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Abstract: V magistrskem delu so podane ugotovitve preizkušanj distančne zaščite v preprostem omrežju, sestavljenem iz dveh daljnovodov in treh tujih omrežij. Uporabljena sta dva numerična zaščitna releja Siemens 7SD5, ustrezni ojačevalniki, digitalni simulator NovaCor in programsko okolje RSCAD FX. Vsi preizkusi so bili izvedeni v realnem času in v zaprti zanki za dva nabora nastavitev obeh zaščitnih relejev. Ugotovljeno je bilo, da bremensko področje za karakteristike pri enofaznih okvarah ni potrebno, s čimer se izboljša občutljivost zaščite pri enofaznih okvarah. Rezultati preizkušanja so pokazali, da lahko dodatno izboljšamo občutljivost zaščite tudi s povečanjem dosega tretje in četrte zaščitne cone. Poleg tega smo s preizkusi potrdili teoretična dognanja, da vmesno napajanje pri okvarah na sosednjem vodu poveča pogrešek izmerjene impedance, pri bolj oddaljenih okvarah pa se zaščita niti ne vzbudi. Rezultati potrjujejo, da je z ustreznim pristopom mogoče zmanjšati tveganje za napačno zaznavo okvare ali neželeno delovanje zaščite, kar prispeva k večji stabilnosti in zanesljivosti elektroenergetskega sistema.
Keywords: distančna zaščita, rezervne zaščitne cone, digitalni simulator v realnem času, preizkušanje opreme v zaprti zanki.
Published in DKUM: 22.10.2025; Views: 0; Downloads: 7
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Abstract: Ground fault relays (GFRs) in resonant-grounded medium voltage distribution networks shall not operate during phase-to-ground (Ph-G) fault inception, allowing the Petersen coil to suppress self-extinguishing faults, but the designated GFR must operate during permanent faults. In order to enhance the performance of GFRs, particularly during high-impedance faults, the scope of this paper is to propose a straightforward, machine-learning-based protection framework. The enhanced GFR is modeled as a classification task. Depending on the GFR’s position and the Ph-G fault location in the network, fault samples are labeled as “no operation,” “primary,” “backup,” or “backup of backup,” forming two-class, three-class, and four-class GFR setups, respectively. This assures selective operation across three protection zones and improves the reliability of all GFRs. The proposed protection scheme employs backward optimal feature selection to identify the most relevant discrete features obtained from measured zero-sequence current and voltage waveforms. An ensemble of k-nearest neighbor classifiers is utilized for accurate classification, simulating the GFR operating conditions, with measurement errors and sensitivity incorporated in the preprocessing. A 20 kV case study network validates the proposed framework, achieving F1-scores exceeding 96 %. The maximum operation delay of the protection scheme for an enhanced GFR is 225 ms, accommodating the required time window (200 ms), prediction time (5 ms), and change detection time (20 ms), thus assuring safe operation. Compared to other machine-learning-based methods used for Ph-G fault protection in resonant-grounded radial networks, this framework is high-performing, fast, and easy to implement, utilizing a simpler structure than neural networks.
Keywords: resonant grounded networks, ground-fault relay, high-impedance faults, ensemble-based learning, optimal feature selection
Published in DKUM: 25.07.2025; Views: 0; Downloads: 4
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Abstract: This paper analyzes the influence of inverter-interfaced distributed generations’ (IIDGs) response during transmission network faults. The simplest and safest solution is to switch IIDGs off during network faults without impacting the network voltages. A more elaborate and efficient concept, required by national grid codes, is based on controlling the IIDGs’ currents, involving positive- and negative-sequence voltage measured at the connection point. In this way the magnitude and phase of the injected currents can be adjusted, although the generated power will depend on the actual line voltages at the connection point. Therefore, an improved concept is proposed to adjust IIDGs’ fault current injection through the required active and reactive power, employing the same voltage characteristics. The proposed, i.e., power-based concept, is more definite than the currentbased one, since the required power will always be generated. The discussed concepts for the fault current injection by IIDGs were tested in different 110-kV networks with loop and radial topologies, and for different short-circuit capabilities of the aggregated network supply. Based on extensive numerical calculations, the power-based concept during transmission networks faults generates more reactive power compared to the current-based concept. However, the voltage support by IIDGs during transmission networks faults, regardless of the concept being used, is influenced mainly by the short-circuit capability of the aggregated network supply. As regards distance protection operation, it is influenced additionally by the network topology, i.e., in radial network topology, the remote relay’s operation can be delayed due to a largely seen impedance.
Keywords: distributed generation, fault current injection, voltage support, distance protection, transmission network faults
Published in DKUM: 16.06.2025; Views: 0; Downloads: 8
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Abstract: New energy sources, storage facilities, power electronics devices, advanced and complex control concepts, economic operating doctrines, and cost-optimized construction and production of machines and equipment in power systems adversely affect small-signal stability associated with local oscillations. The objective of the article is to analyze local oscillations and the causes that affect them in order to reduce their negative impact. There are no recognized analyses of the oscillations of modern operating synchronous generators exposed to new conditions in power systems. The basic idea is to perform a numerical analysis of local oscillations of a large number of synchronous generators in the power system. The paper represents the local mode data obtained from a systematic analysis of synchronous generators in the Slovenian power system. Analyzed were 74 synchronous generators of the Slovenian power system, plus many additional synchronous generators for which data were accessible in references. The mathematical models convenient for the study of local oscillations are described first in the paper. Next, the influences of transmission lines, size of the synchronous generators, operating conditions, and control systems were investigated. The paper’s merit is the applicable rules that have been defined to help power plant operators avoid stability-problematic situations. Consequently, boundaries were estimated of the eigenvalues of local modes. Finally, experiments were performed with a laboratory-size synchronous generator to assess the regularity of the numerically obtained conclusions. The obtained results enable the prediction of local oscillations’ frequencies and dampings and will be useful in PSS planning.
Keywords: power system, synchronous generators, oscillations, local modes, eigenvalue analysis
Published in DKUM: 27.03.2025; Views: 0; Downloads: 15
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Abstract: This paper addresses the lack of consideration of short time scales, below one hour, such as sub-15-min and sub1-hr, in grid codes for frequency quality analysis. These time scales are becoming increasingly important due to the flexible market-based operation of power systems as well as the rising penetration of renewable energy sources and battery energy storage systems. For this, firstly, a set of frequency-quality indices is considered, complementing established statistical indices commonly used in power-quality standards. These indices provide valuable insights for quantifying variations, events, fluctuations, and outliers specific to the discussed time scales. Among all the implemented indices, the proposed indices are based on over/under frequency events (6 indices), fast frequency rise/drop events (6 indices), and summation of positive and negative peaks (1 index), of which the 5 with the lowest thresholds are identified as the most dominant. Secondly, k-means and k-medoids clustering methods in a learning scheme are employed to identify typical patterns within the discussed time windows, in which the number of clusters is determined based on prior knowledge linked to reality. In order to clarify the frequency variations and patterns, three frequency case studies are analyzed: case 1 (sub-15-min scale, 10-s values, 6 months), case 2 (sub-1-hr scale, 10-s values, 6 months), and case 3 (sub-1-hr, 3-min values, the year 2021). Results obtained from the indices and learning methods demonstrate a full picture of the information within the windows. The maximum value of the highest frequency value minus the lowest one over the windows is about 0.35 Hz for cases 1 and 2 and 0.25 Hz for case 3. Over-frequency values (with a typical 0.1% threshold) slightly dominates under-frequency values in cases 1 and 2, while the opposite is observed in case 3. Medium fluctuations occur in 35% of windows for cases 1 and 2 and 41% for case 3. Outlier values are detected using the quartile method in 70% of windows for case 2, surpassing the other two cases. About six or seven typical patterns are also extracted using the presented learning scheme, revealing the frequency trends within the short time windows. The proposed approaches offer a simpler alternative than tracking frequency single values and also capture more comprehensive information than existing approaches that analyze the aggregated frequency values at the end of the specific time windows without considering the frequency trends. In this way, the network operators have the possibility to monitor the frequency quality and trends within short time scales using the most dominant indices and typical patterns.
Keywords: quantifying power system frequency quality, statistical indices, pattern extracting, machine learning, short time scales, renewable energy sources
Published in DKUM: 23.08.2024; Views: 50; Downloads: 17
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