-adaptive action strategy (SAAS) and a parameter optimization method of SP-PFC in bipolar DC distribution systems are proposed. Firstly, the common- and different-mode (CDM) equivalent circuits of the bipolar DC distribution system with SP-PFC in different fault stages are established, which avoids the line coupling inductance. Based on this, the influence of different parameters and line coupling inductance on the fault current limiting capability are investigated. It is found that the SP-PFC has the best fault current limiting capability when the capacitance and inductance of filter are inversely proportional. To realize the adaptability of fault current limiting capability under different fault severities, the SAAS of SP-PFC is proposed. The validity of the CDM equivalent circuits and parameter optimization method, and the effectiveness of the SAAS are verified by simulations and experiments.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"732-746"},"PeriodicalIF":5.7,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10648967","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143698222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Power System Reliability Evaluation Based on Sequential Monte Carlo Simulation Considering Multiple Failure Modes of Components 基于顺序蒙特卡洛模拟的电力系统可靠性评估（考虑组件的多种失效模式

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-08-26 DOI: 10.35833/MPCE.2023.000939

Wei Huang;Bo Hu;Changzheng Shao;Wei Li;Xiaozhe Wang;Kaigui Xie;C. Y. Chung

{"title":"Power System Reliability Evaluation Based on Sequential Monte Carlo Simulation Considering Multiple Failure Modes of Components","authors":"Wei Huang;Bo Hu;Changzheng Shao;Wei Li;Xiaozhe Wang;Kaigui Xie;C. Y. Chung","doi":"10.35833/MPCE.2023.000939","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000939","url":null,"abstract":"The component aging has become a significant concern worldwide, and the frequent failures pose a serious threat to the reliability of modern power systems. In light of this issue, this paper presents a power system reliability evaluation method based on sequential Monte Carlo simulation (SMCS) to quantify system reliability considering multiple failure modes of components. First, a three-state component reliability model is established to explicitly describe the state transition process of the component subject to both aging failure and random failure modes. In this model, the impact of each failure mode is decoupled and characterized as the combination of two state duration variables, which are separately modeled using specific probability distributions. Subsequently, SMCS is used to integrate the three-state component reliability model for state transition sequence generation and system reliability evaluation. Therefore, various reliability metrics, including the probability of load curtailment (PLC), expected frequency of load curtailment (EFLC), and expected energy not supplied (EENS), can be estimated. To ensure the applicability of the proposed method, Hash table grouping and the maximum feasible load level judgment techniques are jointly adopted to enhance its computational performance. Case studies are conducted on different aging scenarios to illustrate and validate the effectiveness and practicality of the proposed method.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 1","pages":"202-214"},"PeriodicalIF":5.7,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10648964","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143184067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0