Pub Date : 2019-10-01DOI: 10.1109/SmartGridComm.2019.8909807
Yan Tian, Zhaoming Lu, Chunlei Sun, Wenpeng Jing
Microgrids are small entities in the smart grid, which consisting of distributed energy resource, energy consumers, and energy storage systems, etc., and can connect to the main grid or work in off-grid mode. This paper focuses on the aggregations of microgrids to form energy communities, which is beneficial to the management and the locality-balance of energy. Considering the time-varying character of photovoltaic power, we propose a novel algorithm to aggregate microgrids using the predicted data of net energy instead of historical data. The proposed algorithm firstly clusters the microgrids with positive net energy into different communities, based on Kmeans method, and then add the remaining microgrids with negative net energy into one selected cluster one by one according to the information of both location and total net energy of the cluster. Moreover, two evaluation factors are proposed to validate the efficiency of the proposed aggregation algorithm. The experimental results demonstrate that the proposed aggregation algorithm can realize the energy balance of all communities as well as guarantee more communities with positive net energy and minimize the average distance of microgrids to the community center than SECs.
{"title":"Locality-balanced Energy Community Aggregations Considering Net Energy Predictions of Microgrids","authors":"Yan Tian, Zhaoming Lu, Chunlei Sun, Wenpeng Jing","doi":"10.1109/SmartGridComm.2019.8909807","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909807","url":null,"abstract":"Microgrids are small entities in the smart grid, which consisting of distributed energy resource, energy consumers, and energy storage systems, etc., and can connect to the main grid or work in off-grid mode. This paper focuses on the aggregations of microgrids to form energy communities, which is beneficial to the management and the locality-balance of energy. Considering the time-varying character of photovoltaic power, we propose a novel algorithm to aggregate microgrids using the predicted data of net energy instead of historical data. The proposed algorithm firstly clusters the microgrids with positive net energy into different communities, based on Kmeans method, and then add the remaining microgrids with negative net energy into one selected cluster one by one according to the information of both location and total net energy of the cluster. Moreover, two evaluation factors are proposed to validate the efficiency of the proposed aggregation algorithm. The experimental results demonstrate that the proposed aggregation algorithm can realize the energy balance of all communities as well as guarantee more communities with positive net energy and minimize the average distance of microgrids to the community center than SECs.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"13 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":"115364104","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.2019.8909811
Yueyu Deng, K. Zhu, Ran Wang, Yong Wan
Application of computing and communications intelligence has increase the openness and complexity of smart grid to a higher degree. However, this shift also makes smart grids more vulnerable to cyber-attacks. Recently, a new type of invisible attack called false data injection attack (FDIA) has been proposed, which can bypass the existing bad data detection and inject false data into the grid measurements. However, most existing work ignore the potential different purposes of FDIA attacks, and simply assuming the purpose as power theft. In this paper, we model two FDIA attacks based on different purposes, one for economic interests, another for destruction. In order to detect these two attacks, we propose a load forecasting based technique for real-time FDIA detection. Firstly, a support vector regression (SVR) is exploit to forecast the load. According to the predicted results and the system model of the power grid, the measurements of the entire smart grid can be calculate by power flow algorithm. Compared with forecasting measurements directly, the computation cost of this method is very small. Then we train a support vector machine (SVM) to detect the potential FDIA attacks based on deviation between the deduced measurements and the true value. Besides, the injection process is also considered in training phase, thus FDIA attacks can be captured in advance. The performance of our proposed detection mechanism is illustrated through the simulation by IEEE 57-bus test system.
{"title":"Real-time Detection of False Data Injection Attacks Based on Load Forecasting in Smart Grid","authors":"Yueyu Deng, K. Zhu, Ran Wang, Yong Wan","doi":"10.1109/SmartGridComm.2019.8909811","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909811","url":null,"abstract":"Application of computing and communications intelligence has increase the openness and complexity of smart grid to a higher degree. However, this shift also makes smart grids more vulnerable to cyber-attacks. Recently, a new type of invisible attack called false data injection attack (FDIA) has been proposed, which can bypass the existing bad data detection and inject false data into the grid measurements. However, most existing work ignore the potential different purposes of FDIA attacks, and simply assuming the purpose as power theft. In this paper, we model two FDIA attacks based on different purposes, one for economic interests, another for destruction. In order to detect these two attacks, we propose a load forecasting based technique for real-time FDIA detection. Firstly, a support vector regression (SVR) is exploit to forecast the load. According to the predicted results and the system model of the power grid, the measurements of the entire smart grid can be calculate by power flow algorithm. Compared with forecasting measurements directly, the computation cost of this method is very small. Then we train a support vector machine (SVM) to detect the potential FDIA attacks based on deviation between the deduced measurements and the true value. Besides, the injection process is also considered in training phase, thus FDIA attacks can be captured in advance. The performance of our proposed detection mechanism is illustrated through the simulation by IEEE 57-bus test system.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"35 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":"116555571","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.2019.8909757
Yonggang Li, W. Dong, Xiaoning Feng, Minghui Zhang
Under Smart Grid circumstance, the problem that the large grid system is difficult to schedule can be solved by the micro-grid. Meanwhile, the shortage of traditional energy makes the demand-supply gap enlarge and renewable energy will become the primary energy supply in the future. Therefore, the study on how to expand renewable energy in the co-generation system in micro-grid is of great significant and valuable. In this paper, the minimum total cost of the expansion plan and the improvement of micro-grid reliability are taken as the optimal goal. The expansion planning model of the wind-thermal co-generation system is established, which uses the Harmony Search (HS) and the Genetic Algorithm (GA) to simulate a micro-grid with five nodes in a decade respectively. The comparison results of the simulation results show that the expansion planning model of the co-generation system with the HS method is more feasible and effective than that with GA. Through the research on the expansion planning of wind-thermal co-generation system, it can provide the decision support and reference for the long-term expansion planning of co-generation system in micro-grid under the Smart Grid.
{"title":"The Expansion Planning of Wind-Thermal Co-generation System Based on Harmony Search Algorithm under Smart Grid","authors":"Yonggang Li, W. Dong, Xiaoning Feng, Minghui Zhang","doi":"10.1109/SmartGridComm.2019.8909757","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909757","url":null,"abstract":"Under Smart Grid circumstance, the problem that the large grid system is difficult to schedule can be solved by the micro-grid. Meanwhile, the shortage of traditional energy makes the demand-supply gap enlarge and renewable energy will become the primary energy supply in the future. Therefore, the study on how to expand renewable energy in the co-generation system in micro-grid is of great significant and valuable. In this paper, the minimum total cost of the expansion plan and the improvement of micro-grid reliability are taken as the optimal goal. The expansion planning model of the wind-thermal co-generation system is established, which uses the Harmony Search (HS) and the Genetic Algorithm (GA) to simulate a micro-grid with five nodes in a decade respectively. The comparison results of the simulation results show that the expansion planning model of the co-generation system with the HS method is more feasible and effective than that with GA. Through the research on the expansion planning of wind-thermal co-generation system, it can provide the decision support and reference for the long-term expansion planning of co-generation system in micro-grid under the Smart Grid.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"125 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":"121965163","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.2019.8909803
Hailong Zhang, Xuan Liu, Ran Li, Ke Zheng
IEEE 1901.1 Standard for Medium Frequency (less than 15 MHz) Power Line Communications for Smart Grid Applications jointly formulated by China Electric Power Research Institute and State Grid Information & Telecom Technology Group was officially released and implemented recently. This standard will promote the rapid development of power line communication (PLC) chip, communication module and intelligent terminal industry. Under this background, in order to accurately quantify the impact of large-scale deployment of PLC systems on various short-wave services and provide support for subsequent decision-making, it is necessary to design a scientific and reasonable electromagnetic (EM) emission test scheme for low-voltage power line broadband carrier communication systems (LVPLBCCS). This test scheme actively draws lessons from the EM emission measurement standards of international PLC systems, and combines with the practical application of China’s PLC systems, develops a test method that meets the practical application scenarios of China. Including conducted disturbance test and radiated disturbance test, the proposed test method was carried out in laboratory conduction project, laboratory radiation project and actual field radiation project, which effectively ensures the reliability, accuracy, practicability and integrity of the test method.
{"title":"Test Methods for EM Emission for Broadband Carrier Communication Systems over Low-voltage Power Lines","authors":"Hailong Zhang, Xuan Liu, Ran Li, Ke Zheng","doi":"10.1109/SmartGridComm.2019.8909803","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909803","url":null,"abstract":"IEEE 1901.1 Standard for Medium Frequency (less than 15 MHz) Power Line Communications for Smart Grid Applications jointly formulated by China Electric Power Research Institute and State Grid Information & Telecom Technology Group was officially released and implemented recently. This standard will promote the rapid development of power line communication (PLC) chip, communication module and intelligent terminal industry. Under this background, in order to accurately quantify the impact of large-scale deployment of PLC systems on various short-wave services and provide support for subsequent decision-making, it is necessary to design a scientific and reasonable electromagnetic (EM) emission test scheme for low-voltage power line broadband carrier communication systems (LVPLBCCS). This test scheme actively draws lessons from the EM emission measurement standards of international PLC systems, and combines with the practical application of China’s PLC systems, develops a test method that meets the practical application scenarios of China. Including conducted disturbance test and radiated disturbance test, the proposed test method was carried out in laboratory conduction project, laboratory radiation project and actual field radiation project, which effectively ensures the reliability, accuracy, practicability and integrity of the test method.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"106 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":"124588505","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.2019.8909709
Arezoo Rajabi, R. Bobba
Wide-area oscillation monitoring and control in power systems is essential for preventing large-scale outages. To detect and estimate oscillation modes in real-time distributed measurement-based mode estimation approaches have been proposed. Unfortunately, these methods are vulnerable to false data injection attacks. In this paper we propose a hierarchical k-means false data detection approach to detect and remove false data from distributed Prony algorithms for oscillation mode estimation. Our proposed method is able to detect both multi-goal adversaries and noisy outliers equally well. We empirically illustrate the resiliency of our method against different attacks and show that it can detect corrupted data and accurately estimate oscillation modes.
{"title":"False Data Detection in Distributed Oscillation Mode Estimation using Hierarchical k-means","authors":"Arezoo Rajabi, R. Bobba","doi":"10.1109/SmartGridComm.2019.8909709","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909709","url":null,"abstract":"Wide-area oscillation monitoring and control in power systems is essential for preventing large-scale outages. To detect and estimate oscillation modes in real-time distributed measurement-based mode estimation approaches have been proposed. Unfortunately, these methods are vulnerable to false data injection attacks. In this paper we propose a hierarchical k-means false data detection approach to detect and remove false data from distributed Prony algorithms for oscillation mode estimation. Our proposed method is able to detect both multi-goal adversaries and noisy outliers equally well. We empirically illustrate the resiliency of our method against different attacks and show that it can detect corrupted data and accurately estimate oscillation modes.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"61 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":"123476971","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.2019.8909808
P. Gupta, Pekka T. Savolainen, Markus Duchon
Due to the advancements in the smart grid technologies, smart mechanisms are required within the Energy Management System (EMS) environments for microgrids. One of the functionalities of EMS is to ensure grid stability. In order to test and validate new mechanisms, appropriate simulation tools exist. Most of the existing validation strategies include modeling the target system in simulation environment and then deploying the mechanism in the real environment. When the validated mechanisms are implemented in real environment, they often do not work as intended and require modification due to the implementation difference within the EMS controller. An EMS should be able to communicate with the simulated model, inject faults in the simulated model and able to perform various control actions. In this paper, we propose a software-in-loop approach, where the grid stability mechanisms are implemented in the EMS, which is deployed in the real environment. EMS must operate exactly the way it does in the simulation environment. For such a capability, the simulation platform should be able to communicate with the EMS. In this work, we consider a 13-node radial distribution grid with one solar panel as a generation unit. The 13-node distribution grid has been modeled using Apros simulation software. SMG2.0, a software application for microgrid is used to monitor, inject electrical faults and trigger recovery mechanisms in the Apros model. A communication architecture called ICT gateway has been developed between Apros and the EMS (SMG2.0). Two fault scenarios (line-breakage and under-voltage) are considered as the fault injection scenarios to evaluate the performance of the communication architecture. When the SMG2.0 detects a line fault, it triggers network reconfiguration as the recovery strategy for the line-breakage scenario in the simulation environment. This approach not only helps in designing fault handling strategies in the electrical network but also helps in designing an effective software application targeted to control the physical entities.
{"title":"ICT gateway to simulation environment for electrical fault injection and recovery","authors":"P. Gupta, Pekka T. Savolainen, Markus Duchon","doi":"10.1109/SmartGridComm.2019.8909808","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909808","url":null,"abstract":"Due to the advancements in the smart grid technologies, smart mechanisms are required within the Energy Management System (EMS) environments for microgrids. One of the functionalities of EMS is to ensure grid stability. In order to test and validate new mechanisms, appropriate simulation tools exist. Most of the existing validation strategies include modeling the target system in simulation environment and then deploying the mechanism in the real environment. When the validated mechanisms are implemented in real environment, they often do not work as intended and require modification due to the implementation difference within the EMS controller. An EMS should be able to communicate with the simulated model, inject faults in the simulated model and able to perform various control actions. In this paper, we propose a software-in-loop approach, where the grid stability mechanisms are implemented in the EMS, which is deployed in the real environment. EMS must operate exactly the way it does in the simulation environment. For such a capability, the simulation platform should be able to communicate with the EMS. In this work, we consider a 13-node radial distribution grid with one solar panel as a generation unit. The 13-node distribution grid has been modeled using Apros simulation software. SMG2.0, a software application for microgrid is used to monitor, inject electrical faults and trigger recovery mechanisms in the Apros model. A communication architecture called ICT gateway has been developed between Apros and the EMS (SMG2.0). Two fault scenarios (line-breakage and under-voltage) are considered as the fault injection scenarios to evaluate the performance of the communication architecture. When the SMG2.0 detects a line fault, it triggers network reconfiguration as the recovery strategy for the line-breakage scenario in the simulation environment. This approach not only helps in designing fault handling strategies in the electrical network but also helps in designing an effective software application targeted to control the physical entities.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"4 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":"116495541","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.2019.8909701
Sungmoon Kwon, Hyunguk Yoo, Taeshik Shon
As more sophisticated cyberattacks against industrial control systems (ICSs) such as crashoverride and TRITON occur frequently, the security of ICS is becoming more and more emphasized. Currently, many security researches have been conducted on ICSs, but most studies focus on messages at the application layer containing data, and the transport layer for data transmission is not considered. However, problems at the transport layer can interfere with normal data acquisition and cause problems in availability which is a key characteristic of the control system. In addition, attacks that exploit this point do not require detailed knowledge of the control system, which may result in fatal results with a lower level of difficulty than other attacks, so security of the transport layer should also be considered as an important factor. Therefore, in this paper, we 1)analyze the transport layer attack that interferes with data acquisition and the protocols that attacks are effective by analyzing from an attacker’s perspective, 2) analyzed transport layer attacks in the DNP3 protocol widely used in ICSs, 3) in order to detect this, propose a many to one bidirectional recurrent neural network (RNN) based detection technique considering the characteristics of ICS, and 4) describe the verification of the proposed model through an actual substation’s DNP3 packet.
{"title":"RNN-based Anomaly Detection in DNP3 Transport Layer","authors":"Sungmoon Kwon, Hyunguk Yoo, Taeshik Shon","doi":"10.1109/SmartGridComm.2019.8909701","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909701","url":null,"abstract":"As more sophisticated cyberattacks against industrial control systems (ICSs) such as crashoverride and TRITON occur frequently, the security of ICS is becoming more and more emphasized. Currently, many security researches have been conducted on ICSs, but most studies focus on messages at the application layer containing data, and the transport layer for data transmission is not considered. However, problems at the transport layer can interfere with normal data acquisition and cause problems in availability which is a key characteristic of the control system. In addition, attacks that exploit this point do not require detailed knowledge of the control system, which may result in fatal results with a lower level of difficulty than other attacks, so security of the transport layer should also be considered as an important factor. Therefore, in this paper, we 1)analyze the transport layer attack that interferes with data acquisition and the protocols that attacks are effective by analyzing from an attacker’s perspective, 2) analyzed transport layer attacks in the DNP3 protocol widely used in ICSs, 3) in order to detect this, propose a many to one bidirectional recurrent neural network (RNN) based detection technique considering the characteristics of ICS, and 4) describe the verification of the proposed model through an actual substation’s DNP3 packet.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"108 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":"124136997","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.2019.8909752
Kursat Rasim Mestav, L. Tong
The problem of distribution system state estimation using smart meters and limited SCADA (Supervisory Control and Data Acquisition) measurement units is considered. To overcome the lack of measurements, a Bayesian state estimator using deep learning is proposed. The proposed method consists of two steps. First, a deep generative adversary network is trained to learn the distribution of net power injections at the loads. Then, a deep regression network is trained using the samples generated from the generative network to obtain minimum mean-squared error (MMSE) estimate of the system state. Our simulation results show the accuracy and the online computation cost of the proposed method are superior to the conventional methods.
研究了利用智能电表和有限的SCADA (Supervisory Control and Data Acquisition)测量单元进行配电系统状态估计的问题。为了克服测量不足的问题，提出了一种基于深度学习的贝叶斯状态估计器。该方法分为两个步骤。首先，训练一个深度生成对手网络来学习负载下净功率注入的分布。然后，利用生成网络生成的样本对深度回归网络进行训练，得到系统状态的最小均方误差(MMSE)估计。仿真结果表明，该方法的精度和在线计算量均优于传统方法。
{"title":"State Estimation in Smart Distribution Systems with Deep Generative Adversary Networks","authors":"Kursat Rasim Mestav, L. Tong","doi":"10.1109/SmartGridComm.2019.8909752","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909752","url":null,"abstract":"The problem of distribution system state estimation using smart meters and limited SCADA (Supervisory Control and Data Acquisition) measurement units is considered. To overcome the lack of measurements, a Bayesian state estimator using deep learning is proposed. The proposed method consists of two steps. First, a deep generative adversary network is trained to learn the distribution of net power injections at the loads. Then, a deep regression network is trained using the samples generated from the generative network to obtain minimum mean-squared error (MMSE) estimate of the system state. Our simulation results show the accuracy and the online computation cost of the proposed method are superior to the conventional methods.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"451 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":"115867658","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.2019.8909805
Moosa Moghimi Haji, Omid Ardakanian
Distribution state estimation is crucial for planning and operation of active distribution networks. This paper extends two state-of-the-art state estimation techniques, namely Weighted Least Squares (WLS) and Ensemble Kalman Filter (EnKF), to unbalanced three-phase distribution networks. These networks are assumed to be equipped with smart meters and distribution- level phasor measurement units (D-PMUs), which are capable of measuring voltage and current phasors. We evaluate the two state estimation methods through extensive simulations in realistic settings where the secondary (low voltage) distribution system is accurately modelled, D-PMUs are installed only at a small number of buses in the primary system, and their measurements are noisy and become available for state estimation after a certain delay. Our results indicate that both methods achieve a sufficiently low error despite the small number of installed D-PMUs, and while EnKF outperforms WLS in some scenarios, the difference between the results gets smaller with more accurate D-PMU measurements. When both voltage and current phasor measurements are available, WLS yields more accurate results under realistic assumptions and is therefore more suitable for real-world applications.
{"title":"Practical Considerations in the Design of Distribution State Estimation Techniques","authors":"Moosa Moghimi Haji, Omid Ardakanian","doi":"10.1109/SmartGridComm.2019.8909805","DOIUrl":"https://doi.org/10.1109/SmartGridComm.2019.8909805","url":null,"abstract":"Distribution state estimation is crucial for planning and operation of active distribution networks. This paper extends two state-of-the-art state estimation techniques, namely Weighted Least Squares (WLS) and Ensemble Kalman Filter (EnKF), to unbalanced three-phase distribution networks. These networks are assumed to be equipped with smart meters and distribution- level phasor measurement units (D-PMUs), which are capable of measuring voltage and current phasors. We evaluate the two state estimation methods through extensive simulations in realistic settings where the secondary (low voltage) distribution system is accurately modelled, D-PMUs are installed only at a small number of buses in the primary system, and their measurements are noisy and become available for state estimation after a certain delay. Our results indicate that both methods achieve a sufficiently low error despite the small number of installed D-PMUs, and while EnKF outperforms WLS in some scenarios, the difference between the results gets smaller with more accurate D-PMU measurements. When both voltage and current phasor measurements are available, WLS yields more accurate results under realistic assumptions and is therefore more suitable for real-world applications.","PeriodicalId":377150,"journal":{"name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"37 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":"130116545","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.2019.8909772
Hongseok Kim, Joo-Hang Lee, S. Bahrami, V. Wong
Recent advancement of distributed renewable generation has motivated microgrids to trade energy directly with one another, as well as with the utility, in order to minimize their operational costs. Energy trading among microgrids, however, confronts challenges such as reaching a fair trading price, maximizing participants’ profit, and satisfying power network constraints. In this paper, we formulate the direct energy trading among multiple microgrids as a generalized Nash bargaining (GNB) problem that involves the distribution network’s operational constraints (e.g., power balance equations, voltage limits). We prove that solving the GNB problem maximizes the social welfare and also distributes the revenue among the microgrids based on their market power. To address the nonconvexity of the GNB problem, we propose a two-phase approach. The first phase involves solving the optimal power flow problem in a distributed fashion using the alternative direction method of multipliers to determine the amount of energy trading. The second phase determines the market clearing price and mutual payments of the microgrids. Simulation results on an IEEE 33-bus system with four microgrids show that the proposed framework substantially reduces total network cost by 37.2%. Our results suggest direct trading need to be enforced by the regulators in order to maximize the social welfare.
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