Fuzzy-based prediction of solar PV and wind power generation for microgrid modeling using particle swarm optimization.

Teferra, Demsew Mitiku; Ngoo, Livingstone M H; Nyakoe, George N

Teferra, Demsew Mitiku; Ngoo, Livingstone M H; Nyakoe, George N.

Afiliación

Teferra DM; Pan-African University Institute of Basic Science, Technology and Innovation, Nairobi, Kenya.
Ngoo LMH; Department of Electrical & Communications Engineering, Multimedia University of Kenya, Nairobi, Kenya.
Nyakoe GN; Department of Electrical Engineering, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya.

Heliyon ; 9(1): e12802, 2023 Jan.

Article en En | MEDLINE | ID: mdl-36704286

Palabras clave

ANFIS, Adaptive Neuro-Fuzzy Inference System; ANN, Artificial Neural Network; ARIMA, Autoregressive Integrated Moving Average; ARMA, Auto-Regressive Moving Average; BPNN, Back Propagation Neural Network; CA, Cultural Algorithm; CNN, Convolutional Neural Network; DNI, Direct Normal Insolation; DSI, Diffused Solar Insolation; ECF, Error Correction Factor; FF, Firefly Algorithm; FOA, Fruit Fly Optimization Algorithm; FR, Fuzzy Regression; Fuzzy system; Fuzzy-GA Hybrid algorithm; Fuzzy-PSO Algorithm; GA, Genetic Algorithm; GHI, Global Horizontal Irradiance; LSSVM, Least-Square Support Vector Machine; MAPE, Mean Absolute Percentage Error; NRMSE, Normalized Root-Mean-Square Error; PSO, Particle Swarm Optimization; PV, Photovoltaic; Particle swarm optimization; SVM, Support Vector Machine; SVR, Support Vector Regression; Solar power prediction model; Wind power prediction model

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Heliyon Año: 2023 Tipo del documento: Article País de afiliación: Kenia

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