Abstract: Thermal performance is considered to be a key measure in building sustainability. One of the technologies used in the current building sustainable design is the rooftop solar PV power generators. The application of this type of technology has expanded vastly during the last five years in many countries. This paper studies the effect of roof shading developed by the solar PV panels on dwellings’ thermal performance. The analysis in this work is performed by using two types of packages: “AccuRate Sustainability” for rating the energy efficiency of residential building design, and “PVSYST” for the solar PV power system design. The former package is used to calculate the annual heating and cooling load, and the later package is used to evaluate the power production from the roof top PV system. The analysis correlates the electrical energy generated from the PV panels to the change in the heating and cooling load due to roof shading. Different roof orientation, roof inclination, roof insulation, as well as PV panel area are considered in this study. The analysis shows that the drop in energy efficiency due to the shaded area of the roof by PV panels is negligible compared to the energy generated by these panels.
Abstract: Various solar energy technologies exist and they have
different application techniques in the generation of electrical power.
The widespread use of photovoltaic (PV) modules in such
technologies has been limited by relatively high costs and low
efficiencies. The efficiency of PV panels decreases as the operating
temperatures increase. This is due to the affect of solar intensity and
ambient temperature. In this work, Computational Fluid Dynamics
(CFD) was used to model the heat transfer from a standard PV panel
and thus determine the rate of dissipation of heat. To accurately
model the specific climatic conditions of the United Arab Emirates
(UAE), a case study of a new build green building in Dubai was
used. A finned heat pipe arrangement is proposed and analyzed to
determine the improved heat dissipation and thus improved
performance efficiency of the PV panel. A prototype of the
arrangement is built for experimental testing to validate the CFD
modeling and proof of concept.
Abstract: Due to the non-linear characteristics of photovoltaic
(PV) array, PV systems typically are equipped with the capability of
maximum power point tracking (MPPT) feature. Moreover, in the
case of PV array under partially shaded conditions, hotspot problem
will occur which could damage the PV cells. Partial shading causes
multiple peaks in the P-V characteristic curves. This paper presents a
hybrid algorithm of Particle Swarm Optimization (PSO) and
Artificial Neural Network (ANN) MPPT algorithm for the detection
of global peak among the multiple peaks in order to extract the true
maximum energy from PV panel. The PV system consists of PV
array, dc-dc boost converter controlled by the proposed MPPT
algorithm and a resistive load. The system was simulated using
MATLAB/Simulink package. The simulation results show that the
proposed algorithm performs well to detect the true global peak
power. The results of the simulations are analyzed and discussed.