Adaptive Reactive Power Optimization in Offshore Wind Farms Based on an Improved Particle Swarm Algorithm

To address the reactive power optimization control problem in offshore wind farms (OWFs), this paper proposes an adaptive reactive power optimization control strategy based on an improved Particle Swarm Optimization (PSO) algorithm. Firstly, an OWF multi-objective optimization control model is estab...

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Vydané v:Electronics (Basel) Ročník 13; číslo 9; s. 1637
Hlavní autori: Fu, Chuanming, Liu, Junfeng, Zeng, Jun, Ma, Ming
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.05.2024
Predmet:
Accuracy
Air-turbines
Algorithms
Analysis
Buildings and facilities
Electric power loss
Mathematical optimization
Multiple objective analysis
Objectives
Offshore energy sources
Optimization
Optimization models
Particle swarm optimization
Rankings
Reactive power
Velocity
Wind power
Wind turbines
ISSN:2079-9292, 2079-9292
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Shrnutí:To address the reactive power optimization control problem in offshore wind farms (OWFs), this paper proposes an adaptive reactive power optimization control strategy based on an improved Particle Swarm Optimization (PSO) algorithm. Firstly, an OWF multi-objective optimization control model is established, with the total sum of voltage deviations at wind turbine (WT) terminals, active power network losses, and reactive power margin of WTs as comprehensive optimization objectives. Innovatively, adaptive weighting coefficients are introduced for the three sub-objectives, enabling the weights of each optimization objective to be adaptively adjusted based on real-time operating conditions, thus enhancing the adaptability of the reactive power optimization model to changes in operating conditions. Secondly, a Uniform Adaptive Particle Swarm Optimization (UAPSO) algorithm is proposed. On one hand, the algorithm initializes the particle swarm using a uniform initialization method; on the other hand, it improves the particle velocity update formula, allowing the inertia coefficient to adaptively adjust based on the number of iterations and the fitness ranking of particles. Simulation results demonstrate the following: (1) Under various operating conditions, the proposed adaptive multi-objective reactive power optimization strategy can ensure the stability of node voltages in offshore wind farms, reduce active power losses, and simultaneously improve reactive power margins. (2) Compared with the traditional PSO algorithm, UAPSO exhibits an approximately 10% improvement in solution speed and enhanced solution accuracy.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics13091637