LAPSE:2023.13144
Published Article

LAPSE:2023.13144
Reactive Power and Voltage Optimization of New-Energy Grid Based on the Improved Flower Pollination Algorithm
February 28, 2023
Abstract
In order to solve the reactive power and voltage control problem caused by the high proportion of new energy connected to the power grid, this paper takes the minimum voltage deviation, minimum network loss and maximum dynamic reactive power margin of the whole system as the comprehensive optimization objectives and establishes a reactive power and voltage optimization model by considering the reactive power regulation ability of SVC (Static Var Compensator) and new energy units. In view of the continuous and discrete variables in the model, the traditional continuous FPA (Flower Pollination Algorithm) is discretized to form an improved continuous-discrete hybrid FPA, and the tournament selection mechanism is adopted to speed up the convergence. Through the example analysis of the IEEE-39 bus system, the feasibility of the proposed reactive power and voltage optimal control method in the new energy grid is verified. Compared with GA (Genetic Algorithm), the results show that the improved FPA has high optimization accuracy, which is suitable for solving the reactive power and voltage optimization problem of the new energy grid.
In order to solve the reactive power and voltage control problem caused by the high proportion of new energy connected to the power grid, this paper takes the minimum voltage deviation, minimum network loss and maximum dynamic reactive power margin of the whole system as the comprehensive optimization objectives and establishes a reactive power and voltage optimization model by considering the reactive power regulation ability of SVC (Static Var Compensator) and new energy units. In view of the continuous and discrete variables in the model, the traditional continuous FPA (Flower Pollination Algorithm) is discretized to form an improved continuous-discrete hybrid FPA, and the tournament selection mechanism is adopted to speed up the convergence. Through the example analysis of the IEEE-39 bus system, the feasibility of the proposed reactive power and voltage optimal control method in the new energy grid is verified. Compared with GA (Genetic Algorithm), the results show that the improved FPA has high optimization accuracy, which is suitable for solving the reactive power and voltage optimization problem of the new energy grid.
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Keywords
dynamic reactive power margin, improved FPA, new-energy grid, reactive power voltage control, tournament selection mechanism
Subject
Suggested Citation
He H, Li J, Zhao W, Li B, Li Y. Reactive Power and Voltage Optimization of New-Energy Grid Based on the Improved Flower Pollination Algorithm. (2023). LAPSE:2023.13144
Author Affiliations
He H: Electric Power Research Institute, State Grid Jiangxi Electric Power Co., Ltd., Nanchang 330096, China
Li J: Electric Power Research Institute, State Grid Jiangxi Electric Power Co., Ltd., Nanchang 330096, China
Zhao W: Electric Power Research Institute, State Grid Jiangxi Electric Power Co., Ltd., Nanchang 330096, China
Li B: School of Mechanical Electronic and Information Engineering, University of Mining and Technology (Beijing), Beijing 100083, China
Li Y: School of Mechanical Electronic and Information Engineering, University of Mining and Technology (Beijing), Beijing 100083, China
Li J: Electric Power Research Institute, State Grid Jiangxi Electric Power Co., Ltd., Nanchang 330096, China
Zhao W: Electric Power Research Institute, State Grid Jiangxi Electric Power Co., Ltd., Nanchang 330096, China
Li B: School of Mechanical Electronic and Information Engineering, University of Mining and Technology (Beijing), Beijing 100083, China
Li Y: School of Mechanical Electronic and Information Engineering, University of Mining and Technology (Beijing), Beijing 100083, China
Journal Name
Energies
Volume
15
Issue
10
First Page
3653
Year
2022
Publication Date
2022-05-16
ISSN
1996-1073
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Original Submission
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PII: en15103653, Publication Type: Journal Article
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LAPSE:2023.13144
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https://doi.org/10.3390/en15103653
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Feb 28, 2023
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