The aim of this investigation is to evaluate the recent advances in the field of solar absorption cooling systems from the viewpoint of solar collector types. A review in the area of photovoltaic thermal (PVT) absorption cooling systems is conducted. This review includes experimental and computational work focusing on collector types and their efficiencies and performance indicators. Compared to vapour compression air conditioning systems, 50% of primary energy was saved by using solar absorption cooling systems and 10-35% maximum electrical efficiency of PVT was achieved. This review shows that Coefficient of Performance (COP) for solar cooling systems is in the range of 0.1-0.91 while the thermal collector efficiencies are in the range of 0.06-0.64. The average area to produce cooling for single effect absorption chillers for experimental and computational projects is 4.95 m 2 /kW c and 5.61 m 2 /kW c respectively. The specific area for flat plat collector (FPC) is in the range of 2.18-9.4 m 2 /kW c , while for evacuated tube collector (ETC) is in the range of 1.27-12.5 m 2 /kW c. For concentrated photovoltaic thermal collector (CPVT) and PVT, the average area to produce cooling for solar absorption chillers are 2.72 m 2 /kW c and 3.1 m 2 /kW c respectively.

Research into photovoltaic thermal systems is important in solar technologies as photovoltaic thermal systems are designed to produce both electrical and thermal energy, this can lead to improved performance of the overall system. The performance of photovoltaic thermal systems is based on several factors that include photovoltaic thermal materials, design, ambient temperature, inlet and outlet fluid temperature and photovoltaic cell temperature. The aim of this study is to investigate the effect of photovoltaic thermal outlet water temperatures and solar cell temperature on both electrical and thermal efficiency for different range of inlet water temperature. To achieve this, a mathematical model of a photovoltaic thermal system was developed to calculate the anticipated system performance. The factors that affect the efficiency of photovoltaic thermal collectors were discussed and the outlet fluid temperature from the photovoltaic thermal is investigated in order to reach the highest overall efficiency for the solar cooling system. An average thermal and electrical efficiency of 65% and 13.7%, respectively, was achieved and the photovoltaic thermal mathematical model was validated with experimental data from literature.

Summary This paper presents a mathematical modeling and current control of DFIG wind turbine system in the presence of unbalanced and harmonic distortions in the grid voltage. A proportional resonant (PR) current controller is modeled and implemented to reduce the impacts caused by the presence of double‐frequency, fifth and seventh harmonic components in the generator torque, active and reactive power and the grid active power to which the wind generation system is connected. To reduce the impacts of the presence of the harmonics and unbalanced voltage in the stator and grid active and reactive powers, the dq‐axis current components of these harmonics are controlled separately in the rotor and grid side converters. The use of PR controllers represents the addition of a specific function that eliminates the negative sequence and harmonic components from the rotor current components which reduce the oscillations of the generator torque and grid active power. The performance of the proposed control algorithm is validated through experiments and evaluated during the grid disturbances.

This work presents an alternative to the conventional photovoltaic maximum power point tracking (MPPT) methods, by using an opposition-based learning firefly algorithm (OFA) that improves the performance of the Photovoltaic (PV) system both in the uniform irradiance changes and in partial shading conditions. The firefly algorithm is based on fireflies’ search for food, according to which individuals emit progressively more intense glows as they approach the objective, attracting the other fireflies. Therefore, the simulation of this behavior can be conducted by solving the objective function that is directly proportional to the distance from the desired result. To implement this algorithm in case of partial shading conditions, it was necessary to adjust the Firefly Algorithm (FA) parameters to fit the MPPT application. These parameters have been extensively tested, converging satisfactorily and guaranteeing to extract the global maximum power point (GMPP) in the cases of normal and partial shading conditions analyzed. The precise adjustment of the coefficients was made possible by visualizing the movement of the particles during the convergence process, while opposition-based learning (OBL) was used with FA to accelerate the convergence process by allowing the particle to move in the opposite direction. The proposed algorithm was simulated in the closest possible way to authentic operating conditions, and variable irradiance and partial shading conditions were implemented experimentally for a 60 [W] PV system. A two-stage PV grid-connected system was designed and deployed to validate the proposed algorithm. In addition, a comparison between the performance of the Perturbation and Observation (P&O) method and the proposed method was carried out to prove the effectiveness of this method over the conventional methods in tracking the GMPP.