IET Renewable Power Generation最新文献_第5页

Identification of Critical Security Boundary for Resilient Power Systems Driven by Model-Data Fusion 基于模型-数据融合的弹性电力系统关键安全边界识别

IF 2.9 4区工程技术

IET Renewable Power Generation Pub Date : 2025-07-20 DOI: 10.1049/rpg2.70103

Weihao Yin, Tiance Zhang, Gengyin Li, Ming Zhou, Jianxiao Wang

{"title":"Identification of Critical Security Boundary for Resilient Power Systems Driven by Model-Data Fusion","authors":"Weihao Yin, Tiance Zhang, Gengyin Li, Ming Zhou, Jianxiao Wang","doi":"10.1049/rpg2.70103","DOIUrl":"10.1049/rpg2.70103","url":null,"abstract":"With the evolution of power system structure and the expansion of renewable energy scale, the security and stability challenges brought by extreme events are becoming increasingly prominent. The traditional transient model of power systems is tailored specifically for certain fault scenarios and exhibits nonlinear characteristics. Consequently, its solutions are often characterized by a time-intensive nature and suboptimal generalization performance. Therefore, a security boundary identification method for resilient power system driven by model-data fusion is proposed in this paper. Based on the security constrained unit commitment model of power system, the umbrella constraint identification method is employed to identify the effective constraints. A massive extreme sample set based on the dynamic response model of the CloudPSS platform is established, and support vector machine is leveraged to identify and extract transient safety constraints. The critical security boundary is characterised by the combination of umbrella constraints and transient safety constraints, which can be embedded into the economic dispatch model to facilitate the secure and efficient operation of power system. Case studies based on IEEE-39 systems verified the effectiveness of the proposed method in different fault scenarios.","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70103","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144663790","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

Forecasting of Power Generation in a Single-Axis Solar Tracking PV System Using an Enhanced Artificial Neural Network-Based Method 基于增强人工神经网络的单轴太阳能跟踪光伏发电预测方法

IF 2.9 4区工程技术

IET Renewable Power Generation Pub Date : 2025-07-17 DOI: 10.1049/rpg2.70100

Mohamed R. Aboelmagd, Ali Selim, Mamdouh Abdel-Akher

{"title":"Forecasting of Power Generation in a Single-Axis Solar Tracking PV System Using an Enhanced Artificial Neural Network-Based Method","authors":"Mohamed R. Aboelmagd, Ali Selim, Mamdouh Abdel-Akher","doi":"10.1049/rpg2.70100","DOIUrl":"10.1049/rpg2.70100","url":null,"abstract":"In order to anticipate photovoltaic (PV) power output in both fixed and tracking solar systems, this study proposes a strong neural network-based framework that models nonlinear dependencies by utilising meteorological factors such as temperature, wind speed, and sun radiation. Strong correlation coefficients (𝑅2) and low mean squared errors (MSE) throughout the training, validation, and testing phases demonstrate the model's high predictive accuracy, which was attained by combining a 10-layer artificial neural network (ANN) architecture optimised with the Adam algorithm and a dynamic learning rate scheduler. To guarantee generalisability, the dataset—which included 8,761 hourly samples over a full year—was carefully divided into three categories: 70% training, 15% validation, and 15% testing. The impact of system design on productivity was highlighted by a comparative analysis that showed a 21% improvement in annual energy yield for tracking systems (231 kWh) versus fixed systems (184 kWh). Regression plots, error histograms, and monthly power generation profiles were among the visual and statistical assessments that showed how well the model captured seasonal and diurnal variations while reducing bias. With error rates lowered to less than 10% and prediction accuracies over 90% in both contexts, the combination of the MATLAB and Python frameworks further confirmed the method's consistency and scalability.","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70100","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647675","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

Resilient Secondary Distributed Model Predictive Control for Autonomous Microgrid Against Cyber Threats 针对网络威胁的自主微电网弹性二次分布式模型预测控制

IF 2.9 4区工程技术

IET Renewable Power Generation Pub Date : 2025-07-15 DOI: 10.1049/rpg2.70102

Saima Ali, Laiq Khan, Saghir Ahmad, Zahid Ullah

{"title":"Resilient Secondary Distributed Model Predictive Control for Autonomous Microgrid Against Cyber Threats","authors":"Saima Ali, Laiq Khan, Saghir Ahmad, Zahid Ullah","doi":"10.1049/rpg2.70102","DOIUrl":"10.1049/rpg2.70102","url":null,"abstract":"This paper aims to present a novel framework for enhancing the cyber-resilience of microgrids (MGs) by integrating consensus-based distributed model predictive control (DMPC) with a residual-based Luenberger sliding mode observer (LSMO). The proposed framework uniquely combines the capability of DMPC for coordinated control among distributed generators (DG) with the robust anomaly detection mechanism of LSMO to ensure operational stability and security. This integration enables the system to detect and respond effectively to both stealthy and false data injection (FDI) attacks while minimizing computational complexity. Extensive simulations demonstrate the ability of the framework to mitigate the impact of cyber-attacks, ensuring voltage and frequency regulation under adversarial conditions. It has been demonstrated that the proposed framework significantly improves the detection accuracy of advanced cyber threats while maintaining system stability through efficient control coordination. In contrast to existing methods, the proposed framework maintains resilience and robust performance in the presence of cyber vulnerabilities. The efficacy of the proposed framework is validated through detailed simulation studies using the Matlab/Simulink software platform, achieving notable improvements in key performance parameters and demonstrating enhanced resilience against cyber-attacks to ensure reliable MG operations. This work contributes to advance resilient MG operations by offering an efficient solution for safeguarding critical energy infrastructure in dynamic and cyber-vulnerable environments.","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70102","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635578","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

Super-Twisting Based Sliding Mode Control of a Single-Phase Grid-Connected Transformerless Inverter for PV Systems With Leakage Current Reduction 泄漏电流减小的光伏系统单相无变压器并网逆变器超扭转滑模控制

IF 2.9 4区工程技术

IET Renewable Power Generation Pub Date : 2025-07-12 DOI: 10.1049/rpg2.70098

Muhammet Cengiz, Turgay Duman

引用次数: 0

Potential Failure Detection Study in a 7 MW Offshore Wind Turbine Using Data-Driven Three-Stage Model Based on Pitch Anglea 基于俯仰角数据驱动三级模型的7mw海上风电机组潜在故障检测研究

IF 2.9 4区工程技术

IET Renewable Power Generation Pub Date : 2025-07-12 DOI: 10.1049/rpg2.70095

Ying Tian, Hui Cao, Dapeng Yan, Jingcheng Wang, Jin Shu

{"title":"Potential Failure Detection Study in a 7 MW Offshore Wind Turbine Using Data-Driven Three-Stage Model Based on Pitch Anglea","authors":"Ying Tian, Hui Cao, Dapeng Yan, Jingcheng Wang, Jin Shu","doi":"10.1049/rpg2.70095","DOIUrl":"10.1049/rpg2.70095","url":null,"abstract":"Offshore wind energy is gaining significant global attention, making it essential to accurately predict potential faults in offshore wind turbines (OWTs) to ensure the stability of power grid operations. The pitch control system is a critical component that governs two key parameters: the blade twist angle and the pitch angle. The pitch angle, being dynamic, serves as a sensitive indicator for detecting subtle variations in blade orientation, which can reveal potential faults that may not be evident in the blade twist angle. This paper presents a three-stage, data-driven methodology for detecting potential failures in the pitch control system of specific 7 MW OWTs through dynamic pitch angle analysis. Stage 1 involves preprocessing raw supervisory control and data acquisition (SCADA) data, which includes anomaly detection and feature extraction. This process filters out obvious anomalies before training the model. Stage 2 involves developing a pitch angle prediction model that utilizes the relevant features identified in Stage 1 to forecast the pitch angle within a specified time interval. This model aims to accurately reflect the optimal operating conditions of the wind turbine by excluding data related to target faults. Stage 3 integrates the predicted pitch angles from Stage 2, which are dynamic parameters, along with selected features from Stage 1, into a model for predicting alarm signals. This model is designed to generate alarm signals for potential faults in the targeted OWT. Comparisons with six other sequential models demonstrate a higher accuracy, while reducing the number of feature extraction parameters. This indicates that the method can efficiently identify potential faults within the pitch control system by utilizing dynamic pitch angle parameters.","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70095","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144606697","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

Bayesian Network Based Evidential Reasoning for EV Charging Navigation Considering Dynamic Multiple Attributes 考虑动态多属性的电动汽车充电导航贝叶斯网络证据推理

IF 2.9 4区工程技术

IET Renewable Power Generation Pub Date : 2025-07-12 DOI: 10.1049/rpg2.70083

Jie-Hui Zheng, Zhiqiang Cao, Zhigang Li, Qing-Hua Wu

{"title":"Bayesian Network Based Evidential Reasoning for EV Charging Navigation Considering Dynamic Multiple Attributes","authors":"Jie-Hui Zheng, Zhiqiang Cao, Zhigang Li, Qing-Hua Wu","doi":"10.1049/rpg2.70083","DOIUrl":"10.1049/rpg2.70083","url":null,"abstract":"As the number of electric vehicles (EVs) gradually increases, short range and lack of charging places make it necessary for EV users to reasonably arrange their travel routes and choose charging stations (CSs) during the journey. This work first models the EV charging path schedule problem as a multi-objective optimization problem where the objective functions include the minimum mileage, travel time and total cost. As the alternatives of the charging navigation is finite and known, solving the multi-objective optimization problem can be transformed into solving the multi-attribute decision problem. Therefore, a Bayesian network based evidential reasoning (ER) algorithm (BNER), is proposed to solve the optimal EV charging navigation problem considering dynamic multiple attributes. The Bayesian network is used to construct an indicator which keeps EV users away from road intersections where congestion is forming, then the indicator will be used to aid path decision making by the ER algorithm. As a kind of multiple attributes decision making algorithm, the BNER will output a relatively satisfactory path through repeated on-line single step decision in time-varying road conditions. Finally, two simulation cases are conducted to prove the effectiveness of the proposed algorithm, with comparisons to other existing navigation methods.","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70083","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144606695","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

Optimal Operation of Multi-Energy Integrated Systems With By-Product Hydrogen Considering Gas Transmission and Source-Load Correlation 考虑输气和源负荷关联的副产氢多能集成系统优化运行

IF 2.9 4区工程技术

IET Renewable Power Generation Pub Date : 2025-07-10 DOI: 10.1049/rpg2.70096

Kun Chen, Qinghao Meng, Luona Xu, Yuan Chi, Niancheng Zhou

{"title":"Optimal Operation of Multi-Energy Integrated Systems With By-Product Hydrogen Considering Gas Transmission and Source-Load Correlation","authors":"Kun Chen, Qinghao Meng, Luona Xu, Yuan Chi, Niancheng Zhou","doi":"10.1049/rpg2.70096","DOIUrl":"10.1049/rpg2.70096","url":null,"abstract":"To improve the localised utilisation rate of by-product hydrogen, this paper proposes an optimised multi-energy integrated operation model for the chlor-alkali industrial park, comprehensively addressing the hydrogen transmission dynamics and the correlated source-load scenarios. First, to accurately depict the state changes and losses during the hydrogen distribution and transmission within the park, a hydrogen network model encompassing three components is established: a compressor with a dynamic compression ratio model, a short-term scale storage/release hydrogen storage tank model and a dynamic pipeline model. Second, recognising the complex spatio-temporal correlation coupling between power sources and diverse types of loads, a scenario generation approach based on D-Vine Copula-Markov-K-Shape (DCMKS) is proposed. Third, an optimised operational model is formulated with an objective to minimise the operational cost of the park, while both energy flow balance and gas flow balance are considered. Finally, a case study based on a chlor-alkali plant in Chongqing is used to demonstrate the effectiveness and efficiency of the proposed model.","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70096","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144598510","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

Optimal Allocation and Techno-Economic Assessment of Hybrid Energy Systems Considering Uncertainty and Reliability: A Case Study in a Remote Region 考虑不确定性和可靠性的混合能源系统优化配置与技术经济评价——以偏远地区为例

IF 2.9 4区工程技术

IET Renewable Power Generation Pub Date : 2025-07-10 DOI: 10.1049/rpg2.70094

Farnoud Sharifi, Mahdi Najafi, Abdolreza Sheikholeslami

{"title":"Optimal Allocation and Techno-Economic Assessment of Hybrid Energy Systems Considering Uncertainty and Reliability: A Case Study in a Remote Region","authors":"Farnoud Sharifi, Mahdi Najafi, Abdolreza Sheikholeslami","doi":"10.1049/rpg2.70094","DOIUrl":"10.1049/rpg2.70094","url":null,"abstract":"In recent years, there has been a growing interest in utilizing stand-alone renewable energy sources (RESs) in remote areas, primarily due to rising energy demand and the increasing cost of fossil fuels. This paper explores the implementation of a hybrid RES for a remote region in Iran, driven by rising energy demand and fossil fuel costs. The system combines a wind turbine, photovoltaic panels, a battery, and a diesel generator, optimized based on real load demand and simulation results. The study seeks to minimize the annualized cost of the system while addressing demand fluctuations, renewable energy uncertainty, and the loss of power supply probability. A modified particle swarm algorithm (MPSO) is used for system sizing and is compared with PSO and constriction coefficient PSO. The findings demonstrate that MPSO offers faster solutions and better cost efficiency. The optimal configuration identified is a PV/wind turbine/battery/diesel system, with a minimum cost of $3100.52. To reduce fossil fuel dependence, a cap on annual diesel consumption is implemented. Incorporating real weather data, the system meets all electric load demands and operational constraints, with an annual cost of $3974.50 and diesel consumption of 98.33 L per year.","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70094","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144589905","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 Two-Stage Hierarchical Energy Management System for Interconnected Microgrids Using ELM and GA 基于ELM和遗传算法的互联微电网两阶段分层能量管理系统

IF 2.9 4区工程技术

IET Renewable Power Generation Pub Date : 2025-07-10 DOI: 10.1049/rpg2.70087

Negar Dehghani Mahmoudabadi, Mehran Khalaj, Davood Jafari, Ali Taghizadeh Herat, Parisa Mousavi Ahranjani

{"title":"A Two-Stage Hierarchical Energy Management System for Interconnected Microgrids Using ELM and GA","authors":"Negar Dehghani Mahmoudabadi, Mehran Khalaj, Davood Jafari, Ali Taghizadeh Herat, Parisa Mousavi Ahranjani","doi":"10.1049/rpg2.70087","DOIUrl":"10.1049/rpg2.70087","url":null,"abstract":"This paper presents a novel hierarchical two-layer energy management system for grid-connected microgrids in the presence of uncertainty. In the first stage, each microgrid separately optimises its own local scheduling with a combination of renewable and dispatchable energy resources. In the second stage, the energy trading among the microgrids is facilitated by a DSO through the application of a Genetic Algorithm (GA) for optimising overall operational costs and system flexibility. In order to tackle the natural variability of the renewable energy resources, an extreme learning machine (ELM) is used to generate probabilistic wind and solar power generation forecasts. The optimisation problem is formulated as a mixed integer nonlinear programming (MINLP) model with continuous and binary decision variables. A 30-day case study of three interconnected microgrids under normal and contingency scenarios is tested using this proposed framework. Simulation results display significant improvements in load shedding reduction, scheduling efficiency, and system flexibility. Also, the modularity of the framework enables scaling and integration of vehicle-to-grid (V2G) technologies, making it a suitable solution for real-world smart grid deployment.","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70087","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144598511","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

Multi-Layer Attention Network With Weather Suppression Function Unmanned Aerial Vehicle Fault Inspection of Wind Farm Stations 具有天气抑制功能的多层关注网络无人机风电场站故障检测

IF 2.9 4区工程技术

IET Renewable Power Generation Pub Date : 2025-07-10 DOI: 10.1049/rpg2.70093

Zhijie Zeng, Ye Tian, Dawei Chen, Xiaojian Wang, Rui Wang, Mingyuan Shi

{"title":"Multi-Layer Attention Network With Weather Suppression Function Unmanned Aerial Vehicle Fault Inspection of Wind Farm Stations","authors":"Zhijie Zeng, Ye Tian, Dawei Chen, Xiaojian Wang, Rui Wang, Mingyuan Shi","doi":"10.1049/rpg2.70093","DOIUrl":"10.1049/rpg2.70093","url":null,"abstract":"With the continuous development of the wind power industry, the inspection work of wind farms is becoming more and more complex, and it is difficult for manual inspection to meet the actual needs. The application of unmanned aerial vehicle (UAV) intelligent inspection technology has brought a new inspection method to wind farms. However, drone inspection may be affected by many factors such as light conditions, rain, snow, fog and other weather factors at the specific site of the wind farm station. Therefore, this paper proposes a multi-layer attention neural network strategy for weather factor suppression of UAV fault inspection of wind farm stations to achieve high-precision unmanned inspection of wind farm stations. Firstly, this paper proposes a multi-layer attention network with a weather suppression function, which can effectively reduce or even eliminate the influence of weather conditions through the weather suppression module and improve the ability of the model to detect small targets through the multi-layer attention network. Based on the multi-layer attention network, this paper constructs the overall design scheme of the cloud-side intelligent inspection system of the wind farm UAV and integrates the multi-scene inspection and perception method based on the fusion of visual and point cloud information to achieve high-precision unmanned inspection. Furthermore, control experiments under normal and harsh conditions are designed to test the model, and the test results show that the model constructed in this paper has excellent performance. According to the comparison of relevant economic benefit indicators, the model in this paper takes into account both accuracy and complexity, and has good practical application value.","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70093","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144589904","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