Abstract

This study aimed to develop a building-integrated photovoltaic (BIPV) device and optimal control methods that increase the photovoltaic (PV) efficiency and visual comfort of the indoor space. A louver-type PV-integrated shading device was suggested and an artificial neural networks (ANN) model was developed to predict PV electricity output, work plane illuminance, and daylight glare index (DGI). The slat tilt angle of the shading device was controlled to maximize PV electricity output based on three different strategies: one without visual comfort constraints, and the other two with visual comfort constraints: work plane illuminance and DGI. Optimal tilt angle was calculated using predictions of the ANN. Experiments were conducted to verify the system modeling and to evaluate the performance of the shading device. Experiment results revealed that the ANN model successfully predicted the PV output, work plane illuminance, and DGI. The PV-integrated shading device was more efficient in producing electricity than the conventional wall-mount PV systems, the control method without visual comfort constraints was most efficient in generating electricity than the other two with such constraints, and excluding the constraints resulted in less comfortable visual environment and reduced energy benefit. From the results analysis, it can be concluded that based on the accurate predictions, the PV-integrated shading device controlled using the proposed methods produced more electricity compared to the wall-mount counterpart.

Highlights

  • Solar power is one of the most promising, reliable, and environmentally friendly renewable energy technologies

  • PV + work plane illuminance (WP) + daylight glare index (DGI) method were lower than that of the PV output only (PV-only) method, their energy savings from natural lighting led to higher overall energy savings

  • Three PV-integrated shading device (PVIS) control methods including PV-only method, PV + work plane illuminance (PV + WP) method, and PV + work plane illuminance + daylight glare index (PV + WP + DGI) method were developed for controlling the louver slat angle and their performance was experimentally tested in the scale model

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Summary

Introduction

Solar power is one of the most promising, reliable, and environmentally friendly renewable energy technologies. The substantial increase in the consumption of these fossil fuels has resulted in significant CO2 emissions, accelerating the greenhouse effect which is the cause of global warming. To confront this issue, it is necessary to replace fossil fuels with renewable resources such as wind and solar energy and to develop strategies for the effective use of natural resources [1,2]. The power conversion efficiency of PV systems has been continuously improved due to research on many aspects including materials and cells [3].

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