Pub Date : 2022-07-17DOI: 10.1109/PESGM48719.2022.9916676
Ratik Mittal, Zhixin Miao
Recently, inverter-based resources are being integrated into the power grid at a rapid rate. Most of these resources are grid-following inverters, where weak grid operation becomes an issue. The research focus has now shifted towards grid forming inverters, which emulate synchronous generators. Thus proper modeling and analysis are required to understand the grid forming inverters. This paper presents the nonlinear analytical model of a grid forming inverter when operating in grid-connected mode in $dq$ -domain. The developed model is validated in the time domain with the Electromagnetic Transients (EMT) test bed when the system operates under weak grid conditions. The analytical model is also used to perform the eigenvalues analysis. The EMT model is simulated in MATLAB/Simscape and the analytical model is simulated in MATLAB/Simulink. Hardware experimentation is also performed for further bench-marking with the help of laboratory scale hardware setup.
{"title":"Analytical Model of A Grid-Forming Inverter","authors":"Ratik Mittal, Zhixin Miao","doi":"10.1109/PESGM48719.2022.9916676","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9916676","url":null,"abstract":"Recently, inverter-based resources are being integrated into the power grid at a rapid rate. Most of these resources are grid-following inverters, where weak grid operation becomes an issue. The research focus has now shifted towards grid forming inverters, which emulate synchronous generators. Thus proper modeling and analysis are required to understand the grid forming inverters. This paper presents the nonlinear analytical model of a grid forming inverter when operating in grid-connected mode in $dq$ -domain. The developed model is validated in the time domain with the Electromagnetic Transients (EMT) test bed when the system operates under weak grid conditions. The analytical model is also used to perform the eigenvalues analysis. The EMT model is simulated in MATLAB/Simscape and the analytical model is simulated in MATLAB/Simulink. Hardware experimentation is also performed for further bench-marking with the help of laboratory scale hardware setup.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"28 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129373343","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9916914
Mansi Girdhar, Junho Hong, Yongsik You, T. Song
Safe and reliable electric vehicle charging stations (EVCSs) have become imperative in an intelligent transportation infrastructure. Over the years, there has been a rapid increase in the deployment of EVCSs to address the upsurging charging demands. However, advances in information and communication technologies (ICT) have rendered this cyber-physical system (CPS) vulnerable to suffering cyber threats, thereby destabilizing the charging ecosystem and even the entire electric grid infrastructure. This paper develops an advanced cybersecurity framework, where STRIDE threat modeling is used to identify potential vulnerabilities in an EVCS. Further, the weighted attack defense tree approach is employed to create multiple attack scenarios, followed by developing Hidden Markov Model (HMM) and Partially Observable Monte-Carlo Planning (POMCP) algorithms for modeling the security attacks. Also, potential mitigation strategies are suggested for the identified threats.
{"title":"Machine Learning-Enabled Cyber Attack Prediction and Mitigation for EV Charging Stations","authors":"Mansi Girdhar, Junho Hong, Yongsik You, T. Song","doi":"10.1109/PESGM48719.2022.9916914","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9916914","url":null,"abstract":"Safe and reliable electric vehicle charging stations (EVCSs) have become imperative in an intelligent transportation infrastructure. Over the years, there has been a rapid increase in the deployment of EVCSs to address the upsurging charging demands. However, advances in information and communication technologies (ICT) have rendered this cyber-physical system (CPS) vulnerable to suffering cyber threats, thereby destabilizing the charging ecosystem and even the entire electric grid infrastructure. This paper develops an advanced cybersecurity framework, where STRIDE threat modeling is used to identify potential vulnerabilities in an EVCS. Further, the weighted attack defense tree approach is employed to create multiple attack scenarios, followed by developing Hidden Markov Model (HMM) and Partially Observable Monte-Carlo Planning (POMCP) algorithms for modeling the security attacks. Also, potential mitigation strategies are suggested for the identified threats.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127528248","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9917234
M. Adham, Manasseh Obi, R. Bass
Utilities and customers are now operating more closely than ever. The prevailing numbers of grid-interactive Distributed Energy Resources are being integrated to provide grid reliability and stability. Different methods of control have been implemented to utilize these Distributed Energy Resources, such as Service-Oriented Load Control and Direct Load Control. This paper investigates the issues associated with the latter. A Direct Load Control method is applied to two Distributed Energy Resources, Electric Water Heater and Heat Pump Water Heater. A load shifting scenario is created where each water heater turns off during water draw events that coincide with peak demand periods. The results of the tests indicated a significant decrease in the temperature of the water in the tank. This implies that using Direct Load Control to control water heaters adversely impacts customer comfort which might lead to unenrollment from Demand Response programs.
{"title":"A Field Test of Direct Load Control of Water Heaters and its Implications for Consumers","authors":"M. Adham, Manasseh Obi, R. Bass","doi":"10.1109/PESGM48719.2022.9917234","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9917234","url":null,"abstract":"Utilities and customers are now operating more closely than ever. The prevailing numbers of grid-interactive Distributed Energy Resources are being integrated to provide grid reliability and stability. Different methods of control have been implemented to utilize these Distributed Energy Resources, such as Service-Oriented Load Control and Direct Load Control. This paper investigates the issues associated with the latter. A Direct Load Control method is applied to two Distributed Energy Resources, Electric Water Heater and Heat Pump Water Heater. A load shifting scenario is created where each water heater turns off during water draw events that coincide with peak demand periods. The results of the tests indicated a significant decrease in the temperature of the water in the tank. This implies that using Direct Load Control to control water heaters adversely impacts customer comfort which might lead to unenrollment from Demand Response programs.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130154822","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9917163
S. Som, R. Dutta, Arindam Mitra, S. Chakrabarti, S. R. Sahoo
A microgrid can be subjected to various unexpected events, such as sudden loss of generation/ load demand, faults, maloperation of capacitor banks, etc. To take appropriate control or remedial actions, the microgrid management system (MGS) should detect and classify an event. Due to economic reasons, all buses and lines in a microgrid are not equipped with measuring devices. Thus, detecting and classifying an event in a sparsely monitored microgrid is a challenging task. This paper proposes an event detector and classifier using measurements collected from few distribution phasor measurement units (DPMUs) connected only at the generator buses. The proposed method is a multi-step process. Firstly, a DPMU measurement based linear state estimator is used to estimate the voltage and current phasors for all the buses in the network. The second step uses the change in the estimated voltage phasors during an event to select a few candidate buses which are further analyzed to classify the event. An offline process is used for training the event classifier, where several time domain and spectral features are extracted from the estimated change in voltage and currents phasors at the candidate buses. In the third step, a neural network is trained using the selected features, which is used for event classification. The proposed method is validated on a 13-bus microgid system simulated using OPALRT hypersim real-time digital simulator.
{"title":"DPMU-based Event Classification in Microgrids Using Time Domain and Spectral Features of Limited Measurements","authors":"S. Som, R. Dutta, Arindam Mitra, S. Chakrabarti, S. R. Sahoo","doi":"10.1109/PESGM48719.2022.9917163","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9917163","url":null,"abstract":"A microgrid can be subjected to various unexpected events, such as sudden loss of generation/ load demand, faults, maloperation of capacitor banks, etc. To take appropriate control or remedial actions, the microgrid management system (MGS) should detect and classify an event. Due to economic reasons, all buses and lines in a microgrid are not equipped with measuring devices. Thus, detecting and classifying an event in a sparsely monitored microgrid is a challenging task. This paper proposes an event detector and classifier using measurements collected from few distribution phasor measurement units (DPMUs) connected only at the generator buses. The proposed method is a multi-step process. Firstly, a DPMU measurement based linear state estimator is used to estimate the voltage and current phasors for all the buses in the network. The second step uses the change in the estimated voltage phasors during an event to select a few candidate buses which are further analyzed to classify the event. An offline process is used for training the event classifier, where several time domain and spectral features are extracted from the estimated change in voltage and currents phasors at the candidate buses. In the third step, a neural network is trained using the selected features, which is used for event classification. The proposed method is validated on a 13-bus microgid system simulated using OPALRT hypersim real-time digital simulator.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130181982","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 : 2022-07-17DOI: 10.1109/pesgm48719.2022.9916744
L. C. da Costa, J. Garcia, F. Thomé, M. Pereira
This work presents a methodology to incorporate reliability constraints in the optimal power systems expansion planning problem. Besides Loss Of Load Probability (LOLP) and Expected Power Not Supplied (EPNS), traditionally used in power systems, this work proposes the use of the risk measures VaR (Value-at-Risk) and CVaR (Conditional Value-at-Risk), widely used in financial markets. The explicit consideration of reliability constraints in the planning problem can be an extremely hard task and, to minimize computational effort, this work applies the Benders decomposition technique splitting the expansion planning problem into an investment problem and two subproblems to evaluate the system's operation cost and the reliability index. The operation subproblem is solved by Stochastic Dual Dynamic Programming (SDDP) and the reliability subproblem by Monte Carlo simulation. The proposed methodology is applied to the real problem of optimal expansion planning of the Bolivian power system.
{"title":"Reliability-Constrained Power System Expansion Planning: A Stochastic Risk-Averse Optimization Approach","authors":"L. C. da Costa, J. Garcia, F. Thomé, M. Pereira","doi":"10.1109/pesgm48719.2022.9916744","DOIUrl":"https://doi.org/10.1109/pesgm48719.2022.9916744","url":null,"abstract":"This work presents a methodology to incorporate reliability constraints in the optimal power systems expansion planning problem. Besides Loss Of Load Probability (LOLP) and Expected Power Not Supplied (EPNS), traditionally used in power systems, this work proposes the use of the risk measures VaR (Value-at-Risk) and CVaR (Conditional Value-at-Risk), widely used in financial markets. The explicit consideration of reliability constraints in the planning problem can be an extremely hard task and, to minimize computational effort, this work applies the Benders decomposition technique splitting the expansion planning problem into an investment problem and two subproblems to evaluate the system's operation cost and the reliability index. The operation subproblem is solved by Stochastic Dual Dynamic Programming (SDDP) and the reliability subproblem by Monte Carlo simulation. The proposed methodology is applied to the real problem of optimal expansion planning of the Bolivian power system.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126915921","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9917203
Zeyu Liu, K. Hou, H. Jia, Junbo Zhao, Dan Wang, Yunfei Mu, Lewei Zhu
With the integration of multiple types of loads and renewable generations, the number of system states significantly grows. As a result, running optimal power flow (OPF) to analyze a myriad of system states is challenging and this seriously restricts the efficiency of the state enumeration method. To address that, this paper proposes a Lagrange Multiplier based State Enumeration (LMSE) approach to accelerate the analysis without loss of accuracy. The core idea is to directly obtain the optimal load shedding of contingency states by Lagrange multiplier-based functions, rather than the time-consuming OPF algorithms. This approach can also be conveniently integrated with the impactincrement method and the clustering technique for further efficiency enhancement. Case studies are performed on the RTS-79 and IEEE 118-bus systems considering multiple types of loads, photovoltaics (PVs), and wind turbines (WTs). Results indicate that the proposed method can significantly reduce the computing time without compromising the calculation accuracy.
{"title":"A Lagrange Multiplier Based State Enumeration Reliability Assessment for Power Systems With Multiple Types of Loads and Renewable Generations","authors":"Zeyu Liu, K. Hou, H. Jia, Junbo Zhao, Dan Wang, Yunfei Mu, Lewei Zhu","doi":"10.1109/PESGM48719.2022.9917203","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9917203","url":null,"abstract":"With the integration of multiple types of loads and renewable generations, the number of system states significantly grows. As a result, running optimal power flow (OPF) to analyze a myriad of system states is challenging and this seriously restricts the efficiency of the state enumeration method. To address that, this paper proposes a Lagrange Multiplier based State Enumeration (LMSE) approach to accelerate the analysis without loss of accuracy. The core idea is to directly obtain the optimal load shedding of contingency states by Lagrange multiplier-based functions, rather than the time-consuming OPF algorithms. This approach can also be conveniently integrated with the impactincrement method and the clustering technique for further efficiency enhancement. Case studies are performed on the RTS-79 and IEEE 118-bus systems considering multiple types of loads, photovoltaics (PVs), and wind turbines (WTs). Results indicate that the proposed method can significantly reduce the computing time without compromising the calculation accuracy.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130585198","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9917142
A. Masoom, J. Mahseredjian, T. Ould-Bachir, A. Guironnet
Electromagnetic Transient (EMT) simulation tools are typically developed using conventional procedural programming languages. On the other hand, modern high-level and equation-based programming languages, such as Modelica, are currently available. Modelica allows formulating models that are easy to develop, maintain and understand by expressing what needs to be computed without stating how it should be computed. This paper presents a Modelica-based simulator for electromagnetic transients. It is demonstrated that this approach offers significant advantages for developing sophisticated models. Computational performance and accuracy are compared to a conventional EMT-type simulation tool.
{"title":"MSEMT: An Advanced Modelica Library for Power System Electromagnetic Transient Studies","authors":"A. Masoom, J. Mahseredjian, T. Ould-Bachir, A. Guironnet","doi":"10.1109/PESGM48719.2022.9917142","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9917142","url":null,"abstract":"Electromagnetic Transient (EMT) simulation tools are typically developed using conventional procedural programming languages. On the other hand, modern high-level and equation-based programming languages, such as Modelica, are currently available. Modelica allows formulating models that are easy to develop, maintain and understand by expressing what needs to be computed without stating how it should be computed. This paper presents a Modelica-based simulator for electromagnetic transients. It is demonstrated that this approach offers significant advantages for developing sophisticated models. Computational performance and accuracy are compared to a conventional EMT-type simulation tool.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"355 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132371778","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9916716
Guoyan Zheng, Honggang Wang, Shaopeng Liu, M. Farrokhifard
The 2021 Oscillation Source Location (OSL) Contest organized by IEEE and North American SynchroPhasor Initiative (NASPI) aimed at evaluating the efficiency of OSL methods and their applicability for practical implementation. The participants were provided with a base model and thirteen test data sets mimicking the real-world challenges of inter-area electromechanical oscillations and/or forced oscillations (FOs). Testing scenarios include FOs resonating with natural modes, faults induced oscillations, various source locations, asset types and controller types. This paper comments on the contest design and presents the top awarded method by team Woodpecker, which highlights (i) physics-guided pattern matching in exploring the sources candidates, and (ii) model-based analytics to verify the source. In particular, Woodpecker demonstrated the usefulness of machine learning pattern recognition (ML-PR) based OSL method for complementing the dissipating energy flow (DEF) method. This approach can identify the oscillation source location based on available PMUs even when the source is not monitored.
{"title":"2021 IEEE-NASPI Oscillation Source Location Contest: Team Woodpecker","authors":"Guoyan Zheng, Honggang Wang, Shaopeng Liu, M. Farrokhifard","doi":"10.1109/PESGM48719.2022.9916716","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9916716","url":null,"abstract":"The 2021 Oscillation Source Location (OSL) Contest organized by IEEE and North American SynchroPhasor Initiative (NASPI) aimed at evaluating the efficiency of OSL methods and their applicability for practical implementation. The participants were provided with a base model and thirteen test data sets mimicking the real-world challenges of inter-area electromechanical oscillations and/or forced oscillations (FOs). Testing scenarios include FOs resonating with natural modes, faults induced oscillations, various source locations, asset types and controller types. This paper comments on the contest design and presents the top awarded method by team Woodpecker, which highlights (i) physics-guided pattern matching in exploring the sources candidates, and (ii) model-based analytics to verify the source. In particular, Woodpecker demonstrated the usefulness of machine learning pattern recognition (ML-PR) based OSL method for complementing the dissipating energy flow (DEF) method. This approach can identify the oscillation source location based on available PMUs even when the source is not monitored.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133002534","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9917053
M. Qais, S. Muyeen
This paper offers a hybrid analytical and estimation based technique to determine the photovoltaic (PV) system parameter in a systematic way. The new model formulation is based on the datasheet parameters under standard test condition and normal operating cell temperature environment, forming the analytical approach's foundation. The estimation part is based on the adaptive filtering algorithm, which shows superiority in estimated parameters compared to existing techniques applied in the photovoltaic system. The proposed approach is made available for a single diode PV model and scaled up aggregated model in extracting the model parameters of two real PV modules in the market, representing the exact /-V characteristics of the manufacturer datasheet. A rigorous comparative analysis is carried out between two adaptive and two optimization based estimations for performance evaluation and recommendation purposes.
{"title":"A novel adaptive filtering algorithm based parameter estimation technique for photovoltaic system","authors":"M. Qais, S. Muyeen","doi":"10.1109/PESGM48719.2022.9917053","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9917053","url":null,"abstract":"This paper offers a hybrid analytical and estimation based technique to determine the photovoltaic (PV) system parameter in a systematic way. The new model formulation is based on the datasheet parameters under standard test condition and normal operating cell temperature environment, forming the analytical approach's foundation. The estimation part is based on the adaptive filtering algorithm, which shows superiority in estimated parameters compared to existing techniques applied in the photovoltaic system. The proposed approach is made available for a single diode PV model and scaled up aggregated model in extracting the model parameters of two real PV modules in the market, representing the exact /-V characteristics of the manufacturer datasheet. A rigorous comparative analysis is carried out between two adaptive and two optimization based estimations for performance evaluation and recommendation purposes.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"219 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132147013","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9916746
G. N. D. de Doile, Gustavo O. Troiano, B. Bonatto, A. D. De Souza, V. Costa
To make cities smarter has become a worldwide purpose as predicted in the United Nations Sustainable Development Goals. In modern power systems, reliability and self-sustainability are crucial requirements. This paper assesses the ability of a real microgrid to operate in islanded mode when a failure of any nature takes place. The circuit analyzed belongs to the satellite city of Taguatinga, located in the suburban area of Brasilia, the Brazilian Capital City. The city electrical data make Taguatinga similar to large cities in the Brazilian context. This work presents the electricity data, as voltage levels, consumption and, local distributed generations. The purpose is to propose solutions for technical, regulatory, and social issues needed to make the city, at least, four days electrically self-sustainable. It was concluded that a tremendous global effort, including government, regulators, and society, will be necessary to make any Brazilian city a smart city, electrically leastwise.
{"title":"Technical, Regulatory, and Social Issues to Make a City Electrically Smart","authors":"G. N. D. de Doile, Gustavo O. Troiano, B. Bonatto, A. D. De Souza, V. Costa","doi":"10.1109/PESGM48719.2022.9916746","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9916746","url":null,"abstract":"To make cities smarter has become a worldwide purpose as predicted in the United Nations Sustainable Development Goals. In modern power systems, reliability and self-sustainability are crucial requirements. This paper assesses the ability of a real microgrid to operate in islanded mode when a failure of any nature takes place. The circuit analyzed belongs to the satellite city of Taguatinga, located in the suburban area of Brasilia, the Brazilian Capital City. The city electrical data make Taguatinga similar to large cities in the Brazilian context. This work presents the electricity data, as voltage levels, consumption and, local distributed generations. The purpose is to propose solutions for technical, regulatory, and social issues needed to make the city, at least, four days electrically self-sustainable. It was concluded that a tremendous global effort, including government, regulators, and society, will be necessary to make any Brazilian city a smart city, electrically leastwise.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"42 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132330141","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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