17 research outputs found

    Islanding detection during intended island operation of nested microgrid

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    In the future, functionalities like islanding detection must also operate during intended island operation of (MV+MV or MV+LV) nested microgrids. In this paper, healthy and faulty islanding detection of LV network connected generation unit during nested (MV+LV) microgrid islanded operation were studied by simulations with PSCAD model from real-life smart grid pilot. Main focus in the simulations was on the study and comparison of usage possibilities of combined (high-speed communication based transfer trip & fault detection/direction + voltage vector shift) and multi-criteria (voltage total harmonic distortion & voltage unbalance) based islanding detection schemes also during intended island operation of nested microgrid consisting only from inverter based generation units.fi=vertaisarvioitu|en=peerReviewed

    Multi-objective active network management scheme studied in Sundom smart grid with MV and LV network connected DER units

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    Use of controllable, flexible, distributed energy resources (DER) in MV and LV networks will be in key role in order to improve local and system-wide grid resiliency and maximize utilization of renewable energy sources (RES). These resources will provide different technical services as part of future active network management (ANM) schemes. Therefore, future ANM and protection methods and solutions have to be adapted and developed so that active control and utilization of DER during both grid-connected and islanded operation modes is enabled. In this paper, multi-objective ANM scheme is studied by PSCAD simulations during grid-connected operation of Sundom Smart Grid. Based on the simulation results conclusions are stated, for example, related to preventing unwanted MV and LV network reactive power / voltage control interactions and potential mutual effects between voltage (U) and frequency (f) control functions (QU-, PU- and Pf -control) of DER units which are actively participating on studied multi-objective ANM scheme.fi=vertaisarvioitu|en=peerReviewed

    Intermittent earth fault passage indication in compensated distribution networks

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    An intermittent or restriking earth fault is a special type of earth fault that is common mostly in compensated cable networks. A great deal of effort has gone into protection against this type of fault. However, locating this fault has not received much attention. Therefore, there is a need to have a reliable method for locating this fault to repair the damaged cable. In this paper, the principles of a new method developed for locating transient intermittent earth faults on distribution networks are presented. The proposed method employs negative and zero sequence currents, and no voltage measurement is required, which means the proposed method has the potential to reduce cost when implemented in practice. It is intended mainly for typical intermittent earth faults in cable distribution networks where the typical fault resistance is in the range of a few ohms. Real data obtained from practical field tests is used to explain the phenomenon. A series of disturbance recordings obtained from field tests validate the proposed method.©2021 Elsevier. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.fi=vertaisarvioitu|en=peerReviewed

    Advanced islanding detection in grid interactive microgrids

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    In the future active network management and protectionsolutions have to enable utilization of intended islandoperation as well as active control and utilizationflexibilities during normal and islanded operation ofgrid interactive microgrids. In this paper, combinedislanding detection schemes for both MV and LVnetwork connected distributed generation units duringnormal grid-connected operation are studied.Utilization of active network management functionalityat MV level enables to control the reactive powerunbalance continuously in order to ensure reliableislanding detection without non-detection zone.Combined scheme also prevents maloperations due toother disturbances.fi=vertaisarvioitu|en=peerReviewed

    Advanced utilization of big data for real-time monitoring and data analytics in Sundom smart grid

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    Modern technologies are increasingly used in many protection, control and monitoring solutions for power distribution grids. Voltage and current measurements are nowadays usually converted to digital signals, which are further processed and stored in different locations depending on the application. At the same time, when data processing and storing capacity is increasing, the number of new data sources also increases. This means that the data transfer capacity may also need to be increased at different levels in future distribution network management and protection architectures. This paper presents how IEC 61850-9-2 standard based raw data streamed from the Sundom Smart Grid can be processed and utilized for power quality monitoring and analytics applications. Digitalization also enables several other parallel applications since the same data stream can be used for several targets when the connectivity, interoperability and data quality are sufficient. In this paper some of these potential parallel applications are also introduced.fi=vertaisarvioitu|en=peerReviewed

    Combined Islanding Detection Scheme Utilizing Active Network Management for Future Resilient Distribution Networks

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    Needed new cost-efficient, reliable, standardised and redundant solutions for future resilient smart grids must utilise possibilities of advanced ICT technologies (such as wireless fifth generation and cloud servers with smart big data analytics) and have cyber-security integrated into all solutions. In this study, resilient, future-proof, grid-code compatible combined islanding detection scheme for medium-voltage (MV) and low-voltage network connected distributed generation units during grid-connected operation is simulated. The utilisation of active network management functionality at the MV level enables to control the reactive power unbalance continuously in order to ensure reliable islanding detection without a non-detection zone. The combined scheme also prevents maloperations due to other disturbances.fi=vertaisarvioitu|en=peerReviewed

    Utilization of a mixture of CTs and current sensors in line differential protection applications

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    The popularity of Rogowski sensors is increasing due to their advantages over conventional CTs. Consequently, network utilities may sometimes end up facing a question whether it would be possible to use line differential protection on a line where the current measurements at the local end are based on CTs, whereas, the remote end measurements are based on current sensors. The main challenge in the use of such a combination in line differential protection applications is that while CTs may saturate, Rogowski sensors do not. Such issues were studied in a hardware-in-the-loop simulation setup. Based on the studies conducted, it appears that the use of mixture of CTs and current sensors for line differential protection applications is a feasible option provided that the CTs are properly dimensioned and that the protection settings are carefully chosen.fi=vertaisarvioitu|en=peerReviewed

    Distribution Network Fault Prediction Utilising Protection Relay Disturbance Recordings And Machine Learning

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    As society becomes increasingly reliant on electricity, the reliability requirements for electricity supply continue to rise. In response, transmission/distribution system operators (T/DSOs) must improve their networks and operational practices to reduce the number of interruptions and enhance their fault localization, isolation, and supply restoration processes to minimize fault duration. This paper proposes a machine learning based fault prediction method that aims to predict incipient faults, allowing T/DSOs to take action before the fault occurs and prevent customer outages

    Active and reactive power requirements at DSO-TSO interface : a cases study based on four European countries

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    The ENTSO-E network code for demand connection sets harmonized requirements for connecting large renewable energy generation units as well as demand response facilities and furthermore reactive power limits which need to be fulfilled at the interface between TSO and DSOs. In this paper, P/Q-measurements for several primary substations in four different countries (Austria, Finland, Germany and Slovenia) are investigated. For the investigated primary substations measurements of active and reactive power over a period of one year in 15-min resolutions were collected. Based on the investigations the impact of reactive power requirements at the TSO-DSO interface is addressed. Moreover, how and on which voltage level the reactive power could be balanced is discussed.fi=vertaisarvioitu|en=peerReviewed

    FUSE – using artificial intelligence in the energy grid of tomorrow

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    The objective of Future Smart Energy (FUSE), a Finnish-German research and development project, is to develop methods based on artificial intelligence (AI) that will help to increase the resilience of future energy distribution grids. The use cases that are investigated include both condition monitoring/predictive maintenance, and distributed demand-side management in medium-voltage and low-voltage grids. The FUSE concept foresees a hierarchical infrastructure of sensing- and data processing nodes that use AI to transform raw data into information on asset and grid status and performance. FUSE supports the upward flow of data and aggregation of information into high-level visualisations for grid operators, as well as the downward flow of soft control signals that trigger the distributed self-control of assets. This study outlines the FUSE concept and presents the first results.This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)fi=vertaisarvioitu|en=peerReviewed
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