Pub Date : 2016-11-21DOI: 10.1109/NAPS.2016.7747887
A. Nagarajan, B. Palmintier, F. Ding, B. Mather, M. Baggu
Simulation of modern distribution system powerflow increasingly requires capturing the impact of advanced PV inverter voltage regulation on powerflow. With Volt/var control, the inverter adjusts its reactive power flow as a function of the point of common coupling (PCC) voltage. Similarly, Volt/watt control curtails active power production as a function of PCC voltage. However, with larger systems and higher penetrations of PV, this active/reactive power flow itself can cause significant changes to the PCC voltage potentially introducing oscillations that slow the convergence of system simulations. Improper treatment of these advanced inverter functions could potentially lead to incorrect results. This paper explores a simple approach to speed such convergence by blending in the previous iteration's reactive power estimate to dampen these oscillations. Results with a single large (5MW) PV system and with multiple 500kW advanced inverters show dramatic improvements using this approach.
{"title":"Improving advanced inverter control convergence in distribution power flow","authors":"A. Nagarajan, B. Palmintier, F. Ding, B. Mather, M. Baggu","doi":"10.1109/NAPS.2016.7747887","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747887","url":null,"abstract":"Simulation of modern distribution system powerflow increasingly requires capturing the impact of advanced PV inverter voltage regulation on powerflow. With Volt/var control, the inverter adjusts its reactive power flow as a function of the point of common coupling (PCC) voltage. Similarly, Volt/watt control curtails active power production as a function of PCC voltage. However, with larger systems and higher penetrations of PV, this active/reactive power flow itself can cause significant changes to the PCC voltage potentially introducing oscillations that slow the convergence of system simulations. Improper treatment of these advanced inverter functions could potentially lead to incorrect results. This paper explores a simple approach to speed such convergence by blending in the previous iteration's reactive power estimate to dampen these oscillations. Results with a single large (5MW) PV system and with multiple 500kW advanced inverters show dramatic improvements using this approach.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"91 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132480138","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 : 2016-11-01DOI: 10.1109/NAPS.2016.7747918
Matthew Long, Travis Simpkins, D. Cutler, Kate Anderson
There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that, of the variables considered, peak demand charges are the most significant predictor of an economically viable battery, and that the shape of the load profile is the most significant predictor of the size of the battery.
{"title":"A statistical analysis of the economic drivers of battery energy storage in commercial buildings","authors":"Matthew Long, Travis Simpkins, D. Cutler, Kate Anderson","doi":"10.1109/NAPS.2016.7747918","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747918","url":null,"abstract":"There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that, of the variables considered, peak demand charges are the most significant predictor of an economically viable battery, and that the shape of the load profile is the most significant predictor of the size of the battery.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132132989","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 : 2016-09-01DOI: 10.1109/NAPS.2016.7747897
M. Khalghani, Sarika Khushalani-Solanki, J. Solanki
In this paper, optimal battery scheduling for Plug-In Hybrid Electric Vehicles (PHEVs) is achieved for load leveling. This proper scheduling can lead to peak shaving and off-peak shaving (valley filling). Due to the uncertain nature of PHEVs, including charging and discharging times and daily movements, stochastic modeling is proposed. Daily movements to and from houses to administrative centers, as well as charging and discharging schedules are chronological-based; therefore, using sequential Monte-Carlo Simulation (MCS) is highly recommended. Furthermore, in order to optimize the scheduling-related fitness functions, Particle Swarm optimization (PSO) algorithm is utilized. Also, this paper focuses on finding the best location of parking lots for these PHEV aggregators. Two indices, voltage unbalance and power loss, for locating the PHEV aggregators are considered. During peak hours, these criteria can be more critical for a three-phase distribution system. Hence, this problem is solved using a multi-objective optimization algorithm based on fuzzification of objectives. The results are compared with those of single-objective algorithms. IEEE 13 node three-phase benchmark system is used for analyzing the proposed method.
{"title":"Optimal integration and location of PHEV aggregators in power distribution systems","authors":"M. Khalghani, Sarika Khushalani-Solanki, J. Solanki","doi":"10.1109/NAPS.2016.7747897","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747897","url":null,"abstract":"In this paper, optimal battery scheduling for Plug-In Hybrid Electric Vehicles (PHEVs) is achieved for load leveling. This proper scheduling can lead to peak shaving and off-peak shaving (valley filling). Due to the uncertain nature of PHEVs, including charging and discharging times and daily movements, stochastic modeling is proposed. Daily movements to and from houses to administrative centers, as well as charging and discharging schedules are chronological-based; therefore, using sequential Monte-Carlo Simulation (MCS) is highly recommended. Furthermore, in order to optimize the scheduling-related fitness functions, Particle Swarm optimization (PSO) algorithm is utilized. Also, this paper focuses on finding the best location of parking lots for these PHEV aggregators. Two indices, voltage unbalance and power loss, for locating the PHEV aggregators are considered. During peak hours, these criteria can be more critical for a three-phase distribution system. Hence, this problem is solved using a multi-objective optimization algorithm based on fuzzification of objectives. The results are compared with those of single-objective algorithms. IEEE 13 node three-phase benchmark system is used for analyzing the proposed method.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115300588","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 : 2016-09-01DOI: 10.1109/NAPS.2016.7747831
Abbas Gholizadeh, V. Aravinthan
Analysis, modeling and development of residential demand response schemes are vital for the next generation active distribution systems. Among residential level deferrable loads thermally controllable loads have shown a great potential to be the candidates for increasing the flexibility of power distribution network. This paper evaluates the benefits of managing residential electric water heater set-points to reduce the overall cost of electricity in the presence of day-ahead forward price at distribution level. Three unique features, (i) consumer comfort by providing more hot water at the time of usage, (ii) reducing residential indoor temperature variations and (iii) reducing the health concerns due to water temperature regulations are addressed in this work. Randomly specified residential units, along with the thermal dynamics are used. ASHRAE standards are used in this work to ensure physical limitations are accurately represented. The results show that appropriately controlling the water heater temperature will be of great value to both utility and consumer demand response programs.
{"title":"Benefit assessment of water-heater management on residential demand response: An event driven approach","authors":"Abbas Gholizadeh, V. Aravinthan","doi":"10.1109/NAPS.2016.7747831","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747831","url":null,"abstract":"Analysis, modeling and development of residential demand response schemes are vital for the next generation active distribution systems. Among residential level deferrable loads thermally controllable loads have shown a great potential to be the candidates for increasing the flexibility of power distribution network. This paper evaluates the benefits of managing residential electric water heater set-points to reduce the overall cost of electricity in the presence of day-ahead forward price at distribution level. Three unique features, (i) consumer comfort by providing more hot water at the time of usage, (ii) reducing residential indoor temperature variations and (iii) reducing the health concerns due to water temperature regulations are addressed in this work. Randomly specified residential units, along with the thermal dynamics are used. ASHRAE standards are used in this work to ensure physical limitations are accurately represented. The results show that appropriately controlling the water heater temperature will be of great value to both utility and consumer demand response programs.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"297 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116639151","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 : 2016-09-01DOI: 10.1109/NAPS.2016.7747944
M. Lwin, Harsha V. Padullaparti, S. Santoso
The power swing phenomenon is characterized by oscillations in power flow between two areas of a power system due to an abrupt imbalance in mechanical and electrical power. Unintentional operation of distance relays during power swings can propagate a disturbance and result in a cascading outage. It is therefore critical that relays operate securely under such conditions. Modern distance relays can provide a function for power swing blocking (PSB). However, the PSB settings can be difficult to calculate without extensive stability studies and may fail to block if the slip frequency is too fast. In this work, we investigate the application of a model-based relaying framework applied to power swing blocking. The framework is named Model-Based Distributed Intelligence (MBDI) because it integrates, at the relay level, real-time knowledge of the network structure and system state in the form of simulation circuit models. We investigate the efficacy of a relay equipped with MBDI to supervise PSB operation during power swing and fault scenarios.
{"title":"Supervision of power swing blocking using model-based distributed intelligence relaying framework","authors":"M. Lwin, Harsha V. Padullaparti, S. Santoso","doi":"10.1109/NAPS.2016.7747944","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747944","url":null,"abstract":"The power swing phenomenon is characterized by oscillations in power flow between two areas of a power system due to an abrupt imbalance in mechanical and electrical power. Unintentional operation of distance relays during power swings can propagate a disturbance and result in a cascading outage. It is therefore critical that relays operate securely under such conditions. Modern distance relays can provide a function for power swing blocking (PSB). However, the PSB settings can be difficult to calculate without extensive stability studies and may fail to block if the slip frequency is too fast. In this work, we investigate the application of a model-based relaying framework applied to power swing blocking. The framework is named Model-Based Distributed Intelligence (MBDI) because it integrates, at the relay level, real-time knowledge of the network structure and system state in the form of simulation circuit models. We investigate the efficacy of a relay equipped with MBDI to supervise PSB operation during power swing and fault scenarios.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127348327","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 : 2016-09-01DOI: 10.1109/NAPS.2016.7747978
Shruti Rao, D. Tylavsky
This paper presents three different true nonlinear reduction methods to obtain network equivalents for radial (distribution-type) networks (using the holomorphically embedded power flow algorithm), which are exact, given computational precision limitations, even when the loads and the real-power generations are scaled. The proposed reduction methods are applied in this paper to reduce a radial distribution system and provide a two-bus-model equivalent which accurately models the real and reactive power load seen at the transmission network due to random changes in the distribution system load. Numerical results are provided for a radial 14-bus system to show the accuracy of the proposed methods in preserving voltages and slack bus power. The approach is shown to have better performance than Ward reduction even when the loads are increased in a random manner.
{"title":"Nonlinear network reduction for distribution networks using the holomorphic embedding method","authors":"Shruti Rao, D. Tylavsky","doi":"10.1109/NAPS.2016.7747978","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747978","url":null,"abstract":"This paper presents three different true nonlinear reduction methods to obtain network equivalents for radial (distribution-type) networks (using the holomorphically embedded power flow algorithm), which are exact, given computational precision limitations, even when the loads and the real-power generations are scaled. The proposed reduction methods are applied in this paper to reduce a radial distribution system and provide a two-bus-model equivalent which accurately models the real and reactive power load seen at the transmission network due to random changes in the distribution system load. Numerical results are provided for a radial 14-bus system to show the accuracy of the proposed methods in preserving voltages and slack bus power. The approach is shown to have better performance than Ward reduction even when the loads are increased in a random manner.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125087360","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 : 2016-09-01DOI: 10.1109/NAPS.2016.7747914
Yingying Zhao, Dongsheng Li, A. Dong, Jiajia Lin, Dahai Kang, Li Shang
Accurate prognosis of wind turbine generator failures is essential for reducing operation and maintenance costs in wind farms. Existing methods rely on expensive, purpose-built condition monitoring systems to conduct diagnosis and prognosis of wind turbine generator failures. In this paper, we present a prognosis method to predict the remaining useful life (RUL) of generators, which requires no additional hardware support beyond widely adopted SCADA system. This work first introduces a notion, Anomaly Operation Index (AOI), to quantitatively measure wind turbine performance degradation in runtime. It then presents a data-driven wind turbine anomaly detection method and a time series analysis method to predict the wind turbine generator RUL. Experimental study on real-world wind farm data demonstrates that the proposed methods can achieve accurate prediction of wind turbine generator RUL and provide sufficient lead time for scheduling maintenance and repair.
{"title":"Fault prognosis of wind turbine generator using SCADA data","authors":"Yingying Zhao, Dongsheng Li, A. Dong, Jiajia Lin, Dahai Kang, Li Shang","doi":"10.1109/NAPS.2016.7747914","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747914","url":null,"abstract":"Accurate prognosis of wind turbine generator failures is essential for reducing operation and maintenance costs in wind farms. Existing methods rely on expensive, purpose-built condition monitoring systems to conduct diagnosis and prognosis of wind turbine generator failures. In this paper, we present a prognosis method to predict the remaining useful life (RUL) of generators, which requires no additional hardware support beyond widely adopted SCADA system. This work first introduces a notion, Anomaly Operation Index (AOI), to quantitatively measure wind turbine performance degradation in runtime. It then presents a data-driven wind turbine anomaly detection method and a time series analysis method to predict the wind turbine generator RUL. Experimental study on real-world wind farm data demonstrates that the proposed methods can achieve accurate prediction of wind turbine generator RUL and provide sufficient lead time for scheduling maintenance and repair.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125096532","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 : 2016-09-01DOI: 10.1109/NAPS.2016.7747896
V. Sarfi, I. Niazazari, H. Livani
This paper proposes a new multi-objective optimization technique for economic emission dispatch in microgrids. This new technique is developed based of fireworks algorithm and is implemented in a microgrid with dispatachable microsources and non-dispatachable renewable energy resources such as solar generators. In this paper the multi-objective fireworks optimization is developed to find the most economic operating condition not only to minimize the fuel cost, but also to find the best environmentally friendly solution without violating any constraints. This method is a swarm intelligence algorithm which solves a multi-objective optimization problem much faster than other well-known algorithms with the help of a quality measure known as S-metric. The results of this new method are compared with the well-accepted methodology, non-dominated sorting genetic algorithm II (NSGA-II) as the benchmark.
{"title":"Multiobjective fireworks optimization framework for economic emission dispatch in microgrids","authors":"V. Sarfi, I. Niazazari, H. Livani","doi":"10.1109/NAPS.2016.7747896","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747896","url":null,"abstract":"This paper proposes a new multi-objective optimization technique for economic emission dispatch in microgrids. This new technique is developed based of fireworks algorithm and is implemented in a microgrid with dispatachable microsources and non-dispatachable renewable energy resources such as solar generators. In this paper the multi-objective fireworks optimization is developed to find the most economic operating condition not only to minimize the fuel cost, but also to find the best environmentally friendly solution without violating any constraints. This method is a swarm intelligence algorithm which solves a multi-objective optimization problem much faster than other well-known algorithms with the help of a quality measure known as S-metric. The results of this new method are compared with the well-accepted methodology, non-dominated sorting genetic algorithm II (NSGA-II) as the benchmark.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126710896","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 : 2016-09-01DOI: 10.1109/NAPS.2016.7747933
Yiyun Yao, Zuyi Li
State estimation (SE) is critical to modern power system control center and is vulnerable to cyber-attacks. In this paper, a SE algorithm based on random measurements selection, which is inspired by the concept of moving target defense (MTD), is developed to prevent and mitigate stealthy cyber-attacks. With the proposed SE, a library of selected measurements scenarios is first generated offline given the available measurements and network topology. During online operation, multiple weighted least square (WLS) based SEs are processed in parallel with randomly picked scenarios from the library. The final solution is selected based on the largest normalized residuals with regard to individual scenarios. The effectiveness of the proposed SE is examined by attack-defense experiments on IEEE 14-bus, 39-bus, 57-bus, and 118-bus systems.
{"title":"MTD-inspired state estimation based on random measurements selection","authors":"Yiyun Yao, Zuyi Li","doi":"10.1109/NAPS.2016.7747933","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747933","url":null,"abstract":"State estimation (SE) is critical to modern power system control center and is vulnerable to cyber-attacks. In this paper, a SE algorithm based on random measurements selection, which is inspired by the concept of moving target defense (MTD), is developed to prevent and mitigate stealthy cyber-attacks. With the proposed SE, a library of selected measurements scenarios is first generated offline given the available measurements and network topology. During online operation, multiple weighted least square (WLS) based SEs are processed in parallel with randomly picked scenarios from the library. The final solution is selected based on the largest normalized residuals with regard to individual scenarios. The effectiveness of the proposed SE is examined by attack-defense experiments on IEEE 14-bus, 39-bus, 57-bus, and 118-bus systems.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114908142","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 : 2016-09-01DOI: 10.1109/NAPS.2016.7747882
Seth Cooper, Andrew Klem, M. H. Nehrir, Hong-zhi Ga
The dual active bridge (DAB) is an attractive device for high-power DC to DC bidirectional power conversion. In order to develop a closed-loop controller for a DAB, an accurate dynamic model must be developed. A continuous model is preferred because it provides more insight into the principle dynamics and is suitable for use in an acuasal simulation. Acausal notation for simulation defines relationships in their natural form, as a system of differential equations, and leaves the method of solving the equations up to the simulation engine. This paper develops a continuous state-space averaged model for a DAB that is shown to be accurate when numerical solutions are compared to a more detailed numerical model that includes switching dynamics. The improved model is suitable for many types of power and control simulations.
{"title":"An improved state-space averaged model of a dual active bridge converter for use in acausal system modeling","authors":"Seth Cooper, Andrew Klem, M. H. Nehrir, Hong-zhi Ga","doi":"10.1109/NAPS.2016.7747882","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747882","url":null,"abstract":"The dual active bridge (DAB) is an attractive device for high-power DC to DC bidirectional power conversion. In order to develop a closed-loop controller for a DAB, an accurate dynamic model must be developed. A continuous model is preferred because it provides more insight into the principle dynamics and is suitable for use in an acuasal simulation. Acausal notation for simulation defines relationships in their natural form, as a system of differential equations, and leaves the method of solving the equations up to the simulation engine. This paper develops a continuous state-space averaged model for a DAB that is shown to be accurate when numerical solutions are compared to a more detailed numerical model that includes switching dynamics. The improved model is suitable for many types of power and control simulations.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122726015","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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