A Preventive Dispatching Method for High Wind Power-Integrated Electrical Systems Considering Probabilistic Transient Stability Constraints

This paper proposes a probabilistic transient stability-constrained preventive dispatching method for power systems under a high inclusion of wind power. First, a set of instability mode (IM)-categorized probabilistic transient stability constraints (PTSCs) are constructed, which facilitate the deve...

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Autores principales:	Yuchuan Chen, S. Mahdi Mazhari, C. Y. Chung, Sherif O. Faried
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Critical clearing time (CCT) machine learning optimal power flow power dispatch probabilistic transient stability uncertainties Distribution or transmission of electric power TK3001-3521 Production of electric energy or power. Powerplants. Central stations TK1001-1841
Acceso en línea:	https://doaj.org/article/e1e57d0c2de9406198485b5761890947
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spelling	oai:doaj.org-article:e1e57d0c2de9406198485b57618909472021-11-10T00:09:35ZA Preventive Dispatching Method for High Wind Power-Integrated Electrical Systems Considering Probabilistic Transient Stability Constraints2687-791010.1109/OAJPE.2021.3098658https://doaj.org/article/e1e57d0c2de9406198485b57618909472021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9492126/https://doaj.org/toc/2687-7910This paper proposes a probabilistic transient stability-constrained preventive dispatching method for power systems under a high inclusion of wind power. First, a set of instability mode (IM)-categorized probabilistic transient stability constraints (PTSCs) are constructed, which facilitate the development of a dispatching plan against various fault scenarios. Next, to avoid massive transient stability simulations in each dispatching operation, a machine learning-based model is trained to predict the critical clearing time (CCT) and IM for all preconceived fault scenarios. Based on the predictions, the system operation plan is assessed with respect to the PTSCs. Then, the sensitivity of the probabilistic level of the CCT is calculated to the active power generated from the critical generators for each IM category. Accordingly, the implicit PTSCs are converted into explicit dispatching constraints, and the dispatch is rescheduled to ensure the probabilistic stability requirements of the system are met at an economical operating cost. The proposed approach is validated on two modified IEEE test systems, reporting high computational efficiency and high-quality solutions.Yuchuan ChenS. Mahdi MazhariC. Y. ChungSherif O. FariedIEEEarticleCritical clearing time (CCT)machine learningoptimal power flowpower dispatchprobabilistic transient stabilityuncertaintiesDistribution or transmission of electric powerTK3001-3521Production of electric energy or power. Powerplants. Central stationsTK1001-1841ENIEEE Open Access Journal of Power and Energy, Vol 8, Pp 472-483 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Critical clearing time (CCT) machine learning optimal power flow power dispatch probabilistic transient stability uncertainties Distribution or transmission of electric power TK3001-3521 Production of electric energy or power. Powerplants. Central stations TK1001-1841
spellingShingle	Critical clearing time (CCT) machine learning optimal power flow power dispatch probabilistic transient stability uncertainties Distribution or transmission of electric power TK3001-3521 Production of electric energy or power. Powerplants. Central stations TK1001-1841 Yuchuan Chen S. Mahdi Mazhari C. Y. Chung Sherif O. Faried A Preventive Dispatching Method for High Wind Power-Integrated Electrical Systems Considering Probabilistic Transient Stability Constraints
description	This paper proposes a probabilistic transient stability-constrained preventive dispatching method for power systems under a high inclusion of wind power. First, a set of instability mode (IM)-categorized probabilistic transient stability constraints (PTSCs) are constructed, which facilitate the development of a dispatching plan against various fault scenarios. Next, to avoid massive transient stability simulations in each dispatching operation, a machine learning-based model is trained to predict the critical clearing time (CCT) and IM for all preconceived fault scenarios. Based on the predictions, the system operation plan is assessed with respect to the PTSCs. Then, the sensitivity of the probabilistic level of the CCT is calculated to the active power generated from the critical generators for each IM category. Accordingly, the implicit PTSCs are converted into explicit dispatching constraints, and the dispatch is rescheduled to ensure the probabilistic stability requirements of the system are met at an economical operating cost. The proposed approach is validated on two modified IEEE test systems, reporting high computational efficiency and high-quality solutions.
format	article
author	Yuchuan Chen S. Mahdi Mazhari C. Y. Chung Sherif O. Faried
author_facet	Yuchuan Chen S. Mahdi Mazhari C. Y. Chung Sherif O. Faried
author_sort	Yuchuan Chen
title	A Preventive Dispatching Method for High Wind Power-Integrated Electrical Systems Considering Probabilistic Transient Stability Constraints
title_short	A Preventive Dispatching Method for High Wind Power-Integrated Electrical Systems Considering Probabilistic Transient Stability Constraints
title_full	A Preventive Dispatching Method for High Wind Power-Integrated Electrical Systems Considering Probabilistic Transient Stability Constraints
title_fullStr	A Preventive Dispatching Method for High Wind Power-Integrated Electrical Systems Considering Probabilistic Transient Stability Constraints
title_full_unstemmed	A Preventive Dispatching Method for High Wind Power-Integrated Electrical Systems Considering Probabilistic Transient Stability Constraints
title_sort	preventive dispatching method for high wind power-integrated electrical systems considering probabilistic transient stability constraints
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/e1e57d0c2de9406198485b5761890947
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A Preventive Dispatching Method for High Wind Power-Integrated Electrical Systems Considering Probabilistic Transient Stability Constraints

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