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Wyszukujesz frazę "parameter optimization" wg kryterium: Temat


Wyświetlanie 1-3 z 3
Tytuł:
Fault diagnosis of power transformer based on improved particle swarm optimization OS-ELM
Autorzy:
Li, Yuancheng
Ma, Longqiang
Powiązania:
https://bibliotekanauki.pl/articles/140428.pdf
Data publikacji:
2019
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
power transformer
fault diagnosis
improved particle swarm optimization
OS-ELM
parameter optimization
Opis:
A transformer is an important part of power transmission and transformation equipment. Once a fault occurs, it may cause a large-scale power outage. The safety of the transformer is related to the safe and stable operation of the power system. Aiming at the problem that the diagnosis result of transformer fault diagnosis method is not ideal and the model is unstable, a transformer fault diagnosis model based on improved particle swarm optimization online sequence extreme learning machine (IPSO-OS-ELM) algorithm is proposed. The improved particle swarmoptimization algorithm is applied to the transformer fault diagnosis model based on the OS-ELM, and the problems of randomly selecting parameters in the hidden layer of the OS-ELM and its network output not stable enough, are solved by optimization. Finally, the effectiveness of the improved fault diagnosis model in improving the accuracy is verified by simulation experiments.
Źródło:
Archives of Electrical Engineering; 2019, 68, 1; 161-172
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Parameter estimation of photovoltaic module relied on golden jackal optimization
Autorzy:
Nguyen, Thuan Thanh
Powiązania:
https://bibliotekanauki.pl/articles/27309949.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
golden jackal optimization
henry gas solubility optimization
particle swarm optimization
PV parameter estimation
single diode model
Opis:
Due to the nonlinear current-voltage (I-V) relationship of the photovoltaic (PV) module, building a precise mathematical model of the PV module is necessary for evaluating and optimizing the PV systems. This paper proposes a method of building PV parameter estimation models based on golden jackal optimization (GJO). GJO is a recently developed algorithm inspired by the idea of the hunting behavior of golden jackals. The explored and exploited searching strategies of GJO are built based on searching for prey as well as harassing and grabbing prey of golden jackals. The performance of GJO is considered on the commercial KC200GT module under various levels of irradiance and temperature. Its performance is compared to well-known particle swarm optimization (PSO), recent Henry gas solubility optimization (HGSO) and some previous methods. The obtained results show that GJO can estimate unknown PV parameters with high precision. Furthermore, GJO can also provide better efficiency than PSO and HGSO in terms of statistical results over several runs. Thus, GJO can be a reliable algorithm for the PV parameter estimation problem under different environmental conditions.
Źródło:
Archives of Electrical Engineering; 2023, 72, 4; 987--1003
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analysis of power system stabilizer Pareto optimisation-when taking into account the uncertainty of power system mathematical model parameters
Autorzy:
Nocoń, A.
Paszek, S.
Powiązania:
https://bibliotekanauki.pl/articles/140408.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
stabilizator systemowy
niepewność parametrów
Pareto-optymalizacja
power system stabilizer
Pareto optimization
parameter uncertainty
Opis:
The paper presents analysis of optimisation results of power system stabilizer (PSS) parameters when taking into account the uncertainty of mathematical model parameters of the power system (PS) elements. The Pareto optimisation was used for optimisation of the system stabilizer parameters. Parameters of five stabilizers of PSS3B type were determined in optimisation process with use of a genetic algorithm with tournament selection. The results obtained were assessed from the point of view of selecting the criterion function. The analysis of influence of the parameter uncertainty on the quality of the results obtained was performed.
Źródło:
Archives of Electrical Engineering; 2011, 60, 4; 385-398
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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