Semi-Transparent Photovoltaic Technology Integration in Smart Buildings

Research conducted over the years has established that the building industry is responsible for a significant portion of the world's energy consumption, accounting for about 30% of the total electricity used. Most of this power usage is directed towards regulating the temperature of buildings, with the primary cause being the glazing systems employed in construction. The main aim of this undertaking is to carry out a thorough analysis of the Cadmium Telluride (CdTe) Solar Cells Semi-Transparent Photovoltaic (STPV) glazing systems. This research implemented experimental testing procedures and numerical models to evaluate the system's optical, thermal, and electrical performance to accomplish this. To perform this analysis, small samples of commercially available thin-film modules that contain CdTe solar cells were utilised for indoor testing. The primary objective of this testing is to quantify the relevant optical, thermal, and electrical parameters that affect the system's performance. This work includes a thorough literature review, which investigates the work that has been done by other researchers and is divided into two main sections. The first section covers the research done on silicon-based solar cells STPV glazing systems. The second section covers the research that has been done on STPV glazing systems with integrated CdTe solar cells. The literature review chapter was followed by a characteristics process that quantifies the optical, thermal, and electrical attributes. This approach was based on a set of experimental tests, these experiments were developed to be carried out in a controlled lab setting and implemented on six different CdTe STPV glazing samples, as well as two clear double-glazing samples and a clear single-glazing sample. To carry out these tests, a scaled-down testbed was built based on Guarded Hot Box and Mobile Window Thermal Test, in addition to the utilising of a heat flux sensor and thermostats that measure the temperatures on both sides of the glazing surfaces, this kit was used to calculate the Heat Transfer Coefficient (U-value). As for the Solar Heat Gain Coefficient (SHGC) and optical characteristics a spectrometer was used. A solar simulator was developed, to carry out the electrical characterisation tests. To achieve constant solar irradiance (1000 W/m2) while maintaining a similar movement, the developed solar simulator was split into two components. First, the sun simulator, which is the stationary part, consists of nine halogen lamps bolted into a frame and the illuminations of these lamps are controlled by a transformer. The second part is the movement simulator, which is a flat plate that moves in two axes. The movement is powered by two DC motors, an Electrical linear actuator that moves vertically, helped by a spherical ball joint installed below the flat plate, and a Geared DC motor which operates in an angular manner. A control unit operated by the data logger has been installed. This unit contains two DC-Motor Drivers with an internal DC power supply and multiple potentiometers to control the speed of both motors in case the unit is operated manually. These outcomes were later used in building the required simulation profiles to evaluate the overall energy consumption of the buildings when utilising semi-transparent photovoltaic glazing systems. The overall energy assessment will be conducted in two stages, the first stage was conducted through a numerical model developed by the EnergyPlus software tool embedded within Designbuilder software. In the second stage, a load flow analysis on a grid level was carried out employing PowerFactory (DIgSILENT) software. The evaluation process has indicated that utilising Argon filled double-glazing system would be the most efficient glazing system from the overall energy consumption point of view. As the Argon-filled double-glazing system has an overall energy consumption of 6477.34 kW, 6590.8 kW, and 8521.04 kW when covering 30%, 60%, and 100% of the wall area respectively. This result is caused by the fact that the heating load is the dominant load in the location of the simulation.