Design of a New Energy Microgrid Optimization Scheduling Algorithm Based on Improved Grey Relational Theory

In order to solve the problem of the large-scale integration of new energy into power grid output fluctuations, this paper proposes a new energy microgrid optimization scheduling algorithm based on a two-stage robust optimization and improved grey correlation theory. This article simulates the fluct...

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Main Authors: Dong Mo, Qiuwen Li, Yan Sun, Yixin Zhuo, Fangming Deng
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Algorithms
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Online Access:https://www.mdpi.com/1999-4893/18/1/36
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author Dong Mo
Qiuwen Li
Yan Sun
Yixin Zhuo
Fangming Deng
author_facet Dong Mo
Qiuwen Li
Yan Sun
Yixin Zhuo
Fangming Deng
author_sort Dong Mo
collection DOAJ
description In order to solve the problem of the large-scale integration of new energy into power grid output fluctuations, this paper proposes a new energy microgrid optimization scheduling algorithm based on a two-stage robust optimization and improved grey correlation theory. This article simulates the fluctuation of the outputs of wind turbines and distributed photovoltaic power plants by changing their robustness indicators, generates economic operating cost data for microgrids in multiple scenarios, and uses an improved grey correlation theory algorithm to analyze the correlation between new energy and various scheduling costs. Subsequently, a weighted analysis is performed on each correlation degree to obtain the correlation degree between new energy and total scheduling operating costs. The experimental results show that the improved grey correlation theory optimization scheduling algorithm for new energy microgrids proposed obtains weighted correlation degrees of 0.730 and 0.798 for photovoltaic power stations and wind turbines, respectively, which are 3.1% and 4.6% higher than traditional grey correlation theory. In addition, the equipment maintenance costs of this method are 0.413 and 0.527, respectively, which are 25.1% and 5.4% lower compared to the traditional method, respectively, indicating that the method effectively improves the accuracy of quantitative analysis.
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institution Kabale University
issn 1999-4893
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series Algorithms
spelling doaj-art-35913a3b3a254c9380fbc43b18d1672c2025-01-24T13:17:33ZengMDPI AGAlgorithms1999-48932025-01-011813610.3390/a18010036Design of a New Energy Microgrid Optimization Scheduling Algorithm Based on Improved Grey Relational TheoryDong Mo0Qiuwen Li1Yan Sun2Yixin Zhuo3Fangming Deng4Power Dispatch and Control Center, Guangxi Power Grid, Nanning 530023, ChinaPower Dispatch and Control Center, Guangxi Power Grid, Nanning 530023, ChinaPower Dispatch and Control Center, Guangxi Power Grid, Nanning 530023, ChinaPower Dispatch and Control Center, Guangxi Power Grid, Nanning 530023, ChinaSchool of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, ChinaIn order to solve the problem of the large-scale integration of new energy into power grid output fluctuations, this paper proposes a new energy microgrid optimization scheduling algorithm based on a two-stage robust optimization and improved grey correlation theory. This article simulates the fluctuation of the outputs of wind turbines and distributed photovoltaic power plants by changing their robustness indicators, generates economic operating cost data for microgrids in multiple scenarios, and uses an improved grey correlation theory algorithm to analyze the correlation between new energy and various scheduling costs. Subsequently, a weighted analysis is performed on each correlation degree to obtain the correlation degree between new energy and total scheduling operating costs. The experimental results show that the improved grey correlation theory optimization scheduling algorithm for new energy microgrids proposed obtains weighted correlation degrees of 0.730 and 0.798 for photovoltaic power stations and wind turbines, respectively, which are 3.1% and 4.6% higher than traditional grey correlation theory. In addition, the equipment maintenance costs of this method are 0.413 and 0.527, respectively, which are 25.1% and 5.4% lower compared to the traditional method, respectively, indicating that the method effectively improves the accuracy of quantitative analysis.https://www.mdpi.com/1999-4893/18/1/36new energymicrogrid systemrobust optimizationgrey correlation theoryoptimize scheduling algorithm
spellingShingle Dong Mo
Qiuwen Li
Yan Sun
Yixin Zhuo
Fangming Deng
Design of a New Energy Microgrid Optimization Scheduling Algorithm Based on Improved Grey Relational Theory
Algorithms
new energy
microgrid system
robust optimization
grey correlation theory
optimize scheduling algorithm
title Design of a New Energy Microgrid Optimization Scheduling Algorithm Based on Improved Grey Relational Theory
title_full Design of a New Energy Microgrid Optimization Scheduling Algorithm Based on Improved Grey Relational Theory
title_fullStr Design of a New Energy Microgrid Optimization Scheduling Algorithm Based on Improved Grey Relational Theory
title_full_unstemmed Design of a New Energy Microgrid Optimization Scheduling Algorithm Based on Improved Grey Relational Theory
title_short Design of a New Energy Microgrid Optimization Scheduling Algorithm Based on Improved Grey Relational Theory
title_sort design of a new energy microgrid optimization scheduling algorithm based on improved grey relational theory
topic new energy
microgrid system
robust optimization
grey correlation theory
optimize scheduling algorithm
url https://www.mdpi.com/1999-4893/18/1/36
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AT yansun designofanewenergymicrogridoptimizationschedulingalgorithmbasedonimprovedgreyrelationaltheory
AT yixinzhuo designofanewenergymicrogridoptimizationschedulingalgorithmbasedonimprovedgreyrelationaltheory
AT fangmingdeng designofanewenergymicrogridoptimizationschedulingalgorithmbasedonimprovedgreyrelationaltheory