The CEER and the 4&lt;sup&gt;th&lt;/sup&gt; Benchmarking Report on Quality of Electricity Supply

Brekke, Karstein; Esteves, José; Bollen, M.H.J.; Schiavo, Luca Lo; Villa, Ferruccio; Reti, Geza; Haber, Alfons; Falcao, Amanda; Westergaard, Thomas; Kolessar, Rémy

doi:10.1109/powereng.2009.4915263

Cited by 6 publications

(4 citation statements)

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“…Outages can be classified based on their nature or duration. According to their nature, outages are defined as follows [7]:…”

Section: Reliability and Supply Continuity In Power Systemsmentioning

confidence: 99%

Investment technique for ensuring energy supply continuity in ring grids

Temiz,

Tür

2024

Turkish Journal of Engineering

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The importance of energy supply for both end-users and electricity distribution entities, as well as the need for reliable energy quality parameters, is significant. This study delves into scenarios where these parameters cannot be met, outlining formulas for calculating compensation and other financial obligations that distribution companies may incur. The study highlights various types of interruptions that disrupt energy supply continuity within electricity distribution networks and elucidates their impacts on the network infrastructure. The establishment of alternative energy sources and the enhancement of the network infrastructure through coupling are recommended to mitigate the consequences of these interruptions. Investments in alternative energy sources and network improvements are compared to penalty amounts incurred when the quality parameters for energy supply continuity cannot be met. The F13/F14 Ring Network, a proposed coupling approach that can improve energy supply, is identified and its installation costs are compared with the existing conditions. Additionally, the magnitude of fines that distribution companies may potentially face is estimated. As a result, a comprehensive cost-benefit analysis is conducted, integrating these comparisons to evaluate the economic sustainability and advantages associated with the proposed F13/F14 Ring Network coupling method.

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“…Outages can be classified based on their nature or duration. According to their nature, outages are defined as follows [7]:…”

Section: Reliability and Supply Continuity In Power Systemsmentioning

confidence: 99%

Investment technique for ensuring energy supply continuity in ring grids

Temiz,

Tür

2024

Turkish Journal of Engineering

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“…Subfigure 1 shows the waveform of the voltage sag, subfigure 2 shows the waveform of the voltage swell, and subfigure 3 shows one of the phases of the transformer energizing. Subfigure 4 shows one of the phases of the motor starting. The black solid line represents the actual measured waveform, and the red dotted line represents the reconstruction.…”

Section: Parameter Selectionmentioning

confidence: 99%

“…Figure 9 shows the result of the parameter, including the dictionary atom and sparse coefficients used. Black represents the coefficient matrix of the reconstructed waveform in subfigure 1 , pink is subfigure 2 , red is subfigure 3 , and gray is subfigure 4 .…”

Section: Parameter Selectionmentioning

confidence: 99%

“…According to the statistics of the Taiwan Power Company, each voltage sag caused an economic loss of about a hundred thousand to one million dollars US dollars to the Hsinchu Science Park in Taiwan. The occurrence of voltage sags leads directly to productivity and product quality declines in enterprises and increased costs, affecting people's normal life and causing huge economic 2 of 15 losses to society [4][5][6]. Therefore, it is necessary to take corresponding action to reduce the impact of voltage sags.…”

Section: Introductionmentioning

confidence: 99%

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Identification Method for Voltage Sags Based on K-means-Singular Value Decomposition and Least Squares Support Vector Machine

et al. 2019

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Voltage sag is one of the most serious problems in power quality. The occurrence of voltage sag will lead to a huge loss in the social economy and have a serious effect on people’s daily life. The identification of sag types is the basis for solving the problem and ensuring the safe grid operation. Therefore, with the measured data uploaded by the sag monitoring system, this paper proposes a sag type identification algorithm based on K-means-Singular Value Decomposition (K-SVD) and Least Squares Support Vector Machine (LS-SVM). Firstly; each phase of the sag sample RMS data is sparsely coded by the K-SVD algorithm and the sparse coding information of each phase data is used as the feature matrix of the sag sample. Then the LS-SVM classifier is used to identify the sag type. This method not only works without any dependence on the sag data feature extraction by artificial ways, but can also judge the short-circuit fault phase, providing more effective information for the repair of grid faults. Finally, based on a comparison with existing methods, the accuracy advantages of the proposed algorithm with be presented.

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