Environmental impacts of solar energy systems: A review

Towards a green economy: Investigating the impact of sustainable finance, green technologies, and environmental policies on environmental degradation

Environmental degradation is a problem, and the consequences, in terms of emission of pollutants into different ecosystems, human health, and sustainable development are disastrous. This study explains the complex interactions that exist among sustainable finance, green technology innovation, green energy adoption, the climate change financial policy, green growth index, government spending, and financial globalization across the globe. This research applies to an extensive dataset that ranges to 23 years in 50 countries by enforcing robust dynamic econometric methods such as unit root tests, cointegration analysis, and generalized method of moments (GMM) estimations for the analysis of these complicated issues. The results show that Sustainable finance (SF) has a negative coefficient of -0.033, suggesting that increased sustainable financial practices contribute to reducing environmental degradation. Similarly, technology innovation (TI) and green energy (GE) both show significant negative impacts on environmental degradation, with coefficients of -0.132 and -0.075, respectively. The green growth index (GGI) has the most substantial negative effect, with a coefficient of -0.686, highlighting its critical role in mitigating environmental degradation. Lastly, the climate-related financial policy index (CRFPI) exhibits a positive coefficient of 0.029, indicating that advancements in financial policies targeting climate issues slightly offset environmental degradation. These results collectively emphasize the importance of financial, technological, and policy interventions in reducing environmental degradation. It also becomes clear that government spending and financial globalization both influence the efficacy of the government actions in reducing environmental pollution, while government efforts are affected by the second factor negatively. Those perceptions reveal why green finance that is advanced technologically along with renewable energy initiatives and governmental policy backing are the need of the hour in view of these very environmental challenges.

A Numerical Simulation Study of the Impact of Kesterites Hole Transport Materials in Quantum Dot-Sensitized Solar Cells Using SCAPS-1D

Energy generation and storage are critical challenges for developing economies due to rising populations and limited access to clean energy resources. Fossil fuels, commonly used for energy production, are costly and contribute to environmental pollution through greenhouse gas emissions. Quantum dot-sensitized solar cells (QDSSCs) offer a promising alternative due to their stability, low cost, and high-power conversion efficiency (PCE) compared to other third-generation solar cells. Kesterite materials, known for their excellent optoelectronic properties and chemical stability, have gained attention for their potential as hole transport layer (HTL) materials in solar cells. In this study, the SCAPS-1D numerical simulator was used to analyze a solar cell with the configuration FTO/TiO2/MoS2/HTL/Ag. The electron transport layer (ETL) used was titanium dioxide (TiO2), while Cu2FeSnS4 (CFTS), Cu2ZnSnS4 (CZTSe), Cu2NiSnS4 (CNTS), and Cu2ZnSnSe4 (CZTSSe) kesterite materials were evaluated as HTLs. MoS2 quantum dot served as the absorber, with FTO as the anode and silver as the back metal contact. The CFTS material outperformed the others, yielding a PCE of 25.86%, a fill factor (FF) of 38.79%, a short-circuit current density (JSC) of 34.52 mA cm-2, and an open-circuit voltage (VOC) of 1.93 V. This study contributes to the advancement of high-performance QDSSCs.

Decapsulating waste photovoltaic laminated modules by the combination treatment of thermal field and the solvent of the N-methyl-2-pyrrolidone

In order to achieve the goal of dual-carbon strategy, China has vigorously developed the photovoltaic industry. However, the life cycle of photovoltaic panels is limited, resulting in a large number of waste photovoltaic laminated modules. Waste photovoltaic laminated modules contain rich metallic and organic resources, and have high recycling value. In the process of recycling waste photovoltaic laminated modules, decapsulation is a key step. Pyrolysis was considered as the common decapsulation technology, but it would cause problems such as loss of organic resources, producing pyrolytic carbon black and toxic gases. This paper reported a wet decapsulation technology. It employed the combined treatment of thermal field and the solvent of N-methyl-2-pyrrolidone to swell ethylene vinyl acetate for liberating the materials of waste photovoltaic laminated modules. Under the conditions of 170 °C and 30 min, the 3 cm × 3 cm-sized waste photovoltaic laminated module was completely decapsulated. The analysis of Fourier transform infrared spectroscopy indicated that N-methyl-2-pyrrolidone was grafted to ethylene vinyl acetate structure, and some new groups were generated, such as N-H and C = O. Calculation results of density functional theory showed that N atom and methylene were active sites in N-methyl-2-pyrrolidone. They could react with the cross-linked bridge and side chain of ethylene vinyl acetate to form N-H and C = O groups, which made ethylene vinyl acetate lose its viscosity and produce decapsulation effect. This paper presents new scientific information for the eco-friendly wet decapsulation of waste photovoltaic laminated modules.

Shedding light on biodiversity: reviewing existing knowledge and exploring hypothesised impacts of agrophotovoltaics

The growing demand for energy and the shift towards green energy solutions have led to the conversion of open spaces and agricultural fields into photovoltaic (PV) power plants, exacerbating the "food-energy-environment" trilemma. Agrophotovoltaics (APVs), a dual-use system combining agriculture and energy production on the same land, presents a potential solution to this challenge. While the environmental impacts of ground-mounted utility-scale PV (USPV) power plants and the effects of APV systems on agricultural yields have been extensively studied and reviewed, the implications for wildlife and biodiversity remain largely unexplored. This knowledge gap is pressing, given the accelerated global adoption of APV systems and the urgency of understanding their broader ecological consequences. In this concise review, we synthesise existing literature on the impacts of USPV installations on biodiversity and the effects of APV on crop production. Building on these foundations, we propose novel hypotheses concerning the potential pathways and mechanisms through which APV systems may influence biodiversity. We explore the complex interactions between agroecosystems and natural ecosystems, examining both direct and indirect effects. Our review culminates in a set of key research questions designed to guide future studies on the biodiversity outcomes of APV deployment. Future research should comprehensively address factors such as habitat type, climate, spatial scale, technology, and agricultural practices, as well as the overarching impacts of climate change. By highlighting the importance of these variables, we aim to facilitate a nuanced understanding of how APV systems can either support or undermine biodiversity. This work not only underscores the critical need for empirical studies in this emerging field but also sets the stage for more informed and sustainable implementation of APV technologies.

Environmental impacts of a stand-alone photovoltaic system in sub-saharan Africa: A case study in Burkina Faso

This study aims to evaluate and compare the environmental impacts of stand-alone photovoltaic (PV) systems with storage installed in Burkina Faso using the life cycle assessment (LCA). SimaPro 9.4 software, Ecoinvent 3.7 database, and the ReCiPe 2018 (H) median method were used to assess the environmental impacts. The functional unit considered is "1 kWh of electricity produced in Burkina Faso by a stand-alone PV system". Four scenarios combining two variables, battery technology (lead-acid and lithium-ion) and end-of-life management (landfill and recycling), were studied to assess 08 environmental indicators. The results show that production and end-of-life management of batteries and PV modules are the main contributors to the environmental impact, with batteries' impact ranging from 73 to 98 % for lead-acid and 50-68 % for lithium-ion batteries. Compared to landfilling, recycling significantly reduces environmental impacts, achieving reductions of 17-77 % for lead-acid batteries (LABs) and 3-99 % for lithium-ion batteries (LIBs). The comparison between scenarios indicates that the LABs PV system with landfilling generates significantly higher scores across all impact categories than LIBs PV scenarios. Specifically, it shows scores over 10 times higher for human carcinogenic toxicity, 5 times higher for human non-carcinogenic toxicity, and 2 times higher for freshwater ecotoxicity. Despite extending battery lifespan, the sensitivity analysis revealed that landfill PV systems remain the most polluting, while in recycled scenarios, this extension brings them closer to the environmental performance of LIBs PV systems. The use of LIBs in photovoltaic systems is more environmentally friendly than that of LABs, regardless of the end-of-life scenario.

Comparative life cycle assessment of integrated renewable energy-based power systems

Integrated renewable-based power cycles should be employed to produce more sustainable electricity. This is a comparative life cycle assessment (LCA) of three combined power plants, encompassing: case 1 involving combined geothermal and wind, case 2 featuring combined geothermal and solar, and case 3 integrating wind and solar systems. The base case perovskite solar cell (PSC) modelling assumes a 3-year lifespan and a power conversion efficiency of 17 %. However, diverse scenarios are evaluated through a sensitivity assessment involving enhancements in lifetime and efficiency. The base case evaluation emphasizes that the phases with the most significant negative environmental effects which includes the drilling of geothermal wells, construction of wind plants, and manufacturing and installation of PSCs. The midpoint findings indicate that boosting the power conversion efficiency of PSC from 17 % to 35 % yields a notable decrease in environmental impact. Moreover, extending the lifetime from 3 to 15 years led to reduction in CO2 emissions from 0.0373 and 0.0185 kg CO2 eq/kWh to 0.026 and 0.0079 kg CO2 eq/kWh in cases 2 and 3, respectively. Assessing worst and best-case scenarios highlights significant declines in certain impact categories. In case 3, terrestrial ecotoxicity (TE), photochemical oxidant formation (POF), human toxicity (HT), marine ecotoxicity (ME), and marine eutrophication (MU) saw reductions exceeding 88 % compared to worst-case results. The environmental effects observed in cases 2 and 3 stem from toxicity and metal depletion, mainly linked to the PSC. Endpoint results revealed that when considering a PSC lifespan of 10 years or more, the detrimental ecosystem impacts of cases 2 and 3 become less severe than those of case 1. Uncertainty assessment has been done for different cases and impact categories. The study's results are also novel in which it evaluated the innovative PSC technology when integrated with other renewable resources, contrasting it with other integrated plants.

Environment random interaction of rime optimization with Nelder-Mead simplex for parameter estimation of photovoltaic models

As countries attach importance to environmental protection, clean energy has become a hot topic. Among them, solar energy, as one of the efficient and easily accessible clean energy sources, has received widespread attention. An essential component in converting solar energy into electricity are solar cells. However, a major optimization difficulty remains in precisely and effectively calculating the parameters of photovoltaic (PV) models. In this regard, this study introduces an improved rime optimization algorithm (RIME), namely ERINMRIME, which integrates the Nelder-Mead simplex (NMs) with the environment random interaction (ERI) strategy. In the later phases of ERINMRIME, the ERI strategy serves as a complementary mechanism for augmenting the solution space exploration ability of the agent. By facilitating external interactions, this method improves the algorithm's efficacy in conducting a global search by keeping it from becoming stuck in local optima. Moreover, by incorporating NMs, ERINMRIME enhances its ability to do local searches, leading to improved space exploration. To evaluate ERINMRIME's optimization performance on PV models, this study conducted experiments on four different models: the single diode model (SDM), the double diode model (DDM), the three-diode model (TDM), and the photovoltaic (PV) module model. The experimental results show that ERINMRIME reduces root mean square error for SDM, DDM, TDM, and PV module models by 46.23%, 59.32%, 61.49%, and 23.95%, respectively, compared with the original RIME. Furthermore, this study compared ERINMRIME with nine improved classical algorithms. The results show that ERINMRIME is a remarkable competitor. Ultimately, this study evaluated the performance of ERINMRIME across three distinct commercial PV models, while considering varying irradiation and temperature conditions. The performance of ERINMRIME is superior to existing similar algorithms in different irradiation and temperature conditions. Therefore, ERINMRIME is an algorithm with great potential in identifying and recognizing unknown parameters of PV models.

Review on Microreactors for Photo-Electrocatalysis Artificial Photosynthesis Regeneration of Coenzymes

In recent years, with the outbreak of the global energy crisis, renewable solar energy has become a focal point of research. However, the utilization efficiency of natural photosynthesis (NPS) is only about 1%. Inspired by NPS, artificial photosynthesis (APS) was developed and utilized in applications such as the regeneration of coenzymes. APS for coenzyme regeneration can overcome the problem of high energy consumption in comparison to electrocatalytic methods. Microreactors represent a promising technology. Compared with the conventional system, it has the advantages of a large specific surface area, the fast diffusion of small molecules, and high efficiency. Introducing microreactors can lead to more efficient, economical, and environmentally friendly coenzyme regeneration in artificial photosynthesis. This review begins with a brief introduction of APS and microreactors, and then summarizes research on traditional electrocatalytic coenzyme regeneration, as well as photocatalytic and photo-electrocatalysis coenzyme regeneration by APS, all based on microreactors, and compares them with the corresponding conventional system. Finally, it looks forward to the promising prospects of this technology.

Forecasting meteorological impacts on the environmental sustainability of a large-scale solar plant via artificial intelligence-based life cycle assessment

Although large-scale solar (LSS) is a promising renewable energy technology, it causes adverse impacts on the ecosystem, human health, and resource depletion throughout its upstream (i.e., raw material extraction to solar panel production) and downstream (i.e., plant demolition and waste management) processes. The LSS operational performance also fluctuates due to meteorological conditions, leading to uncertainty in electricity generation and raising concerns about its overall environmental performance. Hitherto, there has been no evidence-backed study that evaluates the ecological sustainability of LSS with the consideration of meteorological uncertainties. In this study, a novel integrated Life Cycle Assessment (LCA) and Artificial Neural Network (ANN) framework is developed to forecast the meteorological impacts on LSS's electricity generation and its life cycle environmental sustainability. For LCA, 18 impact categories and three damage categories are characterised and assessed by ReCiPe 2016 via SimaPro v. 9.1. For ANN, a feedforward neural network is applied via Neural Designer 5.9.3. Taking an LSS plant in Malaysia as a case study, the photovoltaic panel production stage contributes the highest environmental impact in LSS (30 % of human health, 30 % of ecosystem quality, and 34 % of resource scarcity). Aluminium recycling reduces by 10 % for human health, 10 % for ecosystem quality, and 9 % for resource scarcity. The emissions avoided by the forecasted LSS-generated electricity offset the environmental burden for human health, ecosystem quality, and resource scarcity 12-68 times, 13-73 times, and 18-98 times, respectively. The developed ANN-LCA framework can provide LSS stakeholders with data-backed insights to effectively design an environmentally conscious LSS facility, considering meteorological influences.

Comprehensive review of the global trends and future perspectives for recycling of decommissioned photovoltaic panels

With the rapid deployment of renewable energy using photovoltaic (PV) panels, the sustainable management of decommissioned PV modules has become challenging. Decommissioned modules contain heavy metals, such as copper, cadmium, and lead, and hazardous polymer substances, such as ethylene vinyl acetate, polyethylene terephthalate, and polyvinylidene fluoride, which can pose a serious threat to the environment if disposed in a landfill. In addition, the low concentration value of critical metals, such as silver, indium, and tellurium, can also be lost. In this context, recycling decommissioned PV panels can be useful to resource recovery of valuable metals while lowering environmental stress. However, the lower share of PV modules and the prolonged life of 25-30 years compared to other waste volumes (e.g., electronic waste) hinder the progress in this direction. In contrast, reaching the end-of-life of the deployed first-generation PV panels is creating attraction toward the recycling of decommissioned modules. Henceforth, exploring the commercial viability of PV recycling necessitates a review of the methodologies that have been investigated on a laboratory scale and have the potential to be up-scaled. In this review, the recent trends in various PV-recycling steps, including frame disassembly, delamination, metal extraction, and recovery, are underlined while the associated problems are determined to suggest the required improvements in future technology. Furthermore, the environmental and economic feasibility of a few techniques are discussed to establish the viability of the recycling process. This review contributes to formulating PV waste management strategies and providing future research directions.

Energy retrofitting strategies for existing buildings in Malaysia: A systematic review and bibliometric analysis

This paper comprehensively examines passive and active energy retrofit strategies as a highly effective approach for reducing building energy consumption and mitigating CO2 emissions while enhancing comfort and sustainability. The paper further examines energy simulation software and assesses the integration of renewable energy systems in building to improve energy efficiency. The review used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, ensuring a rigorous and comprehensive analysis. In addition, the study utilized bibliometric analysis with VOSviewer to provide valuable insights into the research trends and influential publications in building energy retrofits. Bibliometric analysis reveals strong collaboration among 17 authors, emphasizing their significant contributions. Keywords like energy retrofitting and efficiency are prominent, indicating their importance in academic literature. Findings show passive strategies are more effective in reducing energy consumption, though a combined approach with active strategies can yield optimal results. Retrofitting presents challenges, such as substantial initial costs and regulatory barriers. User acceptance is crucial, considering potential disruptions. The review highlights the importance of energy simulation software, with tools like EnergyPlus, eQUEST, and IES VE identified for evaluating and identifying cost-effective retrofit measures in building performance. By providing comprehensive insights into the various strategies and tools available for retrofitting buildings to achieve energy efficiency and sustainability goals, this review serves as an authoritative resource for building owners, managers, and professionals in the building industry. It offers invaluable guidance for informed decision-making and facilitates implementing effective, energy-efficient, and sustainable building retrofitting practices.

Solar reforming as an emerging technology for circular chemical industries

The adverse environmental impacts of greenhouse gas emissions and persistent waste accumulation are driving the demand for sustainable approaches to clean-energy production and waste recycling. By coupling the thermodynamically favourable oxidation of waste-derived organic carbon streams with fuel-forming reduction reactions suitable for producing clean hydrogen or converting CO2 to fuels, solar reforming simultaneously valorizes waste and generates useful chemical products. With appropriate light harvesting, catalyst design, device configurations and waste pre-treatment strategies, a range of sustainable fuels and value-added chemicals can already be selectively produced from diverse waste feedstocks, including biomass and plastics, demonstrating the potential of solar-powered upcycling plants. This Review highlights solar reforming as an emerging technology that is currently transitioning from fundamental research towards practical application. We investigate the chemistry and compatibility of waste pre-treatment, introduce process classifications, explore the mechanisms of different solar reforming technologies, and suggest appropriate concepts, metrics and pathways for various deployment scenarios in a net-zero-carbon future.

Weakly Supervised Solar Panel Mapping via Uncertainty Adjusted Label Transition in Aerial Images

This paper proposes a novel uncertainty-adjusted label transition (UALT) method for weakly supervised solar panel mapping (WS-SPM) in aerial Images. In weakly supervised learning (WSL), the noisy nature of pseudo labels (PLs) often leads to poor model performance. To address this problem, we formulate the task as a label-noise learning problem and build a statistically consistent mapping model by estimating the instance-dependent transition matrix (IDTM). We propose to estimate the IDTM with a parameterized label transition network describing the relationship between the latent clean labels and noisy PLs. A trace regularizer is employed to impose constraints on the form of IDTM for its stability. To further reduce the estimation difficulty of IDTM, we incorporate uncertainty estimation to first improve the accuracy of noisy dataset distillation and then mitigate the negative impacts of falsely distilled examples with an uncertainty-adjusted re-weighting strategy. Extensive experiments and ablation studies on two challenging aerial data sets support the validity of the proposed UALT.

Development of NaCl-MgCl2-CaCl2 Ternary Salt for High-Temperature Thermal Energy Storage Using Machine Learning

NaCl-MgCl2-CaCl2 eutectic ternary chloride salts are potential heat transfer and storage materials for high-temperature thermal energy storage. In this study, first-principles molecular dynamics simulation results were used as a data set to develop an interatomic potential for ternary chloride salts using a neural network machine learning method. Deep potential molecular dynamics (DPMD) simulations were performed to predict the microstructure and thermophysical properties of the NaCl-MgCl2-CaCl2 ternary salt. This work reveals that DPMD simulations can accurately calculate the microstructure and thermophysical properties of ternary chloride salts. The association strength of chloride ions and cations follows the order of Mg2+ > Ca2+ > Na+, and the coordination number decreases gradually with increasing temperature, indicating a progressively looser and more disordered molten structure. Furthermore, thermophysical properties, such as density, specific heat capacity, thermal conductivity, and viscosity, are in good agreement with the experimental measurements. Machine learning molecular dynamics will provide a feasible multivariate molten salt exploration method for the design of next-generation solar power plants and thermal energy storage systems.

Impact of belt and road initiative policy and interacting effect of renewable energy toward carbon neutrality

The Belt and Road Initiative (BRI) represents a comprehensive developmental blueprint that has been deployed across numerous Asian, European, and African nations, aimed at fostering economic growth and enhanced regional connectivity. However, concerns have been raised about its potential impact on the environment, specifically in the context of carbon dioxide (CO2) emissions. Employing non-parametric analytical techniques, this research undertakes an empirical investigation into the relationship between economic growth (GDP), renewable energy consumption (REC), and CO2 emissions within the context of BRI participant countries, spanning the years from 2000 to 2018. The findings of this study reveal that REC exerts a pronounced and statistically significant mitigating effect on CO2 emissions, implying that an increase in REC corresponds to a reduction in CO2 emissions. In contrast, trade openness (TRADE) exhibits a positive and statistically significant influence on CO2 emissions, signifying that greater trade openness is associated with heightened CO2 emissions. However, the observed effects of GDP, fixed telephone subscriptions (FTS), and mobile cellular subscriptions (MCS) on CO2 emissions remain inconclusive, as their impact lacks statistical significance. The effect estimates of covariates on CO2 emissions using various models reveal that REC and TRADE significantly affect CO2 emissions, while GDP, FTS, and MCS still yield uncertain results. The outcomes draw attention to the necessity of implementing policies that encourage the use of REC and reducing trade openness as an efficient way of neutralizing CO2 emissions. This research provides valuable insights into the impact of the BRI on CO2 emissions and emphasizes the importance of addressing the environmental implications of this initiative. Policymakers should carefully consider these findings and develop effective strategies to foster sustainable development.

Impact of alloying iron pyrite by ruthenium on its band gap values and its insight to photovoltaic performance

In pursuit of augmenting the band gap value of thin films composed of F e S 2 Pyrite, our study encompasses both theoretical and experimental investigations. Specifically, we sought to delve into the electronic and optical properties of F e S 2 alloyed with ruthenium, denoted as F e 1 - x R u x S 2 , where x varied across a range of values (x = 0.3966, 0.1586, 0.0496, 0.0347, 0.0106, and 0.00). Our theoretical analysis employed the Linear Muffin-Tin Orbital technique within the Atomic-Sphere approximation (LMTO-ASA) framework, focusing on the density of states. In parallel, our experimental samples were fabricated via a cost-effective and straightforward method involving the sulfuration of amorphous iron oxide thin films, which were deposited through spray pyrolysis of an aqueous solution containing FeCl3.6H2O onto heated glass substrates at 400 °C. This comprehensive investigation sheds light on the influence of alloying on the atomic structure and the optical characteristics of R u x F e 1 - x S 2 samples. Utilizing X-ray diffraction (XRD) and optical characterizations, we observed a notable widening of the band gap of F e S 2 , ranging from 0.90508 to 1.38 eV, when approximately 1.06% of the Fe atoms were replaced with ruthenium atoms (x = 0.0106 concentration of Ru). This finding holds significant implications for the potential applications of our samples in photovoltaic technologies.

Performance analysis of digitally controlled nonlinear systems considering time delay issues

In this paper, a comprehensive investigation into discretization, effective sample time selection considering delays in the system, and time and frequency domain analysis of a DC-DC buck converter, which plays a vital role in photovoltaic (PV) systems, is conducted to enhance the understanding of their dynamic behavior, optimize control algorithms, improve system efficiency, and ensure reliable power conversion in photovoltaic applications. To effectively address the non-linear behavior and enhance digital control of a buck converter by selecting the best sample time, several approaches can be employed. These include accurate modeling and identification of non-linear elements, development of advanced control algorithms that account for non-linearities, implementation of adaptive control techniques, and utilization of feedback mechanisms to compensate for deviations from linearity. By considering and mitigating the non-linear behavior, digital control systems can achieve improved accuracy, stability, and transient behavior in regulating the buck converter's output waveforms (voltage or current). The results of the study demonstrated that the trapezoidal integration method which is also known as bilinear approximation, or Tustin's approach outperformed other commonly used discretization methods, such as first-order hold (FOH), zero-order hold (ZOH), impulse response matching (impulse invariant), and matched pole-zero (MPZ) technique, in dual-domain (both time and frequency) analysis. The key finding highlighting the superiority of the bilinear approximation was its ability to achieve the closest match in the frequency domain bridging the continuous-time and discrete systems. This finding emphasizes the significance of the bilinear approach in preserving the frequency characteristics of the original continuous-time system during discretization. By employing this method, the discrete system closely approximated the behavior of its continuous-time counterpart, ensuring accurate frequency-domain representation.

Reliability and performance evaluation of a solar PV-powered underground water pumping system

The operation and effectiveness of a solar-powered underground water pumping system are affected by many environmental and technical factors. The impact of these factors must be investigated to be considered when developing these systems and to ensure their dependability. This study evaluated the dependability and performance of photovoltaic water pumping system (PVWPS) under real operating conditions by examining the effects of solar irradiance, panels' temperature, and components' efficiency. From December 2020 to June 2021, experiments were conducted on a 10 hp PVWPS located in Bani Salamah, Al-Qanater-Giza Governorate, Egypt, at latitude 30.3° N, longitude 30.8° E, and 19 m above sea level. The irradiance values reached 755.7, 792.7, and 805.7 W/m2 at 12:00 p.m. in December, March, and June, respectively. Furthermore, the irradiance has a significant impact on the pump flow rate, as the amount of pumped water during the day reached 129, 164.1, and 181.8 m3/day, respectively. The panels' temperatures rose to 35.7 °C, 39.9 °C, and 44 °C, respectively. It was observed that when the temperature rises by 1 degree Celsius, efficiency falls by 0.48%. The average efficiency of photovoltaic solar panels reached its highest value in March (13.8%) and its lowest value in December (13%).

Imperfect makes perfect: defect engineering of photoelectrodes towards efficient photoelectrochemical water splitting

Photoelectrochemical (PEC) water splitting for hydrogen evolution has been considered as a promising technology to solve the energy and environmental issues. However, the solar-to-hydrogen (STH) conversion efficiencies of current PEC systems are far from meeting the commercial demand (10%) due to the lack of efficient photoelectrode materials. The recent rapid development of defect engineering of photoelectrodes has significantly improved the PEC performance, which is expected to break through the bottleneck of low STH efficiency. In this review, the category and the construction methods of different defects in photoelectrode materials are summarized. Based on the in-depth summary and analysis of existing reports, the PEC performance enhancement mechanism of defect engineering is critically discussed in terms of light absorption, carrier separation and transport, and surface redox reactions. Finally, the application prospects and challenges of defect engineering for PEC water splitting are presented, and the future research directions in this field are also proposed.

Embracing the future of circular bio-enabled economy: unveiling the prospects of microbial fuel cells in achieving true sustainable energy

Sustainable development and energy security, highlighted by the United Nations Sustainable Development Goals (SDGs), necessitate the use of renewable and sustainable energy sources. However, upon careful evaluation of literature, we have discovered that many existing and emerging renewable energy systems (RESs) prioritize renewability over true sustainability. These systems not only suffer from performance inconsistencies and lack of scalability but also fall short in fully embodying the principles of sustainability and circular economy. To address this gap, we propose considering microbial fuel cells (MFCs) as a viable alternative and integral part of the renewable energy ecosystem. MFCs harness the omnipresence, abundance, and cost-effectiveness of their essential components, making them a promising candidate. Through our comprehensive analysis, we shed light on the limitations and advancements of this technology, which underscore the remarkable potential of MFCs to revolutionize our perception of clean, sustainable energy.

A Comparison of Capacitive Deionization and Membrane Capacitive Deionization Using Novel Fabricated Ion Exchange Membranes

Another technique for desalination, known as membrane capacitive deionization (MCDI), has been investigated as an alternative. This approach has the potential to lower the voltage that is required, in addition to improving the ability to renew the electrodes. In this study, the desalination effectiveness of capacitive deionization (CDI) was compared to that of MCDI, employing newly produced cellulose acetate ion exchange membranes (IEMs), which were utilized for the very first time in MCDI. As expected, the salt adsorption and charge efficiency of MCDI were shown to be higher than those of CDI. Despite this, the unique electrosorption behavior of the former reveals that ion transport via the IEMs is a crucial rate-controlling step in the desalination process. We monitored the concentration of salt in the CDI and MCDI effluent streams, but we also evaluated the pH of the effluent stream in each of these systems and investigated the factors that may have caused these shifts. The significant change in pH that takes place during one adsorption and desorption cycle in CDI (pH range: 2.3-11.6) may cause problems in feed water that already contains components that are prone to scaling. In the case of MCDI, the fall in pH was only slightly more noticeable. Based on these findings, it appears that CDI and MCDI are promising new desalination techniques that has the potential to be more ecologically friendly and efficient than conventional methods of desalination. MCDI has some advantages over CDI in its higher salt removal efficiency, faster regeneration, and longer lifetime, but it is also more expensive and complex. The best choice for a particular application will depend on the specific requirements.

Comprehensive review of environmental factors influencing the performance of photovoltaic panels: Concern over emissions at various phases throughout the lifecycle

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.

A Novel Photo-Thermal-Electric Conversion System with an Integrated Support Material

In conventional photo-thermal-electric conversion systems, the photo-thermal conversion module is coupled to a thermoelectric conversion module. However, the physical contact interface between the modules causes serious energy loss. In order to solve this problem, a novel photo-thermal-electric conversion system with an integrated support material has been developed, with a photo-thermal conversion component at the top, an inside thermoelectric conversion component, and a cooling component at the bottom, surrounded by a water conduction component. The supporting materials of each part are polydimethylsiloxane (PDMS), and there is no apparent physical interface between each part. This integrated support material reduces the heat loss caused by the mechanically coupled interfaces in traditional components. In addition, the confined edge 2D water transport path effectively reduces the heat loss due to water convection. Under 1 sun irradiation, the water evaporation rate and open-circuit voltage of the integrated system reach 2.46 kg m^-2 h^-1 and 30 mV, respectively, and are nearly 1.4 times and 5.8 times higher than those of non-integrated systems.

Membrane-based carbon capture: Recent progress, challenges, and their role in achieving the sustainable development goals

The rapid growth in the consumption of fossil fuels resulted in climate change and severe health issues. Among the different proposed methods to control climate change, carbon capture technologies are the best choice in the current stage. In this study, the various membrane technologies used for carbon capture and their impact on achieving sustainable development goals (SDGs) are discussed. Membrane-based carbon capture processes in pre-combustion and post-combustion, which are known as membrane gas separation (MGS) and membrane contactor (MC), respectively, along with the process of fabrication and the different limitations that hinder their performances are discussed. Additionally, the 17 SDGs, where each representing a crucial topic in the current global task of a sustainable future, that are impacted by membrane-based carbon capture technologies are discussed. Membrane-based carbon capture technologies showed to have mixed impacts on different SDGs, varying in intensity and usefulness. It was found that the membrane-based carbon capture technologies had mostly influenced SDG 7 by enhancement in the zero-emission production, SDG 9 by providing 38-42% cost savings compared to liquid absorption, SDG 3 through reducing pollution and particulate matter emissions by 23%, and SDG 13, with SDG 13 being the most positively influenced by membrane-based carbon capture technologies, as they significantly reduce the CO₂ emissions and have high CO₂ capture yields (80-90%), thus supporting the objectives of SDG 13 in combatting climate change.

Reshoring silicon photovoltaics manufacturing contributes to decarbonization and climate change mitigation

The globalized supply chain for crystalline silicon (c-Si) photovoltaic (PV) panels is increasingly fragile, as the now-mundane freight crisis and other geopolitical risks threaten to postpone major PV projects. Here, we study and report the results of climate change implications of reshoring solar panel manufacturing as a robust and resilient strategy to reduce reliance on foreign PV panel supplies. We project that if the U.S. could fully bring c-Si PV panel manufacturing back home by 2035, the estimated greenhouse gas emissions and energy consumption would be 30% and 13% lower, respectively, than having relied on global imports in 2020, as solar power emerges as a major renewable energy source. If the reshored manufacturing target is achieved by 2050, the climate change and energy impacts would be further reduced by 33% and 17%, compared to the 2020 level. The reshored manufacturing demonstrates significant progress in domestic competitiveness and toward decarbonization goals, and the positive reductions in climate change impacts align with the climate target.

Hydrogen Evolution Reaction Performance of Ni-Co-Coated Graphene-Based 3D Printed Electrodes

Additive manufacturing has been a very promising topic in recent years for research and development studies and industrial applications. Its electrochemical applications are very popular due to the cost-effective rapid production from the environmentally friendly method. In this study, three-dimensional (3D) printed electrodes are prepared by Ni and Co coatings in different molar ratios. Different Ni/Co molar ratios (x:y) of the Ni/Co/x:y alloys are prepared as 1:1, 1:4, and 4:1 and they are named Ni/Co/1:1, Ni/Co/4:1, and Ni/Co/1:4, respectively. According to the results, when the 3D electrode samples are coated with Ni and Co at different molar ratios, the kinetic performance of the NiCo-coated 3D electrode samples for hydrogen evolution reaction is enhanced compared to that of the uncoated 3D electrode sample. The results indicate that the Ni/Co/1:4-coated 3D electrode has the highest kinetic activity for hydrogen evolution reactions (HERs). The calculated Tafel's slope and overpotential value (η₁₀) for HER are determined as 164.65 mV/dec and 101.92 mV, respectively. Moreover, the Ni/Co/1:4-coated 3D electrode has an 81.2% higher current density than the other electrode. It is observed that the 3D printing of the electrochemical electrodes is very promising when they are coated with Ni-Co metals in different ratios. This study provides a new perspective on the use of 3D printed electrodes for high-performance water electrolysis.

Life cycle assessment of photovoltaic electricity production by mono-crystalline solar systems: a case study in Canada

Photovoltaic (PV) system is widely recognized as one of the cleanest technologies for electricity production, which transforms solar energy into electrical energy. However, there are considerable amounts of emissions during its life cycle. In this study, life cycle assessment (LCA) was used to evaluate the environmental and human health impacts of PV electricity production in Canada. The PV potential varies considerably among the provinces, with higher values in Manitoba (MB), Saskatchewan (SK), Alberta (AB), and southern Ontario (ON). A grid-connected slanted-roof mono-crystalline silicon (mono-Si) PV system with a capacity of 3 kWp (the peak power of the system in kilowatts) in Toronto, Ontario, was considered as the case study system. Ten impact categories were considered including (1) acidification, (2) carcinogenic, (3) ecotoxicity, (4) eutrophication, (5) fossil fuel depletion, (6) global warming, (7) non-carcinogenic, (8) ozone depletion, (9) respiratory effects, and (10) smog. Among the four components of the PV system, i.e., mono-Si panel, mounting system, inverter, and electric installation, the mono-Si panel production was the highest contributor in seven out of ten impact categories, including acidification (68%), eutrophication (60%), fossil fuel depletion (81%), global warming (77%), ozone depletion (88%), respiratory effects (74%), and smog (70%). For the other three processes, the electric installation contributed most to ecotoxicity at 58%, followed by the mounting system in the carcinogenic category (29%), and the inverter in the non-carcinogenic category (31%). By normalizing the impacts based on the reference scores in Canada, it was found that the ecotoxicity and carcinogenic categories had dominant contributions to the overall impact by 53% and 42%, respectively. The global warming potential impact was estimated as 79 gr CO₂ eq /kWh, which is close to the mean value of 79.5 gr CO₂ eq /kWh, reported in the literature. The sensitivity analysis indicated that a 10% increase in the panel and mounting system area will increase the ozone depletion and carcinogenic categories by 8.1% and 2.8%, respectively.

Decarbonization of Power and Industrial Sectors: The Role of Membrane Processes

Carbon dioxide (CO₂) is the single largest contributor to climate change due to its increased emissions since global industrialization began. Carbon Capture, Storage, and Utilization (CCSU) is regarded as a promising strategy to mitigate climate change, reducing the atmospheric concentration of CO₂ from power and industrial activities. Post-combustion carbon capture (PCC) is necessary to implement CCSU into existing facilities without changing the combustion block. In this study, the recent research on various PCC technologies is discussed, along with the membrane technology for PCC, emphasizing the different types of membranes and their gas separation performances. Additionally, an overall comparison of membrane separation technology with respect to other PCC methods is implemented based on six different key parameters-CO₂ purity and recovery, technological maturity, scalability, environmental concerns, and capital and operational expenditures. In general, membrane separation is found to be the most competitive technique in conventional absorption as long as the highly-performed membrane materials and the technology itself reach the full commercialization stage. Recent updates on the main characteristics of different flue gas streams and the Technology Readiness Levels (TRL) of each PCC technology are also provided with a brief discussion of their latest progresses.

Aluminum Cation Doping in Ruddlesden-Popper Sr2TiO4 Enables High-Performance Photocatalytic Hydrogen Evolution

Hydrogen (H2) is regarded as a promising and renewable energy carrier to achieve a sustainable future. Among the various H2 production routes, photocatalytic water splitting has received particular interest; it strongly relies on the optical and structural properties of photocatalysts such as their sunlight absorption capabilities, carrier transport properties, and amount of oxygen vacancy. Perovskite oxides have been widely investigated as photocatalysts for photocatalytic water splitting to produce H2 because of their distinct optical properties, tunable band gaps and excellent compositional/structural flexibility. Herein, an aluminum cation (Al3+) doping strategy is developed to enhance the photocatalytic performance of Ruddlesden-Popper (RP) Sr2TiO4 perovskite oxides for photocatalytic H2 production. After optimizing the Al3+ substitution concentration, Sr2Ti0.9Al0.1O4 exhibits a superior H2 evolution rate of 331 μmol h−1 g−1, which is ~3 times better than that of Sr2TiO4 under full-range light illumination, due to its enhanced light harvesting capabilities, facilitated charge transfer, and tailored band structure. This work presents a simple and useful Al3+ cation doping strategy to boost the photocatalytic performance of RP-phase perovskites for solar water splitting.

DFT investigation of the electronic and optical properties of hexagonal MX2/ZrXO (M = W, Mo and X = S, Se) van der Waals heterostructures for photovoltaic solar cell application

The van der Waals heterostructure of Janus materials with a TMD monolayer was used to create a two-dimensional class of nanomaterials for photovoltaic solar cell applications. It is one of the potential methods for enhancing the performance of photovoltaic systems. Two monolayers of different 2D materials, Janus (ZrXO) and TMDs (MX₂), are stacked together to form the heterojunction. Based on density functional theory structural, electrical, and optical properties were investigated. The favorable stacking and stability of the MX₂/ZrXO (M = W, Mo and X = S, Se) van der Waals heterostructures are confirmed through binding energies, phonon dispersion and ab initio molecular dynamics calculations. Standard excitonic peaks, which correspond to the bound valence-band hole and conduction-band electron, as well as excitonic peaks involving the mid-gap charges, can be seen in the system's computed absorption spectrum. MX₂/ZrXO van der Waals heterostructures are excellent photovoltaic candidates with a maximum achived power conversion efficiency of above 22%. Furthermore, we discovered that the heterostructure materials have a high absorption efficiency which is good for the intended photovoltaic solar cell application.

Recent progress in use of MXene in perovskite solar cells: for interfacial modification, work-function tuning and additive engineering

The use of perovskites in photovoltaic and related industries has achieved tremendous success over the last decade. However, there are still obstacles to overcome in terms of boosting their performance and resolving stability issues for future commercialization. The introduction of a new 2D material of halide perovskites is now the key advancement in boosting the solar energy conversion efficiency. The implication of a new 2D material (MXene) in perovskite solar cells has been initiated since its first report in 2018, showing excellent transparency, electrical conductivity, carrier mobility, superior mechanical strength, and tunable work function. Based on distinctive features at the hetero-interface, halide perovskite and MXene heterostructures (HPs/Mx) have recently exhibited exceptional improvements in both the performance and stability of perovskite solar cells. Furthermore, the wide families of HPs and MXene materials allow playing with the composition and functionalities of HP/Mx interfaces by applying rational designing and alterations. In this review a comprehensive study of implementing MXenes in perovskite solar cells is presented. First, the implementation of MXenes in perovskites as an additive, and then in charge extraction layers (HTL/ETL), is described in detail. It is worth noting that still only Ti₃C₂T_x, Nb₂CT_x,V₂CT_x MXene is being incorporated into perovskite photovoltaics. Finally, the present obstacles in the use of MXenes in PSCS are discussed, along with the future research potential. This review is expected to provide a complete and in-depth description of the current state of research and to open up new opportunities for the study of other MXenes in PSCs.

A Closer Look at the Environmental Impact of Solar and Wind Energy

Moving towards a sustainable society implies constant improvement in the way energy is supplied and consumed, with wider implementation of solar and wind energy facilities in stand-alone or hybrid configurations. The goal of this work is to evaluate the lifecycle performance (construction and operation-related impact) of large-scale solar and wind energy systems and to compare it with conventional coal and natural gas fossil fuel plants under similar conditions. Environmental analyses of energy conversion systems today usually neglect the construction-related environmental impact of fossil fuel plants, because it is significantly smaller than the impact related to the operation of the plant. However, the construction of large-scale renewable plants implies the use of rare materials, transport-related emissions, and other environmentally impactful activities. The plants evaluated here are configured and compared for similar emissions and similar power output. It is found that the life-cycle environmental impact of the renewable plants could, in some specific cases, exceed that of the fossil fuel plants. Understanding the reasons behind this and the possible limitations of the different technologies can help plan for sustainable energy systems in the future. Finally, solutions to minimize the impact of renewable energy are proposed for more environmentally friendly implementation and future research.

Photovoltaic Fuzzy Logical Control MPPT Based on Adaptive Genetic Simulated Annealing Algorithm-Optimized BP Neural Network

The P–U characteristic curve of the photovoltaic (PV) cell is a single peak curve with only one maximum power point (MPP). However, the fluctuation of the irradiance level and ambient temperature will cause the drift of MPP. In the maximum power point tracking (MPPT) algorithm of PV systems, BP neural network (BPNN) has an unstable learning rate and poor performance, while the genetic algorithm (GA) tends to fall into local optimum. Therefore, a novel PV fuzzy MPPT algorithm based on an adaptive genetic simulated annealing-optimized BP neural network (AGSA-BPNN-FLC) is proposed in this paper. First, the adaptive GA is adopted to generate the corresponding population and increase the population diversity. Second, the simulated annealing (SA) algorithm is applied to the parent and offspring with a higher fitness value to improve the convergence rate of GA, and the optimal weight threshold of BPNN are updated by GA and SA algorithm. Third, the optimized BPNN is employed to predict the MPP voltage of PV cells. Finally, the fuzzy logical control (FLC) is used to eliminate local power oscillation and improve the robustness of the PV system. The proposed algorithm is applied and compared with GA-BPNN, simulated annealing-genetic (SA-GA), particle swarm optimization (PSO), grey wolf optimization (GWO) and FLC algorithm under the condition that both the irradiance and temperature change. Simulation results indicate that the proposed MPPT algorithm is superior to the above-mentioned algorithms with efficiency, steady-state oscillation rate, tracking time and stability accuracy, and they have a good universality and robustness.

Environmental trade-offs of direct air capture technologies in climate change mitigation toward 2100

Direct air capture (DAC) is critical for achieving stringent climate targets, yet the environmental implications of its large-scale deployment have not been evaluated in this context. Performing a prospective life cycle assessment for two promising technologies in a series of climate change mitigation scenarios, we find that electricity sector decarbonization and DAC technology improvements are both indispensable to avoid environmental problem-shifting. Decarbonizing the electricity sector improves the sequestration efficiency, but also increases the terrestrial ecotoxicity and metal depletion levels per tonne of CO2 sequestered via DAC. These increases can be reduced by improvements in DAC material and energy use efficiencies. DAC exhibits regional environmental impact variations, highlighting the importance of smart siting related to energy system planning and integration. DAC deployment aids the achievement of long-term climate targets, its environmental and climate performance however depend on sectoral mitigation actions, and thus should not suggest a relaxation of sectoral decarbonization targets.

Effect of dust and methods of cleaning on the performance of solar PV module for different climate regions: Comprehensive review

Recent achievement and progress in solar PV play a significant role in controlling climate change. This study reviewed comprehensively electrical characteristics, life cycle of dust, optical characteristics, and different cleaning techniques related to the effect of dust on the performance of PV modules throughout different climate regions of the world. The power maximum power point (MPP) and curve of PV module under the effect of irradiance and temperature were presented. The effect of dust (shading) on the electrical efficiency of PV module was discussed based on soft, partial, and complete (soiling) shading. The physical properties of dust around the globe such as PM₁₀ concentration, dust loading (mgm^-2), and fine dust particles concentration were covered and discussed. Reasons behind the accumulation of dust based on, location and installation factors, dust type, and environmental factors. Environmental reasons causing dust and dust removal in accordance with the life cycle of dust was covered in detail. All the reasons that cause the generation, accumulation and removal of dust during its life cycle were explained. All forces responsible for the adhesion phase of the dust life cycle were presented. The effect of dust on PV module transmittance and electrical parameters module were discussed in detail based on physical properties of the dust at its location and installation conditions. Self-cleaning super hydrophobic surfaces based on methods such as solvents, vapor-assisted coating, powder coating, and polymerization were discussed. All cleaning technologies, including self-cleaning technologies, based on the material coating used, and the manufacturing of PV cells was compared. The future prospective for PV technologies and cleaning methods were also covered.

Kirigami-inspired Automatically Self-inclining Bifacial Solar Cell Arrays to Enhance Energy Yield under Both Sunny and Cloudy Conditions

The application of photovoltaics (PVs) is expanding in various locations ranging from industrial facilities to residential housing. The emphasized concept in the PVs field is shifting from “watt-per-cost” to “energy-yield-per-watt.” To attain a high energy yield, fixed modules are not well suited to capture both direct and omnidirectional light. To achieve a high energy yield under both light conditions, we propose a self-inclining bifacial solar cell array fabricated by integrating a photothermal actuator, which senses incident light by itself, and actuating solar cells that incline at the appropriate angle to maximize captured light. In the vertical illumination state, the specific power of the self-inclining bifacial two-cell array is 11% higher than a fixed-angle aligned array. In an outside environment with a large proportion of diffused light, the self-inclining bifacial two-cell array also shows higher performance. We expect this work to enable PVs to be applied without regard to weather conditions.

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Proposing self-inclinable bifacial solar cell array depends on the weather condition

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It can automatically change its alignment angle using a photothermal actuator

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By self-incline at the appropriate angle, maximize captured light

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It shows better performance under predominantly diffused incident light

Comparison of Feedforward Perceptron Network with LSTM for Solar Cell Radiation Prediction

Intermittency of electrical power in developing countries, as well as some European countries such as Turkey, can be eluded by taking advantage of solar energy. Correct prediction of solar radiation constitutes a very important step to take advantage of PV solar panels. We propose an experimental study to predict the amount of solar radiation using a classical artificial neural network (ANN) and deep learning methods. PV panel and solar radiation data were collected at Duzce University in Turkey. Moreover, we included meteorological data collected from the Meteorological Ministry of Turkey in Duzce. Data were collected on a daily basis with a 5-min interval. Data were cleaned and preprocessed to train long-short-term memory (LSTM) and ANN models to predict the solar radiation amount of one day ahead. Models were evaluated using coefficient of determination (R2), mean square error (MSE), root mean squared error (RMSE), mean absolute error (MAE), and mean biased error (MBE). LSTM outperformed ANN with R2, MSE, RMSE, MAE, and MBE of 0.93, 0.008, 0.089, 0.17, and 0.09, respectively. Moreover, we compared our results with two similar studies in the literature. The proposed study paves the way for utilizing renewable energy by leveraging the usage of PV panels.

Photo-Charging of Li(Ni0.65Co0.15Mn0.20)O2 Lithium-Ion Battery Using Silicon Solar Cells

This study reports an integrated device in which a lithium-ion battery (LIB) and Si solar cells are interconnected. The LIB is fabricated using the Li(Ni_0.65Co_0.15Mn_0.20)O₂ (NCM622) cathode and the Li₄Ti₅O₁₂ (LTO) anode. The surface and shape morphologies of the NCM and LTO powders were investigated by field emission scanning electron microscopy (FE-SEM). In addition, the structural properties were thoroughly examined by X-ray diffraction (XRD). Further, their electrochemical characterization was carried out on a potentiostat. The specific discharge capacity of the NCM cathode (half-cell) was 188.09 mAh/g at 0.1 C current density. In further experiments, the NCM-LTO full-cell has also shown an excellent specific capacity of 160 mAh/g at a high current density of 1 C. Additionally, the capacity retention was outstanding, with 99.63% at 1 C after 50 cycles. Moreover, to meet the charging voltage requirements of the NCM-LTO full-cell, six Si solar cells were connected in series. The open-circuit voltage (V_OC) and the short-circuit photocurrent density (J_SC) for the Si solar cells were 3.37 V and 5.42 mA/cm². The calculated fill factor (FF) and efficiency for the Si solar cells were 0.796 and 14.54%, respectively. Lastly, the integrated device has delivered a very high-power conversion-storage efficiency of 7.95%.

Impact of COVID-19 on the Renewable Energy Sector and Mitigation Strategies

This review explores the impact of the COVID-19 pandemic on the renewable energy (RE) sector, especially in countries with the highest RE capacities, e.g., the USA, China, India, and the EU. It highlights stimulus packages put in place by governments worldwide and their sustainability to cushion the RE sector. Commissioning of RE projects has stalled due to lack of funding allocation and interruptions in the supply of equipment and components due to lockdown measures. Despite the need to fund COVID-19 vaccination programs and other related health services, the world must not neglect other sectors of the economy, creating more problems, such as worsening the climate change situation in the long run. This review aims to present the information needed to sustain future energy during the COVID-19 global pandemic.

Applicability of Hydropower Generation and Pumped Hydro Energy Storage in the Middle East and North Africa

Energy storage for medium- to large-scale applications is an important aspect of balancing demand and supply cycles. Hydropower generation coupled with pumped hydro storage is an old but effective supply/demand buffer that is a function of the availability of a freshwater resource and the ability to construct an elevated water reservoir. This work reviews the technological feasibility of hydropower generation and also pumped hydro storage and its geographical distribution around the world. There is also an emphasis on installations in the Middle East and North Africa (MENA) in terms of available capacity as well as past and future developments and expansions. A discussion is presented on a project taking place in the United Arab Emirates (UAE) in the Hatta region, which has a water reservoir that would be fit for utilization for pumped hydro storage applications. Once the project is commissioned in 2024, it will provide an estimated 2.06 TWh per year, helping the UAE achieve the goal of relying on 25% renewable energy resources in their energy mix by 2030. These results were obtained by using EnergyPLAN software to project the effect of utilizing various energy resources to face the expected demand of ~38 TWh in 2030.

Parameter Estimation-Based Slime Mold Algorithm of Photocatalytic Methane Reforming Process for Hydrogen Production

The key contribution of this paper is to determine the optimal operating parameters of the methane reforming process for hydrogen production. The proposed strategy contained two phases: ANFIS modelling and optimization. Four input controlling parameters were considered to increase the hydrogen: irradiation time (min), metal loading, methane concentration, and steam concentration. In the first phase, an ANFIS model was created with the help of the experimental data samples. The subtractive clustering (SC) technique was used to generate the fuzzy rules. In addition, the Gaussian-type and weighed average were used for the fuzzification and defuzzification methods, respectively. The reliability of the resulting model was assessed statistically by RMSE and the correlation (R2) measures. The small RMSE value and high R2 value of testing samples assured the correctness of the modelling phase, as they reached 0.0668 and 0.981, respectively. Based on the robust model, the optimization phase was applied. The slime mold algorithm (SMA), as a recent as well as simple optimizer, was applied to look for the best set of parameters that maximizes hydrogen production. The resulting values were compared by the findings of three competitive optimizers, namely particle swarm optimization (PSO), Harris hawks optimization (HHO), and evolutionary strategy HHO (EESHHO). By running the optimizers 30 times, the statistical results showed that the SMA obtained the maximum value with high mean, standard deviation, and median. Furthermore, the proposed strategy of combining the ANFIS modelling and the SMA optimizer produced an increase in the hydrogen production by 15.7% in comparison to both the experimental and traditional RSM techniques.

High energy storage quasi-solid-state supercapacitor enabled by metal chalcogenide nanowires and iron-based nitrogen-doped graphene nanostructures

Transition metal selenides (TMS) have excellent research prospects and significant attention in supercapacitors (SCs) owing to their high electrical conductivity, superior electrochemical activity and excellent structural stability. However, the commercial utilization of TMS remains challenge due to their elaborate synthesis. Present study designed a hierarchical cobalt selenide (CoSe₂) nanowire array on Ni-foam to serve as a positive electrode for asymmetric SCs (ASCs). The nanowires-like morphology of CoSe₂ was highly advantageous for SCs, as it offered enhanced electrical conductivity, plenty of surface sites, and short ion diffusion. The as-obtained, CoSe₂ nanowire electrode demonstrated outstanding electrochemical features, with an areal capacity of 1.08 mAh cm^-2 at 3 mA cm^-2, high-rate performance (69.5 % at 50 mA cm^-2), as well as outstanding stability after 10,000 cycles. The iron titanium nitride@nitrogen-doped graphene (Fe-TiN@NG) was prepared as a negative electrode to construct the ASCs cell. The obtained ASCs cell illustrated an energy density of 91.8 W h kg^-1 at a power density of 281.4 W kg^-1 and capacity retention of 94.6% over 10,000 cycles. The overall results provide a more efficient strategy to develop redox-ambitious active materials with a high capacity for advanced energy-storage systems.