Pub Date : 2022-10-25DOI: 10.1109/SmartGridComm52983.2022.9961009
Mohand Ouamer Nait Belaid, V. Audebert, B. Deneuville, R. Langar
The increased integration of distributed energy resources (DERs) results in a two-way dynamic operation of the power distribution grid. Consequently, conventional Protection, Automation, and Control (PAC) systems are not able to manage DER related constraints in the distribution grid. New Fault location, Isolation, and service Recovery (FLISR) schemes based on communication capabilities are gaining a lot of momentum. Together with the 5th generation of mobile networks (5G), they improve the reactivity and the coordination of the grid defense lines. In this context, we present in this paper a FLISR traffic management framework in 5G Integrated Access and Backhaul (IAB) networks. Our framework consists first in optimizing the placement of FLISR protection functions within the Radio Access Network (RAN). Then, a joint routing and link scheduling of FLISR traffic in the 5G-RAN is proposed by taking into account the energy consumption. To achieve this, we formulate the master problem as two correlated integer linear programs (ILP) and present an optimal solution to solve it. Our objective is to find the best trade-off between the achieved network throughput and energy consumption, while ensuring the latency constraint of FLISR traffic. Our approach is compliant with the Software-Defined Radio Access Network (SD-RAN) paradigm since it can be integrated as a control flow application on top of a SD-RAN controller. Through a case study, we show that our proposed approach achieves significant gains in terms of energy consumption, flow acceptance and achieved network throughput, compared to baseline routing and placement strategies.
{"title":"Smart Grid Critical Traffic Routing and Link Scheduling in 5G IAB Networks","authors":"Mohand Ouamer Nait Belaid, V. Audebert, B. Deneuville, R. Langar","doi":"10.1109/SmartGridComm52983.2022.9961009","DOIUrl":"https://doi.org/10.1109/SmartGridComm52983.2022.9961009","url":null,"abstract":"The increased integration of distributed energy resources (DERs) results in a two-way dynamic operation of the power distribution grid. Consequently, conventional Protection, Automation, and Control (PAC) systems are not able to manage DER related constraints in the distribution grid. New Fault location, Isolation, and service Recovery (FLISR) schemes based on communication capabilities are gaining a lot of momentum. Together with the 5th generation of mobile networks (5G), they improve the reactivity and the coordination of the grid defense lines. In this context, we present in this paper a FLISR traffic management framework in 5G Integrated Access and Backhaul (IAB) networks. Our framework consists first in optimizing the placement of FLISR protection functions within the Radio Access Network (RAN). Then, a joint routing and link scheduling of FLISR traffic in the 5G-RAN is proposed by taking into account the energy consumption. To achieve this, we formulate the master problem as two correlated integer linear programs (ILP) and present an optimal solution to solve it. Our objective is to find the best trade-off between the achieved network throughput and energy consumption, while ensuring the latency constraint of FLISR traffic. Our approach is compliant with the Software-Defined Radio Access Network (SD-RAN) paradigm since it can be integrated as a control flow application on top of a SD-RAN controller. Through a case study, we show that our proposed approach achieves significant gains in terms of energy consumption, flow acceptance and achieved network throughput, compared to baseline routing and placement strategies.","PeriodicalId":252202,"journal":{"name":"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125014181","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 : 2022-10-25DOI: 10.1109/SmartGridComm52983.2022.9961023
Dennis Overbeck, Fabian Kurtz, S. Böcker, C. Wietfeld
The shift towards renewable energies is increasing communication demands, particularly in novel energy grid architectures. One such approach is the concept of cellular energy systems, which divide the grid into regions with the potential to operate independently. Management of the resulting energy flows between and within cells is highly complex. Thus communication becomes increasingly challenging. A promising method for handling the resulting mixed-critical data flows is the fifth generation of mobile radio networks, i.e., 5G. It enables reliable communication in public and private infrastructures via network slicing. Here, a single physical network is split up into multiple slices, each addressing the requirements of various services and devices optimally. This enables cost-efficient communications based on widely available Information and Communications Technology (ICT) infrastructures. In this work we provide an integrated architecture as well as a physical cellular energy system testing setup. This is supported by an open-source 4G/5G software stack and gateways for handling mixed-critical grid communications. The physical testbed is located at the Smart Grid Technology Lab (SGTL) at TU Dortmund university and enables real-world analysis of relevant scenarios. Results illustrate the capabilities of Radio Access Network (RAN) network slicing and provide insights on deploying dedicated mobile radio networks in cellular energy systems with mixed-critical services.
{"title":"Design of a 5G Network Slicing Architecture for Mixed-Critical Services in Cellular Energy Systems","authors":"Dennis Overbeck, Fabian Kurtz, S. Böcker, C. Wietfeld","doi":"10.1109/SmartGridComm52983.2022.9961023","DOIUrl":"https://doi.org/10.1109/SmartGridComm52983.2022.9961023","url":null,"abstract":"The shift towards renewable energies is increasing communication demands, particularly in novel energy grid architectures. One such approach is the concept of cellular energy systems, which divide the grid into regions with the potential to operate independently. Management of the resulting energy flows between and within cells is highly complex. Thus communication becomes increasingly challenging. A promising method for handling the resulting mixed-critical data flows is the fifth generation of mobile radio networks, i.e., 5G. It enables reliable communication in public and private infrastructures via network slicing. Here, a single physical network is split up into multiple slices, each addressing the requirements of various services and devices optimally. This enables cost-efficient communications based on widely available Information and Communications Technology (ICT) infrastructures. In this work we provide an integrated architecture as well as a physical cellular energy system testing setup. This is supported by an open-source 4G/5G software stack and gateways for handling mixed-critical grid communications. The physical testbed is located at the Smart Grid Technology Lab (SGTL) at TU Dortmund university and enables real-world analysis of relevant scenarios. Results illustrate the capabilities of Radio Access Network (RAN) network slicing and provide insights on deploying dedicated mobile radio networks in cellular energy systems with mixed-critical services.","PeriodicalId":252202,"journal":{"name":"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126982489","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 : 2022-10-25DOI: 10.1109/SmartGridComm52983.2022.9961046
Seerin Ahmad, Bohyun Ahn, Taesic Kim, Jinchun Choi, Myungsuk Chae, Dongjun Han, D. Won
Distributed energy resource management system (DERMS) is a supervision system managing distributed energy resources (DERs) in a distribution system. However, the centralized DERMS has a potential risk of a single point of failure posed by cyber-attacks (e.g., denial of service attacks and ransomware attacks). This will cause visibility and control losses of the DER system. In this paper, blockchain (BC) technology is leveraged to enhance the resilience of DERMS by recovering the operation of a DER system during the DERMS outage. The proposed BC system is a governance platform for the DER system proving security and resilient control services on behalf of the DERMS until the availability of the DERMS is recovered. The feasibility of the proposed BC-integrated DERMS system toward a resilient DER system is validated by using a cyber-physical co-simulation testbed.
{"title":"Blockchain-Integrated Resilient Distributed Energy Resources Management System","authors":"Seerin Ahmad, Bohyun Ahn, Taesic Kim, Jinchun Choi, Myungsuk Chae, Dongjun Han, D. Won","doi":"10.1109/SmartGridComm52983.2022.9961046","DOIUrl":"https://doi.org/10.1109/SmartGridComm52983.2022.9961046","url":null,"abstract":"Distributed energy resource management system (DERMS) is a supervision system managing distributed energy resources (DERs) in a distribution system. However, the centralized DERMS has a potential risk of a single point of failure posed by cyber-attacks (e.g., denial of service attacks and ransomware attacks). This will cause visibility and control losses of the DER system. In this paper, blockchain (BC) technology is leveraged to enhance the resilience of DERMS by recovering the operation of a DER system during the DERMS outage. The proposed BC system is a governance platform for the DER system proving security and resilient control services on behalf of the DERMS until the availability of the DERMS is recovered. The feasibility of the proposed BC-integrated DERMS system toward a resilient DER system is validated by using a cyber-physical co-simulation testbed.","PeriodicalId":252202,"journal":{"name":"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129977946","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}
With the development of information and communications technology (ICT) in DC microgrids (DCmGs), the threat of false data injection attacks (FDIAs) is becoming more and more serious. However, the existing literature mainly focuses on the detection and identification of FDIAs in DCmGs, while the data recovery after the perception of FDIAs has never been thor-oughly investigated yet. In this paper, we propose a distributed data recovery scheme to eliminate the adverse impact caused by FDIAs in DCmGs. Firstly, by observing the point of common coupling (PCC) voltage under FDIAs, the injected constant bias can be roughly estimated. In order to obtain the precise constant bias, the mean filter (MF) is adopted to handle the measurement noises and small oscillations. Then, the estimated precise constant bias is compensated for the communicated signal to eliminate the attack impact. Furthermore, our proposed data recovery scheme, which only needs local information, is fully distributed. Finally, the accuracy and effectiveness of the distributed data recovery scheme are evaluated through systematical hardware-in-the-loop (HIL) experiments.
{"title":"Distributed Data Recovery Against False Data Injection Attacks in DC Microgrids","authors":"Zexuan Jin, Mengxiang Liu, Ruilong Deng, Peng Cheng","doi":"10.1109/SmartGridComm52983.2022.9960968","DOIUrl":"https://doi.org/10.1109/SmartGridComm52983.2022.9960968","url":null,"abstract":"With the development of information and communications technology (ICT) in DC microgrids (DCmGs), the threat of false data injection attacks (FDIAs) is becoming more and more serious. However, the existing literature mainly focuses on the detection and identification of FDIAs in DCmGs, while the data recovery after the perception of FDIAs has never been thor-oughly investigated yet. In this paper, we propose a distributed data recovery scheme to eliminate the adverse impact caused by FDIAs in DCmGs. Firstly, by observing the point of common coupling (PCC) voltage under FDIAs, the injected constant bias can be roughly estimated. In order to obtain the precise constant bias, the mean filter (MF) is adopted to handle the measurement noises and small oscillations. Then, the estimated precise constant bias is compensated for the communicated signal to eliminate the attack impact. Furthermore, our proposed data recovery scheme, which only needs local information, is fully distributed. Finally, the accuracy and effectiveness of the distributed data recovery scheme are evaluated through systematical hardware-in-the-loop (HIL) experiments.","PeriodicalId":252202,"journal":{"name":"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115786480","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 : 2022-10-25DOI: 10.1109/SmartGridComm52983.2022.9960992
H. Malik, A. Pouttu
Existing ICT networks are characterized by high level of energy consumption. In order to power up 5G base station sites, rising energy cost and high carbon emissions are major concerns that need to be dealt with. To achieve carbon neutrality, ICT sector needs to transform base station sites in a self-sustainable manner using renewable energy sources, local batteries and energy conservation techniques, even in adverse weather conditions and unexpected power outages. In this paper, short term-forecasting models are studied for accurate energy consumption and production forecast. The proposed architecture provides adaptive energy conservation technique using time series data analysis and Long Short-Term Memory for 5GNR base station site which is independent of traditional power sources and is completely powered by green energy. The accuracy analysis of this study was performed by the Mean Square Error (MSE) and Root Mean Square Error (RMSE). The results show high accuracy levels of LSTM model in guiding short-term energy forecasting for green ICT networks.
{"title":"Integration of LSTM based Model to guide short-term energy forecasting for green ICT networks in smart grids","authors":"H. Malik, A. Pouttu","doi":"10.1109/SmartGridComm52983.2022.9960992","DOIUrl":"https://doi.org/10.1109/SmartGridComm52983.2022.9960992","url":null,"abstract":"Existing ICT networks are characterized by high level of energy consumption. In order to power up 5G base station sites, rising energy cost and high carbon emissions are major concerns that need to be dealt with. To achieve carbon neutrality, ICT sector needs to transform base station sites in a self-sustainable manner using renewable energy sources, local batteries and energy conservation techniques, even in adverse weather conditions and unexpected power outages. In this paper, short term-forecasting models are studied for accurate energy consumption and production forecast. The proposed architecture provides adaptive energy conservation technique using time series data analysis and Long Short-Term Memory for 5GNR base station site which is independent of traditional power sources and is completely powered by green energy. The accuracy analysis of this study was performed by the Mean Square Error (MSE) and Root Mean Square Error (RMSE). The results show high accuracy levels of LSTM model in guiding short-term energy forecasting for green ICT networks.","PeriodicalId":252202,"journal":{"name":"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127350085","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 : 2022-10-25DOI: 10.1109/SmartGridComm52983.2022.9961040
Thanasis G. Papaioannou, G. Stamoulis
Energy flexibility management can significantly support the smoother and more cost-effective green transformation of the energy mix. However, effective management of the flexibility of residential loads can only be achieved if users are successfully engaged into the process. In this paper, we propose an optimization framework that incorporates provision of different forms of monetary and non-monetary incentives to prosumers, i.e., rewards, lotteries, peer-pressure, for providing flexibility at specific time slots. Economic rewards are offered according to a simple, yet very powerful, linear incentives' function. Dynamic tariffs per time slot for purchasing and selling electricity are accommodated in this framework as well. The optimization problem of the DR aggregator is modeled as a cost-minimization one; its solution as a Stackelberg game is outlined for the case of full information on user-utility functions by the DR aggregator. Moreover, a distributed iterative algorithm is developed for solving the flexibility-management problem in the case where user-utility functions are not known to the aggregator. Numerical results show that this optimization framework is able to elicit the required flexibility from users at a minimum incentive cost, especially when monetary rewards are combined with peer pressure.
{"title":"An Optimization Framework for Effective Flexibility Management for Prosumers","authors":"Thanasis G. Papaioannou, G. Stamoulis","doi":"10.1109/SmartGridComm52983.2022.9961040","DOIUrl":"https://doi.org/10.1109/SmartGridComm52983.2022.9961040","url":null,"abstract":"Energy flexibility management can significantly support the smoother and more cost-effective green transformation of the energy mix. However, effective management of the flexibility of residential loads can only be achieved if users are successfully engaged into the process. In this paper, we propose an optimization framework that incorporates provision of different forms of monetary and non-monetary incentives to prosumers, i.e., rewards, lotteries, peer-pressure, for providing flexibility at specific time slots. Economic rewards are offered according to a simple, yet very powerful, linear incentives' function. Dynamic tariffs per time slot for purchasing and selling electricity are accommodated in this framework as well. The optimization problem of the DR aggregator is modeled as a cost-minimization one; its solution as a Stackelberg game is outlined for the case of full information on user-utility functions by the DR aggregator. Moreover, a distributed iterative algorithm is developed for solving the flexibility-management problem in the case where user-utility functions are not known to the aggregator. Numerical results show that this optimization framework is able to elicit the required flexibility from users at a minimum incentive cost, especially when monetary rewards are combined with peer pressure.","PeriodicalId":252202,"journal":{"name":"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121139394","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 : 2022-10-25DOI: 10.1109/SmartGridComm52983.2022.9961044
Zhoubing Li, Meng Zhang, Lin Li, Xiaohong Guan
Fault diagnosis is an important guarantee for the stable and safe operation of microgrids, which consists of fault detection and fault localization. However, most current researches separately deal with these two issues, which cannot obtain completed fault diagnosis results. This paper proposes a solution based on deep learning, namely branch convolution neural network (CNN) with a majority voting (B-CNN-MV) model, to simultaneously realize fault detection and fault localization through two branches. One of the branches realizes fault detection and the other performs fault localization. Firstly, in each branch, the CNN module extracts the two-dimensional image features of each sample in the spatial dimension and outputs primary classification results. Then, the classification results from the CNN module within one period of data constitute the temporal dimension input for the following majority voting module. Finally, the majority voting modules after each branch employ these temporal dimension inputs to calculate the final fault type and location results. Through this new design, the information on accurate fault type and fault location can be obtained simultaneously. Moreover, the test results show the proposed B-CNN-MV model can also achieve a high accuracy even in the case of insufficient data.
{"title":"Fault Diagnosis of Microgrids Using Branch Convolution Neural Network and Majority Voting","authors":"Zhoubing Li, Meng Zhang, Lin Li, Xiaohong Guan","doi":"10.1109/SmartGridComm52983.2022.9961044","DOIUrl":"https://doi.org/10.1109/SmartGridComm52983.2022.9961044","url":null,"abstract":"Fault diagnosis is an important guarantee for the stable and safe operation of microgrids, which consists of fault detection and fault localization. However, most current researches separately deal with these two issues, which cannot obtain completed fault diagnosis results. This paper proposes a solution based on deep learning, namely branch convolution neural network (CNN) with a majority voting (B-CNN-MV) model, to simultaneously realize fault detection and fault localization through two branches. One of the branches realizes fault detection and the other performs fault localization. Firstly, in each branch, the CNN module extracts the two-dimensional image features of each sample in the spatial dimension and outputs primary classification results. Then, the classification results from the CNN module within one period of data constitute the temporal dimension input for the following majority voting module. Finally, the majority voting modules after each branch employ these temporal dimension inputs to calculate the final fault type and location results. Through this new design, the information on accurate fault type and fault location can be obtained simultaneously. Moreover, the test results show the proposed B-CNN-MV model can also achieve a high accuracy even in the case of insufficient data.","PeriodicalId":252202,"journal":{"name":"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121147266","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 : 2022-10-25DOI: 10.1109/SmartGridComm52983.2022.9961050
D. Nicol
We describe a method where a utility can anonymize network device configurations and upload them to a remote service provider who analyzes connectivity (oblivious to the anonymization) and returns the results in anonymized coordinates to the utility, where they are de-anonymized. The approach has application for sharing problematic configurations with vendors, for cloud-based services that analyze connectivity and detect problems, and for connectivity of the sort regulated by NERC-CIP requirements.
{"title":"Connectivity Preserving Anonymization of Smart Grid Network Configurations","authors":"D. Nicol","doi":"10.1109/SmartGridComm52983.2022.9961050","DOIUrl":"https://doi.org/10.1109/SmartGridComm52983.2022.9961050","url":null,"abstract":"We describe a method where a utility can anonymize network device configurations and upload them to a remote service provider who analyzes connectivity (oblivious to the anonymization) and returns the results in anonymized coordinates to the utility, where they are de-anonymized. The approach has application for sharing problematic configurations with vendors, for cloud-based services that analyze connectivity and detect problems, and for connectivity of the sort regulated by NERC-CIP requirements.","PeriodicalId":252202,"journal":{"name":"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131443855","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 : 2022-10-25DOI: 10.1109/SmartGridComm52983.2022.9961061
Ömer Sen, Florian Schmidtke, F. Carere, F. Santori, Andreas Ulbig, A. Monti
While the increasing penetration of information and communication technology into distribution grid brings numerous benefits, it also opens up a new threat landscape, particularly through cyberattacks. To provide a basis for countermeasures against such threats, this paper addresses the investigation of the impact and manifestations of cyberattacks on smart grids by replicating the power grid in a secure, isolated, and controlled laboratory environment as a cyber-physical twin. Currently, detecting intrusions by unauthorized third parties into the central monitoring and control system of grid operators, especially attacks within the grid perimeter, is a major challenge. The development and validation of methods to detect and prevent coordinated and timed attacks on electric power systems depends not only on the availability and quality of data from such attack scenarios, but also on suitable realistic investigation environments. However, to create a comprehensive investigation environment, a realistic representation of the study object is required to thoroughly investigate critical cyberattacks on grid operations and evaluate their impact on the power grid using real data. In this paper, we demonstrate our cyber-physical twin approach using a microgrid in the context of a cyberattack case study.
{"title":"Investigating the Cybersecurity of Smart Grids Based on Cyber-Physical Twin Approach","authors":"Ömer Sen, Florian Schmidtke, F. Carere, F. Santori, Andreas Ulbig, A. Monti","doi":"10.1109/SmartGridComm52983.2022.9961061","DOIUrl":"https://doi.org/10.1109/SmartGridComm52983.2022.9961061","url":null,"abstract":"While the increasing penetration of information and communication technology into distribution grid brings numerous benefits, it also opens up a new threat landscape, particularly through cyberattacks. To provide a basis for countermeasures against such threats, this paper addresses the investigation of the impact and manifestations of cyberattacks on smart grids by replicating the power grid in a secure, isolated, and controlled laboratory environment as a cyber-physical twin. Currently, detecting intrusions by unauthorized third parties into the central monitoring and control system of grid operators, especially attacks within the grid perimeter, is a major challenge. The development and validation of methods to detect and prevent coordinated and timed attacks on electric power systems depends not only on the availability and quality of data from such attack scenarios, but also on suitable realistic investigation environments. However, to create a comprehensive investigation environment, a realistic representation of the study object is required to thoroughly investigate critical cyberattacks on grid operations and evaluate their impact on the power grid using real data. In this paper, we demonstrate our cyber-physical twin approach using a microgrid in the context of a cyberattack case study.","PeriodicalId":252202,"journal":{"name":"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134178842","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 : 2022-10-25DOI: 10.1109/SmartGridComm52983.2022.9960999
Qisheng Huang, Yunshu Liu, Peng-jie Sun, Junling Li, Jin Xu
Many countries have implemented different policies to achieve carbon neutrality in the current century. The cap-and-trade policy is one of the popular policies. The cap-and-trade policy provides carbon emission quotas for power generation companies. Each company must carefully determine its energy production based on the carbon emission quota and demand uncertainty. In this paper, we analyze the cooperation among different power generation companies using the coalitional game theory. We show the optimality of the grand coalition for minimizing the total cost by proving that the cost function is subadditive. This result highlights the benefits of cooperation. We further propose a cost allocation mechanism that allocates the total cost to different power generation companies. We prove that the proposed cost allocation mechanism is in the core of the coalitional game such that no group of power generation companies has any incentive to leave the grand coalition. Numerical experiments have been conducted to validate the established theoretical results.
{"title":"Cooperative Carbon Emission Trading: A Coalitional Game Approach","authors":"Qisheng Huang, Yunshu Liu, Peng-jie Sun, Junling Li, Jin Xu","doi":"10.1109/SmartGridComm52983.2022.9960999","DOIUrl":"https://doi.org/10.1109/SmartGridComm52983.2022.9960999","url":null,"abstract":"Many countries have implemented different policies to achieve carbon neutrality in the current century. The cap-and-trade policy is one of the popular policies. The cap-and-trade policy provides carbon emission quotas for power generation companies. Each company must carefully determine its energy production based on the carbon emission quota and demand uncertainty. In this paper, we analyze the cooperation among different power generation companies using the coalitional game theory. We show the optimality of the grand coalition for minimizing the total cost by proving that the cost function is subadditive. This result highlights the benefits of cooperation. We further propose a cost allocation mechanism that allocates the total cost to different power generation companies. We prove that the proposed cost allocation mechanism is in the core of the coalitional game such that no group of power generation companies has any incentive to leave the grand coalition. Numerical experiments have been conducted to validate the established theoretical results.","PeriodicalId":252202,"journal":{"name":"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"274 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134448251","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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