Implementation of an Economic System to Measure Solar Radiatio

Authors

Mohamed Darwish, Omar G. Angulo Castro, Ricardo Valenzuela, Alejandro Ortega, Gildardo Jimenez

Abstract

A data acquisition system based on a pyranometer, data acquisition board and a computer to record and display the data are developed Pyranometer based in solar cell, National Instrument USB-6008 as data acquisition, LABView as interface system. Made this a considerably cheap system. The pyranometer was physically located on the top of the roof, reading was taken every 30 minutes during 33 days in January, March, April and May (why not Feb?), no night readings. All measurements from 6:00 am to 6:00 pm. Location at 31.19’07’’N and 110.56’45’’O, 1000 meters above sea level. Result shows a reading error within 7% and above 2%.

Solar Irradiance Estimation Based on Photovoltaic Module Short Circuit Current Measurement

Authors

Rodney H.G. Tan, Priscilla L.J.Tai, V.H. Mok

Abstract

This paper using the estimation method of solar irradiance based on the short circuit current output produce by the photovoltaic module. Paper trying to prove the feasibility of this method with desired accuracy. Paper introduced Photovoltaic Module Model as a circuit model, according to the property of its solar cell diode, derived the relation between short circuit currents and the solar irradiance leads to this. By acquiring the datasheet for solar cells diodes from their manufacturers, parameters for this relation can be derived using mathematical models. By considering these parameters, the solar irradiance can be estimated. However, the result shows that the highest error can reach 15.9%, making this estimation not a very ideal method for high accuracy applies but only for rough estimation while expensive measure device like pyranometers are desired.

PV-based Li-ion Battery Charger with Neural MPPT for Autonomous Sea Vehicles

Authors

M. C. Di Piazza, M. Luna, M. Pucci, G. Vitale

Abstract

Photovoltaic battery charger based on a DC-DC boost converter for a small size marine autonomous vehicle is developed. Neural-based technique is used to estimate the solar irradiance on the basis of the actual PV panel voltage and current to provide maximum output. This techniques is called Growing Neural Gas, and is exploited to realize a virtual Pyranometer to acquire instant solar irradiance. The GNG network is a self-supervised system to create best topology for the vehicle. GNG then is trained to learn data by experiment, and then recalling these by online calculation to estimate the irradiance. On the basis of this estimate, maximum power point tracking (MPPT) can be realized.

Accurate measurements of solar irradiance for evaluation of photovoltaic power profiles

Authors

Filippo Spertino, Member, IEEE, Paolo Di Leo, Valeria Cocina

Abstract

Based on five meteorological stations and the yearly experimental results, this paper discuss an observed phenomenon called ‘broken clouds’. This phenomena lead to noticeable peaks in measurement and PV power system. This effect occurs when clouds around sun amplified the beam irradiance, causing 20% more irradiance observed up to 500 W/m^2 lasting for minutes. It represent that investigation for this phenomena can be very useful to generate desired peak power. This still need for further study.

Development of Data Acquisition System for Hybrid Power Plant

Authors

Aryuanto Soetedjo, Yusuf Ismail Nakhoda

Abstract

Data acquisition system integrated wind speed monitor, Pyranometer and PV temperature measurement is realized. Low cost PV module is used as PV sensor. LABView is used as monitoring both wind speed and Pyranometer, and a SCADA system used to control the system is introduced by L. Wang and K.H. Liu in ‘mplementation of a Web-Based Real-Time Monitoring and Control System for a Hybrid Wind-PV-Battery Renewable Energy System’. Pyranometer works at 10 V and 30mA. Low error down to 3.45% for solar irradiance measurement is realized. Work represent that high accuracy integrated measurement system to monitor both wind a solar irradiance can be achieved at a considerably cheap price.

A Neural Network-Based Low-Cost Solar Irradiance Sensor

Authors

Fernando Mancilla-David, Francesco Riganti-Fulginei, Antonino Laudani, Alessandro Salvini

Abstract

Pyranometer is too expensive to be exploited in PV plants(?). To solve this, this paper introduced an approach to maximize efficiency based on neural networks. PV cell as irradiance sensor and a temperature senor and a low cost controller is used to realize this is introduced here to lower the cost. To use neural network (NN), a training set is introduced for learning, according to PV array mathematical model. After setting up the model, dataset was generated through experimental synthesis. System provide data for model to compute the irradiance. Compared to commercial Pyranometer(LM-10 HTD), this system provide a matched regression line, represents its high accuracy. However, paper did not give further discussion about the ignorance of peak irradiance due to algorithm.

An Improved Model-Based Maximum Power Point Tracker for Photovoltaic Panels

Authors

Loredana Cristaldi, Marco Faifer, Marco Rossi, and Sergio Toscani

Abstract

A model-based maximum power point tracker is said to be able to offers a better dynamic performance than observation based MPPT system. It even did not require direct irradiance measurement. This paper built a circuit model. Meanwhile, it take generated thermal energy into account as uncoverted solar irradiance.

A New Approach to Maximum Power Point Tracking for Photovoltaic Panels

Authors

Loredana Cristaldi, Marco Faifer, Marco Rossi, Sergio Toscani

Abstract

MPPT( Maximum Power Point Tracker) system is designed and this paper shows a method that applied no direct measurement for solar irradiance for this system. This methods based on preset model, based on solar cell circuit model. According to measured circuit cell temperature, module voltage and current, the irradiance can be calculated. This system does not require radiometer that appeared in many model based MPPT systems. Its result shows a acceptable average error within 5%, although with several high error point as high as 25%.

A Prototype of an Integrated Pyranometer for Measuring Multi-Parameters

Authors

Faiz Syazwan, Abdul Aziz1, Shahril Irwan Sulaiman, Hedzlin Zainuddin

Abstract

System was design integrated with Pyranometer and temperature sensor module. Solar cell is used as sensor to build Pyranometer. Compare to commercial Pyranometer, this integrated solar censor can provide measurement with error between -6.01% and +2.92%.

Simulation and energy management of an experimental solar system through adaptive neural networks

Authors

R.H. Fouad, M.S.Ashhab, A. Mukattash, S. Idwan

Abstract

A solar system is built integrated a solar trainer that contains a photovoltaic panel, a DC centrifugal pump, flat plate collectors, storage tank, a flowmeter for measuring the water mass flow rate, pipes, pyranometer for measuring the solar intensity, thermocouples for measuring various system temperatures and wind speed meter. For Pyranometer, an artificial neural network is applied based on the difference between measured data and pre-learnt data. To increase accuracy, short term prediction is modeled according to Kaczmarz’s algorithm. Adaptation technique is introduced to improve the accuracy. ANN is used as a technique to compensate for system parts degradation, environmental variations, time changes and modeling errors. Result shows that adaptive ANN is more accurate than non-adaptive ANN system.

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