Microbial fuel cells for sustainable energy and wastewater treatment: Integrating seaweed biomass, machine learning, and hybrid systems for enhanced performance.

Geothermal energy represents a sustainable and low-carbon resource with strong potential to support decentralized energy systems in volcanic regions. In underexplored areas such as Mount Cameroon, accurate assessment and optimal utilization of geothermal resources are critical for reliable energy supply. Recent global seismic tomography models indicate a pronounced shear-wave low-velocity anomaly beneath Mount Cameroon, suggesting elevated subsurface temperatures consistent with geothermal potential. Building on this geophysical evidence, this study proposes an off-grid hybrid energy system integrating geothermal power, and fuel cell technology to simultaneously supply electricity and hydrogen. A comprehensive techno-economic, environmental, and sensitivity considerations were taken into account using HOMER Pro to identify the optimal system configuration under local demand conditions. The load profile shows recurrent peaks, requiring a flexible and dispatchable hybrid system. Results indicate that the optimal configuration comprises a 110 kW geothermal steam turbine, a 50 kW fuel cell, a 10 kW electrolyzer, a 25.5 kW power converter, and a 20 kg hydrogen storage tank. This system achieves reliable power supply with a net present cost of approximately US$ 1.84 million and a levelized cost of energy of US$ 0.465/kWh, while ensuring zero direct carbon emissions. Sensitivity analyses reveal that system economics are most influenced by fuel cell capital and replacement costs. The proposed hybrid system demonstrates the technical feasibility and economic viability of coupling geothermal energy with hydrogen technologies in volcanic regions. The results highlight its potential as a replicable solution for clean, resilient, and decentralized energy access in remote and underserved communities.

• A GIS-based approach combined with a siting algorithm for optimal RE siting. • Incorporating CO2 budgets into the logic of spatial planning for REs. • Current land use regulations allow for the production of carbon-neutral electricity. • Achieving climate protection goals requires substantial changes to the landscape.

Data-driven multi-objective optimization of a novel waste-fueled polygeneration system for simultaneous production of hydrogen, freshwater, hot water, chilled water, cooling power, and electricity

DEMO reactor aims to demonstrate the feasibility of electrical energy production from nuclear fusion source in a tokamak configuration. Within the DEMO pre-conceptual design assessment, the water-cooled lithium lead (WCLL) and helium-cooled pebble bed (HCPB) concepts were selected as Breeding Blanket (BB) candidates. Along the research pathway toward blanket selection, safety analyses of these two options were performed using selected postulated initiating events (PIEs) as reference scenarios. For the WCLL BB, the out-vessel loss of liquid metal was identified as a major safety concern. This paper presents a numerical analysis of this postulated accidental scenario, carried out adopting MELCOR code. Large rupture (double-ended 200%) and leak (5%), occurring at two different positions (middle and bottom) of lithium-lead (LiPb) Cold Leg (CL) in both the inboard (IB) and outboard (OB) loop, were simulated implementing a detailed MELCOR nodalisation. The exothermic reactions of LiPb with air and steam present in the DEMO building were evaluated, adopting an in-house conservative numerical model, since only pure lithium-air/steam chemical reactions are available in the default MELCOR version. The LiPb mass flow rate discharged into the building was evaluated along with the LiPb volume transients in the hot and cold leg and segments of both the IB and OB loops. The time-dependent mass evolution of the reactants and products involved in the LiPb-air/steam chemical reactions was also calculated. Moreover, the increase in temperature and pressure within the considered building volume due to the energy released is shown. These numerical analyses do not implement safety or mitigation functions and the results presented should be considered highly conservative.

Solar photovoltaic systems are central to the future of electricity production worldwide. However, their performance degrades with age. The rate of decline in real-world usage critically affects the financial viability and carbon mitigation potential of photovoltaic installations. Earlier studies are typically limited by small sample sizes or short observation periods, and limited treatment of a potential non-linear relationship to environmental factors. This study uses high-dimensional fixed-effects panel regression encompassing up to 16 years of data from over 1 million solar installations in Germany (34 GW of capacity). Key robustness checks, including separate regressions for a self-consumption subsample and sensitivity analysis for air pollution, confirm the reliability of the estimates. The Findings show that power production falls by an average of 0.59% per year. Degradation rates decrease with age, with system output declining between 7% and 13% slower at age 10 than when new, and are one-third higher for larger installations ( > 30 kW p ). Output is significantly affected by environmental variables. Each day of extreme heat or cold and each microgram of particulate matter reduce annual output by 0.038–0.101%. Heat-related degradation intensifies over time, while cold and pollution have stronger effects on newer installations. By providing robust evidence from a population several orders of magnitude larger than previous studies, this study supports improved economic and environmental forecasts and strategic planning for global solar energy expansion. Back of the envelope, the estimated cost of degradation would compared to average literature results decrease by about €638 million p.a. to maintain installed capacity in 2040. • Output from 1.25 m German PV systems (34 GW capacity) spanning up to 16 years. • Fleet-scale, real-world solar performance ratio declines by 0.59% per year. • Degradation slows with age, by year 10 the rate is 7%–13% lower than when new. • Large PV systems (>30 kW p ) degrade ∼ 33% faster than small systems. • Heat, frost and PM 10 each reduce performance, heat damage worsens with age.

Renewable energy optimization in isolated microgrids: A Python-based tool for cost-effective solutions using genetic algorithms

The rapid growth of residential photovoltaic (PV) installations has increased interest in electrical storage units (ESUs) as a means of enhancing self-consumption and reducing surplus electricity fed into the grid. However, in temperate climates characterized by strong seasonal variability in solar generation, the economic viability of residential battery storage remains uncertain. This study examines whether ESUs provide measurable financial benefits under such climatic conditions, particularly after the transition from net-metering to net-billing schemes. The analysis combines empirical household electricity consumption data with simulation-based modeling of PV–battery operation. Periods of surplus energy production during high solar generation were taken into account, as well as periods of increased energy demand in the winter season and technical limitations related to energy storage, including the difference between actual and nominal capacity of energy storage systems. The results indicate that although battery storage increases self-consumption and reduces grid injection during peak generation periods, its economic performance is limited by the seasonal mismatch between electricity production and demand. Consequently, under net-billing conditions, residential ESUs do not automatically ensure economic profitability in temperate climates.

The decoupled operation of electricity and water systems under variable demand conditions and tightly coupled operational constraints tends to increase total operating costs and reduce overall resource-use efficiency. In response, this study develops an integrated optimization framework for the short-term management of water–energy nexus systems composed of thermal generating units, co-production units, and a desalination plant. The proposed formulation is designed to simultaneously satisfy electricity and water demands while minimizing the total operating cost over a 24 h scheduling horizon. Methodologically, the problem is formulated as a mixed-integer nonlinear programming (MINLP) model implemented and solved in GAMS. The model explicitly incorporates electricity and water balance equations, generation-capacity limits, desalination bounds, thermal ramp-rate constraints, technical coupling relationships between electric power and water production in co-production units, and non-separable quadratic cost functions that preserve the techno-economic structure of joint production. The results confirm the technical and economic consistency of the integrated dispatch. In particular, the optimized solution satisfies an electricity demand of 45,491 MWh and a water demand of 7930 m3 with complete hourly balance consistency over the full scheduling horizon. Thermal units supply 59.4% of total electricity production, whereas co-production units contribute the remaining 40.6%. From the hydraulic perspective, the desalination plant provides 61.7% of total water demand, while co-production units supply 38.3%. The resulting total operating cost is USD 179,618.92. Relative to a decoupled benchmark, the integrated formulation reduces the total operating cost by USD 25,325.92, equivalent to 12.36%. These findings demonstrate that the proposed MINLP framework provides a robust and operationally relevant tool for the short-term planning of strongly coupled water–energy systems.

Decarbonizing the transportation sector requires quick adoption of low-carbon energy carriers, with green hydrogen becoming a promising option for zero/low-emission mobility. Hydrogen refueling stations powered by renewable energy sources present a practical way to cut down lifecycle greenhouse gases and ease grid congestion. Nonetheless, most existing photovoltaic (PV)-based hydrogen production systems focus solely on electrical aspects, overlooking thermal energy flows and temperature effects that greatly impact PV and Electrolyzer performance. This study provides a thorough techno-economic evaluation of a hybrid PV/photovoltaic-thermal (PVT) green hydrogen system for refueling stations. The simulation framework models the combined electrical, thermal, and hydrogen subsystems under realistic conditions, incorporating rooftop PV/PVT collectors, battery storage, a water Electrolyzer, and hydrogen storage. Thermal energy from the PVT is used to pre-heat Electrolyzer feedwater, lowering electricity demand for hydrogen production and boosting PV efficiency via active cooling. Hydrogen production follows a demand-driven control strategy based on randomly generated stochastic daily refueling events. Three configurations are compared: (i) grid-only electrolysis, (ii) PV-only assisted electrolysis, and (iii) fully integrated PV/PVT-assisted electrolysis. The results show that the integrated PV/PVT setup significantly increases self-consumption, autarky rate, and overall efficiency, while lowering reliance on grid electricity and hydrogen production costs. Developed case studies highlight the economic feasibility and real-world viability of PV/PVT-assisted (decentralized) hydrogen refueling infrastructure.

Direct phosphorus recovery from anaerobic digestion sludge by microbial fuel cell with anolyte circulation: Optimization and key factors identification.

ABSTRACT Coal-fired power plants continue to play a significant role in the global energy mix, as evidenced by the stable electricity production levels maintained by major economies such as the United States, China, and India. However, due to the negative impact of such power plants on the environment, in recent years there has been an intensive search for the methods and means of reducing the concentration of anthropogenic oxides in the flue gases of coal-fired power plants. One of these methods is the combustion of coal mixed with various additives, for example, with water (water-coal fuels (WCF)), but such fuels do not provide high heat of combustion. Therefore, it is advisable to analyze the prospects of burning a mixture of moisture-saturated particles of coal and wood. The article presents the results of the experimental studies of heat and mass transfer processes occurring jointly under the conditions of intensive phase (evaporation of moisture) and thermochemical (interaction of fuel with oxidizer, formation of anthropogenic combustion products) transformations during ignition of dry and wet coal particles together with wood biomass particles. This article presents the results of experimental and numerical studies of heat and mass transfer processes occurring simultaneously under conditions of intense phase (moisture evaporation) and thermochemical (fuel-oxidizer interaction, formation of anthropogenic combustion products) transformations during the ignition of dry and wet coal particles along with woody biomass particles. The experimental and numerical modeling results correlate well. Based on the results of experimental and theoretical studies, it has been established that moderate wetting of coal particles, as well as the addition of woody biomass particles (both dry and wetted) to the coal, leads to a significant reduction (from 5 to 35%, depending on the oxidizer temperature T = 873–1273 K) in the proportion of nitrogen oxides (NOx) in the gaseous combustion products of the fuel mixtures. It is shown that, as a result of the adsorption of NOx by water vapor, nitric acid vapor is formed in the combustion products. The research results presented in the article confirm the possibility of using mixtures of moistened coals with woody biomass for the purpose of sequestering nitrogen oxides during fuel combustion.

The Albanian energy sector is highly reliant on hydropower, making the national energy balance vulnerable to seasonal variability and hydrological shocks. This study analyzes quarterly electricity production data for 2012Q1-2025Q3 using Seasonal-Trend decomposition via Loess (STL) and Seasonal Autoregressive Integrated Moving Average (SARIMA) modelling. STL is used to isolate trend and seasonal strength, while a SARIMA(0,1,2)(0,1,1)4 model is estimated to generate production forecasts for the 2025Q4-2030Q4 horizon (Q = calendar quarter). Results confirm a dominant seasonal component (FS = 0.635) and a recurring seasonal trough in Q3. A post-2022 increase in volatility is reflected in widening 95% prediction intervals, indicating that while the seasonal timing of stress is predictable, the magnitude of future outcomes becomes increasingly uncertain over the medium term. To operationalize this risk, the study implements a hydrological drought stress test on Albania's quarterly net domestic production (Yp), using the SARIMA baseline as the reference path. The sensitivity results quantify sizable, seasonally concentrated supply gaps under proportional production shocks (- 10% and - 25%), reinforcing the structural nature of the recurring third-quarter (Q3) deficit and its implications for adequacy and import coverage. The findings inform resilience planning by quantifying the scale and timing of seasonal shortfalls and by motivating diversification and flexibility options that are seasonally complementary to hydropower. In particular, solar PV is discussed as a potential counter-cyclical contributor conditional on scale-up, grid hosting capacity, and balancing resources. The paper concludes that hydropower-centric strategies alone are insufficient for medium-term stability and highlights the role of diversified non-hydro resources, grid-efficiency improvements, and storage in hedging forecasted production troughs and reducing exposure to external balancing needs.

The China-Pakistan financial hall CPEC is a very essential mission of China's Belt and avenue assignment (BRI), it goals to decorate connectivity and monetary cooperation between China and Pakistan. It became initiated in 2015, it includes infrastructure, power, and industrial projects. It has numerous key additives consist of highways, railways, and the improvement of Gwadar Port. CPEC ambitions to improve Pakistan's infrastructure, decorate electricity production, and create monetary possibilities whilst offering China with a shorter exchange course to the middle East and Africa. Although geopolitical and financial challenges, CPEC remains a very important of China and Pakistani relations, fostering regional trade and development. Throughout my research I measured several indicators such as social media usage, misinformation, public trust and the use of free digital services that influence public perception on CPEC. I collected 300 responses from students of university of Sargodha, Pakistan through closed ended questionnaire survey. Their responses played an important role to understand the real time scenario.

Urban rooftop photovoltaic systems represent a substantial yet still underutilized renewable energy resource, particularly in high-density residential environments. Accurate large-scale assessment of rooftop solar potential, however, remains challenging due to the complex geometry of urban morphology and the limited availability of high-resolution geospatial data. This study presents a large-scale methodological framework for estimating the theoretical photovoltaic potential of urban rooftop spaces using Unmanned Aerial System (UAS)-based digital photogrammetry and GIS-based spatial analysis. The approach integrates centimeter-resolution Digital Surface Models (DSMs) and orthophotos derived from fixed-wing UAS surveys with detailed rooftop vectorization and solar radiation modeling implemented in a GIS environment. The methodology accounts for rooftop geometry, surface orientation, slope, shading effects, and rooftop-mounted obstacles. The methodology consists of data collection of high-resolution RGB imagery suitable for detailed three-dimensional reconstruction. The images are captured with a UAS equipped with a S.O.D.A. 3D photogrammetric camera, creating a dense, georeferenced three-dimensional point cloud based on UAS imagery. Based on the point cloud, a high-resolution Digital Surface Model (DSM) was produced. Rooftop boundaries and rooftop-mounted structures were digitized on the basis of an orthophoto created from UAS imagery. The analysis workflow consists of solar modeling using ArcGIS Pro, including calculating the solar radiation. The next methodological step is to filter low radiation rooftops, steep slopes, and northern-oriented rooftops. Finally, we calculate the potential electricity production. The framework was applied to high-density residential districts in Sofia, Bulgaria, dominated by prefabricated panel buildings with predominantly flat rooftops. Drone applications in such studies are typically restricted to modeling individual roofs, which severely limits their scalability for district-wide evaluations. To overcome this, the study employs a specialized fixed-wing UAS uniquely certified for legal operations over densely populated urban environments. This platform rapidly maps large territories, ensuring consistent lighting and shading conditions that significantly enhance the accuracy of subsequent rooftop digitization. Furthermore, the resulting centimeter-level precision enables the exact vectorization of micro-rooftop obstacles. Capturing these intricate details is a critical innovation that effectively prevents the overestimation of solar energy potential commonly observed in conventional large-scale models. Solar radiation was modeled at the pixel level for a full annual cycle and filtered using photovoltaic suitability criteria, including minimum annual radiation thresholds, slope, and aspect constraints. Theoretical electricity production was subsequently estimated using zonal statistics and system performance parameters representative of contemporary photovoltaic installations. The results indicate a total theoretical annual electricity potential of approximately 76.7 GWh for the analyzed rooftop spaces, with an average production of about 34 MWh per rooftop and pronounced spatial variability driven by rooftop geometry and exposure conditions. The findings demonstrate the significant renewable energy potential embedded in existing urban rooftop infrastructure and highlight the applicability of UAS-based photogrammetry for high-resolution, large-area solar potential assessments. The proposed framework provides actionable information for urban energy planning, municipal solar cadaster development, and the strategic integration of photovoltaic systems into dense urban environments, particularly in regions lacking open-access high-resolution geospatial datasets.

Agrivoltaic systems offer a pathway to simultaneously produce food and electricity, yet their effectiveness depends on how photovoltaic configurations influence crop productivity under specific environmental conditions. This study evaluated land-use efficiency in an Andean–Amazon transition region using monofacial, bifacial, and semitransparent photovoltaic configurations integrated with a maize–bean intercrop. Land-use efficiency was quantified through the Land Equivalent Ratio (LER), combining agricultural yield and electrical energy production. All configurations achieved LER values above 1.0, confirming a clear advantage over separate land use. The semitransparent configuration showed the highest LER (1.95–1.99), followed by bifacial (1.66–1.90) and monofacial systems (1.51–1.72). LER variation was driven primarily by crop productivity rather than energy yield, while normalized photovoltaic performance remained stable across configurations. These results demonstrate that agrivoltaic performance is governed by system-level crop response, emphasizing the role of photovoltaic design in optimizing food–energy systems under tropical mountain conditions.

This study presents a fully integrated process for the flexible conversion of biogenic waste into synthetic natural gas (bio-SNG) and electricity centred on a 100 kWth dual concentric bubbling fluidised bed steam gasifier. The raw syngas is processed in a high-temperature gas cleaning section, and the resulting clean, H2-rich syngas is directed to three alternative downstream configurations: (i) conventional methanation, (ii) enhanced methanation with external H2 supplied by a reversible solid oxide cell (rSOC), and (iii) electricity generation via the same rSOC operating in fuel cell mode. The overall process is modelled in Aspen Plus, in which the gasification section is constrained by experimentally derived syngas data, while downstream units are described through thermodynamic and kinetics-based models. Methanation is simulated using a plug-flow reactor model based on validated kinetic expressions, while the rSOC operating in electrolysis and fuel cell mode is modelled using performance parameters of commercial stacks. A plant-wide heat integration strategy based on composite curve analysis is implemented to maximise internal heat recovery and minimise external utilities. The enhanced methanation configuration enables the production of bio-SNG with high methane content (up to 93.3 vol.% dry, N2-free), with a yield 0.72 kg/kgBiomass and a fuel efficiency of 70.1%. In electricity production mode, the system reaches an electrical efficiency of 43.1% with complete elimination of auxiliary fuel through thermal integration. These results demonstrate the capability of a single integrated plant to flexibly switch between fuel synthesis and power generation, enhancing adaptability to fluctuating electricity and methane market conditions while maintaining high efficiency.

Our research showed that the nanoparticles incorporated within the Metal-Organic Framework (MOF) substrate can facilitate self-driven electron transfer without the need for external stimulation to produce reactive oxygen species (ROS). The potential difference between bismuth nanoparticles and the central metal in the MOF is recognized as a key factor in the process of autonomous electron transfer. This study investigates the impact of central metal on electrochemical performance of bismuth nanoparticles and the production of active radical species. In this work, the MOF-303 with aluminum central metal was chosen to reduce the potential difference compared to previous our research focused on zirconium metal. The results indicate that the reduction in potential difference leads to a decrease in impedance and an increase in semiconductor capability. These changes improve the performance of bismuth nanoparticles in electron transfer, resulting in increased production of reactive oxygen species (ROS) under physiological conditions. Concurrently, this system depletes intracellular glutathione (GSH), converting it to oxidized glutathione (GSSG), and thereby disrupts redox homeostasis in tumor microenvironments. The acidic pH further enhances GSH oxidation, demonstrating the potential of Bi@MOF-303 as a pH-responsive, self-driven ROS amplifier. Live/dead cell staining assay validated the findings, revealing that Bi@MOF-303 had the highest percentage of cell death. This was due to significant oxidative stress caused by its self-driven electron transfer and depletion of GSH. Our innovative protocol, which emphasizes the accumulation of ROS in cancer cells through self-driven electron transfer, highlights the importance of central metal selection and its impact on electrical behavior and active species production for the first time.

Techno-economic analysis of an integrated desalination-renewable-hydrogen system for zero-emission freshwater and electricity production

Technical analysis for optimum hydrogen production using nuclear–renewable hybrid energy system