A Photovoltaic Power Forecasting Method Based on DA-RKELM Algorithm

Authors

Mingqi Wei, 1. School of Mechanical Engineering, Shenyang University, Shenyang 110041, China; ;
Tianrui Zhang, 1. School of Mechanical Engineering, Shenyang University, Shenyang 110041, China; ;
Xiuxiu Gao, 1. School of Mechanical Engineering, Shenyang University, Shenyang 110041, China; ;
Shumei Wang, 2. School of Business Administration, Shenyang University, Shenyang 110041, China;

Abstract

Abstract: Aiming at the power grid safety problems caused by the fluctuation and randomness of photo-voltaic power generation, a method for predicting photo-voltaic power generation of a regular nuclear limit learning machine based on the optimization of a dragonfly algorithm was proposed. Through correlation analysis, the key factors affecting the photo-voltaic power generation are determined, and the photo-voltaic power prediction model is constructed. Dragonfly algorithm is used to obtain the optimal weight and threshold value of the network, and regularization function and kernel function are introduced based on the standard limit learning machine to avoid the over fitting problem caused by the traditional gradient descent method and enhance the spatial mapping ability of the model. Simulation experiments show that compared with DA-ELM, PSO-ELM and GA- ELM models, the DA-RKELM prediction model achieve higher prediction accuracy, closer to the actual operating power of photo-voltaic power generation.

Recommended Citation

Wei, Mingqi; Zhang, Tianrui; Gao, Xiuxiu; and Wang, Shumei (2020) "A Photovoltaic Power Forecasting Method Based on DA-RKELM Algorithm," Journal of System Simulation: Vol. 32: Iss. 10, Article 22.
DOI: 10.16182/j.issn1004731x.joss.20-FZ0289
Available at: https://dc-china-simulation.researchcommons.org/journal/vol32/iss10/22

First Page

2041

Revised Date

2020-06-02

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.20-FZ0289

Last Page

2051

CLC

TM615

Recommended Citation

Wei Mingqi, Zhang Tianrui, Gao Xiuxiu, Wang Shumei. A Photovoltaic Power Forecasting Method Based on DA-RKELM Algorithm[J]. Journal of System Simulation, 2020, 32(10): 2041-2051.

DOI

10.16182/j.issn1004731x.joss.20-FZ0289