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The instability of the increasingly important photovoltaic (PV) electricity generation in Korea due to a dependence on meteorological conditions is an emerging problem. In this study, we examined the influence of various meteorological conditions on the prediction accuracy of PV generation and module temperature. The predictions were based on weather data acquired from the Korea Meteorological Administration and compared with actual PV generation data from the Dangjin coal yard PV power facility. The results were analyzed on the basis of meteorological conditions, insolation, ambient temperature, and wind velocity. [ABSTRACT FROM AUTHOR]

Solar photovoltaics have emerged as an economic source of renewable electricity generation for regions with high solar irradiation. Still, the installation of utility-scale PV systems is often disrupted due to the unavailability of land. Sparsely populated areas with a hot, dry climate can mitigate the land-energy conflict as they experience higher solar irradiation. In arid areas, the PV systems incur more losses due to dust deposition on PV modules and reduced energy conversion efficiency at higher temperatures. The shortage of water makes the module cleaning procedures cost-prohibitive. Floating Solar photovoltaic (FSPV) systems resolve these problems due to their reduced land footprint, higher efficiency, and reduce evaporative water loss. This study estimates the energy generation of a 4.8 MW FSPV-based microgrid in a hot, semi-arid urban area. By utilizing 5% area of the waterbody, the FSPV system yields 8.876 GWh of electricity annually, to meet 41.7% electricity demand of the study area. The system generates 16.7% more power compared to the land-based PV system. The performance ratio of 82%, and a DC capacity utilization factor of 20.3% is achieved. The system saves 52,810.32 m3 of water per year, compensating for the water requirement of 786.99 m3. for cleaning and dust removal of PV modules. The weekly cleaning procedure limits the soiling loss to 2.79%, compared to 8.47% after a month without cleaning. The FSPV-based microgrid reduces annual CO2 emissions by 2.93 tonnes. This study shall enable engineers, urban planners, and policymakers to develop clean energy-based, sustainable microgrid solutions for urban areas. [ABSTRACT FROM AUTHOR]

This work reports a novel TiO2/g-C3N4 photoanode-based photocatalytic fuel cell (PFC) designed to convert chemical energy from simulated wastewater. The g-C3N4 modified TiO2 nanorod was successfully synthesized by a facile hydrothermal method. The results indicated that the maximum photocurrent density reached 2.44 mA cm-2 at 1.23 V vs. RHE by 1.167 g L-1 g-C3N4 loaded TiO2 composite. On the basis of analysis, the photoelectrochemical mechanism of the composite photoanode was proposed. This mainly demonstrated that the composite photoanode increases the electron donor density and boosts charge separation efficiency. In addition, the power density and hydrogen production of the proposed PFC were enhanced by 5.37 and 1.49 times compared to TiO2 photoanode-based PFC. To find the origins of the excellent performance of PFC, the influence of the organic compounds were investigated. The ESR measurement results indicated that the organic matter was captured by the photoexcited holes directly to facilitate the charge separation. The achieved power density and hydrogen production of 0.14 mW cm-2 and 21.60 μmol h-1 cm-2 were measured using RhB as the model pollutant, which was 2.42 and 1.23 times higher than the experiments with PBS electrolyte. This study proposed a novel PFC system converts the organic pollutant to the hydrogen and the electricity. [ABSTRACT FROM AUTHOR]

The electricity system and the industrial sector interrelate on the path to decarbonization. The study addresses the drivers and environmental pressure within the industrial sector on the National Electricity System (NES). This article aims to characterize the metabolic pattern of the NES and the industrial sector using the Multiscale Integrated Analysis of Social and Ecological Metabolism (MuSIASEM) from a bioeconomic perspective to identify fields of opportunity in the regulatory policy instruments. A set of extensive and intensive variables (2019) on energy, production factors, and emissions was used at different hierarchical levels based on both subsectors. Our results show that the NES used primary energy sources (PES) and secondary energy carriers to fulfill its functions, of which 72% were domestic sources and 28% were imported. México imported 79.5% of the natural gas (NG) for electricity generation. However, there are favorable conditions for renewable PES to increase the installed capacity of solar plants between 3 and 4 orders of magnitude and 2–3 in wind power from the current capacity. NES's energy consumption per hour of human time is 17,388 MJ/h, with 65% being the heat equivalent to a total energy input consumed of 2139 PJ/y. Public plants contributed 43.7% to the generation, and the independent and self-supply producers the rest. End uses needed the supply of 69.3% of electricity from baseload plants. Sixty-three percent of the metabolic pattern of the industrial sector is based on heat and fuel processes, which depend on NG imports. The NES is reorganizing and recovering its energy autonomy. [ABSTRACT FROM AUTHOR]

Electric power generation safety incidents can lead to severe consequences, including casualties and widespread power outages. Previous research has mainly focused on the mechanisms and causal relationships of accidents. However, these incidents result from multiple factors working together, lacking systematic analysis. This study examines 161 electric power generation safety incidents from 2015 to 2022, utilizing Grounded Theory for coding to construct a causal model. The derived model is used as a conditional variable for fuzzy set qualitative comparative analysis (fsQCA), with accident severity as the outcome variable. Forty-five cases are selected for assigning values, and R language and fsQCA software are integrated for univariate necessary condition analysis, followed by configurational analysis. Results show the Grounded Theory-derived causal model includes six factors: human unsafe behavior, equipment factors, enterprise safety management, on-site safety management, safety qualifications of personnel, and environmental factors. Necessary condition analysis indicates incidents result from multiple conditions. Configurational analysis identifies seven paths condensed into three types: management deficiency, low safety qualifications, and unsafe behavior. Recommendations are proposed for each type, discussing intrinsic connections between variables based on conditional variables in configurational paths. The aim is to reduce electric power generation safety incidents, ensure personnel safety, and guarantee continuous electricity supply. [ABSTRACT FROM AUTHOR]

Energy waste from power plants, typically emitted into the atmosphere, contributes to climate change and resource depletion. Integrating heat recovery systems into power plants can improve overall efficiency. This study focused on utilizing waste heat from a 500-MWe coal-based supercritical standalone plant through the organic Rankine cycle. The power plant uses Indian coal as a fuel input, and five distinct working fluids, R245fa, methanol, acetone, ethanol, and benzene, are considered working fluids for the ORC system. Thermodynamic analysis indicates that the standalone plant exhibits energy and exergy efficiencies of 27.33% and 25.01%, respectively. Following the integration of ORC, an overall efficiency improvement is observed. The increment in efficiency is because of the waste heat utilization, where the ORC generates additional electricity generation with outputs of 9.91 MWe for R245fa, 13.71 MWe for methanol, 13.97 MWe for acetone, 14.04 MWe for ethanol, and 14.11 MWe for benzene. Additionally, the study reveals a substantial reduction in CO2 emissions compared to the coal-based power plant with the same production of power, amounting to approximately 216.43 tons for R245fa, 299.43 tons for methanol, 305.10 tons for acetone, 306.63 tons for ethanol, and 308.16 tons for benzene. The thermodynamic investigation identifies the superior performance of the benzene-based ORC among the chosen fluids, and the economic study concludes that the ethanol-based ORC stands out as the most favorable option among the considered alternatives. [ABSTRACT FROM AUTHOR]

Solar thermal energy-based electricity is capital-intensive, and complex while technically evolving to achieve an optimal design. Global commitments and timelines to increase renewable energy share in the grid have promoted technically mature solar photovoltaics and wind. However, the potential of solar thermal energy for industrial applications, cogeneration and polygeneration is on the back foot for lack of policy, complexity, technical readiness level, cost of components and workable business models. Solar collectors that can generate high-quality steam for power generation is complex and costly; while, modified version of linear Fresnel reflector's (LFR) are prospective for various requirements. The current work looks into the possibility of an LFR and heliostat combination to generate steam at 45 bar, 400C temperature to produce electricity. The levelized cost of electricity (LCOE) and levelized cost of water (LCOW) is found to be INR 5.11 kWh−1 and INR 43.03 m−3, in a 70:30 debt–equity scenario. An IRR of 8.55% is achieved with a payback of 12.5 years, with the sale of electricity at INR 10.11 kWh−1 and water at INR 45 m−3. To reduce the LCOE, LCOW and have an attractive IRR, the viability gap funding (VGF) as an option is tried out. The impact of VGF at, 0%, 10%, 20% and 30% on water generation, electricity generation, IRR, NPV and payback are found. It is found that as the VGF increase, there is a better generation cost for electricity and water, with an improved IRR. However, with the VGF trend and corresponding reduction in electricity and water production cost, it will be ideal to have the VGF close to 15% to keep the electricity sale price at approximately INR 8.5 kWh−1 and water pricing at INR 46 m−3. [ABSTRACT FROM AUTHOR]

Solar energy production is an intermittent process that is affected by weather and climate conditions. This can lead to unstable and fluctuating electricity generation, which can cause financial losses and damage to the power grid. To better control power production, it is important to predict solar energy production. Big data and machine learning algorithms have yielded excellent results in this regard. This study compares the performance of two different machine learning approaches to solar energy production prediction: regression and classification. The regression approach predicts the actual power output, while the classification approach predicts whether the power output will be above or below a certain threshold. The study found that the random forest regressor algorithm performed the best in terms of accuracy, with mean absolute errors and root mean square errors of 0.046 and 0.11, respectively. However, it did not predict peak power values effectively, which can lead to higher errors. The long short-term memory algorithm performed better in classifying peak power values. The study concluded that classification models may be better at generalizing than regression models. This proposed approach is valuable for interpreting model performance and improving prediction accuracy. [ABSTRACT FROM AUTHOR]

Today, the silicon photovoltaic cell (SPVC) solar panels are being deployed across the globe by all most all the governments to generate renewable carbon neutral electricity to use in place of the one generated at thermal power plants by burning fossil fuels. These SPVC solar panels generate electricity with less than 20% efficiency, and heat energy with more than 30% efficiency. This 10% excess heat energy released into the atmosphere can cause a very severe damage to the environment and ecology as it is million times higher than the one caused by the equivalent CO2 gas in the atmosphere with a concentration of about 421 ppm. To avoid the harmful and danger effects of heat energy released by these SPVC solar panels into the atmosphere, either they have to be stopped using or the heat generated by them has to be trapped to use for the beneficial purposes of the society or any other alternate safe solar panels have to be developed. In this study, for the first time, the SLAPE (Semiconductor and Liquid Assisted Photothermal Effect) solar panels are introduced to generate electricity from sunlight. In these new solar panels, a semiconducting material along with a stable organic solvent is employed to capture the sunlight reaching the earth surface and to convert it into the heat energy. This in situ generated heat energy is then converted into a rotational mechanical energy with the help of an heat engine, and then into electricity with the help of suitable electric generator. To establish the Proof of Concept (poc), in this study, SPV cells as semiconducting material and γ-butyrolactone were employed to fabricate a one square meter area SLAPE solar panel and generated about 17 V AC electricity with the help of a custom manufactured reciprocally moved steam engine (RMSE) and an electric generator. Thus obtained results are presented and discussed along this article. [ABSTRACT FROM AUTHOR]

When studies investigate the impact of average schooling or learning scores on economic development, they rarely focus on the effect of inequality in learning quality on economic development. Human capital is defined as inclusive sources combining citizens' knowledge and treatment skills. This study uses global learning data to investigate a novel effect of the inequality of reading, math, and science learning scores on economic development and energy selection based on links between and within countries. We found that reducing learning outcome inequality among secondary students is crucial for improving economic development from both short-term and long-term perspectives. Moreover, the positive association between students' learning quality and economic development is confirmed. Compared to the within-country effect, the greater between-country effect of the relationship between learning quality and economic development is confirmed, showing that expectations of the between-country effect might overestimate the favorable effect of education on economic development. On the contrary, the findings show that population learning inequality is less likely to affect national attitudes toward nuclear electricity generation or renewable energy adoption. The insightful policy implications suggest that policy makers should consider reducing learning outcome inequality among students and improving the within-country relationship between education and economic development. [ABSTRACT FROM AUTHOR]

Water evaporation-induced electricity generation is a promising technology for renewable energy harvesting. However, the output power of some reported two-dimensional (2D) nanofluidic films is still restricted by the relatively weak water–solid interactions within the tortuous nanochannels. To further enhance the comprehension and utilization of water–solid interactions, it is of utmost importance to conduct an in-depth investigation and propose a regulatory concept encompassing ion transport. Herein, we propose tortuosity regulation of 2D nanofluidic titanium oxide (Ti0.87O2) films to optimize the ion transport within the interlayer nanochannel for enhanced efficiency in water evaporation-induced electricity generation for the first time. The significance of tortuosity in ion transport is elucidated by designing three 2D nanofluidic films with different tortuosity. Tortuosity analysis and in situ Raman measurement demonstrate that low tortuosity can facilitate the formation of efficient pathways for hydrated proton transport and promote water–solid interactions. Consequently, devices fabricated with the optimized 2D nanofluidic films exhibited a significantly enhanced output power density of approximately 204.01 µW·cm−2, far exceeding those prepared by the high-tortuosity 2D nanofluidic films. This work highlights the significance of the construction of low tortuosity channels for 2D nanofluidic films with excellent performance. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) aquaculture offers a promising solution for sustainable electricity generation for farm and grid utilization (SEG/FGU). This fusion of solar technology and aquaculture methods is crucial for sustainable food production and eco-friendly power and grid integration. However, there is a significant gap in research, with a lack of comprehensive studies that highlight current advancements, publication patterns, research focal points, key contributors, and future avenues for advancing FGU research. A bibliometric analysis of the SEG/FGU research based on Scopus data revealed a steady rise in publications due to environmental issues, research collaborations, and funding availability. China emerged as the top nation with the most articles published (18 articles and 240 citations) on SEG/FGU growth and development, with Alexander Golberg, Tel Aviv University (Israel), and the National Natural Science Foundation of China (NSFC) as prolific authors, institutions, and funders, respectively. China's supremacy has been attributed to the availability of funding from significant programs like NSFC. Three prominent research focal points emerged: the integration of solar energy, agriculture, and desalination; the progression of PV technology within the renewable energy sector; and the intersection of aquaculture and ecological stewardship. The current research focus is on enhancing efficiency, developing effective energy storage solutions, and expanding the scope of applications for agricultural practices. However, significant research voids persist in sustainable aquaculture applications, designing and integrating hybrid PV systems, and achieving scalability in PV technology. [ABSTRACT FROM AUTHOR]

Renewable energy has grown substantially in recent years due to its efficacy in mitigating climate change. The rapid proliferation of solar photovoltaic (PV) systems and subsequent alterations in land use have led to concerns about the impact on local ecosystems. Particularly in Japan, seminatural grasslands, which are valuable habitats, are being developed as solar PVs. Here, we focused on stilt-mounted agrivoltaic systems, capable of both photovoltaic power generation and plant growth beneath solar panels. By repurposing this technology, the coexistence of vegetation and solar PV systems can be possibly ensured. To assess the feasibility of this proposed approach, we initially examined the suitability of installing solar PV in seminatural grasslands. The suitability of seminatural grasslands, solar PVs, and random points for solar PV was evaluated in terms of electricity generation and construction costs. The environmental conditions of seminatural grasslands were found to be advantageous for electricity generation. On the other hand, in terms of construction costs, seminatural grasslands were comparable to randomly selected sites. These findings indicate that the suitability of existing seminatural grasslands for solar PV plant installations is not considerably lower than that of other land types. The idea of reconciling solar power generation with ecosystem conservation holds promise and warrants further investigation toward its realization. [ABSTRACT FROM AUTHOR]

The use of photovoltaic panels for sustainable electricity generation is increasing worldwide. Hence, large solar power plants must be monitored to find defects quickly and easily, avoiding prolonged interruptions in electricity generation. The present study aims to analyse the incorporation of transfer learning in convolutional neural network models to classify defects in visible spectral images of solar panels. Deep learning with convolutional neural networks is known for their precise classification of images, but they need a significant volume of images and training time. Transfer learning is intended to help the training process become faster and more precise. In addition, a publicly available image dataset was constructed using 36,000 images containing three classes of defects and a class without defects to evaluate tested network models. In this study, 17 networks were tested as potential classification models. The best network exhibited an accuracy higher than 99%. This accuracy was obtained with the MobileNetV3 network, which was optimised with Nvidia Tensor RT to run on an edge device with low power consumption and low weight, enabling the real-time classification of the defects presented in this study and allowing the classification of an image in an average of 50 ms. This approach has yet to be explored in the literature, and this paper aims to contribute to this discussion. The presented work has the limitation of not making image segmentation, where the image obtained by the camera is directly classified. From experiments with a large dataset close to an in-field solar plant inspection, trained models successfully classified the defined classes. These findings help solar plant operation and maintenance teams make quick and accurate decisions about scheduled maintenance. [ABSTRACT FROM AUTHOR]

Hydrogen will become a key player in transitioning toward a net-zero energy system. However, a clear pathway toward a unified European hydrogen infrastructure to support the rapid scale-up of hydrogen production is still under discussion. This study explores plausible pathways using a fully sector-coupled energy system model. Here, we assess the emergence of hydrogen infrastructure build-outs connecting neighboring European nations through hydrogen import and domestic production centers with Western and Central European demands via four distinct hydrogen corridors. We identify a potential lock-in effect of blue hydrogen in the medium term, highlighting the risk of long-term dependence on methane. In contrast, we show that a self-sufficient Europe relying on domestic green hydrogen by 2050 would increase yearly expenses by around 3% and require 518 gigawatts of electrolysis capacity. This study emphasizes the importance of rapidly scaling up electrolysis capacity, building hydrogen networks and storage facilities, deploying renewable electricity generation, and ensuring coherent coordination across European nations. A European hydrogen infrastructure supports a rapid scale-up of key production centers at Europe's periphery. However, uncertainties in hydrogen demand, production pathways, and potential imports challenge the network design and storage development. [ABSTRACT FROM AUTHOR]

Landfill leachate, which is a complicated organic sewage water, presents substantial dangers to human health and the environment if not properly handled. Electrochemical technology has arisen as a promising strategy for effectively mitigating contaminants in landfill leachate. In this comprehensive review, we explore various theoretical and practical aspects of methods for treating landfill leachate. This exploration includes examining their performance, mechanisms, applications, associated challenges, existing issues, and potential strategies for enhancement, particularly in terms of cost-effectiveness. In addition, this critique provides a comparative investigation between these treatment approaches and the utilization of diverse kinds of microbial fuel cells (MFCs) in terms of their effectiveness in treating landfill leachate and generating power. The examination of these technologies also extends to their use in diverse global contexts, providing insights into operational parameters and regional variations. This extensive assessment serves the primary goal of assisting researchers in understanding the optimal methods for treating landfill leachate and comparing them to different types of MFCs. It offers a valuable resource for the large-scale design and implementation of processes that ensure both the safe treatment of landfill leachate and the generation of electricity. The review not only provides an overview of the current state of landfill leachate treatment but also identifies key challenges and sets the stage for future research directions, ultimately contributing to more sustainable and effective solutions in the management of this critical environmental issue. [ABSTRACT FROM AUTHOR]

Background: Renewable energies are key to reduce CO2 emissions and other environmental impacts of fossil-fueled electricity generation. However, renewable energy systems can also cause negative environmental effects. In this paper, we analyze the potential environmental trade-offs associated with different spatio-technical (de)centralization options for a renewable electricity system. For this purpose, we first review the potential environmental life cycle impacts of key technologies for renewable electricity systems. Subsequently, we develop a framework identifying which factors determine actual environmental effects of renewable electricity systems. We apply the framework to four basic spatio-technical (de)centralization options for the future Germany electricity system. Results: Our analysis shows that all (de)centralization options are associated with potential environmental trade-offs. We find that the (de)centralization of the system is a relevant factor determining these trade-offs. For instance, the two more centralized options considered have lower environmental impacts related to PV, whereas the two more decentralized options have lower environmental impacts related to grid infrastructure. However, we also find that the trade-offs depend on the specific way (de)centralization is pursued. For instance, only in one of the two considered more decentralized development options, there is a potential environmental trade-off between higher impacts related to battery storage and lower impacts related to offshore wind power. Conclusions: Our analysis reveals that the spatio-technical (de)centralization of a renewable electricity system plays a role for its environmental trade-offs while further factors like the institutional and stakeholder management in place also shape the environmental trade-offs. Policy makers should acknowledge the identified potential environmental trade-offs and their influencing factors when making policies favoring certain spatio-technical (de)centralization options. Highlights: Review of potential environmental impacts of key renewable technologies Framework on determinants of actual environmental effects of electricity systems Review of electricity system (de)centralization scenarios for Germany Application of framework to four spatio-technical (de)centralization options Environmental trade-off analysis for the four (de)centralization options [ABSTRACT FROM AUTHOR]

PV panels are vastly used for sustainable electricity generation, while they can also help the environment by improving buildings' energy consumption. The best placement for PV panels installation in buildings with flat roofs is the roof. When placed on a building's roof, PV panels affect the building's energy loads by shading the roof surface. However, the shading effect of PV panels could be different depending on the roof's thermal properties and surface materials. The combined effect of shading caused by PV panels and cool materials could significantly change the roof surface temperature, and the building energy demand. In light of the lack of studies considering this combined effect, the present study aims to evaluate the energy-saving effects of different roof materials covered with solar PV panels for a typical residential building in four cities with different climate conditions in Iran. Applying a simulation tool, Ladybug Tools have been utilized for determining the building energy loads and PV panels' power generation. The obtained results indicate that PV panels significantly affect the cooling load of the building, especially during peak times. The hottest city, Bandar-Abbas, benefits the most, with a maximum saved energy ratio (SER) of 3.4%, while the coldest city, Ardabil, has the least SER, 0.5%. Additionally, in cold and moderate climates, the highest SER occurs for the lowest R-value and solar absorption roof, while for hot climates, the highest SER occurs for the roofs with the highest R-value and the lowest solar absorption. Overall, the shading effect of PV panels becomes more significant when solar absorption is high, and the roof R-value is low. Despite the decrease in cooling energy load, PV panels might increase the heating load. Depending on the climate, this contradictory effect of the roof's thermal properties and PV panels shading should be considered in the design process of buildings. Highlights: Cities with hot-humid and cold climates have the highest and the lowest SER, respectively. PV shading is more significant on roofs with high solar absorption and low R-value. The effect of PV panels on heating load varies based on climate. [ABSTRACT FROM AUTHOR]

The proposed study analyzes the efficiency of the European energy mix of electricity generation technologies from two perspectives: environmental and economic. The context is that of European energy dependence and a technology mix conditioned by the import of fossil fuels. The impact is centered, among other elements, on the leakage of national income and the emission of polluting gases. The aim is to determine the participation that each type of power plant in each country should present in order to minimize the total environmental impact. In order to solve this problem, a double optimization is proposed through the use of two methodologies: one based on a multi-criteria decision-making method (MCDM) model with which to evaluate the environmental performance of each power plant, and a second optimization based on a quadratic model of portfolios modern portfolio theory (MPT), with which to evaluate the efficiency of the portfolio of technologies from the cost/risk binomial. The results confirm that an environmentally efficient portfolio leads to higher levels of economic risk-taking, with a slight increase in the level of assumed cost. Nevertheless, from the results obtained, it is possible to say that hydro (with a share between 11 and 13%) and wind (37–44% mix participation) technologies resulted to be preferred options both environmentally and in terms of minimum risk efficiency. Nuclear power generation stands out as one of the main baseload technologies with shares between 25 and 35% in environmental and cost/risk efficiency. As main findings, Hydro, supercritical lignite, solar PV and wind are identified as preferential technologies to be present in both minimum risk and minimum cost efficient portfolios. In case European Union pursues for minimizing the cost of electricity production, the shares of supercritical lignite, nuclear, solar PV and wind energy go up to the maximum allowed limits. The novelty lies in the application of both methodologies with which to complement the analysis and design efficient portfolios of energy technologies from environmental and economic points of view. One possible future approach would be to assess (with the MPT model) new environmentally optimal portfolios obtained through the application of other MCDM techniques. [ABSTRACT FROM AUTHOR]

In Africa, mitigating climate change in a context of a growing human population and developing economies requires a bold transition to renewable energy (RE) resources. Declining costs for solar photovoltaics (by 90% between 2009 and 2023) and wind turbines (by 57% between 2010 and 2023) fuelled their construction, and hybrid forms such as floating photovoltaics (FPV) on existing hydropower reservoirs are increasingly being explored. Nevertheless, 65% of the proposed RE capacity in Africa remains hydropower, despite confirmed ecological, socioeconomic, and political ramifications on different spatiotemporal scales. The 673 proposed hydropower plants (HPPs) would increasingly affect river systems and threaten their biodiversity. While there is clear evidence that a transition to RE in Africa is technically feasible, there is a lack of spatially explicit studies on how this transition could be implemented. Hence, the aim of the present study is to explore options for an RE mix that avoids additional hydropower construction and, therefore, further river fragmentation. Attribute data of the open-accessible Renewable Power Plant Database (RePP Africa) were analysed to assess the amount of lost capacity due to operation stops. Geospatial analyses of solar irradiation and existing reservoir data were used to derive the potential for FPV. The degree of possible replacement of future hydropower was assessed under consideration of economically feasible wind and solar photovoltaic (PV) potential. To enhance electricity generation from existing HPPs, efficient and sustainable renewable power plant planning must integrate the risk of failure, as it has diminished the available capacity in the past up to 24%. Our findings further reveal that 25 African countries could replace the proposed hydropower development by FPV covering less than 25% of the surface area of their existing hydropower reservoirs. All 36 African countries could replace proposed hydroelectricity generation by fully exploiting feasible onshore wind and solar PV potential with a mean surplus of 371 TWh per year. In summary, our findings provide scientific evidence to support policy discussions on the potential electricity gains from (1) minimizing plant failure, (2) installing FPV as a co-use option, and (3) exploiting wind and solar resources. This study provides quantitative, data-based, and spatially explicit scenarios on the implementation of an RE mix that could relieve the dam building pressure on African rivers. [ABSTRACT FROM AUTHOR]

Electrogen is a microbial group that plays an important role as anodic biocatalyst of microbial fuel cells (MFCs), one of the most extensively studied microbial-based technologies for bioelectricity generation. The aims of this research were to isolate potential electrogenic bacteria from aquaculture pond sediments and conduct a thorough evaluation on the MFCs' electricity production and efficiency parameters. A total of 18 electrogenic bacteria having various electrochemical abilities was successfully isolated using thioglycollate solid media enriched with Fe3+. Five isolates (namely KCf1, KCf2, KCf4, KCf10, and KCf14) were non-pathogenic electrogens and able to produce relatively stable and high open-circuit voltage values (690–810 mV) on glucose-fed MFCs. Further evaluations on electricity production in close-circuit mode (fixed resistor technique, polarization tests, and analysis of power overshoot phenomenon) and efficiency parameters (Coulombic and energy efficiencies) showed that KCf2, molecular identified as Bacillus altitudinis AC11.2, was the most potential MFC biocatalyst among all isolates. It produced an MPP value of 67.11 mW m−2, current density of 333.03 mA m−2, and Coulombic and energy efficiency of 53.86% and 63.27%, respectively. Efforts to increase the MFC's electrical output have been done by assembling four reactors in series and parallel circuits, obtaining the maximum total voltage of 1.6–2.0 V (for series configuration). This potential output was higher than a portable zinc–carbon battery (1.5 V) and a Ni–Cd battery (1.2 V). However, the voltage reversal suffered in series circuits was another challenge in the development of MFCs for bioelectricity production, since the existence of this phenomenon due to biological factors (microbial metabolism dynamics) are not easy to be controlled. [ABSTRACT FROM AUTHOR]

With the increasing integration of renewable energy sources into distribution and transmission networks, the efficiency of cascade H-bridge multilevel inverters (MLIs) in power control applications has become increasingly significant for sustainable electricity generation. Traditionally, obtaining optimal switching angles of MLIs to minimize total harmonic distortion (THD) requires solving the selective harmonic elimination equations. To this end, this research aims to use two recently developed intelligent optimization algorithms, dandelion optimizer and gold rush optimizer, to solve this problem. To evaluate the effectiveness of the proposed algorithms, an eleven-level cascaded H-bridge MLI (CHB-MLI) was considered in the study. Simulation results for different modulation indices were obtained, and the accuracy and solution quality were compared with genetic algorithm and particle swarm optimization algorithms. MATLAB/Simulink-based models were used to verify numerical computations, ensuring the reliability of the findings. This research contributes to the field by providing insights into obtaining optimal switching angles and minimizing THD in MLIs by applying intelligent optimization algorithms. [ABSTRACT FROM AUTHOR]

Smart Grid (SG) technology utilizes advanced network communication and monitoring technologies to manage and regulate electricity generation and transport. However, this increased reliance on technology and connectivity also introduces new vulnerabilities, making SG communication networks susceptible to large-scale attacks. While previous surveys have mainly provided high-level overviews of SG architecture, our analysis goes further by presenting a comprehensive architectural diagram encompassing key SG components and communication links. This holistic view enhances understanding of potential cyber threats and enables systematic cyber risk assessment for SGs. Additionally, we propose a taxonomy of various cyberattack types based on their targets and methods, offering detailed insights into vulnerabilities. Unlike other reviews focused narrowly on protection and detection, our proposed categorization covers all five functions of the National Institute of Standards and Technology cybersecurity framework. This delivers a broad perspective to help organizations implement balanced and robust security. Consequently, we have identified critical research gaps, especially regarding response and recovery mechanisms. This underscores the need for further investigation to bolster SG cybersecurity. These research needs, among others, are highlighted as open issues in our concluding section. [ABSTRACT FROM AUTHOR]

Manufacturers and electricity companies can play a vital role in sustainable development through eco-innovation implementation and renewable electricity generation. Investigating electricity suppliers' and product manufacturers' decisions is essential to illustrate the evolution of their behavior. This paper establishes a two-population evolutionary game, focusing on the strategies of electricity suppliers and manufacturers. We consider two strategies for the electricity suppliers: (1) renewable electricity generation along with non-renewable electricity and (2) non-renewable electricity generation, and two strategies for manufacturers: (1) eco-innovation implementation and (2) Non-eco-innovation implementation. Also, pricing decisions for products and renewable electricity and determining the level of eco-innovation are investigated in this research. The results demonstrate that suppliers' evolutionary behavior leads to renewable electricity generation, and manufacturers' behavior drives eco-innovation implementation under the government's support. Also, the results indicate that the entire population of electricity suppliers shift toward their sustainable strategy, i.e., renewable electricity generation, in a shorter time than manufacturers. [ABSTRACT FROM AUTHOR]

Purpose: Several studies using life cycle assessment (LCA) have highlighted nuclear electricity's possible role as a low carbon-emitting electricity source. But the variability of results has also been questioned by several published LCA reviews, the latest identified dating back from 2016. This article aims at assessing whether new developments and knowledge confirm this statement. Methods: Meta-analysis is a systematic review approach that allows to assess this variability. It was applied in this study to measure and understand the dynamics behind the greenhouse gases (GHG) emissions of nuclear electricity in a life cycle perspective. From 114 publications identified since 2012, 22 primary studies were selected and analysed to provide a meta-database of 63 estimations of greenhouse gases (GHG) per kWh generated. A descriptive analysis of the meta-database provided a status of the art on the topic in terms of approaches adopted, data sources, etc. Additional data exploitation using boxplot graphs was performed to assess the dispersion and variability of the results around these figures depending on several factors such as extraction mining technique and energy demand, enrichment technology used, reactor's size, and type of LCA practitioners. Results and discussion: The life cycle GHG emissions of nuclear electricity found with the meta-analysis were 3.09 g CO2 eq./kWh (min), 6.36 g CO2 eq./kWh (median), 12.4 g CO2 eq./kWh (average excluding extrema), and 43.2 g CO2 eq./kWh (max), although extremum values were also identified at 53.4, 60.0, and one outlier, based on theoretical scenarios. Using principal component analysis (PCA), the two most influential variables of the environmental performance of nuclear electricity were identified: GHG emissions intensity of the electricity consumed during the enrichment of uranium and energy demand for the extraction of uranium ore. Conclusions: Finally, the contributions of this meta-analysis to current knowledge on the GHG emissions intensity of nuclear electricity generation systems were discussed, including life cycle step breakdown, data gaps, limits, and uncertainties associated to the back end and reactor activities. Among the main areas for improvement for future LCA studies, the study helped identify a need for consolidated industrial data along with harmonised practices regarding system boundary definition. [ABSTRACT FROM AUTHOR]

A circular economy based on symbiotic relationships among sectors, where the waste from one is resource to another, holds promise for cost-effective and sustainable production. This research explores such a model for the agriculture, energy, and construction sectors in California. Here, we develop new an understanding for the synergistic utilization mechanisms for rice hull, a byproduct from rice production, as a feedstock for electricity generation and rice hull ash (RHA) used as a supplementary cementitious material in concrete. A suite of methods including experimental analysis, techno-economic analysis (TEA), and life-cycle assessment (LCA) were applied to estimate the cost and environmental performance of the system. TEA results showed that the electricity price required for break even on expenses without selling RHA is $0.07/kWh, lower than the market price. As such, RHA may be available at little to no cost to concrete producers. Our experimental results showed the viability of RHA to be used as a supplementary cementitious material, meaning it can replace a portion of the cement used in concrete. LCA results showed that replacing 15% of cement with RHA in concrete can reduce carbon dioxide equivalent (CO2e) emissions by 15% while still meeting material performance targets. While the substitution rate of RHA for cement may be modest, RHA generated from California alone could mitigate 0.2% of total CO2e from the entire cement production sector in the United States and 1% in California. [ABSTRACT FROM AUTHOR]

The study presents the economic feasibility assessment of converting the produced biogas from water hyacinth biomass into electricity. Approximately, 0.3793 m3CH4/kgVS was generated from the water hyacinth biomass. The research indicated that the available water hyacinth population on the Lower Volta River in the year 2020 could potentially generate a methane yield of 53.676 × 106m3. The volume of methane gas generated had the potential to produce an annual electricity output of 110.792 × 106 kWh, which could be integrated into the national grid. The economic analysis indicated positive results with an initial total investment cost of $67,273,700. The project showed a positive net present value (NPV) of $8,923,769 and a levelized cost of 0.172 $/kWh. The simple payback and equity payback periods were determined to be 5.5 and 11.3 years, respectively. Furthermore, a sensitivity analysis conducted showed that the project's NPV remained positive when variations in input parameters such as initial cost, operations, and maintenance cost were less than 15% sensitive range. However, a 30% reduction in the feed-in tariff cost resulted in a negative NPV. In conclusion, biogas production from water hyacinth biomass in Ghana can make a significant contribution to the country's energy mix and help alleviate the energy shortfall in rural areas. [ABSTRACT FROM AUTHOR]

Increased global attention is being paid to the food-health-climate trilemma. In this study, we evaluate the climate impacts of Mexico's food consumption patterns by creating a high-resolution (262 sectors) Environmentally Extended Input-Output (EEIO) model called MXEEIO. We focus on the differences between food away from home (FAFH) and food at home (FAH) and compare Mexico's results with those of the USA. The results show that the main components of food spending in Mexico were meat, baked products, and beverages, raising concerns about their potential negative health effects if consumed excessively. Mexico's total greenhouse gas (GHG) emissions from food consumption were estimated at 149 million metric tons (MMT) in 2013, as opposed to 797 MMT for the USA. Meat and dairy products were the main contributors to Mexico's food-related GHG emissions, accounting for 57% of total emissions. Mexico spent a much smaller proportion of food-related income on FAFH than the USA (13% vs. 52%), suggesting great potential for growth as Mexico's per capita GDP continues to rise. Detailed contribution analysis shows that reducing Mexico's food-related GHG emissions would benefit most from a transition to low-carbon cattle farming, but mitigation efforts in other sectors such as crop cultivation and electricity generation are also important. Overall, our study underscores the significance of food-related GHG emissions in Mexico, especially those from meat and dairy products, and the mitigation challenges these sectors face. [ABSTRACT FROM AUTHOR]

Plant microbial fuel cells (PMFC) have attracted great scholarly attention as a renewable energy source. These cells have three main components: anode, cathode chambers, and a proton exchange membrane. In this study, a dual-chamber plant microbial fuel cell system was designed using Cyperus papyrus and Shewanella oneidensis. The effects of various factors, including the size of the electrodes, the distance between the electrodes, and the inoculation volume of Shewanella oneidensis, on the ability of electricity generation, were scrutinized. The results indicated that increasing the size area of the electrodes from 2 × 2 to 4 × 4 and 6 × 6 cm2 caused an increase in the output voltage by 43% and 58%, respectively. The PMFC produced a maximum power of 240 mW, with a Coulombic efficiency ranging from 0.66 to 0.75%. The plant microbial fuel cell designed in this study seemed to have a high potential to remove wastewater contaminants. Based on the results, during five days of setting up the system, COD and BOD decreased by 61.75% and 93.16%, respectively, which shows that in addition to generating power, the designed PMFC had a high potential to remove wastewater contaminants. [ABSTRACT FROM AUTHOR]

The decision-making of generator start-up sequence plays a pivotal role in the power system restoration process following the blackout. In this paper, an optimized deep Q-learning network (DQN) algorithm is proposed to address this challenge. The generator start-up process is modeled as a Markov Decision Process (MDP) based on its characteristics. The DQN is tasked with deciding both the generator start-up sequence and the corresponding restoration path. To address the limitations of DQN, such as low exploration efficiency and slow convergence, the study incorporates the Artificial Potential Field (APF) algorithm to refine the reward function of it. This integration results in the development of the F-DQN (APF-DQN) algorithm, which enhances training efficiency. The effectiveness of this proposed method is demonstrated through the IEEE 39-bus test system. The results reveal that the DQN algorithm is capable of efficiently solving the model of the generator start-up sequence after the blackout. Moreover, the F-DQN algorithm exhibits superior learning efficiency, faster convergence, and higher-quality optimal solutions compared to the DQN. This paper also discusses the applicability of this method under partial blackouts. When compared to other decision-making algorithms, the proposed method offers a restoration scheme that is both time-efficient and results in increased electricity generation. [ABSTRACT FROM AUTHOR]

The present study explores the status of nuclear energy developments for generation of electric power. Notably, India's pivotal role in advancing nuclear technology is highlighted, particularly with the development of a cutting-edge nuclear Fast Breeder Reactor (FBR) technology-based power plant. India has been developing the latest nuclear Fast Breeder Reactor (FBR) technology-based power plant having power generation capacity 10 times higher than the existing nuclear power plants. The review incorporates the most important component of the FBR system i.e. cold trap. Model Sodium Cold Trap (MSCT) is used by India to demonstrate the regeneration of secondary sodium cold trap.The development, advancements and challenges towards the Model Sodium Cold Trap (MSCT) are discussed in detail. It is possible to increase the maximum in-situ regeneration of MSCT up to 82%. This paper also reviews status of energy production using renewable and non-renewable energy sources. Finally, the scope in the advancements of nuclear reactor technology and related future opportunities has also been included. [ABSTRACT FROM AUTHOR]

Landfills are associated with significant environmental problems that pose serious concerns to the environment due to the continuous emission of methane and other greenhouse gases. This study uses the ZODM, FODM, MTM, and six simulations in the LandGEM-V-3.03 model to estimate and predict the methane emissions from the Rajbandh landfill in Khulna city. The predicted average emissions from 2000 to 2036 demonstrate remarkably close emissions (2.14–2.97 Gg/year) from FODM, MTM, and three LandGEM-V-3.03 simulations (site-specific SP, CAAA, and IC). This study compares the output and underlying assumptions of each model and suggests the FODM and LandGEM SP simulations can be suitable for estimating methane emissions in the conditions of Khulna. In addition, this study also investigated the feasibility of electricity generation using emitted methane at the landfill site. It reveals that the Rajbandh landfill holds the economically viable potential to establish a 1 MW power plant without subsidy. The total environmental lifetime benefits from this electricity generation project are estimated to reduce 0.563 MMTCO2-eq emissions. The outcome of this study may apply to other Bangladeshi landfills and improve waste management planning and energy security. [ABSTRACT FROM AUTHOR]

Selective ion transport underpins fundamental biological processes for efficient energy conversion and signal propagation. Mimicking these 'ionics' in synthetic nanofluidic channels has been increasingly promising for realizing self-sustained systems by harvesting clean energy from diverse environments, such as light, moisture, salinity gradient, etc. Here, we report a spatially nanoconfined ion separation strategy that enables harvesting electricity from CO2 adsorption. This breakthrough relies on the development of Nanosheet-Agarose Hydrogel (NAH) composite-based generators, wherein the oppositely charged ions are released in water-filled hydrogel channels upon adsorbing CO2. By tuning the ion size and ion-channel interactions, the released cations at the hundred-nanometer scale are spatially confined within the hydrogel network, while ångström-scale anions pass through unhindered. This leads to near-perfect anion/cation separation across the generator with a selectivity (D-/D+) of up to 1.8 × 106, allowing conversion into external electricity. With amplification by connecting multiple as-designed generators, the ion separation-induced electricity reaching 5 V is used to power electronic devices. This study introduces an effective spatial nanoconfinement strategy for widely demanded high-precision ion separation, encouraging a carbon-negative technique with simultaneous CO2 adsorption and energy generation. Nanogenerators have promising applications in energy and environment-related fields. Here, the authors developed Nanosheet-Agarose Hydrogel generators to enable near-perfect anion/cation separation, leading to simultaneously CO2 adsorption and energy generation. [ABSTRACT FROM AUTHOR]

Research-based education is a long-standing tradition at the University of Tartu (UT). Basic knowledge of electrochemistry and the principles of developing electrochemical devices have been taught and implemented at UT since 1960. For instance, during then, self-made alkaline electrolysers were used to generate hydrogen. The hydrogen was further purified and used to saturate aqueous and non-aqueous electrolytes. The fundamental electrochemical research has formed a solid background on which the development of supercapacitors and Na+-ion or Li+-ion batteries is based today. Since 1991, the Ph.D., MSc and undergraduate students have investigated the properties of high surface–area carbon materials in non-aqueous electrolytes to develop energy conversion and storage devices with high energy and power density. Moreover, porous thin-film complex metal hydride–based hydrogen storage devices are also under study. The research of solid oxide fuel cells (SOFC) and polymer electrolyte membrane fuel cells (PEMFC) began at the UT in 2001 and 2010, respectively. Based on the collected knowledge, a sustainable green electricity and hydrogen generation-storage complex (GEHGSC) was constructed, consisting of solar cells and fuel cells for electricity generation, batteries for storage and electrolysers for hydrogen generation. The main aim of GEHGSC is to educate students, young scientists and local authorities specialized in sustainable energy technologies and applied electrochemistry. Electrolyzed hydrogen has been used for experimental testing of SOFC and PEMFC, produced at the Institute of Chemistry. The 300 bar hydrogen compressor has been installed, and thereafter, the PEMFC-powered self-driving car Iseauto, completed by contract for Auve Tech OÜ, has been fuelled with hydrogen produced by GEHGSC. [ABSTRACT FROM AUTHOR]

Microbial fuel cell (MFC), a bio-electrochemical device that exploits electroactive microbes, has gained more attention in developing countries, such as Indonesia. Unfortunately, studies related to bio-electrochemistry are often constrained due to the need for precise and high-cost instrumentation, such as data logger/acquisition or data logging-multimeter for continuously monitoring electricity generation of MFCs in the rigid time interval. This present work aimed at two issues: (1) to evaluate the use of a low-cost microcontroller-based data logger, the developed multi-channels Arduino UNO-based data logging system, for monitoring the electricity generation of ten MFC bioreactors simultaneously, and (2) to evaluate the electrochemical performance of MFCs biocatalysts by ten electroactive microbes isolated from aquaculture pond sediment in Indonesia. The monitoring system worked with a multi-channels Arduino UNO, a multiplexer, an external 16-bit ADC (analogue to digital converter) ADS1115, and a RTC (real time clock) module. The MFC performance was evaluated in the terms of open circuit voltage and close circuit voltage (polarization curve, power density, and losses). Statistical analysis confirmed the high accuracy of the developed system with the average of absolute and relative error values of 1.21 mV and 1.26%, respectively, comparable to traditional multimeter utilized for MFC electricity measurement. These results suggested that the developed data logging system could be a considerable option as a low-cost monitoring device for electrochemical studies of MFCs. Electrochemical performances of ten anodic biocatalysts were also evaluated, suggesting that there were three effective bacteria (isolate KCf2, KCf4, and KCf10) for producing relatively stable bioelectricity in the reactor of MFCs. These three electroactive microbes can produce power density of 0.069 W m−2, 0.021 W m−2, and 0.010 W m−2, respectively. [ABSTRACT FROM AUTHOR]

Climate change mitigation generally require rapid decarbonization in the power sector, including phase-out of fossil fuel-fired generators. Given recent technological developments, co-firing of hydrogen or ammonia, could help decarbonize fossil-based generators, but little is known about how its effects would play out globally. Here, we explore this topic using an energy system model. The results indicate that hydrogen co-firing occurs solely in stringent mitigation like 1.5 °C scenarios, where around half of existing coal and gas power capacity can be retrofitted for hydrogen co-firing, reducing stranded capacity, mainly in the Organization for Economic Co-operation and Development (OECD) countries and Asia. However, electricity supply from co-firing generators is limited to about 1% of total electricity generation, because hydrogen co-firing is mainly used as a backup option to balance the variable renewable energies. The incremental fuel cost of hydrogen results in lower capacity factor of hydrogen co-fired generators, whereas low-carbon hydrogen contributes to reducing emission cost associated with carbon pricing. While hydrogen co-firing may play a role in balancing intermittency of variable renewable energies, it will not seriously delay the phase-out of fossil-based generators. Effects of hydrogen and ammonia co-firing with fossil power generation on decarbonization scenario are assessed. Co-fired generation is limited to <1% because of higher cost of hydrogen. It will not delay the phase-out of fossil-based generators. [ABSTRACT FROM AUTHOR]

With the increasing scarcity of global energy, the rapid development of science and technology, and the growing demand for environmental protection, wind energy is receiving increasing attention as the cleanest source of energy. Due to its pollution-free nature and widespread availability, it has become a preferred source of electricity generation in many countries. However, wind speed prediction plays a vital role in wind power generation. Traditional prediction models, due to randomness and uncertainty, often produce unstable and inaccurate results, leading to power and economic losses. Therefore, this study proposes a hybrid prediction system based on an information processing strategy and a multi-objective optimization algorithm. By preprocessing the data and optimizing the combination of five individual models, the singularity of a single model is overcome, a Pareto-optimal solution is obtained, and accurate and stable prediction results are provided. To verify the effectiveness of the proposed combined model in predicting wind speed, various experiments on a wind speed series were conducted based on a wind power station located in Penglai, China. The results show that the combined model proposed in this study has better prediction performance than conventional models. [ABSTRACT FROM AUTHOR]

A sustainable, affordable, and eco-friendly solution has been proposed to address water heating, electricity generation, space cooling, and photovoltaic (PV) cooling requirements in scorching climates. The photovoltaic thermal system (PV/T) and the direct expansion PV/T heat pump (PV/T DXHP) were numerically studied using MATLAB. A butterfly serpentine flow collector (BSFC) and phase change material (PCM) were assimilated in the PV system and MATLAB model was developed to evaluate the economic and enviroeconomic performance of the PV/T water system (PV/T-W), PV/T PCM water system (PV/T PCM-W), the PV/T DXHP system, and the PV/T PCM heat pump system (PV/T-PCM-DXHP). In this study, annual energy production, socioeconomic factors, enviro-economic indicators, and environmental characteristics are assessed and compared. Also, an economic, environmental, and enviro-economic analysis was conducted to assess the commercial viability of the suggested system. The PV/T PCM-DXHP demonstrated the highest electrical performance of 53.69%, which is comparatively higher than the other three configurations. The discounted levelized cost of energy (DLCOE) and payback period (DPP) of the PV/T PCM-DXHP were ₹2.87 per kW-h and 3–4 years, respectively, resulting in a total savings of ₹67,7403 over its lifetime. Furthermore, installing this system mitigated 280.72 tonnes of CO2 emissions and saved the mitigation cost by ₹329,700 throughout its operational lifecycle. [ABSTRACT FROM AUTHOR]

The studies have focused on changes in CO2 emissions over different periods, including the COVID-19 pandemic. Even if CO2 emissions are temporarily reduced during the pandemic according to annual figures, this may be misleading. Considering annual figures is important to understand the overall trend, but using data with much higher frequency (e.g., daily) is much better suited to investigate dynamic relationships and external effects. Therefore, this study comprehensively analyzes the association between CO2 emissions and disaggregated electricity generation (EG) sources across the globe by employing the novel wavelet local multiple correlation (WLMC) approach on daily data from 1st January 2020 to 31st March 2023. The results demonstrate that (1) based on the main statistics, daily CO2 emissions range between 69 MtCO2 and 116 MtCO2, indicating that there is an oscillation, but no sharp changes over the analyzed period. (2) based on the baseline regression using the dynamic ordinary least squares (DOLS) approach, the constructed estimation models have a high predictive ability of CO2 emissions, reaching ~ 94%; (3) in the further analysis employing the WLMC approach, there are significant externalities between EG resources, which affect CO2 emissions. The results present novel insights about time- and frequency-varying effects as well as a disaggregated analysis of the effect of EG on CO2 emissions, demonstrating the significance of the energy transition towards clean sources around the world. [ABSTRACT FROM AUTHOR]

To achieve the Sustainable Development Goals by 2030, low-income sub-Saharan African countries urgently need to electrify. Biogas production from anaerobic digestion could make a contribution to a solution to improved electricity generation and access in these regions. This study evaluates its feasibility using Malawi as a case study. The aim is to provide households with a continuous supply of gas for cooking and electricity. The study examines different sizes of fixed dome reactors (3, 6, 12 m3) and assumes individual household ownership of 2, 4, and 6 cows. Several feedstocks and conditions are considered, such as cow dung alone, co-generation of cow dung with human faeces, cow dung with grass, and cow dung with maize residue. The economic benefits of selling biogas and fertilisers are calculated, and the cost of construction for different sizes of reactors is determined. Results show that co-generation of cow dung and grass silage in the reactor of 12 m3 with six cows has a positive net present value (NPV) of $8962, while for a small farm with a 6 m3 reactor capacity, co-digestion of cow dung with maize residue is preferable. The feasibility of the technology depends heavily on current national economic conditions, such as inflation, electricity prices, and construction material costs. A sensitivity analysis estimated that a 25% increase in the cost of electricity could increase the net present value (NPV) from − $3345 to $1526 for the generation of biogas from cow dung alone. Overall, this technology could have a significant impact on the lives of low-income households in sub-Saharan Africa by improving their access to electricity and providing a source of income through the sale of biogas and digestate. [ABSTRACT FROM AUTHOR]

The research on constructed wetland (CW) and microbial fuel cell (MFC) has been separate studies worldwide with crucial achievements being made in both fields. Due to environmentally friendly feature (of CW) and rich microbial population and excellent electrode catalytic activity (of MFC), CW and MFC have their own anticipated application prospect in wastewater purification and biological electricity generation. More significantly, the idea of embedding MFC into CW to form CW-MFC expands the scope for both of them and this has received much interest in recent years due to its striking features of sewage treatment efficiency, electricity generation, sustainability, and environmental friendliness. The increasing interest and the lack of soul of CW-MFC emerging to the new researchers reflect the need to recall the idea and summarize its development with regard to achieving its reality via some key issues This forms the basis of the paper. The paper also includes how to enhance the efficiency of electricity generation and supplement energy consumption, the degradation of emerging pollutants, and the degradation mechanism as well as the potential joint application of CW-MFC with other treatment technique. A mass of CW-MFC design parameters has been synthesized from the literature. Challenges and potential directions of CW-MFC in the future are prospected. It is expected that the paper can serve as a linkage for bridging knowledge gaps for further studies of CW-MFC. [ABSTRACT FROM AUTHOR]

This paper presents a numerical algorithm for environmental/economic load dispatch (EELD) with emissions constraints, which takes into account the emissions trading system's effect on electricity generation cost and is implemented using a Python computer program. The developed program is applied to a power system of six (6) fossil-fueled electricity generating units with NOx, SO2 and CO2 constraints and proved to be significantly beneficial not only for the environment but also for the power company and the consumers. The proposed algorithm uses multi-objective optimization and incorporates both fuel and emissions allowances costs. The schedule of generating units is calculated and the testing of all possible weighting factor combinations with resolution of 0.01 is carried out showing that the proposed algorithm is fast, cost effective and environmentally friendly. [ABSTRACT FROM AUTHOR]

The electrode played an essential role in the operation of CW-MFC system due to its synergistic effect, and the development of electrode strategy has promoted the application of CW-MFC since 2012. In this paper, according to the material and the quantity, the electrode types in CW-MFC were distinctly divided into unified model, composited model, modified model, and multi-electrodes model combined with non-conductive or conductive particle. Different electrode strategies were provided to improve the performance of CW-MFC towards electricity generation, removal of pollutants, and control of greenhouse gas emission, and the coordination mechanism was further reviewed. Furthermore, the development process of the electrode strategy was summarized, and the low-cost, sustainable, and innovated electrode materials were emphatically recommended. For the scale-up application, multi-electrode model was systematically reviewed based on the optimizing of the material, shape, spacing distance, and connection type of electrode. This review may provide guidance to maximize the advantages of CW-MFC applications. Highlights: • Electronic receiver and non-conductive or conductive particle was firstly classified. • The electrode application on electricity generation and pollutant removal was reviewed. • The application of emerging electrode materials in CW-MFC was summarized. • The multi-anode and multi-cathode strategy may facilitate the scaling-up of CW-MFC. • The development of electrode material was prospected to extend the function of CW-MFC. [ABSTRACT FROM AUTHOR]

The generation of electricity from renewable sources has made considerable strides in today's industrialized nations. The primary objective of this research is to examine the grid integration of solar systems within permissible total harmonic distortion (THD) limits, with the help of a proposed cascaded feedforward neural network (CFNN) controller fed advanced power conversion devices such as symmetrical hybrid (SH), switched inductor (SL), and switched capacitor (SC) based boost converter and reduced switch cascade multilevel inverter (CMLI). The SH–SL–SC converter for power conversion features a high voltage gain and reduced switch CMLI features minimum number of power electronic switches and low harmonic content in both the voltage and current profiles. When producing a control signal for the recommended SH–SL–SC boost converter, the proposed CFNN-MPPT controller performs better under different weather scenarios where it needs significant data to operate effectively. Consequently, the CFNN-MPPT controller fed SH–SC–SC boost converter-based PV system is integrated into the grid through reduced switch CMLI where it is controlled by proposed CFNN controller. The CMLI can be operated on asynchronous input voltage sources and making it ideal for PV systems when integrated to the grid with improved power quality by reducing total harmonic distortion (THD) to less than 5% at point of common coupling. With reference to the standards outlined in IEEE 1547 and 519, the simulation's outcomes were reviewed. Finally, a symmetric hybrid SL–SC boost converter and modified cascaded nine level inverter have been conceived and produced as a laboratory prototype model and its output waveforms are presented in this article. The proposed intelligent controller fed converter exhibits enhancements in the converter voltage gain and power quality by lowering the THD level at PCC in the grid integration with the PV power systems. [ABSTRACT FROM AUTHOR]

The use of microturbines in irrigation applications represents a great opportunity for increasing sustainable energy generation. Irrigation systems have water flow that can be used to generate electricity based on microturbines that are acceptably configure such, that efficiency in crop irrigation is not affected. This research validates this use of microturbines through a system designed specifically for the characterization of microturbine generation technology. This system includes a closed water pumping circuit capable of working under, different water flow settings, as well as flow, pressure, and electricity generation sensors. For this system, the production range of the microturbines and the pressure loss associated with the various proposed configurations are characterized and specifically quantified for the best performance. After design and characterization of a scalable microturbine system, the feasibility and benefits of this application to supporting most relevant crops supplied by localized irrigation are analysed. The experiments demonstrate the greatest benefit with the implementation of 15 series microturbines each at 80 V, alongside non-Citrus fruit, where a favourable balance is achieved for the amortization period in vineyards and citrus fruit. The results validate a profitable and sustainable design for electricity generation, with return on investment rates of up to 53%. Therefore, this research offers real and extensive applications, while being scalable to rural, residential, urban and industrial settings. Key Points: • Development of an experimental system for the characterization of water microturbines and validation in irrigation systems. • Design of a system to obtain clean energy from the pressure head excess of irrigation systems based on experimental characterization. • Analysis of the feasibility and investment of the application of the sustainable energy generation system to different crops. [ABSTRACT FROM AUTHOR]

The recovery of spent lithium-ion batteries (LiBs) has critical resource and environmental benefits for the promotion of electric vehicles under carbon neutrality. However, different recovery processes will cause uncertain impacts especially when net-zero-carbon-emissions technologies are included. This paper investigates the pyrometallurgical and hydrometallurgical recovery processes for spent ternary LiBs in China based on life cycle assessment framework, then simulates the environmental impacts under different carbon neutrality scenarios, in which the decarbonization of electricity generation, the reconstruction of industrial processes, and the promotion of hydrogen are considered. Results suggest that the current environmental impacts of pyrometallurgical recovery process is greater than that of hydrometallurgical recovery process. Abiotic Depletion Potentials of resources and fossil fuels (ADP element, ADP fossil) and Human Toxicity Potentials are the main indicators that cause these differences. Besides, a multi-scenarios simulation is conducted considering the innovation of carbon neutral technology and expansion of EVs market. It is found that the improvement in energy structure and industrial processes will significantly affect the environmental performance of each recovery process. The pyrometallurgical recovery process has great potentials to improve environmental benefits with net-zero transition of energy system. [ABSTRACT FROM AUTHOR]

Amid China's rapid economic expansion, the country's industrial solid waste (ISW) problem is escalating. As each sector generates distinct types of ISW, a multi-indicator assessment of each sector is essential to address China's New Solid Waste Policy. To investigate the ISW situation of each sector and perform a comprehensive assessment, we formulate an industrial solid waste ecological analysis framework based on ISW generation and ISW flow in the sector. Various indicators (i.e., solid waste utilization coefficient, solid waste threat coefficient, and solid waste threat intensity) are employed to assess the utilization of solid waste generated for each sector, as well as the threat of solid waste originating in each sector to society. Ecological network analysis probes the interrelationships between diverse sectors. Taking Shanghai in 2017 as an example, the study indicates that some sectors (e.g., production and supply of electric power and heat power (EH) and metal smelting and rolling processing sector (MS)) exhibit higher direct ISW generation and the direct industrial solid waste value-added coefficient (SVAC) for common industrial solid waste (CISW). Specifically, the direct CISW generation of EH and MS is 539.21Mt and 277.00Mt respectively. The direct SVAC of EH and MS is 157.06kg/103RMB and 126.27kg/103RMB respectively. These sectors should prioritize reducing emissions at the source. Additionally, the threats to society from various sectors are relatively insignificant for the CISW, while for the hazardous waste (HW), all sectors pose a considerable threat to Shanghai's society. Moreover, some sectors (e.g., mining industry) exhibit the highest mutualism relationships in the CISW and the HW. Enhancing mining sector technologies is a vital strategy for mitigating ISW sources. Specifically, MI has 9 pairs of mutualism relationships in the CISW and 8 pairs in the HW. These insights will provide empirical evidence for tackling the ISW problem in Shanghai. [ABSTRACT FROM AUTHOR]

Solar photovoltaic (PV) farming is increasingly being used to power electric vehicles (EVs). Although many studies have developed dynamic EV charging prediction and scheduling models, few of them have coupled rooftop PV electricity generation with the spatiotemporal EV charging demands at an urban scale. Thus, this study develops a research framework containing three interconnected modules to investigate the feasibility of EV charging powered by rooftop PVs. The framework is constructed by the statistics of time serial EV charging demands at each station, the planning of rooftop PV installations associated with all charging stations, and the development of a dynamic dispatching algorithm to transmit surplus electricity from one station to another. The algorithm can maximize the overall balance between supply and demand, maximize the total PV electricity generation while minimising the total PV area, minimize the number of PV charging stations used as the suppliers for dynamic dispatch, and minimize the total electricity transmission distance between stations given the same power supply. The experiment utilizes a complete EV charging dataset containing 5574 charging piles with more than 9.7 million records in June and July in Guangzhou, China. The results show that rooftop PVs can supply more than 90% of the charging demand. The results encourage and inspire us to generalize and promote such a solution in other cities. Future work can refine the algorithm by adapting different PV sizes into various charging stations to further improve the electricity generation capability and the dynamic dispatching efficiency. [ABSTRACT FROM AUTHOR]

Livestock farming has exerted intense environmental pressure on our planet. The high emissions to the environment and the high demands of resources for the production process have encouraged the search for decarbonization and circularity in the livestock sector. In this context, the objective of this study was to evaluate and compare the environmental performance of two different uses for biogas generated in the anaerobic digestion of animal waste, either for electricity generation or biomethane. For this purpose, a life cycle assessment approach was applied to evaluate the potential of anaerobic digestion as a management technology for three different livestock wastes, related to beef cattle, dairy, and sheep in the Brazilian animal production context. The results suggest that the treatment scenarios focusing on biomethane generation were able to mitigate the highest percentage of damages (77 to 108%) in the global warming category when compared to the scenarios without the use of anaerobic digestion (3.00·102 to 3.71·103 kgCO2 eq) or in the perspective of electricity generation (mitigation of 74 to 96%). In terms of freshwater eutrophication, the generation of electricity (− 2.17·10−2 to 2.31·10−3 kg P eq) is more favorable than the purification of biogas to biomethane (− 1.73·10−2 to 2.44·10−3 kg P eq), due to the loss of methane in the upgrading process. In terms of terrestrial ecotoxicity, all scenarios are very similar, with negative values (− 1.19·101 to − 7.17·102 kg 1,4-DCB) due to the benefit of nutrient recovery, especially nitrogen, associated with the use of digestate as fertilizer, which was one of the critical points in all scenarios. Based on these results, it is evident that proper management of all stages of the treatment life cycle is the key to decarbonization and circularity in livestock waste management. The biogas use does not present different effects on the environmental performance of the scenarios studied, demonstrating that the purpose should be chosen according to the needs of each plant or management system. [ABSTRACT FROM AUTHOR]

It is noted that the traditional direct filed-oriented control (DFOC) is widely used in the field of electric power generation from wind due to its fast response dynamic, ease of implementation and simplicity, but this strategy is characterized by the presence of large ripples at the level of both active and reactive powers. This work presents a new algorithm for DFOC strategy of an asynchronous generator (AG) in a wind power (WP) system, which is based on the use of a new nonlinear controller called fractional-order synergetic control–fractional-order proportional-integral (FOSC–FOPI) controller, where the proposed technique parameters are calculated using the particle swarm optimization (PSO) strategy. It has been observed that the DFOC–FOSC–FOPI–PSO strategy is robust and works well in case of changing generator parameters. Three tests were performed to study the behavior of the designed technique under different working conditions, where the behavior of the DFOC–FOSC–FOPI–PSO strategy was compared with the behavior of the traditional DFOC technique in terms of power ripple ratio, overshoot, steady-state error, response time, tracking reference, and current quality. The simulation of the designed technique based on the FOSC–FOPI–PSO strategy of the AG–WP system is carried out using Matlab software, where the simulation results showed that the suggested technique is better than the classical technique (with PI controller) in terms of improving response time of active power (33.33%) and reactive power (10%) in second test, reduction of the steady-state error of reactive power (96.95%) and active power (97.14) in first test, minimization of harmonic distortion of current (96.57%) in third test and significant minimization of ripples of active power (99.67%, 44.69%, and 98.95%) and reactive power (99.25%, 53.65%, and 70.50%) in the three tests. The effectiveness of the DFOC–FOSC–FOPI–PSO strategy is very high, so it can be a reliable solution for controlling various generators. [ABSTRACT FROM AUTHOR]