Pub Date : 2014-11-01DOI: 10.1109/SmartGridComm.2014.7007725
Ke Ma, Le Xie, P. Kumar
We present a layered decomposition approach that permits a holistic solution to the storage, scheduling and pricing problems of Electric Vehicle (EV) Charging Stations. By exploiting time scales, these problems can be decomposed and solved layer by layer. In the top layer, at a long time scale, with grid power price and renewable energy represented by their long-term averages, and total demand following the price-demand curve, the optimal pricing scheme is obtained. The real-time charging and discharging operation of the battery, is considered in the middle layer. With average number of customers arriving determined by the price set at the top layer, the middle layer determines the optimal amounts of energy to buy from the grid and to use for charging. At the bottom layer, the scheduling policy of EV charging is determined while satisfying the total battery consumption obtained at the middle layer. We illustrate the algorithms with a simple example using ERCOT data, demonstrating the implementability of the architectural solution in real-time market operation of an EV charging station. Simulations show that the architectural decomposition does not incur any significant cost penalty.
{"title":"A layered architecture for EV charging stations based on time scale decomposition","authors":"Ke Ma, Le Xie, P. Kumar","doi":"10.1109/SmartGridComm.2014.7007725","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2014.7007725","url":null,"abstract":"We present a layered decomposition approach that permits a holistic solution to the storage, scheduling and pricing problems of Electric Vehicle (EV) Charging Stations. By exploiting time scales, these problems can be decomposed and solved layer by layer. In the top layer, at a long time scale, with grid power price and renewable energy represented by their long-term averages, and total demand following the price-demand curve, the optimal pricing scheme is obtained. The real-time charging and discharging operation of the battery, is considered in the middle layer. With average number of customers arriving determined by the price set at the top layer, the middle layer determines the optimal amounts of energy to buy from the grid and to use for charging. At the bottom layer, the scheduling policy of EV charging is determined while satisfying the total battery consumption obtained at the middle layer. We illustrate the algorithms with a simple example using ERCOT data, demonstrating the implementability of the architectural solution in real-time market operation of an EV charging station. Simulations show that the architectural decomposition does not incur any significant cost penalty.","PeriodicalId":6499,"journal":{"name":"2014 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"6 1","pages":"674-679"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80669327","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 : 2014-11-01DOI: 10.1109/SmartGridComm.2014.7007625
S. Riverso, Fabio Sarzo, G. Ferrari-Trecate
In this paper we propose a new decentralized control scheme for Islanded microGrids (ImGs) composed by the interconnection of Distributed Generation Units (DGUs). Local controllers regulate voltage and frequency at the Point of Common Coupling (PCC) of each DGU and they are able to guarantee stability of the overall ImG. The control design procedure is decentralized, since, besides two global scalar quantities, the synthesis of a local controller uses only information on the corresponding DGU and lines connected to it. Most important, our design procedure enables Plug-and-Play (PnP) operations: when a DGU is plugged in or out, only DGUs physically connected to it have to retune their local controllers. We study the performance of the proposed controllers simulating different scenarios in MatLab/Simulink and using indexes proposed in IEEE standards.
{"title":"Voltage and frequency control of islanded microgrids: A plug-and-play approach","authors":"S. Riverso, Fabio Sarzo, G. Ferrari-Trecate","doi":"10.1109/SmartGridComm.2014.7007625","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2014.7007625","url":null,"abstract":"In this paper we propose a new decentralized control scheme for Islanded microGrids (ImGs) composed by the interconnection of Distributed Generation Units (DGUs). Local controllers regulate voltage and frequency at the Point of Common Coupling (PCC) of each DGU and they are able to guarantee stability of the overall ImG. The control design procedure is decentralized, since, besides two global scalar quantities, the synthesis of a local controller uses only information on the corresponding DGU and lines connected to it. Most important, our design procedure enables Plug-and-Play (PnP) operations: when a DGU is plugged in or out, only DGUs physically connected to it have to retune their local controllers. We study the performance of the proposed controllers simulating different scenarios in MatLab/Simulink and using indexes proposed in IEEE standards.","PeriodicalId":6499,"journal":{"name":"2014 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"25 1","pages":"73-78"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80717722","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 : 2014-11-01DOI: 10.1109/SmartGridComm.2014.7007637
Wenyuan Tang, R. Jain
We consider an auction design problem, where an aggregator procures wind power from multiple wind farms. While the realized generation of each wind farm is random, the probability distribution can be learned beforehand as its private information. Since the wind farms are geographically close, the distributions are possibly correlated. We formulate a unified optimization problem to study both the welfare-maximizing and the revenue-maximizing objectives. We show that the aggregator may extract the full surplus by exploiting the correlation among the distributions. We also illustrate, through a numerical example, the case where full surplus extraction is not achievable.
{"title":"Buying random yet correlated wind power","authors":"Wenyuan Tang, R. Jain","doi":"10.1109/SmartGridComm.2014.7007637","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2014.7007637","url":null,"abstract":"We consider an auction design problem, where an aggregator procures wind power from multiple wind farms. While the realized generation of each wind farm is random, the probability distribution can be learned beforehand as its private information. Since the wind farms are geographically close, the distributions are possibly correlated. We formulate a unified optimization problem to study both the welfare-maximizing and the revenue-maximizing objectives. We show that the aggregator may extract the full surplus by exploiting the correlation among the distributions. We also illustrate, through a numerical example, the case where full surplus extraction is not achievable.","PeriodicalId":6499,"journal":{"name":"2014 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"8 1","pages":"145-150"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90846822","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 : 2014-11-01DOI: 10.1109/SmartGridComm.2014.7007634
B. O. Akyurek, A. S. Akyurek, J. Kleissl, T. Simunic
With the increasing penetration of renewable energy resources within the Smart Grid, solar forecasting has become an important problem for hour-ahead and day-ahead planning. Within this work, we analyze the Analog Forecast method family, which uses past observations to improve the forecast product. We first show that the frequently used euclidean distance metric has drawbacks and leads to poor performance relatively. In this paper, we introduce a new method, TESLA forecasting, which is very fast and light, and we show through case studies that we can beat the persistence method, a state of the art comparison method, by up-to 50% in terms of root mean square error to give an accurate forecasting result. An extension is also provided to improve the forecast accuracy by decreasing the forecast horizon.
{"title":"TESLA: Taylor expanded solar analog forecasting","authors":"B. O. Akyurek, A. S. Akyurek, J. Kleissl, T. Simunic","doi":"10.1109/SmartGridComm.2014.7007634","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2014.7007634","url":null,"abstract":"With the increasing penetration of renewable energy resources within the Smart Grid, solar forecasting has become an important problem for hour-ahead and day-ahead planning. Within this work, we analyze the Analog Forecast method family, which uses past observations to improve the forecast product. We first show that the frequently used euclidean distance metric has drawbacks and leads to poor performance relatively. In this paper, we introduce a new method, TESLA forecasting, which is very fast and light, and we show through case studies that we can beat the persistence method, a state of the art comparison method, by up-to 50% in terms of root mean square error to give an accurate forecasting result. An extension is also provided to improve the forecast accuracy by decreasing the forecast horizon.","PeriodicalId":6499,"journal":{"name":"2014 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"40 1","pages":"127-132"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79964916","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 : 2014-11-01DOI: 10.1109/SmartGridComm.2014.7007777
T. Shawly, Jun Liu, N. Burow, S. Bagchi, R. Berthier, R. Bobba
The growing reliance on Cyber technology for Smart Grid and other Cyber-Physical Systems (CPS) applications increases high assurance challenges. Advanced Metering Infrastructure (AMI) is a critical part of smart grid and failure to address security risks in it might disrupt utilities in their mission to deliver power reliably. The objective of this paper is to find mitigation actions for attacks that might be launched against AMI. The paper introduces a tool called SecAMI that calculates the relationship between the speed at which an attack spreads, the speed at which it can be detected, and the consequences on the availability of the AMI. The results from SecAMI can be used as a performance metric to significantly improve the development and the deployment of Intrusion Detection Systems (IDSs) in an AMI environment. Experimental results with an IDS called Amilyzer show that centralized IDS might not work efficiently in scalable systems comparing with distributed IDS in term of detection time, especially with a Distributed Denial of Service (DDoS) attack or remote disconnects on the AMI.
{"title":"A risk assessment tool for advanced metering infrastructures","authors":"T. Shawly, Jun Liu, N. Burow, S. Bagchi, R. Berthier, R. Bobba","doi":"10.1109/SmartGridComm.2014.7007777","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2014.7007777","url":null,"abstract":"The growing reliance on Cyber technology for Smart Grid and other Cyber-Physical Systems (CPS) applications increases high assurance challenges. Advanced Metering Infrastructure (AMI) is a critical part of smart grid and failure to address security risks in it might disrupt utilities in their mission to deliver power reliably. The objective of this paper is to find mitigation actions for attacks that might be launched against AMI. The paper introduces a tool called SecAMI that calculates the relationship between the speed at which an attack spreads, the speed at which it can be detected, and the consequences on the availability of the AMI. The results from SecAMI can be used as a performance metric to significantly improve the development and the deployment of Intrusion Detection Systems (IDSs) in an AMI environment. Experimental results with an IDS called Amilyzer show that centralized IDS might not work efficiently in scalable systems comparing with distributed IDS in term of detection time, especially with a Distributed Denial of Service (DDoS) attack or remote disconnects on the AMI.","PeriodicalId":6499,"journal":{"name":"2014 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"38 1","pages":"989-994"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88499971","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 : 2014-11-01DOI: 10.1109/SmartGridComm.2014.7007659
J. Monteiro, J. Eduardo, P. Cardoso, J. Semião
Several protocols have recently been defined for smart grids that enable the communication between electric devices and energy management systems. While these protocols and architectures can already be applied in different fields of micro grids, it is still not clear how the distributed resources and constraints of such electrical grids can be managed in an optimum way. In order to achieve a reduction in electricity costs and maximizing investments made in renewable sources, an optimization mechanism should be used to perform load scheduling, considering different variables such as forecasted power generation curve from renewable sources, different tariffs' rates, electric circuit constraints, user restrictions and correspondent comfort levels. Given these considerations, this work defines and evaluates a distributed micro grid resource management architecture and protocol which is able to optimize load scheduling while considering all the mentioned restrictions and parameters. The proposed architecture was implemented on a multi-agent simulator and the performed tests show that significant reductions in electricity cost can be achieved using this methodology.
{"title":"A distributed load scheduling mechanism for micro grids","authors":"J. Monteiro, J. Eduardo, P. Cardoso, J. Semião","doi":"10.1109/SmartGridComm.2014.7007659","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2014.7007659","url":null,"abstract":"Several protocols have recently been defined for smart grids that enable the communication between electric devices and energy management systems. While these protocols and architectures can already be applied in different fields of micro grids, it is still not clear how the distributed resources and constraints of such electrical grids can be managed in an optimum way. In order to achieve a reduction in electricity costs and maximizing investments made in renewable sources, an optimization mechanism should be used to perform load scheduling, considering different variables such as forecasted power generation curve from renewable sources, different tariffs' rates, electric circuit constraints, user restrictions and correspondent comfort levels. Given these considerations, this work defines and evaluates a distributed micro grid resource management architecture and protocol which is able to optimize load scheduling while considering all the mentioned restrictions and parameters. The proposed architecture was implemented on a multi-agent simulator and the performed tests show that significant reductions in electricity cost can be achieved using this methodology.","PeriodicalId":6499,"journal":{"name":"2014 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"11 1","pages":"278-283"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87222049","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 : 2014-11-01DOI: 10.1109/SmartGridComm.2014.7007678
K. Katsaros, Binxu Yang, W. Chai, G. Pavlou
With the introduction of new power sources, such as distributed renewable energy resources, and loads, such as electric vehicles, electrical distribution networks must accommodate new energy flow patterns in a considerably dynamic environment. This leads to the need for increasing the observability of the grid to enable a series of mission-critical applications such as voltage/congestion control and fault detection/location. The deployment of Phasor Measurement Units appears to be a promising approach, offering high precision grid monitoring. However, while the low delay requirements of such applications raise a significant challenge to the communication infrastructure, there is currently no clear vision on the exact communication technologies and network topologies that could support these requirements. In this paper, we address this challenge by taking a systematic approach on the design of low latency communication infrastructures. Based on a large set of real medium voltage grid topologies from a European distribution network, we first perform a detailed analysis of the communication requirements. Guided by this analysis, we then propose two algorithms, PLeC and BW-PLeC algorithms, for the design of low latency communication infrastructures that enhance the currently available power-line communication technology with newer high-speed communication links at strategic points in the grid to satisfy the delay requirements while reducing deployment costs.
{"title":"Low latency communication infrastructure for synchrophasor applications in distribution networks","authors":"K. Katsaros, Binxu Yang, W. Chai, G. Pavlou","doi":"10.1109/SmartGridComm.2014.7007678","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2014.7007678","url":null,"abstract":"With the introduction of new power sources, such as distributed renewable energy resources, and loads, such as electric vehicles, electrical distribution networks must accommodate new energy flow patterns in a considerably dynamic environment. This leads to the need for increasing the observability of the grid to enable a series of mission-critical applications such as voltage/congestion control and fault detection/location. The deployment of Phasor Measurement Units appears to be a promising approach, offering high precision grid monitoring. However, while the low delay requirements of such applications raise a significant challenge to the communication infrastructure, there is currently no clear vision on the exact communication technologies and network topologies that could support these requirements. In this paper, we address this challenge by taking a systematic approach on the design of low latency communication infrastructures. Based on a large set of real medium voltage grid topologies from a European distribution network, we first perform a detailed analysis of the communication requirements. Guided by this analysis, we then propose two algorithms, PLeC and BW-PLeC algorithms, for the design of low latency communication infrastructures that enhance the currently available power-line communication technology with newer high-speed communication links at strategic points in the grid to satisfy the delay requirements while reducing deployment costs.","PeriodicalId":6499,"journal":{"name":"2014 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"184 1","pages":"392-397"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85672366","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 : 2014-11-01DOI: 10.1109/SmartGridComm.2014.7007631
Sun Sun, Min Dong, B. Liang
The problem of real-time power balancing in a grid-connected microgrid is studied. We consider a microgrid powered by a conventional generator (CG) and multiple renewable generators (RGs) each co-located with one distributed storage (DS) unit. An aggregator operates the microgrid and aims to minimize the long-term system cost, including all RGs' cost, the CG's cost, and the cost for exploiting external energy markets. We jointly manage the supply side, demand side, and DS units, taking into account the randomness of the system, and incorporating the ramping constraint of the CG. A real-time algorithm is proposed, which does not require any statistics of the system. We analytically characterize the gap between the system cost under our algorithm and the minimum cost, demonstrating that our algorithm is asymptotically optimal as the DS energy capacity increases and the CG ramping constraint loosens. In simulation, we compare the proposed algorithm with a greedy algorithm as well as a lower bound on the optimum. Simulation shows that our algorithm outperforms the greedy one and its performance can be close to the optimum even with small DS units.
{"title":"Joint supply, demand, and energy storage management towards microgrid cost minimization","authors":"Sun Sun, Min Dong, B. Liang","doi":"10.1109/SmartGridComm.2014.7007631","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2014.7007631","url":null,"abstract":"The problem of real-time power balancing in a grid-connected microgrid is studied. We consider a microgrid powered by a conventional generator (CG) and multiple renewable generators (RGs) each co-located with one distributed storage (DS) unit. An aggregator operates the microgrid and aims to minimize the long-term system cost, including all RGs' cost, the CG's cost, and the cost for exploiting external energy markets. We jointly manage the supply side, demand side, and DS units, taking into account the randomness of the system, and incorporating the ramping constraint of the CG. A real-time algorithm is proposed, which does not require any statistics of the system. We analytically characterize the gap between the system cost under our algorithm and the minimum cost, demonstrating that our algorithm is asymptotically optimal as the DS energy capacity increases and the CG ramping constraint loosens. In simulation, we compare the proposed algorithm with a greedy algorithm as well as a lower bound on the optimum. Simulation shows that our algorithm outperforms the greedy one and its performance can be close to the optimum even with small DS units.","PeriodicalId":6499,"journal":{"name":"2014 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"118 1","pages":"109-114"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73295498","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 : 2014-11-01DOI: 10.1109/SmartGridComm.2014.7007646
Wenbo Shi, Xiaorong Xie, C. Chu, R. Gadh
Energy management in microgrids is typically formulated as a non-linear optimization problem. Solving it in a centralized manner not only requires high computational capabilities at the microgrid central controller (MGCC) but may also infringe customer privacy. Existing distributed approaches, on the other hand, assume that all the generations and loads are connected to one bus and ignore the underlying power distribution network and the associated power flows and system operational constraints. Consequently, the schedules produced by those algorithms may violate those constraints and thus are not feasible in practice. Therefore, the focus of this paper is on the design of a distributed energy management strategy (EMS) for the optimal operation of microgrids with consideration of the distribution network and the associated constraints. Specifically, we formulate microgrid energy management as an optimal power flow problem and propose a distributed EMS where the MGCC and the local controllers jointly compute an optimal schedule. As one demonstration, we apply the proposed distributed EMS to a real microgrid in Guangdong Province, China consisting of photovoltaics, wind turbines, diesel generators, and a battery energy storage system. The simulation results demonstrate that the proposed distributed EMS is effective in both islanded and grid-connected mode. It is also shown that the proposed algorithm converges fast.
{"title":"A distributed optimal energy management strategy for microgrids","authors":"Wenbo Shi, Xiaorong Xie, C. Chu, R. Gadh","doi":"10.1109/SmartGridComm.2014.7007646","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2014.7007646","url":null,"abstract":"Energy management in microgrids is typically formulated as a non-linear optimization problem. Solving it in a centralized manner not only requires high computational capabilities at the microgrid central controller (MGCC) but may also infringe customer privacy. Existing distributed approaches, on the other hand, assume that all the generations and loads are connected to one bus and ignore the underlying power distribution network and the associated power flows and system operational constraints. Consequently, the schedules produced by those algorithms may violate those constraints and thus are not feasible in practice. Therefore, the focus of this paper is on the design of a distributed energy management strategy (EMS) for the optimal operation of microgrids with consideration of the distribution network and the associated constraints. Specifically, we formulate microgrid energy management as an optimal power flow problem and propose a distributed EMS where the MGCC and the local controllers jointly compute an optimal schedule. As one demonstration, we apply the proposed distributed EMS to a real microgrid in Guangdong Province, China consisting of photovoltaics, wind turbines, diesel generators, and a battery energy storage system. The simulation results demonstrate that the proposed distributed EMS is effective in both islanded and grid-connected mode. It is also shown that the proposed algorithm converges fast.","PeriodicalId":6499,"journal":{"name":"2014 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"287 1","pages":"200-205"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74768257","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 : 2014-11-01DOI: 10.1109/SmartGridComm.2014.7007655
Daniel Gyllstrom, N. Braga, J. Kurose
In this paper, we design and evaluate algorithms for fast recovery from link failures in a smart grid communication network, addressing all three aspects of link failure recovery: (a) link failure detection, (b) algorithms for computing backup multicast trees, and (c) fast backup tree installation. To address (a), we design link-failure detection and reporting mechanisms that use OpenFlow to detect link failures when and where they occur inside the network. OpenFlow is an open source framework that cleanly separates the control and data planes for use in network management and control. For part (b), we formulate a new problem, Multicast Recycling, that computes backup multicast trees that aim to minimize control plane signaling overhead. We prove Multicast Recycling is at least NP-hard and present a corresponding approximation algorithm. Lastly, two control plane algorithms are proposed that signal data plane switches to install pre-computed backup trees. An optimized version of each installation algorithm is designed that finds a near minimum set of forwarding rules by sharing rules across multicast groups, thereby reducing backup tree install time and associated control state. We implement these algorithms in the POX OpenFlow controller and evaluate them using the Mininet emulator, quantifying control plane signaling and installation time.
{"title":"Recovery from link failures in a Smart Grid communication network using OpenFlow","authors":"Daniel Gyllstrom, N. Braga, J. Kurose","doi":"10.1109/SmartGridComm.2014.7007655","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2014.7007655","url":null,"abstract":"In this paper, we design and evaluate algorithms for fast recovery from link failures in a smart grid communication network, addressing all three aspects of link failure recovery: (a) link failure detection, (b) algorithms for computing backup multicast trees, and (c) fast backup tree installation. To address (a), we design link-failure detection and reporting mechanisms that use OpenFlow to detect link failures when and where they occur inside the network. OpenFlow is an open source framework that cleanly separates the control and data planes for use in network management and control. For part (b), we formulate a new problem, Multicast Recycling, that computes backup multicast trees that aim to minimize control plane signaling overhead. We prove Multicast Recycling is at least NP-hard and present a corresponding approximation algorithm. Lastly, two control plane algorithms are proposed that signal data plane switches to install pre-computed backup trees. An optimized version of each installation algorithm is designed that finds a near minimum set of forwarding rules by sharing rules across multicast groups, thereby reducing backup tree install time and associated control state. We implement these algorithms in the POX OpenFlow controller and evaluate them using the Mininet emulator, quantifying control plane signaling and installation time.","PeriodicalId":6499,"journal":{"name":"2014 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"119 1","pages":"254-259"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74443031","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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