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Optimization of Load Distribution Method for Hydropower Units Based on Output Fluctuation Constraint and Double-Layer Nested Model

Authors :
Hong Pan
Zhengliang Luo
Chenyang Hang
Yuan Zheng
Fang Feng
Xiaonan Zheng
Source :
Mathematics, Vol 12, Iss 5, p 662 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

During the load distribution of hydropower units, the frequent crossing of vibration zones as well as large output fluctuations affect the stability of the power station. A multi-objective double-layer intelligent nesting model that considers the constraint of the output fluctuation of units is proposed to address these problems. The nonlinear constraint unit commitment optimization model layer is built based on outer dynamic programming, and the load distribution optimization model layer is constructed based on the improved biogeography-based optimization algorithm. Simultaneously, the unit output fluctuation constraint is established based on whether the unit combination changes in order to limit the unit output fluctuation. The results of this model indicate that compared with traditional load allocation models, the application of the method proposed in this paper can reduce the fluctuation range of unit output by 85.01%. In addition, except for the inevitable vibration zone crossings during startup and shutdown processes, the unit does not cross the vibration zone during operation, which greatly improves the unit’s vibration isolation and optimization capabilities. The multi-objective double-layer intelligent nested model proposed in this paper has significant advantages in the field of load allocation for hydropower units. It effectively improves the stability and reliability of unit operation, and this method can be applied to practical load allocation processes. It is of great significance for the research on load allocation optimization of hydropower units.

Details

Language :
English
ISSN :
22277390
Volume :
12
Issue :
5
Database :
Directory of Open Access Journals
Journal :
Mathematics
Publication Type :
Academic Journal
Accession number :
edsdoj.3f11f165f916468db6b2a53f383ac160
Document Type :
article
Full Text :
https://doi.org/10.3390/math12050662