Pub Date : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384939
A. Bracale, P. De Falco, L. P. D. Noia, R. Rizzo
Lithium-ion batteries are often operated to reach excellence in technical and economical performance, but they rapidly degrade as a consequence of charge/discharge profiles. Maintaining the knowledge of the actual capacity of the battery is mandatory to pursue the objectives without incurring into unexpected constraints. This paper addresses battery prognostic from the viewpoint of probabilistic prediction of the State of Health (SoH) and of the Remaining Useful Life (RUL) of the batteries. Two probabilistic models based on time series and quantile regression, each developed in a different framework, are developed and compared for this purpose. They are specifically suited up to exploit data coming from Accelerated Degradation Tests (ADTs). Moreover, a dedicated procedure to extract a single, point value from the probabilistic predictions is presented to let the models work also in deterministic scenarios. Numerical experiments conducted on actual public data confirm the validity of the proposal, within a rigorous comparison with relevant benchmarks taken from the literature on the topic.
{"title":"Probabilistic State of Health and Remaining Useful Life Prediction for Li-ion Batteries","authors":"A. Bracale, P. De Falco, L. P. D. Noia, R. Rizzo","doi":"10.1109/TPEC51183.2021.9384939","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384939","url":null,"abstract":"Lithium-ion batteries are often operated to reach excellence in technical and economical performance, but they rapidly degrade as a consequence of charge/discharge profiles. Maintaining the knowledge of the actual capacity of the battery is mandatory to pursue the objectives without incurring into unexpected constraints. This paper addresses battery prognostic from the viewpoint of probabilistic prediction of the State of Health (SoH) and of the Remaining Useful Life (RUL) of the batteries. Two probabilistic models based on time series and quantile regression, each developed in a different framework, are developed and compared for this purpose. They are specifically suited up to exploit data coming from Accelerated Degradation Tests (ADTs). Moreover, a dedicated procedure to extract a single, point value from the probabilistic predictions is presented to let the models work also in deterministic scenarios. Numerical experiments conducted on actual public data confirm the validity of the proposal, within a rigorous comparison with relevant benchmarks taken from the literature on the topic.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126595067","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 : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384912
S. Mohiuddin, Junjian Qi
In this paper, we propose an attack resilient distributed control for islanded AC microgrid (MG) systems. The distributed control on an MG is implemented based on a sparse communication network where each agent only has access to the information of itself and the neighboring distributed generators (DGs). Although distributed control has several advantages compared with its centralized counterpart, the increased dependence on communication and lack of access to global information make it vulnerable to cyber threats from malicious entities. To increase the resiliency of the distributed control, we propose to incorporate a distributed robust state estimation scheme. In the proposed scheme, the voltage and frequency references are calculated based on the results of the distributed estimator instead of directly using the local measurements. The performance of the proposed attack resilient control approach is validated through simulation results on a test microgrid system under false data injection attack.
{"title":"Attack Resilient Distributed Control for AC Microgrids with Distributed Robust State Estimation","authors":"S. Mohiuddin, Junjian Qi","doi":"10.1109/TPEC51183.2021.9384912","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384912","url":null,"abstract":"In this paper, we propose an attack resilient distributed control for islanded AC microgrid (MG) systems. The distributed control on an MG is implemented based on a sparse communication network where each agent only has access to the information of itself and the neighboring distributed generators (DGs). Although distributed control has several advantages compared with its centralized counterpart, the increased dependence on communication and lack of access to global information make it vulnerable to cyber threats from malicious entities. To increase the resiliency of the distributed control, we propose to incorporate a distributed robust state estimation scheme. In the proposed scheme, the voltage and frequency references are calculated based on the results of the distributed estimator instead of directly using the local measurements. The performance of the proposed attack resilient control approach is validated through simulation results on a test microgrid system under false data injection attack.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126782498","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 : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384955
Andrew Foster, Hao Huang, M. Narimani, Laura Homiller, K. Davis, A. Layton
The identification of critical components in electric power grids is an important challenge power engineers face. Similarly, many ecologists face the challenge of identifying important species in food web networks. Drawing similarities between power grid networks and food web networks, this study utilizes proposed identification methods from ecology literature to identify critical components in electric power grids. These ecological methods used include measures of Sum of the Trophic Overlap (STO) and Weighted Trophic Overlap (WTO). We also study a method proposed from power engineering literature that uses the Normalized Line Outage Distribution Factor (NLODF) to compare the different methods. The intention of this study is to determine if bio-inspiration in criticality metrics provides a feasible tool to use in power grid analysis. The proposed engineering method utilizing NLODF is found to be more accurate in identifying critical lines in power grids when considering all lines in the grid. However, the ecological metric STO is found to be as good as NLODF when considering the top 10,20, or 30% of lines. STO was the most accurate metric in the largest grid analyzed, suggesting STO may be more accurate in larger grids. The comparable performance of the ecological and engineering methods suggests the ecological methods can be used to accurately identify critical components in electric power grids.
{"title":"Ecological Uniqueness for Understanding Line Importance in Power Grids","authors":"Andrew Foster, Hao Huang, M. Narimani, Laura Homiller, K. Davis, A. Layton","doi":"10.1109/TPEC51183.2021.9384955","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384955","url":null,"abstract":"The identification of critical components in electric power grids is an important challenge power engineers face. Similarly, many ecologists face the challenge of identifying important species in food web networks. Drawing similarities between power grid networks and food web networks, this study utilizes proposed identification methods from ecology literature to identify critical components in electric power grids. These ecological methods used include measures of Sum of the Trophic Overlap (STO) and Weighted Trophic Overlap (WTO). We also study a method proposed from power engineering literature that uses the Normalized Line Outage Distribution Factor (NLODF) to compare the different methods. The intention of this study is to determine if bio-inspiration in criticality metrics provides a feasible tool to use in power grid analysis. The proposed engineering method utilizing NLODF is found to be more accurate in identifying critical lines in power grids when considering all lines in the grid. However, the ecological metric STO is found to be as good as NLODF when considering the top 10,20, or 30% of lines. STO was the most accurate metric in the largest grid analyzed, suggesting STO may be more accurate in larger grids. The comparable performance of the ecological and engineering methods suggests the ecological methods can be used to accurately identify critical components in electric power grids.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134267259","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 : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384972
A. Parizad, C. Hatziadoniu
The integration of Information and Communication Technologies (ICT) into the modern power system makes it a complicated cyber-physical system (CPS). In this case, an adversary may find some loopholes, penetrate to CPS layer, compromise data, and consequently result in security and stability issues. In this paper, we proposed a laboratory set up to emulate the attacker's behavior and then detect the injected false data. To this end, RTU hardware and software are used to simulate a typical SCADA system. A protocol analyzer software is also employed to simulate a cyber-attack, inject false data, and send it to the control center. In the second stage, we developed a two-stage framework to detect FDIA. First, the LSTM, as a supervised learning algorithm, is utilized to build a predictive model. In this process, hyperparameter optimization is implemented to improve the accuracy of the developed model. In the second stage, an unsupervised scoring algorithm is applied to the real-time data to find the sequences of injected false data. Also, a penalty factor is considered during the detection procedure to prevent the algorithm from greedy search behavior. Simulation results on a real-world data set (Chicago load/weather) show the proposed method's effectiveness in the cyberattack implementation and FDIA detection problem.
{"title":"A Laboratory Set-Up for Cyber Attacks Simulation Using Protocol Analyzer and RTU Hardware Applying Semi-Supervised Detection Algorithm","authors":"A. Parizad, C. Hatziadoniu","doi":"10.1109/TPEC51183.2021.9384972","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384972","url":null,"abstract":"The integration of Information and Communication Technologies (ICT) into the modern power system makes it a complicated cyber-physical system (CPS). In this case, an adversary may find some loopholes, penetrate to CPS layer, compromise data, and consequently result in security and stability issues. In this paper, we proposed a laboratory set up to emulate the attacker's behavior and then detect the injected false data. To this end, RTU hardware and software are used to simulate a typical SCADA system. A protocol analyzer software is also employed to simulate a cyber-attack, inject false data, and send it to the control center. In the second stage, we developed a two-stage framework to detect FDIA. First, the LSTM, as a supervised learning algorithm, is utilized to build a predictive model. In this process, hyperparameter optimization is implemented to improve the accuracy of the developed model. In the second stage, an unsupervised scoring algorithm is applied to the real-time data to find the sequences of injected false data. Also, a penalty factor is considered during the detection procedure to prevent the algorithm from greedy search behavior. Simulation results on a real-world data set (Chicago load/weather) show the proposed method's effectiveness in the cyberattack implementation and FDIA detection problem.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127758352","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 : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384915
Toby Meyers, B. Mather
Two major issues facing grid-forming inverters are synchronism and phase reference inaccuracies. Prior literature has addressed these problems with solutions such as disciplining the phase reference using GPS and active synchronization modes but these methods have not yet been integrated together. This paper serves to unite solutions and develop a means for an inverter to remain synchronized and grid-forming without phase reference inaccuracies through a novel time-disciplined active synchronization phase reference. Further, this work expands upon prior literature on active synchronization to include black-start capabilities. Finally, the time disciplined phase reference is evaluated in Simulink as a grid-forming inverter capable of any synchronization circumstance and assessed by key metrics from modern standards.
{"title":"Time Disciplined Non-PLL Active Synchronization for Grid Forming Inverters","authors":"Toby Meyers, B. Mather","doi":"10.1109/TPEC51183.2021.9384915","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384915","url":null,"abstract":"Two major issues facing grid-forming inverters are synchronism and phase reference inaccuracies. Prior literature has addressed these problems with solutions such as disciplining the phase reference using GPS and active synchronization modes but these methods have not yet been integrated together. This paper serves to unite solutions and develop a means for an inverter to remain synchronized and grid-forming without phase reference inaccuracies through a novel time-disciplined active synchronization phase reference. Further, this work expands upon prior literature on active synchronization to include black-start capabilities. Finally, the time disciplined phase reference is evaluated in Simulink as a grid-forming inverter capable of any synchronization circumstance and assessed by key metrics from modern standards.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127856717","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 : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384987
J. Desai, V. Makwana
The transformer's protection against internal faults like phase to phase faults, phase to ground faults, and inter-turn faults are provided using the percentage bias differential protection scheme. The paper introduced dual-slope implementation in percentage bias differential relay by considering mal-operation of the percentage bias differential relay against high external fault current and inrush current harmonics. The paper's beginning shows the modeling and analysis of a percentage bias differential protection scheme to protect the 132KV/33KV primary distribution transformer. The issues of a percentage bias differential protection scheme are explained in the middle of the paper. The dual slop algorithm is designed and implemented on a radial distribution system using MATLAB software environment. The results show that the through fault stability of the transformer is improved due to dual-slope implementation. The risk of maloperation of bias differential scheme due to high external fault current and harmonic inrush current is considerably reduced after implementing dual-slope characteristics. The proposed algorithm is practical for deploying in the digital signal controller (DSC) for protection engineers.
{"title":"Modeling and Implementation of Percentage Bias Differential Relay with Dual-Slope Characteristic","authors":"J. Desai, V. Makwana","doi":"10.1109/TPEC51183.2021.9384987","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384987","url":null,"abstract":"The transformer's protection against internal faults like phase to phase faults, phase to ground faults, and inter-turn faults are provided using the percentage bias differential protection scheme. The paper introduced dual-slope implementation in percentage bias differential relay by considering mal-operation of the percentage bias differential relay against high external fault current and inrush current harmonics. The paper's beginning shows the modeling and analysis of a percentage bias differential protection scheme to protect the 132KV/33KV primary distribution transformer. The issues of a percentage bias differential protection scheme are explained in the middle of the paper. The dual slop algorithm is designed and implemented on a radial distribution system using MATLAB software environment. The results show that the through fault stability of the transformer is improved due to dual-slope implementation. The risk of maloperation of bias differential scheme due to high external fault current and harmonic inrush current is considerably reduced after implementing dual-slope characteristics. The proposed algorithm is practical for deploying in the digital signal controller (DSC) for protection engineers.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127217821","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 : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384954
Mahendra Kumar, Y. V. Hote
In Today's world, the penetration of renewable energy sources in the modern power system for electrification of society and industry, is exponential growing. The dc-dc converter is the most important circuitry in such type of systems to regulate the output voltage. The boost converter is mostly preferred for step-up the output voltage level in practical applications. The output voltage regulation is a challenging task for control engineers of the boost converter. In this direction, the paper addresses a novel PID-Type controller for output voltage control of a non-ideal dc-dc boost converter. This novel PID-Type controller is a proportional-integral-derivative-double derivative (PIDD2) control design. Most important concern with the proposed control design is that a few tuning algorithms are available in the literature. In the paper, the tuning of PIDD2 is carried-out using internal model control (IMC) method. IMC is a robust tunning approach. The robustness of proposed control system is evaluated under the sudden change in load, sudden change in supply voltage, and sudden change in reference voltage. The efficacy of proposed control scheme is evaluated in comparison to the existing control schemes. The simulation results show the efficacy and effectiveness of the proposed controller design under the influence of different uncertainties and perturbations. Further, the experimental results present for the validation of proposed control design on nonideal dc-dc boost converter.
{"title":"PIDD2 Controller Design Based on Internal Model Control Approach for a Non-Ideal DC-DC Boost Converter","authors":"Mahendra Kumar, Y. V. Hote","doi":"10.1109/TPEC51183.2021.9384954","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384954","url":null,"abstract":"In Today's world, the penetration of renewable energy sources in the modern power system for electrification of society and industry, is exponential growing. The dc-dc converter is the most important circuitry in such type of systems to regulate the output voltage. The boost converter is mostly preferred for step-up the output voltage level in practical applications. The output voltage regulation is a challenging task for control engineers of the boost converter. In this direction, the paper addresses a novel PID-Type controller for output voltage control of a non-ideal dc-dc boost converter. This novel PID-Type controller is a proportional-integral-derivative-double derivative (PIDD2) control design. Most important concern with the proposed control design is that a few tuning algorithms are available in the literature. In the paper, the tuning of PIDD2 is carried-out using internal model control (IMC) method. IMC is a robust tunning approach. The robustness of proposed control system is evaluated under the sudden change in load, sudden change in supply voltage, and sudden change in reference voltage. The efficacy of proposed control scheme is evaluated in comparison to the existing control schemes. The simulation results show the efficacy and effectiveness of the proposed controller design under the influence of different uncertainties and perturbations. Further, the experimental results present for the validation of proposed control design on nonideal dc-dc boost converter.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124895535","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 : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384931
Hemanth Chaduvula, D. Das
The optimal economic-emission dispatch is acquired through optimal energy management of sources in the microgrid. The dispatch from distributed energy resources (DERs) and power exchange with the grid are managed for achieving the optimal operation in the microgrid. The optimal scheduling of microgrid varies according to its mode of connection to the grid. In this paper, the concept of zero bus load flow (ZBLF) is performed in a microgrid by known power injection from the grid. The particle swarm optimization (PSO) technique is employed for attaining the optimum output values of sources with distinct characteristics. In this work, the PSO embedded Fuzzy multi-objective approach is implemented for optimal energy management in the microgrid. The objectives such as operation cost, emission, and cost of energy loss are considered in a 24-hour time horizon. The degree of satisfaction of each objective is attained by representing in the fuzzy domain due to its imprecise nature. The results of Fuzzy-PSO method are validated with nondominated sorting genetic algorithm II (NSGA-II). The proposed technique has been applied to a 33-bus grid connected microgrid system.
{"title":"Optimal energy dispatch based on zero bus load flow in microgrid having multiple sources using Fuzzy-Particle Swarm Optimization approach","authors":"Hemanth Chaduvula, D. Das","doi":"10.1109/TPEC51183.2021.9384931","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384931","url":null,"abstract":"The optimal economic-emission dispatch is acquired through optimal energy management of sources in the microgrid. The dispatch from distributed energy resources (DERs) and power exchange with the grid are managed for achieving the optimal operation in the microgrid. The optimal scheduling of microgrid varies according to its mode of connection to the grid. In this paper, the concept of zero bus load flow (ZBLF) is performed in a microgrid by known power injection from the grid. The particle swarm optimization (PSO) technique is employed for attaining the optimum output values of sources with distinct characteristics. In this work, the PSO embedded Fuzzy multi-objective approach is implemented for optimal energy management in the microgrid. The objectives such as operation cost, emission, and cost of energy loss are considered in a 24-hour time horizon. The degree of satisfaction of each objective is attained by representing in the fuzzy domain due to its imprecise nature. The results of Fuzzy-PSO method are validated with nondominated sorting genetic algorithm II (NSGA-II). The proposed technique has been applied to a 33-bus grid connected microgrid system.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"185 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121044595","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 : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384941
M. E. Bento, R. Ramos
The load margin is an important index used in power system operation centers to assess how far the system is from an instability mechanism. Usually, this load margin is calculated considering the Voltage Stability requirements through static models. However, as the load level increases in one direction, low-dampened low-frequency oscillation modes can arise and they compromise the angular stability of the system. Thus, it is important to consider the dynamic model of the system and determine the load margin by meeting the requirements of Voltage and Small-Signal Stability. This article proposes a method based on Particle Swarm Optimization to determine the load margin of power systems meeting the requirements of the Voltage Stability (voltage collapse) and Small-Signal Stability (eigenvalues with low damping). Case studies on the IEEE 39-bus system are presented and discussed.
{"title":"Computing the Load Margin of Power Systems Using Particle Swarm Optimization","authors":"M. E. Bento, R. Ramos","doi":"10.1109/TPEC51183.2021.9384941","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384941","url":null,"abstract":"The load margin is an important index used in power system operation centers to assess how far the system is from an instability mechanism. Usually, this load margin is calculated considering the Voltage Stability requirements through static models. However, as the load level increases in one direction, low-dampened low-frequency oscillation modes can arise and they compromise the angular stability of the system. Thus, it is important to consider the dynamic model of the system and determine the load margin by meeting the requirements of Voltage and Small-Signal Stability. This article proposes a method based on Particle Swarm Optimization to determine the load margin of power systems meeting the requirements of the Voltage Stability (voltage collapse) and Small-Signal Stability (eigenvalues with low damping). Case studies on the IEEE 39-bus system are presented and discussed.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"227 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127687940","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 : 2021-02-02DOI: 10.1109/TPEC51183.2021.9384964
Mohannad Alkhraijah, Maad Alowaifeer, S. Grijalva, D. Molzahn
Distributed algorithms provide attractive features for solving Optimal Power Flow (OPF) problems in interconnected power systems compared to traditional centralized algorithms. Distributed algorithms help to maintain the control autonomy and data privacy of subsystems, which is particularly relevant in competitive markets and practical control system implementations. This paper analyzes a distributed optimization algorithm known as the “Auxiliary Principle Problem” to solve multiperiod distributed DCOPF problems with distributed energy resources including energy storage systems. The proposed approach enables multiple interconnected systems with their own sub-objectives to share their resources and to participate in an electricity market without implicitly sharing information about their local generators or internal network parameters. The paper also shows how the proposed approach can enable future microgrids to coordinate their operation, reduce the total operational cost, and avoid internal constraint violations caused by unscheduled flows (USF) while maintaining the subsystems' autonomy. We use an 11-bus test system consisting of two interconnected subsystems to evaluate the proposed approach and analyze the impact of USF.
{"title":"Distributed Multi-Period DCOPF via an Auxiliary Principle Problem Algorithm","authors":"Mohannad Alkhraijah, Maad Alowaifeer, S. Grijalva, D. Molzahn","doi":"10.1109/TPEC51183.2021.9384964","DOIUrl":"https://doi.org/10.1109/TPEC51183.2021.9384964","url":null,"abstract":"Distributed algorithms provide attractive features for solving Optimal Power Flow (OPF) problems in interconnected power systems compared to traditional centralized algorithms. Distributed algorithms help to maintain the control autonomy and data privacy of subsystems, which is particularly relevant in competitive markets and practical control system implementations. This paper analyzes a distributed optimization algorithm known as the “Auxiliary Principle Problem” to solve multiperiod distributed DCOPF problems with distributed energy resources including energy storage systems. The proposed approach enables multiple interconnected systems with their own sub-objectives to share their resources and to participate in an electricity market without implicitly sharing information about their local generators or internal network parameters. The paper also shows how the proposed approach can enable future microgrids to coordinate their operation, reduce the total operational cost, and avoid internal constraint violations caused by unscheduled flows (USF) while maintaining the subsystems' autonomy. We use an 11-bus test system consisting of two interconnected subsystems to evaluate the proposed approach and analyze the impact of USF.","PeriodicalId":354018,"journal":{"name":"2021 IEEE Texas Power and Energy Conference (TPEC)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131146889","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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