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Photovoltaic technology has proven to be a reliable, economical, and clean energy source that is capable of adapting to diverse geographical conditions. However, factors such as soiling overshadow these qualities, thus leading to production losses and affecting the profitability of this technology. For these reasons, soiling is a highly studied topic, which involves considering the physicochemical characterization of the deposited material, mitigation strategies, effect predictions, and cleaning mechanisms. However, there is a relatively unexplored area related to the microbiological contribution to soiling. The surface of photovoltaic modules, along with the deposited material and local atmospheric factors, fosters favorable conditions for the colonization of microorganisms. These microorganisms influence the soiling mechanisms and optical properties of photovoltaic modules. This work presents a detailed characterization of the microbial diversity present in the soiling deposited on photovoltaic modules installed in the Atacama Desert. Two study sites were defined: Antofagasta and the Solar Platform of the Atacama Desert, which have warm and cold desert climates, respectively. Mineralogical characterization tests, heavy metal analyses, TOC, and inorganic element analyses were conducted on the deposited material. Additionally, the culturable isolates and the metagenomic DNA of the soiling samples and biofilms grown on standard PV glass were characterized using next-generation sequencing. The results show that the deposited soiling contained a microbiological component that had adapted to extreme desert conditions. The presence of the genera Arthrobacter, Kocuria, and Dietzia were identified in the culturable isolates from Antofagasta, while Arthrobacter and Dietzia were obtained from the Solar Platform of the Atacama Desert. The metagenomic DNA was mainly represented by the genera Pontibacter, Noviherbaspirillum, Massilia, Arthrobacter, Hymenobacter, and Deinococcus at Antofagasta. However, at the Solar Platform of the Atacama Desert, the analyzed samples presented DNA concentrations below 0.5 ng/µL, which made their preparation unviable. At the PSDA, the biofilms formed by the genera Peribacillus and Kocuria were identified, whereas the UA showed a greater abundance of bacteria that favored biofilm formation, including those that belonged to the genera Bacillus, Sporosarcina, Bhargavaea, Mesaobacillus, Cytobacillus, Caldakalibacillus, and Planococcus. Based on these results, we propose a soiling mechanism that considers the microbiological contribution to material cementation.

Based on economic feasibility, renewable generators can use pumped hydro storage (PHS) to improve their profitability by performing energy arbitrage under real-time pricing (RTP) schemes. In this paper, we present a new method to optimise the size of and manage utility-scale wind–PV systems using PHS with energy arbitrage under RTP. PHS is used to supply load consumption and/or energy arbitrage. Further, both load-supply and power-generating systems are considered, and a genetic algorithm metaheuristic technique is used to perform the optimisation efficiently. Irradiance, wind speed, temperature, hourly electricity price, component characteristics, and financial data are used as data, and the system is simulated in 15 min time steps during the system lifetime for each combination of components and control variables. Uncertainty is considered for the meteorological data and electricity prices. The pump and turbine efficiencies and available head and penstock losses are considered as variables (not fixed values) to obtain accurate simulations. A sample application in Spain is demonstrated by performing a sensitivity analysis of different locations, electricity prices, and costs. PHS is not worth considering with the present cost of components. In load-supply systems in Zaragoza (Spain), we found that PHS would be worth considering if its cost was lower than 850 EUR/kW (considering all PHS components except reservoirs) +20 EUR/m3 for reservoirs (equivalent to 105 EUR/kWh with a 70 m head), whereas in Gran Canaria Island (with a considerably higher irradiation and wind speed), the required PHS cost is considerably lower (~350 EUR/kW + 10 EUR/m3). For power-generating systems, PHS required costs ranging from 400–700 EUR/kW + 15–20 EUR/m3 for obtaining the optimal PV–wind–PHS system with economic results similar to those of the optimal power-generating system without PHS. Thus, the renewable–PHS system with energy arbitrage under RTP could be profitable for many locations globally given the wide range of the PHS cost; however, each case is different and must be evaluated individually. The presented model can be used for optimising the renewable–PHS system in any location with any costs and RTP schemes.

Within a city, there is a lack of space for the installation of photovoltaic panels, especially in cities with significant artistic heritage. Hence, there is a need to identify new spaces for the installation of renewable energy systems capable of supplying part of the city’s energy demand. Large infrastructures for public use such as stadiums, because of their characteristics, can become an essential resource for surrounding communities by installing photovoltaic panels on their roofs. This innovative approach can supply renewable electricity to the local community, aligning with the concept of renewable energy communities (RECs). This study focuses on the Olympic Stadium in Rome, exploring a new way to produce and share the electricity generated. An energy simulation of the photovoltaic plant was carried out by means of a transient calculation tool System Advisor Model (SAM). Then, the energy output from photovoltaics was correlated with the stadium, streetlight, and household electrical energy demands. The results highlight the suitability of the photovoltaic plant and the energy, economic, and environmental advantages derived from its exploitation.

As the global shift toward sustainable transportation gains momentum, the integration of electric vehicles (EVs) becomes imperative, necessitating a robust and environmentally friendly charging infrastructure. Leveraging the abundant solar potential in the region, this study examines the technical, economic, and environmental feasibility of deploying photovoltaic electric vehicle charging stations (PV-EVCSs) in Hail City, Saudi Arabia, as a case study. This study examines factors such as the energy demand, grid integration, and user accessibility, aiming to address the challenges and opportunities presented by the urban fabric. The proposed solar charging station network seeks to catalyze a paradigm shift toward a cleaner and more sustainable transportation ecosystem, embodying a forward-thinking approach to meeting the evolving needs of urban mobility in the 21st century. The analysis encompasses many scenarios, encompassing a range of car battery sizes, charger powers, and car slots per station. Zone 4 is identified as the most crucial area, where seven charging stations are needed to fulfill the expected demand in the absence of any private charging alternatives. The economic evaluation of the 1047.35 kWp PV system reveals an estimated conventional payback time of 11.69 years, accompanied by a return on assets of 10.17%. The system generates accumulated cash flows amounting to SR 7,169,294.62 over 30 years, while the estimated operational and maintenance expenses are predicted to be SR 50,000 per year. The overall investment cost for the solar PV and EV charging stations is SR 4,487,982. This cost is offset by the yearly electricity savings from solar and grid sources, which can reach up to SR 396,465.26 by year 30. This work presents a detailed plan for the future of sustainable transport. It combines technical, environmental, and economic aspects to promote a cleaner and more sustainable urban mobility system.

Considering global warming and environmental problems, the importance of renewable energy sources is increasing day by day. In particular, the effects of wind and solar power, which are variable renewable power sources, on the power system necessitate their evaluation in terms of the reliability of the power system. Photovoltaic panels, which enable the conversion of solar power into electrical power with semiconductors, have started to take an important place in global energy investments today. Photovoltaic power plants increase the demand for this energy source with continuous energy conversion depending on sunshine duration and radiation intensity. Among the renewable energy sources, the most easily utilized energy source, regardless of geographical conditions, is the sun. To prevent the energy production of PV power plants from being interrupted, it is necessary to address and analyze all kinds of faults that will affect power production in order to increase the reliability of the system. Academic studies in this field are generally grouped under two topics: classification of faults or modeling of electrical faults. Based on this, in this study, the problems that occur during the installation and operation of photovoltaic systems are classified, and the relevant faults are modeled and simulated in MATLAB Simulink version 23.2 (R2023b). Thus, a scientific approach to the problems of photovoltaic power plant operating conditions has been gained, which will be the basis for academic studies.

The United Arab Emirates (UAE) experiences up to 50% power losses in photovoltaic (PV) panels caused by frequent dust accumulation over the panels trailed by extreme temperature. Compositional and morphological insights into dust particle can potentially help design PV cleaning mechanisms inclusive of self-cleaning explored in the current article. Five different locations were studied to discover potential differences in dust samples. The collected samples were characterised employing Optical Microscopy, Scanning Electron Microscopy (SEM), X-ray Powder Diffraction (XRD), and Elemental Composition Analysis (Energy Dispersive Spectrometry, EDS). The micrographs revealed that the majority of particles were irregularly shaped, providing interlocking for the dust to stay over the surface. The particle size ranged from 0.01 to 300 µm, and some of the collected dust exhibited cavities. XRD analyses revealed variations in the chemical composition among the samples studied. Elemental Composition Analysis via EDS revealed both consistent patterns and variations in element presence among the dust samples, highlighting specific detections of chlorine (Cl) at some sites.

The operational reliability of power systems is threatened by the random failure of components and uncertain power output of renewable energies, such as photovoltaics. Under such circumstances, reliability evaluation is necessary for maintaining a continuous and stable energy supply. However, traditional reliability evaluation methods are usually extremely time-consuming, considering the numerous system states that need to be analysed. Hence, the reliability evaluation process cannot follow up the dynamic changes in PV output, which makes the timeline of the evaluation disappointing. This paper proposes an efficient reliability evaluation method for power systems with PV integration. The method reveals the analytical relationship between the reliability levels of the power system and the uncertainty factors that influence the reliability, such as the PV output. In this way, the dynamic reliability evaluation is achieved, and the evaluation results can be updated timely when the output of PV changes. First, a Gaussian mixture-hidden Markov model (GMM-HMM) is used to model the distribution characteristics of PV output. Then, the state enumeration and the hyperbolic truncated polynomial chaos expansion method are used to determine the analytical relationship between the reliability indices and PV output. Lastly, based on the analytical function, the operational reliability of the power systems is dynamically evaluated considering the real-time PV output. The effectiveness of the proposed method is verified using the modified IEEE 30 system as an example.

Multi-microgrid collaborative scheduling can promote the local consumption of renewable energy in the smart grid and reduce the operating costs of the power grid park. At the same time, the access of the distributed energy storage (ES) system provides an opportunity to further enhance the park’s peak shaving and valley filling capacity, thereby reducing costs. However, the uncertainty of photovoltaic (PV) power generation and load demand seriously affects the profit maximization of the microgrid in the park. To address this challenge, this paper proposes a stochastic optimal scheduling strategy for industrial park smart microgrids with multiple transformers based on the information gap decision theory (IGDT). We first introduce a revenue maximization model for industrial parks, incorporating a two-part tariff system and distributed ES. Subsequently, we employ an envelope constraint model to accurately represent the uncertainty associated with PV generation and load demand. By integrating these components, we establish the IGDT stochastic optimization scheduling model for industrial parks with multiple transformers. Finally, we simulate and analyze the performance of the proposed IGDT model under various cost deviation factors during typical spring and summer days. The simulation results demonstrate the effectiveness of the proposed control strategy in mitigating the impact of PV generation and load uncertainty on industrial parks. The IGDT-based scheduling approach provides an efficient solution for maximizing revenue and enhancing the operational stability of industrial park microgrids.

In this paper, we present a new maximum power point tracking (MPPT) algorithm that can identify whether a boost converter is operating in continuous conduction mode (CCM) or discontinuous conduction mode (DCM). The conventional MPPT algorithm assumes that the converter is always in CCM mode, even though this is not always the case. The converter can enter DCM mode due to factors such as the inductor size, irradiance and temperature conditions, voltage step size of the algorithm, and operating point of the PV array. In the proposed work, the conduction mode of a boost converter is evaluated under different conditions. The region of the I–V curve where the converter is likely to operate in DCM mode is identified and a mathematical expression developed in this work is then used to detect the conduction mode of the converter. The proposed algorithm incorporates this expression into a modified perturb and observe (P&O) algorithm. In each iteration, the algorithm first detects the conduction mode of the converter. If the converter is in DCM mode, the algorithm takes a large voltage step to force the converter back into CCM mode, i.e., into the constant current region. The proposed MPPT algorithm was tested using simulation experiments, and the results show that the proposed algorithm can significantly improve the efficiency of the MPPT process.

Satisfying the increased power demand of electric vehicles (EVs) charged by clean energy sources will become an important aspect that impacts the sustainability and the carbon emissions of the smart grid. A photovoltaic (PV)-powered charging station (PVCS) formed by PV modules and a stationary storage system with a public grid connection can provide cost-efficient and reliable charging strategies for EV batteries. Moreover, the utilization of vehicle-to-grid (V2G) service is a promising solution, as EVs spend most of their time idle in charging stations. As a result, V2G services have the potential to provide advantages to both public grid operators and EV users. In this paper, an energy management algorithm of a PVCS formulated with mixed-integer linear programming is presented to minimize the total energy cost of the participation of EV users in V2G service. Simulation results demonstrate that the proposed optimization method satisfies EV user demands while providing V2G service and highlights the benefits of the V2G service where the determined costs of the proposed algorithm perform significantly better compared to the baseline scenario (simulation without optimization).

Research on renewable energy sources and power electronic converters has been increasing due to environmental concerns. Many countries have established targets to decrease CO2 emissions and boost the proportion of renewable energy, with solar power being a prominent area of investigation in the recent literature. Techniques are being developed to optimize the energy recovered from PV cells and increase system efficiency, including modeling PV cells, the use of converter topologies to connect PV systems to high-power inverters, and the use of MPPT methods. Certain MPPT algorithms are intricate and demand high processing power. The literature describes several MPPT methods; however, the number of hardware resources required by MPPT algorithms is typically not disclosed. This work proposes a novel MPPT technique based on integral feedback conductance and incremental conductance error, considering the current dynamics of the boost converter. This MPPT algorithm is compared to the most widely used techniques in the literature and evaluates each method’s efficiency, performance, and computational needs using an HIL system. Comparisons are made with well-known MPPT algorithms, such as perturb and observe, incremental conductance, and newer techniques based on fuzzy logic and neural networks (NNs). As the NN that is most widely used in the literature depends on irradiation and temperature, an additional NN that is trained using the proposed method is also investigated.

This study proposes a community solar operation strategy for smart energy communities (SECs), which comprise members of an energy consumption group, to minimize the electricity bill of its members. When sharing resources within a group, resource distribution is a critical problem, and fairness in resource sharing is the main constraint for operation. The proposed community solar operation is formulated as a mixed-integer liner problem that can be optimally solved using centralized control and future time information. However, obtaining information of a future time is not causal. By decomposing the problem into individual problems that are solved by each member at each decision time, the proposed strategy operates the community solar in a distributed manner with partial information. The simulation results using the real dataset recorded in Korea show that the use of the proposed operation strategy results in a fair distribution of electricity bill savings with a marginal benefit reduction of 10% compared to the optimal operation that requires a centralized control and information on the future time. Moreover, a discussion on the tradeoff between the benefits of electricity bill savings and guarantee of fairness is provided. Based on the results, this study can serve as a reference for the design of community solar operations for SECs.

Floating solar power has a higher power generation efficiency than existing solar power generation methods. It is easier to secure in an installation area as well as to connect to other renewable energy sources. Floating solar power is considered an essential component for achieving carbon neutrality because it compensates for the shortcomings of existing solar power systems and maximizes their advantages. In this study, a performance comparison was conducted between pivotless tracking-type and fixed-type solar power systems. These systems were installed at the Irwol Reservoir in Suwon, South Korea, and monitored for comparison between May 2019 and June 2020. The tracking-type system generated approximately 14% more energy than the fixed-type system; the performance was maximized in May, which showed 25.63% more output power, and the performance was minimized in winter, with 3% more generated power. Owing to its pivotless structure, this system can be used in the solar industry.

The COVID-19 pandemic with subsequent economic fluctuations during consecutive epidemics waves and preventive measures in the form of lockdowns, and Russia’s invasion of Ukraine have had a meaningful impact on the European economy, including the energy market. These events have caused an increase in the prices of many products, including fossil fuels, and also a lack of their availability. The changes inspired the authors to conduct research on the current situation in Poland in the field of renewable energy and coal. The paper describes the research on the impact of the development of RES (mainly photovoltaic sources) on the change in the energy generation profile in the case of Poland. The article analyzes the impact of RES (renewable energy sources) on the reduction of CO2 emissions. The conducted analysis was based on the historical similarity of the replacement of conventional (carbon) sources by PV (photovoltaics) by determining in how many cases (%), a specific carbon source will be displaced. Based on the prepared forecast, it was determined that by the end of the year, the installed capacity in PV will reach the level of 11,213 MWp (in wind energy, it will be 7875 MWp). Replacement (reduction of consumption) of approximately 1.5 million Mg of hard coal and 2.87 million Mg of lignite was concluded to be possible (~4.4% and 6.3% of the hard-coal and lignite volume used for energy production). Limiting this volume of hard coal and lignite will also reduce CO2 emissions in the entire NPS by 5.24 million Mg (−5%) in 2022.

The necessity for further growth in the demand for electricity, particularly in the remote countryside, has been essential to Algeria’s economic and social progress in recent years. The Saharan regions account for around 80% of Algeria’s surface and have significant power demands. These areas are distinguished by their scattered population, extremely hot weather with high radiation levels (7 kw h/m2/day), and minimal energy use. Photovoltaic technology is one of the finest ways to harness solar power. The conversion of radiant energy (light quanta) into electrical energy can be achieved with the use of semiconductor materials. The effects of a solar cell depend on parameters such as solar cell technology, the position of the photovoltaic array, climate, and geographic data of the site. This paper presented: the role of site choice in the production of photovoltaic electricity. The results obtained for five sites in Algeria: Ouargla, Algers, Bechar, Sidi Bel Abbès, and Batna, confirmed that desert sites (Ouargla, Bechar) have a good photovoltaic efficiency result with large solar power irradiance.

An I-V curve measurement technique is one of the most important techniques available for characterising photovoltaic cells. Measuring an accurate I-V curve at the single-cell level is a challenging task because of the low voltages and high currents implied, requiring the management of very low impedances. In this paper, the authors propose a low-cost device for I-V curve measurements of single (or small amounts) of cells in a series based on the charge transfer between two capacitors of equal capacitance. Our measurement strategy allows us to trace the usual first quadrant curve (the normal working region of solar cells) as well as the second and fourth quadrants of the I-V curve, which are quite important for research purposes. A prototype was built to demonstrate the feasibility and successful measurements of the three-quadrant I-V curve, obtained for more than 20 different cells. To use the device in a laboratory, without depending on the solar irradiation, a modular platform was 3D-printed, integrating a board with infrared LEDs as irradiating devices, and housing (to place the solar cell under test). The result is a useful low-cost setup for three-quadrant I-V curve tracing that works as expected.

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.

On-board photovoltaic (PV) energy generation is starting to be deployed in a variety of vehicles while still discussing its benefits. Integration requirements vary greatly for the different vehicles. Numerous types of PV cells and modules technologies are ready or under development to meet the challenges of this demanding sector. A comprehensive review of fast-changing vehicle-integrated photovoltaic (VIPV) products and lightweight PV cell and module technologies adapted for integration into electric vehicles (EVs) is presented in this paper. The number of VIPV projects and/or products is on a steady rise, especially car-based PV integration. Our analysis differentiates projects according to their development stage and technical solutions. The advantages and drawbacks of various PV cell and module technologies are discussed, in addition to recommendations for wide-scale deployment of the technologies.

Shingled photovoltaic (PV) modules with increased output have attracted growing interest compared to conventional PV modules. However, the area per unit solar cell of shingled PV modules is smaller because these modules are manufactured by dividing and bonding solar cells, which means that shingled PV modules can easily have inferior shading characteristics. Therefore, analysis of the extent to which the shadow affects the output loss is essential, and the circuit needs to be designed accordingly. In this study, the loss resulting from the shading of the shingled string used to manufacture the shingled module was analyzed using simulation. A divided cell was modeled using a double-diode model, and a shingled string was formed by connecting the cell in series. The shading pattern was simulated according to the shading ratio of the vertical and horizontal patterns, and in the case of the shingled string, greater losses occurred in the vertical direction than the horizontal direction. In addition, it was modularized and compared with a conventional PV module and a shingled PV module. The results confirmed that the shingled PV module delivered higher shading output than the conventional PV module in less shade, and the result of the shading characteristic simulation of the shingled PV module was confirmed to be accurate within an error of 1%.

In photovoltaic systems, parasitic capacitance is often formed between PV panels and the ground. Because of the switching nature of PV converters, a high-frequency voltage is usually generated over these parasitic capacitances; this, in turn, can result in a common-mode current known as leakage current. This current can badly reach a high value if a resonance circuit is excited through the PV’s parasitic capacitance and the converter’s inductive components. Transformers are usually used for leakage current mitigation. However, this decreases the efficiency and increases the cost, size, and weight of the PV systems. Number of strategies have been introduced to mitigate the leakage current in transformer-less converters. Among these strategies, using common-ground converters is considered the most effective solution as it offers a solid connection between the negative terminal of PV modules and the neutral of the grid side; thus, complete mitigation of the leakage current is achieved. Number of common-ground inverters have been recently presented. These inverters are different in their size, cost, boosting capability, the possibility of producing DC currents, and their capability to offer multilevel shaping of output voltage. This work introduces a comprehensive review and classification for various common-ground PV inverters. Therefore, a clear picture of the advantages and disadvantages of these inverters is clarified. This provides a useful indication for a trade-off between gaining some of the advantages and losing others in PV systems. In addition, the potentials for optimization based on different performance indicators are identified.

In this paper, the gradient temperature and the thermomechanical stresses of a photovoltaic panel has been studied with and without heatsink. For this purpose, a three-dimensional analysis was carried out. Accordingly, a heat transfer analysis was developed. The numerical results show a cooling close to 26.7% with the proposed triangle fins compared with the rectangular fins studied before by another author, and the temperature distribution was determined. With this information, the stress analysis was carried out in order to find the effect on the panel due to the thermomechanical stresses. The aluminium frame was restricted to move freely. The resulting stresses field established the magnitude of the alternative stresses, resulting in a 6.7% drop compared with a reference panel. The guidelines of IEC 61215 have to be take into account. Due to the results obtained, the use of this kind of system in desert conditions is desirable because of its high operational temperature and due to the increase in heat transfer by the fins.

In recent years, the photovoltaic (PV) system was designed to supply solar power through photovoltaic arrays. The PV generator exhibits nonlinear voltage–current characteristics and its maximum power point tracking (MPPT), which varies with temperature and radiation. In the event of non-uniform solar insolation, several multiple maximum power points (MPPs) appear in the power–voltage characteristic of the PV module. Thus, a hybrid combination of binary particle swarm optimization (BPSO) and grey wolf optimization (GWO) is proposed herein to handle multiple MPPs. This combination is nowhere found in the literature, so the author chose this hybrid technique; and the main advantage of the proposed method is its ability to predict the global MPP (GMPP) in a very short time and to maintain accurate performance, even under different environmental conditions. Moreover, a 31-level multilevel inverter (MLI) was designed with a lower blocking voltage process to reduce the complexity of the circuit design. The entire system was executed in the MATLAB platform to examine the performance of the PV system, which was shown to extract a maximum power of 92.930 kW. The simulation design clearly showed that the proposed method with a 31-level MLI achieved better results in terms of total harmonic distortion (THD) at 1.60%, which is less when compared to the existing genetic algorithm (GA) and artificial neural networks (ANNs).

The operative temperature of a photovoltaic cell influences the electric conversion yield. This can be enhanced by cooling the panel. Among the studied solutions, phase change materials (PCM) exploit latent heat and absorb a large amount of energy at a nearly constant temperature. PCMs suffer from a low thermal conductivity. Under these premises the paper presents a hybrid graphene/fins/PCM cooling system to maximize efficiency gains and thermal recovery. An indoor laboratory characterization, under a solar simulator, compares the proposed model with a reference one (an identical, simple PV module) under fixed environmental conditions. Outdoor tests investigate the performances of the two systems under natural conditions. Indoor results show that the front temperature of the proposed PCM integrated module is averagely 6 °C less, with a peak of 8 °C, than the reference case. This means an increase in the electric yield of about 3%. Outdoor investigations prove that, when the PCM is solid and during the melting phase, the proposed system is averagely 1.12 °C and 4.87 °C colder than the reference case, respectively. The thermal efficiency is 30% and 65%, respectively. Once the melting process is completed, the performance becomes worse, and the hybrid panel is almost 3 °C warmer than the simple panel.

The operating temperature is an essential parameter determining the performance of a photovoltaic (PV) module. Moreover, the estimation of the temperature in the absence of measurements is very complex, especially for outdoor conditions. Fortunately, several models with and without wind speed have been proposed to predict the outdoor operating temperature of a PV module. However, a problem for these models is that their accuracy decreases when the sampling interval is smaller due to the thermal inertia of the PV modules. In this paper, two models, one with wind speed and the other without wind speed, are proposed to improve the precision of estimating the operating temperature of outdoor PV modules. The innovative aspect of this study is two novel thermal models that consider the variation of solar irradiation over time and the thermal inertia of the PV module. The calculation is applied to different types of PV modules, including crystalline silicon, thin film as well as tandem technology at different locations. The models are compared to models that are described in the literature. The results obtained in different time steps show that our proposed models achieve better performance and can be applied to different PV technologies.

This study investigates the potential application of Stateflow (SF) to design an energy management strategy (EMS) for a renewable-based hybrid energy system (HES). The SF is an extended finite state machine; it provides a platform to design, model, and execute complex event-driven systems using an interactive graphical environment. The HES comprises photovoltaics (PV), energy storage units (ESU) and a diesel generator (Gen), integrated with the power grid that experiences a regular load shedding condition (scheduled power outages). The EMS optimizes the energy production and utilization during both modes of HES operation, i.e., grid-connected mode and the islanded mode. For islanded operation mode, a resilient power delivery is ensured when the system is subjected to intermittent renewable supply and grid vulnerability. The contributions of this paper are twofold: first is to propose an integrated framework of HES to address the problem of load shedding, and second is to design and implement a resilient EMS in the SF environment. The validation of the proposed EMS demonstrates its feasibility to serve the load for various operating scenarios. The latter include operations under seasonal variation, abnormal weather conditions, and different load shedding patterns. The simulation results reveal that the proposed EMS not only ensures uninterrupted power supply during load shedding but also reduces grid burden by maximizing the use of PV energy. In addition, the SF-based adopted methodology is envisaged to be a useful alternative to the popular design method using the conventional software tools, particularly for event-driven systems.

Prediction of energy production is crucial for the design and installation of PV plants. In this study, five free and commercial software tools to predict photovoltaic energy production are evaluated: RETScreen, Solar Advisor Model (SAM), PVGIS, PVSyst, and PV*SOL. The evaluation involves a comparison of monthly and annually predicted data on energy supplied to the national grid with real field data collected from three real PV plants. All the systems, located in Castile and Leon (Spain), have three different tilting systems: fixed mounting, horizontal-axis tracking, and dual-axis tracking. The last 12 years of operating data, from 2008 to 2020, are used in the evaluation. Although the commercial software tools were easier to use and their installations could be described in detail, their results were not appreciably superior. In annual global terms, the results hid poor estimations throughout the year, where overestimations were compensated by underestimated results. This fact was reflected in the monthly results: the software yielded overestimates during the colder months, while the models showed better estimates during the warmer months. In most studies, the deviation was below 10% when the annual results were analyzed. The accuracy of the software was also reduced when the complexity of the dual-axis solar tracking systems replaced the fixed installation.

The performance of photovoltaic (PV) arrays are affected by the operating temperature, which is influenced by thermal losses to the ambient environment. The factors affecting thermal losses include wind speed, wind direction, and ambient temperature. The purpose of this work is to analyze how the aforementioned factors affect array efficiency, temperature, and heat transfer coefficient/thermal loss factor. Data on ambient and array temperatures, wind speed and direction, solar irradiance, and electrical output were collected from a PV array mounted on a CanmetENERGY facility in Varennes, Canada, and analyzed. The results were compared with computational fluid dynamics (CFD) simulations and existing results from PVsyst. The findings can be summarized into three points. First, ambient temperature and wind speed are important factors in determining PV performance, while wind direction seems to play a minor role. Second, CFD simulations found that temperature variation on the PV array surface is greater at lower wind speeds, and decreases at higher wind speeds. Lastly, an empirical correlation of heat transfer coefficient/thermal loss factor has been developed.

Several models for estimating the lifetimes of lead-acid and Li-ion (LiFePO4) batteries are analyzed and applied to a photovoltaic (PV)-battery standalone system. This kind of system usually includes a battery bank sized for 2.5 autonomy days or more. The results obtained by each model in different locations with very different average temperatures are compared. Two different locations have been considered: the Pyrenees mountains in Spain and Tindouf in Argelia. Classical battery aging models (equivalent full cycles model and rainflow cycle count model) generally used by researchers and software tools are not adequate as they overestimate the battery life in all cases. For OPzS lead-acid batteries, an advanced weighted Ah-throughput model is necessary to correctly estimate its lifetime, obtaining a battery life of roughly 12 years for the Pyrenees and around 5 years for the case Tindouf. For Li-ion batteries, both the cycle and calendar aging must be considered, obtaining more than 20 years of battery life estimation for the Pyrenees and 13 years for Tindouf. In the cases studied, the lifetime of LiFePO4 batteries is around two times the OPzS lifetime. As nowadays the cost of LiFePO4 batteries is around two times the OPzS ones, Li-ion batteries can be competitive with OPzS batteries in PV-battery standalone systems.

This paper proposes a novel control method for enhancing transient stability by using renewable energy sources (RES). The kinetic energy accumulated in a rotor of variable speed wind generator (VSWG) is proactively used as the active power source, which is controlled according to the frequency measured at the wind farm. In addition, coordinated reactive power control according to the grid voltage is also carried out to more effectively use the kinetic energy of the VSWG. The effects of the proposed control system were evaluated by simulation analyses performed using a modified IEEE nine-bus power system network made up of synchronous generators (SGs), a photovoltaic (PV) system and a VSWG-based wind farm. Furthermore, the coordinated reactive power control between the VSWG and PV system was also demonstrated.

This review study, framed in the Work group 4 “Photovoltaic in built environment” within the COST Action PEARL PV, CA16235, aims to examine applications of integrated and applied photovoltaic technologies on ten landmark buildings characterised by distinctive geometries, highlighting the aesthetics of their architecture and quality of PV integration based on a proposed set of seven criteria. The selected building samples cover a large design diversity related to the quality of PV systems integration into building envelope that could serve as a basis for general guidelines of best architectural and technological practice. After introducing the problem and defining the research methodology, an analysis of ten landmark buildings is presented, as representative models of aesthetics of their architecture, photovoltaic integration and implementation and energy performance. The study concludes with the main characteristics of photovoltaic integration on landmark buildings. The paper is intended to support both engineers and architects in comprehending the convergent development of contemporary architecture and photovoltaic technology, as well as the need for a closer collaboration, sometimes resulting in architectural masterworks that promote the diffusion of photovoltaics to the public.

Microcrystalline silicon, which is widely used in the microelectronics industry, is usually fabricated by chemical vapor deposition techniques. In recent years, magnetron sputtering has been considered as an alternative because it is a simpler, cheaper and more eco-friendly technique. The big drawback of this technique, however, is the need to recrystallize the as-deposited amorphous silicon, which can be done by metal-induced crystallization. Among the different suitable metals, copper has not been extensively investigated for this purpose. Furthermore, the applicability of the microcrystalline film prepared by this method has not been evaluated for photovoltaic device fabrication. Therefore, this paper reports the fabrication of p-type microcrystalline silicon thin film by magnetron sputtering and copper-induced crystallization techniques, and evaluates its appropriateness for solar cell fabrication. In the first step, 60 nm of silicon followed by 10 nm of copper were deposited on n-type silicon wafer and glass substrates, both by the magnetron sputtering technique. Then, the as-deposited samples were annealed at temperatures from 450 °C to 950 °C. The crystal properties of the resulting films were characterized by Raman and X-ray diffraction spectroscopies and optical and secondary emission microscopies, while their electrical characteristics were determined by Hall-effect, J-V curve and external quantum efficiency measurements. These characterizations confirmed the formation of a layer of microcrystalline silicon mostly in the direction with a crystallization ratio of 93% and a largest grain size of 20 nm. The hole concentration and mobility of the fabricated p-type microcrystalline silicon layer were about 1017~1019 cm−3 and 8 cm2/V.s, respectively. By using the fabricated film as the emitter layer of a p-n junction solar cell, a good rectification ratio of 4100 and reverse saturation current density of 85 nA.cm−2 were measured under dark conditions. The highest photovoltaic conversion efficiency, i.e., 2.6%, with an open-circuit voltage of 440 mV and short-circuit current density of 16.7 mA/cm2, were measured under AM1.5G irradiance. These results indicate that microcrystalline silicon created by magnetron sputtering and copper-induced crystallization has considerable potential for photovoltaic device fabrication.

The 2030 Agenda for Sustainable Development set 17 Sustainable Development Goals (SDGs). These include ensuring access to affordable, reliable, sustainable and modern energy for all (SGD7) and making cities and human settlements inclusive, safe, resilient and sustainable (SGD11). Thus, across the globe, major cities are moving in the smart city direction, by, for example, incorporating photovoltaics (PV), electric buses and sensors to improve public transportation. We study the concept of integrated PV bus stop shelters for the city of Lisbon. We identified the suitable locations for these, with respect to solar exposure, by using a Geographic Information System (GIS) solar radiation map. Then, using proxies to describe tourist and commuter demand, we determined that 54% of all current city bus stop shelters have the potential to receive PV-based solutions. Promoting innovative solutions such as this one will support smart mobility and urban sustainability while increasing quality of life, the ultimate goal of the Smart Cities movement.

The drying performance of paddy rice using an inflatable solar dryer (ISD), or also known as GrainPro® Solar Bubble Dryer™, was evaluated and compared to conventional sun drying in Burkina Faso. Drying time was around eight hours. Thermal imaging was conducted to observe temperature distribution in the ISD during drying and mixing. Shadow casting was observed in the ISD due to the round shape of the black plastic film, which reduced the temperature of the paddy rice to about 10 °C. The temperature inside the ISD was up to 13 °C higher than the ambient temperature, whereas the temperature of paddy rice on the top layer was about 5 °C higher than on the bottom. The final moisture content of paddy rice dried in the ISD and under the sun was not considerably different. Under certain circumstances, impurities in paddy rice dried in the ISD could be substantially lower than for sun drying. The aflatoxin level of paddy rice was under the maximum limit of the EU regulation. Drying paddy rice seemed to be effective to remove aflatoxin type AFG2 content. Further adaptation of the ISD design for drying operations on rough surfaces and sandy soils is suggested.

The outdoor field test of the 4-terminal on Si tandem photovoltaic module (specifically, InGaP/GaAs on Si) was investigated and a performance model, considering spectrum change affected by fluctuation of atmospheric parameters, was developed and validated. The 4-terminal on Si tandem photovoltaic module had about 40% advantage in seasonal performance loss compared with standard InGaP/GaAs/InGaAs 2-terminal tandem photovoltaic module. This advantage increases (subarctic zone < temperate zone < subtropical zone). The developed and validated model used an all-climate spectrum model and considered fluctuation of atmospheric parameters. It can be applied every type of on-Si tandem solar cells.

Photonic crystals have the advantage of minimizing thermal losses from solar cells, reflecting the solar radiation that is not absorbed by the photovoltaic device. To optimize this optical response, photonic crystals are designed considering the relative position of the Bragg peak and the bandgap of the solar cell, under normal incident irradiation conditions. The aim of this research article was to determine experimentally the optical limits of a solar cell coupled to a photonic crystal acting as beam splitter. For that purpose, the photovoltaic system was characterized under indoor and outdoor conditions; angular dependence of the irradiation source was determined in each case, and both results were compared with good agreement. Moreover, other parameters such as irradiation spectrum and polarization of the light were investigated. The main conclusion is that photovoltaic performance is highly affected by the Bragg peak shifting and the profile is distorted, due to the angular dependence with the sun. These experimental limits must be considered at the early design stage to avoid performance losses.

Because semiconductors absorb wavelengths dependent on the light absorption coefficient, photovoltaic (PV) energy output is affected by the solar spectrum. Therefore, it is necessary to consider the solar spectrum for highly accurate PV output estimation. Bird’s model has been used as a general spectral model. However, atmospheric parameters such as aerosol optical depth and precipitable water have a constant value in the model that only applies to clear days. In this study, atmospheric parameters were extracted using the Bird’s spectrum model from the measured global spectrum and the seasonal fluctuation of atmospheric parameters was examined. We propose an overcast spectrum model and calculate the all-weather solar spectrum from clear to overcast sky through linear combination. Three types of PV modules (fixed Si, two-axis tracking Si, and fixed InGaP/GaAs/InGaAs triple-junction solar cells) were installed at the University of Miyazaki. The estimated performance ratio (PR), which takes into account incident angle and spectral variations, was consistent with the measured PR. Finally, the energy yield of various PVs installed across Japan was successfully estimated.

The energy yield of vehicle-integrated photovoltaics (VIPV) differs from that of standard photovoltaics (PV). It is mainly by the difference of the solar irradiance onto the car roof and car bodies as well as its curved shape. Both meaningful and practical modeling and measurement of solar irradiance for VIPV need to be established, rather than the extension of the current technologies. The solar irradiance is modeled by a random distribution of shading objects and car orientation with the correction of the curved surface of the PV modules. The measurement of the solar irradiance onto the car roof and car body is done using five pyranometers in five local axes on the car for one year. The measured dynamic solar irradiance onto the car body and car roof is used for validation of the solar irradiance model in the car.

In recent years, the photovoltaic (PV) power generation system has been widely discussed and researched. Research on electric energy focuses on the development of Maximum Power Point Tracking (MPPT) technology, and many methods have been proposed. However, these studies have a common defect: the tracking continues near the maximum power point (MPP), so that the waveform of output power jitters, thus causing power loss and rapid wearing of electronic modules. In order to remedy this defect, this paper proposes a new type of fractional order chaos synchronization dynamic error detector for the MPPT design of a PV power system. In this study, the Sprott chaos synchronization dynamic error system was used to control the pulse width duty cycle of PWM and optimize the power oscillation of a PV power system during steady-state response. The simulation and experimental results showed that the voltage detector proposed in this paper can reduce the power oscillation of a PV power system during steady-state response, and increase the overall system efficiency. From the steady-state responses of MPPT, it can be seen that about 0.2 vibration amplitude can be suppressed with control action. Therefore, about 4% of steady-state vibration energy can be saved.

This paper proposes the re-planning operation method using Tabu Search for direct current (DC) smart house with photovoltaic (PV), solar collector (SC), battery and heat pump system. The proposed method is based on solar radiation forecasting using reported weather data, Fuzzy theory and Recurrent Neural Network. Additionally, the re-planning operation method is proposed with consideration of solar radiation forecast error, battery and inverter losses. In this paper, it is assumed that the installation location for DC smart house is Okinawa, which is located in Southwest Japan. The validity of proposed method is confirmed by comparing the simulation results.

The energy supplied by photovoltaic (PV) panels connected to the grid creates more flexibility for energy management; however, oversizing the PV system may result in an energy surplus, an essential factor to be considered during energy efficiency optimization. The economic analysis of energy supply systems for buildings and industry should include a detailed feasibility analysis and a life cycle perspective. Simulations were performed to quantify the potential savings when the excess of PV energy (surplus) is supposed to be exported to the grid by considering the net metering and net billing approaches. Our objective was to evaluate the electrical demand of a logistics center with pre-design modeling and simulation, and determine the adequate system configurations by considering the life cycle costing (LCC). We established a baseline and three alternative economic scenarios for optimization. Combining the use of TRNSYS 180 Simulation Studio and its optimization library component, GenOp (Generic Optimization Program), we simulated different options of grid energy contracts considering the variable tariffs and the integration with PVs. Based on the LCC, a single-objective optimization (SOO) process was performed. This approach allowed us to envisage possible configurations, reducing up to a quarter of annual grid energy consumption that represents savings of around 21% for the LCC in a timeframe of 20 years, reaching up to 39% when the export of the PV surplus energy is considered. The payback period of investments is below six years for the optimal scenarios.

Renewable energy sources have emerged as an alternative to meet the growing demand for energy, mitigate climate change, and contribute to sustainable development. The integration of these systems is carried out in a distributed manner via microgrid systems; this provides a set of technological solutions that allows information exchange between the consumers and the distributed generation centers, which implies that they need to be managed optimally. Energy management in microgrids is defined as an information and control system that provides the necessary functionality, which ensures that both the generation and distribution systems supply energy at minimal operational costs. This paper presents a literature review of energy management in microgrid systems using renewable energies, along with a comparative analysis of the different optimization objectives, constraints, solution approaches, and simulation tools applied to both the interconnected and isolated microgrids. To manage the intermittent nature of renewable energy, energy storage technology is considered to be an attractive option due to increased technological maturity, energy density, and capability of providing grid services such as frequency response. Finally, future directions on predictive modeling mainly for energy storage systems are also proposed.

Within the city of Guayaquil, the Protector Prosperina Forest is located, which protects an area rich in biodiversity. To prevent visitors from damaging the forest, the Polytechnic community has established a tourism intervention plan based on sustainability criteria, generating responsible and ecological tourism. Therefore, the project aims to improvement of spaces, signage, and construction of energy systems using renewable energy for lighting and loading of electronic devices, will also, serve as logistical technical support for the operation of the sensor network and information acquisition for the monitoring of diversity forest through audio and video, especially for the protection of those species that are in danger of extinction. In this initiative to raise awareness and promote the protection of the forest and the sustainable use of its resources, autonomous photovoltaic stations have been installed in 5 strategic locations for the development of the aforementioned activities.

Bismuth oxyiodide (BiOI) is expected to be promising material for photovoltaic devices since it has good activity under the visible range. Here, we studied the annealing treatment on BiOI and its effect on the photovoltaic application. Firstly, the synthesized BiOI from Bi(NO3)3 and KI was annealed at varied temperatures (100−550 °C). The structural investigation by X-ray diffraction and Raman spectroscopy analysis was supported with morphology and optical analysis by scanning electron microscope (SEM) and UV-Visible spectroscopy. Due to the heating treatment, it could result in iodine-deficient bismuth-based materials, namely Bi7O9I3, Bi5O7I, and β-Bi2O3. Secondly, the photovoltaic test measurement was performed by solar simulator air mass (AM) 1.5 illumination which presented the current-voltage curve from each material. The enhancement of photovoltaic performance was given by the increase of temperature up to 300 °C. At that temperature, the performance of the device which consisted of Bi7O9I3 achieved three times higher efficiency than the annealed parent BiOI at 100 °C. Hence, the structural changing owing to the oxygen addition to BiOI structure had an impact on the photoelectrochemical cell. Based on this work, it is possible to attempt BiOI derivation with suitable holes and electron transport layers for better photovoltaic performance.

Solar power generation deals with uncertainty and intermittency issues that lead to some difficulties in controlling the whole grid system due to imbalanced power production and power demand. The forecasting of solar power is an effort in securing the integration of renewable energy into the grid. This work proposes a forecasting model called WT-ANFIS-HFPSO which combines the wavelet transform (WT), adaptive neuro-fuzzy inference system (ANFIS) and hybrid firefly and particle swarm optimization algorithm (HFPSO). In the proposed work, the WT model is used to eliminate the noise in the meteorological data and solar power data whereby the ANFIS is functioning as the forecasting model of the hourly solar power data. The HFPSO is the hybridization of the firefly (FF) and particle swarm optimization (PSO) algorithm, which is employed in optimizing the premise parameters of the ANFIS to increase the accuracy of the model. The results obtained from WT-ANFIS-HFPSO are then compared with several other forecasting strategies. From the comparative analysis, the WT-ANFIS-HFPSO showed superior performance in terms of statistical error analysis, confirming its reliability as an excellent forecaster of hourly solar power data.

The technical performance of an inflatable solar dryer (ISD) to dry amaranth leaves (Amaranthus spp.) was investigated. To handle the drying of lightweight materials, modification was made by adding an air deflector and trays inside the ISD. Computational performance of the ISD solar energy system was evaluated using MATLAB Simulink. The estimated air mass flow in the inlet of the ISD was 0.75 kg/s. Using computational fluid dynamics (CFD), the uniformity of air distribution in the ISD was evaluated. The solar radiation reported during good drying performance ranged between 510 and 950 W/m2. In a controlled charging system, a 100 Wp PV module typically generated voltage between 10.22 and 18.75 V. Drying conditions at temperatures of 40 °C or above were typically achieved in the ISD from 12:00 to 16:00. Temperature inside the ISD could reach up to 69.4 °C during the day and 13.4 °C during the night. The highest relative humidity of 97.4% was recorded during the night. Opening the ISD while mixing the product could lead to considerable heat loss. Fluctuation of solar radiation and shaded areas in the ISD appeared to be the major factors affecting the drying performance.

In high penetrations, demand side management (DMS) applications augment a substation power transformer’s load profile, which can ultimately affect the unit’s capacity limits. Energy storage (ES) applications reduce the evening peaking demand, while time-of-use rates incentivize end-users to charge electric vehicles overnight. The daily load profile is further augmented by high penetrations of photovoltaic (PV) systems, which reduce the midday demand. The resulting load profile exhibits a more flattened characteristic when compared to the historical cyclic profile. Although the initial impact of PV and ES applications may reduce a unit’s peak demand, long-term system planning and emergency conditions may require operation near or above the nameplate rating. Researchers have already determined that a flattened load profile excessively ages a unit’s dielectrics more rapidly. The focus of this research was to identify an approach for establishing new transformer capacity limits for units serving flattened load profiles with a high harmonic content. The analysis utilizes IEEE standards C57.91 and C57.110 to develop an aging model of a 50 MVA SPX Waukesha transformer. The results establish a guideline for determining transformer capacity limits for normal operation, long-term emergency operation, and short-term emergency operation when serving systems with high penetrations of DSM applications.

This paper presents an analysis that frames the impact of various smart grid technologies, with an objective to provide a transparent framework for residential smart grid demonstration projects based on predefined and clearly formulated key performance indicators. The analysis inspects measured energy data of 217 households from three smart grid pilot projects in the Netherlands and a public dataset with smart meter data from 70 households as a reference. The datasets were evaluated for one year and compared to provide insights on technologies and other differences based on seven key performance indicators, giving a comprehensive overview: monthly electricity consumption (100–600 kWh) and production (4–200 kWh); annually imported (3.1–4.5 MWh) and exported (0.2–1 MWh) electricity; residual load; peak of imported (4.8–6.8 kW) and exported (0.3–2.2 kW) electricity; import simultaneity (20–70.5%); feed in simultaneity (75–89%); self-sufficiency (18–20%); and self-consumption (50–70%). It was found that the electrification of heating systems in buildings by using heat pumps leads to an increase of annual electricity consumption and peak loads of approximately 30% compared to the average Dutch households without heat pumps. Moreover, these peaks have a high degree of simultaneity. To increase both the self-sufficiency and self-consumption of households, further investigations will be required to optimize smart grid systems.

In this study, geographic information system (GIS)-based methods and their applications in solar power system planning and design were reviewed. Three types of GIS-based studies, including those on solar radiation mapping, site evaluation, and potential assessment, were considered to elucidate the role of GISs as problem-solving tools in relation to photovoltaic and concentrated solar power systems for the conversion of solar energy into electricity. The review was performed by classifying previous GIS-based studies into several subtopics according to the complexity of the employed GIS-based methods, the type of solar power conversion technology, or the scale of the study area. Because GISs are appropriate for handling geospatial data related to solar resource and site suitability conditions on various scales, the applications of GIS-based methods in solar power system planning and design could be expanded further.

This article presents an in-situ comparative analysis and power quality tests of a newly developed photovoltaic charging system for e-bikes. The various control methods of the inverter are modeled and a single-phase grid-connected inverter is tested under different conditions. Models are constituted for two current control methods; the proportional resonance and the synchronous rotating frames. In order to determine the influence of the control parameters, the system is analyzed analytically in the time domain as well as in the frequency domain by simulation. The tests indicated the resonance instability of the photovoltaic inverter. The passivity impedance-based stability criterion is applied in order to analyze the phenomenon of resonance instability. In conclusion, the phase-locked loop (PLL) bandwidth and control parameters of the current loop have a major effect on the output admittance of the inverter, which should be adjusted to make the system stable.

Perovskite solar cells have achieved photo-conversion efficiencies greater than 20%, making them a promising candidate as an emerging solar cell technology. While perovskite solar cells are expected to eventually compete with existing silicon-based solar cells on the market, their long-term stability has become a major bottleneck. In particular, perovskite films are found to be very sensitive to external factors such as air, UV light, light soaking, thermal stress and others. Among these stressors, light, oxygen and moisture-induced degradation can be slowed by integrating barrier or interface layers within the device architecture. However, the most representative perovskite absorber material, CH3NH3PbI3 (MAPbI3), appears to be thermally unstable even in an inert environment. This poses a substantial challenge for solar cell applications because device temperatures can be over 45 °C higher than ambient temperatures when operating under direct sunlight. Herein, recent advances in resolving thermal stability problems are highlighted through literature review. Moreover, the most recent and promising strategies for overcoming thermal degradation are also summarized.