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A Novel Loss of Excitation Protection Principle for Synchronous Condenser Based on Leading Rate Read chapter Read first chapter

2020 | OriginalPaper | Chapter

Analysis of the Characteristics of Cross-Border Power Trade Network Based on Complex Network Theory

Authors : Kai Fan, Rong Fu

Published in: Proceedings of PURPLE MOUNTAIN FORUM 2019-International Forum on Smart Grid Protection and Control

Publisher: Springer Nature Singapore

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Abstract

With the opening of the regional electricity market, the interconnection and interoperability of international power grids is constantly moving forward. In the face of increasing cross-border power commodity trade, social network analysis is widely used to analyze the structural characteristics of cross-border power trade networks, but traditional analysis only focuses on the topological structure of power trade network, lacks consideration of trade volume. Based on this, this paper uses complex network theory to establish a cross-border power trade weighted network for cross-border power trade along the “Belt and Road” region. In view of the trade volume in power trade, the weights of network links and nodes are taken into account. Then this paper improves the calculation method of aggregation coefficient and network structure entropy, and the characteristics of network structure such as degree distribution, aggregation and heterogeneity of cross-border power trade network are analyzed.

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previous chapter Analysis of Electricity Price Affordability of Large Industry Consumers in Yunnan Electricity Market
next chapter Power Trading Strategy Considering User Response Characteristics Under Incentive Conditions
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Metadata
Title
Analysis of the Characteristics of Cross-Border Power Trade Network Based on Complex Network Theory
Authors
Kai Fan
Rong Fu
Copyright Year
2020
Publisher
Springer Nature Singapore
Book
Proceedings of PURPLE MOUNTAIN FORUM 2019-International Forum on Smart Grid Protection and Control

Print ISBN: 978-981-13-9778-3

Electronic ISBN: 978-981-13-9779-0

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-13-9779-0_79