Iet Generation Transmission & Distribution最新文献

Resilience-oriented load restoration method for power-gas-water systems considering public safety impact 考虑到公共安全影响的以复原力为导向的电力-天然气-水系统负荷恢复方法

IF 2 4区工程技术

Iet Generation Transmission & Distribution Pub Date : 2024-10-28 DOI: 10.1049/gtd2.13281

Haiyang Wan, Wenxia Liu, Shuai Zhang, Qingxin Shi, Rui Cheng, Wei Feng

{"title":"Resilience-oriented load restoration method for power-gas-water systems considering public safety impact","authors":"Haiyang Wan, Wenxia Liu, Shuai Zhang, Qingxin Shi, Rui Cheng, Wei Feng","doi":"10.1049/gtd2.13281","DOIUrl":"https://doi.org/10.1049/gtd2.13281","url":null,"abstract":"Focusing solely on enhancing the resilience of power systems at a systemic level would lead to a significant underestimation of the actual impact of extreme disasters. Equally vital is the assurance of livelihood security amidst such extreme conditions, which is crucial for the development of a truly resilient power system. Hence, this paper attempts to incorporate quantifiable metrics assessing public safety impacts into resilience enhancement works, thereby guiding the precise allocation of funds. Considering that the residents' intuitive feelings are the most direct reflection of the severity of the disaster, this paper employs the modified prospect theory to formulate functions representing residents' psychological risk perception and risk-taking willingness to tolerate risks during disruptions in power, gas, and water supplies. Meanwhile, in order to accurately calculate the energy loss duration for each residential customer, a resilience enhancement method for post-disaster collaborative dispatch of electricity-gas-water systems is proposed. With the objective of minimizing the public safety and economic impact of disasters, the optimal multi-source collaborative emergency restoration strategy is developed. The significant necessity and efficiency of the proposed strategy are verified with exhaustive case studies. Numerical results evince the resilience enhancement by considering the livelihood security in the post-disaster restoration stage.","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"18 21","pages":"3350-3364"},"PeriodicalIF":2.0,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13281","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142679923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Enhancing distance protection in transmission grids with high penetration of renewable energy sources through cooperative protection 通过协同保护加强可再生能源渗透率高的输电网的距离保护

IF 2 4区工程技术

Iet Generation Transmission & Distribution Pub Date : 2024-10-21 DOI: 10.1049/gtd2.13295

Sayed Mahdi Koloushani, Seyed Abbas Taher

{"title":"Enhancing distance protection in transmission grids with high penetration of renewable energy sources through cooperative protection","authors":"Sayed Mahdi Koloushani, Seyed Abbas Taher","doi":"10.1049/gtd2.13295","DOIUrl":"https://doi.org/10.1049/gtd2.13295","url":null,"abstract":"This article introduces innovative protection strategies, including cooperative protection, for power transmission grids amidst a significant shift towards renewable energy sources (RES) such as wind and solar power, as well as inverter-based resources (IBRs). The method employs a global consensus algorithm to achieve cooperative protection efficiently. This scheme leverages consensus protocols to dynamically oversee distance relay decisions, ensuring efficient fault detection and localization. The decentralized nature of the proposed method enhances robustness and security, while its high-speed operation is ensured through non-iterative global consensus algorithms, which provide rapid fault detection and localization crucial for real-time protection. By incorporating virtual leaders and leveraging existing communication infrastructure, the method achieves superior selectivity in identifying faulty lines, enhancing the reliability and stability of power transmission grids with high-RES penetration. Notably, the method does not require learning and training processes, making it adaptable to varying power system topologies without the need for extensive retraining or adaptation periods. The proposed methodology enables simultaneous participation in multiple protection zones by establishing interaction rules between agents. Virtual leaders simplify the selection of protection areas, enhancing scalability and fault localization. Simulation results conducted on the IEEE 39-bus test system validate the effectiveness of the proposed method.","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"18 21","pages":"3462-3475"},"PeriodicalIF":2.0,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13295","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 node deployment and resource optimization method for CPDS based on cloud-fog-edge collaboration 一种基于云-雾-边协作的 CPDS 节点部署和资源优化方法

IF 2 4区工程技术

Iet Generation Transmission & Distribution Pub Date : 2024-10-21 DOI: 10.1049/gtd2.13286

Xiaoping Xiong, Geng Yang

{"title":"A node deployment and resource optimization method for CPDS based on cloud-fog-edge collaboration","authors":"Xiaoping Xiong, Geng Yang","doi":"10.1049/gtd2.13286","DOIUrl":"https://doi.org/10.1049/gtd2.13286","url":null,"abstract":"With the development of the Internet of Things (IoT) in power distribution and the advancement of energy information integration technologies, the explosive growth in network data volume caused by massive terminal devices connecting to the power distribution network has become a significant challenge. Multi-terminal collaborative computing is a key approach to addressing issues such as high latency and high energy consumption. In this article, fog computing is introduced into the computing network of the power distribution system, and a cloud-fog-edge collaborative computing architecture for intelligent power distribution networks is proposed. Within this framework, an improved weighted K-means method based on information entropy theory is presented for node partitioning. Subsequently, an improved multi-objective particle swarm optimization algorithm (MWM-MOPSO) is employed to solve the task resource allocation problem. Finally, the effectiveness of the proposed architecture and allocation strategy is validated through simulations on the OPNET and PureEdgeSim platforms. The results demonstrate that, compared to traditional cloud-edge service architectures, the proposed architecture and task offloading scheme achieve better performance in terms of processing latency and energy consumption.","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"18 21","pages":"3524-3537"},"PeriodicalIF":2.0,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13286","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Short-circuit current of a hydropower plant with consideration of constant switching and fault arc voltages 考虑到恒定开关电压和故障电弧电压的水电站短路电流

IF 2 4区工程技术

Iet Generation Transmission & Distribution Pub Date : 2024-10-17 DOI: 10.1049/gtd2.13297

Darko Brankovic, Robert Schuerhuber

{"title":"Short-circuit current of a hydropower plant with consideration of constant switching and fault arc voltages","authors":"Darko Brankovic, Robert Schuerhuber","doi":"10.1049/gtd2.13297","DOIUrl":"https://doi.org/10.1049/gtd2.13297","url":null,"abstract":"The correct generator circuit breaker (GCB) dimensioning is essential for the safe and reliable operation of a power plant or generation system. The dimensioning is usually based on standardized calculation methods according to standards (IEC standard 60909-0, IEC/IEEE standard 62271-37-013, IEEE Std C37), often supplemented by selected transient calculations. A non-systematic approach can often be observed here, which does not adequately take into account significant influencing variables or operating states of the generator. This article therefore systematically examines various parameters that influence the short-circuit current components of the generator and are relevant for the dimensioning of the generator circuit-breaker: short-circuit angle, operating point, impedance ratios, phase clearing, switching arc, and fault arc. The results of the current parameters most relevant to the dimensioning of the GCB were then compared for different calculation methods. Special attention was paid to the effect of the switching and fault arc, which were modelled as a constant arc voltage, and its effect on the short-circuit currents is systematically recorded. This work aims to summarize all relevant variables that influence the generator short-circuit current and are relevant for the dimensioning of the GCB and to present the different results based on a short-circuit calculation according to the standard and transient calculation to create a basis for a proper dimensioning of the generator circuit breaker.","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"18 21","pages":"3476-3486"},"PeriodicalIF":2.0,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13297","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Wavelet CNN-LSTM time series forecasting of electricity power generation considering biomass thermal systems 考虑生物质热能系统的小波 CNN-LSTM 发电时间序列预测

IF 2 4区工程技术

Iet Generation Transmission & Distribution Pub Date : 2024-10-15 DOI: 10.1049/gtd2.13292

William Gouvêa Buratto, Rafael Ninno Muniz, Ademir Nied, Carlos Frederico de Oliveira Barros, Rodolfo Cardoso, Gabriel Villarrubia Gonzalez

{"title":"Wavelet CNN-LSTM time series forecasting of electricity power generation considering biomass thermal systems","authors":"William Gouvêa Buratto, Rafael Ninno Muniz, Ademir Nied, Carlos Frederico de Oliveira Barros, Rodolfo Cardoso, Gabriel Villarrubia Gonzalez","doi":"10.1049/gtd2.13292","DOIUrl":"https://doi.org/10.1049/gtd2.13292","url":null,"abstract":"The use of biomass as a renewable energy source for electricity generation has gained attention due to its sustainability and environmental benefits. However, the intermittent electricity demand poses challenges for optimizing electricity generation in thermal systems. Time series forecasting techniques are crucial in addressing these challenges by providing accurate predictions of biomass availability and electricity generation. Here, wavelet transform is applied for denoising, convolutional neural networks (CNN) are used to extract features of the time series, and long short-term memory (LSTM) is applied to perform the predictions. The result of the mean absolute percentage error equal to 0.0148 shows that the wavelet CNN-LSTM is a promising machine-learning methodology for electricity generation forecasting. Additionally, this paper discusses the importance of model evaluation techniques and validation strategies to assess the performance of forecasting models in real-world applications. The major contribution of this paper is related to improving forecasting using a hybrid method that outperforms other models based on deep learning. Finally, future research directions and potential advancements in time series forecasting for biomass thermal systems are outlined to foster continued innovation in sustainable energy generation.","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"18 21","pages":"3437-3451"},"PeriodicalIF":2.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13292","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Optimizing decentralized implementation of state estimation in active distribution networks 优化主动配电网络中状态估计的分散实施

IF 2 4区工程技术

Iet Generation Transmission & Distribution Pub Date : 2024-10-15 DOI: 10.1049/gtd2.13296

Mohammad Gholami, Aref Eskandari, Sajjad Fattaheian-Dehkordi, Matti Lehtonen

{"title":"Optimizing decentralized implementation of state estimation in active distribution networks","authors":"Mohammad Gholami, Aref Eskandari, Sajjad Fattaheian-Dehkordi, Matti Lehtonen","doi":"10.1049/gtd2.13296","DOIUrl":"https://doi.org/10.1049/gtd2.13296","url":null,"abstract":"The challenges facing active distribution networks have highlighted the position of the distribution system state estimation (DSSE) process in the distribution management systems as its most important function. Here, regarding the extensive scale of distribution networks and the weaknesses of centralized methods, the decentralized implementation of the DSSE process has received considerable attention. However, predefined network partitioning is supposed in previous works and zone size effects on the performance of the DSSE process have not been assessed. In response, a method for finding the optimal number of network zones and their size is proposed here. For this purpose, initially, an algorithm is used to partition the network into all possible configurations with different sizes. Subsequently, performance metrics affected by zone sizes, such as execution time, accuracy of the DSSE results, and reliability in achieving the results at the control centre, are modelled. Finally, by applying the decentralized DSSE method across all partitioning scenarios and calculating performance metrics, the most efficient and cost-effective partitioning scenario can be identified. The performance of the proposed method is evaluated using the modified 77-bus UK distribution network as an active test case, and the findings are subsequently presented and analysed.","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"18 21","pages":"3538-3553"},"PeriodicalIF":2.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13296","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Enhancing distribution system stability and efficiency through multi-power supply startup optimization for new energy integration 通过多电源启动优化提高配电系统稳定性和效率，促进新能源整合

IF 2 4区工程技术

Iet Generation Transmission & Distribution Pub Date : 2024-10-14 DOI: 10.1049/gtd2.13299

Qinglin Meng, Xinyu Tong, Sheharyar Hussain, Fengzhang Luo, Fei Zhou, Ying He, Lei Liu, Bing Sun, Botong Li

{"title":"Enhancing distribution system stability and efficiency through multi-power supply startup optimization for new energy integration","authors":"Qinglin Meng, Xinyu Tong, Sheharyar Hussain, Fengzhang Luo, Fei Zhou, Ying He, Lei Liu, Bing Sun, Botong Li","doi":"10.1049/gtd2.13299","DOIUrl":"https://doi.org/10.1049/gtd2.13299","url":null,"abstract":"This paper addresses the challenge of maximizing power capture from new energy sources, including coal, wind, solar, and hydroelectric power, which often lack sufficient inertia support. This deficiency can lead to frequency instability and cascading failures within the power system. A cooperative optimization model for the start-up of multiple power supplies, designed to enhance the integration of new energy sources while maintaining system stability is proposed. The model incorporates primary frequency modulation and the intrinsic inertia support capabilities of self-synchronous voltage source field stations, considering dynamic frequency constraints. Additionally, it employs new energy units with primary frequency modulation to provide inertia support during curtailment, particularly when conventional units cannot meet frequency standards due to existing constraints. Extensive simulations and comparative analyses demonstrate that the proposed model improves new energy utilization by up to 37.5% and reduces operational costs by approximately 16%, enhancing overall operational efficiency in high energy consumption scenarios.","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"18 21","pages":"3487-3500"},"PeriodicalIF":2.0,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13299","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Improving protection reliability of series-compensated transmission lines by a fault detection method through an ML-based model 通过基于 ML 模型的故障检测方法提高串联补偿输电线路的保护可靠性

IF 2 4区工程技术

Iet Generation Transmission & Distribution Pub Date : 2024-10-13 DOI: 10.1049/gtd2.13294

Hossein Ebrahimi, Sajjad Golshannavaz, Amin Yazdaninejadi, Edris Pouresmaeil

{"title":"Improving protection reliability of series-compensated transmission lines by a fault detection method through an ML-based model","authors":"Hossein Ebrahimi, Sajjad Golshannavaz, Amin Yazdaninejadi, Edris Pouresmaeil","doi":"10.1049/gtd2.13294","DOIUrl":"https://doi.org/10.1049/gtd2.13294","url":null,"abstract":"This article addresses the distance protection challenges associated with the series-compensated transmission lines and the impact of fault resistance by employing a machine-learning model. In the proposed model, stacked layers of bidirectional long short-term memory (Bi-LSTM) cells are fed by voltage and current signals to distinguish between different fault scenarios. This method takes advantage of only local bus measurements to prevent information leakage in communication channels. Moreover, to make the proposed method harmonics-robust and improve the correlation interpretation between the features for the Bi-LSTM model, the 3-phase raw measurement signals are passed through a discrete Fourier transform (DFT) which extracts their fundamental frequency component magnitudes and angles. Then, an extensive amount of fault scenarios including different compensation levels, fault resistances, and fault locations in normal and power-swing operational conditions are simulated to train the model. Finally, to validate the performance of the proposed protection method in the series-compensated transmission lines, distinctive studies are also carried out based on electromagnetic transient simulations. The obtained results confirm the remarkable performance of the proposed method in discriminating fault types, faulty phases, internal or external faults, and normal or power-swing conditions of the power system.","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"18 21","pages":"3452-3461"},"PeriodicalIF":2.0,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13294","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Determining the optimal bid direction of a generation company using the gradient vector of the profit function in the network constraints of the electricity market 利用电力市场网络约束下的利润函数梯度向量确定发电公司的最佳投标方向

IF 2 4区工程技术

Iet Generation Transmission & Distribution Pub Date : 2024-10-09 DOI: 10.1049/gtd2.13280

Mohammad Ebrahim Hajiabadi, Mahdi Samadi, Mohammad Hassan Nikkhah, Hossein Lotfi, Li Li

{"title":"Determining the optimal bid direction of a generation company using the gradient vector of the profit function in the network constraints of the electricity market","authors":"Mohammad Ebrahim Hajiabadi, Mahdi Samadi, Mohammad Hassan Nikkhah, Hossein Lotfi, Li Li","doi":"10.1049/gtd2.13280","DOIUrl":"https://doi.org/10.1049/gtd2.13280","url":null,"abstract":"One of the primary challenges faced by generation companies (GenCos), which operate multiple generation units within the electricity market, is the determination of the optimal bid price for these units to maximize profit. This paper proposes a novel approach to ascertain the optimal bid price direction for GenCos by leveraging the gradient vector of the profit function within the constraints of the electricity market. First, the Jacobian matrix of unit profits is computed using the electricity market structural decomposition method. This matrix highlights how the profit of generation units is affected by market input parameters, including the bid prices of the units. Then, the gradient vector of the GenCos' profit function and the optimal bid price direction are derived from the Jacobian matrix. The methodology is applied to a 24-bus IEEE network, with results validated against those from a simulation method to confirm the efficacy of the proposed approach. The simulation results show that the highest and lowest profit changes with a step increase of 0.1$/MWh are observed for GenCo 4 and GenCo 6 with values of 60.28 and 2.20 $/h, respectively. The proposed approach can be effective in the changes of bid direction of the units of a GenCo to achieve the highest possible profit.","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"18 21","pages":"3339-3349"},"PeriodicalIF":2.0,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13280","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 data-driven transient stability-based approach for out-of-step prediction in power systems 基于数据驱动的暂态稳定方法，用于电力系统的失步预测

IF 2 4区工程技术

Iet Generation Transmission & Distribution Pub Date : 2024-10-09 DOI: 10.1049/gtd2.13290

Sirwan Shazdeh, Hêmin Golpîra, Hassan Bevrani

{"title":"A data-driven transient stability-based approach for out-of-step prediction in power systems","authors":"Sirwan Shazdeh, Hêmin Golpîra, Hassan Bevrani","doi":"10.1049/gtd2.13290","DOIUrl":"https://doi.org/10.1049/gtd2.13290","url":null,"abstract":"This paper presents a prediction-based algorithm designed to address out-of-step (OOS) conditions in power systems. The algorithm utilizes generator data obtained from phasor measurement units. The transient stability of a multi-machine power system is evaluated using the equal-area criterion (EAC). The proposed algorithm calculates the characteristics of the P-δ curves within the EAC framework after a large disturbance. The critical P-δ trace is determined by analysing the cumulative energy in the acceleration area following fault clearance. The stability margin of the rotor angle is then computed based on the actual active power and its relationship with the critical curve. The algorithm predicts the occurrence of OOS by comparing the measured active power with the corresponding value on the critical curve. Furthermore, a complementary strategy is proposed to predict the OOS condition in integrated inverter-based power systems. The effectiveness of the proposed algorithm is validated through simulations conducted on the 73-bus IEEE test power system.","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"18 21","pages":"3407-3423"},"PeriodicalIF":2.0,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13290","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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