Pub Date : 2013-12-19DOI: 10.1109/SmartGridComm.2013.6687960
T. Wijaya, Dipyaman Banerjee, T. Ganu, D. Chakraborty, S. Battacharya, Thanasis G. Papaioannou, D. Seetharam, K. Aberer
Demand Response (DR) is a mechanism in which electricity consumers alter their demand in response to power grid's supply and economic conditions. DR programs have the potential to improve resource efficiency, sustainability, grid reliability and economic viability by providing tighter alignment between demand and supply. However, implementing DR program is a non-trivial task as it requires good knowledge of electricity consumption preferences, economic models and contextual factors. Developing such knowledge through real world studies can be expensive and be time consuming. As a result, utility companies have been finding it complicated to analyze potential viability and return on investments of DR programs for various `what-if' scenarios. To address this problem, we present DRSim - a cyber-physical simulator that allows utility companies to study demand side participation aspects of communities with various practical scenarios. DRSim is based on the principles of agent-oriented modeling of users' behavior and context. It is able to model the emergent behavior of a community based on real data traces that contain partial information about the environment. DRSim is a highly extensible framework to accommodate new data sources, new analytical functionalities and evolve its modeling power. Feasibility experiments show the modeling and analysis potential of DRSim in practical settings.
{"title":"DRSim: A cyber physical simulator for Demand Response systems","authors":"T. Wijaya, Dipyaman Banerjee, T. Ganu, D. Chakraborty, S. Battacharya, Thanasis G. Papaioannou, D. Seetharam, K. Aberer","doi":"10.1109/SmartGridComm.2013.6687960","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687960","url":null,"abstract":"Demand Response (DR) is a mechanism in which electricity consumers alter their demand in response to power grid's supply and economic conditions. DR programs have the potential to improve resource efficiency, sustainability, grid reliability and economic viability by providing tighter alignment between demand and supply. However, implementing DR program is a non-trivial task as it requires good knowledge of electricity consumption preferences, economic models and contextual factors. Developing such knowledge through real world studies can be expensive and be time consuming. As a result, utility companies have been finding it complicated to analyze potential viability and return on investments of DR programs for various `what-if' scenarios. To address this problem, we present DRSim - a cyber-physical simulator that allows utility companies to study demand side participation aspects of communities with various practical scenarios. DRSim is based on the principles of agent-oriented modeling of users' behavior and context. It is able to model the emergent behavior of a community based on real data traces that contain partial information about the environment. DRSim is a highly extensible framework to accommodate new data sources, new analytical functionalities and evolve its modeling power. Feasibility experiments show the modeling and analysis potential of DRSim in practical settings.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124646944","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 : 2013-12-19DOI: 10.1109/SmartGridComm.2013.6687934
Ceeman Vellaithurai, A. Srivastava, S. Zonouz
Trustworthy critical power grid infrastructures require suitable cyber and power security protection efforts. Expert system operators play a crucial role in protecting complex power-grid networks; however, inefficient training of system operators regarding potential cyber attacks and physical security threats can potentially result in malicious compromises and catastrophic consequences. In this paper, we present SECPSIM, a user-friendly framework based on mathematical models of corrective control actions against various intrusions and failure scenarios. Our experimental results show that SECPSIM can help in learning and provide appropriate corrective cyber-physical control actions efficiently, and provide inexperienced individuals with an effective tutorial user interface.
{"title":"SECPSIM: A Training Simulator for cyber-power infrastructure security","authors":"Ceeman Vellaithurai, A. Srivastava, S. Zonouz","doi":"10.1109/SmartGridComm.2013.6687934","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687934","url":null,"abstract":"Trustworthy critical power grid infrastructures require suitable cyber and power security protection efforts. Expert system operators play a crucial role in protecting complex power-grid networks; however, inefficient training of system operators regarding potential cyber attacks and physical security threats can potentially result in malicious compromises and catastrophic consequences. In this paper, we present SECPSIM, a user-friendly framework based on mathematical models of corrective control actions against various intrusions and failure scenarios. Our experimental results show that SECPSIM can help in learning and provide appropriate corrective cyber-physical control actions efficiently, and provide inexperienced individuals with an effective tutorial user interface.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124027124","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 : 2013-12-19DOI: 10.1109/SmartGridComm.2013.6687938
Yun Wei, C. Ji, F. Galvan, Stephen Couvillon, George Orellana
Resilience of power distribution is pertinent to the energy grid under severe weather. This work develops an analytical formulation for large-scale failure and recovery of power distribution induced by severe weather. A focus is on incorporating pertinent characteristics of topological network structures into spatial temporal modeling. Such characteristics are new notations as dynamic failure- and recovery-neighborhoods. The neighborhoods quantify correlated failures and recoveries due to topology and types of components in power distribution. The resulting model is a multi-scale non-stationary spatial temporal random process. Dynamic resilience is then defined based on the model. Using the model and large-scale real data from Hurricane Ike, unique characteristics are identified: The failures follow the 80/20 rule where 74.3% of the total failures result from 20.7% of failure neighborhoods with up to 72 components “failed” together. Thus the hurricane caused a large number of correlated failures. Unlike the failures, the recoveries follow 60/90 rule: 59.3% of recoveries resulted from 92.7% of all neighborhoods where either one component alone or two together recovered. Thus about 60% recoveries were uncorrelated and required individual restorations. The failure and recovery processes are further studied through the resilience metric to identify the least resilient regions and time durations.
{"title":"Dynamic modeling and resilience for power distribution","authors":"Yun Wei, C. Ji, F. Galvan, Stephen Couvillon, George Orellana","doi":"10.1109/SmartGridComm.2013.6687938","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687938","url":null,"abstract":"Resilience of power distribution is pertinent to the energy grid under severe weather. This work develops an analytical formulation for large-scale failure and recovery of power distribution induced by severe weather. A focus is on incorporating pertinent characteristics of topological network structures into spatial temporal modeling. Such characteristics are new notations as dynamic failure- and recovery-neighborhoods. The neighborhoods quantify correlated failures and recoveries due to topology and types of components in power distribution. The resulting model is a multi-scale non-stationary spatial temporal random process. Dynamic resilience is then defined based on the model. Using the model and large-scale real data from Hurricane Ike, unique characteristics are identified: The failures follow the 80/20 rule where 74.3% of the total failures result from 20.7% of failure neighborhoods with up to 72 components “failed” together. Thus the hurricane caused a large number of correlated failures. Unlike the failures, the recoveries follow 60/90 rule: 59.3% of recoveries resulted from 92.7% of all neighborhoods where either one component alone or two together recovered. Thus about 60% recoveries were uncorrelated and required individual restorations. The failure and recovery processes are further studied through the resilience metric to identify the least resilient regions and time durations.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125116792","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 : 2013-12-19DOI: 10.1109/SmartGridComm.2013.6687932
Jay Taneja, Virginia Smith, D. Culler, C. Rosenberg
Electricity grids are transforming as renewables proliferate, yet operational concerns due to fluctuations in renewables sources could limit the ultimate potential for high penetrations of renewables. In this paper, we compare three electricity grids - California, Germany, and Ontario - studying the effects of relative cost of solar and wind generation on the selection of the renewables mix, and examine the resulting excess generation. We then observe the effects of the renewables mix and the use of baseload energy generation on the limits to renewables penetration, quantifying what proportion of delivered energy can be provided by renewables. Our study shows that the optimal renewables mix, from the perspective of minimizing total cost of generation, is highly dependent on the relative costs of technology, and that above a certain penetration rate, different for each grid, the optimal mix must contain both solar and wind generation.
{"title":"A comparative study of high renewables penetration electricity grids","authors":"Jay Taneja, Virginia Smith, D. Culler, C. Rosenberg","doi":"10.1109/SmartGridComm.2013.6687932","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687932","url":null,"abstract":"Electricity grids are transforming as renewables proliferate, yet operational concerns due to fluctuations in renewables sources could limit the ultimate potential for high penetrations of renewables. In this paper, we compare three electricity grids - California, Germany, and Ontario - studying the effects of relative cost of solar and wind generation on the selection of the renewables mix, and examine the resulting excess generation. We then observe the effects of the renewables mix and the use of baseload energy generation on the limits to renewables penetration, quantifying what proportion of delivered energy can be provided by renewables. Our study shows that the optimal renewables mix, from the perspective of minimizing total cost of generation, is highly dependent on the relative costs of technology, and that above a certain penetration rate, different for each grid, the optimal mix must contain both solar and wind generation.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115471171","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 : 2013-12-19DOI: 10.1109/SmartGridComm.2013.6687939
Xiao Li, H. Poor, A. Scaglione
In this paper, the blind topology identification problem for power systems only using power injection data at each bus is considered. As metering becomes widespread in the smart grid, a natural question arising is how much information about the underlying infrastructure can be inferred from such data. The identifiability of the grid topology is studied, and an efficient learning algorithm to estimate the grid Laplacian matrix (i.e., the graph equivalent of the grid admittance matrix) is proposed. Finally, the performance of our algorithm for the IEEE-14 bus system is demonstrated, and the consistency of the recovered graph with the true graph associated with the underlying power grid is shown in simulations.
{"title":"Blind topology identification for power systems","authors":"Xiao Li, H. Poor, A. Scaglione","doi":"10.1109/SmartGridComm.2013.6687939","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687939","url":null,"abstract":"In this paper, the blind topology identification problem for power systems only using power injection data at each bus is considered. As metering becomes widespread in the smart grid, a natural question arising is how much information about the underlying infrastructure can be inferred from such data. The identifiability of the grid topology is studied, and an efficient learning algorithm to estimate the grid Laplacian matrix (i.e., the graph equivalent of the grid admittance matrix) is proposed. Finally, the performance of our algorithm for the IEEE-14 bus system is demonstrated, and the consistency of the recovered graph with the true graph associated with the underlying power grid is shown in simulations.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126662754","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 : 2013-12-19DOI: 10.1109/SmartGridComm.2013.6687986
Husheng Li, Zhu Han, J. Song
In many cyber physical systems such as smart grids, communications are of key importance for controlling or optimizing the operation of physical dynamics. It is possible that the realtime measurement traffic for controlling the physical dynamics overlays delay-tolerant queuing data flows such as Internet service in the same communication infrastructure. The scheduling of the hybrid system is then important for the performance of both realtime control and data throughput. To balance both controls of the physical dynamics and queuing dynamics, they are integrated within the same framework of stochastic optimization, which is solved using approximate algorithm. The proposed algorithm is then applied in the context of smart grids and is demonstrated to achieve good performance over simple scheduling algorithms that are not aware of the physical dynamics state.
{"title":"Stabilizing hybrid data traffics in cyber physical systems with case study on smart grid","authors":"Husheng Li, Zhu Han, J. Song","doi":"10.1109/SmartGridComm.2013.6687986","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687986","url":null,"abstract":"In many cyber physical systems such as smart grids, communications are of key importance for controlling or optimizing the operation of physical dynamics. It is possible that the realtime measurement traffic for controlling the physical dynamics overlays delay-tolerant queuing data flows such as Internet service in the same communication infrastructure. The scheduling of the hybrid system is then important for the performance of both realtime control and data throughput. To balance both controls of the physical dynamics and queuing dynamics, they are integrated within the same framework of stochastic optimization, which is solved using approximate algorithm. The proposed algorithm is then applied in the context of smart grids and is demonstrated to achieve good performance over simple scheduling algorithms that are not aware of the physical dynamics state.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125966620","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 : 2013-12-19DOI: 10.1109/SmartGridComm.2013.6688040
Hao Huang, Jin Xu, Zhenzhou Peng, Shinjae Yoo, Dantong Yu, D. Huang, Hong Qin
Variability of solar energy is the most significant issue for integrating solar energy into the power Grid. There are pressing demands to develop methods to accurately estimate cloud motion that directly affects the stability of solar power output.We propose a solar prediction system that can detect cloud movements from the TSI (total sky imager) images, and then estimate the future cloud position over solar panels and subsequent solar irradiance fluctuations incurred by cloud transients. The experiment studies show that our proposed approach significantly improves the quality of cloud motion estimation within a time window (up to a few minutes) that is sufficient for grid operators to take actions to mitigate the solar power volatility.
{"title":"Cloud motion estimation for short term solar irradiation prediction","authors":"Hao Huang, Jin Xu, Zhenzhou Peng, Shinjae Yoo, Dantong Yu, D. Huang, Hong Qin","doi":"10.1109/SmartGridComm.2013.6688040","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6688040","url":null,"abstract":"Variability of solar energy is the most significant issue for integrating solar energy into the power Grid. There are pressing demands to develop methods to accurately estimate cloud motion that directly affects the stability of solar power output.We propose a solar prediction system that can detect cloud movements from the TSI (total sky imager) images, and then estimate the future cloud position over solar panels and subsequent solar irradiance fluctuations incurred by cloud transients. The experiment studies show that our proposed approach significantly improves the quality of cloud motion estimation within a time window (up to a few minutes) that is sufficient for grid operators to take actions to mitigate the solar power volatility.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124886361","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 : 2013-12-19DOI: 10.1109/SmartGridComm.2013.6687984
B. Scheidegger, Y. Pignolet, E. Ferranti
IT infrastructures in commercial and industrial sites are recently undergoing an evolution, which requires them to integrate large numbers of heterogeneous devices, often using multi-protocol networks. One of the driver of this evolution is represented by a recent trend in the energy sector, where local sites are encouraged to build their own microgrids. Furthermore, the lowering costs of sites automation and monitoring systems are making their adoption by industrial and commercial sites much easier to justify.In order to make the most out of these innovations, the communication between all the players of these systems is vital, and a constant monitoring of it essential. However, despite the importance of the data network, there exist currently no vendor-independent analysis and management tools tailored for such networks, usually comprised of various, sometimes very different, network types. Therefore, we present Smart Eagle, a distributed network analysis and monitoring tool capable of dealing with building automation and low-rate wireless personal area networks. We introduce the architecture of Smart Eagle, and report on our experience in taking measurements on an existing site management communication network. In particular, we were able to gather meaningful measurements from both IEEE 802.15.4 and KNX networks, without intervening on existing devices or on the underlying network infrastructure.
{"title":"Smart Eagle - A bird's-eye view on heterogeneous networks for commercial and industrial sites","authors":"B. Scheidegger, Y. Pignolet, E. Ferranti","doi":"10.1109/SmartGridComm.2013.6687984","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687984","url":null,"abstract":"IT infrastructures in commercial and industrial sites are recently undergoing an evolution, which requires them to integrate large numbers of heterogeneous devices, often using multi-protocol networks. One of the driver of this evolution is represented by a recent trend in the energy sector, where local sites are encouraged to build their own microgrids. Furthermore, the lowering costs of sites automation and monitoring systems are making their adoption by industrial and commercial sites much easier to justify.In order to make the most out of these innovations, the communication between all the players of these systems is vital, and a constant monitoring of it essential. However, despite the importance of the data network, there exist currently no vendor-independent analysis and management tools tailored for such networks, usually comprised of various, sometimes very different, network types. Therefore, we present Smart Eagle, a distributed network analysis and monitoring tool capable of dealing with building automation and low-rate wireless personal area networks. We introduce the architecture of Smart Eagle, and report on our experience in taking measurements on an existing site management communication network. In particular, we were able to gather meaningful measurements from both IEEE 802.15.4 and KNX networks, without intervening on existing devices or on the underlying network infrastructure.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130166062","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 : 2013-12-19DOI: 10.1109/SmartGridComm.2013.6687948
Woongsup Lee, Lin Xiang, R. Schober, V. Wong
In this paper, we study the competitive interactions between electric vehicle charging stations (EVCSs) with renewable electricity generation facilities (REGFs). As electric vehicles (EVs) become more popular, there will be a competition between neighboring EVCSs to attract more EVs. Therefore, an EVCS is likely to set its electricity price by taking into account the competition with neighboring EVCSs, such that its revenue is maximized. We model the competitive interactions between EVCSs by using game theory. In this paper, we show that the game played by EVCSs is a supermodular game and there exists a unique pure Nash equilibrium for best response algorithms with arbitrary initial policy. Simulation results confirm the convergence of the game between EVCSs. The results also verify that it is beneficial for both EVs and EVCSs to have REGFs and all EVCSs will have REGFs in the long run.
{"title":"Analysis of the behavior of electric vehicle charging stations with renewable generations","authors":"Woongsup Lee, Lin Xiang, R. Schober, V. Wong","doi":"10.1109/SmartGridComm.2013.6687948","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687948","url":null,"abstract":"In this paper, we study the competitive interactions between electric vehicle charging stations (EVCSs) with renewable electricity generation facilities (REGFs). As electric vehicles (EVs) become more popular, there will be a competition between neighboring EVCSs to attract more EVs. Therefore, an EVCS is likely to set its electricity price by taking into account the competition with neighboring EVCSs, such that its revenue is maximized. We model the competitive interactions between EVCSs by using game theory. In this paper, we show that the game played by EVCSs is a supermodular game and there exists a unique pure Nash equilibrium for best response algorithms with arbitrary initial policy. Simulation results confirm the convergence of the game between EVCSs. The results also verify that it is beneficial for both EVs and EVCSs to have REGFs and all EVCSs will have REGFs in the long run.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131500259","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 : 2013-12-19DOI: 10.1109/SmartGridComm.2013.6688015
Sardar Ali, Kyle Weston, D. Marinakis, Kui Wu
Power quality is a crucial component of power grid reliability. Due to the high cost of measurement devices, the monitoring of power quality is non-trivial. Our objective is to deploy measurement devices on suitable power links to reduce the uncertainty of power quality estimation on non-monitored power links. To realize our objective, we first model the power grid network as a data-driven network. Using entropy-based measurements and Bayesian network models, we propose different algorithms which identify the most suitable power links for power meter placement. Our proposed solution is efficient, and has the potential to significantly reduce the uncertainty of power quality values on non-monitored power links.
{"title":"Intelligent meter placement for power quality estimation in smart grid","authors":"Sardar Ali, Kyle Weston, D. Marinakis, Kui Wu","doi":"10.1109/SmartGridComm.2013.6688015","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6688015","url":null,"abstract":"Power quality is a crucial component of power grid reliability. Due to the high cost of measurement devices, the monitoring of power quality is non-trivial. Our objective is to deploy measurement devices on suitable power links to reduce the uncertainty of power quality estimation on non-monitored power links. To realize our objective, we first model the power grid network as a data-driven network. Using entropy-based measurements and Bayesian network models, we propose different algorithms which identify the most suitable power links for power meter placement. Our proposed solution is efficient, and has the potential to significantly reduce the uncertainty of power quality values on non-monitored power links.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128972715","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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