Forecasting of Solar Power using Quantum GA - GNN
نویسنده
چکیده
Artificial Neural Network has been popularly used for forecasting purposes over the past. There are some innate problems in neural network such as indefinite configuration, architecture, and learning issues, etc. To vanquish these problems, Generalized Neural Network (GNN) has been used. This paper illustrates the development of Quantum GA-GNN method for forecasting of solar photovoltaic system power output. The actual data has been collected from the solar system installed at the rooftop of the University building and processed. The forecasting models also developed using Artificial Neural Network (ANN), and the results are compared.
منابع مشابه
Interval-based Solar PV Power Forecasting Using MLP-NSGAII in Niroo Research Institute of Iran
This research aims to predict PV output power by using different neuro-evolutionary methods. The proposed approach was evaluated by a data set, which was collected at 5-minute intervals in the photovoltaic laboratory of Niroo Research Institute of Iran (Tehran). The data has been divided into three intervals based on the amount of solar irradiation, and different neural networks were used for p...
متن کاملNumerical Modeling of Electronic and Electrical Characteristics of 0.3 0.7 Al Ga N / GaN Multiple Quantum Well Solar Cells
The present study was conducted to investigate current density of0.3 0.7 Al Ga N/ GaN multiple quantum well solar cell (MQWSC) under hydrostaticpressure. The effects of hydrostatic pressure were taken into account to measureparameters of 0.3 0.7 Al Ga N/ GaN MQWSC, such as interband transition energy, electronholewave functions, absorption coefficient, and dielectric con...
متن کاملShort-Term Load Forecasting Using Soft Computing Techniques
Electric load forecasting is essential for developing a power supply strategy to improve the reliability of the ac power line data network and provide optimal load scheduling for developing countries where the demand is increased with high growth rate. In this paper, a short-term load forecasting realized by a generalized neuron–wavelet method is proposed. The proposed method consists of wavele...
متن کاملSILAR Sensitization as an Effective Method for Making Efficient Quantum Dot Sensitized Solar Cells
CdSe quantum dots were in situ deposited on various structures of TiO2 photoanode by successive ionic layer adsorption and reaction (SILAR). Various sensitized TiO2 structures were integrated as a photoanode in order to make quantum dot sensitized solar cells. High power conversion efficiency was obtained; 2.89 % (Voc=524 mV, Jsc=9.78 mA/cm2, FF=0.56) for the cells that sensitized by SILAR meth...
متن کاملAssessment of forecasting techniques for solar power production with no exogenous inputs
We evaluate and compare several forecasting techniques using no exogenous inputs for predicting the solar power output of a 1 MWp, single-axis tracking, photovoltaic power plant operating in Merced, California. The production data used in this work corresponds to hourly averaged power collected from November 2009 to August 2011. Data prior to January 2011 is used to train the several forecastin...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2015