Predictive Multimodal Deep Learning-Based Sustainable Renewable and Non-Renewable Energy Utilization

The climate crisis has sparked a global shift toward renewable energy sources, increasing the demand for models that provide accurate risk assessment and forecasting to support informed investment decisions. The novelty of this study is to analyze renewable energy investments through three methodological approaches: risk assessment, deep learning-based volatility forecasting, and renewable energy demand forecasting. First, risk profiles of two renewable energy stocks (NextEra Energy and Iberdrola) and two traditional energy stocks (ExxonMobil and Chevron) are evaluated for the time period 2020 to 2024. Second, deep learning (DL) models such as recurrent neural network (RNN), long short-term memory (LSTM), gated recurrent unit (GRU), bidirectional long short-term memory (BiLSTM), bidirectional gated recurrent unit (BiGRU) are employed, and it is shown that renewable energy stocks have more stable performance across all DL models, with BiLSTM revealed as the most robust architecture. Third, UK liquid biofuel consumption trends are analyzed using multiple forecasting methods, including Mean, Naïve, Seasonal Naïve, Drift, and machine learning models. It is shown that the neural network autoregressive (NNAR) model has the highest forecast accuracy, and among the combined forecast models, constrained least squares achieved the highest forecast accuracy. The results indicate that renewable energy produces lower risk exposure and more stable returns, and improves predictability despite short-term volatility.

The transition to a low carbon society is dependent on renewable energy-based electrification. Nevertheless, energy programs have resulted in growing societal polarization in several regions. Therefore, around the globe, government and legislative authorities at the local, regional, national, and international levels are highly concerned about the environmental impacts and risk factors that influence the energy paradigm. Thus, to minimize and/or limit the environmental insecurity issues, the world needs swift and effective actions to secure the climate for a better tomorrow. Moreover, there is a dire need to look for new energy alternatives, along with reducing the complete dependence on petro-based energy sources. Keeping this burning issue in mind, herein, an effort has been made to present the potential of several renewable energy sources, including wind-based renewable energy, solar-based renewable energy, hydro-based renewable energy, and biomass-based renewable energy. Following a brief introduction of energy-related problems and opportunities, a comparative overview is given to renewable vs. non-renewable energy sources. Then, several renewable energy sources, including wind, solar, hydro, and biomass, along with the worldwide energy capacity of each energy source are given with suitable examples and statistics. Finally, risk factors, concluding remarks, and future guidelines are discussed towards the end.

Energy crisis and environmental safety has become a thing of global concern, Nigeria inclusive. This is due to the increasing energy prices and environmental impact. Energy generated from the non-renewable energy sources has been linked up with this energy crisis and non-friendly environment. Research is therefore been geared towards harnessing renewable energy resources as alternative sources of energy generation. Renewable energy sources such as hydropower, wind, geothermal and solar just to mention a few are environmentally friendly. This study therefore aims at exploring renewable energy sources and thus designing a small hydropower plant using Ikere gorge Dam as case study. A survey was conducted through personal interview and probing of previous records of the site. Basic parameters such as flow rate of 31.8 m3/s and a head of 30 m were obtained. These parameters were used together with the standard equations for the design of the small hydropower plant. Costing analysis of the plant was carried out in other to estimate the cost of the plant. The comparative analysis of the renewable and non-renewable energy sources was also carried out. The theoretical power obtained for small hydropower project is 9.36 MW. The initial cost of the project is estimated at N63,343,970 with an estimated annual maintenance cost of N500,000. The annual energy output is 3.6 × 107 kWh and the project has estimated annual revenue of N579,960,000. When compared with other renewable energy sources, the cost of small hydropower plant is low and when compared with dwindling oil prices and environmental effects of non-renewable energy sources, small hydropower stands second to none. The study established that Ikere gorge Dam is a feasible site for a small hydropower plant and a small hydropower plant has also been designed; hence small hydropower plant is therefore recommended.

On a theoretical and practical level, the benefits and environmental impacts resulting from the use of renewable and non-renewable energy sources have been mostly accepted, understood, and calculated. In addition, infrastructure construction studies have been conducted, studied, and implemented for the utilization of most energy sources. The cognitive processes for processing information about processable energy sources are not directly involved with renewable or non-renewable energy sources but refer to each of the energy sources that make them up separately. The aim of the present paper is to carefully select the best or most suitable landscaping design, phytotechnical planning, phytotechnical material, and phytotechnical method for the arrangement of renewable energy sources (RES) environment. The methodology that will be used will be as follows: Collection of findings from data sources and data collection such as literature review. Consideration of alternative solutions for findings. State whether the hypothesis or theory is supported or not supported and/or can answer the research questions. Consideration of the generalizability of the findings. There are specific factors for a phytotechnical method in photovoltaic energy power generating stations that need to be considered and analyzed in the present paper. Such as planting surfaces that are safe for planting, planting species to be used and related to the soil morphology or physiology, plants’ height, preparatory interventions to create suitable conditions at planting sites, and growing methods and maintenance of the planting. These factors are defined according to the classification of photovoltaic station work (A1, A2, B, exempt from environmental licensing). The results include the selection of the necessary plant species according to the principles of phyto-technical arrangement and the necessary specifications.

Urbanisation and industry necessitate a substantial amount of energy, which increases the urgency of this issue. This study used the Ordinary Least Square (OLS) method to analyse the influence of urbanisation and industrialization on energy use in Nigeria from 1981 to 2021. A positive and statistically significant effect of urbanisation on the usage of renewable and nonrenewable energy sources has been observed in empirical studies. It was also discovered that industrialization positively influenced the utilisation of both renewable and nonrenewable energy sources, though the former just marginally so and the latter far more so statistically. Furthermore, trade openness positively impacted non-renewable energy use while having no effect on renewable energy use. The usage of renewable energy increased substantially during periods of economic expansion, while the use of nonrenewable energy decreased significantly over these same periods. Because of the current trend in urbanisation and industry, power generation should be a top concern.

The effectiveness of power plants of various types in Russia (Siberia and the Far East) and neighboring Asian countries (China, Korea, Japan) was evaluated according to the criterion of the cost of generated electricity. Differences in energy development conditions in these countries (technical and economic indicators of power plants etc.), prices of fossil fuels, climatic characteristics) was taken into account. Two options for the use of renewable energy sources (RES) are considered - unfavorable and favorable (basic and ecological). They differ in the values of RES capacity factor due to different climatic conditions, as well as charges for carbon dioxide emissions (carbon tax). It is shown that under conditions that are less favorable for renewable energy sources, fossil fuel power plants or nuclear power plants are the most economical options. The dependences of the electricity cost on the carbon tax under favorable conditions for renewable energy have been obtained. Values of carbon tax, at which renewable energy sources produce cheaper electricity than organic-fueled power plants have been found.

This study aims to determine students' abilities in learning renewable and non-renewable energy sources in science subjects and what are the learning difficulties of students in renewable and non-renewable energy sources in science subjects and the factors that cause students' learning difficulties in renewable and non-renewable energy sources in science subjects class III students. In the research used a qualitative approach with the type of case study research, the techniques used were observation and interviews. In the study, it was obtained the value of students' ability to work on Renewable and Non-Renewable Energy Sources questions. In Class III SD IT Nur Ihsan Medan students with an average score of 63 are included in the high criteria with difficulty working on question number 1 with a difficulty percentage of 64%, working on problem number 2 with a difficulty percentage of 68%, working on problem number 3 with a difficulty percentage of 64%. , working on question number 4 with a difficulty percentage of 60% and working on question number 5 with a difficulty percentage of 64%.

Sentiment Analysis of Self Driving Car Dataset: A comparative study of Deep Learning approaches

Design of pilot-scale delamination plant along with techno-economic and life cycle assessments considering renewable and non-renewable energy sources

Small and Medium-sized Enterprises (SMEs) in Sri Lanka are increasingly turning to social media to gain insights into consumer preferences; however, they frequently lack sophisticated analytical tools to derive actionable insights. This research introduces a hybrid deep learning framework aimed at sentiment and emotion analysis specifically for the Sri Lankan cake sector. Customer reviews and social media comments were gathered and processed through various methods including text cleaning, emoji translation, stopword elimination, tokenization, and sequence padding. Several deep learning models— Convolutional Neural Networks (CNN), Bidirectional Long Short-Term Memory (BiLSTM), and Gated Recurrent Units (GRU) were assessed, along with hybrid models that combined CNN and BiLSTM with GPT-2 embeddings. The CNN+GPT-2 model achieved the highest accuracy in sentiment classification at 96.14%, while BiLSTM performed best in emotion classification with an accuracy of 91.57%. In terms of trend forecasting, Long Short-Term Memory (LSTM) outshone both SARIMA and Prophet, yielding the lowest error metrics and the most reliable sentiment predictions. These results underscore the potential of hybrid deep learning and transformer-based models to effectively capture complex consumer sentiments and provide SMEs with practical, AI-driven insights. This study is among the first to implement such hybrid NLP models within a localized Sri Lankan context, presenting a scalable approach for business intelligence and informed decision-making.

This paper reviews the energy sector in Rwanda with an accent on Renewable Energy. In Rwanda, energy sector plays a vital role in supporting socio-economic evolution and has a close connection to the growth of other economic sectors. The country has both renewable and non-renewable energy sources. Energy policies of the country give special attention to the use of modern, clean and energy efficient technologies. Most of Electricity in Rwanda comes from renewable sources: The total currently installed electricity capacity is 160 MW (March 2015), of which approximately more than 60% comes from hydrological resources along with other indigenous sources and less than 40% comes from diesel-powered generators. The current on-grid access to electricity is estimated at 23% of households and off-grid is 1.5%. Rwanda has envisaged increasing electric power supply by maximizing use of various indigenous energy resources and reach its ambitious target of 563 MW (domestic generation + imports) with electricity access of 70% (on-grid and off-grid) by the end of 2018. However, several challenges laying behind the development in the electric energy sector and utilization of renewable energy resources should be addressed. Challenges to be tackled and measures to be taken to achieve this goal have been presented in this study.

Despite humans' acknowledgement of the main drivers of global warming, greenhouse gas (GHG) emissions are still increasing dramatically worldwide. GHG emissions in the U.S. have increased by 17% during the 1990-2009 period and are expected to increase even more with the economic growth after the current recession. Although current dominant policy for combating global warming relies on substitution of fossil energy sources with the renewable ones, we argue that such a general policy may be inefficient. In fact, such a policy is only a short-fix solution to the problem and may be associated with unintended consequences or secondary effects on other sectors and valuable natural resources. This paper highlights the necessity of multi-criteria decision analysis to select energy sources which are not only efficient in terms of GHG emissions reduction, but also will have minimal adverse effects on other sectors and resources. By simultaneous consideration of performances of energy sources under different sustainability criteria, it is discussed why some renewable energy sources may be even less promising than some nonrenewable energy sources in reducing GHG emissions without affecting other resources and violating the sustainability rationales. The three considered sustainability criteria in this study include carbon footprint, water footprint, and cost, reflecting the environmental efficiency, water use efficiency, and economic efficiency, respectively. The performances of a range of non-renewable and renewable energy sources are considered under the three sustainability criteria to rank the energy sources based on different social choice rules with respect to the uncertainty involved in estimating the performances.

Oil drives the entire world economy, and it is entirely a geostrategy issue. The strong development of the economy over the past few decades has provided a global stage for those countries that have a stable political establishment while managing enormous amounts of oil. Now, year after year, it is becoming increasingly clear that the importance of oil and gas is falling away, and it is those energy sources that bring about a reduction in the half-life that comes into the scene. Oil and gas are non-renewable energy sources and as such are naturally limited, therefore their reserve will become economically unprofitable in the future, and exploitation will reach its natural end. The aim of this research paper is divided into two structures: the first thesis concerns giving a fresh insight into the state of the oil market from the beginning of the pandemic to the present day. The issue of geopolitical relations between Riyadh and Moscow is to be addressed here and how much of a negative consequence the price war has left on their fiscal calculations, although geopolitical friction has deepened the shock further into financial markets. Thus, the fiscal calculation of both countries suffered revenue shocks, but it also prompted an even deeper decline in stock indexes and temporary stagflation of the global economy. The second thesis refers to a brief review of the analysis of the long-term future of non-renewable and renewable energy sources. The future of cleaner forms of energy is imperative, but also a challenging task, as this means shifting the entire structure of national economies to green and renewable. The focus is on giving insight into why this is a necessity, but also why there could be a dangerous precedent and negative cash flows in some structures of the economy. Currently, and any future planning and fulfillment of climate guidelines, must not lead to an increase in energy poverty and consequently a decrease in living standards, because in all geopolitical games the line is always drawn between rich and poor countries, that is, advanced economies and developing economies. Therefore, the long-term and global leaders in green and renewable energy sources will be those countries that successfully implement public interests in these projects, because only in this way can the goal be met – shifting a certain structure of the economy to cleaner sources while satisfying social utility and increasing employment.

Short-term solar radiation forecasting using hybrid deep residual learning and gated LSTM recurrent network with differential covariance matrix adaptation evolution strategy

Short-term forecasting of wind power generation using artificial intelligence