Assessment of Load and Generation Modelling on the Quasi-Static Analysis of Distribution Networks

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Date

2021

Authors

Lamprianidou, I. S.
Papadopoulos, T. A.
Kryonidis, G. C.
Yetkin, E. Fatih
Pippi, K. D.
Chrysochos, A., I

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Publisher

Elsevier

Open Access Color

Green Open Access

No

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No
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Top 10%
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Top 10%

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Abstract

Quasi-static analysis of power systems can be performed by means of timeseries-based and probability density function-based models. In this paper, the effect of different load and generation modelling approaches on the quasi-static analysis of distribution networks is investigated. Different simplified load and distributed renewable energy sources generation timeseries-based models are considered as well as probabilistic analysis. Moreover, a more sophisticated approach based on cluster analysis is introduced to identify harmonized sets of representative load and generation patterns. To determine the optimum number of clusters, a three-step methodology is proposed. The examined cases include the quasi-static analysis of distribution networks for different operational conditions to identify the simplified modelling approaches that can efficiently predict the network voltages and losses. Finally, the computational efficiency by using the simplified models is evaluated in temperature-dependent power flow analysis of distribution networks. (C) 2021 Elsevier Ltd. All rights reserved.

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Keywords

Pattern-Recognition, Time-Series, Power-Flow, Reanalysis, Energy, Clustering, Pattern-Recognition, Distributed generation modelling, Time-Series, Load modelling, Power-Flow, Load timeseries, Reanalysis, Photovoltaic systems, Energy, Wind turbines, Energy, Reanalysis, Pattern-Recognition, Clustering, Load modelling, Distributed generation modelling, Wind turbines, Time-Series, Load timeseries, Photovoltaic systems, Power-Flow

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Fields of Science

0211 other engineering and technologies, 02 engineering and technology, 0202 electrical engineering, electronic engineering, information engineering

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OpenCitations Citation Count
8

Source

Sustainable Energy Grids & Networks

Volume

27

Issue

Start Page

100509

End Page

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CrossRef : 8

Scopus : 10

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Mendeley Readers : 8

SCOPUS™ Citations

10

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Web of Science™ Citations

7

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2

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