Photovoltaic Potential Research Articles

Estimation of Photovoltaic Potential of Solar-Powered Electric Vehicle: Case Study of Commuters on Donghae Expressway, Korea

Estimation of Photovoltaic Potential of Solar-Powered Electric Vehicle: Case Study of Commuters on Donghae Expressway, Korea

Multifaceted anchoring ligands for uniform orientation and enhanced cubic-phase stability of perovskite quantum dots

All-inorganic CsPbI3 perovskite quantum dots (PQDs) hold significant potential for next-generation photovoltaics due to their unique optoelectronic properties, and the surface-bound ligand playing a key role in the stability and functionality of CsPbI3 PQDs. Initially used long-chain ligands in PQDs synthesis stabilize the black phase but hinder charge transport when employed to solar cells, necessitating their replacement with shorter ones. However, this leads to the formation of surface defects and loss of tensile strain, resulting in the transition to the undesired orthorhombic phase (δ-phase) and compromising PQD solar cell performance. Therefore, developing a ligand exchange process that achieves the optimal balance between conductivity and stability in PQD solid films continues to be a significant challenge. To address these issues, we developed an efficient ligand-exchange process utilizing a multifaceted anchoring ligand, 2-thiophenemethylammonium iodide (ThMAI). The larger ionic size of ThMA+ compared to Cs+ facilitates the restoration of surface tensile strain in PQDs, while its thiophene and ammonium groups enable effective passivation of surface defects. Owing to these advantages, ThMAI-treated CsPbI3 PQD thin films exhibit improved carrier lifetime, uniform PQD orientation, and increased ambient stability. As a result, the ThMAI-treated CsPbI3 PQD solar cells demonstrate an improved power conversion efficiency (PCE) of 15.3 % and an enhanced device stability.

Examining effects of air pollution on photovoltaic systems via interpretable random forest model

Renewable energy plays a vital role in power generation and solar photovoltaic systems due to resource availability throughout the year. This work aims to investigate the impact of air pollutants and meteorological parameters on the performance of the photovoltaic systems locally, taking into consideration the advantages of the photovoltaic power potential of the SW part of Romania, where Craiova is located (average solar radiation intensity >1350 kWh/m2/year). This study is based on a one-year dataset provided by a sensor that monitors particulate matter concentrations, volatile organic compounds, dioxide of carbon, ozone, noise, formaldehyde and three climate parameters (temperature, pressure, and relative humidity). The research methodology applies an innovative interpretable random forest model emphasising the implications of air pollution for photovoltaic systems. The proposed machine learning model was trained to predict the particulate matter level in air based on the basic environmental variable measurements. The study presents six random forest models of varying complexity, which reach the accuracy of classification for the selected problem up to 99 %, and applies the Shapley Additive Explanations technique to interpret the decision-making model. The observation regarding the highest concentration of particulate matter occurring during cold months, which typically do not align with peak solar irradiance, underscores the importance of considering various environmental factors in solar energy planning. With its practical implications, this insight offers decision-makers valuable information about the feasibility of optimising solar energy generation despite seasonal variations in air pollution levels, directly addressing their needs and concerns.

Hybrid wind-solar energy potential modeling using ERA5 and solar irradiation data in google Earth Engine

Renewable energies play a significant role in mitigating the climate change impacts. Wind and solar energy are projected to supply larger amount to the total renewable energy capacity of many nations. Long-term wind and solar data availability and analysis is vital for sustainable renewable energy farming. In this research, we analyze wind speed u- and v-components at 10 m height of the ERA5 daily reanalysis aggregates at a mesh of 31 Km during a long period (2010–2020) over the Red Sea and the Gulf of Suez coasts of Egypt. Google Earth Engine (GEE) code is developed and used for the analysis. The prime objective is to derive estimates on the spatio-temporal variability of speed, direction, and the wind energy estimates in the area. Further, the solar energy potential has been evaluated using reference data of the PVOUT – Photovoltaic power potential (kWh/m2/day) data, at nearly 1 km resolution, which is normalized at the evaluated sites, and then used to rank sites with their solar energy potential. Evaluation of estimates is carried out at selected thirteen sites distributed along the coasts to better understand the hybrid wind-solar energy potential. Frequency analysis is carried out to the wind speed spatial estimates to demarcate highest frequency wind events potential for wind farming. Reference in-situ wind speed observations available at daily and monthly time scales for Hurghada weather station is used for investigating the reanalysis data performance. The Hurghada site had the highest average wind speed (6.7 m s−1), frequency of events (75 %), and mean daily (60.4 kWh) and annual (22.02 MWh) wind energy. The windiest time intervals were the September month, 2017 year, and the summer season. The north had wind energy directions of 130°, while the south had 110°. Trend analysis showed declining trends for northern locations and rising yearly wind speed estimates for Berenice (0.005) and Halayeb (0.002). El-Tor location had the highest solar energy output, with a daily mean of 5.52 kWh/m2 and an annual mean of almost 2015 kWh/m2. The Hurghada, Jemsa, G. Zeit, and El-Tor sites achieved the highest rankings in terms of hybrid wind-solar energy potential. The results can be very valuable for optimal location of hybrid solar-wind energy facilities and provide viable and promising solutions for sustainably meeting Egypt's growing clean energy demands.

Determination of photovoltaic hydrogen production potential in Portugal: a techno-economic analysis

Determination of photovoltaic hydrogen production potential in Portugal: a techno-economic analysis

Band Engineering of Perovskite Quantum Dot Solids for High-Performance Solar Cells.

CsPbI3 perovskite quantum dot (PQD) shows high potential for next-generation photovoltaics due to their tunable surface chemistry, good solution-processability and unique photophysical properties. However, the remained long-chain ligand attached to the PQD surface significantly impedes the charge carrier transport within the PQD solids, thereby predominantly influencing the charge extraction of PQD solar cells (PQDSCs). Herein, a ligand-induced energy level modulation is reported for band engineering of PQD solids to improve the charge extraction of PQDSCs. Detailed theoretical calculations and systemic experimental studies are performed to comprehensively understand the photophysical properties of the PQD solids dominated by the surface ligands of PQDs. The results reveal that 4-nitrobenzenethiol and 4-methoxybenzenethiol molecules with different dipole moments can firmly anchor to the PQD surface through the thiol group to modulate the energy levels of PQDs, and a gradient band structure within the PQD solid is subsequently realized. Consequently, the band-engineered PQDSC delivers an efficiency of up to 16.44%, which is one of the highest efficiencies of CsPbI3 PQDSCs. This work provides a feasible avenue for the band engineering of PQD solids by tuning the surface chemistry of PQDs for high-performing solar cells or other optoelectronic devices.

City-Level Solar Photovoltaic Potential Using Integrated Surface Models and Himawari Satellite in Jakarta and Bandung Indonesia

This research focuses on the detailed modeling of solar PV (Photovoltaic) in urban areas by integrating a detailed reconstructed digital surface model (DSM) and high-temporal-resolution satellite data. This study introduces enhancing method for open digital surface model from medium to high resolution to capture building height details, and integrating the new DSM with high-temporal satellite data to get detail spatial and temporal resolution of solar PV. The DSM reconstruction, building heights are determined using a combination of multi-data and multi-machine learning regression approaches to achieve building height results closely aligned with actual height. In Jakarta, building heights ranged from 5 to 223 m, while in Bandung, they ranged from around 3.58 to 254 m. The combination scenarios had a mean absolute error of 1.584 m, and the coefficient of determination (R2) was 0.754. The integration of new DSM detail data and high-temporal data employs an approach to integrate surface solar irradiance by shadow, sky view factor, and reflectance irradiance from surrounding object. The annual average energy potential in Jakarta and Bandung ranges from 260 to 420 W/Wp. Areas near tall buildings exhibit lower potential because of the shadow effect and sky view factor. This research hopefully can contribute to urban planning for carbon neutrality by providing a more detailed understanding of solar PV potential in urban areas in the absence of detailed data limitations.

Chlorination of benzyl group on the terminal unit of A2-A1-D-A1-A2 type nonfullerene acceptor for high-voltage organic solar cells

Benzotriazole (BTA)-based A2-A1-D-A1-A2 type wide-bandgap (WBG) non-fullerene acceptors (NFAs) have shown promising potential in indoor photovoltaic, and in-depth investigation of their structure-property relationship is of great significance. Herein, we explored the chlorination effect of the side chain on the terminals. We introduced Cl atoms into the benzyl side chains in parent BTA5 to synthesize two NFAs, BTA5-Cl with mono-chlorinated benzyl groups and BTA5-2Cl containing bi-chlorinated benzyl groups. We chose D18-Cl with deep-energy levels and strong crystallinity to pair with these three acceptors, affording high photovoltage and photocurrent. With the stepwise chlorination, the open-circuit voltage (VOC) values decrease from 1.28, 1.22, to 1.20 V, while the corresponding power conversion efficiencies (PCEs) improve from 5.07 %, 9.15 %, to 10.96 %. Compared with BTA5-based OSCs, introducing Cl atoms downshifts the energy levels and slightly increases the non-radiative energy loss (0.14 < 0.17 < 0.19 eV), resulting in a sequential decrease in VOC. However, more chlorine atom replacements produce more effective exciton dissociation, higher charge transfer, and balanced carrier mobility in the blend films, ultimately achieving better PCEs. This work indicates that chlorination of the benzyl group on the terminals can improve the device's performance, implying good application potential in indoor photovoltaics.

Exploring spin photovoltaics in defective armchair phosphorene nanoribbons

This study explores the spin photovoltaic potential within armchair phosphorene nanoribbons (APNRs) that feature a periodic distribution of monovacancies (MVs) under the influence of light radiation. We investigate spin-semiconducting behavior induced by MV defects by utilizing both the mean-field Hubbard approximation and the self-consistent non-equilibrium Green's function model. This behavior is characterized by localized and anisotropic band structures around the Fermi energy, particularly within the antiferromagnetic phase. The existence of spin-splitting band gaps in defective APNRs not only enables the crafting of spin-optoelectronic nanodevices but also allows for the manipulation of electronic structure behavior with applied electric fields in both the vertical and transverse directions. Notably, the implementation of electric fields, offering tunability in electronic structure, results in varied spin photovoltaic responses encompassing a broad spectrum of photon energies from visible to ultraviolet. This research reveals promising avenues for advancing the field of spin-optoelectronic devices by MVs in APNRs.

Tuning the photovoltaic potential of thiazole based materials via incorporation of selenophene and electron acceptors rings at peripheral positions: A DFT approach

The non-fullerene acceptor (NFA) chromophores have sparked scientific and economic interest, due to their rapid advancements in power conversion efficiencies. Therefore, a series of new chlorothiazole based compounds (STM1-STM6) with A1–π–A2–π–A1 configuration was designed using reference chromophore (STMR). Structural modifications were made via incorporating selenophene and extended acceptor units, to enhance photovoltaic response in the designed materials. Density functional theory/time dependent-density functional theory (DFT/TD-DFT) calculations were executed at M06/6-311G (d,p) level to investigate key electronic and photovoltaic properties of STM1-STM6. So, various analyses such as UV–Visible, frontier molecular orbitals (FMOs), transition density matrix (TDM), density of states (DOS), open circuit voltage (Voc) and binding energy (Eb) were conducted to comprehend the photovoltaic properties. The designing in structural aspects with terminal acceptors and π-linker induced a reduction in energy gaps (ΔE = 2.078–2.237 eV) with an enhancement in the bathochromic shift (λmax = 744.650–798.250 nm in chloroform) than reference compound. A higher exciton dissociation rate was observed in all the compounds due to lower binding energy values (Eb = 0.525–0.572 eV). Additionally, TDM and DOS findings further endorsed the effective charge delocalization from HOMO to LUMO. Among all the examined compounds, STM3 exhibited the smallest band gap (2.078 eV), highest absorption maxima (798.250 nm), and the lowest exciton binding energy (0.525 eV), indicating significant electronic properties. Moreover, Voc analysis was conducted with respect to HOMOPBDBT-LUMOacceptor for all the designed chromophores; consequently, STM2 demonstrated a substantial Voc value of 1.647 V. Similarly, electron hole analysis was also conducted and significant electron and hole density was observed in all the investigated compounds, especially in STM2. The entitled compounds with photovoltaic potential would be considered as promising materials for the development of solar energy devices.

Performance enhancement of inorganic Cs2AgInBr6-based perovskite solar cell by numerical simulation

To fulfil the growing need for energy, researchers are consistently working on enhancing the effectiveness of solar cells. Keeping the same goal in mind, a completely inorganic Cs2AgInBr6-based perovskite solar cell (PSC) is simulated by the SCAPS 1D simulation package. A completely inorganic design is preferred to achieve good stability and a good efficiency of 32.517 %. Enhancement in device performance is achieved by optimizing various parameters, including the back electrode's work function, absorber thickness and defect density, and charge transport layers' thickness, doping density and defect density. Under optimized conditions, a conversion efficiency of 32.517 % is achieved using palladium (Pd) as the back contact metal. The study emphasizes an absorber thickness of 600 nm and defect density of 1.8 × 1011 cm−3 as optimal for maximizing photovoltaic performance parameters. The charge transport layers TiO2 as ETL and CuO as HTL are optimized to achieve the utmost photovoltaic properties. The HTL thicknesses around 200 nm and ETL thicknesses around 10 nm are suitable for high-efficiency solar cells. The p-type doping in HTL and n-type doping in ETL is varied from 1014 cm−3 to 1023 cm−3. The changing doping level has a small affect on the photovoltaic parameters. Considering all four parameters, the medium doping levels around 1018 cm−3 are good for HTL and ETL. Further, the effect of series resistance, shunt resistance, and temperature on perovskite solar cell performance are also investigated. The power conversion efficiency and fill factor are better at lower temperatures. The efficiency decreases from 34.189 % to 26.211 % and the fill factor declines from 91.400 % to 85.002 % as the temperature rises from 260 K to 450 K. Overall, the research ensures the significant improvement in photovoltaic potential for inorganic Cs2AgInBr6 based PSCs through the utilization of low-cost back contact metal Pd and inorganic transport materials such as TiO2 and CuO. The article will serve as a comprehensive guide for researchers keen on developing perovskite solar cells, specifically focusing on selecting various material properties for the absorber and charge transport layers.

Incidence of non-working days on limiting photovoltaic potential on a building with day-hours high power consumption, without storage and grid injection

Incidence of non-working days on limiting photovoltaic potential on a building with day-hours high power consumption, without storage and grid injection

Research on geometry optimization of park office buildings with the goal of zero energy

At the conceptual design stage, the building geometry design can predict the building load demand and renewable energy application potential to some extent. Geometry design interventions are critical to efficiently achieving the goal of zero-energy buildings. In the existing studies, the typicality and representativeness of the object geometry in the practice project are not high, and the influence of different geometry indices on energy savings and photovoltaic (PV) utilization potential under the same type of plane shape is rarely considered. In addition, the surrounding building shading situations considered are single. There is still significant room for improvement in the typical geometries selection and optimization condition settings. This paper presents a study of three typical park office building geometries in hot summer and cold winter regions. An optimization method based on the genetic algorithm and energy consumption simulation is proposed that takes into account both building energy savings and PV utilization potential improvements. The geometry-related indices of each typical geometry are then optimized under different PV layout scenarios and surrounding shading situations, and suitable geometry design strategies for typical office buildings are proposed under each optimization scenario. Geometry optimization can significantly reduce building energy consumption (the building energy-saving rate is 1.3–10.7 %) and increase PV generation (enhancement of 13.37–66.67 % for PV generation potential), thus lowering the net energy consumption of buildings. The findings of this study can be used to guide the design of park office building geometries in hot summer and cold winter regions with the goal of zero energy, as well as to promote the practice of zero-energy office buildings at the regional and national levels.

Harnessing rooftop solar photovoltaic potential in Islamabad, Pakistan: A remote sensing and deep learning approach

Solar energy shines as a beacon for sustainable development, with rooftop solar photovoltaic (PV) installations playing a crucial role. This study proposes a novel framework to precisely assess citywide existing solar power generation and analyze future potential under various rooftop utilization scenarios (10–50 %). To illustrate the methodology, the existing solar PV yield and future potential of Islamabad are explored as a case study. Employing open-source satellite data and deep learning (DL), this study quantified the electricity generation from current solar infrastructure and projected future possibilities. DL models like Mask R–CNN and Deeplab-v3 are trained on extensive custom datasets for solar panels and rooftops extraction. The study delineated 19,000 solar arrays, covering an area of 0.8 sqkm, and extracted 75.08 sqkm of suitable rooftops for future installations. The analysis revealed, current solar infrastructure generates 141.42 GWh electricity, satisfying 6.34 % of Islamabad's annual energy demand. Utilizing 50 % rooftop area could generate 6578 GWh annually, meeting 294 % of the city's electricity needs. This research contributes to the strategic planning for solar energy infrastructure, demonstrating the substantial role rooftop solar can play in meeting urban energy needs. This can inform policy decisions and guide investment opportunities for expanding clean energy in the city.

Application of Satellite Data for Estimating Rooftop Solar Photovoltaic Potential

Rooftop solar photovoltaics can significantly contribute to global energy transitions by providing clean, decentralized energy without the need for new land, thereby avoiding land-use conflicts. It serves as a valuable complement to other renewable-energy sources and is expected to play a crucial role in future electricity systems. Due to the spatiotemporal variability in the solar radiation on roof surfaces, it is essential to determine the potentials of the rooftop photovoltaics and its variations in specific regions. In Germany, this potential was assessed in 5 km × 5 km zones, as well as at the federal-state and national levels. High-quality satellite and reanalysis data were used to determine the power output of the solar photovoltaics. Additionally, high-resolution (2 m × 2 m) European Settlement Map data, calibrated with solar cadastre data, were utilized to evaluate different scenarios. The results show that the potential is concentrated in larger urban areas and the southwestern part of Germany due to the availability of rooftop space and solar radiation. Overall, the national rooftop areas are substantial across all scenarios, ranging from 2100 to 4500 km2. The applied methods and scenarios provide a straightforward way to reveal the spatiotemporal variability and define realistic ranges of the solar photovoltaic potential without requiring detailed information about each building. However, assessing the rooftop photovoltaic potential remains challenging and uncertain due to the lack of large-scale, high-resolution data on building characteristics and the complexity of the solar radiation distribution in urban environments.

Energy efficiency and greenhouse gas emission reduction potential of solar PV and biomass-based systems for a food processing plant

The industrial sector is one of the most energy-intensive sectors, with a share of nearly 38 % (156 EJ) of all energy used globally in 2020. Historical energy demand and consumption data from a poultry processing plant have been analyzed to lower greenhouse gas emissions (GHG) and reliance on traditional energy sources. The study includes energy, economic, and emissions analyses for (a) solar photovoltaic (PV) systems, (b) biomass fuels, and (c) coal-fired with wood. Fixed, single, and two-axis tracking solar PV systems that are company-owned and funded by banks are considered. The historical energy consumption data of the plant shows that 52.36 % of energy demand is met by electrical energy and 47.63 % by thermal energy. The yearly electricity demand is 9,938 MWh, costs $1,192,560, and emits 5117.6 tCO2. Thermal energy demand is based on an annual use of 898 tonnes of coal and 71.6 tonnes of liquefied petroleum gas (LPG), which costs $ 143,681 and emits 2977.7 tonnes of carbon dioxide (tCO2). Feasibility of 1.3 MW, fixed axis company-owned, solar PV plant shows an annual electricity production of 1876 MWh, GHG emission reduction of 965.9 tCO2 with a payback period of 3.4 years. Biomass system delivers yearly fuel cost savings of $25,724, reducing 2784 tCO2 with a 1.9-year payback period. Co-firing biomass offers a 3.58 % fuel cost saving and 557 tCO2 with a 0.93-year payback period. It concluded that the wood fuel feedstock biomass option is most suitable renewable energy resource for such large-scale poultry facilities.

Unveiling the potential of bifacial photovoltaics in harvesting indoor light energy: A comprehensive review

Bifacial photovoltaics (BPVs) have received tremendous attention as a potential contender for efficient and cost-effective light energy harvesting. Recently, advancements in BPV technologies have broadened their scope, allowing them to harness artificial indoor light energy efficiently from both top and bottom sides. This innovative approach has demonstrated its effectiveness in energy harvesting through a single-cell design. Among various available PV technologies, thin-film perovskite photovoltaics (PPVs) exhibit exceptional promise for indoor applications in low-light environments. They offer high-power conversion efficiency and ease of design, making them a superior choice when compared to other emerging indoor PV technologies such as kesterite and dye-sensitized PVs. To improve the performance of the indoor BPVs, it is necessary to further review several characteristics relating to their materials, architecture, processing, and indoor characterizations. Additionally, a comprehensive understanding of charge-transfer mechanisms, the variability in indoor lighting sources, the development of standardized indoor simulators, assessment of materials toxicity, and considerations of scalability are essential elements that must be addressed to advance this technology. In summary, this review examines recent developments, emerging trends, challenges, and provide suggestions for the further advancement of i-BPVs, also highlighting their potential as reliable and sustainable indoor energy-harvesting solution.

Direction Dependent Ferroelectricity and Conductivity in a Single Crystal 2D Halide Double Perovskite.

Halide ferroelectric materials have garnered a lot of interest because of their distinctive electrical and structural characteristics. In this study, the design and development of a new non-centrosymmetric 2D layered halide double perovskite material, Cl1.14Br2.86PA4AgInBr8 (CPAIn) is reported. This material shows ferroelectric properties above room temperature, with a Curie temperature of 190 °C. This behavior is achieved through the substitution of the halogenated A-site organic linker, 3-chloropropylammonium. CPAIn exhibits anisotropic ferroelectric behavior with higher spontaneous polarization of 6.25 µC cm-2 along the perpendicular direction to the octahedral layers, whereas the value decreases to 0.174 µC cm-2 between sheets. While using bottom contact to study the nature of polarity within a sheet, the P-E loop displays capacitive loop. The nature and value of polarization is highly direction dependent, and to further understand the mechanism of conduction, a combination of temperature-dependent impedance studies and poling dependent conductivity techniques are employed. These directional dependent properties hold immense potential in memory devices, sensors and photovoltaics, piezoelectric devices and energy storage.

High‐Throughput Screening of Low‐Bandgap Organic Semiconductors for Photovoltaic Applications: In the Search of Correlations

Low‐bandgap nonfullerene acceptors (NFAs) offer a unique potential for photovoltaic (PV) applications, such as transparent PV and agrivoltaics. Evaluating each new PV system to achieve the optimum thickness, microstructure, and device performance is, however, a complex multiparametric challenge with large time and resource requirements. Herein, the PV potential of low‐bandgap donor and NFA materials by combining high‐throughput screening and statistical methods is evaluated. The use of thickness gradients (20–600 nm) facilitates the fabrication of more than 2000 doctor‐bladed devices from 24 different low‐bandgap blend combinations. The corresponding power conversion efficiencies varies significantly, from 0.06% to 10.45% across materials and thicknesses. The self‐consistency of the large dataset allows to perform a parameter sensitivity study as well as parameter correlation analysis. These reveal that the choice of materials and energy alignment‐related features (i.e., electron affinity offset, ionization energy offset, bandgap, and energy loss) has the largest influence on final device performance, while processing conditions appear less important for the final efficiencies. Our study demonstrates that high‐throughput experimentation is a perfect match for correlation analyses in order to gain a statistically meaningful understanding of these systems, potentially accelerating the discovery of new materials.

Theoretical designing of 9,9'-dicarbazole-based dye via end-group modification for indoor DSSC applications

Molecular modeling has garnered significant attention in the realm of organic solar cells (OSCs) because it holds the promise of producing more efficient OSCs with notably enhanced power conversion efficiency (PCE). In this quest, we have undertaken a strategic modification of the acceptor moieties within the recently synthesized metal-free dicarbazole-based organic dye Cz-2, resulting in five novel theoretical dyes, designated as PT1-PT5. Numerous simulations encompassed both the newly designed compounds and the reference (Cz-2) by using DFT and TD-DFT, a comprehensive characterization aimed at enhancing photovoltaic and optoelectronic properties. We probed into the analysis of ground state geometry, frontier molecular orbitals, transition density matrix, optical properties, density of state, binding energy, molecular electrostatic potential, reorganizational energy, open-circuit voltage, and fill factor. Our findings unveiled a common trend among all the theoretical dyes, a reduction in band gap (Eg), a notable red-shift in absorbance ranging from 434 nm to 554 nm, and lowered binding and excitation energy. The decreased reorganization energy i.e., λ e and λ h, spanning a range from 0.0040 to 0.0052 eV and 0.0043 to 0.0075 eV respectively, promised significantly enhanced charge mobility. Intriguingly, the binding energies of all the designed compounds consistently registered values lower than that of reference (R), with figures ranging from 0.55 to 0.64 eV, compared to the binding energy of R (0.67 eV). These dyes show significant potential for indoor photovoltaics as they can absorb light in the visible range for indoor renewable energy applications. Our comprehensive analyses suggest that PT1-PT5 are promising candidates with great potential for advancing the field of renewable energy.