Short-Term Solar Irradiance Forecasting and Photovoltaic System Management Using Octonion Neural Networks
- PDF / 1,417,775 Bytes
- 8 Pages / 612 x 792 pts (letter) Page_size
- 99 Downloads / 211 Views
R RADIATION AND ITS PREDICTION
Short-Term Solar Irradiance Forecasting and Photovoltaic System Management Using Octonion Neural Networks Kamel Aimeura, Lyes Saad Saoudb, *, and Reza Ghorbanic aElectrification of Industrial Enterprises Laboratory, Department of Physics, Faculty of Sciences, University M’Hamed Bougara,
Boumerdès, 35000 Algeria Electrification of Industrial Enterprises Laboratory, Electrical Systems Engineering Department, Faculty of Engineer Sciences, University M’Hamed Bougara, Boumerdès, 35000 Algeria c Department of Mechanical Engineering, University of Hawaii at Manoa, Honolulu, HI, 96822 USA *e-mail: [email protected]
b
Received May 4, 2019; revised July 29, 2019; accepted March 23, 2020
Abstract—In this paper, the octonion neural network is investigated to forecast the short-term solar irradiance. The previous and the next eight values solar irradiance are organized into two octonion values; thereby the network could be constructed. This method not just gives the opportunity to forecast eight values ahead solar irradiance using one octonion input but also takes all the advantages of the octonion domain. The octonion input contains the past values solar irradiance which produces dynamics naturally to the network and decreases the input dimension vector. The octonion training algorithm has eight dimensions rather than one dimension in the real-valued neural networks. Comparison with the real-valued neural networks for forecasting solar irradiance shows that the proposed method is promising to deal with such problem. The optimal structure is used to manage the an autonomous photovoltaic (PV) system that contains the PV modules and the battery bank. The use of the proposed method presents benefits for the number of the used modules and for the battery energy requested as well. Keywords: octonion neural network, solar irradiance, forecasting, renewable energy, hypercomplex networks, PV system management DOI: 10.3103/S0003701X20030020
INTRODUCTION Actually, artificial intelligence becomes one primordial field. Octonion Valued Neural Networks (OVNNs), which are the particular architecture of the hypercomplex neural network, are promising strategies for demonstrating nonlinear frameworks in high measurements naturally [1]. The OVNNs are based on an octonion number which is eight-dimensional hypercomplex number. All the OVNNs parameters (i.e. weights, biases, inputs, and outputs) are octonion numbers, i.e. they have a place in octonion space. Two fundamental focal points could be gotten when utilizing OVNNs contrasting with the genuine esteemed frame: (1) The quantities of information sources and yields are lessened eight times. (2) Seven different measurements are added to the genuine esteemed learning calculation. In writing, the OVNNs have discovered a primordial place in a true application [2]. In literature, several procedures and models have been proposed to deal with solar irradiation, where neural systems possessed an awesome part. In [3–17], the aggregate sun based radiation time
Data Loading...
