Pub Date : 2018-10-01DOI: 10.1109/SmartGridComm.2018.8587444
J. Petersen, J. Bendtsen, Pierre J. C. Vogler-Finck, J. Stoustrup
In this paper we propose a scheme for managing energy flexibility in buildings with significant thermal masses and centralized climate control, such as commercial buildings, which can be used to provide ancillary services to the local electrical system (demand response). The scheme relies on being able to manipulate the forward flow temperature in the climate control system along with heating/cooling of zones of the building, and thereby controlling the electrical power consumption of the system. A Model Predictive Control law is formulated to provide pre-storage of thermal energy in the manipulated zones without violating comfort requirements. The scheme is illustrated on a case study of a Danish shopping center, from which actual heating/cooling data have been collected for identification of thermal dynamics. The Coefficient of Performance of the system’s chiller is assumed to have a known dependence on flow and temperature, which is exploited to relate electrical power consumption to forward flow temperature. Simulation studies indicate potentials for significant power curtailment, in the order of 100 kW for one hour for the shopping center as a whole.
{"title":"Energy Flexibility for Systems with large Thermal Masses with Applications to Shopping Centers","authors":"J. Petersen, J. Bendtsen, Pierre J. C. Vogler-Finck, J. Stoustrup","doi":"10.1109/SmartGridComm.2018.8587444","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2018.8587444","url":null,"abstract":"In this paper we propose a scheme for managing energy flexibility in buildings with significant thermal masses and centralized climate control, such as commercial buildings, which can be used to provide ancillary services to the local electrical system (demand response). The scheme relies on being able to manipulate the forward flow temperature in the climate control system along with heating/cooling of zones of the building, and thereby controlling the electrical power consumption of the system. A Model Predictive Control law is formulated to provide pre-storage of thermal energy in the manipulated zones without violating comfort requirements. The scheme is illustrated on a case study of a Danish shopping center, from which actual heating/cooling data have been collected for identification of thermal dynamics. The Coefficient of Performance of the system’s chiller is assumed to have a known dependence on flow and temperature, which is exploited to relate electrical power consumption to forward flow temperature. Simulation studies indicate potentials for significant power curtailment, in the order of 100 kW for one hour for the shopping center as a whole.","PeriodicalId":213523,"journal":{"name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115030215","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 : 2018-10-01DOI: 10.1109/SmartGridComm.2018.8587572
Angelo Pinto, T. Pinto, Isabel Praça, Z. Vale, P. Faria
Electricity markets are complex and dynamic environments, mostly due to the large scale integration of renewable energy sources in the system. Negotiation in these markets is a significant challenge, especially when considering negotiations at the local level (e.g., between buildings and distributed energy resources). It is essential for a negotiator to be able to identify the negotiation profile of the players with whom he is negotiating. If a negotiator knows these profiles, it is possible to adapt the negotiation strategy and get better results in a negotiation. In order to identify and define such negotiation profiles, a clustering process is proposed in this paper. The clustering process is performed using the kml-k-means algorithm, in which several negotiation approaches are evaluated in order to identify and define players’ negotiation profiles. A case study is presented, using as input data, information from proposals made during a set of negotiations. Results show that the proposed approach is able to identify players’ negotiation profiles used in bilateral negotiations in electricity markets.
{"title":"Clustering-based negotiation profiles definition for local energy transactions","authors":"Angelo Pinto, T. Pinto, Isabel Praça, Z. Vale, P. Faria","doi":"10.1109/SmartGridComm.2018.8587572","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2018.8587572","url":null,"abstract":"Electricity markets are complex and dynamic environments, mostly due to the large scale integration of renewable energy sources in the system. Negotiation in these markets is a significant challenge, especially when considering negotiations at the local level (e.g., between buildings and distributed energy resources). It is essential for a negotiator to be able to identify the negotiation profile of the players with whom he is negotiating. If a negotiator knows these profiles, it is possible to adapt the negotiation strategy and get better results in a negotiation. In order to identify and define such negotiation profiles, a clustering process is proposed in this paper. The clustering process is performed using the kml-k-means algorithm, in which several negotiation approaches are evaluated in order to identify and define players’ negotiation profiles. A case study is presented, using as input data, information from proposals made during a set of negotiations. Results show that the proposed approach is able to identify players’ negotiation profiles used in bilateral negotiations in electricity markets.","PeriodicalId":213523,"journal":{"name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122692342","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 : 2018-10-01DOI: 10.1109/SmartGridComm.2018.8587412
Brida V. Mbuwir, M. Kaffash, Geert Deconinck
Motivated by the recent developments in machine learning and artificial intelligence, this work contributes to the application of reinforcement learning in Multi-Carrier Energy Systems (MCESs) to provide flexibility at the residential level. The work addresses the problem of providing flexibility through the operation of a storage device, and flexibility of supply by considering several infrastructures to meet the residential thermal and electrical demand in a MCES with a photovoltaic (PV) installation. The problem of providing flexibility using a battery is formulated as a sequential decision making problem under uncertainty where, at every time step, the uncertainty is due to the lack of knowledge about future electricity demand and weather dependent PV production. This paper proposes to address this problem using fitted Q-iteration, a batch Reinforcement Learning (RL) algorithm. The proposed method is tested using data from a typical Belgian residential household. Simulation results show that, an optimal interaction of the different energy carriers in the system can be obtained using RL and without providing a detailed model of the MCES.
{"title":"Battery Scheduling in a Residential Multi-Carrier Energy System Using Reinforcement Learning","authors":"Brida V. Mbuwir, M. Kaffash, Geert Deconinck","doi":"10.1109/SmartGridComm.2018.8587412","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2018.8587412","url":null,"abstract":"Motivated by the recent developments in machine learning and artificial intelligence, this work contributes to the application of reinforcement learning in Multi-Carrier Energy Systems (MCESs) to provide flexibility at the residential level. The work addresses the problem of providing flexibility through the operation of a storage device, and flexibility of supply by considering several infrastructures to meet the residential thermal and electrical demand in a MCES with a photovoltaic (PV) installation. The problem of providing flexibility using a battery is formulated as a sequential decision making problem under uncertainty where, at every time step, the uncertainty is due to the lack of knowledge about future electricity demand and weather dependent PV production. This paper proposes to address this problem using fitted Q-iteration, a batch Reinforcement Learning (RL) algorithm. The proposed method is tested using data from a typical Belgian residential household. Simulation results show that, an optimal interaction of the different energy carriers in the system can be obtained using RL and without providing a detailed model of the MCES.","PeriodicalId":213523,"journal":{"name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128511785","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 : 2018-10-01DOI: 10.1109/SmartGridComm.2018.8587436
Ezzeldin Shereen, G. Dán
Real-time monitoring and control in power systems is increasingly dependent on Phasor Measurement Units (PMUs). PMUs depend on precise time synchronization, and thus it is essential to ensure the security of time synchronization. In this paper we consider the detection of low-rate time synchronization attacks against PMUs. Based on a general clock model and a PMU measurement model we provide a closed form expression for the correlation between the clock frequency adjustments and the measured PMU phase angles in the absence of an attack. Leveraging the intuition that an attack would affect the correlation between these two quantities, we propose a model-based and a non-parametric correlation-based detector for time synchronization attacks. We evaluate the proposed detectors using extensive simulations. Our results show that they outperform traditional change detection techniques for clocks with low accuracy, for which attack detection is most challenging.
{"title":"Correlation-based Detection of PMU Time Synchronization Attacks","authors":"Ezzeldin Shereen, G. Dán","doi":"10.1109/SmartGridComm.2018.8587436","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2018.8587436","url":null,"abstract":"Real-time monitoring and control in power systems is increasingly dependent on Phasor Measurement Units (PMUs). PMUs depend on precise time synchronization, and thus it is essential to ensure the security of time synchronization. In this paper we consider the detection of low-rate time synchronization attacks against PMUs. Based on a general clock model and a PMU measurement model we provide a closed form expression for the correlation between the clock frequency adjustments and the measured PMU phase angles in the absence of an attack. Leveraging the intuition that an attack would affect the correlation between these two quantities, we propose a model-based and a non-parametric correlation-based detector for time synchronization attacks. We evaluate the proposed detectors using extensive simulations. Our results show that they outperform traditional change detection techniques for clocks with low accuracy, for which attack detection is most challenging.","PeriodicalId":213523,"journal":{"name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127554129","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 : 2018-10-01DOI: 10.1109/SmartGridComm.2018.8587425
D. Licea, M. Ghogho
The efficiency of microgrids with storage capacity strongly depends on the energy management system (EMS) which controls the energy flows in the system, including the charging and discharging process of the storage component. In this paper we focus on a residential microgrid, which consists of a grid-tied PV system and a battery, and propose a new low-complexity closed-loop EMS based on a nonlinear and time-variant feedback. The main characteristic of the proposed EMS is that instead of directly optimizing the energy flows, it optimizes the parameters of a two-layer controller. This EMS is tested using real irradiance and electrical consumption measurements. Results show a satisfactory performance of the proposed EMS.
{"title":"Low Complexity Closed-Loop Energy Manager for a Grid-Tied PV System with Battery","authors":"D. Licea, M. Ghogho","doi":"10.1109/SmartGridComm.2018.8587425","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2018.8587425","url":null,"abstract":"The efficiency of microgrids with storage capacity strongly depends on the energy management system (EMS) which controls the energy flows in the system, including the charging and discharging process of the storage component. In this paper we focus on a residential microgrid, which consists of a grid-tied PV system and a battery, and propose a new low-complexity closed-loop EMS based on a nonlinear and time-variant feedback. The main characteristic of the proposed EMS is that instead of directly optimizing the energy flows, it optimizes the parameters of a two-layer controller. This EMS is tested using real irradiance and electrical consumption measurements. Results show a satisfactory performance of the proposed EMS.","PeriodicalId":213523,"journal":{"name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126422154","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 : 2018-10-01DOI: 10.1109/SmartGridComm.2018.8587473
M. Kallitsis, Shrijita Bhattacharya, G. Michailidis
The bi-directional communication capabilities that emerged into the smart power grid play a critical role in the grid’s secure, reliable and efficient operation. Nevertheless, the data communication functionalities introduced to Advanced Metering Infrastructure (AMI) nodes end the grid’s isolation, and expose the network into an array of cyber-security threats that jeopardize the grid’s stability and availability. For instance, malware amenable to inject false data into the AMI can compromise the grid’s state estimation process and lead to catastrophic power outages. In this paper, we explore several statistical spatio-temporal models for efficient diagnosis of false data injection attacks in smart grids. The proposed methods leverage the data co-linearities that naturally arise in the AMI measurements of the electric network to provide forecasts for the network’s AMI observations, aiming to quickly detect the presence of “bad data”. We evaluate the proposed approaches with data tampered with stealth attacks compiled via three different attack strategies. Further, we juxtapose them against two other forecasting-aided detection methods appearing in the literature, and discuss the trade-offs of all techniques when employed on real-world power grid data, obtained from a large university campus.
{"title":"Detection of False Data Injection Attacks in Smart Grids Based on Forecasts","authors":"M. Kallitsis, Shrijita Bhattacharya, G. Michailidis","doi":"10.1109/SmartGridComm.2018.8587473","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2018.8587473","url":null,"abstract":"The bi-directional communication capabilities that emerged into the smart power grid play a critical role in the grid’s secure, reliable and efficient operation. Nevertheless, the data communication functionalities introduced to Advanced Metering Infrastructure (AMI) nodes end the grid’s isolation, and expose the network into an array of cyber-security threats that jeopardize the grid’s stability and availability. For instance, malware amenable to inject false data into the AMI can compromise the grid’s state estimation process and lead to catastrophic power outages. In this paper, we explore several statistical spatio-temporal models for efficient diagnosis of false data injection attacks in smart grids. The proposed methods leverage the data co-linearities that naturally arise in the AMI measurements of the electric network to provide forecasts for the network’s AMI observations, aiming to quickly detect the presence of “bad data”. We evaluate the proposed approaches with data tampered with stealth attacks compiled via three different attack strategies. Further, we juxtapose them against two other forecasting-aided detection methods appearing in the literature, and discuss the trade-offs of all techniques when employed on real-world power grid data, obtained from a large university campus.","PeriodicalId":213523,"journal":{"name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132562136","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 : 2018-10-01DOI: 10.1109/SmartGridComm.2018.8587457
M. Masi, Tanja Pavleska, Helder Aranha
The Energy sector and Smart Grids face great interoperability challenges, with virtual power plants (VPPs) being a major representative. In this paper, we present a methodology that automates and facilitates the design of solution architectures, producing a structured approach for building interoperable complex systems. Building on solid approaches that incorporate theory and practice of the healthcare enterprise and the Smart Grid sector, our methodology automates critical and time-consuming design steps that are currently performed manually. To accomplish the automation, we enhance and formalize validated principles and frameworks, but moreover, we introduce novel mechanisms to cater for architecture solution correctness, completeness and cohesiveness. The proposed methodology is applied to a VPP use case to demonstrate the applicability of such an architectural approach to other domains as well. An implementation tool of the methodology is also provided to support the practicality of the approach and to enable testability and result-reproducibility.
{"title":"Automating Smart Grid Solution Architecture Design","authors":"M. Masi, Tanja Pavleska, Helder Aranha","doi":"10.1109/SmartGridComm.2018.8587457","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2018.8587457","url":null,"abstract":"The Energy sector and Smart Grids face great interoperability challenges, with virtual power plants (VPPs) being a major representative. In this paper, we present a methodology that automates and facilitates the design of solution architectures, producing a structured approach for building interoperable complex systems. Building on solid approaches that incorporate theory and practice of the healthcare enterprise and the Smart Grid sector, our methodology automates critical and time-consuming design steps that are currently performed manually. To accomplish the automation, we enhance and formalize validated principles and frameworks, but moreover, we introduce novel mechanisms to cater for architecture solution correctness, completeness and cohesiveness. The proposed methodology is applied to a VPP use case to demonstrate the applicability of such an architectural approach to other domains as well. An implementation tool of the methodology is also provided to support the practicality of the approach and to enable testability and result-reproducibility.","PeriodicalId":213523,"journal":{"name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"358 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133267194","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 : 2018-10-01DOI: 10.1109/SmartGridComm.2018.8587535
S. Bahrami, Y. Chen, V. Wong
A price-based demand response program is a viable solution for distribution network operators (DNOs) to motivate electricity consumers toward scheduling their load demand during off-peak periods. This paper addresses the problem of load scheduling in a demand response program, while accounting for load demand uncertainty and the distribution network operational constraints. The centralized load control is a non convex optimization problem due to the ac power flow equations. We use convex relaxation techniques to transform the problem into a semidefinite program (SDP), which is solved using online convex optimization techniques to address the load demand uncertainty. To tackle the issue of computational complexity, we use proximal Jacobian alternating direction method of multipliers (PJ-ADMM) to decompose the centralized problem into the customers' load scheduling subproblems. The decentralized algorithm is executed by each customer to schedule its load demand in real-time. Via simulations on the IEEE 37-bus test feeder, we show that the proposed algorithm enables customers to approximate the optimal load profile in the benchmark scenario without load uncertainty, and the approximation is tight. Furthermore, we show a negligible gap of 2.3% between the customers' cost with the proposed algorithm and the cost in the benchmark scenario.
{"title":"An Autonomous Demand Response Algorithm based on Online Convex Optimization","authors":"S. Bahrami, Y. Chen, V. Wong","doi":"10.1109/SmartGridComm.2018.8587535","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2018.8587535","url":null,"abstract":"A price-based demand response program is a viable solution for distribution network operators (DNOs) to motivate electricity consumers toward scheduling their load demand during off-peak periods. This paper addresses the problem of load scheduling in a demand response program, while accounting for load demand uncertainty and the distribution network operational constraints. The centralized load control is a non convex optimization problem due to the ac power flow equations. We use convex relaxation techniques to transform the problem into a semidefinite program (SDP), which is solved using online convex optimization techniques to address the load demand uncertainty. To tackle the issue of computational complexity, we use proximal Jacobian alternating direction method of multipliers (PJ-ADMM) to decompose the centralized problem into the customers' load scheduling subproblems. The decentralized algorithm is executed by each customer to schedule its load demand in real-time. Via simulations on the IEEE 37-bus test feeder, we show that the proposed algorithm enables customers to approximate the optimal load profile in the benchmark scenario without load uncertainty, and the approximation is tight. Furthermore, we show a negligible gap of 2.3% between the customers' cost with the proposed algorithm and the cost in the benchmark scenario.","PeriodicalId":213523,"journal":{"name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131329396","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 : 2018-10-01DOI: 10.1109/SmartGridComm.2018.8587438
C. Silva, P. Faria, Z. Vale
The stakeholders that belong to the energy market will have to adapt to the changes that the implementation of the concept of Smart Grid imposes. This concept requires new business models that include the demand response programs, the use of distributed generation and especially the remuneration that will be made for their contribution. The exposed methodology can be presented as a solution for virtual power players in this new challenge. Throughout this article, this methodology was tested regarding the remuneration of aggregate groups of distributed generation. It will also be analyzed the meaning of this tariff for both sides - aggregator and producers.
{"title":"Assessment of Distributed Generation Units Remuneration Using Different Clustering Methods for Aggregation","authors":"C. Silva, P. Faria, Z. Vale","doi":"10.1109/SmartGridComm.2018.8587438","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2018.8587438","url":null,"abstract":"The stakeholders that belong to the energy market will have to adapt to the changes that the implementation of the concept of Smart Grid imposes. This concept requires new business models that include the demand response programs, the use of distributed generation and especially the remuneration that will be made for their contribution. The exposed methodology can be presented as a solution for virtual power players in this new challenge. Throughout this article, this methodology was tested regarding the remuneration of aggregate groups of distributed generation. It will also be analyzed the meaning of this tariff for both sides - aggregator and producers.","PeriodicalId":213523,"journal":{"name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129526555","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 : 2018-10-01DOI: 10.1109/SmartGridComm.2018.8587462
Hui Lin, Z. Kalbarczyk, R. Iyer
Control-related attacks can use malicious commands crafted in legitimate formats to initiate perturbations to power systems. Our previous work used the steady state of power systems (e.g., through power flow analysis) to estimate the consequences of such commands [1]. However, when power systems move from one steady state to another, their physical components go through a transient period, during which the system state can experience oscillations. An anomaly in an oscillation can make power systems lose synchronisms and experience catastrophic consequences. Analysis based on the steady state cannot understand and predict those harmful oscillations. In this paper, we study the impacts of control-related attacks on the dynamic responses of a power grid, by mapping malicious commands (e.g., that disconnect transmission lines) delivered via communication networks to power systems’ electromechanical models. Based on theoretical analysis and numerical simulations, we find that it is challenging for attackers to destabilize a power system, but they can introduce large oscillations in the transient period and thereby cause physical damage.
{"title":"Impact of Malicious SCADA Commands on Power Grids’ Dynamic Responses","authors":"Hui Lin, Z. Kalbarczyk, R. Iyer","doi":"10.1109/SmartGridComm.2018.8587462","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2018.8587462","url":null,"abstract":"Control-related attacks can use malicious commands crafted in legitimate formats to initiate perturbations to power systems. Our previous work used the steady state of power systems (e.g., through power flow analysis) to estimate the consequences of such commands [1]. However, when power systems move from one steady state to another, their physical components go through a transient period, during which the system state can experience oscillations. An anomaly in an oscillation can make power systems lose synchronisms and experience catastrophic consequences. Analysis based on the steady state cannot understand and predict those harmful oscillations. In this paper, we study the impacts of control-related attacks on the dynamic responses of a power grid, by mapping malicious commands (e.g., that disconnect transmission lines) delivered via communication networks to power systems’ electromechanical models. Based on theoretical analysis and numerical simulations, we find that it is challenging for attackers to destabilize a power system, but they can introduce large oscillations in the transient period and thereby cause physical damage.","PeriodicalId":213523,"journal":{"name":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126044160","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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