Sustainable Energy Grids & Networks最新文献_第7页

Identification of generator coherency in power systems with wind farm 风电场电力系统中发电机一致性的识别

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2024-08-16 DOI: 10.1016/j.segan.2024.101502

Jiajun Liu, Lipeng Liu, Ji Sun, Chenjing Li, Haokun Xu

{"title":"Identification of generator coherency in power systems with wind farm","authors":"Jiajun Liu, Lipeng Liu, Ji Sun, Chenjing Li, Haokun Xu","doi":"10.1016/j.segan.2024.101502","DOIUrl":"10.1016/j.segan.2024.101502","url":null,"abstract":"<div><div>In the context of the \"dual carbon\" goal, the penetration rate of new energy represented by wind power is gradually increasing. The large-scale grid connection of wind power makes the power system more complex and uncertain. The output of wind farms changes the system flow, indirectly affecting the power angle characteristics of synchronous generators, and thereby changing the coherence between generators. Affects synchronous generator homology identification. This paper proposes a generator homology identification method for power systems containing wind farms, in response to the problem that the existing methods for identifying unit homology have not taken into account the adverse effects of wind farms on identification results. Translate the influence of wind farms on the homology of synchronous generators into the contraction admittance matrix as a static electrical distance indicator; Select dynamic data reflecting the homology of synchronous generators after disturbance, and form four dynamic indicators to measure the power angle increment curve between each generator: Euclidean distance, Chebyshev distance, grey correlation, and correlation coefficient; By using the combination weighting method to determine the weights of each indicator, a comprehensive similarity matrix is formed, and the optimal clustering results are determined using fuzzy system clustering and F-statistical values. Finally, the effectiveness of the proposed method was verified using EPRI-9 node system, EPRI-36 node system, and IEEE68 node system as examples.</div><div>© 2017 Elsevier Inc. All rights reserved.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101502"},"PeriodicalIF":4.8,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Integrating Bayesian inference and neural ODEs for microgrids dynamics parameters estimation 整合贝叶斯推理和神经 ODEs，实现微电网动态参数估计

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2024-08-15 DOI: 10.1016/j.segan.2024.101498

Fathi Farah Fadoul , Ramazan Çağlar

{"title":"Integrating Bayesian inference and neural ODEs for microgrids dynamics parameters estimation","authors":"Fathi Farah Fadoul , Ramazan Çağlar","doi":"10.1016/j.segan.2024.101498","DOIUrl":"10.1016/j.segan.2024.101498","url":null,"abstract":"<div><p>The integration of solar and wind energy sources in microgrids has witnessed significant growth, giving rise to distinct challenges due to their intermittent nature when it comes to achieving efficient microgrid control. However, estimating the parameters of the dynamic microgrid components facilitates capturing the complex and time-varying characteristics of renewable energy generation. This requires an accurate estimation of the parameters from the dynamic differential equations for effective modeling and control. In this research paper, we presented a novel methodology based on the integration of Bayesian inference and Neural ODEs. The Bayesian inference quantifies the uncertainty, and the Neural ODEs model the dynamic systems. By combining the strengths of both methods, we aimed to achieve a precise and robust parameter estimation of the dynamic microgrid components. The methodology is validated on a simulated microgrid that consists of a diesel generator, Solar PV array, double-fed induction generator, and a battery energy storage system. The results showed promised inferences estimation obtained from the parameter posterior distribution even in the presence of uncertainty. This can enhance our understanding of the dynamics of renewable energy systems and can contribute to the advancement of decision-making microgrid control strategies.</p></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"39 ","pages":"Article 101498"},"PeriodicalIF":4.8,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142040185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comprehensive analysis of smart grids functionalities virtualization 智能电网功能虚拟化综合分析

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2024-08-15 DOI: 10.1016/j.segan.2024.101507

Laura Lázaro-Elorriaga , David Guerra , Imanol García-Pastor , Cristina Martínez , Eutimio Sanchez , Eugenio Perea

{"title":"Comprehensive analysis of smart grids functionalities virtualization","authors":"Laura Lázaro-Elorriaga , David Guerra , Imanol García-Pastor , Cristina Martínez , Eutimio Sanchez , Eugenio Perea","doi":"10.1016/j.segan.2024.101507","DOIUrl":"10.1016/j.segan.2024.101507","url":null,"abstract":"<div><p>The implementation of advanced digital technologies in the conventional electric grid has triggered a transformation towards an intelligent network, known as Smart Grid. The associated benefits are diverse, ranging from more efficient energy management and demand response to the distributed integration of renewable energy sources. Ultimately, this transition promotes a more reliable, sustainable, and cost-effective energy supply. In this context, there is increasing recognition of the advantages of employing intelligent at edge to provide redundancy, virtualize functions that were previously in different proprietary hardware in the same device, or introduce new functionalities into the electric grid. This study focuses on conducting a comprehensive analysis on the key aspects to consider when implementing virtualized solutions in substations. Strategies have been sought to ensure the optimal deployment of virtualized nodes within the electrical sector, taking into account factors such as functional requirements, facility types, virtualization methodologies, and node specifications, among others. Furthermore, throughout the study, several virtualization tools have been analysed to determine their feasibility and the advantages they offer when integrated into the Smart Grid.</p></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"40 ","pages":"Article 101507"},"PeriodicalIF":4.8,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352467724002364/pdfft?md5=55d95e4bffb335f7472701e074a2be7e&pid=1-s2.0-S2352467724002364-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 reliability assessment in distributed generation networks: Incorporating dynamic correlation of wind-solar power output uncertainty 加强分布式发电网络的可靠性评估：纳入风能-太阳能输出不确定性的动态相关性

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2024-08-14 DOI: 10.1016/j.segan.2024.101505

Kang Li, Pengfei Duan, Qingwen Xue, Yuanda Cheng, Jing Hua, Jinglei Chen, Panhao Guo

{"title":"Enhancing reliability assessment in distributed generation networks: Incorporating dynamic correlation of wind-solar power output uncertainty","authors":"Kang Li, Pengfei Duan, Qingwen Xue, Yuanda Cheng, Jing Hua, Jinglei Chen, Panhao Guo","doi":"10.1016/j.segan.2024.101505","DOIUrl":"10.1016/j.segan.2024.101505","url":null,"abstract":"<div><p>Amidst escalating environmental concerns and energy scarcity, the integration of distributed generation (DG) within distribution networks (DN) has emerged as a pivotal developmental trend. The uncertainty inherent in renewable energy output often disrupts DG networks. Notably, the dynamic correlation between key renewable sources, such as wind and solar energy, significantly influences the reliability analysis of these networks.To comprehensively assess the impact of wind-solar power output uncertainty and its dynamic correlation on DN reliability, this study leverages copula theory to express the dynamic correlation coefficient between wind and solar power. This coefficient is formulated as the dynamic correlation of wind-solar power through copula dynamic correlation coefficient. Employing an auto-regressive moving average (ARMA) model with constraints solved using maximum likelihood kernel (MLK), we construct the wind-solar joint output (WSJO) model. Subsequently, utilizing sequential Monte Carlo simulation (MCS) with the WSJO model, we analyze DN reliability. In case of DN failure, the WSJO model generates random samples of the wind-solar joint output sequence. Subsequent power restoration to governed islands enables the calculation of DN reliability indices. The WSJO model constructed in this study accounts for wind resource output uncertainty and dynamic correlation, aligning more closely with actual distributed generation output and enhancing the accuracy of reliability assessment. Finally, we simulate the improved IEEE-RBTS-BUS6-F4 system to underscore the crucial role of considering wind-solar energy's dynamic correlation in DN reliability assessment.</p></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"39 ","pages":"Article 101505"},"PeriodicalIF":4.8,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141997353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing local energy sharing reliability within peer-to-peer prosumer communities: A cellular automata and deep learning approach 增强点对点专业消费者社区内的本地能源共享可靠性：细胞自动机和深度学习方法

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2024-08-13 DOI: 10.1016/j.segan.2024.101504

Hamza El Kasri , Iliasse Abdennour , Mustapha Ouardouz , Abdes Samed Bernoussi

{"title":"Enhancing local energy sharing reliability within peer-to-peer prosumer communities: A cellular automata and deep learning approach","authors":"Hamza El Kasri , Iliasse Abdennour , Mustapha Ouardouz , Abdes Samed Bernoussi","doi":"10.1016/j.segan.2024.101504","DOIUrl":"10.1016/j.segan.2024.101504","url":null,"abstract":"<div><p>This study introduces a significant advancement in peer-to-peer (P2P) energy trading systems within smart grids, addressing a crucial gap in existing research by incorporating optimal energy storage capacities to accommodate varying energy demands resulting from lifestyle changes. Through a two-level optimization approach, aimed at maximizing self consumption and optimizing energy flow within the grid, we propose a novel energy management strategy. Our contribution lies in the introduction of a new layer of deep learning and rules control, forming a self-energy sharing system for each prosumer. This architecture, termed the smart node, integrates deep learning techniques, to predict and customize energy services through dynamic adjustment of lower and upper bounds of battery capacities. Additionally, we leverage cellular automaton (CA) approaches to establish sustainable consensus among P2P network users, enhancing the adaptability and efficiency of the energy management system. The results show that the proposed algorithm could reduce the energy consumed by the P2P community from the utility by around 20% and maximize the collective self-consumption by around 8% compared to conventional energy trading in microgrids.</p></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"39 ","pages":"Article 101504"},"PeriodicalIF":4.8,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142058278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Leak identification and quantification in gas network using operational data and deep learning framework 利用运行数据和深度学习框架识别和量化天然气管网中的泄漏点

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2024-08-13 DOI: 10.1016/j.segan.2024.101496

Elham Ebrahimi , Mohammadrahim Kazemzadeh , Antonio Ficarella

{"title":"Leak identification and quantification in gas network using operational data and deep learning framework","authors":"Elham Ebrahimi , Mohammadrahim Kazemzadeh , Antonio Ficarella","doi":"10.1016/j.segan.2024.101496","DOIUrl":"10.1016/j.segan.2024.101496","url":null,"abstract":"<div><p>In this study, we introduce an innovative deep learning framework designed to achieve precise detection, localization, and rate estimation of gas distribution pipeline system leakages. Our method surpasses conventional statistical approaches, particularly those based on Bayesian inference, by accommodating the system’s intricate behaviors, including variable usage and production from both sources and sinks. Notably, our approach demonstrates remarkable accuracy in localizing leakages even amidst multiple occurrences within the system. Specifically, achieving over 98% accuracy in single-leakage scenarios underscores its effectiveness. Furthermore, through data augmentation involving the introduction of noise into the training dataset, we significantly enhance the model’s performance, particularly when tested against real-world-like noisy data. This study not only showcases the efficacy of our proposed deep learning framework but also underscores its adaptability and robustness in addressing complex challenges in gas pipeline systems.</p></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"39 ","pages":"Article 101496"},"PeriodicalIF":4.8,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S235246772400225X/pdfft?md5=d1fbee711a0e12c9d61ba2b7cc20c153&pid=1-s2.0-S235246772400225X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142021297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Week-ahead dispatching of active distribution networks using hybrid energy storage systems 利用混合储能系统对主动配电网进行周前调度

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2024-08-13 DOI: 10.1016/j.segan.2024.101500

Matthieu Jacobs, Rahul Gupta, Mario Paolone

{"title":"Week-ahead dispatching of active distribution networks using hybrid energy storage systems","authors":"Matthieu Jacobs, Rahul Gupta, Mario Paolone","doi":"10.1016/j.segan.2024.101500","DOIUrl":"10.1016/j.segan.2024.101500","url":null,"abstract":"<div><p>This paper presents a week-long scheduling approach to address the issues associated with uncertain stochastic generation. Specifically, the method is designed for active distribution networks (ADNs) hosting hybrid energy storages, composed by a hydrogen energy storage system (HESS) and a battery energy storage system (BESS). The inclusion of a pressurized HESS allows to balance energy over longer time periods, as opposed to methods considering only BESSs. To this end, this paper combines linearized models for the electricity grid with linearized models of the HESS to solve a tractable scheduling problem. The proposed optimal schedule consists of an active power trajectory at the grid connection point (GCP), called the dispatch plan, and the unit commitment schedule of a PEM fuel cell and electrolyzer system interfacing the electricity network with the HESS. Additionally, a bilevel model predictive control strategy is proposed, where the upper layer MPC computes a storage target accounting for the full horizon, while the lower layer computes the controllable resource setpoints to minimize the dispatch tracking error in each period. A numerical experiment shows the effectiveness of the proposed scheduling and control to accurately compute and track a dispatch plan over a full week. The results clearly show the benefits of combining a HESS with a BESS especially in periods where the prosumption is highly uncertain. Finally, we discuss the computational challenges associated with the weekly horizon and the use of a HESS that exhibits different dynamics than a BESS and propose an approach to mitigate the computational cost.</p></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"39 ","pages":"Article 101500"},"PeriodicalIF":4.8,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352467724002297/pdfft?md5=16b93726a0af2d264cb90fb7225699a8&pid=1-s2.0-S2352467724002297-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142002241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Optimal distributed energy scheduling for port microgrid system considering the coupling of renewable energy and demand 考虑可再生能源与需求耦合的港口微电网系统最优分布式能源调度

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2024-08-13 DOI: 10.1016/j.segan.2024.101506

Chang Xiong , Yixin Su , Hao Wang , Danhong Zhang , Binyu Xiong

{"title":"Optimal distributed energy scheduling for port microgrid system considering the coupling of renewable energy and demand","authors":"Chang Xiong , Yixin Su , Hao Wang , Danhong Zhang , Binyu Xiong","doi":"10.1016/j.segan.2024.101506","DOIUrl":"10.1016/j.segan.2024.101506","url":null,"abstract":"<div><p>The increased uptake of distributed renewable energy in port areas is facilitating the electrification and net zero transition of marine ports. Effective operation that considers unique characteristics of the port is critical to minimize the operating cost in the port microgrid (PMG). In this paper, we propose a joint scheduling method that considers the impact of tidal patterns on the period and intensity of port operations. The method takes advantage of the strong correlations between renewable energy (solar, wind and tidal) and multi-class load to support the PMG operator in determining the most cost-effective scheduling of energy supply and flexible loads during port activities. Additionally, the traditional centralized operation is vulnerable to local failures, and distributed operation for hundreds of energy units will result in significant computational burden, neither of which is suitable for the PMG operation. Our work decouples the PMG system based on the port functions and thus decomposes the PMG operation into a few subproblems. Then, we hierarchically solve the primal and dual problems by a distributed algorithm. Simulation results illustrate the benefits of tidal energy in the renewable generation mix. Furthermore, the proposed method achieves cost reductions of 12.4% and 21.7% under two different tidal patterns.</p></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"39 ","pages":"Article 101506"},"PeriodicalIF":4.8,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141997352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Source-load coordinated dispatching model taking into account the similarity between renewable energy and load power 考虑到可再生能源与负载功率相似性的源-负载协调调度模型

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2024-08-13 DOI: 10.1016/j.segan.2024.101499

Jingjie Huang , Zhiyao Zhang , Liang Yuan , Hongming Yang , Zhaoyang Dong , Renjun Zhou

{"title":"Source-load coordinated dispatching model taking into account the similarity between renewable energy and load power","authors":"Jingjie Huang , Zhiyao Zhang , Liang Yuan , Hongming Yang , Zhaoyang Dong , Renjun Zhou","doi":"10.1016/j.segan.2024.101499","DOIUrl":"10.1016/j.segan.2024.101499","url":null,"abstract":"<div><p>With the deployment of renewable energy, the load curve is expected to follow the renewable energy output curve to minimize the fluctuation of thermal power output in the source-load coordinated dispatching. The traditional indicators for the load curve are no longer enough to describe the load characteristics. A new load indicator called the source-load similarity distance is proposed by improving the similarity measurement method of the time series and calculating the similarity distance between the renewable energy output curve and the load curve. By combining the Euclidean distance with the improved dynamic time warping, the source-load similarity distance is obtained and the data distribution and morphological fluctuation characteristics can be simultaneously considered. The source-load coordinated dispatching model is also established to minimize the source-load similarity distance. The simulation results show that the source-load similarity distance can effectively describe the similarity characteristics of the renewable energy output curve and the load curve. Increasing the source-load similarity distance can reduce the thermal power operation cost by 56.2 % and the cost of demand response by 25.3 %, and increase the utilization rate of wind power by 4.6 % compared to the dispatching model with the standard deviation indicator.</p></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"39 ","pages":"Article 101499"},"PeriodicalIF":4.8,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142047969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Electric vehicle supply equipment monitoring and early fault detection through autoencoders 通过自动编码器监测电动汽车供电设备并及早发现故障

IF 4.8 2区工程技术

Sustainable Energy Grids & Networks Pub Date : 2024-08-13 DOI: 10.1016/j.segan.2024.101497

Maciej Sakwa , Alfredo Nespoli , Silvana Matrone , Sonia Leva , Alice Guerini , Andrea Demartini , Emanuele Ogliari

引用次数: 0