Research on large-scale clean energy optimal scheduling method based on multi-source data-driven

With the large-scale growth and grid connection of intermittent renewable energy such as wind and solar, the problem of increasing renewable energy curtailment rate and system backup flexibility has become increasingly prominent. In order to solve the problem of high proportion of renewable energy s...
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Autor*in:	Chuanyu Xiong [verfasserIn] Lingfeng Xu [verfasserIn] Li Ma [verfasserIn] Pan Hu [verfasserIn] Ziyong Ye [verfasserIn] Jialun Sun [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	multi-area economic dispatching multi-source data-driven clean energy systems new power system constraint planning

Übergeordnetes Werk:	In: Frontiers in Energy Research - Frontiers Media S.A., 2014, 11(2024)
Übergeordnetes Werk:	volume:11 ; year:2024

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fenrg.2023.1230818

Katalog-ID:	DOAJ09797305X

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author	Chuanyu Xiong
spellingShingle	Chuanyu Xiong misc multi-area economic dispatching misc multi-source data-driven misc clean energy systems misc new power system misc constraint planning misc General Works misc A Research on large-scale clean energy optimal scheduling method based on multi-source data-driven
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topic_title	Research on large-scale clean energy optimal scheduling method based on multi-source data-driven multi-area economic dispatching multi-source data-driven clean energy systems new power system constraint planning
topic	misc multi-area economic dispatching misc multi-source data-driven misc clean energy systems misc new power system misc constraint planning misc General Works misc A
topic_unstemmed	misc multi-area economic dispatching misc multi-source data-driven misc clean energy systems misc new power system misc constraint planning misc General Works misc A
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title	Research on large-scale clean energy optimal scheduling method based on multi-source data-driven
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title_sort	research on large-scale clean energy optimal scheduling method based on multi-source data-driven
title_auth	Research on large-scale clean energy optimal scheduling method based on multi-source data-driven
abstract	With the large-scale growth and grid connection of intermittent renewable energy such as wind and solar, the problem of increasing renewable energy curtailment rate and system backup flexibility has become increasingly prominent. In order to solve the problem of high proportion of renewable energy scientific consumption and flexible and stable operation of energy system. We propose a flexible and economical dispatch method based on data-driven multi-regional power system. For the problem of economic dispatch of multi-area power system, a mathematical calculation model is established to satisfy the constraints of unit output, system power balance, unit ramp rate, and valve point effect, and to consider the requirement of minimizing the cost of multi-area power load comprehensively. Based on data-driven, this paper adopts an improved fruit fly optimization algorithm to quickly find the global optimal solution. The calculations are performed by IEEE6 simulation test system, and the results verify the feasibility of the proposed algorithm. The improved fruit fly optimization algorithm is compared and analyzed with other algorithms considering the quality of the obtained solutions. The results show the effectiveness and superiority of the proposed algorithm in solving multi-area economic dispatching problems in real power systems.
abstractGer	With the large-scale growth and grid connection of intermittent renewable energy such as wind and solar, the problem of increasing renewable energy curtailment rate and system backup flexibility has become increasingly prominent. In order to solve the problem of high proportion of renewable energy scientific consumption and flexible and stable operation of energy system. We propose a flexible and economical dispatch method based on data-driven multi-regional power system. For the problem of economic dispatch of multi-area power system, a mathematical calculation model is established to satisfy the constraints of unit output, system power balance, unit ramp rate, and valve point effect, and to consider the requirement of minimizing the cost of multi-area power load comprehensively. Based on data-driven, this paper adopts an improved fruit fly optimization algorithm to quickly find the global optimal solution. The calculations are performed by IEEE6 simulation test system, and the results verify the feasibility of the proposed algorithm. The improved fruit fly optimization algorithm is compared and analyzed with other algorithms considering the quality of the obtained solutions. The results show the effectiveness and superiority of the proposed algorithm in solving multi-area economic dispatching problems in real power systems.
abstract_unstemmed	With the large-scale growth and grid connection of intermittent renewable energy such as wind and solar, the problem of increasing renewable energy curtailment rate and system backup flexibility has become increasingly prominent. In order to solve the problem of high proportion of renewable energy scientific consumption and flexible and stable operation of energy system. We propose a flexible and economical dispatch method based on data-driven multi-regional power system. For the problem of economic dispatch of multi-area power system, a mathematical calculation model is established to satisfy the constraints of unit output, system power balance, unit ramp rate, and valve point effect, and to consider the requirement of minimizing the cost of multi-area power load comprehensively. Based on data-driven, this paper adopts an improved fruit fly optimization algorithm to quickly find the global optimal solution. The calculations are performed by IEEE6 simulation test system, and the results verify the feasibility of the proposed algorithm. The improved fruit fly optimization algorithm is compared and analyzed with other algorithms considering the quality of the obtained solutions. The results show the effectiveness and superiority of the proposed algorithm in solving multi-area economic dispatching problems in real power systems.
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title_short	Research on large-scale clean energy optimal scheduling method based on multi-source data-driven
url	https://doi.org/10.3389/fenrg.2023.1230818 https://doaj.org/article/83d3d24d7dda476c9ca615f233cb1567 https://www.frontiersin.org/articles/10.3389/fenrg.2023.1230818/full https://doaj.org/toc/2296-598X
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up_date	2024-07-03T14:45:28.210Z
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Research on large-scale clean energy optimal scheduling method based on multi-source data-driven

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