Solar energy overview and maximizing power output of a solar array using sun trackers

2016 ◽  
Author(s):  
Hamid Allamehzadeh
Keyword(s):  
Solar Energy ◽  
Power Output ◽  
Solar Array

scholarly journals Predicting the Performance of Solar Power Generation Using Deep Learning Methods

2021 ◽  
Vol 11 (15) ◽  
pp. 6887
Author(s):  
Chung-Hong Lee ◽  
Hsin-Chang Yang ◽  
Guan-Bo Ye
Keyword(s):  
Power Generation ◽  
Solar Energy ◽  
Power Output ◽  
Power Plants ◽  
Solar Power ◽  
Photovoltaic Cell ◽  
Power Prediction ◽  
Seasonal Characteristics ◽  
Variable Nature ◽  
Solar Power Plants

In recent years, many countries have provided promotion policies related to renewable energy in order to take advantage of the environmental factors of sufficient sunlight. However, the application of solar energy in the power grid also has disadvantages. The most obvious is the variability of power output, which will put pressure on the system. As more grid reserves are needed to compensate for fluctuations in power output, the variable nature of solar power may hinder further deployment. Besides, one of the main issues surrounding solar energy is the variability and unpredictability of sunlight. If it is cloudy or covered by clouds during the day, the photovoltaic cell cannot produce satisfactory electricity. How to collect relevant factors (variables) and data to make predictions so that the solar system can increase the power generation of solar power plants is an important topic that every solar supplier is constantly thinking about. The view is taken, therefore, in this work, we utilized the historical monitoring data collected by the ground-connected solar power plants to predict the power generation, using daily characteristics (24 h) to replace the usual seasonal characteristics (365 days) as the experimental basis. Further, we implemented daily numerical prediction of the whole-point power generation. The preliminary experimental evaluations demonstrate that our developed method is sensible, allowing for exploring the performance of solar power prediction.

Prediction of solar array power output based on limited measured data

1993 ◽  
Vol 29 (1) ◽  
pp. 67-76 ◽  
Author(s):  
S.K. Sharma ◽  
Anil Agarwal ◽  
S. Anandavally ◽  
N. Srinivasamurthy ◽  
B.L. Agrawal
Keyword(s):  
Power Output ◽  
Measured Data ◽  
Solar Array

Evacuated Tube Heat Pipe Solar Collectors Applied to Recirculation Loop in a Federal Building: SSA Philadelphia

Solar Energy ◽  
2004 ◽  
Author(s):  
Andy Walker ◽  
Fariborz Mahjouri ◽  
Robert Stiteler
Keyword(s):  
Solar Energy ◽  
Heat Pipe ◽  
Heat Loss ◽  
Heating System ◽  
Hot Water ◽  
Solar Array ◽  
Solar Collectors ◽  
Water Heating ◽  
Evacuated Tube ◽  
Recirculation Loop

This paper describes design, simulation, construction and measured initial performance of a solar water heating system (360 Evacuated Heat-Pipe Collector tubes, 54 m2 gross area, 36 m2 net absorber area) installed at the top of the hot water recirculation loop in the Social Security Mid-Atlantic Center in Philadelphia. Water returning to the hot water storage tank is heated by the solar array when solar energy is available. This new approach, as opposed to the more conventional approach of preheating incoming water, is made possible by the thermal diode effect of heat pipes and low heat loss from evacuated tube solar collectors. The simplicity of this approach and its low installation costs makes the deployment of solar energy in existing commercial buildings more attractive, especially where the roof is far removed from the water heating system, which is often in the basement. Initial observed performance of the system is reported. Hourly simulation estimates annual energy delivery of 111 GJ/year of solar heat and that the annual efficiency (based on the 54 m2 gross area) of the solar collectors is 41%, and that of the entire system including parasitic pump power, heat loss due to freeze protection, and heat loss from connecting piping is 34%. Annual average collector efficiency based on a net aperture area of 36 m2 is 61.5% according to the hourly simulation.

scholarly journals Short Time Solar Power Forecasting Using Persistence Extreme Learning Machine Approach

2021 ◽  
Vol 294 ◽  
pp. 01002
Author(s):  
Xiaoyan Xiang ◽  
Yao Sun ◽  
Xiaofei Deng
Keyword(s):  
Solar Energy ◽  
Extreme Learning Machine ◽  
Power Output ◽  
Smart Grids ◽  
Large Scale ◽  
Solar Power ◽  
Learning Algorithm ◽  
Power Performance ◽  
Energy Prediction ◽  
Learning Machine

Solar energy in nature is irregular, so photovoltaic (PV) power performance is intermittent, and highly dependent on solar radiation, temperature and other meteorological parameters. Accurately predicting solar power to ensure the economic operation of micro-grids (MG) and smart grids is an important challenge to improve the large-scale application of PV to traditional power systems. In this paper, a hybrid machine learning algorithm is proposed to predict solar power accurately, and Persistence Extreme Learning Machine(P-ELM) algorithm is used to train the system. The input parameters are the temperature, sunshine and solar power output at the time of i, and the output parameters are the temperature, sunshine and solar power output at the time i+1. The proposed method can realize the prediction of solar power output 20 minutes in advance. Mean absolute error (MAE) and root-mean-square error (RMSE) are used to characterize the performance of P-ELM algorithm, and compared with ELM algorithm. The results show that the accuracy of P-ELM algorithm is better in short-term prediction, and P-ELM algorithm is very suitable for real-time solar energy prediction accuracy and reliability.

scholarly journals Comparative Analysis of Small-Scale Organic Rankine Cycle Systems for Solar Energy Utilisation

Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 829 ◽  
Author(s):  
Ruiqi Wang ◽  
Long Jiang ◽  
Zhiwei Ma ◽  
Abigail Gonzalez-Diaz ◽  
Yaodong Wang ◽  
...  
Keyword(s):  
Solar Energy ◽  
Power Output ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Hot Water ◽  
Superior Performance ◽  
Small Scale ◽  
Water Storage Tank ◽  
Solar Thermal Collector ◽  
Cycle Systems

Small-scale organic Rankine cycle (ORC) systems driven by solar energy are compared in this paper, which aims to explore the potential of power generation for domestic utilisation. A solar thermal collector was used as the heat source for a hot water storage tank. Thermal performance was then evaluated in terms of both the conventional ORC and an ORC using thermal driven pump (TDP). It is established that the solar ORC using TDP has a superior performance to the conventional ORC under most working conditions. Results demonstrate that power output of the ORC using TDP ranges from 72 W to 82 W with the increase of evaporating temperature, which shows an improvement of up to 3.3% at a 100 °C evaporating temperature when compared with the power output of the conventional ORC. Energy and exergy efficiencies of the ORC using TDP increase from 11.3% to 12.6% and from 45.8% to 51.3% when the evaporating temperature increases from 75 °C to 100 °C. The efficiency of the ORC using TDP is improved by up to 3.27%. Additionally, the exergy destruction using TDP can be reduced in the evaporator and condenser. The highest exergy efficiency in the evaporator is 96.9%, an improvement of 62% in comparison with that of the conventional ORC, i.e., 59.9%. Thus, the small-scale solar ORC system using TDP is more promising for household application.

On the Solar PV Monitoring System

2019 ◽  
Vol 19 (1) ◽  
pp. 28-32 ◽  
Author(s):  
Muhanned Al-Rawi
Keyword(s):  
Solar Energy ◽  
Monitoring System ◽  
Power Output ◽  
Energy Sector ◽  
Solar Panel ◽  
Free Form ◽  
Solar Pv

AbstractSolar energy is increasingly becoming commonplace in the society with the ever rising electricity bills and reduction in price in solar equipment. Being an “essentially free” form of energy it is necessary to contribute to developments that support or improve the solar energy sector. This paper presents a way to monitor the voltage, current and power output from a solar panel, with the aim of monitoring and projecting the output from a solar farm.

Modeling and Simulation of Solar Irradiance and Daylight Duration for a High-Power-Output Solar Module System

2014 ◽  
Vol 629 ◽  
pp. 475-480 ◽  
Author(s):  
Parvathy Rajendran ◽  
Howard Smith ◽  
Muhammad Hazim bin Masral
Keyword(s):  
Solar Energy ◽  
Power Output ◽  
Solar Irradiance ◽  
Geographical Location ◽  
Poor Performance ◽  
Atmospheric Conditions ◽  
Solar Module ◽  
Solar Powered ◽  
Module Systems ◽  
Module System

Solar energy is the largest available renewable energy for enhancing the endurance of a solar-powered unmanned aerial vehicle (UAV). However, harnessing solar energy is a great challenge because the power output efficiency of solar module systems is only 15% to 30%. A solar-powered UAV has the potential to outperform a battery-powered UAV, particularly in tasks involving a pseudo satellite that requires long operating hours. Atmospheric conditions and geographical location are the main causes of the poor performance of solar modules. Despite the improvements in solar cell efficiency over the years, solar module systems can still barely convert half of the sun’s power into electricity. This limitation hinders the use of current solar module systems for harvesting solar energy. Recent studies have focused not only on the type of solar cells but also on the positioning system. However, understanding and research on the solar irradiance intensity, as well as on the effect of daylight duration on the power output, remain lacking. A comprehensive model was developed to address this gap and investigate how the movement of the sun movement affects the performance of solar module systems. This simulation model found that daylight duration is more important than available solar irradiance. Higher solar irradiance and daylight duration corresponds to a higher power output of the solar module system. Daylight duration also depends on latitude where higher latitudes lead to longer daylight duration. On the other hand, longitudinal coordinates and elevation have minor effects on the estimation of daylight duration. Therefore, the northern hemisphere has more advantages than southern hemisphere during summer and vice versa.

scholarly journals Simulation and Implementation of Grid Tied Solar Photovoltaic System with Fuzzy Control Based Universal Bridge Inverter

2020 ◽  
Vol 6 (12) ◽  
pp. 5-12
Author(s):  
Usha Verma ◽  
N K Singh
Keyword(s):  
Solar Energy ◽  
Fuzzy Set ◽  
Power Output ◽  
Active Power ◽  
Solar Photovoltaic ◽  
Solar Pv ◽  
Pv System ◽  
Efficient Operation ◽  
Current Output ◽  
Power Enhancement

Worldwide renewable energy resources, especially solar energy, are growing dramatically in view of energy shortage and environmental concerns. Large-scale solar photovoltaic (PV) systems are typically connected to medium voltage distribution grids, where power converters are required to convert solar energy into electricity in such a grid-interactive PV system. This study are designing of solar energy system in MATLABSIMULINK environment which can be integrated with the grid for its efficient operation. The grid integration is necessary to ace the system reliable under various environmental conditions. Enhancing the DC input voltage to the inverter so that in its aspect the AC output from the inverter is also enhanced. And designing of a universal bridge inverter and AI based intelligent control for it such that it enhances the power output from the solar PV system. Designing of efficient rules for the inverter control using FUZZY algorithm. This work proposes an optimized active power enhancement method and evaluates the effect of fuzzy based controller for power enhancement on system reliability and power quality in the grid-interactive PV system with cascaded converter modules. Fuzzy set of rules are defined in a manner such that it is proved to be effective in enhancing the current output keeping the grid voltage same and hence the power output from the systems of cascaded PV modules. it can be concluded that if designing a cascaded PV solar system it is possible to increase the active power output from the inverter just by using fuzzy set of rules for firing pulses in the inverter.

Performance Evaluation of the Thermophotovoltaic-Driven Thermoionic Refrigerator

2019 ◽  
Vol 142 (3) ◽  
Author(s):  
Emin Açıkkalp ◽  
Süheyla Yerel Kandemir ◽  
Mohammad H. Ahmadi
Keyword(s):  
Energy Source ◽  
Performance Evaluation ◽  
Solar Energy ◽  
Cooling Rate ◽  
Power Output ◽  
Exergy Efficiency ◽  
Exergy Destruction ◽  
Destruction Rate ◽  
Operation Conditions

Abstract In this study, the thermophotovoltaic (TPV)-driven thermionic refrigerator (TIR) is presented as an alternative refrigerator operated by the solar energy. Solar energy is the main energy source and its performance is analyzed. Power output density of the TPV, cooling rate density, COP, exergy destruction rate densities, and exergy efficiencies are the considered parameters. Calculations are performed numerically; results are presented and discussed. The most suitable operation conditions are defined. According to the results, the cooling rate density is 648 W/m2, power output densities are 1189.86 W/m2 and 667.234 W/m2 for the eg = 0.3 eV and eg = 0.4 eV, and the exergy efficiency of the system is about 0.071.

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