Chris Wembridge;Mark Davies;James Lord;Evan Franklin;Sarah Lyden;Michael Negnevitsky
{"title":"Fast Fault-Tolerant Grid Frequency Measurement","authors":"Chris Wembridge;Mark Davies;James Lord;Evan Franklin;Sarah Lyden;Michael Negnevitsky","doi":"10.1109/OAJPE.2024.3438153","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3438153","url":null,"abstract":"As power systems adopt greater levels of asynchronous generation, operators increasingly need to accurately monitor and manage their systems. With inverter-based generation progressively displacing traditional synchronous generators, power systems generally experience increased rate of change of grid frequency and wider propagation of voltage disturbances after a network contingency event. Inverter-based resources are now being leveraged to mitigate larger frequency disturbances, by delivering fast frequency control ancillary services. For this to be effective, accurate and robust, fast and fault-tolerant grid frequency measurements are needed. Commonly deployed frequency measurement techniques are susceptible to significant measurement error when exposed to unbalanced faults and frequency deviations. More robust techniques for measuring frequency are thus needed. This paper describes in detail a measurement strategy that extracts the continuous phase angle of the positive phase sequence phasor, from voltage signals. The method is demonstrated to provide robust measurements in the presence of simultaneously and rapidly varying voltage and frequency. From real-world measurements, using the Tasmanian power system as a case-study, the method is shown to be equivalent to or outperform measurement devices currently deployed in power systems. This paper provides all necessary control block diagrams required for integration into various modelling packages and frequency measurement devices.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"373-382"},"PeriodicalIF":3.3,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10623224","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141993935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Detecting Anomaly Classification Using PCA-Kmeans and Ensembled Classifier for Wind Turbines","authors":"Prince Waqas Khan;Yung-Cheol Byun","doi":"10.1109/OAJPE.2024.3437414","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3437414","url":null,"abstract":"Monitoring wind turbine performance is vital for ensuring wind turbines’ safe, efficient, and cost-effective operation over time. Using principal component analysis (PCA), k-means clustering for labeling, and an ensemble classifier for finding outliers, this study suggests a new way to find anomalies in wind turbines. The primary objective is to improve the precision of anomaly detection in wind turbines by leveraging machine-learning techniques. The proposed methodology utilizes the output of the PCA-Kmeans model to label supervisory control and data acquisition (SCADA) data. Furthermore, a stacking ensemble classifier is employed to refine the model’s precision. Our proposed model achieved a classification accuracy of 99%, which is a significant improvement compared to existing approaches. The significance of this study lies in its potential to enable more efficient wind turbine operation by identifying and resolving anomalies that may reduce their performance. This can ultimately contribute to achieving a sustainable and renewable energy future.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"349-361"},"PeriodicalIF":3.3,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10621021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141973524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Synchronization and Rebound Effects in Residential Loads","authors":"Nora Agah;Eve Tsybina;Viswadeep Lebakula;Justin Hill;Jeff Munk;Helia Zandi","doi":"10.1109/OAJPE.2024.3432389","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3432389","url":null,"abstract":"Increasing fuel prices and capacity investment deferral place an increasing demand for peak reduction from distribution level systems. Residential and commercial devices, such as HVAC systems and water heaters, are increasingly involved in load control programs, and their use may generate synchronization and rebound effects, such as artificial peaks caused by device optimization. While there have been concerns over device synchronization, few studies quantify the extent of this effect with numerical values. In this study, we attempt to investigate whether control efforts result in device synchronization or rebound effects. We focus on three clustering methods – Ward’s clustering, Euclidean K-means, and Density-based spatial clustering of applications with noise – to evaluate the extent of synchronization of a fleet of water heaters and HVAC systems in Atlanta, Georgia. Our findings show that synchronization and rebound effects are present in the neighborhood’s water heaters, but none were found in the HVAC systems. Further, high usage water heaters are more susceptible to synchronization and rebound effects.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"676-689"},"PeriodicalIF":3.3,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10606292","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142875075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Holistic Approach to the Efficient Estimation of Operational Flexibility From Distributed Resources","authors":"Nikolaos Savvopoulos;Nikos Hatziargyriou;Hannu Laaksonen","doi":"10.1109/OAJPE.2024.3429390","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3429390","url":null,"abstract":"The integration of Distributed Energy Resources (DER) like renewable generation into the power system has increased the need to develop effective strategies for procurement of flexibility services from these distribution network connected resources. In order to realize the flexibility potential of DERs to support flexibility needs of the system operators, the aggregated available flexibility at the interconnection point between transmission and distribution system needs to be estimated. This paper presents a novel optimization-based method to estimate the time-dependent flexibility at a primary distribution substation while accounting for the uncertainty of renewable generation. The proposed approach integrates the stochasticity of the flexibility resources using a scenario-based robust optimization and incorporates the intertemporal constraints of DER into the estimation process, ensuring a realistic representation of the flexibility capability over time. The scenarios are derived through sampling from a probability distribution of the renewable energy forecasts. This process utilizes a joint probability distribution and copulas to account for the temporal and spatial correlation among the renewable energy sources of the same region. Based on the joint hourly probability of the different scenarios a robust solution is finally obtained according to the assumed confidence level.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"325-337"},"PeriodicalIF":3.3,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10599483","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141965981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Quantifying Stability in Inverter-Based Weak Grids in the Presence of Synchronous Condensers","authors":"Sajjad Hadavi;Nabil Mohammed;Ali Mehrizi-Sani;Behrooz Bahrani","doi":"10.1109/OAJPE.2024.3428365","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3428365","url":null,"abstract":"The high penetration of renewable energy resources, integrated via power electronic inverters, into weak and low-inertia grids has led to the emergence of new challenges within power systems. The absence of native inertia in inverter-based resources (IBRs), in contrast to fossil-fuel-based generators, can result in sustained oscillations and instability. Synchronous Condensers (SynCons) are being considered as a reborn technology to address the challenges associated with system strengthening and inertia support in IBR-dominant power systems. Despite the well-established nature of SynCons, an additional assessment is necessary to analyze the stability of a weak grid with a high penetration of renewable resources, particularly in the presence of SynCons. This paper proposes a quantitative index for the stability analysis of a system incorporating black-boxed IBRs and SynCons. The proposed index is derived from impedance-based stability analysis. The impact of a SynCon on the proposed stability index is evaluated in a single-machine infinite-bus system, and its accuracy is further verified in an IEEE 39-bus system. Additionally, the findings are corroborated through time-domain simulation tests conducted in PSCAD/EMTDC software.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"314-324"},"PeriodicalIF":3.3,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10598181","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141966055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Binhot P. Nababan;Kevin Marojahan Banjar-Nahor;Musa Partahi Marbun;Suwarno;Nanang Hariyanto
{"title":"Switching Analysis in Hybrid OHL-Submarine Cable 500-kV Transmission System","authors":"Binhot P. Nababan;Kevin Marojahan Banjar-Nahor;Musa Partahi Marbun;Suwarno;Nanang Hariyanto","doi":"10.1109/OAJPE.2024.3425893","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3425893","url":null,"abstract":"This study focuses on analyzing switching transients in the upcoming 500 kV Java-Bali Connection (JBC) hybrid OHL and submarine cable project using DIgSILENT PowerFactory software, based on a realistic power system model. Distributed-parameter models with constant parameters of the Bergeron model are utilized. Analysis of the traveling wave effect on the line is conducted, and the integration time step based on the time of the traveling wave is carefully selected. Statistical distributions of energization are produced by varying the circuit configuration and system short-circuit power. It is found that the Switching Withstand Voltage (SWV) during the energization process remain below 1175 kV. The probability distribution is fitted to a normal distribution, with the skewness and kurtosis shown to be skewed to the right and having a lower peak than that of the normal distribution, respectively. When a three-phase short-circuit at the line breaker is induced, the rate of rise of recovery voltage (RRRV) exceeds the IEC standard envelope if only one circuit is operating. In this contribution, switching analysis during no-load energization and de-energization in the planning stage of the mixed OHL-submarine cable is examined.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"293-302"},"PeriodicalIF":3.3,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10592028","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141965197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Walter Gil-González;Oscar Danilo Montoya;Luis F. Grisales-Noreña;Fabio Andrade
{"title":"Robust Next-Day Scheduling of PV Generation Sources Supplying a Standalone DC Microgrid via a Semi-Definite Programming Model","authors":"Walter Gil-González;Oscar Danilo Montoya;Luis F. Grisales-Noreña;Fabio Andrade","doi":"10.1109/OAJPE.2024.3425374","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3425374","url":null,"abstract":"This study focuses on optimizing the efficient operation of standalone direct-current (DC) microgrids with photovoltaic (PV) sources using semi-definite programming (SDP) optimization. The PV source operation model is formulated as a nonlinear programming (NLP) problem with the objective of minimizing daily energy losses and reducing CO2 emissions compared to diesel generators. Transforming the NLP model into convex optimization involves a linear matrix model that combines positive semi-definite matrices with an affine space. This approach enhances robustness by incorporating uncertainties in demand and PV source power. The robust SDP model employs a min–max strategy for worst-case scenario energy management dispatch (EMD). Evaluating a 27-bus standalone DC microgrid, the SDP model outperforms random-based algorithms by achieving global optima in both objectives. Under uncertainties, the energy loss objective increases by 21.6706% with demand uncertainty, 0.3997% with PV source uncertainty, and 22.2009% with both. Meanwhile, the CO2 emissions objective increases by 11.9184%, 1.8237%, and 14.0045%, respectively. Additional simulations on an 85-node DC network confirm the efficacy of SDP in worst-case scenario EMD. All simulations utilized MATLAB’s Yalmip tool with the Mosek solver.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"446-456"},"PeriodicalIF":3.3,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10589696","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142173981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Small-Signal Stability Analysis for Large-Scale Power Electronics- Based Power Systems","authors":"Liang Qiao;Yaosuo Xue;Le Kong;Fei Wang;Nupur","doi":"10.1109/OAJPE.2024.3421307","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3421307","url":null,"abstract":"This paper aims to develop a small-signal stability analysis method for large-scale power electronics-based power systems. For this purpose, the nodal admittance matrix (NAM)-based approach is recognized as the most precise technique. However, the original implementation of NAM method is tailored for the entire system, thereby correlating the matrix dimensions with the number of converters present in the system. Consequently, it becomes impractical to directly apply the original NAM method to a large-scale system. To address this challenge, this paper introduces a novel system-partitioning-based NAM approach. In this method, the large-scale system is decomposed into several subsystems first, followed by analysis at the interconnection level. The general concept, the detailed mathematical derivation, and the applications of the proposed method to a 6-converter system and a modified 140-bus NPCC system are presented. It has been validated that the proposed approach can significantly reduce computational burden while simultaneously preserving the accuracy for large-scale PE-rich power systems.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"280-292"},"PeriodicalIF":3.3,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10585300","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141602521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. A. R. R. Jayasinghe;J. H. E. Malindi;R. M. A. M. Rajapaksha;V. Logeeshan;Chathura Wanigasekara
{"title":"Classification and Localization of Faults in AC Microgrids Through Discrete Wavelet Transform and Artificial Neural Networks","authors":"J. A. R. R. Jayasinghe;J. H. E. Malindi;R. M. A. M. Rajapaksha;V. Logeeshan;Chathura Wanigasekara","doi":"10.1109/OAJPE.2024.3422387","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3422387","url":null,"abstract":"The widespread integration of renewable energy sources to the main electrical grids has led to the increased adoption of AC microgrids. However, the protection of AC microgrids is a challenging task due to inverter interfaces, bidirectional power flow, multiple modes of operation and the requirement for selective phase tripping. This paper presents an innovative artificial neural network (ANN) based approach for fast and accurate identification and localization of symmetrical and asymmetrical faults occurring in the distribution networks of AC microgrids. In the proposed methodology, the three phase and the neutral currents which are sampled at either ends of the distribution lines, undergo discrete wavelet transform to extract the features exhibited during faults in the network. These features are used by two neural networks for classification and localization of the fault. To achieve high accuracy and computational efficiency, the network architectures of the ANNs are optimized, and the extracted features contain the detailed information required for ANNs to clearly distinguish different fault types and locations. A comprehensive evaluation and validation reveal that the proposed scheme accurately and efficiently classifies and localizes faults in AC microgrids. The existing research gap of fault localization in AC microgrids is also addressed through this approach.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"303-313"},"PeriodicalIF":3.3,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10583937","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141964858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Amir Reza Nikzad;Amr Adel Mohamed;Bala Venkatesh;John Penaranda
{"title":"Estimating Aggregate Capacity of Connected DERs and Forecasting Feeder Power Flow With Limited Data Availability","authors":"Amir Reza Nikzad;Amr Adel Mohamed;Bala Venkatesh;John Penaranda","doi":"10.1109/OAJPE.2024.3413606","DOIUrl":"https://doi.org/10.1109/OAJPE.2024.3413606","url":null,"abstract":"By 2050, zero-carbon electric power systems will rely heavily on innumerable distributed energy resources (DERs), such as wind and solar. Accurate estimation of the aggregate connected DER capacity becomes pivotal in such a landscape. However, forecasting, power flow analysis, and optimization of feeders for operational decision-making by individually modeling each of these numerous renewables in the absence of complete information are operationally challenging and technically impractical. In response, we introduce a method to accurately estimate the aggregate capacities of the connected DERs on distribution feeders and a near-term forecasting method. Our proposal comprises: 1) ovel deep learning-based architecture with a few convolutional neural network and long short-term memory (CNN-LSTM) modules to represent feeder connected aggregate models of DERs and loads and associated training algorithms; 2) method for estimating aggregate capacities of connected renewables and loads; and 3) method for short-term (hourly) high-resolution forecasting. This step of estimation of the aggregate capacities of connected DERs, is a sequel to solving feeder hosting capacity problem. The method is tested using a North American utility feeder data, achieving an average accuracy of 95.56% for forecasting aggregate load power, 93.70% for feeder flow predictions, and 97.53% for estimating the aggregate capacity of DERs.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"11 ","pages":"266-279"},"PeriodicalIF":3.3,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10555337","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141435288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}