Renewable Energy Production Research Articles

A Discussion of the Properties of Nanoparticles

Nanoparticles (NPs) have begun as versatile building blocks through applications spanning diverse fields. This review provides a general idea of nanoparticle properties, highlighting recent advancements and future prospects. Various techniques, such as sol-gel synthesis, chemical reduction, and green synthesis, offer control over shape, size, and composition, supporting custommade production for precise applications. NPs possess high surface area-to-volume ratios and tunable optical, magnetic, and catalytic properties, alongside biocompatibility and functional ability, making them suitable for various applications. In medicine, NPs facilitate drug delivery, imaging, diagnostics, and therapeutics, ensuring targeted delivery and enhanced efficacy. In electronics, they drive advancements in displays, sensors, photovoltaics, and data storage. Additionally, NPs contribute to energy technologies like fuel cells, batteries, solar cells, and catalysis for renewable energy production. Despite their promise, NPs raise concerns about environmental and health impacts. Efforts are underway to address issues like toxicity, environmental persistence, and regulatory oversight for their safe use. In conclusion, NPs denote a rapidly progressing field with significant potential to address challenges and drive innovation across industries. Continued research and collaboration are crucial to explore their synthesis, properties, applications, and impacts, ensuring sustainable and responsible utilization of nanotechnology.

Fabrication of heterogeneous catalyst for production of biodiesel form municipal sludge

Sewage sludge, a semi-solid byproducts of municipal wastewater treatment processes, offers a sustainable and cost-effective feedstock for biodiesel production through the synthesis of catalytic heterogeneous catalysts. In this study, we developed a novel heterogeneous catalyst by impregnating aluminum nitrate and calcite, obtained from carbon dioxide-sequestering bacteria, onto DigSBiochar (Biochar derived from digested sewage sludge). The produced catalyst was subsequently immobilized with the lipase enzyme isolated from Bacillus sp., creating a bioactive material for the transesterification of lipids in sewage sludge. Comprehensive characterization of the biocatalysts was conducted using Energy Dispersive Spectroscopy (EDS), Fourier Transform Infrared Spectroscopy (FTIR), and Field Emission Scanning Electron Microscopy (FE-SEM). Gas Chromatography-Mass Spectrometry (GC-MS) analysis of the resulting fatty acid methyl esters (FAMEs) demonstrated that the highest yield was achieved with the enzyme immobilized on the activated heterogeneous catalyst using methanol (99 %), followed by the activated heterogeneous catalyst with methanol (96 %), and methanol with Sulfuric acid (82 %). This study underscores the potential of utilizing municipal sewage sludge as a valuable resource for producing efficient heterogeneous catalysts, thereby advancing sustainable waste management practices and promoting renewable energy production.

Production of biogas from various types of spent mushroom substrate under different growth conditions

The mushroom cultivation industry effectively utilizes a diverse range of lignocellulosic waste but generates a significant amount of spent mushroom substrate (SMS) that poses disposal challenges. However, SMS can be used to generate valuable biogas. This study aimed to generate biogas by utilizing different types of spent mushroom substrate (SMS) obtained from three mushroom varieties. These mushroom varieties were cultivated in three types of greenhouses: Photovoltaic Shading greenhouse (PSG), shading greenhouse (SHG), and Control greenhouse (CG). The study found that the total solids (TS) and the amount of SMS used had a significant impact on both the total gas production and the removal of volatile solids (VS). The results demonstrated the feasibility of utilizing SMS as a raw material for biogas production, with variations observed depending on SMS type and greenhouse conditions. It contributes to knowledge in sustainable waste management and renewable energy production from agricultural by-products.

Do various financial resources ensure renewable energy production and environmental protection in OECD countries: modelling for insight.

The recent global energy crisis scenario echoes the past, and the vulnerability of traditional fuels remains the proximate cause of environmental degradation. The fundamental changes in mobilising finance resources are predominant in an energy transition. So, acknowledging finance and energy transition via financial and environmental technology is necessary to meet sustainable development goals. Accordingly, this study employs panel econometric models to investigate how financial resources can ensure the production of renewable energy and environmental protection in 38 OECD member nations over a time period from 2000 to 2021. The empirical finding shows that foreign direct investment and financial technology ameliorate environmental performance by alleviating CO2 emissions. Environmental technologies positively impact environmental protection by eliminating CO2 emissions. The financial resources ensure renewable energy production and environmental protection by reducing the environmental externalities and encouraging renewable energy consumption. Similarly, the consumption of renewable energy catalyses environmental improvement. Economic globalisation spurs environmental externalities. The D-H causality test also shows a reciprocal movement from environmental performance to financial technology, environmental technology and renewable energy consumption. The study's outcomes offer a new model of insight for governments as well as financial and energy policymakers to protect the environment. Enable sustainable development in OECD countries by empowering financial innovation through fintech and incentivising environmental technology to increase renewable energy production.

Green integrative large scale treatment of tannery effluent, CO2 sequestration, and biofuel production using oleaginous green microalga Nannochloropsis oculata TSD05: An ecotechnological approach

In this present investigation, the freshwater microalga Nannochloropsis oculata TSD05 was used to demonstrate multiforius environmental applications viz., bioremediation of tannery effluent, carbon sequestration, and green renewable biodiesel production from treated microalgal biomass. The microalga Nannochloropsis oculata TSD05 was exhibited unique heavy metal reduction capabilities and reduced significant amount of heavy metals viz., 96.62% of copper (Cu2+), 99.9% of chromium (Cr3+), 98.36% of zinc (Zn2+), 98.71% of cadmium (Cd2+), 97.96% of lead (Pb2+), 98.88% of Cobalt (Co2+), and 98.76% of nickel (Ni2+). The biosorption capacity rate (qmax) of heavy metals reduction and highest R2 of 97.84% exhibited at 12 days of effluent treatment by Langmuir and Freundlich isotherm models. The phytotoxicity analysis was tested againt treated tannery effluent using Vigna radiate, Sapindus muukorossi seeds and 98.45%, 99.05% seeds were germinated. The Nannochloropsis oculata TSD05 microalga was utilized 98.45% of CO2 by biofixation kinetics, 372 mg g−1 of lipid, 3.65 mg mL−1 of biomass and 4.64 mLg−1 of biodiesel were produced. The produced biodiesel was confirmed and identification of 18 fatty acid methyl ester (biodiesel) compounds using GCMS. The recognition of 17 functional groups was identified using FTIR analysis and the microalga Nannochloropsis oculata TSD05 potential for sustainable and renewable green energy production. The potential future application of Nannochloropsis oculata TSD05 is to increase lipid production and biodiesel yield. Scaling up the bioremediation process can also validate these microalga's feasibility for use in wastewater treament. Enhancing heavy metal biosorption and carbon sequestration efficiency through genetic engineering could also maximize environmental benefits.

Automated monitoring of natural parameters of renewable energy production systems

The paper discusses the urgent issues of the need to automate the monitoring of natural parameters of renewable energy production systems. Monitoring involves the collec- tion and analysis of various parameters of the natural environment that affect the efficiency and environmental friendliness of systems powered by renewable energy. Based on analytical materials and practical work related to techno-economic and ecological studies concerning the assessment of water reserves in indi- vidual wells, the study focused on the development of technologies and technical means for monitoring. It was found that, in practice, hydrogeological research on groundwaters use outdated methods and technical means for measuring and storing data. A local automated system for monitoring well parameters was developed and constructed. It ensures the operation of the hydrothermal heat pump system at the experimental site of the Institute of Renewable Energy of the National Academy of Sciences of Ukraine. This system was tested in our research. The benefits of this study are revealing the need to create an intelligent monitoring system with the possibility of automated decision-making regarding the management of renewable energy generation systems, depending on changes in the am- bient parameters. A network automated system for monitoring natural parameters was developed, consisting of several wireless sensor subsystems that communicate with each other via wireless connection and transmit information to the gateway. The gateway, in turn, is connected to the computer with a graphical interface for interaction with the system. The results of work indicate that the proposed structures for automated water monitoring are simple and easy to implement. Consequently, the study revealed that one of the prospects is the development of automated monitoring systems with intelligent features, capable of making optimal individual decisions regard- ing the management of renewable energy generation systems under variable environmental parameters. As a result, the data obtained from this study have significant scientific and practical implications for advancing the design methodology of geothermal heat pump wells, focusing on long-term forecasts and assessments of their ecological and economic efficiency.

Smart feasibility optimization of hybrid renewable water supply systems by digital twin technologies: A multicriteria approach applied to isolated cities

This research presents a multicriteria approach for the best hybrid water supply solution of a multipurpose Pumped-Storage Hydropower (PSH) system, using the Generalized Reduced Gradient (GRG) method in Solver, with the optimization process considering key factors, such as Net Present Value (NPV), the number of energy conversion devices, renewable energy production, source availability, reservoir capacities, topographic constraints, and energy tariffs. The methodology combines a literature review, methodological development, and machine learning applications for hybrid water-energy systems. Results indicate that solar-only solutions are insufficient in high hydropower potential scenarios while integrating wind turbines significantly enhances energy production and profitability by generating surplus energy for grid sales. The timing of energy sales and the incorporation of battery storage also impact NPV, which can exceed 180 million euros. Wind energy contributes to continuous profitability and optimized system performance, particularly in isolated regions. The PSH system can manage 130,000 cubic meters of water daily, storing 25 MWh of energy, and reducing CO2 emissions by over 18,000 tonnes per year. These findings highlight the importance of renewables, such as wind energy, and effective operational management. It enhances the economic viability and environmental sustainability of hybrid water-energy systems.

The heterogeneous impacts of climate finance on energy efficiency and renewable energy production in developing countries

Climate finance (CF) is considered to be a key financial innovation to enhance energy efficiency (EE) and facilitate the pathway to energy transition (ET). However, the varied impacts of CF on EE and renewable energy production (REP) have been masked. Thus, this study examines the heterogeneous impacts of CF on EE and REP for 81 developing countries (DCs) for the period 2002–2019. The method of moments quantile regression (MMQR) approach is used to control for distributional and unobserved individual heterogeneity. We calculate EE using parametric stochastic frontier analysis (SFA). Also, the effects of CF on EE and REP are investigated subject to income heterogeneity and based on Copenhagen (COP15) and Paris (COP21) climate accords. The findings revealed that DCs with lower REP benefit the most from increased CF, and the positive effects break down for countries with the largest distributions of REP. Besides, CF positively contributes to EE across all quantiles of DCs. The results further imply that the impacts of CF are income-dependent, with positive effects on the EE and REP of middle-income economies and more pronounced after the COP15 and COP21 climate accords. Several policy implications are forwarded based on the findings.

Advances in Offshore Aquaculture and Renewable Energy Production

Advances in Offshore Aquaculture and Renewable Energy Production

Response of renewable energy minerals to energy policy and technological advancement: An assessment of the Russian energy crisis

The world is turning to renewable energy sources to combat environmental degradation. This is part of Sustainable Development Goal (SDG)-7, which envisions affordable and clean energy. However, achieving the SDG-7 targets and spreading clean energy requires extracting and utilizing various minerals. Russia is one of the leading countries in the world in terms of cobalt, graphite, and rare elements used for renewable energy production. Russia must increase the production of minerals for renewable energy production to achieve SDG-7. In this context, the study aims to investigate the impact of energy policy uncertainty (ENPU), environmental policy stringency (EPS), environmental patents (ETEC), and information and communication technologies (ICT) on renewable energy minerals in Russia. To this end, the study uses novel multivariate quantile-on-quantile regression (M-QQR) and cross-quantilogram (CQ) approaches for the period from 2002m9–2020m12. The M-QQR results show that EPS, ICT, and ETEC increase the extraction of renewable energy minerals, while ENPU inhibits the extraction of cobalt, graphite, and rare elements. The main results indicate that technological progress supports the extraction of renewable energy minerals in Russia and that a strict environmental fiscal policy contributes to the achievement of SDG-7. Based on the findings, Russia needs to support technological progress in the ecological field, implement strict environmental policies, and reduce uncertainties related to energy policies to extract renewable energy minerals and advance the achievement of SDG-7.

Green ammonia imports could supplement long-duration energy storage in the UK

Abstract There is growing recognition of the need for long-duration energy storage to cope with low frequency (i.e. seasonal to multi-annual) variability in renewable energy supplies. Recent analysis for the UK has estimated that 60–100 TWh of hydrogen storage could be required to provide zero-carbon backup for renewable energy supplies in 2050. However, the analysis did not consider the potential role of green energy imports as a supplement to domestic energy storage. Using a global spatially-explicit model of green hydrogen/ammonia production and shipping we estimate the lowest import costs for green ammonia to the UK, and compare them with the levelized costs of energy storage across scenarios of varying domestic renewable energy production. The results indicate that imported green ammonia could offer a cost-comparable alternative to domestic hydrogen production, storage and power generation, whilst increasing energy system resilience through supply diversification, at a similar or cheaper delivered energy cost compared to a hydrogen-only storage system. In countries lacking the geological potential for low-cost hydrogen storage, green ammonia imports could have an even more significant role.

Improving the anaerobic digestion of sewage sludge by adding cobalt nanoparticles

ABSTRACT This work evaluated the effects of cobalt nanoparticles (CoNPs) (0.025–7 mg/gVS) on the intensification of sewage sludge anaerobic digestion (AD) using biochemical methane potential (BMP) tests. This study was motivated by the need to improve the efficiency and stability of anaerobic digestion of sewage sludge, a critical process in waste management and renewable energy production. The effects at doses less than 2 mg/gVS were not substantial, but 3–7 mg/gVS improved the performance. The maximum biogas yield was 232 mL/gVS (at a dose of 7 mg/gVS), whereas it was 132 mL/gVS in the control (zero dose). Similarly, the reductions in the volatile solids and methane contents reached maxima of 16 and 74.3%, respectively. The analyses of volatile fatty acids, redox potential, and electron transfer system activity indicated that the addition of CoNPs stimulated the early stages of AD. Finally, acetate consumption and the increase in CH4 content suggested that CoNPs positively affected system stability and acetoclastic methanogenesis. That is, CoNPs effectively intensified the behaviour and stability of the anaerobic process. The novelty of this research lies in the comprehensive evaluation of the effects of CoNPs across a wide range of doses on sewage sludge AD, providing new insights into the optimisation of this process for increased biogas production and organic matter reduction.

On-Grid Hybrid PV/WT Renewable Energy System for Green Hydrogen Production

The term "Power-to-X" (PtX) refers to a set of techniques for converting electrical energy into another form of energy, primarily focusing on hydrogen production. Produced hydrogen can be stored, distributed, and then used directly (to regenerate electricity, generate heat, or in transportation, steel, and chemical industries) or indirectly to produce ammonia, fertilizers, methane, methanol, e-fuels, and more. Thus, PtX is a mean of storing intermittent energy and a key contributor to the energy transition and decarbonization. In this article, we examine a grid-connected green hydrogen production system. This 1 MW renewable capacity system consists of a 300 kW wind turbine, a 700 kW photovoltaic field, and a 209 kW electrolyzer. In this system, any excess energy is integrated into the grid, enhancing overall energy sustainability. Conversely, when energy output is insufficient for the electrolyzer, the deficit is sourced from the grid, ensuring continuous and reliable operation. This dynamic interaction with the grid optimizes energy usage and reinforces the stability of the system. The results show an annual hydrogen production of about 16 tons, renewable energy production of approximately 1.9 GWh/year, a 20.85% capacity factor, a shortage of about 144.5 MWh, and an energy excess of about 824 MWh.

Quantifying Phospholipids in Organic Samples Using a Hydrophilic Interaction Liquid Chromatography-Inductively Coupled Plasma High-Resolution Mass Spectrometry (HILIC-ICP-HRMS) Method.

In this study, a novel method using hydrophilic interaction liquid chromatography (HILIC) coupled with inductively coupled plasma high-resolution mass spectrometry (ICP-HRMS) was introduced for the quantification of phospholipids in oil samples. The method employed a bridged ethyl hybrid (BEH) stationary phase HILIC column with a tetrahydrofuran (THF)/water mobile phase, enhancing the solubility and detection of phospholipids. During the study, a gradient/matrix effect on ICP-HRMS sensitivity was observed and successfully compensated for experimentally, ensuring reliable quantification results. This approach has proven effective for a wide range of different oil samples including vegetable oils, animal fats, and phospholipid supplements. Notably, this method allowed the direct quantification of phospholipids in oil samples, bypassing the need for prior sample preparation methods, such as solid phase extraction (SPE), thereby streamlining the analytical process. The precision, accuracy, and reduced need for extensive sample preparation offered by this method mark a significant advancement in lipids analysis. Its robustness and broad applicability have substantial implications for industries such as food and renewable energy production, where both efficient and accurate lipid identification and quantification are crucial.

Use of Triboelectric Nanogenerators in Advanced Hybrid Renewable Energy Systems for High Efficiency in Sustainable Energy Production: A Review

Renewable energy is the best choice for clean and sustainable energy development. A single renewable energy system reveals an intermittent disadvantage during the energy production process due to the effects of weather, season, day/night, and working environment. A generally hybrid renewable energy system (HRES) is an energy production scheme that is built based on a combination of two or more single renewable energy sources (such as solar energy, wind power, hydropower, thermal energy, and ocean energy) to produce electrical energy for energy consumption, energy storage, or a power transmission line. HRESs feature the outstanding characteristics of enhancing energy conversion efficiency and reducing fluctuations during the energy production process. Triboelectric nanogenerator (TENG) technology transduces wasted mechanical energies into electrical energy. The TENG can harvest renewable energy sources (such as wind, water flow, and ocean energy) into electricity with a sustainable working ability that can be integrated into an HRES for high power efficiency in sustainable renewable energy production. This article reviews the recent techniques and methods using HRESs and triboelectric nanogenerators (TENGs) in advanced hybrid renewable energy systems for improvements in the efficiency of harvesting energy, sustainable energy production, and practical applications. The paper mentions the benefits, challenges, and specific solutions related to the development and utilization of HRESs. The results show that the TENG is a highly potential power source for harvesting energy, renewable energy integration, application, and sustainable energy development. The results are a useful reference source for developing HRES models for practical applications and robust development in the near future.

Harnessing solar energy for sustainable green hydrogen production in Türkiye: Opportunities, and economic viability

Hydrogen emerges as a promising solution for Türkiye, offering opportunities to enhance renewable energy production and reduce greenhouse gas emissions. Türkiye has significant potential for green hydrogen production, leveraging its abundant renewable energy resources and lower installation costs for renewable energy-based power plants.This study assesses the impact of capital expenditure (CAPEX) on the Levelized Cost of Hydrogen (LCOH) in Türkiye, focusing on both current and projected costs. The LCOH ranges from $3.79/kgH2 to $5.11/kgH2 for low and high CAPEX scenarios, given Türkiye's solar electricity cost of $40.32/MWh in 2024. Looking ahead to 2035, achieving Türkiye's hydrogen cost target of $2.4/kgH2 will require reducing electricity costs to $31/MWh for low CAPEX and $15.3/MWh for high CAPEX. The current electricity cost of $40.3/MWh is significantly above these targets, highlighting the need for substantial technological advancements and cost-reduction strategies to meet future economic objectives for sustainable hydrogen production.

Prioritizing industrial wastes and technologies for bioenergy production: Case study

Energy supply stability in the industrial sector is crucial to maintain operational efficiency and avoiding costly disruptions. In the face of pressing environmental challenges, transitioning to sustainable, efficient, and eco-friendly energy sources is imperative. This study aims to assess the potential of industrial waste for bioenergy production in Khorasan Province, Iran, addressing the research gap of developing a comprehensive framework of criteria that was lacking in previous studies. Employing a combined technology and material assessment methodology, the research began with the collection and analysis of questionnaires to identify and weight critical criteria using Shannon Entropy and expert insights. The Additive Ratio Assessment method was then used to rank various types of industrial waste and technologies according to established value criteria. The Findings reveal that anaerobic digestion of organic waste emerges as the most viable bioenergy solution with an 85 % desirability score, followed by anaerobic digestion of sewage sludge and gasification of plastic waste, scoring 77.31 % and 69.41 %, respectively. The innovative aspect of this study is the development and implementation of five novel evaluation criteria, including process temperature, technology lifetime, production cost, waste collection cost, and waste separation cost, which have not been previously applied to the assessment of industrial waste for renewable energy production, especially in developing countries.

Free carrier generation efficiency in organic photovoltaic films determined using photo-MIS-CELIV

Solution processed organic photovoltaic (OPV) devices are promising for low-embedded energy and large-scale renewable energy production. The efficiency of charge carrier generation is a critical factor influencing the performance of photovoltaic devices. However, quantifying charge carrier generation can be challenging, with the results from experimental methods not always being easily correlated with solar cell performance. In this paper, we describe how photoinduced metal-insulating-semiconductor charge-extraction-by-linearly-increasing-voltage (photo-MIS-CELIV) can be used to determine the free charge carrier generation efficiency (FCGE) in OPV films. One of the benefits of this approach is that the FCGE can be measured alongside the charge mobility to provide a holistic picture of the fate of charges, from generation to extraction. We demonstrate this method through quantifying the FCGE of bulk heterojunctions of PCE10:ITIC-4F, D18:Y6 and PPDT2FBT:PC71BM, obtaining values of 47.4 ± 1.6 %, 75.0 ± 2.5 % and 70.6 ± 4.6 %, respectively. The measured FCGEs for these blends were consistent with the device-based external quantum efficiencies (EQEs) at the excitation wavelength used. The use of photo-MIS-CELIV for quantifying the FCGE increases its utility beyond simple charge mobility measurements and provides an extra method to enable optimisation of OPV device performance.

The Determination of Woody Biomass Resources and Their Energy Potential from Hazelnut Tree Cultivation

The aim of this study was to estimate the shoot weight of four selected hazelnut cultivars and to see if the morphological characteristics of the cultivar and the age of the shoots affect their quality when used as fuel. This study shows that the cultivar ‘Olga’ generated the highest amounts of woody biomass (6507 t·ha−1), while ‘Olbrzymi z Halle’ generated the lowest (3843 t·ha−1). ‘Olbrzymi z Halle’ had the highest calorific values (HHVs) (18.08 MJ·t·ha−1 for annual shoots and 18.03 MJ·kg−1 for perennial shoots) and ‘Olga’ had the lowest calorific values (16.64 MJ·kg−1 for annual shoots and 16.39 MJ·kg−1 for perennial shoots). The age of the shoots had a minimal effect on the chemical and energy parameters. Emissions were the highest for ‘Olbrzymi z Halle’ (CO: 57.74 MJ·kg−1 for perennial shoots, CO2: 1414.05 MJ·kg−1) and lowest for ‘Olga’ (CO: 50.57 MJ·kg−1, CO2: 1238.46 MJ·kg−1). The cultivar ‘Olbrzymi z Halle’, which generated the least amount of biomass compared to the other cultivars, stands out for its high energy value due to its low moisture and ash contents and its high carbon and hydrogen contents, making it attractive for the purposes of biofuel production and supporting sustainable agriculture. The practical implications of the research findings include the selection of suitable varieties for biofuel production, the management of biomass moisture content, and the optimisation of combustion techniques to reduce emissions. The potential for using hazelnut shoots as a biofuel highlights the importance of sustainable agriculture and renewable energy production. The results provide valuable information that can support decisions regarding the cultivation and use of hazelnut shoots for biofuel production while minimising negative environmental impacts.

Estimating the Wind Power by Using K-Nearest Neighbors (KNN) and Python

In recent years the production and distribution of renewable energy has become a popular trend in power generation, and renewable energy sources such as hydro, solar, and wind energy are examples of natural and clean energy sources. Among the renewable energy sources, wind energy source is one of the trending and crucial energy sources that has outstanding electricity power generation. This research investigates an estimation model of wind power to address the real-life issues in renewable energy power generation by estimating an accurate amount of wind power production by applying the machine learning (ML) K-Nearest Neighbors (KNN) technique integrated with Python programming. To achieve the expected outcome for this research, it is expected to collect data from wind energy, wind speed forecasts, and all the relevant information that supports the research in analyzing the technique. There are various meteorological methods to evaluate the performance of wind power generation, but in this research, the methodology is to employ machine learning techniques such as KNN integrated with Python coding to achieve estimated wind energy output. Python is a software program and is diversely used for coding various algorithmic formulas to obtain results. In this research, Python is best suited for investigating the performance of the KNN technique for estimating the most accurate result for wind power generation. Here, the report presents the methods of applying the KNN technique and displaying the outcome on screen by a graph representation. The outcome of the research showed that the KNN is a more reliable technique to make an accurate prediction on wind power generation. A similar approach can be implemented in various renewable energy data to estimate an accurate energy output.