Pub Date : 2022-05-02DOI: 10.1109/ICPS54075.2022.9773789
Suntiti Yoomak, A. Ngaopitakkul
This study investigated the feasibility of using a wind energy harvesting in a nano-grid road lighting system. A two-blade Savonius wind turbine was installed on a traffic island to generate electrical energy from vehicle movement. The wind flow velocity stemming from the movement of different vehicles and affecting the wind turbine was analysed by computational fluid dynamics method using ANSYS software. The economic feasibility of using various energy harvesting systems for solar, wind, and piezoelectric energy for a nano-grid road lighting system was evaluated. Further, the optimisation between different renewable energy sources and storage systems for the nano-grid road lighting system was performed using HOMER Pro software. The results showed that the electrical energy production using wind velocity from vehicle movement was feasible, although the wind velocity was unstable. An economic evaluation revealed that the use of piezoelectric energy systems was unfeasible owing to their high investment costs compared to their power generation. The behaviour of power generation from renewable energy and load consumption significantly affected the size of energy harvesting and storage systems. Therefore, the mismatch between solar energy and road lighting system consumption increased the size of solar and energy storage systems, leading to low economic feasibility. In contrast, the hybrid solar–wind system demonstrated great economic feasibility.
{"title":"Feasibility Study of Using Energy Harvesting Systems in Terms of Energy production and Economic Evaluation for a Nanogrid Road Lighting System","authors":"Suntiti Yoomak, A. Ngaopitakkul","doi":"10.1109/ICPS54075.2022.9773789","DOIUrl":"https://doi.org/10.1109/ICPS54075.2022.9773789","url":null,"abstract":"This study investigated the feasibility of using a wind energy harvesting in a nano-grid road lighting system. A two-blade Savonius wind turbine was installed on a traffic island to generate electrical energy from vehicle movement. The wind flow velocity stemming from the movement of different vehicles and affecting the wind turbine was analysed by computational fluid dynamics method using ANSYS software. The economic feasibility of using various energy harvesting systems for solar, wind, and piezoelectric energy for a nano-grid road lighting system was evaluated. Further, the optimisation between different renewable energy sources and storage systems for the nano-grid road lighting system was performed using HOMER Pro software. The results showed that the electrical energy production using wind velocity from vehicle movement was feasible, although the wind velocity was unstable. An economic evaluation revealed that the use of piezoelectric energy systems was unfeasible owing to their high investment costs compared to their power generation. The behaviour of power generation from renewable energy and load consumption significantly affected the size of energy harvesting and storage systems. Therefore, the mismatch between solar energy and road lighting system consumption increased the size of solar and energy storage systems, leading to low economic feasibility. In contrast, the hybrid solar–wind system demonstrated great economic feasibility.","PeriodicalId":428784,"journal":{"name":"2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I&CPS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129210735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-02DOI: 10.1109/ICPS54075.2022.9773857
Md. Nasmus Sakib Khan Shabbir, Xiaodong Liang, S. Chakrabarti
To maximize the reactive power support from a wind power plant (WPP) and maintain the power factor (PF) at the point of interconnection (POI) within acceptable limits, an adaptive droop coefficient-based WPP controller is proposed in this paper. The controller consists of a central WPP controller and a local wind turbine generator (WTG) controller. An integrated power factor controller enables the central WPP controller to regulate the power factor at the POI under normal operation. An updated droop coefficient model considering the depth of voltage deviations and the range of reactive power capability enables the controller to push the WTG more towards its maximum reactive power limit. For accurate estimation of the maximum reactive power capability, a comprehensive model considering a wide range of limiting factors has been used. To ensure faster and robust operation, both the central WPP controller and local WTG controller are operated in the voltage control mode. Additional reactive power is exported from the grid side converter (GSC) through a developed GSC controller. The effectiveness of the proposed controller is validated through case studies in MATLAB/Simulink environment.
{"title":"An Adaptive Droop Coefficient Based Voltage Control Approach for Wind Power Plants through Enhanced Reactive Power Support","authors":"Md. Nasmus Sakib Khan Shabbir, Xiaodong Liang, S. Chakrabarti","doi":"10.1109/ICPS54075.2022.9773857","DOIUrl":"https://doi.org/10.1109/ICPS54075.2022.9773857","url":null,"abstract":"To maximize the reactive power support from a wind power plant (WPP) and maintain the power factor (PF) at the point of interconnection (POI) within acceptable limits, an adaptive droop coefficient-based WPP controller is proposed in this paper. The controller consists of a central WPP controller and a local wind turbine generator (WTG) controller. An integrated power factor controller enables the central WPP controller to regulate the power factor at the POI under normal operation. An updated droop coefficient model considering the depth of voltage deviations and the range of reactive power capability enables the controller to push the WTG more towards its maximum reactive power limit. For accurate estimation of the maximum reactive power capability, a comprehensive model considering a wide range of limiting factors has been used. To ensure faster and robust operation, both the central WPP controller and local WTG controller are operated in the voltage control mode. Additional reactive power is exported from the grid side converter (GSC) through a developed GSC controller. The effectiveness of the proposed controller is validated through case studies in MATLAB/Simulink environment.","PeriodicalId":428784,"journal":{"name":"2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I&CPS)","volume":"1 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122172217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-02DOI: 10.1109/ICPS54075.2022.9773870
K. Subramaniam, M. Illindala
Several types of hidden faults, like arcing and leakage faults along with the short circuit faults, are common in spacecraft power systems. They pose severe challenges threatening the mission success. In this paper, a multi-layered ring bus dc microgrid architecture is used for the design of space exploration vehicle and surface power systems, due to its enhanced reliability of critical loads and high-power density. Layer interconnecting intelligent three tie contactor units (ICUs) are proposed at every microgrid layer interconnecting nodes, which share the status of their contactors with all the local ICUs and source converters in its layer. Using this information, the local ICUs installed at each node in a microgrid layer use a peer-to-peer communication based adaptive protection scheme to detect and quickly isolate any hidden high impedance or short circuit fault in its layer. The proposed protection scheme is tested with the simulation of multiple fault scenarios in the microgrid using the MATLAB model.
{"title":"Intelligent Three Tie Contactor Switch Unit based Protection for Multi-Layered Ring-Bus DC Microgrids","authors":"K. Subramaniam, M. Illindala","doi":"10.1109/ICPS54075.2022.9773870","DOIUrl":"https://doi.org/10.1109/ICPS54075.2022.9773870","url":null,"abstract":"Several types of hidden faults, like arcing and leakage faults along with the short circuit faults, are common in spacecraft power systems. They pose severe challenges threatening the mission success. In this paper, a multi-layered ring bus dc microgrid architecture is used for the design of space exploration vehicle and surface power systems, due to its enhanced reliability of critical loads and high-power density. Layer interconnecting intelligent three tie contactor units (ICUs) are proposed at every microgrid layer interconnecting nodes, which share the status of their contactors with all the local ICUs and source converters in its layer. Using this information, the local ICUs installed at each node in a microgrid layer use a peer-to-peer communication based adaptive protection scheme to detect and quickly isolate any hidden high impedance or short circuit fault in its layer. The proposed protection scheme is tested with the simulation of multiple fault scenarios in the microgrid using the MATLAB model.","PeriodicalId":428784,"journal":{"name":"2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I&CPS)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114919890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-02DOI: 10.1109/ICPS54075.2022.9773884
Hohyeon Han, Seunghwan Kim, Sungsan Choi, Junhyun Park, Tacklim Lee, Sanguk Park, Sehyun Park
Recently, greenhouse gas emissions have reached their highest level, and many policies are being pursued worldwide. In order to cope with the climate crisis, we are pursuing strategies such as energy conversion and carbon emission reduction, creating a low-carbon industrial ecosystem, and strengthening the carbon neutral system. This paper presented the simulation method and study for the optimal reduction of carbon emissions in residential areas by analyzing data on carbon emissions from different energy sources and adjusting the ratio of use by energy sources. Each energy source consists of simulation of adjusting the hourly carbon emissions and the ratio of use by energy source according to the amount of energy generated and generated. The reduction of carbon emissions per area was analyzed by adjusting the ratio of power generation and carbon emissions by energy source. By reducing carbon through this method, we suggested alternatives and realizations for carbon neutrality.
{"title":"Optimal Energy Use Ratio Adjustment Simulation to Reduce Carbon Emissions","authors":"Hohyeon Han, Seunghwan Kim, Sungsan Choi, Junhyun Park, Tacklim Lee, Sanguk Park, Sehyun Park","doi":"10.1109/ICPS54075.2022.9773884","DOIUrl":"https://doi.org/10.1109/ICPS54075.2022.9773884","url":null,"abstract":"Recently, greenhouse gas emissions have reached their highest level, and many policies are being pursued worldwide. In order to cope with the climate crisis, we are pursuing strategies such as energy conversion and carbon emission reduction, creating a low-carbon industrial ecosystem, and strengthening the carbon neutral system. This paper presented the simulation method and study for the optimal reduction of carbon emissions in residential areas by analyzing data on carbon emissions from different energy sources and adjusting the ratio of use by energy sources. Each energy source consists of simulation of adjusting the hourly carbon emissions and the ratio of use by energy source according to the amount of energy generated and generated. The reduction of carbon emissions per area was analyzed by adjusting the ratio of power generation and carbon emissions by energy source. By reducing carbon through this method, we suggested alternatives and realizations for carbon neutrality.","PeriodicalId":428784,"journal":{"name":"2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I&CPS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128522162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Electricity Price Forecasting (EPF) is essential to the bidding strategy formulation and the market operation. However, lack of data and volatility of power generation have put forward new challenges for EPF. To address this problem, we propose an online self-adaptive forecasting method based on random forests. Our approach takes possible fluctuations of the market into consideration, and adapts to them by maintaining training sets of different size. A case study using actual electricity market data has shown that our proposed approach obtains higher accuracy as well as sheds light on possible concept drift in the market.
{"title":"Electricity Market Price Forecasting for a High Renewable Penetrated Power System via Random Forest","authors":"Keqi Xu, Beibei Sun, Peng Wang, Zhizhong Zhu, Huidi Tang","doi":"10.1109/ICPS54075.2022.9773839","DOIUrl":"https://doi.org/10.1109/ICPS54075.2022.9773839","url":null,"abstract":"The Electricity Price Forecasting (EPF) is essential to the bidding strategy formulation and the market operation. However, lack of data and volatility of power generation have put forward new challenges for EPF. To address this problem, we propose an online self-adaptive forecasting method based on random forests. Our approach takes possible fluctuations of the market into consideration, and adapts to them by maintaining training sets of different size. A case study using actual electricity market data has shown that our proposed approach obtains higher accuracy as well as sheds light on possible concept drift in the market.","PeriodicalId":428784,"journal":{"name":"2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I&CPS)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122124943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This work proposed a model and the procedures of deterministic and probabilistic forecasts, e.g., hour-ahead and day-ahead, for wind power generation. The contents of this research include numerical weather prediction, data pre-processing technique, and forecasting models using artificial intelligence methods. Regarding the inputs of the model, we had considered three kinds of NWP wind speeds, generated by the Central Weather Bureau based on three atmospheric models, namely WRFD, RWRF and WEPS, and historical wind power generation. The measured wind speeds, out of an anemometer tower, were used to compare with the NWP wind speeds to help us select the least error time combination. Regarding data pre-processing, NWP wind-speed correction based on the height of wind turbines and PCA and EMD for exacting wind-speed feature had been tested. As for the forecast model, we used artificial neural network and XGBoost to predict the generation of wind power, and a number of error indexes had been used to evaluate the performance of the forecasts. The empirical data from a wind farm in Taiwan verifies the accuracy of the proposed method. What worth mentioning, the importance of model selection, numerical weather prediction, and data pre-processing is self-evident.
{"title":"Deterministic and Probabilistic Wind Power Forecasts by Considering Various Atmospheric Models and Feature Engineering Approaches","authors":"Yuan-Kang Wu, Cheng-Liang Huang, Sheng-Hong Wu, Jing-Shan Hong, Hui-Ling Chang","doi":"10.1109/ICPS54075.2022.9773790","DOIUrl":"https://doi.org/10.1109/ICPS54075.2022.9773790","url":null,"abstract":"This work proposed a model and the procedures of deterministic and probabilistic forecasts, e.g., hour-ahead and day-ahead, for wind power generation. The contents of this research include numerical weather prediction, data pre-processing technique, and forecasting models using artificial intelligence methods. Regarding the inputs of the model, we had considered three kinds of NWP wind speeds, generated by the Central Weather Bureau based on three atmospheric models, namely WRFD, RWRF and WEPS, and historical wind power generation. The measured wind speeds, out of an anemometer tower, were used to compare with the NWP wind speeds to help us select the least error time combination. Regarding data pre-processing, NWP wind-speed correction based on the height of wind turbines and PCA and EMD for exacting wind-speed feature had been tested. As for the forecast model, we used artificial neural network and XGBoost to predict the generation of wind power, and a number of error indexes had been used to evaluate the performance of the forecasts. The empirical data from a wind farm in Taiwan verifies the accuracy of the proposed method. What worth mentioning, the importance of model selection, numerical weather prediction, and data pre-processing is self-evident.","PeriodicalId":428784,"journal":{"name":"2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I&CPS)","volume":"54 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123423884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As the penetration of photovoltaic (PV) solar generation increases, numerous residential and commercial solar PV systems without meters are being installed. The majority of these systems, however, are not monitored by power system operators. Therefore, the uncertainty of net load owing to these invisible solar power generation will raise additional challenges for power system operation. To reduce the above-mentioned impact, this work proposes a novel method to estimate the total solar power generation in a large region from a small representative subset. The proposed method is capable of capturing all relevant information that assists in the identification of representative subsets. Moreover, different optimization algorithms are utilized and evaluated to select the optimal number of clusters and representative subsets. As a case study, the power generation of 166 PV sites in Taiwan was collected and analyzed. The proposed method demonstrates a significant improvement in estimating the aggregated power generation compared to other existing studies.
{"title":"A Novel Data-Driven Method to Estimate Invisible Solar Power Generation: A Case Study in Taiwan","authors":"Thi Bich Phuong Nguyen, Yuan-Kang Wu, Manh-Hai Pham","doi":"10.1109/ICPS54075.2022.9773788","DOIUrl":"https://doi.org/10.1109/ICPS54075.2022.9773788","url":null,"abstract":"As the penetration of photovoltaic (PV) solar generation increases, numerous residential and commercial solar PV systems without meters are being installed. The majority of these systems, however, are not monitored by power system operators. Therefore, the uncertainty of net load owing to these invisible solar power generation will raise additional challenges for power system operation. To reduce the above-mentioned impact, this work proposes a novel method to estimate the total solar power generation in a large region from a small representative subset. The proposed method is capable of capturing all relevant information that assists in the identification of representative subsets. Moreover, different optimization algorithms are utilized and evaluated to select the optimal number of clusters and representative subsets. As a case study, the power generation of 166 PV sites in Taiwan was collected and analyzed. The proposed method demonstrates a significant improvement in estimating the aggregated power generation compared to other existing studies.","PeriodicalId":428784,"journal":{"name":"2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I&CPS)","volume":"6 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122980941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-02DOI: 10.1109/ICPS54075.2022.9773801
K. Subramaniam, M. Illindala
Fault current levels vary in microgrids due to the plug-and-play nature of distributed energy resources (DERs) having different operating modes. This results in maloperation of time-graded overcurrent relay-based protection schemes in an ac microgrid. A higher penetration of DERs or microgrid islanding reduces the fault current contribution from the upstream section of feeder. This condition disrupts the coordination between protective devices operating with pre-defined I-t curves. To address such protection mis-coordination issues, a novel protection scheme that integrates an intelligent three tie contactor unit (ICU) at each DER node is proposed. The ICUs facilitate detecting the operating mode and network topology through their in-built peer-to-peer communication capability. Strategically, each ICU estimates the fault current level in its protection zone and autonomously updates the I-t curves of associated reclosers/breakers. The ICUs limit the synchronous generator-based DERs infeed at the zone of fault and facilitate the inverter-based DERs to ride-through while operating in volt-reactive power mode. It would ensure effectiveness of the existing time-graded overcurrent-based protection coordination for selectively isolating the fault. After the selective fault isolation, the local DERs re-synchronize and operate in parallel with the rest of microgrid system.
{"title":"Intelligent Three Tie Contactor Switch Unit based Fault Detection and Isolation in AC Microgrids","authors":"K. Subramaniam, M. Illindala","doi":"10.1109/ICPS54075.2022.9773801","DOIUrl":"https://doi.org/10.1109/ICPS54075.2022.9773801","url":null,"abstract":"Fault current levels vary in microgrids due to the plug-and-play nature of distributed energy resources (DERs) having different operating modes. This results in maloperation of time-graded overcurrent relay-based protection schemes in an ac microgrid. A higher penetration of DERs or microgrid islanding reduces the fault current contribution from the upstream section of feeder. This condition disrupts the coordination between protective devices operating with pre-defined I-t curves. To address such protection mis-coordination issues, a novel protection scheme that integrates an intelligent three tie contactor unit (ICU) at each DER node is proposed. The ICUs facilitate detecting the operating mode and network topology through their in-built peer-to-peer communication capability. Strategically, each ICU estimates the fault current level in its protection zone and autonomously updates the I-t curves of associated reclosers/breakers. The ICUs limit the synchronous generator-based DERs infeed at the zone of fault and facilitate the inverter-based DERs to ride-through while operating in volt-reactive power mode. It would ensure effectiveness of the existing time-graded overcurrent-based protection coordination for selectively isolating the fault. After the selective fault isolation, the local DERs re-synchronize and operate in parallel with the rest of microgrid system.","PeriodicalId":428784,"journal":{"name":"2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I&CPS)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116465842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-02DOI: 10.1109/ICPS54075.2022.9773921
Chujie Zeng, W. Qiu, Weikang Wang, Kaiqi Sun, Chang Chen, Lakshmi Sundaresh, Yilu Liu
Power system disturbances can damage electrical components or even collapse an interconnected power grid. The accurate estimation for the disturbance magnitude is critical in ensuring the reliability of the power grid and protecting electrical components. To address this issue, this paper proposes a machine learning approach to estimate the disturbance magnitude. This approach combines the estimations of the conventional approaches to provide a more accurate estimation. Evaluated with the confirmed cases in western interconnection and field-collected measurements from FNET/GridEye, the proposed method achieves 91.2% accuracy on magnitude estimation, which is 7% better than the conventional approaches. Moreover, the proposed method does not require a complex system topology, which makes it adaptive to various sizes of power systems.
{"title":"Disturbance Magnitude Estimation: MLP-based Fusion Approach for Bulk Power Systems","authors":"Chujie Zeng, W. Qiu, Weikang Wang, Kaiqi Sun, Chang Chen, Lakshmi Sundaresh, Yilu Liu","doi":"10.1109/ICPS54075.2022.9773921","DOIUrl":"https://doi.org/10.1109/ICPS54075.2022.9773921","url":null,"abstract":"Power system disturbances can damage electrical components or even collapse an interconnected power grid. The accurate estimation for the disturbance magnitude is critical in ensuring the reliability of the power grid and protecting electrical components. To address this issue, this paper proposes a machine learning approach to estimate the disturbance magnitude. This approach combines the estimations of the conventional approaches to provide a more accurate estimation. Evaluated with the confirmed cases in western interconnection and field-collected measurements from FNET/GridEye, the proposed method achieves 91.2% accuracy on magnitude estimation, which is 7% better than the conventional approaches. Moreover, the proposed method does not require a complex system topology, which makes it adaptive to various sizes of power systems.","PeriodicalId":428784,"journal":{"name":"2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I&CPS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121562494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-02DOI: 10.1109/ICPS54075.2022.9773828
Juan David Gordill, David F. Celeita, G. Ramos
This work presents a fault location method in distribution systems based on neural networks using a phase-angle jump as the model’s single input. The IEEE 34 nodes system was used. Different fault scenarios have been considered to train ANN models including various incipient angles, fault types, fault resistance values, and various fault distances that typically affect a fault location algorithm’s accuracy. Different load conditions were not considered in this particular study. Nine different models were trained specifically with particular fault types and fault resistance values and one model was trained with all fault scenarios regardless of the latter obtaining the best performance with three different models trained specifically for locating each fault type considered.
{"title":"A novel fault location method for distribution systems using phase-angle jumps based on neural networks","authors":"Juan David Gordill, David F. Celeita, G. Ramos","doi":"10.1109/ICPS54075.2022.9773828","DOIUrl":"https://doi.org/10.1109/ICPS54075.2022.9773828","url":null,"abstract":"This work presents a fault location method in distribution systems based on neural networks using a phase-angle jump as the model’s single input. The IEEE 34 nodes system was used. Different fault scenarios have been considered to train ANN models including various incipient angles, fault types, fault resistance values, and various fault distances that typically affect a fault location algorithm’s accuracy. Different load conditions were not considered in this particular study. Nine different models were trained specifically with particular fault types and fault resistance values and one model was trained with all fault scenarios regardless of the latter obtaining the best performance with three different models trained specifically for locating each fault type considered.","PeriodicalId":428784,"journal":{"name":"2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I&CPS)","volume":"238 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121309994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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