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Accurate weather forecasting is increasingly crucial as climate change intensifies the unpredictability of weather patterns, posing challenges to traditional forecasting models reliant on human observation or numerical methods. Researchers are working on precise weather forecasting to improve our preparedness, enabling fast response to any disaster. Among other techniques, deep learning is a prudent method to predict weather forecasts since it can automatically learn and train from a vast amount of data to generate and portray accurate features of an incident. This study evaluates deep learning techniques for weather forecasting based on different meteorological characteristics. This paper examines a few weather variables to evaluate the prediction performance of several deep learning solutions using TensorFlow and pre-trained Keras applications models. For this purpose, the top ten accuracy-based deep learning model architectures have been investigated and evaluated. The operation of each model is distinct. Models like EfficientNetB7, ResNet, MobileNet, VGG19, Xception Inception, ResNetV2, and VGG16 employ a combination of image classification and deep learning models to predict the weather. The WEAPD dataset of 6877 images representing 11 weather phenomena categories was utilized, and the models were trained and validated using an 80:10:10 split. Predictions, extraction of features, and fine-tuning of models were achieved with an accuracy of up to 83.39%. Most models performed well in image classification, enhancing the proposed framework and achieving significant precision in generating weather photos and reports.

Abstract This study investigates the viability of hybrid photovoltaic (PV), wind, and fuel cell (FC) systems for on‐grid and off‐grid operations for the Ashrayan‐3 housing project in Bangladesh, with an increased focus on sustainable energy solutions. Motivated by the issue of the delivery of proper and sustainable energy services to remote locations, we conducted an extensive analysis of load demand and found that an average daily demand of 46,176.65 kWh exists, with a peak load of 4852.8 kW. In this research, the HOMER software has been used to make a simulation of five different hybrid system configurations with differing mixes of renewable technologies. From the analyses, the systems based 100% on renewable resources suffer more initial capital costs, with a total net present cost increase of up to 20%, in comparison to conventional systems. On the other hand, the systems give much lower operational costs and cost of energies (COEs) of a minimum of $0.0253/kWh, reported from the on‐grid PV‐based system. On the other hand, the off‐grid PV–FC–wind turbine system showed a COE of $0.286/kWh, along with a decrease in CO2 emissions by about 15,000 kg/year, showing a 30% decrease, compared with on‐grid systems. The results form a basis for the conclusion that such hybrid renewable energy systems are both economically and environmentally feasible. They can reduce COEs by up to 70% in off‐grid systems. This proves that the quality of life and energy security in developing regions will be highly increased, supporting the goals of sustainable development.

A meteorological drought study is performed using monthly time scale data from three separate locations in southern Sindh, Pakistan. Rainfall and temperature have been used to identify the drought. These data were transformed into drought indices known as the standardized precipitation evapotranspiration index (SPEI) and standardized precipitation index (SPI), which were derived using (the Hargreaves equation). In this study, two indices are compared for three separate meteorological stations Chhor, Mithi, and Badin where most socioeconomic livelihoods depend heavily on water. The SPEI is produced through a simple water balance combining precipitation and temperature, in distinction to the SPI, it just considers precipitation. In conclusion, our study showed that both indices were capable of detecting droughts that fluctuated in time across the reference period of 2004–2021. SPI and SPEI's direction of change was similar, however the impact on the drought condition varied. SPEI discovered more droughts with longer durations and greater with 13 moderate droughts at SPEI-3 for Chhor and Badin Station while Mithi indicated 8 moderate droughts during 2004-2021 and SPI-3 indicated 4 moderates for Chhor, Mithi and Badin indicated 6 moderate drought. Conversely, SPEI discovered more moderate-level droughts than SPI, however they were of shorter length and less frequent occurrence than the severe to moderate droughts. The findings imply that drought characteristics are significantly influenced by temperature variability.

Abstract In Pakistan, around 58% of current electricity is generated from fossil fuels and only 2.4% is generated using renewable energy (RE) resources even though country is blessed with enormous RE potential. Among other RE resources, Pakistan's geographical location offers high solar energy potential, which implies that actual potential assessment should be undertaken. This study, as such, undertakes a comprehensive assessment of solar energy potential and prospects of solar photovoltaic (PV) systems for both off‐grid and grid‐connected systems. This study also estimates the future available capacity of rooftop and rural off‐grid solar PV capacity. Three different types of solar PV modules of the same size, that is, thin‐film, premium, and standard were modeled to compare energy outputs. NREL's System Advisor Model (SAM) is used to estimate the geographical and technical potential of solar PV considering updated data and geographical information. SAM results suggest that an average of 4.5 kWh/kWp/day is obtained from an installed capacity of 1 KWp. The logistic modeling equations are further used to forecast the solar PV penetration over a period until 2090. The research investigation concludes that 2.8 × 106 GWh of electricity can be generated annually in Pakistan. The estimated results prove that solar PV has the potential to meet the present as well as future energy needs of Pakistan.

Abstract Pakistan has faced an electricity shortfall for over two decades despite various efforts taken at different levels. Though electricity supply in recent times has crossed the demand, the supply‐side stresses and deciding optimal power generation pathways have always been a challenge for policymakers and researchers. In this study using a LEAP energy model, following the sectoral electricity demand forecast, four supply‐side scenarios have been developed and analyzed for the study period 2017‐2055. In each scenario, referred to as Business as Usual (BAU), Renewable Energy Technologies (RET), Coal Power Penetration (CPP), and High‐Efficiency Low‐Emission (HELE) scenario, electricity generation, installed generation capacity, cost of production, and GHG emissions are estimated and compared for seeking long‐term optimal energy pathways for Pakistan. The study results reveal that for the end year (2055), RET is an environmentally sustainable scenario with an estimated electricity generation of 2421 TWh, which is enough to meet the electricity demand of 2374TWh. The GHG emissions under the RET scenario are estimated to be 857 million metric Tons, which are around 50% less than CPP and 40% less than the BAU scenario. However, the cost of generation is higher than BAU and CPP scenarios. The CPP scenario emerges to be cost‐competitive, however with the highest GHG emissions. This study thus suggests that convergence of RET with the CPP scenario could be an appealing option for Pakistan to meet increasing demand with energy security and environmental sustainability.

The doubly fed induction generator (DFIG)-based wind energy conversion system (WECS) suffers from voltage and frequency fluctuations due to the stochastic nature of wind speed as well as nonlinear loads. Moreover, the high penetration of wind energy into the power grid is a challenge for its smooth operation. Hence, symmetrical faults are most intense, inflicting the stator winding to low voltage, disturbing the low-voltage ride-through (LVRT) functionality of a DFIG. The vector control strategy with proportional–integral (PI) controllers was used to control rotor-side converter (RSC) and grid-side converter (GSC) parameters. During a symmetrical fault, however, a series grid-side converter (SGSC) with a shunt injection transformer on the stator side was used to keep the rotor current at an acceptable level in accordance with grid code requirements (GCRs). For the validation of results, the proposed scheme of PI + SGSC is compared with PI and a combination of PI with Dynamic Impedance Fault Current Limiter (DIFCL). The MATLAB simulation results demonstrate that the proposed scheme provides superior performance by providing 77.6% and 20.61% improved performance in rotor current compared to that of PI and PI + DIFCL control schemes for improving the LVRT performance of DFIG.

Condition monitoring of wind turbines is progressively increasing to maintain the continuity of clean energy supply to power grids. This issue is of great importance since it prevents wind turbines from failing and overheating, as most wind turbines with doubly fed induction generators (DFIG) are overheated due to faults in generator bearings. Bearing fault detection has become a main topic targeting the optimum operation, unscheduled downtime, and maintenance cost of turbine generators. Wind turbines are equipped with condition monitoring devices. However, effective and reliable fault detection still faces significant difficulties. As the majority of health monitoring techniques are primarily focused on a single operating condition, they are unable to effectively determine the health condition of turbines, which results in unwanted downtimes. New and reliable strategies for data analysis were incorporated into this research, given the large amount and variety of data. The development of a new model of the temperature of the DFIG bearing versus wind speed to identify false alarms is the key innovation of this work. This research aims to analyze the parameters for condition monitoring of DFIG bearings using SCADA data for k-means clustering training. The variables of k are obtained by the elbow method that revealed three classes of k (k = 0, 1, and 2). Box plot visualization is used to quantify data points. The average rotation speed and average temperature measurement of the DFIG bearings are found to be primary indicators to characterize normal or irregular operating conditions. In order to evaluate the performance of the clustering model, an analysis of the assessment indices is also executed. The ultimate goal of the study is to be able to use SCADA-recorded data to provide advance warning of failures or performance issues.

The integration of distributed generation (DG) into a power distribution network allows the establishment of a microgrid (MG) system when the main grid experiences a malfunction or is undergoing maintenance. In this case, the power-generating capacity of distributed generators may be less than the load demand. This study presents a strategy for the effective utilization of deployed active and reactive power sources under power mismatch conditions in the islanded distribution networks. Initially, the DGs’ and capacitors’ optimal placement and capacity were identified using the Jaya algorithm (JA) with the aim to reduce power losses in the grid-connected mode. Later, the DG and capacitor combination’s optimal power factor was determined to withstand the islanded distribution network’s highest possible power demand in the event of a power mismatch. To assess the optimal value of the DG–capacitor pair’s operating power factor (pfsource) for the islanded operation, an analytical approach has been proposed that determines the best trade-off between power losses and the under-utilization of accessible generation. The test results on 33-bus and 69-bus IEEE distribution networks demonstrate that holding the islanded network’s load power factor (pfload) equal to pfsource during the power imbalance conditions allows the installed distributed sources to effectively operate at full capacity. As expected, the proposed strategy will assist the utility companies in designing efficient energy management or load shedding schemes to effectively cope with the power mismatch conditions.

Energy storage is becoming a critical issue due to the diminishing availability of fossil fuels and the intermittent nature of current renewable energy sources. As a result, thermal management (TM) and thermal energy systems have gained significant attention due to their crucial roles in various industries. Among the different TM materials, MXenes, a member of the transition metal carbide/nitride family, have emerged as a promising material due to their unique 2D nanostructure, changeable surface chemistry, high electrical/thermal conductivity, light absorptivity, and low infrared emissivity. This review outlines the synthesis methods of MXenes and their various features and applications in thermal management. These 2D materials exhibit outstanding optical and thermal properties, making them suitable for thermal energy generation and storage. The study also covers the potential applications of MXene in the desalination industry, hybrid photovoltaic thermal systems, solar energy storage, electronics, and other thermal management related industries. The findings suggest that MXene-based TM materials have remarkable features that significantly influence thermal energy storage and conversion and present opportunities for further research in efficiently using these materials.

In this study, modeling and thermodynamic analysis of the combined double flash geothermal cycle generation was conducted using zeotropic fluid as the working fluid in the Organic Rankine Cycle (ORC). The analysis was performed based on the first and second laws of thermodynamics. Hexane, cyclohexane, isohexane, R245fa, and R236ea exhibit good performance at higher temperatures. In this study, three fluids—hexane, cyclohexane, and isohexane—were used. First, the model results for the pure fluids were compared with those of previous studies. Then, the important parameters of the cycle, including the efficiency of the first law of thermodynamics, the efficiency of the second law of thermodynamics, net productive power, and the amount of exergy destruction caused by changing the mass fraction of the refrigerant for the zeotropic fluids (investigated for the whole cycle and ORC), were obtained and compared.

Solar photovoltaic (PV) technology has a lower adoption rate than expected because of different weather conditions (sunny, cloudy, windy, rainy, and stormy) and high material manufacturing costs. To overcome the barriers to adoption, many researchers are developing methods to increase its performance. A photovoltaic–thermal absorber hybrid system may shift its performance, but to become more efficient, the technology could improve with some strong thermal absorber materials. A phase change material (PCM) could be a suitable possibility to enhance the (electrical and thermal) PV performance. In this study, a solar PVT hybrid system is developed with a PCM and analyzed for comparative performance based on Malaysian weather conditions. The result shows PV performance (both electrical and thermal) was increased by utilizing PCMs. Electrical and thermal efficiency measurements for different collector configurations are compared, and PV performance and temperature readings are presented and discussed. The maximum electrical and thermal efficiency found for PVT and PVT-PCM are 14.57% and 15.32%, and 75.29% and 86.19%, respectively. However, the present work may provide extensive experimental methods for developing a PVT-PCM hybrid system to enhance electrical and thermal performance and use in different applications.

Despite being a limited and scarce resource, the necessity and exploitation of fossil fuels are unstoppable in serving human demands. In order to supply energy demand without causing environmental damage, it is crucial to utilize a variety of renewable feedstock resources. Biochar, made up mostly of carbon, oxygen, and hydrogen, is the product of the thermochemical processes of pyrolysis, hydrothermal carbonization, torrefaction, and hydrothermal liquefaction. Biochar, once activated, has the potential to act as a catalyst in a variety of energy generation processes, including transesterification and fermentation. Transesterification is the process that is used to produce biodiesel from a variety of oils, both edible and non-edible, as well as animal fats in the presence of either a homogeneous or a heterogeneous catalyst. When selecting a catalyst, the amount of free fatty acid (FFA) content in the oil is considered. Homogeneous catalysts are superior to heterogeneous catalysts because they are unaffected by the concentration of free fatty acids in the oil. Homogeneous catalysts are extremely hazardous, as they are poisonous, combustible, and corrosive. In addition, the production of soaps as a byproduct and a large volume of wastewater from the use of homogeneous catalysts necessitates additional pretreatment procedures and costs for adequate disposal. This article examines the biochar-based fuel-generation catalyst in detail. At first, a wide variety of thermochemical methods were provided for manufacturing biochar and its production. Biochar’s chemical nature was analyzed, and the case for using it as a catalyst in the production of biofuels was also scrutinized. An explanation of how the biochar catalyst can improve fuel synthesis is provided for readers. Biodiesel’s transesterification and esterification processes, biomass hydrolysis, and biohydrogen generation with the help of a biochar catalyst are all reviewed in detail.

Pakistan has been facing energy crises for more than a decade as a result of its reliance on imported fossil fuels, circular debt, political instability, and absurd energy policies. However, the country has abundant renewable energy resources which, if harnessed, may help to effectively cope with ever-increasing energy demand. This review study investigates the country’s economic and energy situations, energy crises, and energy sector performance. A critical analysis of studies conducted on Pakistan’s energy planning since its independence in 1947 is, and policies announced to date are assessed. This review reveals that the economic situation of the country has remained severely stressed, and energy sector performance has been compromised over the years for various underlying reasons. The energy policy narrative in the early decades of the post-independence period focused on water resource management, whereas energy concerns were only realized in the late 1960s as demand grew. The first-ever energy and power planning study in Pakistan was conducted in 1967, and since then, various studies have been conducted to support the medium-term development plans of the government. These planning studies inspired further development, and in 1994, the first-ever electricity-focused power policy was announced by the government in response to industrial growth and subsequent electricity demand. However, this and subsequent policies were fossil-fuel-centric until 2006, when the government announced the first-ever renewable energy policy. This 2006 policy focused on increasing renewable energy penetration in the overall energy mix by setting specific targets. However, these targets have rarely been accomplished as a result of a lack of an effective planning paradigm, as most of studies have been conducted without sound demand forecasting and without considering renewable energy’s potential to meet growing demand. As such, planning efforts based on proven methodologies/modeling tools and the undertaking of demand forecasts and renewable energy assessments are inevitable for countries such as Pakistan. Therefore, we suggest that sectoral energy demand forecasting, estimation of renewable energy potential with end use, and modeling of optimal penetration of renewable energy using energy modeling tools will be helpful to develop sustainable energy policies in Pakistan to eradicate the energy crisis.

This paper reviews the optimization strategies for the optimal simultaneous allocation of distributed generation (DG) and shunts capacitor banks (SCBs) in electrical distribution networks. These optimization strategies aim to determine the optimal size, location, and combination of DGs and SCBs to constitute a techno-economic system while satisfying the constraints and energy demand of the load. The optimization strategies explicitly reviewed include the problem formulations, optimization techniques, restrictions posed for optimization problems, decision variables, and network operating modes typically assumed while allocating the DGs and SCBs. In addition, there is an attempt to highlight the limitations of the existing literature and future research directions. This study undertakes a comprehensive review of the literature that systematically considers the simultaneous application of DGs and SCBs to advance the existing literature, which lacks such a review. Expectedly, this review will serve as a principle platform for researchers intending to explore the subject area for further improvement.

To mitigate the consequences of climate change, there is an increasing need to minimize the usage of fossil fuels, especially in the industrial sector because the majority of the industrial sector primarily rely on fossil fuels to meet their needs for heat energy, and a practical strategy to reduce reliance on fossil fuels is to use energy from the sun. Due to their environmental advantages, energy security, and viability as a potential substitute for fossil fuels, solar thermal collectors are acknowledged as promising technology to harness solar thermal energy fir process heating applications. This review is a thorough compendium and evaluation of contemporary literature on solar thermal collectors and their applications in industry. Apart from applications, this review paper also assesses the challenges and limitations currently hindering the global acceptance of this technology in the industrial sector.

With an expected annual increase of 1.2%, the industrial sector already consumes over 54% of all the energy generated globally. The majority of industrial sectors presently relies on fossil fuels to fulfil their needs for heat energy, but renewable sources, especially solar energy, can be substituted for them. For an underdeveloped country such as Pakistan, its industrial sector is important for the country’s economic development and long-term growth. The use of solar thermal energy potentially offers a significant and cheap alternative to fossil fuels. The current study focuses on a process heating system based on flat-plate solar collectors, developed to provide low to moderate temperature process heat. The innovative model’s thermal efficiency and economic feasibility have undergone a thorough investigation and analysis through TRNSYS simulations. The system portrayed a 79% thermal energy efficiency and 4.31% exergy efficiency during peak hours. The optimized system for three different temperatures of 60 °C, 70 °C, and 80 °C was designed and evaluated. The system presented a total of 82 tons of CO2 prevention annually. The economic analysis consisting of three parameters, NPV, IRR and PBP, also deemed the FPC-based solar thermal system economically profitable.

Geothermal is a renewable energy source, but this is not as often seen as other renewable energy sources, such as solar, wind, hydro, etc. Several applications could be implemented through geothermal energy, and heating & cooling systems are one of them. Because of the limits of technology, it is hard to improve cooling systems as an application. To address long-term sustainable space heating and cooling, it is imperative to develop geothermal technology. It is known as the oldest, most flexible, most adaptable, and most prevalent approach toward using renewable energy. Therefore, this review has reviewed the global development and challenges of geothermal energy for cooling systems. There are large reserves of geothermal energy available around the world, and numerous scholars have emphasized its importance, but due to a lack of knowledge, no operational work has been done in using these systems for cooling up to this point. This review paper examines globally available geothermal energy sources and technologies for environmentally friendly and sustainable cooling supplies. Finally, the benefits and challenges of geothermal systems for cooling are outlined to promote local, regional, and global investment in utilizing these resources for cooling.

Solar light absorber surface is probably one of the most important components in solar still that dictates the distillate yield. In this work, a systematic study is conducted to investigate the effect of particle size and concentration of titanium oxide (TiO2) in black paint in increasing the solar still absorber surface temperature. The various available particle sizes, i.e., 20, 150, and 400 nm, are mixed in black paint with varying concentrations and are applied on the absorber plate. XRD is used for phase identification of as-received powders. UV-Vis spectroscopy is used to examine light absorption properties. Finally, extensive indoor testing (using an improvised solar simulator) and outdoor testing are conducted to optimize the concentration. An increase in surface temperature is observed with the introduction of TiO2 nanoparticles in black paint. Furthermore, the increase in particle size leads to an increase in temperature. The highest surface temperatures of 104.86°C, 105.42°C, and 106.32°C are recorded for specimens with particles sizes 20 nm (at 15 wt% concentration), 150 nm (at 10 wt% concentration), and 400 nm (at 7 wt% concentration), respectively. Furthermore, the highest temperature of 69.69°C is recorded for TiO2-400 nm specimens under outdoor conditions, which is 15.97% higher than that of the bare aluminum plate. The increase in surface temperature may be due to high UV absorption. Moreover, an increase in particle size leads to high light-scattering ability, further improving the light-harvesting ability.

For over a decade, distributed generations (DGs) have sufficiently convinced the researchers that they are the economic and environment-friendly solution that can be integrated with the centralized generations. The optimal planning of distributed generations requires the appropriate location and sizing and their corresponding control with various power network types to obtain the best of the technical, economical, commercial, and regulatory objectives. Most of these objectives are conflicting in nature and require multi-objective solutions. Therefore, this paper brings a comprehensive literature review and a critical analysis of the state of the art of the optimal multi-objective planning of DG installation in the power network with different objective functions and their constraints. The paper considers the adoption of optimization techniques for distributed generation planning in radial distribution systems from different power system performance viewpoints; it considers the use of different DG types, distribution models, DG variables, and mathematical formulations; and it considers the participation of different countries in the stated DG placement and sizing problem. Moreover, the summary of the literature review and critical analysis of this article helps the researchers and engineers to explore the research gap and to find the future recommendations for the robust optimal planning of the DGs working with various objectives and algorithms. The paper considers the adoption of uncertainties on the load and generation side, the introduction of DGs with energy storage backups, and the testing of DG placement and sizing on large and complex distribution networks.

Solid fuel combustion in a chamber does not necessarily occur at a constant rate and may show fluctuations due to variables such as varying burning rates, chamber pressure, and residual combustion. These variables can cause the fuel to burn disproportionately. The acoustic environment of obstacle vortex-driven flow due to transient combustion with pressure oscillations in a solid fuel chamber is numerically investigated in the present study. Solid fuel combustion is considered transient, and flow characteristics of the present problem are governed by large eddies shed from an obstacle. Since unsteady Reynolds-averaged Navier-Stokes (URANS) simulations are not appropriate to compute the present flow phenomenon, therefore, a detached eddy simulation (DES) is performed to precisely predict the flow behavior. Simulation of steady-state combustion is carried out to validate the numerical results with available experimental data from the literature. The simulation of transient combustion shows that if the combustion frequency is close to the chamber’s modal frequency of the chamber, its amplitude increases greatly and creates an acute acoustic environment. This will result in fuel savings. The amplitude of pressure oscillation up to 18% and 5% of mean pressure are evident at the first and second mode of forced oscillation frequencies respectively. Interestingly, it is also found that pressure oscillation always occurs at inlet mass flux disturbance frequency and not between the disturbance and natural frequency of the chamber. As a result, it is evident that the combustion process or chamber configuration could be modified to ensure that both frequencies are far away enough to interact and create both a harsh acoustic environment and sufficient fuel to burn disproportionately.

The availability of fresh drinkable water and water security is becoming a global challenge for sustainable development. In this regard, solar stills, due to their ease in operation, installation, and utilization of direct sunlight (as thermal energy), promise a better and sustainable future technology for water security in urban and remote areas. The major issue is its low distillate productivity, which limits its widespread commercialization. In this study, the effect of silicon (Si) particles is examined to improve the absorber surface temperature of the solar still absorber plate, which is the major component for increased distillate yield. Various weight percentages of Si particles were introduced in paint and coated on the aluminum absorber surface. Extensive indoor (using a self-made halogen light-based solar simulator) and outdoor testing were conducted to optimize the concentration. The coatings with 15 wt % Si in the paint exhibited the highest increase in temperature, namely, 98.5 °C under indoor controlled conditions at 1000 W/m2 irradiation, which is 65.81% higher than a bare aluminum plate and 37.09% higher compared to a black paint-coated aluminum plate. On the other hand, coatings with 10 wt % Si reached up to 73.2 °C under uncontrolled outdoor conditions compared to 68.8 °C for the black paint-coated aluminum plate. A further increase in concentration did not improve the surface temperature, which was due to an excessive increase in thermal conductivity and high convective heat losses.