Selective and decentralized underfrequency protection schemes in the distribution grid

Albrecht, Marvin; Robitzky, Lena; Rehtanz, Christian

doi:10.1109/ptc.2017.7981111

Cited by 5 publications

(3 citation statements)

References 7 publications

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“…A detailed analysis of this frequency control is shown in [10]. Two main protection function for low and medium voltage distribution grid are overload control and voltage stability.…”

Section: Fig 8 Concept Of Grid Supporting Charging Infrastructurementioning

confidence: 99%

Using Flexibilities of E-Mobility in planning and operation of electrical grid with grid-supporting charging infrastructure

Maasmann

Kippelt²

2019

EPJ Web Conf.

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This Research Approach shows how to use flexibilities of E-Mobility in planning and operation of electric grid with grid-supporting charging infrastructure. In the first part, we show how to deal with controlled and uncontrolled charging behavior during the planning of electrical grid. Therefore we show a tool for generating load curves and simultaneity factors and an example, how to use them for grid planning. The second part shows the concept of grid-supporting charging infrastructure, a simulation of the main functions and a feasible implementation in the Smart Grid Technology Lab of TU Dortmund University.

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“…A detailed analysis of this frequency control is shown in [10]. Two main protection function for low and medium voltage distribution grid are overload control and voltage stability.…”

Section: Fig 8 Concept Of Grid Supporting Charging Infrastructurementioning

confidence: 99%

Using Flexibilities of E-Mobility in planning and operation of electrical grid with grid-supporting charging infrastructure

Maasmann

Kippelt²

2019

EPJ Web Conf.

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“…• advanced load monitoring concepts including centralized [4][5][6][7][8][9][10][11][12][13][14][15][16] or decentralized monitoring [17][18][19][20][21][22]; • application of various types of hybrid systems [13,23,24] including those using advanced optimization algorithms (e.g., meta-heuristic techniques [14,15]); • application of wide area monitoring systems [25][26][27][28] or smart grid technology [13,[26][27][28][29][30][31][32][33][34]; • use of information technology [4,33,34] including Supervisory Control and Data Acquisition (SCADA) systems [35][36][37].…”

Section: Introductionmentioning

confidence: 99%

Underfrequency Load Shedding: An Innovative Algorithm Based on Fuzzy Logic

Małkowski

Nieznański

2020

Energies

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In contemporary power systems, the load shedding schemes are typically based on disconnecting a pre-specified amount of load after the frequency drops below a predetermined value. The actual conditions at the time of disturbance may largely differ from the assumptions, which can lead to non-optimal or ineffective operation of the load shedding scheme. For many years, increasing the effectiveness of the underfrequency load shedding (UFLS) schemes has been the subject of research around the world. Unfortunately, the proposed solutions often require costly technical resources and/or large amounts of real-time data monitoring. This paper puts forth an UFLS scheme characterized by increased effectiveness in the case of large disturbances and reduced disconnected power in the case of small and medium disturbances compared to the conventional load-shedding solutions. These advantages are achieved by replacing time-consuming consecutive load dropping with the simultaneous load dropping mechanism and by replacing ineffective fixed-frequency activation thresholds independent of the state of the system with implicit adaptive thresholds based on fuzzy logic computations. The proposed algorithm does not require complex and costly technical solutions. The performance of the proposed scheme was validated using multivariate computer simulations. Selected test results are included in this paper.

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“…In addition, the number and total capacity of generators that are tied to the distribution network is increasing steadily in France and many other countries, under the effect of massive distributed renewable energy sources (DRES) deployment. This trend is challenging the traditional ufls scheme [13–15]; indeed, the consumption profile of many feeders now results both from local consumption and from local generation – not from local loads alone any more. This potentially increases the risk that the weight of a particular UFLS step will vary wildly over time and drift away from its target weight.…”

Section: Introductionmentioning

confidence: 99%

Clustering‐based method for the feeder selection to improve the characteristics of load shedding

Potel

Cadoux

Garcia³

et al. 2019

IET Smart Grid

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Under-frequency load shedding (UFLS) schemes are designed by specifying a given amount of load to shed at various frequency thresholds to prevent the collapse of the electrical power system in the event of a large generation-load imbalance. An UFLS step is constituted of a group of medium-voltage feeders that trip when a given frequency threshold is reached. This study focuses on the method to be used when allocating a given feeder to a given step. First, the authors introduce performance metrics to quantify the accuracy level with which the UFLS target is met. Second, they model: the allocation method currently used in France; a variant of that method; and a new method introduced in this study, based on an automated clustering technique. Third, based on real consumption patterns measured from a vast area in France, and using the introduced performance metrics, they compare the efficiency of the three described methods. This study is conducted for the current state of loading of the considered distribution network and for a hypothetical situation with an increased share of distribution-side photovoltaic generation. For the chosen performance metrics, they demonstrate that the first two methods provide similar results while the clustering-based method performs remarkably better.

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Selective and decentralized underfrequency protection schemes in the distribution grid

Cited by 5 publications

References 7 publications

Using Flexibilities of E-Mobility in planning and operation of electrical grid with grid-supporting charging infrastructure

Using Flexibilities of E-Mobility in planning and operation of electrical grid with grid-supporting charging infrastructure

Underfrequency Load Shedding: An Innovative Algorithm Based on Fuzzy Logic

Clustering‐based method for the feeder selection to improve the characteristics of load shedding

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