Assessment of solar data estimation models for four cities in Iran

Date

2015-04-29

Author

Jahani, Elham
Sadati, S. M. Sajed
Yousefzadeh, Moslem

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

270
views

0
downloads

The estimated solar resources are important for designing renewable energy systems since measured data are not always available. The estimation models have been introduced in several studies. These models are mainly dependent on local meteorological data and need to be assessed for different locations and times. The current study compares the results of Angstrom's model and a neural network (NN) model developed for this study with measured data for four cities in Iran. The time resolution for the estimated global horizontal insolation is monthly. The results show that the developed NN model has promising performance and considering the calibration process for Angstrom's model it can be used as an alternative. The NN model uses climatic data to estimate the solar insolation which makes it more flexible in terms of being applicable for different regions. (C) 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Subject Keywords

Iran, Artificial neural network, Angstrom's model, Global insolation, Solar resources

URI

https://hdl.handle.net/11511/66311

DOI

https://doi.org/10.1002/pssc.201510105

Collections

Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Study Case of Solar Thermal and Photovoltaic Heat Pump System for Different Cities in Turkey Moia-Pol, Andreu; Pujol-Nadal, Ramon; Martinez-Moll, Victor; Bonyadi, Nima; Baker, Derek (2016-10-14) The combination of solar thermal, photovoltaic, and heat pump technologies is a welcome advancement in countries with large solar resources such as Turkey. These systems could have similar efficiencies throughout the year for different locations in Turkey if we adjust the solar storage according to the weather conditions. In this paper, solar heating with a heat pump system for buildings have been designed to achieve different values of the fraction of primary energy saved using Flat Plate Collectors (FPC) ...
Solar Power Generation Analysis and Forecasting Real-World Data Using LSTM and Autoregressive CNN tosun, nail; sert, egemen; Ayaz, Enes; YILMAZ, ekin; GÖL, MURAT (2020-09-22) Generated power of a solar panel is volatile and susceptible to environmental conditions. In this study, we have analyzed variables affecting the generated power of a 17.5 kW real-world solar power plant with respect to five independent variables over the generated power: irradiance, time of measurement, panel's temperature, ambient temperature and cloudiness of the weather at the time of measurement. After our analysis, we have trained three different models to predict intra-day solar power forecasts of th...
Assessment of renewable energy based micro-grids for small communities Sadati, S.M. Sajed; Taylan, Onur; Sustainable Environment and Energy Systems (2016-7) Deploying renewable energy systems to supply electricity faces many challenges related to cost and variability of the renewable resources. One possible solution to these challenges is to hybridize renewable energy systems with conventional power systems and include energy storage systems. In this study, the feasibility analysis of two cases for electricity generation systems as (i) photovoltaic (PV)-battery-pumped hydro system (PHS) and (ii) PV-wind-battery are presented as a Renewable Energy Micro-Gr...
Evaluation and Comparisons of the Models to Calculate Solar Irradiation on Inclined Solar Panels for Ankara Özden, Talat; Akınoğlu, Bülent Gültekin; Karaveli, Abdullah Buğrahan (2017-11-29) In the optimization and feasibility analysis of renewable energy systems, the accuracy of the simulation methods is extremely important. Thus, in the case of solar energy systems, estimating the monthly average daily solar irradiation incident on inclined solar panels is the main step of long-term feasibility analysis toward reaching the viable investments. In fact, most solar energy investor companies use silicon solar irradiation measuring instruments in Turkey although only a few of them also measure the...
Using artificial neural network (ANN) techniques for solar irradiation predictions Akbaba, Erol Can; Akınoğlu, Bülent Gültekin; Department of Physics (2019) Estimation of solar energy is a task with many benefits to a diverse group of people. This purpose is pursued with many different methodologies. Artificial Neural Networks (ANNs) are the novel methods of choice in the last decade. We compare the classical solar irradiation estimation methods with different ANN schemes including different inputs, data amount and estimation target. Our analyses show that the use of ANN to predict solar irradiation reaching the Earth’s surface gives similar results with that o...

Citation Formats

E. Jahani, S. M. S. Sadati, and M. Yousefzadeh, “Assessment of solar data estimation models for four cities in Iran,” 2015, vol. 12, p. 1272, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/66311.