Pub Date : 2022-10-09DOI: 10.1109/IAS54023.2022.9939893
I. K. Amin, Md. Nahid Islam, Azam Jaman, Md. Kabir Hasan, Muslima Akter Bithi, M. Uddin
As the demand of electric power generation has increased vastly across the world, the requirement of upgraded schemes for efficient power extraction and bulky storage has burgeoned tantamountly. To adopt the randomness and best uti-lization of the renewable energy sources, power profile prediction and energy management of large-scale solar and wind farms are major concerns for grid operators. A bulk efficient energy storage system may eliminate the issues related to unpredictability of sustainable power sources. Mostly conventional deep cycle lead-acid battery banks are utilized to meet massive storage requirement in solar and wind farms. However, the high cost, extensive maintenance, requirement of extra space and relatively short lifetime are the major shortcomings of lead-acid batteries. On the other hand, the development of Vanadium Redox-flow battery (VRFB) makes it possible to be utilized for large-scale storage because of its viable chemical composition, compact energy density and long lifecycle. In this paper, a multiphysics model of a 8 MW-h Vanadium redox-flow battery is developed for large-scale storage. The features of the VRFB have been analyzed for variation of its key parameters. To observe the effectiveness of the proposed model, a 3 MW grid-connected hybrid renewable power system consisting of photovoltaic (PV) panels and wind turbines is simulated with proposed storage unit. The battery framework is designed in COMSOL Multiphysics platform and dynamic simulations are performed in MATLAB/Simulink en-vironment. The results show that the proposed model exhibits compatible performance in managing the energy flow from the hybrid sources towards the load by maintaining the real power demanded by the grid operator.
{"title":"Modeling and Performance Analysis of Redox-Flow Battery Unit for Large-Scale Hybrid Renewable Energy Systems","authors":"I. K. Amin, Md. Nahid Islam, Azam Jaman, Md. Kabir Hasan, Muslima Akter Bithi, M. Uddin","doi":"10.1109/IAS54023.2022.9939893","DOIUrl":"https://doi.org/10.1109/IAS54023.2022.9939893","url":null,"abstract":"As the demand of electric power generation has increased vastly across the world, the requirement of upgraded schemes for efficient power extraction and bulky storage has burgeoned tantamountly. To adopt the randomness and best uti-lization of the renewable energy sources, power profile prediction and energy management of large-scale solar and wind farms are major concerns for grid operators. A bulk efficient energy storage system may eliminate the issues related to unpredictability of sustainable power sources. Mostly conventional deep cycle lead-acid battery banks are utilized to meet massive storage requirement in solar and wind farms. However, the high cost, extensive maintenance, requirement of extra space and relatively short lifetime are the major shortcomings of lead-acid batteries. On the other hand, the development of Vanadium Redox-flow battery (VRFB) makes it possible to be utilized for large-scale storage because of its viable chemical composition, compact energy density and long lifecycle. In this paper, a multiphysics model of a 8 MW-h Vanadium redox-flow battery is developed for large-scale storage. The features of the VRFB have been analyzed for variation of its key parameters. To observe the effectiveness of the proposed model, a 3 MW grid-connected hybrid renewable power system consisting of photovoltaic (PV) panels and wind turbines is simulated with proposed storage unit. The battery framework is designed in COMSOL Multiphysics platform and dynamic simulations are performed in MATLAB/Simulink en-vironment. The results show that the proposed model exhibits compatible performance in managing the energy flow from the hybrid sources towards the load by maintaining the real power demanded by the grid operator.","PeriodicalId":193587,"journal":{"name":"2022 IEEE Industry Applications Society Annual Meeting (IAS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116127869","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 : 2022-10-09DOI: 10.1109/IAS54023.2022.9939721
P. Chiradeja, C. Pothisarn, Panu Srisuksai, Suntiti Yoomak, A. Ngaopitakkul, Natthanon Phannil
Faults in the distribution system of the Thai electrical system occur frequently. Such faults directly affect the protective equipment of the distribution system. The protective device disconnects the circuit unnecessarily on many occasions because it detects a higher current than expected. In this study, a 22-kV distribution system and a very small power plant (VSPP) were connected. The system consists of two feeders. Feeder 1 supplies electricity directly to the load; a fault was enforced in this feeder. Feeder 2 supplies electricity directly to the load; the VSPP was connected to this feeder. The fault in Feeder 1 was simulated, and the behavior of the defense system was studied. Unnecessary disconnection of the VSPP circuit took place because the high fault current caused the overcurrent protection relay to operate instantaneously. Therefore, a neutral ground resistance was installed at the VSPP transformer to reduce the fault current, extend the relay operating time to the delay range, and reduce unnecessary disconnections of the overcurrent protection relay of the VSPP. In addition, when a fault occurs in the distribution system, the faulted phase voltage decreases, whereas the non-faulted phase voltage increases. Surge arresters and voltage transformers must be able to withstand an increase in voltage. This is also explained and discussed in this paper.
{"title":"Study on Installation of Neutral Ground Resistance in Very Small Power Plant Transformer","authors":"P. Chiradeja, C. Pothisarn, Panu Srisuksai, Suntiti Yoomak, A. Ngaopitakkul, Natthanon Phannil","doi":"10.1109/IAS54023.2022.9939721","DOIUrl":"https://doi.org/10.1109/IAS54023.2022.9939721","url":null,"abstract":"Faults in the distribution system of the Thai electrical system occur frequently. Such faults directly affect the protective equipment of the distribution system. The protective device disconnects the circuit unnecessarily on many occasions because it detects a higher current than expected. In this study, a 22-kV distribution system and a very small power plant (VSPP) were connected. The system consists of two feeders. Feeder 1 supplies electricity directly to the load; a fault was enforced in this feeder. Feeder 2 supplies electricity directly to the load; the VSPP was connected to this feeder. The fault in Feeder 1 was simulated, and the behavior of the defense system was studied. Unnecessary disconnection of the VSPP circuit took place because the high fault current caused the overcurrent protection relay to operate instantaneously. Therefore, a neutral ground resistance was installed at the VSPP transformer to reduce the fault current, extend the relay operating time to the delay range, and reduce unnecessary disconnections of the overcurrent protection relay of the VSPP. In addition, when a fault occurs in the distribution system, the faulted phase voltage decreases, whereas the non-faulted phase voltage increases. Surge arresters and voltage transformers must be able to withstand an increase in voltage. This is also explained and discussed in this paper.","PeriodicalId":193587,"journal":{"name":"2022 IEEE Industry Applications Society Annual Meeting (IAS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122456264","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 : 2022-10-09DOI: 10.1109/IAS54023.2022.9939736
Paweł Pietrzak, David Malec, A. Picot, P. Maussion, Tahar Hamiti, Loucif Benmamas, P. Manfe
The presented study falls within the scope of research on multi-factor tests and lifetime prediction of insulation systems for electrical machines. It is an attempt to find an indicator of state or remaining life of an insulation system for inverter fed electric motors. Samples of twisted pairs are subjected to high temperature and inverter voltage over long periods of time. Partial Discharge Inception Voltage (PDIV) is measured over the course of their life. The article contains the description of the experimental test bench, method of PDIV measurement and a method of analysis and modeling of the obtained PDIV evolution over time. Changes of PDIV over time are observed. The found evolution of PDIV is modeled with Inverse Power Model with a prediction error of a few percent.
{"title":"Modelling of PDIV evolution over time under multiple ageing factors for insulation of inverter-fed electrical machines","authors":"Paweł Pietrzak, David Malec, A. Picot, P. Maussion, Tahar Hamiti, Loucif Benmamas, P. Manfe","doi":"10.1109/IAS54023.2022.9939736","DOIUrl":"https://doi.org/10.1109/IAS54023.2022.9939736","url":null,"abstract":"The presented study falls within the scope of research on multi-factor tests and lifetime prediction of insulation systems for electrical machines. It is an attempt to find an indicator of state or remaining life of an insulation system for inverter fed electric motors. Samples of twisted pairs are subjected to high temperature and inverter voltage over long periods of time. Partial Discharge Inception Voltage (PDIV) is measured over the course of their life. The article contains the description of the experimental test bench, method of PDIV measurement and a method of analysis and modeling of the obtained PDIV evolution over time. Changes of PDIV over time are observed. The found evolution of PDIV is modeled with Inverse Power Model with a prediction error of a few percent.","PeriodicalId":193587,"journal":{"name":"2022 IEEE Industry Applications Society Annual Meeting (IAS)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116822943","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 : 2022-10-09DOI: 10.1109/IAS54023.2022.9940050
Saad Alzahrani, Khalil Sinjari, J. Mitra
The protection of microgrids (MGs) is an emerging research issue due to integrating various levels of distributed generation (DG). Although microgrid can operate in two modes of operation: grid-connected and islanded, detecting the fault cur-rent poses a significant challenge, essentially when the microgrid operates in islanded mode. This paper presents a new approach for detecting faults in multiple protection zones utilizing a Multi-Agent System (MAS) technique and state observer. The proposed framework comprises decentralized Multi-Agents, which will communicate, interact, and exchange the data for detecting the fault through the residual current value of state observer at a given protection zone. The agents then send a trip signal to isolate/restore the faulted section. The proposed fault detection scheme has been tested and applied to an islanded microgrid configuration and demonstrated to be an effective means to detect the fault for multiple protection zones of the microgrid system.
{"title":"Multi-Agent and State Observer-Based Technique for Fault Detection of Microgrid System","authors":"Saad Alzahrani, Khalil Sinjari, J. Mitra","doi":"10.1109/IAS54023.2022.9940050","DOIUrl":"https://doi.org/10.1109/IAS54023.2022.9940050","url":null,"abstract":"The protection of microgrids (MGs) is an emerging research issue due to integrating various levels of distributed generation (DG). Although microgrid can operate in two modes of operation: grid-connected and islanded, detecting the fault cur-rent poses a significant challenge, essentially when the microgrid operates in islanded mode. This paper presents a new approach for detecting faults in multiple protection zones utilizing a Multi-Agent System (MAS) technique and state observer. The proposed framework comprises decentralized Multi-Agents, which will communicate, interact, and exchange the data for detecting the fault through the residual current value of state observer at a given protection zone. The agents then send a trip signal to isolate/restore the faulted section. The proposed fault detection scheme has been tested and applied to an islanded microgrid configuration and demonstrated to be an effective means to detect the fault for multiple protection zones of the microgrid system.","PeriodicalId":193587,"journal":{"name":"2022 IEEE Industry Applications Society Annual Meeting (IAS)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127029134","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 : 2022-10-09DOI: 10.1109/IAS54023.2022.9939768
M. Faisal, M. Hannan, P. Ker, K. Muttaqi
Microgrid (MG) concept with renewable technologies have the challenges of supplying reliable power considering the intermittent nature of the sources. Energy storage system (ESS) has become a viable solution to control the power fluctuation and thus providing the reliable power to the consumer. However, commonly used charging-discharging control techniques have the limitations of solving overcharging or over-discharging problem, fast charging capability, and rapid response time. To overcome these problems, fuzzy logic controller (FLC) has been proposed to control the charging-discharging due to its easy implementation, no mathematical calculation, and simplicity. However, existing FLC technologies have the limitations in considering the battery control parameters, and selecting the safe operating region (20% to 80%) of the battery state of charge (SOC). Therefore, this research proposes an improved FLC considering the available power from grid and distributed sources, load demand, battery SOC and temperature. To improve the performance of the controller, membership functions (MFs) of the FLC have been optimized by using genetic algorithm (GA). To prove the superiority of GA, another widely used optimization algorithm, particle swarm optimization (PSO) is applied with the same load variation. Obtained results show that, the minimum and maximum SOC level for fuzzy-GA only system has been improved compared to fuzzy only and fuzzy-PSO system. Therefore, it can be concluded that, the developed model works efficiently in controlling the charging and discharging of the battery. The authors are in progress to apply the controller system for MG connected waste water treatment plant.
{"title":"Genetic Algorithm based Fuzzy Logic Controller for Optimal Charging-Discharging of Energy Storage in Microgrid applications","authors":"M. Faisal, M. Hannan, P. Ker, K. Muttaqi","doi":"10.1109/IAS54023.2022.9939768","DOIUrl":"https://doi.org/10.1109/IAS54023.2022.9939768","url":null,"abstract":"Microgrid (MG) concept with renewable technologies have the challenges of supplying reliable power considering the intermittent nature of the sources. Energy storage system (ESS) has become a viable solution to control the power fluctuation and thus providing the reliable power to the consumer. However, commonly used charging-discharging control techniques have the limitations of solving overcharging or over-discharging problem, fast charging capability, and rapid response time. To overcome these problems, fuzzy logic controller (FLC) has been proposed to control the charging-discharging due to its easy implementation, no mathematical calculation, and simplicity. However, existing FLC technologies have the limitations in considering the battery control parameters, and selecting the safe operating region (20% to 80%) of the battery state of charge (SOC). Therefore, this research proposes an improved FLC considering the available power from grid and distributed sources, load demand, battery SOC and temperature. To improve the performance of the controller, membership functions (MFs) of the FLC have been optimized by using genetic algorithm (GA). To prove the superiority of GA, another widely used optimization algorithm, particle swarm optimization (PSO) is applied with the same load variation. Obtained results show that, the minimum and maximum SOC level for fuzzy-GA only system has been improved compared to fuzzy only and fuzzy-PSO system. Therefore, it can be concluded that, the developed model works efficiently in controlling the charging and discharging of the battery. The authors are in progress to apply the controller system for MG connected waste water treatment plant.","PeriodicalId":193587,"journal":{"name":"2022 IEEE Industry Applications Society Annual Meeting (IAS)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124246907","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 : 2022-10-09DOI: 10.1109/IAS54023.2022.9939862
Adedoyin Inaolaji, Alper Savasci, S. Paudyal, S. Kamalasadan
Volt-VAr optimization (VVO) is usually performed by a central coordinator which provides the optimal setpoints of the control devices in the network for efficient voltage regulation in active distribution networks. However, such a central control scheme is prone to a single-point failure and results in privacy concerns. Conversely, distributed optimization methods decompose the entire network into subsystems such that local controllers compute a local optimization problem and have limited communication with their neighboring control agents, thereby enhancing data dignity. This work, therefore, adopts a distributed VVO approach which is based on the alternating direction method of multipliers (ADMM). The linearized Dist3Flow model (LinDist3Flow) is used as a convex grid model and the distributed VVO minimizes voltage deviation in an unbalanced active distribution system subject to limits on voltage magnitudes and inverter active and reactive power capabilities. Case studies implemented on the IEEE-123 node system and a 2522-node system demonstrate that ADMM-based VVO converges to the same solution as that obtained from the centralized VVO, but the performance of the ADMM algorithm is sensitive to the choice of the penalty parameter. Moreover, if the centralized formulation is convex and already tractable for even large-scale feeders, then solving the distributed counterpart might not necessarily provide any computational advantage but is still desirable for reasons such as data privacy and robustness to processor failure.
{"title":"A Consensus ADMM-Based Distributed Volt-VAr Optimization for Unbalanced Distribution Networks","authors":"Adedoyin Inaolaji, Alper Savasci, S. Paudyal, S. Kamalasadan","doi":"10.1109/IAS54023.2022.9939862","DOIUrl":"https://doi.org/10.1109/IAS54023.2022.9939862","url":null,"abstract":"Volt-VAr optimization (VVO) is usually performed by a central coordinator which provides the optimal setpoints of the control devices in the network for efficient voltage regulation in active distribution networks. However, such a central control scheme is prone to a single-point failure and results in privacy concerns. Conversely, distributed optimization methods decompose the entire network into subsystems such that local controllers compute a local optimization problem and have limited communication with their neighboring control agents, thereby enhancing data dignity. This work, therefore, adopts a distributed VVO approach which is based on the alternating direction method of multipliers (ADMM). The linearized Dist3Flow model (LinDist3Flow) is used as a convex grid model and the distributed VVO minimizes voltage deviation in an unbalanced active distribution system subject to limits on voltage magnitudes and inverter active and reactive power capabilities. Case studies implemented on the IEEE-123 node system and a 2522-node system demonstrate that ADMM-based VVO converges to the same solution as that obtained from the centralized VVO, but the performance of the ADMM algorithm is sensitive to the choice of the penalty parameter. Moreover, if the centralized formulation is convex and already tractable for even large-scale feeders, then solving the distributed counterpart might not necessarily provide any computational advantage but is still desirable for reasons such as data privacy and robustness to processor failure.","PeriodicalId":193587,"journal":{"name":"2022 IEEE Industry Applications Society Annual Meeting (IAS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123522521","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 : 2022-10-09DOI: 10.1109/IAS54023.2022.9939987
Surendra Bajagain, Chuan Qin, Sanjeev Pannala, Amal Srivastava, Anamika Dubey
In contrast to traditional utility monitoring and operational tools, advanced distribution management systems (ADMS) provide the advanced operational features to monitor, secure and operate the distribution system in an integrated manner. Large-scale adoption of ADMS at utilities is in the early stage since advanced applications within ADMS environments are still evolving. The topology estimation module is one of the important and challenging ADMS application with enhanced automation. For accurate topology estimation, the topology estimator should capture both uncertainties due to load and PV injection in node measurement data. Load/PV estimation module can provide individual/disaggregated load and PV estimates and supports accurate network estimates. This paper provides a proof-of-the concept for the integration of advanced applications (Load/PV estimation and topology estimation) within an industrial ADMS environment using utility feeder data.
{"title":"Integrating Advanced Applications in Industrial ADMS for Estimating PV Resources and Topology","authors":"Surendra Bajagain, Chuan Qin, Sanjeev Pannala, Amal Srivastava, Anamika Dubey","doi":"10.1109/IAS54023.2022.9939987","DOIUrl":"https://doi.org/10.1109/IAS54023.2022.9939987","url":null,"abstract":"In contrast to traditional utility monitoring and operational tools, advanced distribution management systems (ADMS) provide the advanced operational features to monitor, secure and operate the distribution system in an integrated manner. Large-scale adoption of ADMS at utilities is in the early stage since advanced applications within ADMS environments are still evolving. The topology estimation module is one of the important and challenging ADMS application with enhanced automation. For accurate topology estimation, the topology estimator should capture both uncertainties due to load and PV injection in node measurement data. Load/PV estimation module can provide individual/disaggregated load and PV estimates and supports accurate network estimates. This paper provides a proof-of-the concept for the integration of advanced applications (Load/PV estimation and topology estimation) within an industrial ADMS environment using utility feeder data.","PeriodicalId":193587,"journal":{"name":"2022 IEEE Industry Applications Society Annual Meeting (IAS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121389321","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 : 2022-10-09DOI: 10.1109/IAS54023.2022.9940042
S. Yahyaee, P. Sreekumar, V. Khadkikar
The presence of unbalance in the load, particularly, in Islanded Microgrids is gaining increased attention recently as it introduces unbalance in both load voltage and current. The existing work in this area is mainly focused on reducing the unbalance in the load voltage or sharing the negative sequence current equally. Furthermore, most of these methods are based on the knowledge of load voltages which requires a low bandwidth communication infrastructure to send the load information to the local DG controllers. However, the low bandwidth communication increases the overall cost and reduces the reliability of system. In this paper, a decentralized control approach for Islanded Micro-grid to share the load current unbalance factors equally among distributed generation (DG) units is proposed. It is shown in the paper that in an Islanded Microgrid, the presence of unbalance in the load current effects the DG output voltages causing them to become unbalanced as well. A droop-based control approach is developed that compensates the unbalance in DG output voltages and thus, achieving equal unbalance current factor sharing. A detailed Matlab/Simulink based study is presented to validate the performance of the proposed decentralized approach.
{"title":"A Novel Decentralized Unbalance Load Sharing Approach For Islanded Microgrids","authors":"S. Yahyaee, P. Sreekumar, V. Khadkikar","doi":"10.1109/IAS54023.2022.9940042","DOIUrl":"https://doi.org/10.1109/IAS54023.2022.9940042","url":null,"abstract":"The presence of unbalance in the load, particularly, in Islanded Microgrids is gaining increased attention recently as it introduces unbalance in both load voltage and current. The existing work in this area is mainly focused on reducing the unbalance in the load voltage or sharing the negative sequence current equally. Furthermore, most of these methods are based on the knowledge of load voltages which requires a low bandwidth communication infrastructure to send the load information to the local DG controllers. However, the low bandwidth communication increases the overall cost and reduces the reliability of system. In this paper, a decentralized control approach for Islanded Micro-grid to share the load current unbalance factors equally among distributed generation (DG) units is proposed. It is shown in the paper that in an Islanded Microgrid, the presence of unbalance in the load current effects the DG output voltages causing them to become unbalanced as well. A droop-based control approach is developed that compensates the unbalance in DG output voltages and thus, achieving equal unbalance current factor sharing. A detailed Matlab/Simulink based study is presented to validate the performance of the proposed decentralized approach.","PeriodicalId":193587,"journal":{"name":"2022 IEEE Industry Applications Society Annual Meeting (IAS)","volume":"89 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116304276","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 : 2022-10-09DOI: 10.1109/IAS54023.2022.9940032
Dongsen Sun, Hanchao Liu, Maozhong Gong
This paper presents a small-signal stability analysis tool for large-scale power systems with high penetration of inverter-based resources (IBRs). Firstly, a network transfer function matrix (NTFM), which represents the information of the system topology, transmission lines, loads, IBRs locations, etc., is derived to model the entire power system network. Secondly, small-signal perturbation method is applied to obtain the sequence impedance/admittance responses of IBRs considering the frequency cross-coupling effects. With the obtained NTFM as well as IBRs' models, a multi-input, multi-output (MIMO) feedback system is constructed, and the generalized Nyquist criterion (GNC)-based stability method is employed to analyze the stability of the entire power system. Different testing cases based on a modified IEEE-14 bus system are leveraged to verify the proposed stability analysis tool.
{"title":"A Stability Analysis Tool for Bulk Power Systems Using Black-Box Models of Inverter-based Resources","authors":"Dongsen Sun, Hanchao Liu, Maozhong Gong","doi":"10.1109/IAS54023.2022.9940032","DOIUrl":"https://doi.org/10.1109/IAS54023.2022.9940032","url":null,"abstract":"This paper presents a small-signal stability analysis tool for large-scale power systems with high penetration of inverter-based resources (IBRs). Firstly, a network transfer function matrix (NTFM), which represents the information of the system topology, transmission lines, loads, IBRs locations, etc., is derived to model the entire power system network. Secondly, small-signal perturbation method is applied to obtain the sequence impedance/admittance responses of IBRs considering the frequency cross-coupling effects. With the obtained NTFM as well as IBRs' models, a multi-input, multi-output (MIMO) feedback system is constructed, and the generalized Nyquist criterion (GNC)-based stability method is employed to analyze the stability of the entire power system. Different testing cases based on a modified IEEE-14 bus system are leveraged to verify the proposed stability analysis tool.","PeriodicalId":193587,"journal":{"name":"2022 IEEE Industry Applications Society Annual Meeting (IAS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127745214","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 : 2022-10-09DOI: 10.1109/IAS54023.2022.9939804
Pablo Alejandro Parra, David F. Celeita, G. Ramos, W. Martínez, G. Chaffey
Modern Distribution Networks (DNs) are highly susceptible to faults, which affects their dependability and reliability. The operation complexity is crucial when DNs include critical infrastructure such as distributed energy resources, storage systems, charging stations and decentralized supply. FLISR (Fault Location, Isolation and Service Restoration) relies on advanced methodologies which aim to improve the quality of service with automated algorithms. This paper proposes a novel Service Restoration approach to automatically assist DNs resupply the out-of-service unfaulted customers after an event. The approach integrates Reinforcement Learning techniques in a co-simulation environment with OpenDSS. The results and contribution of this study could improve power supply quality and reliability of DNs throughout advanced Service Restoration (SR) methodologies. The idea is validated in real-time simulation to offer a performance assessment after training with co-simulated data.
{"title":"Reinforcement Learning for Service Restoration Algorithms in Distribution Networks","authors":"Pablo Alejandro Parra, David F. Celeita, G. Ramos, W. Martínez, G. Chaffey","doi":"10.1109/IAS54023.2022.9939804","DOIUrl":"https://doi.org/10.1109/IAS54023.2022.9939804","url":null,"abstract":"Modern Distribution Networks (DNs) are highly susceptible to faults, which affects their dependability and reliability. The operation complexity is crucial when DNs include critical infrastructure such as distributed energy resources, storage systems, charging stations and decentralized supply. FLISR (Fault Location, Isolation and Service Restoration) relies on advanced methodologies which aim to improve the quality of service with automated algorithms. This paper proposes a novel Service Restoration approach to automatically assist DNs resupply the out-of-service unfaulted customers after an event. The approach integrates Reinforcement Learning techniques in a co-simulation environment with OpenDSS. The results and contribution of this study could improve power supply quality and reliability of DNs throughout advanced Service Restoration (SR) methodologies. The idea is validated in real-time simulation to offer a performance assessment after training with co-simulated data.","PeriodicalId":193587,"journal":{"name":"2022 IEEE Industry Applications Society Annual Meeting (IAS)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126514559","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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