Coordinated optimization for controlling short circuit current and multi-infeed DC interaction

Due to increased penetration of renewable energies, DC links and other emerging technologies, power system operation and planning have to cope with various uncertainties and risks. In order to solve the problems of exceeding short circuit current and multi-infeed DC interaction, a coordinated optimi...
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Autor*in:	Dong Yang [verfasserIn] Kang Zhao [verfasserIn] Yutian Liu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2014

Schlagwörter:	Operation and planning Multiple DC infeed Short circuit current Sensitivity analysis Multi-objective optimization

Übergeordnetes Werk:	In: Journal of Modern Power Systems and Clean Energy - IEEE, 2016, 2(2014), 4, Seite 274-284
Übergeordnetes Werk:	volume:2 ; year:2014 ; number:4 ; pages:274-284

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1007/s40565-014-0081-z

Katalog-ID:	DOAJ008188238

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topic_facet	Operation and planning Multiple DC infeed Short circuit current Sensitivity analysis Multi-objective optimization Production of electric energy or power. Powerplants. Central stations Renewable energy sources
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container_title	Journal of Modern Power Systems and Clean Energy
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callnumber-first	T - Technology
author	Dong Yang
spellingShingle	Dong Yang misc TK1001-1841 misc TJ807-830 misc Operation and planning misc Multiple DC infeed misc Short circuit current misc Sensitivity analysis misc Multi-objective optimization misc Production of electric energy or power. Powerplants. Central stations misc Renewable energy sources Coordinated optimization for controlling short circuit current and multi-infeed DC interaction
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topic_title	TK1001-1841 TJ807-830 Coordinated optimization for controlling short circuit current and multi-infeed DC interaction Operation and planning Multiple DC infeed Short circuit current Sensitivity analysis Multi-objective optimization
topic	misc TK1001-1841 misc TJ807-830 misc Operation and planning misc Multiple DC infeed misc Short circuit current misc Sensitivity analysis misc Multi-objective optimization misc Production of electric energy or power. Powerplants. Central stations misc Renewable energy sources
topic_unstemmed	misc TK1001-1841 misc TJ807-830 misc Operation and planning misc Multiple DC infeed misc Short circuit current misc Sensitivity analysis misc Multi-objective optimization misc Production of electric energy or power. Powerplants. Central stations misc Renewable energy sources
topic_browse	misc TK1001-1841 misc TJ807-830 misc Operation and planning misc Multiple DC infeed misc Short circuit current misc Sensitivity analysis misc Multi-objective optimization misc Production of electric energy or power. Powerplants. Central stations misc Renewable energy sources
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
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title	Coordinated optimization for controlling short circuit current and multi-infeed DC interaction
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title_full	Coordinated optimization for controlling short circuit current and multi-infeed DC interaction
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title_sort	coordinated optimization for controlling short circuit current and multi-infeed dc interaction
callnumber	TK1001-1841
title_auth	Coordinated optimization for controlling short circuit current and multi-infeed DC interaction
abstract	Due to increased penetration of renewable energies, DC links and other emerging technologies, power system operation and planning have to cope with various uncertainties and risks. In order to solve the problems of exceeding short circuit current and multi-infeed DC interaction, a coordinated optimization method is presented in this paper. Firstly, a branch selection strategy is proposed by analyzing the sensitivity relationship between current limiting measures and the impedance matrix. Secondly, the impact of network structure changes on the multi-infeed DC system is derived. Then the coordinated optimization model is established, which considers the cost and effect of current limiting measures, the tightness of network structure and the voltage support capability of AC system to multiple DCs. Finally, the non-dominated sorting genetic algorithm II combining with the branch selection strategy, is used to find the Pareto optimal schemes. Case studies on a planning power system demonstrated the feasibility and speediness of this method.
abstractGer	Due to increased penetration of renewable energies, DC links and other emerging technologies, power system operation and planning have to cope with various uncertainties and risks. In order to solve the problems of exceeding short circuit current and multi-infeed DC interaction, a coordinated optimization method is presented in this paper. Firstly, a branch selection strategy is proposed by analyzing the sensitivity relationship between current limiting measures and the impedance matrix. Secondly, the impact of network structure changes on the multi-infeed DC system is derived. Then the coordinated optimization model is established, which considers the cost and effect of current limiting measures, the tightness of network structure and the voltage support capability of AC system to multiple DCs. Finally, the non-dominated sorting genetic algorithm II combining with the branch selection strategy, is used to find the Pareto optimal schemes. Case studies on a planning power system demonstrated the feasibility and speediness of this method.
abstract_unstemmed	Due to increased penetration of renewable energies, DC links and other emerging technologies, power system operation and planning have to cope with various uncertainties and risks. In order to solve the problems of exceeding short circuit current and multi-infeed DC interaction, a coordinated optimization method is presented in this paper. Firstly, a branch selection strategy is proposed by analyzing the sensitivity relationship between current limiting measures and the impedance matrix. Secondly, the impact of network structure changes on the multi-infeed DC system is derived. Then the coordinated optimization model is established, which considers the cost and effect of current limiting measures, the tightness of network structure and the voltage support capability of AC system to multiple DCs. Finally, the non-dominated sorting genetic algorithm II combining with the branch selection strategy, is used to find the Pareto optimal schemes. Case studies on a planning power system demonstrated the feasibility and speediness of this method.
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title_short	Coordinated optimization for controlling short circuit current and multi-infeed DC interaction
url	https://doi.org/10.1007/s40565-014-0081-z https://doaj.org/article/7493ba3e76a74d6c846c2dcbde8f0ca8 https://ieeexplore.ieee.org/document/9005341/ https://doaj.org/toc/2196-5420
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up_date	2024-07-03T16:29:14.224Z
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Coordinated optimization for controlling short circuit current and multi-infeed DC interaction

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