62 research outputs found

    Optimal phasor data concentrator installation for traffic reduction in smart grid wide-area monitoring systems

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    Conference Theme: the Power of Global CommunicationsSymposium on Selected Areas in CommunicationsAs one of the core components in wide-area monitoring systems (WAMS), phasor measurement units (PMUs) acquire highly accurate and time-synchronized phasor data at high frequency for smart grid monitoring, protection, and control. Despite the advantages of PMUs, they do generate much data and create a heavy burden on the communication network. One way of alleviating such burden is to install phasor data concentrators (PDC) across the power system to concentrate data generated by the PMUs. Although PDCs are expensive as well, this may still be a much cheaper and more practical option than building a high bandwidth network for WAMS. Therefore, it is very important to solve the optimal PDC installation problem so as to achieve a desired level of traffic reduction. This paper is the first to address this problem and we give solutions for the IEEE 14-bus, 30-bus, and 57-bus systems.published_or_final_versio

    Software Defined Networks based Smart Grid Communication: A Comprehensive Survey

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    The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. This article serves as a comprehensive survey on SDN-based SGC. In this article, we first discuss taxonomy of advantages of SDNbased SGC.We then discuss SDN-based SGC architectures, along with case studies. Our article provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.Comment: Accepte

    A survey on smart grid communication system

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    Low-cost implementation and characterization of an active phasor data concentrator

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    The main components of an advanced measurement system based on synchrophasor technology for the monitoring of power systems are the phasor measurement unit (PMU), which represents the ‘sensor’, and the phasor data concentrator (PDC), which collects the data forwarded by PMUs installed on the field. For the purpose of extending the benefit of synchrophasor technology from transmission grids to distribution networks, different projects are seeking to use low-cost platforms to design devices with PMU functionalities. In this perspective, in order to achieve a complete synchrophasor-based measurement architecture based on low-cost technologies, this work presents a PDC design based on a low-cost platform. Despite the simplicity of the considered hardware, advanced PDC functionalities and innovative control logics are implemented in the prototype. The proposed device is characterised by several experimental tests aimed at assessing its performance in terms of both time synchronisation and capability of managing several PMU data streams. The feasibility of some additional functionalities and control logics is evaluated in the context of different possible scenarios

    Advanced Wide-Area Monitoring System Design, Implementation, and Application

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    Wide-area monitoring systems (WAMSs) provide an unprecedented way to collect, store and analyze ultra-high-resolution synchrophasor measurements to improve the dynamic observability in power grids. This dissertation focuses on designing and implementing a wide-area monitoring system and a series of applications to assist grid operators with various functionalities. The contributions of this dissertation are below: First, a synchrophasor data collection system is developed to collect, store, and forward GPS-synchronized, high-resolution, rich-type, and massive-volume synchrophasor data. a distributed data storage system is developed to store the synchrophasor data. A memory-based cache system is discussed to improve the efficiency of real-time situation awareness. In addition, a synchronization system is developed to synchronize the configurations among the cloud nodes. Reliability and Fault-Tolerance of the developed system are discussed. Second, a novel lossy synchrophasor data compression approach is proposed. This section first introduces the synchrophasor data compression problem, then proposes a methodology for lossy data compression, and finally presents the evaluation results. The feasibility of the proposed approach is discussed. Third, a novel intelligent system, SynchroService, is developed to provide critical functionalities for a synchrophasor system. Functionalities including data query, event query, device management, and system authentication are discussed. Finally, the resiliency and the security of the developed system are evaluated. Fourth, a series of synchrophasor-based applications are developed to utilize the high-resolution synchrophasor data to assist power system engineers to monitor the performance of the grid as well as investigate the root cause of large power system disturbances. Lastly, a deep learning-based event detection and verification system is developed to provide accurate event detection functionality. This section introduces the data preprocessing, model design, and performance evaluation. Lastly, the implementation of the developed system is discussed

    Architecture and Experimental Validation of a Low-Latency Phasor Data Concentrator

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    The paper presents the design principles of a Phasor Data Concentrator (PDC) that implements both the absolute and relative time data pushing logics together with a third one that aims at minimizing the latency introduced by the PDC without increasing the data incompleteness, as suggested in the IEEE Guide C37.244-2013. The performance of the aforementioned logics are assessed and compared in terms of reliability, determinism and reduction of the overall latency in two real Phasor Measurement Unit (PMU) installations adopting different telecom infrastructures. The first one is based on optical fiber links that transmit synchrophasor data measured by 15 PMUs installed in the sub-transmission network of the city of Lausanne, Switzerland. The second one adopts a 4G LTE wireless infrastructure to support the data streaming of 10 PMUs installed in a distribution network supplying the city of Huissen, in the Netherlands. The experimental results show that the proposed logic is characterized by the lowest latency, whereas the absolute time logic better mitigates the synchrophasor data latency variations

    A Review of Rule Learning Based Intrusion Detection Systems and Their Prospects in Smart Grids

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    PMU-based estimation of voltage-to-power sensitivity for distribution networks considering the sparsity of Jacobian matrix

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    With increasing integration of various distributed energy resources, electric distribution networks are changing to an energy exchange platform. Accurate voltage-to-power sensitivities play a vital role in system operation and control. Relative to the off-line method, measurement-based sensitivity estimation avoids the errors caused by incorrect device parameters and changes in network topology. An online estimation of the voltage-to-power sensitivity based on phasor measurement units is proposed. The sparsity of the Jacobian matrix is fully used by reformulating the original least-squares estimation problem as a sparse-recovery problem via compressive sensing. To accommodate the deficiency of the existing greedy algorithm caused by the correlation of the sensing matrix, a modified sparse-recovery algorithm is proposed based on the mutual coherence of the phase angle and voltage magnitude variation vectors. The proposed method can ensure the accuracy of estimation with fewer measurements and can improve the computational efficiency. Case studies on the IEEE 33-node test feeder verify the correctness and effectiveness of the proposed method
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