Pub Date : 2013-12-19DOI: 10.1109/SmartGridComm.2013.6687950
Baris Aksanli, T. Simunic
Residential energy consumption shows significant diurnal patterns that can be leveraged by energy storage devices. Batteries can store energy from either local renewable sources or from the grid when the electricity is cheaper, and provide it when the prices are higher. However, batteries are chemical devices and their efficiency and lifetime highly depends on the usage patterns. In this paper, we develop a framework that considers the physical properties of batteries, tests the feasibility of a battery deployment and finds the best battery types and configurations for a particular residential configuration. We validate the outcomes our framework through simulations that are informed by measurements. Our framework shows that up to 43% savings can be obtained with batteries, which may be lower or completely eliminated if the batteries are not used in specific configurations.
{"title":"Optimal battery configuration in a residential home with time-of-use pricing","authors":"Baris Aksanli, T. Simunic","doi":"10.1109/SmartGridComm.2013.6687950","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687950","url":null,"abstract":"Residential energy consumption shows significant diurnal patterns that can be leveraged by energy storage devices. Batteries can store energy from either local renewable sources or from the grid when the electricity is cheaper, and provide it when the prices are higher. However, batteries are chemical devices and their efficiency and lifetime highly depends on the usage patterns. In this paper, we develop a framework that considers the physical properties of batteries, tests the feasibility of a battery deployment and finds the best battery types and configurations for a particular residential configuration. We validate the outcomes our framework through simulations that are informed by measurements. Our framework shows that up to 43% savings can be obtained with batteries, which may be lower or completely eliminated if the batteries are not used in specific configurations.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121424397","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.2013.6687929
Ramzi Charni, M. Maier
The majority of previous studies give good insight in the overall costs of various communications network architectures but most consider only the vertical integration model. However, it is necessary to take a closer look at the possibilities and gains through collaboration. In this work, we develop a flexible, generic yet comprehensive total cost of ownership (TCO) framework, which calculates the overall costs related to the rollout of smart grid communications networks for different scenarios. Further, we present our novel collaborative implementation model for a shared infrastructure for both broadband access and smart grid communications. In addition, buildings currently shift from a product to a service (i.e., renewable power supply). Thus, our idea is that housing companies will collaborate by offering the positive renewable energy to communications network providers. We study the impact of this model on TCO and compare it with tradionnal vertical integration model. The sensitivity analysis for the key cost parameters is conducted. We also analyze the risk related to renewable energy intermittency.
{"title":"Impact study of collaborative implementation models on total cost of ownership of integrated fiber-wireless smart grid communications infrastructures","authors":"Ramzi Charni, M. Maier","doi":"10.1109/SmartGridComm.2013.6687929","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687929","url":null,"abstract":"The majority of previous studies give good insight in the overall costs of various communications network architectures but most consider only the vertical integration model. However, it is necessary to take a closer look at the possibilities and gains through collaboration. In this work, we develop a flexible, generic yet comprehensive total cost of ownership (TCO) framework, which calculates the overall costs related to the rollout of smart grid communications networks for different scenarios. Further, we present our novel collaborative implementation model for a shared infrastructure for both broadband access and smart grid communications. In addition, buildings currently shift from a product to a service (i.e., renewable power supply). Thus, our idea is that housing companies will collaborate by offering the positive renewable energy to communications network providers. We study the impact of this model on TCO and compare it with tradionnal vertical integration model. The sensitivity analysis for the key cost parameters is conducted. We also analyze the risk related to renewable energy intermittency.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126367768","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.2013.6687977
B. Karimi, V. Namboodiri, Murtuza Jadliwala
Advanced Metering Infrastructure (AMI) initiatives are a popular tool to incorporate changes for modernizing the electricity grid, reduce peak loads, and meet energy-efficiency targets. There is the looming issue of how to communicate and handle consumer data collected by electric utilities and manage limited communication network resources. Several data relay points are required to collect data distributedly and send them through a communication backhaul. This work studies the smart meter message concatenation (SMMC) problem of how to concatenate multiple small smart metering messages arriving at data concentrator units (DCUs) in order to reduce protocol overhead and thus network utilization. This problem needs to deal with the added constraint that each originating message from its source may have its own stated deadline that must be taken into account during the concatenation process. Six heuristic algorithms are proposed and evaluated to gain a better understanding of the best data volume reduction policies that can be applied at data concentrators of smart grids.
{"title":"On the scalable collection of metering data in smart grids through message concatenation","authors":"B. Karimi, V. Namboodiri, Murtuza Jadliwala","doi":"10.1109/SmartGridComm.2013.6687977","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687977","url":null,"abstract":"Advanced Metering Infrastructure (AMI) initiatives are a popular tool to incorporate changes for modernizing the electricity grid, reduce peak loads, and meet energy-efficiency targets. There is the looming issue of how to communicate and handle consumer data collected by electric utilities and manage limited communication network resources. Several data relay points are required to collect data distributedly and send them through a communication backhaul. This work studies the smart meter message concatenation (SMMC) problem of how to concatenate multiple small smart metering messages arriving at data concentrator units (DCUs) in order to reduce protocol overhead and thus network utilization. This problem needs to deal with the added constraint that each originating message from its source may have its own stated deadline that must be taken into account during the concatenation process. Six heuristic algorithms are proposed and evaluated to gain a better understanding of the best data volume reduction policies that can be applied at data concentrators of smart grids.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128233447","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.2013.6687972
Cesar Carrizo, Kentaro Kobayashi, Hiraku Okada, M. Katayama
This paper presents a simple scheme to improve the performance of a system involving a power line to transfer signals to control the motion of a single machine. The feedback loop consists of a power line with its characteristic cyclostationary noise which allows for predictable and virtually error free transmission instants as well as predictable instants of high probability of error. We evaluate the effectiveness of a predictive control scheme adapted to the cyclostationary noise in the power line environment. In other words, we explore the cooperation between the system's physical and application layers to achieve an overall optimization. To rate the performance of our system we evaluate and compare the stability and accuracy of the control in the systems with and without the scheme. As a result, it is confirmed that with the predictive control scheme added to the channel prediction scheme, the periodic instants of low noise can be successfully exploited to send additional data to be used when there is high noise, and therefore optimize the system's performance.
{"title":"Feedback control scheme with prediction for power line communication channels","authors":"Cesar Carrizo, Kentaro Kobayashi, Hiraku Okada, M. Katayama","doi":"10.1109/SmartGridComm.2013.6687972","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687972","url":null,"abstract":"This paper presents a simple scheme to improve the performance of a system involving a power line to transfer signals to control the motion of a single machine. The feedback loop consists of a power line with its characteristic cyclostationary noise which allows for predictable and virtually error free transmission instants as well as predictable instants of high probability of error. We evaluate the effectiveness of a predictive control scheme adapted to the cyclostationary noise in the power line environment. In other words, we explore the cooperation between the system's physical and application layers to achieve an overall optimization. To rate the performance of our system we evaluate and compare the stability and accuracy of the control in the systems with and without the scheme. As a result, it is confirmed that with the predictive control scheme added to the channel prediction scheme, the periodic instants of low noise can be successfully exploited to send additional data to be used when there is high noise, and therefore optimize the system's performance.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134368642","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.2013.6687954
Chen Wang, M. Groot
Demand Response(DR) is a method for stimulating end-users to adjust consumption to support the change in the electricity market. DR can be used to improve the stability of power supply including the power generation, transmission and distribution. It can also be used to improve electricity market operation. Furthermore, significant cost savings can be made on the consumer side via the financial incentives in a range of DR programs. As the cloud computing paradigm gains popularity, there is an associated rapid growth of public and private data centers. Data center energy consumption increases significantly. Putting data center energy consumption in the context of power grid becomes important. In this paper, we propose an architecture to integrate data centre computer clusters with a DR service. The resource manager of a cluster can therefore take DR events into account when allocating resources. We particularly focus on resource provisioning for parallel workloads in such a cluster, and propose a DR strategy that is capable of balancing energy savings and user satisfaction.
{"title":"Enabling Demand Response in a computer cluster","authors":"Chen Wang, M. Groot","doi":"10.1109/SmartGridComm.2013.6687954","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687954","url":null,"abstract":"Demand Response(DR) is a method for stimulating end-users to adjust consumption to support the change in the electricity market. DR can be used to improve the stability of power supply including the power generation, transmission and distribution. It can also be used to improve electricity market operation. Furthermore, significant cost savings can be made on the consumer side via the financial incentives in a range of DR programs. As the cloud computing paradigm gains popularity, there is an associated rapid growth of public and private data centers. Data center energy consumption increases significantly. Putting data center energy consumption in the context of power grid becomes important. In this paper, we propose an architecture to integrate data centre computer clusters with a DR service. The resource manager of a cluster can therefore take DR events into account when allocating resources. We particularly focus on resource provisioning for parallel workloads in such a cluster, and propose a DR strategy that is capable of balancing energy savings and user satisfaction.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134298112","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.2013.6687962
H. Ziekow, C. Goebel, Jens Strüker, H. Jacobsen
The aim of this paper is to quantify the impact of disaggregated electric power measurements on the accuracy of household demand forecasts. Demand forecasting on the household level is regarded as an essential mechanism for matching distributed power generation and demand in smart power grids. We use state-of-the-art forecasting tools, in particular support vector machines and neural networks, to evaluate the use of disaggregated smart home sensor data for household-level demand forecasting. Our investigation leverages high resolution data from 3 private households collected over 30 days. Our key results are as follows: First, by comparing the accuracy of the machine learning based forecasts with a persistence forecast we show that advanced forecasting methods already yield better forecasts, even when carried out on aggregated household consumption data that could be obtained from smart meters (1-7%). Second, our comparison of forecasts based on disaggregated data from smart home sensors with the persistence and smart meter benchmarks reveals further forecast improvements (4-33%). Third, our sensitivity analysis with respect to the time resolution of data shows that more data only improves forecasting accuracy up to a certain point. Thus, having more sensors appears to be more valuable than increasing the time resolution of measurements.
{"title":"The potential of smart home sensors in forecasting household electricity demand","authors":"H. Ziekow, C. Goebel, Jens Strüker, H. Jacobsen","doi":"10.1109/SmartGridComm.2013.6687962","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687962","url":null,"abstract":"The aim of this paper is to quantify the impact of disaggregated electric power measurements on the accuracy of household demand forecasts. Demand forecasting on the household level is regarded as an essential mechanism for matching distributed power generation and demand in smart power grids. We use state-of-the-art forecasting tools, in particular support vector machines and neural networks, to evaluate the use of disaggregated smart home sensor data for household-level demand forecasting. Our investigation leverages high resolution data from 3 private households collected over 30 days. Our key results are as follows: First, by comparing the accuracy of the machine learning based forecasts with a persistence forecast we show that advanced forecasting methods already yield better forecasts, even when carried out on aggregated household consumption data that could be obtained from smart meters (1-7%). Second, our comparison of forecasts based on disaggregated data from smart home sensors with the persistence and smart meter benchmarks reveals further forecast improvements (4-33%). Third, our sensitivity analysis with respect to the time resolution of data shows that more data only improves forecasting accuracy up to a certain point. Thus, having more sensors appears to be more valuable than increasing the time resolution of measurements.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"186 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116328642","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.2013.6687993
M. Rahman, E. Al-Shaer, Md. Ashfaqur Rahman
The power system state estimation is very important for maintaining the power system securely, reliably, and efficiently. An attacker can compromise meters or communication systems and introduce false measurements, which can evade existing bad data detection algorithms and lead to incorrect state estimation. This kind of stealthy attack is well-known as Undetected False Data Injection (UFDI) attack. However, attackers usually have different constraints with respect to knowledge, capabilities, resources, and attack targets. These attack attributes are important to consider in order to know the potential attack vectors. In this paper, we propose a formal model for UFDI attack verification in order to provide security analytics for power grid state estimation. Our model formalizes the grid information and different constraints, particularly with respect to attackers' point of view. The solution to the model provides an attack vector, when it exists, by satisfying the given constraints. We demonstrate our UFDI attack verification model with the help of an example. We evaluated our proposed model by running experiments on different IEEE test systems and we found that our model is very efficient in solving problems with hundreds of buses.
{"title":"A formal model for verifying stealthy attacks on state estimation in power grids","authors":"M. Rahman, E. Al-Shaer, Md. Ashfaqur Rahman","doi":"10.1109/SmartGridComm.2013.6687993","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687993","url":null,"abstract":"The power system state estimation is very important for maintaining the power system securely, reliably, and efficiently. An attacker can compromise meters or communication systems and introduce false measurements, which can evade existing bad data detection algorithms and lead to incorrect state estimation. This kind of stealthy attack is well-known as Undetected False Data Injection (UFDI) attack. However, attackers usually have different constraints with respect to knowledge, capabilities, resources, and attack targets. These attack attributes are important to consider in order to know the potential attack vectors. In this paper, we propose a formal model for UFDI attack verification in order to provide security analytics for power grid state estimation. Our model formalizes the grid information and different constraints, particularly with respect to attackers' point of view. The solution to the model provides an attack vector, when it exists, by satisfying the given constraints. We demonstrate our UFDI attack verification model with the help of an example. We evaluated our proposed model by running experiments on different IEEE test systems and we found that our model is very efficient in solving problems with hundreds of buses.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123454434","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.2013.6688025
C. Kikkert
The development of an On-line PLC frequency impedance analyzer is presented. This analyzer will allow the impedances of power lines, transformers and other loads to be determined at PLC frequencies while they are powered up. This then allows efficient PLC couplers to be designed and PLC communication networks to be analyzed, to ensure that no parts of the network cause data communication failure by presenting short circuits at PLC frequencies to the rest of the network.
{"title":"An On-line PLC frequency impedance analyzer","authors":"C. Kikkert","doi":"10.1109/SmartGridComm.2013.6688025","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6688025","url":null,"abstract":"The development of an On-line PLC frequency impedance analyzer is presented. This analyzer will allow the impedances of power lines, transformers and other loads to be determined at PLC frequencies while they are powered up. This then allows efficient PLC couplers to be designed and PLC communication networks to be analyzed, to ensure that no parts of the network cause data communication failure by presenting short circuits at PLC frequencies to the rest of the network.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123783156","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.2013.6687964
Yuemin Ding, S. Hong
Demand response energy management improves the reliability of electrical grids and reduces electricity cost of consumers by shifting part of the demand from peak to off-peak demand periods. On the demand side, industrial facilities consume huge amounts of electricity, highlighting the urgent need to implement demand response energy management. In this study, we propose a general model of demand response energy management systems for industrial facilities. The model consists of model elements, model architecture, and approaches to industrial demand response. The proposed model provides a straightforward means of designing and analyzing demand response systems in industrial facilities and assists in developing standards for such systems. We also present an example of this model applied to a steel manufacturing facility.
{"title":"A model of demand response energy management system in industrial facilities","authors":"Yuemin Ding, S. Hong","doi":"10.1109/SmartGridComm.2013.6687964","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6687964","url":null,"abstract":"Demand response energy management improves the reliability of electrical grids and reduces electricity cost of consumers by shifting part of the demand from peak to off-peak demand periods. On the demand side, industrial facilities consume huge amounts of electricity, highlighting the urgent need to implement demand response energy management. In this study, we propose a general model of demand response energy management systems for industrial facilities. The model consists of model elements, model architecture, and approaches to industrial demand response. The proposed model provides a straightforward means of designing and analyzing demand response systems in industrial facilities and assists in developing standards for such systems. We also present an example of this model applied to a steel manufacturing facility.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"95 Suppl 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127534266","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.2013.6688022
Yong Ding, M. A. Neumann, M. Budde, M. Beigl, P. Silva, Lin Zhang
We are facing a restructuring of the power industry towards a smart grid. The vision of the smart grid represents not only the creation of intelligent power supply networks to allow efficient and reliable use of energy resources, but also the redesign of the market structure coupled with it. In order to develop a smart grid-ready power market, the integration of the physical reality of the power grid into the economic market model has been set as the first requirement. To address this problem, we present a feedback control model to interconnect the physical grid and the economic market in a decoupled control loop. Our proposed control loop consists of two subsystems, namely an Optimal Power Flow (OPF)-based physical system and a Continuous Double Auction (CDA)-based economic system. A dynamic coefficient matrix generated by the Locational Marginal Pricing (LMP) algorithm is adopted for the market clearing mechanism to account for the real-time power flow and transmission constraints. Finally, we demonstrate some initial experiments for a feasibility test of the interaction between the proposed physical power system and economic power market.
{"title":"A control loop approach for integrating the future decentralized power markets and grids","authors":"Yong Ding, M. A. Neumann, M. Budde, M. Beigl, P. Silva, Lin Zhang","doi":"10.1109/SmartGridComm.2013.6688022","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2013.6688022","url":null,"abstract":"We are facing a restructuring of the power industry towards a smart grid. The vision of the smart grid represents not only the creation of intelligent power supply networks to allow efficient and reliable use of energy resources, but also the redesign of the market structure coupled with it. In order to develop a smart grid-ready power market, the integration of the physical reality of the power grid into the economic market model has been set as the first requirement. To address this problem, we present a feedback control model to interconnect the physical grid and the economic market in a decoupled control loop. Our proposed control loop consists of two subsystems, namely an Optimal Power Flow (OPF)-based physical system and a Continuous Double Auction (CDA)-based economic system. A dynamic coefficient matrix generated by the Locational Marginal Pricing (LMP) algorithm is adopted for the market clearing mechanism to account for the real-time power flow and transmission constraints. Finally, we demonstrate some initial experiments for a feasibility test of the interaction between the proposed physical power system and economic power market.","PeriodicalId":136434,"journal":{"name":"2013 IEEE International Conference on Smart Grid Communications (SmartGridComm)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126357847","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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