Pub Date : 2019-10-01DOI: 10.1109/SmartGridComm.2019.8909695
Mohammadhafez Bazrafshan, Hao Zhu, A. Khodaei, Nikolaos Gatsis
During grid overload or upon occurrence of certain contingencies, a corrective action is required to eliminate congestion and reduce transmission line thermal limit violations. In this paper, we propose to use demand-responsive loads for such a purpose. Cost considerations include power retrieved from the slack reserves and the dis-utility of consumers for providing demand-response actions. Violations of voltage and generator reactive power limits are also accounted for. The idea is to topologically re-arrange the consumption of flexible loads to achieve grid de-congestion while maintaining the aggregate network power consumption constant to avoid interference with frequency control procedures. Our formulation is based on nonlinear power flows and easily allows the inclusion of voltage-dependent loads. An online gradient projection algorithm with closed-form updates is developed to solve the non-convex grid de-congestion problem. Approximate gradient calculations based on fast-decoupled load flow are further provided to simplify the algorithm and make it amenable to distributed implementation.
{"title":"Online Demand Response of Voltage-Dependent Loads for Corrective Grid De-Congestion","authors":"Mohammadhafez Bazrafshan, Hao Zhu, A. Khodaei, Nikolaos Gatsis","doi":"10.1109/SmartGridComm.2019.8909695","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909695","url":null,"abstract":"During grid overload or upon occurrence of certain contingencies, a corrective action is required to eliminate congestion and reduce transmission line thermal limit violations. In this paper, we propose to use demand-responsive loads for such a purpose. Cost considerations include power retrieved from the slack reserves and the dis-utility of consumers for providing demand-response actions. Violations of voltage and generator reactive power limits are also accounted for. The idea is to topologically re-arrange the consumption of flexible loads to achieve grid de-congestion while maintaining the aggregate network power consumption constant to avoid interference with frequency control procedures. Our formulation is based on nonlinear power flows and easily allows the inclusion of voltage-dependent loads. An online gradient projection algorithm with closed-form updates is developed to solve the non-convex grid de-congestion problem. Approximate gradient calculations based on fast-decoupled load flow are further provided to simplify the algorithm and make it amenable to distributed implementation.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"436 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113999475","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 : 2019-10-01DOI: 10.1109/SmartGridComm.2019.8909743
Farzana Kabir, N. Yu, W. Yao, Rui Yang, Y. Zhang
Accurate estimation of solar photovoltaic (PV) generation is crucial for distribution grid control and optimization. Unfortunately, most of the residential solar PV installations are behind-the-meter. Thus, utilities only have access to the net load readings. This paper presents an unsupervised framework for estimating solar PV generation by disaggregating the net load readings. The proposed framework synergistically combines a physical PV system performance model with a statistical model for load estimation. Specifically, our algorithm iteratively estimates solar PV generation with a physical model and electric load with the Hidden Markov model regression. The proposed algorithm is also capable of estimating the key technical parameters of the solar PV systems. Our proposed method is validated against net load and solar PV generation data gathered from residential customers located in Austin, Texas. The validation results show that our method reduces mean squared error by 44% compared to the state-of-the-art disaggregation algorithm.
{"title":"Estimation of Behind-the-Meter Solar Generation by Integrating Physical with Statistical Models","authors":"Farzana Kabir, N. Yu, W. Yao, Rui Yang, Y. Zhang","doi":"10.1109/SmartGridComm.2019.8909743","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909743","url":null,"abstract":"Accurate estimation of solar photovoltaic (PV) generation is crucial for distribution grid control and optimization. Unfortunately, most of the residential solar PV installations are behind-the-meter. Thus, utilities only have access to the net load readings. This paper presents an unsupervised framework for estimating solar PV generation by disaggregating the net load readings. The proposed framework synergistically combines a physical PV system performance model with a statistical model for load estimation. Specifically, our algorithm iteratively estimates solar PV generation with a physical model and electric load with the Hidden Markov model regression. The proposed algorithm is also capable of estimating the key technical parameters of the solar PV systems. Our proposed method is validated against net load and solar PV generation data gathered from residential customers located in Austin, Texas. The validation results show that our method reduces mean squared error by 44% compared to the state-of-the-art disaggregation algorithm.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122911188","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 : 2019-10-01DOI: 10.1109/SmartGridComm.2019.8909696
Y. Li, Cong Li, Guidong Wu, Chenyu Zhang
The coordination of various terminals in the power grid requires time consistency. If there is an error in time synchronization, it will cause time misalignment and difficulties in grid data analysis. Due to the existence of massive terminals in the power grid, the existing time synchronization technology cannot be applied to the big data scenario for multi-source grid. Mobile Edge Computing (MEC) effectively combines Internet of Things (IoT) and mobile network technologies to achieve a more flexible time distribution mechanism and more accurate edge-side time synchronization accuracy. MEC and Precision Time Protocol(PTP) are applied to time distribution for the power grid in this paper. And a high-precision time distribution mechanism based on MEC for multi-source power grid is described in this paper. Simulation results show that the time synchronization accuracy can be improved by using MEC for time distribution.
{"title":"Research on High-precision Time Distribution Mechanism of Multi-source Power Grid Based on MEC","authors":"Y. Li, Cong Li, Guidong Wu, Chenyu Zhang","doi":"10.1109/SmartGridComm.2019.8909696","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909696","url":null,"abstract":"The coordination of various terminals in the power grid requires time consistency. If there is an error in time synchronization, it will cause time misalignment and difficulties in grid data analysis. Due to the existence of massive terminals in the power grid, the existing time synchronization technology cannot be applied to the big data scenario for multi-source grid. Mobile Edge Computing (MEC) effectively combines Internet of Things (IoT) and mobile network technologies to achieve a more flexible time distribution mechanism and more accurate edge-side time synchronization accuracy. MEC and Precision Time Protocol(PTP) are applied to time distribution for the power grid in this paper. And a high-precision time distribution mechanism based on MEC for multi-source power grid is described in this paper. Simulation results show that the time synchronization accuracy can be improved by using MEC for time distribution.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131096798","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 : 2019-10-01DOI: 10.1109/SmartGridComm.2019.8909742
Alexandre Rio, Y. Maurel, Olivier Barais, Yoran Bugni
Energy efficiency is a concern impacting both ecology and economy. Most approaches aiming at reducing the energy impact of a site focus on only one specific aspect of the ecosystem: appliances, local generation or energy storage.A trade-off analysis of the many factors to consider is challenging and must be supported by tools. This paper proposes a Model-Driven Engineering approach mixing all these concerns into one comprehensive model. This model can then be used to size either local production means, either energy storage capacity and also help to analyze differences between technologies. It also enables process optimization by modeling activity variability: it takes the weather into account to give regular feedback to the end user. This approach is illustrated by simulation using real consumption and local production data from a representative agricultural site. We show its use by: sizing solar panels, by choosing between battery technologies and specification and by evaluating different demand response scenarios while examining the economic sustainability of these choices.
{"title":"Benefits of Energy Management Systems on local energy efficiency, an agricultural case study","authors":"Alexandre Rio, Y. Maurel, Olivier Barais, Yoran Bugni","doi":"10.1109/SmartGridComm.2019.8909742","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909742","url":null,"abstract":"Energy efficiency is a concern impacting both ecology and economy. Most approaches aiming at reducing the energy impact of a site focus on only one specific aspect of the ecosystem: appliances, local generation or energy storage.A trade-off analysis of the many factors to consider is challenging and must be supported by tools. This paper proposes a Model-Driven Engineering approach mixing all these concerns into one comprehensive model. This model can then be used to size either local production means, either energy storage capacity and also help to analyze differences between technologies. It also enables process optimization by modeling activity variability: it takes the weather into account to give regular feedback to the end user. This approach is illustrated by simulation using real consumption and local production data from a representative agricultural site. We show its use by: sizing solar panels, by choosing between battery technologies and specification and by evaluating different demand response scenarios while examining the economic sustainability of these choices.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132541831","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 : 2019-10-01DOI: 10.1109/SmartGridComm.2019.8909773
H. Hao, Yuchen Wang, Yi Shi, Zhenyu Li, Yiling Wu, Chenwan Li
Communication network has become an essential part of smart grid infrastructure and is under fundamental change within the energy industry. Clear trends indicate that utilities are looking for an upgrade of communication solutions that are able to support massive connections, higher data rate, and lower latency. To achieve this goal, ownership or self-licensing is seen by the utilities as a much more cost effective method of accessing the spectrum. Nevertheless, for many countries, existing narrowband spectrum allocation are likely to remain unchanged for five to ten years due to existing licensed systems under operation. To avoid the difficulty of spectrum refarming, this paper introduces an innovative communication technology – Internet of Things-Grid (IoT-G) – which achieves excellent broadband transmission performances by aggregating existing fragmented narrowband spectrum. This technology inherits several key air interface design elements of 3GPP Release 15 IoT features as well as a number of low-latency design concepts from 3GPP 5G systems. Building upon the cellular ecosystem, IoT-G has a mature industrial chain including end-to-end chipsets, terminals and network equipment. It has passed multiple field tests in 2018, and is planned for large-scale nationwide deployment in 7 provinces and 22 cities in China in 2019.
{"title":"IoT-G: A Low-Latency and High-Reliability Private Power Wireless Communication Architecture for Smart Grid","authors":"H. Hao, Yuchen Wang, Yi Shi, Zhenyu Li, Yiling Wu, Chenwan Li","doi":"10.1109/SmartGridComm.2019.8909773","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909773","url":null,"abstract":"Communication network has become an essential part of smart grid infrastructure and is under fundamental change within the energy industry. Clear trends indicate that utilities are looking for an upgrade of communication solutions that are able to support massive connections, higher data rate, and lower latency. To achieve this goal, ownership or self-licensing is seen by the utilities as a much more cost effective method of accessing the spectrum. Nevertheless, for many countries, existing narrowband spectrum allocation are likely to remain unchanged for five to ten years due to existing licensed systems under operation. To avoid the difficulty of spectrum refarming, this paper introduces an innovative communication technology – Internet of Things-Grid (IoT-G) – which achieves excellent broadband transmission performances by aggregating existing fragmented narrowband spectrum. This technology inherits several key air interface design elements of 3GPP Release 15 IoT features as well as a number of low-latency design concepts from 3GPP 5G systems. Building upon the cellular ecosystem, IoT-G has a mature industrial chain including end-to-end chipsets, terminals and network equipment. It has passed multiple field tests in 2018, and is planned for large-scale nationwide deployment in 7 provinces and 22 cities in China in 2019.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134061019","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 : 2019-10-01DOI: 10.1109/SmartGridComm.2019.8909756
Lingling Tang, Yulin Yi, Yuexing Peng
Electrical load forecasting is an important part of power system planning and operation, which can guide the power enterprises to arrange generation plan reasonably, reduce the cost of power generation, and provide a reference for power grid reconstruction and optimization. However, due to the complicated inner non-linear property and seasonality pattern of electrical load, accurate short-term load forecasting (STLF) is of big challenge. In this paper, we firstly study the large time-span quasi-periodicity of load sequences, including the inner correlation of a short load segment and the quasi-periodicity among the load segments spanning different time duration from a week to a month. Then, an ensemble method is proposed, which combines Auto-regressive Integrated Moving Average (ARIMA) and Long Short Term Memory (LSTM) in order to fully exploit the large time-span quasi-periodicity of the loads. Here, ARIMA model captures the stationary pattern of the load segments, while LSTM extracts the complicated non-linear relations of load segments. The proposed method is evaluated on a data set of load consumption in Toronto, and the results show the proposed method outperforms the existing popular STLF models with a small payload of computational complexity.
{"title":"An ensemble deep learning model for short-term load forecasting based on ARIMA and LSTM","authors":"Lingling Tang, Yulin Yi, Yuexing Peng","doi":"10.1109/SmartGridComm.2019.8909756","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909756","url":null,"abstract":"Electrical load forecasting is an important part of power system planning and operation, which can guide the power enterprises to arrange generation plan reasonably, reduce the cost of power generation, and provide a reference for power grid reconstruction and optimization. However, due to the complicated inner non-linear property and seasonality pattern of electrical load, accurate short-term load forecasting (STLF) is of big challenge. In this paper, we firstly study the large time-span quasi-periodicity of load sequences, including the inner correlation of a short load segment and the quasi-periodicity among the load segments spanning different time duration from a week to a month. Then, an ensemble method is proposed, which combines Auto-regressive Integrated Moving Average (ARIMA) and Long Short Term Memory (LSTM) in order to fully exploit the large time-span quasi-periodicity of the loads. Here, ARIMA model captures the stationary pattern of the load segments, while LSTM extracts the complicated non-linear relations of load segments. The proposed method is evaluated on a data set of load consumption in Toronto, and the results show the proposed method outperforms the existing popular STLF models with a small payload of computational complexity.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134532263","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 : 2019-10-01DOI: 10.1109/SmartGridComm.2019.8909783
P. Biswas, Heng Chuan Tan, Qingbo Zhu, Yuan Li, D. Mashima, Binbin Chen
Cyber attacks pose a major threat to smart grid infrastructures where communication links bind physical devices to provide critical measurement, protection, and control functionalities. Substation is an integral part of a power system. Modern substations with intelligent electronic devices and remote access interface are more prone to cyber attacks. Hence, there is an urgent need to consider cybersecurity at the electrical substation level. This paper makes a systematic effort to develop a synthesized dataset focusing on IEC 61850 GOOSE communication that is essential for automation and protection in smart grid. The dataset is intended to facilitate the research community to study the cybersecurity of substations. We present the physical system of a typical distribution level substation and several of its critical electrical protection operation scenarios under different disturbances, followed by several cyber-attack scenarios. We have generated a dataset with multiple traces that correspond to these scenarios and demonstrated how the dataset can be used to support substation cybersecurity research.
{"title":"A Synthesized Dataset for Cybersecurity Study of IEC 61850 based Substation","authors":"P. Biswas, Heng Chuan Tan, Qingbo Zhu, Yuan Li, D. Mashima, Binbin Chen","doi":"10.1109/SmartGridComm.2019.8909783","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909783","url":null,"abstract":"Cyber attacks pose a major threat to smart grid infrastructures where communication links bind physical devices to provide critical measurement, protection, and control functionalities. Substation is an integral part of a power system. Modern substations with intelligent electronic devices and remote access interface are more prone to cyber attacks. Hence, there is an urgent need to consider cybersecurity at the electrical substation level. This paper makes a systematic effort to develop a synthesized dataset focusing on IEC 61850 GOOSE communication that is essential for automation and protection in smart grid. The dataset is intended to facilitate the research community to study the cybersecurity of substations. We present the physical system of a typical distribution level substation and several of its critical electrical protection operation scenarios under different disturbances, followed by several cyber-attack scenarios. We have generated a dataset with multiple traces that correspond to these scenarios and demonstrated how the dataset can be used to support substation cybersecurity research.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133036945","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 : 2019-10-01DOI: 10.1109/SmartGridComm.2019.8909705
Chenfeng Zhu, A. Reinhardt
More and more smart meters are being rolled out in domestic and commercial buildings as well as industrial sites worldwide. They enable the timely and fine-grained monitoring of electrical energy generation and consumption. Besides storing measured data locally, most smart meters are equipped with communication interfaces to transfer collected readings to metering service providers. This not only allows for accurate billing, but also enables the extraction of additional information from collected data, particularly when they have been sampled at a high temporal resolution. The communication link used to exchange meter data can, however, be prone to disruptions and transmission errors. Consequently, while consumption data used for billing purposes might only be removed from a smart meter’s internal buffer when they have been reported correctly, intermediate readings can be irrevocably lost during communication link outages. Because such readings are often useful for analytics purposes, their loss should be avoided. We hence propose a hybrid data transmission scheme that combines the real-time reporting of consumption readings with a background synchronization process that ensures the lossless exchange of data. We evaluate our design in a practical setting and demonstrate its efficacy in recovering data after the metering device has been physically disconnected from the network.
{"title":"Reliable Streaming and Synchronization of Smart Meter Data over Intermittent Data Connections","authors":"Chenfeng Zhu, A. Reinhardt","doi":"10.1109/SmartGridComm.2019.8909705","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909705","url":null,"abstract":"More and more smart meters are being rolled out in domestic and commercial buildings as well as industrial sites worldwide. They enable the timely and fine-grained monitoring of electrical energy generation and consumption. Besides storing measured data locally, most smart meters are equipped with communication interfaces to transfer collected readings to metering service providers. This not only allows for accurate billing, but also enables the extraction of additional information from collected data, particularly when they have been sampled at a high temporal resolution. The communication link used to exchange meter data can, however, be prone to disruptions and transmission errors. Consequently, while consumption data used for billing purposes might only be removed from a smart meter’s internal buffer when they have been reported correctly, intermediate readings can be irrevocably lost during communication link outages. Because such readings are often useful for analytics purposes, their loss should be avoided. We hence propose a hybrid data transmission scheme that combines the real-time reporting of consumption readings with a background synchronization process that ensures the lossless exchange of data. We evaluate our design in a practical setting and demonstrate its efficacy in recovering data after the metering device has been physically disconnected from the network.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114795367","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 : 2019-10-01DOI: 10.1109/SmartGridComm.2019.8909780
R. R. Kumar, D. Kundur, B. Sikdar
Centralized controllers are popularly used in Microgrid as it ensures its economic and stable operation. The measurements taken for such a controller are prone to false data injection (FDI) attacks which may result in destabilizing the microgrid. This paper presents a technique that uses transient information for detecting the FDI attacks in a microgrid. The detection technique works on the principle that any legitimate change in the system will be accompanied by a transient that can be observed by the measurement system. The transient solution is obtained using a backward forward sweep technique which is developed in this paper. This technique is much efficient than the Electromagnetic Transient Program (EMTP) as it solves the dynamic equations by exploiting the radial feature of the microgrid network. The solution is compared against the measured values such that in the event of an FDI attack, transients may not be present and hence it will have high deviations. The proposed technique is evaluated on a microgrid under the FDI attack and the results are presented.
{"title":"Transient Model-Based Detection Scheme for False Data Injection Attacks in Microgrids","authors":"R. R. Kumar, D. Kundur, B. Sikdar","doi":"10.1109/SmartGridComm.2019.8909780","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909780","url":null,"abstract":"Centralized controllers are popularly used in Microgrid as it ensures its economic and stable operation. The measurements taken for such a controller are prone to false data injection (FDI) attacks which may result in destabilizing the microgrid. This paper presents a technique that uses transient information for detecting the FDI attacks in a microgrid. The detection technique works on the principle that any legitimate change in the system will be accompanied by a transient that can be observed by the measurement system. The transient solution is obtained using a backward forward sweep technique which is developed in this paper. This technique is much efficient than the Electromagnetic Transient Program (EMTP) as it solves the dynamic equations by exploiting the radial feature of the microgrid network. The solution is compared against the measured values such that in the event of an FDI attack, transients may not be present and hence it will have high deviations. The proposed technique is evaluated on a microgrid under the FDI attack and the results are presented.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123763169","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 : 2019-10-01DOI: 10.1109/SmartGridComm.2019.8909718
Oluwafemi Kolade, Ling Cheng
The powerline channel is classified as harsh due to its original design which was not intended for communication. Permutation codes have shown to combine efficiently with ${M}$-ary frequency shift keying (MFSK) in order to mitigate the effects of impulse noise in the powerline channel. The use of orthogonal frequency division multiplexing with ${M}$-ary frequency shift keying (OFDM-MFSK) also allows non-coherent detection and is efficient in environments where estimation of the channel is challenging. This paper proposes an OFDM-MFSK based subcarrier coding in the frequency domain using permutation codes. This scheme aims at improving the bit error rate (BER) performance by mitigating against the effects of impulse noise in the powerline channel. Subcarrier detection using the soft information from the received subcarriers is also possible, thereby increasing the BER while reducing the complexity of the scheme for a large number of subcarriers.
{"title":"Impulse Noise Mitigation Using Subcarrier Coding of OFDM-MFSK Scheme in Powerline Channel","authors":"Oluwafemi Kolade, Ling Cheng","doi":"10.1109/SmartGridComm.2019.8909718","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909718","url":null,"abstract":"The powerline channel is classified as harsh due to its original design which was not intended for communication. Permutation codes have shown to combine efficiently with ${M}$-ary frequency shift keying (MFSK) in order to mitigate the effects of impulse noise in the powerline channel. The use of orthogonal frequency division multiplexing with ${M}$-ary frequency shift keying (OFDM-MFSK) also allows non-coherent detection and is efficient in environments where estimation of the channel is challenging. This paper proposes an OFDM-MFSK based subcarrier coding in the frequency domain using permutation codes. This scheme aims at improving the bit error rate (BER) performance by mitigating against the effects of impulse noise in the powerline channel. Subcarrier detection using the soft information from the received subcarriers is also possible, thereby increasing the BER while reducing the complexity of the scheme for a large number of subcarriers.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121925837","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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