Output Power Of Solar Array Research Articles

A Fast Maximum Power Point Tracking For Mismatching Compensation For Pv Systems Under Normal And Partially Shaded Conditions

To increase the efficiency of photovoltaic (PV) systems, maximum power point tracking of the solar arrays is needed. Output power of solar arrays depends on the solar irradiance, temperature and load. Irradiance changing effects on current is more than voltage and with irradiance increasing, current increases more than voltage and finally power increases. But effect of temperature changing is more on voltage and with temperature increasing, voltage decreases and in result the power decreases. If solar array be under shade conditions, it’s P-I characteristic has multiple peaks and finding of real maximum power point is a problem. This paper presents a fast maximum power point tracking with improved Particle Swarm Optimizationfor PV systems under normal and partially shaded conditions. Simulation results confirm that proposed MPPT algorithm and kinds of it with high accuracy can track the peak power point under different irradiation, temperature and partially shaded conditions and they have results near to real value.

Output Power Prediction Method of GEO Satellite Solar Array Based-on the Modified Equivalent Circuit Model

It proposed a single-exponential equivalent circuit model in order to predict the output power of geostationary satellite solar array. The key factors of the model are the short-circuit current ( ) , the open-circuit voltage( ) , the maximum power point current ( ) and the maximum power point voltage( ), which are used with corresponding coefficient to calculate the updated four parameters and I-V characteristics equation based on the new light intensity and temperature. Then, the power of various light intensity and temperature are calculated according to the provided voltage data, and a modified model is achieved by considering the attenuation factor. At last, this paper presents two experiments of the short-term and long-term solar array output power prediction. The comparison results of the predicted power and real power illustrate the prediction accuracy of 85%. Therefore, this power prediction model is sufficient for most engineering applications.

The Analysis of Abnormal Phenomena of GEO Satellites Solar Array

Satellites solar array provides sustainable and reliable energy for satellite by changing the solar energy into electrical energy in order to ensure the normal working of the satellite. The working status of solar array is directly related to the satellites normal running in orbit. The thesis summarized the normal trend of the GEO satellites solar array output power, through comparing the real output power of a certain satellites solar array with the normal trend, and detected four abnormal phenomena of solar array output power. Then the thesis analyzed the reasons, and made related suggestions.

Intelligent Monitoring and Predicting Output Power Losses of Solar Arrays Based on Particle Filtering

Solar arrays are the main source of energy to the on-orbit satellite, whose output power largely determines the life cycle of on-orbit satellites. Monitoring and further forecasting the output power of solar arrays by using the real-time observational data are very important for the study of satellite design and on-orbit satellite control. In this paper, we firstly describe the dynamical model of output power with summarizing the influencing factors of attenuation for solar arrays and elaborating the evolution trend of influencing factors which change with time. Based on the empirical model, a particle filtering algorithm is formulated to predict the output power of solar arrays and update the model parameters, simultaneously. Finally, using eight-year observational data of voltage and current from a synchronous on-orbit satellite, an experiment is carried out to illustrate the reliability and accuracy of the particle filtering method. Comparative results with classical curve fitting also are presented with statistical root mean square error and mean relative error analysis.

A Photovoltaic Generation System with Improvement of Power Degradation Caused by Non-Uniform Insolation

This paper proposes a new photovoltaic generation system which effectively uses generated power of shadowed cells. In this system, a capacitor is connected to the solar cell module in parallel. The generated power of the shadowed cells is charged into the capacitor. This charged power is added to the solar cell array output power. The proposed system needs no external power supplies and is very compact and cost-effective. The energy efficiency of the system is much better than that of the bypass diode method. The experiment shows the usefulness of this system.

Space weather effects on the MAGION-4 and MAGION-5 solar cells

Abstract. Data on solar array efficiency measured on board two Czech MAGION micro-satellites between August 1995 and June 2002, during the period of increasing and high solar activity, were used to study the space weather effects on photo-voltaic solar cells. A stronger degradation of the solar array was observed on MAGION-5 in comparison with MAGION-4. This fact can be explained by the essential difference between the two orbits. The MAGION-5 s/c was in the radiation belts more than 40% of the time, whereas the MAGION-4 was only present about 4% of the time. The experimental data refer to periods of low as well as high solar activity, with an enhanced occurrence of strong solar events. The evaluation of the data set covering a period of more than 6 years has shown that solar proton flares can have an almost immediate effect on the solar array efficiency. However, in the case of MAGION-5, an important role in solar cell degradation is played by the long-term effect of energetic particles in the radiation belts. Periods with a distinctly steeper decrease in the solar array output power were observed and can be explained by an increase of particle flux density in the radiation belts. Periods in slower decline of the solar array output power correspond to periods in low radiation belt indices based on the NOAA POES s/c data.