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This study presents the research study, both theoretical and experimental, on the effect of double pass solar air heater (DPSAH) using staggered-diamond shaped fins effects. Diamond shaped fins are considered to have the potential to improve the convective heat transfer and increase energy efficiency as well. Forty number of diamond shaped fins have been used in this experiment which have been fixed to the plate absorber where there are four mass flow rates (0.0104 kg/s, 0.0157 kg/s, 0.0209 kg/s, 0.0261 kg/s) used and three variations of solar radiations (600 W/m2, 800 W/m2 and 1000 W/m2). The effect of mass flow rates, solar radiation and outlet temperature has greatly affected the overall performance of DPSAH with staggered-diamond shaped fins. For the computational domain fluid, the configuration of mass flow rates and solar radiation is analyzed using COMSOL Multiphysics 5.6.1, hence the actual experiment has been carried out based on the simulation results. The highest thermal efficiency obtained for experiment and simulation were 59.34% and 62.01% for mass flow rates of 0.0261 kg/s using solar irradiance of 1000 W/m2.

The societal and economic reliance on non-renewable energy sources, primarily fossil fuels, has raised concerns about an imminent energy crisis and climate change. The transition towards renewable energy sources faces challenges, notably in understanding turbine shear forces within wind technology. To address this gap, a novel solution emerges in the form of the ducted horizontal-axis helical wind turbine. This innovative design aims to improve airflow dynamics and mitigate adverse forces. Computational fluid dynamics and experimental assessments were employed to evaluate its performance. The results indicate a promising technology, showcasing the turbine’s potential to harness energy from diverse wind sources. The venturi duct aided in the augmentation of the velocity, thereby increasing the maximum energy content of the wind by 179.16%. In addition, 12.16% of the augmented energy was recovered by the turbine. Notably, the integration of a honeycomb structure demonstrated increased revolutions per minute (RPM) by rectifying the flow and reducing the circular wind, suggesting the impact of circular wind components on turbine performance. The absence of the honeycomb structure allows the turbine to encounter more turbulent wind (circular wind), which is the result of the movement of the fan. Strikingly, the downwash velocity of the turbine was observed to be equal to the incoming velocity, suggesting the absence of an axial induction factor and, consequently, no back force on the system. However, limitations persist in the transient modelling and in determining optimal performance across varying wind speeds due to experimental constraints. Despite these challenges, this turbine marks a significant stride in wind technology, highlighting its adaptability and potential for heightened efficiency, particularly at higher speeds. Further refinement and exploration are imperative for broadening the turbine’s application in renewable energy generation. This research emphasizes the turbine’s capacity to adapt to different wind velocities, signaling a promising avenue for more efficient and sustainable energy production.

Photovoltaic thermal (PVT) technologies have a significant downside in addition to their numerous advantages. PVT technologies are constrained by the fact that its photovoltaic module gains heat due to exposure to solar irradiance, which reduces the photovoltaic efficiency. Jet impingement is one of the most effective methods to cool a photovoltaic module. An indoor experiment using a solar simulator was conducted on a bifacial PVT solar collector cooled by a reversed circular flow jet impingement (RCFJI) to evaluate the energy performance of the PVT collector. The study was conducted under a constant solar irradiance of 900W/m2 and flowrate (mass) ranging from 0.01 to 0.14 kg/s. Three bifacial modules with 0.22, 0.33, and 0.66 packing factors were mounted 25 mm above the RCFJI for cooling. The 0.66 packing factor module recorded the highest photovoltaic efficiency of 10.91 % at 0.14 kg/s flowrate (mass). Meanwhile, the 0.22 and 0.33 packing factors recorded a photovoltaic efficiency of 4.50 % and 6.45 %, respectively. The highest thermal efficiency recorded under the same operating condition was 61.43 %, using a 0.66 packing factor. Overall, the highest combined photovoltaic thermal (PVT) efficiency for 0.22, 0.33, and 0.66 was 56.62 %, 61.88 %, and 72.35 %, respectively.

The airfoil blade is the primary component of a wind turbine, and its aerodynamic properties play a crucial role in determining the energy conversion efficiency of these blades. Many researchers have proposed different airfoil modifications intending to enhance the aerodynamic characteristics and limit the unsteady interaction with the atmospheric boundary layer. This study evaluates the benefits of mounting wedge tails (WTs) on the trailing edge of an airfoil. The aerodynamic characteristics of a 2-D, steady-state NACA 0021 airfoil featuring the wedge tails (WT) and fish wedge tails (FWT) were studied computationally by employing the shear stress transport (SST) k-ω turbulence model. Different WT and FWT configurations were studied at various wedge length (L) to wedge height (H) ratios, L/H, at the airfoil's trailing edge. The effects of different L/H ratios, including L/H > 1, L/H = 1, and L/H

The electrical output of photovoltaic (PV) modules degrades with continued exposure to extreme temperatures caused by solar radiation. The uniqueness of this research lies in the utilization of multidirectional fins with varying heights, which effectively accelerate heat transfer in PV cooling systems by inducing a transition in the boundary layer within the confined zone of the fins. The research aims to investigate the effect of using Multidirectional Tapered Fin Heat Sinks (MTFHS) to improve the efficiency of PV modules by utilizing aluminum alloy material as heatsinks. The proposed multidirectional design aims to facilitate enhanced heat transfer by promoting airflow in the central area of the PV module. The experimental procedures in our study differ from previous research as we utilized the latest generation of PV modules (405 Wp, PERC Half-cut cells) to fill the discrepancy between laboratory-based investigations and practical applications. Two PV modules were tested for an outdoor parametric analysis under outdoor operating conditions, with solar irradiance recorded from 200 to 1000 W/m2 and ambient temperatures ranging from 26° to 38 °C. Findings indicated that the proposed MTFHS could lower PV module temperatures by 12 ⁰C. Reduced temperature boosts PV module efficiency by 1.53%. Cooling advancements proved vital in contributing to sustainability in PV system installations.

The primary limitation of photovoltaic thermal (PVT) technologies is the adverse effect of solar irradiance-induced heat absorption. In order to enhance the efficiency of the system, it is essential to incorporate a cooling mechanism. The utilization of a reversed circular flow jet impingement (RCFJI) was implemented as a cooling mechanism for a bifacial PVT solar collector. This study aims to analyze the exergy efficiency of a RCFJI bifacial PVT solar collector. An indoor experiment was conducted using a solar simulator with a solar irradiance of 500–900W/m2 and a mass flow rate of 0.01–0.14 kg/s. The findings revealed that the highest photovoltaic exergy attained was 47.2W under solar irradiance of 900W/m2 and a mass flow rate of 0.14 kg/s. Meanwhile, the highest thermal exergy attained was 9.67W under 900W/m2 solar irradiance and 0.14 kg/s mass flow rate. Overall, the exergy efficiency attained a maximum value of 12.64% under 900W/m2, while the lowest exergy efficiency observed was 12.25% under 500W/m2. In addition, the optimal operational mass flow determined was 0.06 kg/s. The findings indicate that the optimal performance of the RCFJI bifacial PVT solar collector is achieved through higher exergy efficiency, which signifies a reduced requirement for input energy. Consequently, more energy can be harnessed.

Renewable energy resources especially wind energy, have seen significant growth in the worldwide energy market as clean energy sources. This has brought attention to areas with low and moderate wind speeds. Small-scale Darrieus vertical axis wind turbine (VAWT) with omnidirectional capability captures potential energy in these areas at a cost-effective scale. Numerous studies have been conducted to optimise their design, hence improving the performance of these turbines. Turbine solidity, σ, representing the ratio of the overall area of the blades over the swept area of the turbine, is one of the influential geometrical factors that significantly affect wind turbine performance. Previous studies on solidity focused on the number of blades and blade length variations, while the study on turbine diameter is limited. Hence, this paper intends to numerically investigate the effect of solidity that corresponds to different turbine diameters. Power performance and flow characteristics are investigated closely according to different solidity, σ and tip speed ratios, λ using high-fidelity computational fluid dynamic (CFD) method, which solves the unsteady Reynolds-Averaged Navier-Stokes (RANS) equations. Solidity and tip speed ratios vary within a wide range of 0.3 – 0.7 and 0.5 – 4.5, respectively. The results show that decreasing the turbine solidity from 0.7 to 0.3 could significantly increase the maximum power coefficient, Cp, by 30%. However, turbine with high solidity (σ = 0.7) generate much higher instantaneous moment coefficient, Cm than the low solidity turbine (σ = 0.3), but at lower λ and a narrower range of λ. The difference in turbine's performance between high and low solidity turbine is attributed to stall experienced by the blade at low λ and the blockage effect experienced by the turbine at moderate to high λ that significantly influence the energy generation at downstream region

Solar irradiation data is essential for the feasibility of solar energy projects. Notably, the intermittent nature of solar irradiation influences solar energy use in all forms, whether energy or agriculture. Accurate solar irradiation prediction is the only solution to effectively use solar energy in different forms. The estimation of solar irradiation is the most critical factor for site selection and sizing of solar energy projects and for selecting a suitable crop selection for the area. But the physical measurement of solar irradiation, due to the cost and technology involved, is not possible for all locations across the globe. Numerous techniques have been implemented to predict solar irradiation for this purpose. The two types of approaches that are most frequently employed are empirical techniques and artificial intelligence (AI). Both approaches have demonstrated good accuracy in various places of the world. To find out the best method, a thorough review of research articles discussing solar irradiation prediction has been done to compare different methods for solar irradiation prediction. In this paper, articles predicting solar irradiation using AI and empirical published from 2017 to 2022 have been reviewed, and both methods have been compared. The review showed that AI methods are more accurate than empirical methods. In empirical models, modified sunshine-based models (MSSM) have the highest accuracy, followed by sunshine-based (SSM) and non-sunshine-based models (NSM). The NSM has a little lower accuracy than MSSM and SSM, but the NSM can give good results in sunshine data unavailability. Also, the literature review confirmed that simple empirical models could predict accurately, and increasing the empirical model's polynomial order cannot improve results. Artificial neural networks (ANN) and Hybrid models have the highest accuracy among AI methods, followed by support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS). The increase in efficiency by hybrid models is minimal, but the complexity of models requires very sophisticated programming knowledge. ANN's most important input factors are maximum and minimum temperatures, temperature differential, relative humidity, clearness index and precipitation.

This research focuses on the thermal properties of three distinctive paraffin waxes—PCMA, PCMB, and PCMC—each characterized by a specific melting point. The crucial phase transition temperature intervals and latent heat values were examined using differential scanning calorimetry (DSC) in the temperature range of 0 °C to 80 °C. These parameters are pivotal for the effective application of these phase change materials (PCMs) in building envelopes, influencing the overall heat storage performance. The study delved into the development and encapsulation of blends containing both the phase change material (PCM) and graphite. This involves combining the chosen PCM with graphite powder and examining the weight ratios of 10% and 20%. The thermal characteristics of these blends revealed that a 10% ratio of graphite powder proved effective in improving the PCM with graphite. This resulted in a reduced range of melting and solidification temperatures while maintaining the essential chemical structure of the PCM without additives. Furthermore, the practical application of PCM–graphite composites within a building’s envelope was explored, revealing a substantial reduction in heat transfer from the exterior to the interior of the building. This underscores the potential for energy-efficient building designs.

Solar energy is an accessible and sustainable energy source to meet the rising air conditioning demand. This study investigated the performance of solar thermal assisted sorption cooling systems, namely, solar absorption (SABC) and adsorption cooling (SADC) systems. A novel analytical approach to determine the techno-economic potential for specific climate conditions has been developed. The climatic conditions of Malaysia were used as a case study. Both cooling systems were simulated using TRNSYS coupled with VISUAL BASIC and optimized using a multi-objective optimization algorithm implemented in MATLAB. The results show that the COPchiller and collector area have the most significant impact on the performance and primary energy consumption of SABC and SADC systems. On average, 36 % and 27 % of the useful energy gain of solar collectors was converted to the cooling effect in SABC and SADC systems, respectively. Meanwhile, the minimum amount of non-renewable primary energy, the non-renewable primary energy savings ratio, and the least payback period are 0.57 and 0.39, 7.6 % and 7.5 %, and 4 and 9 years, for the SABC and SADC systems, respectively.

Mersing is one of the places that have the potential for wind power development in Malaysia. Researchers often suggest it as an ideal place for generating electricity from wind power. However, before a location is chosen, several factors need to be considered. By analyzing the location ahead of time, resource waste can be avoided and maximum profitability to various parties can be realized. For this study, the focus is to identify the distribution of the wind speed of Mersing and to determine the optimal average of wind speed. This study is critical because the wind speed data for any region has its distribution. It changes daily and by season. Moreover, no determination has been made regarding selecting the average wind speed used for wind studies. The wind speed data is averaged to 1, 10, 30, and 60 minutes and used to find the optimal wind speed average. This study used Kolmogorov-Smirnov and Chi-Square as the goodness of fit. The finding shows that the wind speed distribution in Mersing varies according to the time average used and the best fit distribution is Gen. Gamma. In contrast, the optimal average wind speed is 10 minutes due to the highest similarity results with 1-minute data. These affect the reliability of the finding, accuracy of the estimation and decisions made. Therefore, the implementation of this study is significant so that the wind distribution in a particular area is more accurate.

This study presents a prediction model for comparing the performance of six different photovoltaic (PV) modules using artificial neural networks (ANNs), with simple inputs for the model. Cell temperature (Tc), irradiance, fill factor (FF), short circuit current (Isc), open-circuit voltage (Voc), maximum power (Pm), and the product of Voc and Isc are the inputs of the neural networks’ processes. A Prova 1011 solar system analyzer was used to extract the datasets of IV curves for six different PV modules under test conditions. As for the result, the highest FF was the mono-crystalline with an average of 0.737, while the lowest was the CIGS module with an average of 0.66. As for efficiency, the most efficient was the mono-crystalline module with an average of 10.32%, while the least was the thin-film module with an average of 7.65%. It is noted that the thin-film and flexible mono-modules have similar performances. The results from the proposed model give a clear idea about the best and worst performances of the PV modules under test conditions. Comparing the prediction process with the real dataset for the PV modules, the prediction accuracy for the model has a mean absolute percentage error (MAPE) of 0.874%, with an average root mean square error (RMSE) and mean absolute deviation (MAD) of, respectively, 0.0638 A and 0.237 A. The accuracy of the proposed model proved its efficiency for predicting the performance of the six PV modules.

The application of AAC has increased considerably in Malaysia since the 1990s. The usage of AAC has some advantages, but it also has negative environmental impacts since rejected concrete will become landfill. This study aimed to use AAC waste powder as a material that would partially replace the sand content to produce a new form of Autoclaved Aerated Concrete (AAC). The physical and mechanical properties of the newly developed AAC were investigated. This paper presents improved mechanical and physical properties of the new form of recycled AAC concrete. Besides these improvements, using recycled AAC could lower production costs. Furthermore, the usage of this recycled waste powder is both economically and environmentally advantageous. This study found that when recycled AAC was substituted for sand, AAC with a fine recycled powder content of 30% had a compressive strength that was around 16% higher than conventional AAC and between 29% and 156% higher than any value attained utilizing an industrial waste product. This study also confirmed that the greater strength could be identical to a higher tobermorite phase and that the recycled AAC surface showed a finer crystalline morphology.