Pub Date : 2016-09-01DOI: 10.1109/NAPS.2016.7747983
Frhat Aeiad, Wenzhong Gao, J. Momoh
Bad data detection and identification is an important step in state estimation procedures. Finding the values of the state variables relies on real time measurements which are normally contaminated by noise or may suffer some error due to misconfiguration. Furthermore, the data is a target for hackers who try to change some measurement readings that lead operators to take wrong decisions. The need for accurate and reliable measurements is one of the research areas that have been extensively investigated in the last few decades. in this paper, Multidimensional Scaling (MDS) is used as a new technique to identify the source of the bad data in the network. Weighted least square and Chi-squared test have been used to calculate the state variables and to test the presence of the bad data. Finally, MDS is used to identify the source of the bad data. Different scenarios have been tested on the IEEE 14 bus system by using the proposed method.
{"title":"Bad data detection for smart grid state estimation","authors":"Frhat Aeiad, Wenzhong Gao, J. Momoh","doi":"10.1109/NAPS.2016.7747983","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747983","url":null,"abstract":"Bad data detection and identification is an important step in state estimation procedures. Finding the values of the state variables relies on real time measurements which are normally contaminated by noise or may suffer some error due to misconfiguration. Furthermore, the data is a target for hackers who try to change some measurement readings that lead operators to take wrong decisions. The need for accurate and reliable measurements is one of the research areas that have been extensively investigated in the last few decades. in this paper, Multidimensional Scaling (MDS) is used as a new technique to identify the source of the bad data in the network. Weighted least square and Chi-squared test have been used to calculate the state variables and to test the presence of the bad data. Finally, MDS is used to identify the source of the bad data. Different scenarios have been tested on the IEEE 14 bus system by using the proposed method.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"45 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":"124893948","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.2016.7747952
F. Diaz-Franco, T. Vu, T. El Mezyani, C. Edrington
This paper focuses on the use of model predictive control (M PC) to control a two-stage photovoltaic (PV) system in order to accomplish new grid code standards for low-voltage ride-through (LVRT). The PV system is composed by a DC/DC boost converter at the generator-side, followed by a two-level three-phase grid - tied inverter. The PV's voltage support function through reactive power injection is examined using the mentioned control technique, and a PV power-reference tracking system is implemented during the Voltage sag to avoid the activation of the overcurrent tripping mechanism. The system is modeled in Matlab/Simulink and PLECS in order to understand its operation, and to evaluate the effectiveness of the MPC proposed algorithm to fulfill LVRT requirements for PV Systems.
{"title":"Low-voltage ride-through for PV systems using model predictive control approach","authors":"F. Diaz-Franco, T. Vu, T. El Mezyani, C. Edrington","doi":"10.1109/NAPS.2016.7747952","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747952","url":null,"abstract":"This paper focuses on the use of model predictive control (M PC) to control a two-stage photovoltaic (PV) system in order to accomplish new grid code standards for low-voltage ride-through (LVRT). The PV system is composed by a DC/DC boost converter at the generator-side, followed by a two-level three-phase grid - tied inverter. The PV's voltage support function through reactive power injection is examined using the mentioned control technique, and a PV power-reference tracking system is implemented during the Voltage sag to avoid the activation of the overcurrent tripping mechanism. The system is modeled in Matlab/Simulink and PLECS in order to understand its operation, and to evaluate the effectiveness of the MPC proposed algorithm to fulfill LVRT requirements for PV Systems.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"21 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":"123657250","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.2016.7747932
Ricardo Siqueira de Carvalho, S. Mohagheghi
Smart grids are cyber-physical systems that integrate an information and communication technology (ICT) network with the existing power system infrastructure. As smart grids become more mature, the interdependency between the cyber and physical systems becomes stronger. Because of this, the traditional reliability assessment, power grid operations, and power system security assessment techniques, where the physical layer of the power system is considered in isolation and without considering the impact of the communication network, are not sufficient for providing a comprehensive picture of the system anymore. Hence, an interdependent study is needed where both the physical layer and the communication network are taken into account. The objective of this paper is to provide a survey of some of the latest studies and findings in the literature about the impact of communication imperfections on smart grid reliability and operation. Also, a brief overview of some of the recent cyber security studies related to power grid operation has been presented. Finally, some current research questions and future trends in smart grid communications and cyber security are discussed.
{"title":"Analyzing impact of communication network topologies on reconfiguration of networked microgrids, impact of communication system on smart grid reliability, security and operation","authors":"Ricardo Siqueira de Carvalho, S. Mohagheghi","doi":"10.1109/NAPS.2016.7747932","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747932","url":null,"abstract":"Smart grids are cyber-physical systems that integrate an information and communication technology (ICT) network with the existing power system infrastructure. As smart grids become more mature, the interdependency between the cyber and physical systems becomes stronger. Because of this, the traditional reliability assessment, power grid operations, and power system security assessment techniques, where the physical layer of the power system is considered in isolation and without considering the impact of the communication network, are not sufficient for providing a comprehensive picture of the system anymore. Hence, an interdependent study is needed where both the physical layer and the communication network are taken into account. The objective of this paper is to provide a survey of some of the latest studies and findings in the literature about the impact of communication imperfections on smart grid reliability and operation. Also, a brief overview of some of the recent cyber security studies related to power grid operation has been presented. Finally, some current research questions and future trends in smart grid communications and cyber security are discussed.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"13 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":"125784009","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.2016.7747830
Bowen Li, Spencer D. Maroukis, Yashen Lin, J. Mathieu
Aggregations of controllable loads are considered to be a fast-responding, cost-efficient, and environmental-friendly candidate for power system ancillary services. Unlike conventional service providers, the potential capacity from the aggregation is highly affected by factors like ambient conditions and load usage patterns. Previous work modeled aggregations of controllable loads (such as air conditioners) as thermal batteries, which are capable of providing reserves but with uncertain capacity. A stochastic optimal power flow problem was formulated to manage this uncertainty, as well as uncertainty in renewable generation. In this paper, we explore how the types and levels of uncertainty, generation reserve costs, and controllable load capacity affect the dispatch solution, operational costs, and CO2 emissions. We also compare the results of two methods for solving the stochastic optimization problem, namely the probabilistically robust method and analytical reformulation assuming Gaussian distributions. Case studies are conducted on a modified IEEE 9-bus system with renewables, controllable loads, and congestion. We find that different types and levels of uncertainty have significant impacts on dispatch and emissions. More controllable loads and less conservative solution methodologies lead to lower costs and emissions.
{"title":"Impact of uncertainty from load-based reserves and renewables on dispatch costs and emissions","authors":"Bowen Li, Spencer D. Maroukis, Yashen Lin, J. Mathieu","doi":"10.1109/NAPS.2016.7747830","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747830","url":null,"abstract":"Aggregations of controllable loads are considered to be a fast-responding, cost-efficient, and environmental-friendly candidate for power system ancillary services. Unlike conventional service providers, the potential capacity from the aggregation is highly affected by factors like ambient conditions and load usage patterns. Previous work modeled aggregations of controllable loads (such as air conditioners) as thermal batteries, which are capable of providing reserves but with uncertain capacity. A stochastic optimal power flow problem was formulated to manage this uncertainty, as well as uncertainty in renewable generation. In this paper, we explore how the types and levels of uncertainty, generation reserve costs, and controllable load capacity affect the dispatch solution, operational costs, and CO2 emissions. We also compare the results of two methods for solving the stochastic optimization problem, namely the probabilistically robust method and analytical reformulation assuming Gaussian distributions. Case studies are conducted on a modified IEEE 9-bus system with renewables, controllable loads, and congestion. We find that different types and levels of uncertainty have significant impacts on dispatch and emissions. More controllable loads and less conservative solution methodologies lead to lower costs and emissions.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"129 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":"130037351","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.2016.7747916
E. Muljadi, V. Gevorgian, A. Wright, J. Donegan, C. Marnagh, J. Mcentee
As renewable generation has become less expensive during recent decades, and it becomes more accepted by the global population, the focus on renewable generation has expanded to include new types with promising future applications, such as river and tidal generation. Although the utilization of power electronics and electric machines in industry is phenomenal, the emphasis on system design is different for various sectors of industry. In precision control, robotics, and weaponry, the design emphasis is on accuracy and reliability with less concern for the cost of the final product. In energy generation, the cost of energy is the prime concern; thus, capital expenditures (CAPEX) and operations and maintenance expenditures (OPEX) are the major design objectives. This paper describes the electrical power conversion aspects of river and tidal generation. Although modern power converter control is available to control the generation side, the design was chosen on the bases of minimizing the CAPEX and OPEX; thus, the architecture is simple and modular for ease of replacement and maintenance. The power conversion is simplified by considering a simple diode bridge and a DC-DC power converter to take advantage of abundant and low-cost photovoltaic inverters that have well-proven grid integration characteristics (i.e., the capability to produce energy with good power quality and control real power and voltage on the grid side).
{"title":"Electrical power conversion of river and tidal power generator","authors":"E. Muljadi, V. Gevorgian, A. Wright, J. Donegan, C. Marnagh, J. Mcentee","doi":"10.1109/NAPS.2016.7747916","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747916","url":null,"abstract":"As renewable generation has become less expensive during recent decades, and it becomes more accepted by the global population, the focus on renewable generation has expanded to include new types with promising future applications, such as river and tidal generation. Although the utilization of power electronics and electric machines in industry is phenomenal, the emphasis on system design is different for various sectors of industry. In precision control, robotics, and weaponry, the design emphasis is on accuracy and reliability with less concern for the cost of the final product. In energy generation, the cost of energy is the prime concern; thus, capital expenditures (CAPEX) and operations and maintenance expenditures (OPEX) are the major design objectives. This paper describes the electrical power conversion aspects of river and tidal generation. Although modern power converter control is available to control the generation side, the design was chosen on the bases of minimizing the CAPEX and OPEX; thus, the architecture is simple and modular for ease of replacement and maintenance. The power conversion is simplified by considering a simple diode bridge and a DC-DC power converter to take advantage of abundant and low-cost photovoltaic inverters that have well-proven grid integration characteristics (i.e., the capability to produce energy with good power quality and control real power and voltage on the grid side).","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"48 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":"128695669","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.2016.7747994
Mohana S. Alanazi, A. Khodaei
Solar forecasting is a pivotal factor in a viable solar energy deployment to support reliable and cost-effective grid operation and control. This paper proposes a new approach to overcome one of the most significant challenges in solar generation forecasting, i.e., the limited availability of the stationary data sets. This challenge is addressed by converting the non-stationary historical solar irradiance data into a stationary set, which will be further validated using an ADF test. This conversion will be followed by a neural network-based forecasting and proper post-processing steps. Numerical simulations exhibit the performance of the proposed method, which has achieved a mean absolute percentage error (MAPE) of less than 1% under different weather conditions.
{"title":"Day-ahead solar forecasting using time series stationarization and feed-forward neural network","authors":"Mohana S. Alanazi, A. Khodaei","doi":"10.1109/NAPS.2016.7747994","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747994","url":null,"abstract":"Solar forecasting is a pivotal factor in a viable solar energy deployment to support reliable and cost-effective grid operation and control. This paper proposes a new approach to overcome one of the most significant challenges in solar generation forecasting, i.e., the limited availability of the stationary data sets. This challenge is addressed by converting the non-stationary historical solar irradiance data into a stationary set, which will be further validated using an ADF test. This conversion will be followed by a neural network-based forecasting and proper post-processing steps. Numerical simulations exhibit the performance of the proposed method, which has achieved a mean absolute percentage error (MAPE) of less than 1% under different weather conditions.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"324 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":"115868949","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.2016.7748000
Liangyi Sun, Rui Fan, A. Meliopoulos, Yu Liu, Zhenyu Tan
A dynamic state estimation (DSE) based protection algorithm using weighted least square (WLS) method was introduced recently. In this paper, the DSE-based protection algorithm using constraint weighted least squares (CWLS) method is applied to capacitor bank protection. This approach monitors the health status of the capacitor bank by fitting real time measurements to the capacitor bank dynamic model via dynamic state estimation. Virtual measurements are added to the measurements set by considering the physical laws that must be obeyed by the capacitor bank (i.e. KVL, KCL). Virtual measurements can be handled as measurements with high accuracy or as constraints to the dynamic state estimation. The CWLS method treats the virtual measurements as constraints while the WLS method treats them as highly accuracy measurements. Comparison of capacitor bank protection results using unconstraint WLS and CWLS is provided. It is shown that the proposed method can detect internal faults and issue the trip signal correctly The use of CWLS provides a more sensitive protection for capacitor banks.
{"title":"Capacitor bank protection via constraint WLS dynamic state estimation method (CWLS-DSE)","authors":"Liangyi Sun, Rui Fan, A. Meliopoulos, Yu Liu, Zhenyu Tan","doi":"10.1109/NAPS.2016.7748000","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7748000","url":null,"abstract":"A dynamic state estimation (DSE) based protection algorithm using weighted least square (WLS) method was introduced recently. In this paper, the DSE-based protection algorithm using constraint weighted least squares (CWLS) method is applied to capacitor bank protection. This approach monitors the health status of the capacitor bank by fitting real time measurements to the capacitor bank dynamic model via dynamic state estimation. Virtual measurements are added to the measurements set by considering the physical laws that must be obeyed by the capacitor bank (i.e. KVL, KCL). Virtual measurements can be handled as measurements with high accuracy or as constraints to the dynamic state estimation. The CWLS method treats the virtual measurements as constraints while the WLS method treats them as highly accuracy measurements. Comparison of capacitor bank protection results using unconstraint WLS and CWLS is provided. It is shown that the proposed method can detect internal faults and issue the trip signal correctly The use of CWLS provides a more sensitive protection for capacitor banks.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"18 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":"127910955","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.2016.7747984
Shengjun Huang, V. Dinavahi
This paper formulates the security constrained transmission expansion planning (SCTEP) into a standard two-stage stochastic programming (SP) problem with complete recourse, which is then tackled by Benders decomposition (BD) due to its special decomposable structure, additionally, three improvements are also employed to accelerate the classical BD: valid inequality, multicut strategy, and optimal precondition. The performance of the improved BD is demonstrated by massively case studies on three classical benchmarks: the Garver 6-bus system, the IEEE 24-bus system, and the IEEE 118-bus system. Significant reduction in both execution time and the number of iterations are achieved for all acceleration strategies.
{"title":"Security constrained transmission expansion planning by accelerated benders decomposition","authors":"Shengjun Huang, V. Dinavahi","doi":"10.1109/NAPS.2016.7747984","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747984","url":null,"abstract":"This paper formulates the security constrained transmission expansion planning (SCTEP) into a standard two-stage stochastic programming (SP) problem with complete recourse, which is then tackled by Benders decomposition (BD) due to its special decomposable structure, additionally, three improvements are also employed to accelerate the classical BD: valid inequality, multicut strategy, and optimal precondition. The performance of the improved BD is demonstrated by massively case studies on three classical benchmarks: the Garver 6-bus system, the IEEE 24-bus system, and the IEEE 118-bus system. Significant reduction in both execution time and the number of iterations are achieved for all acceleration strategies.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"14 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":"128781107","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.2016.7747901
M. Backes, Ikponmwosa Idehen, Timothy M. Yardley, Prosper Panumpabi
Power Africa is an initiative launched by US President Barack Obama in July 2013 to bring power to unelectrified communities in Sub-Saharan Africa. We developed a power system model of the rural village of Katumbi, Tanzania. Utilizing RTDS, a cutting edge technology for power system simulation, we built and verified a microgrid based on real data from Katumbi. The microgrid is powered by distributed energy resources such as a solar panel farm, wind turbines, and thermal generation. The control capabilities of the microgrid are reactive power support, fault voltage ride through, load shedding, and voltage unbalance. Simulation shows the microgrid is able to withstand a variety of disturbances, and is built for a population and geographic expansion of Katumbi due to the numerous benefits that electrification provides rural communities. The microgrid allows for the addition of community resources such as a hospital, freezers to store the catch of fishermen, a school, and a tower for wireless communication within the community. These will bring economic, social, and health benefits to this rural, impoverished community.
{"title":"Off-grid microgrid development for the village of Katumbi in Tanzania","authors":"M. Backes, Ikponmwosa Idehen, Timothy M. Yardley, Prosper Panumpabi","doi":"10.1109/NAPS.2016.7747901","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747901","url":null,"abstract":"Power Africa is an initiative launched by US President Barack Obama in July 2013 to bring power to unelectrified communities in Sub-Saharan Africa. We developed a power system model of the rural village of Katumbi, Tanzania. Utilizing RTDS, a cutting edge technology for power system simulation, we built and verified a microgrid based on real data from Katumbi. The microgrid is powered by distributed energy resources such as a solar panel farm, wind turbines, and thermal generation. The control capabilities of the microgrid are reactive power support, fault voltage ride through, load shedding, and voltage unbalance. Simulation shows the microgrid is able to withstand a variety of disturbances, and is built for a population and geographic expansion of Katumbi due to the numerous benefits that electrification provides rural communities. The microgrid allows for the addition of community resources such as a hospital, freezers to store the catch of fishermen, a school, and a tower for wireless communication within the community. These will bring economic, social, and health benefits to this rural, impoverished community.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"47 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":"134445336","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.2016.7747962
K. Baker, E. Dall’Anese, T. Summers
This paper outlines a data-driven, distributionally robust approach to solve chance-constrained AC optimal power flow problems in distribution networks. Uncertain forecasts for loads and power generated by photovoltaic (PV) systems are considered, with the goal of minimizing PV curtailment while meeting power flow and voltage regulation constraints. A data-driven approach is utilized to develop a distributionally robust conservative convex approximation of the chance-constraints; particularly, the mean and covariance matrix of the forecast errors are updated online, and leveraged to enforce voltage regulation with predetermined probability via Chebyshev-based bounds. By combining an accurate linear approximation of the AC power flow equations with the distributionally robust chance constraint reformulation, the resulting optimization problem becomes convex and computationally tractable.
{"title":"Distribution-agnostic stochastic optimal power flow for distribution grids","authors":"K. Baker, E. Dall’Anese, T. Summers","doi":"10.1109/NAPS.2016.7747962","DOIUrl":"https://doi.org/10.1109/NAPS.2016.7747962","url":null,"abstract":"This paper outlines a data-driven, distributionally robust approach to solve chance-constrained AC optimal power flow problems in distribution networks. Uncertain forecasts for loads and power generated by photovoltaic (PV) systems are considered, with the goal of minimizing PV curtailment while meeting power flow and voltage regulation constraints. A data-driven approach is utilized to develop a distributionally robust conservative convex approximation of the chance-constraints; particularly, the mean and covariance matrix of the forecast errors are updated online, and leveraged to enforce voltage regulation with predetermined probability via Chebyshev-based bounds. By combining an accurate linear approximation of the AC power flow equations with the distributionally robust chance constraint reformulation, the resulting optimization problem becomes convex and computationally tractable.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"13 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":"127757545","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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