The ability of band offsets at multiferroic/metal and multiferroic/electrolyte interfaces in controlling charge transfer and thus altering the photoactivity performance has sparked significant attention in solar energy conversion applications. Here, we demonstrate that the band offsets of the two interfaces play the key role in determining charge transport direction in a downward self-polarized BFO film. Electrons tend to move to BFO/electrolyte interface for water reduction. Our experimental and first-principle calculations reveal that the presence of neodymium (Nd) dopants in BFO enhances the photoelectrochemical performance by reduction of the local electron-hole pair recombination sites and modulation of the band gap to improve the visible light absorption. This opens a promising route to the heterostructure design by modulating the band gap to promote efficient charge transfer.
2D perovskites is one of the proposed strategies to enhance the moisture resistance, since the larger organic cations can act as a natural barrier. Nevertheless, 2D perovskites hinder the charge transport in certain directions, reducing the solar cell power conversion efficiency. A nanostructured mixed-dimensionality approach is presented to overcome the charge transport limitation, obtaining power conversion efficiencies over 9%.
Dye-sensitized solar cells (DSSCs) serve as low-costing alternatives to silicon solar cells because of their low material and fabrication costs. Usually, they utilize Pt as the counter electrode (CE) to catalyze the iodine redox couple and to complete the electric circuit. Given that Pt is a rare and expensive metal, various carbon materials have been intensively investigated because of their low costs, high surface areas, excellent electrochemical stabilities, reasonable electrochemical activities, and high corrosion resistances. In this feature article, we provide an overview of recent studies on the electrochemical properties and photovoltaic performances of carbon-based CEs (e.g., activated carbon, nanosized carbon, carbon black, graphene, graphite, carbon nanotubes, and composite carbon). We focus on scientific challenges associated with each material and highlight recent advances achieved in overcoming these obstacles. Finally, we discuss possible future directions for this field of research aimed at obtaining highly efficient DSSCs.
Here, we report that long-term stable and efficient organic solar cells (OSCs) can be obtained through the following strategies: i) combination of rapid-drying blade-coating deposition with an appropriate thermal annealing treatment to obtain an optimized morphology of the active layer; ii) insertion of interfacial layers to optimize the interfacial properties. The resulting devices based on poly[4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b;4,5-b']dithiophene-2,6-diyl-alt-(4-(2-ethylhexyl)-3-fluorothieno[3,4-b]thiophene-2-carboxylate-2,6-diyl)] (PBDTTT-EFT):[6,6]-phenyl C71 butyric acid methyl ester (PC71 BM) blend as the active layer exhibits a power conversion efficiency (PCE) up to 9.57 %, which represents the highest efficiency ever reported for blade-coated OSCs. Importantly, the conventional structure devices based on poly(3-hexylthiophene) (P3HT):phenyl-C61 -butyric acid methyl ester (PCBM) blend can retain approximately 65 % of their initial PCE for almost 2 years under operating conditions, which is the best result ever reported for long-term stable OSCs under operational conditions. More encouragingly, long-term stable large-area OSCs (active area=216 cm2 ) based on P3HT:PCBM blend are also demonstrated. Our findings represent an important step toward the development of large-area OSCs with high performance and long-term stability.
Graphene (GR) and its derivatives are promising materials on the horizon of nanotechnology and material science and have attracted a tremendous amount of research interest in recent years. The unique atom-thick 2D structure with sp(2) hybridization and large specific surface area, high thermal conductivity, superior electron mobility, and chemical stability have made GR and its derivatives extremely attractive components for composite materials for solar energy conversion, energy storage, environmental purification, and biosensor applications. This review gives a brief introduction of GR's unique structure, band structure engineering, physical and chemical properties, and recent energy-related progress of GR-based materials in the fields of energy conversion (e.g., photocatalysis, photoelectrochemical water splitting, CO2 reduction, dye-sensitized and organic solar cells, and photosensitizers in photovoltaic devices) and energy storage (batteries, fuel cells, and supercapacitors). The vast coverage of advancements in environmental applications of GR-based materials for photocatalytic degradation of organic pollutants, gas sensing, and removal of heavy-metal ions is presented. Additionally, the use of graphene composites in the biosensing field is discussed. We conclude the review with remarks on the challenges, prospects, and further development of GR-based materials in the exciting fields of energy, environment, and bioscience.
Since a few centuries ago, organochlorine compounds (OCs) become one of the threatened contaminants in the world. Due to the lipophilic and hydrophobic properties, OCs always discover in fat or lipid layers through bioaccumulation and biomagnification. The OCs are able to retain in soil, sediment and water for long time as it is volatile, OCs will evaporate from soil and condense in water easily and frequently, which pollute the shelter of aquatic life and it affects the function of organs and damage system in human body. Photocatalysis that employs the usage of semiconductor nanophotocatalyst and solar energy can be the possible alternative for current conventional water remediation technologies. With the benefits of utilizing renewable energy, no production of harmful by-products and easy operation, degradation of organic pollutants in rural water bodies can be established. Besides, nanophotocatalyst that is synthesized with nanotechnology outnumbered conventional catalyst with larger surface area to volume ratio, thus higher photocatalytic activity is observed. In contrast, disadvantages particularly no residual effect in water distribution network, requirement of post-treatment and easily affected by various factors accompanied with photocatalysis method cannot be ignored. These various factors constrained the photocatalytic efficiency via nanocatalysts which causes the full capacity of solar photocatalysis has yet to be put into practice. Therefore, further modifications and research are still required in nanophotocatalysts' synthesis to overcome limitations such as large band gaps and photodecontamination.
Considering the limitation of fossil fuel resources and their environmental effects, the use of renewable energies is increasing. In the current research, a combined cooling and power production (CCPP) system is investigated, the energy source of which is solar energy. Solar energy absorbs by solar flat plate collectors (SFPC). The system produces power with the help of an organic Rankine cycle (ORC). An ejector refrigeration cycle (ERC) system is considered to provide cooling capacity. The motive flow is supplied from the expander extraction in the ERC system. Various working fluids have been applied so far for the ORC-ERC cogeneration system. This research investigates the effect of using two working fluids R-11 and R-2545fa, and the zeotropic mixtures obtained by mixing these two fluids. A multiobjective optimization process is considered to select the appropriate working fluid. In the optimization design process, the goal is to minimize the total cost rate (TCR) and maximize the exergy efficiency of the system. The design variables are the quantity of SFPC, heat recovery vapor generator (HRVG) pressure, ejector motive flow pressure, evaporator pressure, condenser pressure, and entertainment ratio. Finally, it is observed that using zeotropic mixtures obtained from these two refrigerants has a better result than using pure refrigerants. Finally, it is observed that the best performance is achieved when R-11 and R245fa are mixed with a ratio of 80 to 20%, respectively and led to 8.5% improvement in exergy efficiency, while the increase in TCR is only 1.5%.
In the third millennium, developing countries will confront significant environmental problems such as ozone depletion, global warming, the shortage of fossil resources, and greenhouse gas emissions. This research looked at a multigenerational system that can generate clean hydrogen, fresh water, electricity, heat, and cooling. The system's components include Rankine and Brayton cycles, an Organic Rankine Cycle (ORC), flash desalination, an Alkaline electrolyzer, and a solar heliostat. The proposed process has been compared for two different start-up modes with a combustion chamber and solar heliostat to compare renewable and fossil fuel sources. This research evaluated various characteristics, including turbine pressure, system efficiency, solar radiation, and isentropic efficiency. The energy and exergy efficiency of the proposed system were obtained at around 78.93% and 47.56%, respectively. Exergy study revealed that heat exchangers and alkaline electrolyzers had the greatest exergy destruction rates, at 78.93% and 47.56%, respectively. The suggested system produces 0.04663 kg/s of hydrogen. Results indicate that at the best operational conditions, the exergetic efficiency, power, and hydrogen generation of 56%, 6000 kW, and 1.28 kg/s is reached, respectively. Also, With a 15% improvement in the Brayton cycle's isentropic efficacy, the quantity of hydrogen produced increases from 0.040 kg/s to 0.0520 kg/s.
Many maximum power point tracking (MPPT) algorithms have been developed in recent years to maximize the produced PV energy. These algorithms are not sufficiently robust because of fast-changing environmental conditions, efficiency, accuracy at steady-state value, and dynamics of the tracking algorithm. Thus, this paper proposes a new random forest (RF) model to improve MPPT performance. The RF model has the ability to capture the nonlinear association of patterns between predictors, such as irradiance and temperature, to determine accurate maximum power point. A RF-based tracker is designed for 25 SolarTIFSTF-120P6 PV modules, with the capacity of 3 kW peak using two high-speed sensors. For this purpose, a complete PV system is modeled using 300,000 data samples and simulated using the MATLAB/SIMULINK package. The proposed RF-based MPPT is then tested under actual environmental conditions for 24 days to validate the accuracy and dynamic response. The response of the RF-based MPPT model is also compared with that of the artificial neural network and adaptive neurofuzzy inference system algorithms for further validation. The results show that the proposed MPPT technique gives significant improvement compared with that of other techniques. In addition, the RF model passes the Bland-Altman test, with more than 95 percent acceptability.
This study presented the implementation of a small-scale (50 W) solar energy harvesting system coupled with an electrolyzer and proton exchange membrane (PEM) fuel cell. The energy from the solar panel would be utilized by the electrolyzer to produce hydrogen gas. The hydrogen gas would be used, in turn, by the PEM fuel cell to generate electricity which supports both DC and AC load. Excess energy from the solar panel is also used to charge the lead-acid backup battery. Analysis of the system showed that 400 mL of hydrogen gas could be produced within every 17 minutes in optimal conditions; between 11 am until 4 pm with bright sunlight. For every 400 mL of hydrogen gas, the PEM fuel cell could sustain continuous operation of a 5V 500 mA DC load for 95 seconds. Theoretically, more than 7000 mL of hydrogen gas could be produced within 5 hours in strong sunlight, which could power up a 50 mA and 500 mA load for 4.7 hours and 28 minutes respectively, during evening or night operations. The proposed system could complement the traditional battery-based storage system while remaining as a clean source of energy production.
Recently, solar photovoltaic (PV) technology has shown tremendous growth among all renewable energy sectors. The attractiveness of a PV system depends deeply of the module and it is primarily determined by its performance. The quantity of electricity and power generated by a PV cell is contingent upon a number of parameters that can be intrinsic to the PV system itself, external or environmental. Thus, to improve the PV panel performance and lifetime, it is crucial to recognize the main parameters that directly influence the module during its operational lifetime. Among these parameters there are numerous factors that positively impact a PV system including the temperature of the solar panel, humidity, wind speed, amount of light, altitude and barometric pressure. On the other hand, the module can be exposed to simultaneous environmental stresses such as dust accumulation, shading and pollution factors. All these factors can gradually decrease the performance of the PV panel. This review not only provides the factors impacting PV panel's performance but also discusses the degradation and failure parameters that can usually affect the PV technology. The major points include: 1) Total quantity of energy extracted from a photovoltaic module is impacted on a daily, quarterly, seasonal, and yearly scale by the amount of dust formed on the surface of the module. 2) Climatic conditions as high temperatures and relative humidity affect the operation of solar cells by more than 70% and lead to a considerable decrease in solar cells efficiency. 3) The PV module current can be affected by soft shading while the voltage does not vary. In the case of hard shadowing, the performance of the photovoltaic module is determined by whether some or all of the cells of the module are shaded. 4) Compared to more traditional forms of energy production, PV systems offer a significant number of advantages to the environment. Nevertheless, these systems can procure greenhouse gas emissions, especially during the production stages. In conclusion, this study underlines the importance of considering multiple parameters while evaluating the performance of photovoltaic modules. Environmental factors can have a major impact on the performance of a PV system. It is critical to consider these factors, as well as intrinsic and other intermediate factors, to optimize the performance of solar energy systems. In addition, continuous monitoring and maintenance of PV systems is essential to ensure maximum efficiency and performance.
Reliable and accurate prediction model capturing the changes in solar radiation is essential in the power generation and renewable carbon-free energy industry. Malaysia has immense potential to develop such an industry due to its location in the equatorial zone and its climatic characteristics with high solar energy resources. However, solar energy accounts for only 2-4.6% of total energy utilization. Recently, in developed countries, various prediction models based on artificial intelligence (AI) techniques have been applied to predict solar radiation. In this study, one of the most recent AI algorithms, namely, boosted decision tree regression (BDTR) model, was applied to predict the changes in solar radiation based on collected data in Malaysia. The proposed model then compared with other conventional regression algorithms, such as linear regression and neural network. Two different normalization techniques (Gaussian normalizer binning normalizer), splitting size, and different input parameters were investigated to enhance the accuracy of the models. Sensitivity analysis and uncertainty analysis were introduced to validate the accuracy of the proposed model. The results revealed that BDTR outperformed other algorithms with a high level of accuracy. The funding of this study could be used as a reliable tool by engineers to improve the renewable energy sector in Malaysia and provide alternative sustainable energy resources.
The solar flat plate collector operating under different convective modes has low efficiency for energy conversion. The energy absorbed by the working fluid in the collector system and its heat transfer characteristics vary with solar insolation and mass flow rate. The performance of the system is improved by reducing the losses from the collector. Various passive methods have been devised to aid energy absorption by the working fluid. Also, working fluids are modified using nanoparticles to improve the thermal properties of the fluid. In the present work, simulation and experimental studies are undertaken for pipe flow at constant heat flux boundary condition in the mixed convection mode. The working fluid at low Reynolds number in the mixed laminar flow range is undertaken with water in thermosyphon mode for different inclination angles of the tube. Local and average coefficients are determined experimentally and compared with theoretical values for water-based Al2O3 nanofluids. The results show an enhancement in heat transfer in the experimental range with Rayleigh number at higher inclinations of the collector tube for water and nanofluids.
Solar cells are considered one of the most important and widespread solar applications in the world. However, the performance of the PV modules is significantly affected by the dust in the air. This paper, therefore, presents a comparison of an outdoor experimental study of dust effect on monocrystalline, and polycrystalline photovoltaic (PV) modules. For analysis, four 100 W PVs were installed horizontally in Sohar, Oman. For each pair of PV modules, one was left dusty due to environmental impact, and the second was cleaned daily. PV performance and environmental parameter measurements were conducted every 30 min for 35 days. The effects of dust on current, voltage, power, and energy were discussed in terms of time and normalized values. Also, cleaning methods were tested to determine the optimum one. It is found that power degradation of monocrystalline (20%) is higher compared with polycrystalline (12%) due to dust accumulation. For monocrystalline, the current, voltage, and power losses ranged between 10.0-24.0%, 2.0-3.5%, and 14.0-31.0%, respectively. However, for polycrystalline, the degradation rates were 16.88-27.92%, 0.455-0.455%, and 17.14-28.1% for current, voltage, and power losses after exposure to outdoor conditions for the same period, respectively. The dust accumulation on the PV surface found after 5 weeks is 0.493 mg/cm2, which can be considered the lowest accumulation rate compared to other Gulf countries, but which, however, leads to less energy degradation as well. It is found that water is sufficient to clean PV in the study area. However, sodium detergent as a cleaner introduced better results compared to water, especially when there is high pollution in the location.
Photovoltaic (PV) system is the cleanest form of electricity generation, and it is the only form with no effect on the environment at all. However, some environmental challenges persist, which must be overcome before solar energy may be used to represent a source of truly clean energy. This paper aims to study the stability and dynamic behavior of a grid-connected environmentally friendly photovoltaic energy system using the bifurcation theory. This theory introduces a systematic method for stability analysis of dynamic systems, under changes in the system parameters. To produce bifurcation diagrams based on the bifurcation theory, a parameter is constantly changed in each step, using MATLAB and AUTO, and eigenvalues are monitored simultaneously. Considering how the eigenvalues approach the system's imaginary axis in accordance with the changes in the targeted parameter, the occurred saddle-node and Hopf bifurcations of the grid-connected PV system are extracted. Using the obtained bifurcations, the system's dynamic stability limits against changes in controlled (controller coefficients) and systematic parameters (such as the Thevenin impedance network) are found.
Due to disparities in the allocation of rainwater and drought, extreme exploitation of groundwater reservoirs has depleted water supplies in many locations. In addition, improper disposal of domestic and industrial waste leads to poor drainage and deterioration of water quality. According to studies, desalination methods are an effective solution for treating unconventional water, i.e., sea and brackish water, and making it usable in daily life. Solar-powered desalination has recently received a great deal of attention around the world. Herein, we summarized challenges and future perspectives associated with solar-powered desalination units. Some hybrid technologies are also discussed like solar-wind desalination and RO-ED crystallizer technology in Morocco and the Middle East and North Africa (MENA) region. Previously, most experimental studies focused on the use of solar energy in traditional desalination methods such as multistage flash and multi-effect distillation. Desalination with reverse osmosis has become popular due to membrane technology improvement and benefits like high recovery ratios and low energy consumption. Furthermore, it has been seen that solar energy is less expensive than the energy obtained from traditional fuels in the MENA area. This article aims to comparatively and systematically review the economic feasibility of the use of solar photovoltaic reverse osmosis in desalination in the MENA region.
Solar energy provides desired thermal energy for diverse applications, including industrial heating, domestic cooking, power generation, desalination, and agri-food preservation. Despite extensive research on solar drying from the scientific community, there are limited practical applications for small-scale use. This review attempts to analyze the design features of three specific types of dryers for food drying applications: solar evacuated tube dryers, biomass dryers, and hybrid solar dryers. The thermal performance of the three dryers is evaluated in terms of drying time, moisture removal, and temperature attained during drying. The review also assesses the prospects of solar dryers, highlighting the need for further research into innovative designs and advanced drying capabilities. The study provides valuable information for enhancing dryer performance with various integrated solutions.
Solar photovoltaic-thermal hybrid with phase change material (PVT-PCM) emerges as an intelligent game changer to stimulate the clean, reliable, and affordable renewable energy technology. This PVT-PCM technology can be manipulated into generating both electricity and thermal energy that feature its practicality for residential and industrial applications. Hybridized of PCM into PVT design adds value to existing architecture with its capability to store excess heat that can be used during insufficient solar irradiation. Present work gives overview of the PVT-PCM system on technology innovation toward commercialization (viz, solar end game) subjected to bibliometric analysis, research and development evolution, and patent activity. A consolidation of these review articles was decluttered to focus on the performance and efficiency of PVT-PCM technology based on the fact that commercialization is ready once the technology is completed and qualified (at technology readiness level, TRL: 8). Economic review was conducted to understand the feasibility of the existing solar technologies and how it affects the PVT-PCM market price. Based on the contemporary findings, promising performance of PVT-PCM technology has underpinned its feasibility and technology readiness. China has predominant local and international framework and expected to be the PVT-PCM technology trendsetter in the next years through its strong international collaborative projects and pioneer in PVT-PCM patent filing. This present work underscores the solar end-game strategy and recommendation to create a path forward to achieve clean energy transition. Though, as to the date of submission of this article, no industry has found to manufacture/sell this hybrid technology in the market.
The large use of renewable sources and plug-in electric vehicles (PEVs) would play a critical part in achieving a low-carbon energy source and reducing greenhouse gas emissions, which are the primary cause of global warming. On the other hand, predicting the instability and intermittent nature of wind and solar power output poses significant challenges. To reduce the unpredictable and random nature of renewable microgrids (MGs) and additional unreliable energy sources, a battery energy storage system (BESS) is connected to an MG system. The uncoordinated charging of PEVs offers further hurdles to the unit commitment (UC) required in contemporary MG management. The UC problem is an exceptionally difficult optimization problem due to the mixed-integer structure, large scale, and nonlinearity. It is further complicated by the multiple uncertainties associated with renewable sources, PEV charging and discharging, and electricity market pricing, in addition to the BESS degradation factor. Therefore, in this study, a new variant of mixed-integer particle swarm optimizer is introduced as a reliable optimization framework to handle the UC problem. This study considers six various case studies of UC problems, including uncertainties and battery degradation to validate the reliability and robustness of the proposed algorithm. Out of which, two case studies defined as a multiobjective problem, and it has been transformed into a single-objective model using different weight factors. The simulation findings demonstrate that the proposed approach and improved methodology for the UC problem are effective than its peers. Based on the average results, the economic consequences of numerous scenarios are thoroughly examined and contrasted, and some significant conclusions are presented.
Over the last decade, interest in the utilization of solar energy for photocatalysis treatment processes has taken centre-stage. Researchers had focused on doping TiO2 with SiO2 to obtain an efficient degradation rate of various types of target pollutants both under UV and visible-light irradiation. In order to further improve this degradation effect, some researchers resorted to incorporate plasmonic metal nanoparticles such as silver and gold into the combined TiO2-SiO2 to fully optimize the TiO2-SiO2's potential in the visible-light region. This article focuses on the challenges in utilizing TiO2 in the visible-light region, the contribution of SiO2 in enhancing photocatalytic activities of the TiO2-SiO2 photocatalyst, and the ability of plasmonic metal nanoparticles (Ag and Au) to edge the TiO2-SiO2 photocatalyst toward an efficient solar photocatalyst.