Search Results (731)

This study evaluates the techno-economic performance of solar photovoltaic (PV) systems for powering a 7 t/day shea butter processing plant to address electricity constraints limiting rural processing and local value capture. Annual electricity demand is modeled under three operational scenarios: (i) a typical processing season from November to February; (ii) an extended season until mid-May; and (iii) near year-round operation with eleven months of processing. Using detailed load modeling and techno-economic simulations in HOMER Pro, off-grid PV/battery systems and grid-connected PV hybrids are compared using the levelized cost of electricity (LCOE). In scenario 1, the national grid remains the most cost-effective solution. Scenario 2 reveals that integrating 35% solar PV into the grid becomes economically attractive, offering a recoverable value of 263.33 thousand USD within 7.73 years. In scenario 3, the grid/PV/battery configuration emerges as the optimal solution, providing the lowest cost of electricity at 0.246 USD/kWh compared to 0.319 USD/kWh for a grid-only supply and delivering an internal rate of return (IRR) of 20.7%. Under the same scenario, the standalone PV/battery system also demonstrates strong economic viability, with a cost of 0.292 USD/kWh and an IRR of 9.2%, lower than average tariffs from PV mini-grid developers in sub-Saharan Africa. These results demonstrate the profitability and viability of PV-based systems in powering food processing facilities in off-grid regions. Full article

The treatment of oily wastewater represents a significant environmental challenge, requiring efficient separation technologies and waste valorization. This study evaluated different types of coagulants (ferric chloride 38% m/m, aluminum polychloride 18% m/m, aluminum sulfate 8% m/m, and ferrous sulfate 6% m/m) and anionic polymers (from six suppliers) for treating poultry slaughterhouse effluent, aiming to optimize both clarification and oil recovery from the floated sludge. Bench-scale jar tests (G = 300 s⁻¹ and 30 s⁻¹) were followed by full-scale validation in a dissolved air flotation unit (100 m³ h⁻¹) at a poultry processing WWTP. Recovered oil was extracted by hot cooking (95 °C) and tridecanter centrifugation, and its quality (moisture, acidity, saponification index) was assessed. A techno-economic analysis, including simple/discounted payback, NPV, IRR, Monte Carlo simulation (10,000 iterations, Python), and deterministic sensitivity analysis, was performed. Ferric chloride (38% m/m) produced the best technical results: treated effluent turbidity < 30 NTU, oil yield of 360 L day⁻¹ with moisture < 2% at the tridecanter outlet, and consistent sludge dewaterability (moisture 55–65%). Oil moisture increased dramatically (to >30%) after storage due to condensate contamination from an inefficient exhaust system, a critical operational flaw that must be corrected. No statistically significant effect of polymer type on oil recovery was observed, although high variability (CV > 50%) was noted during PAC tests. The simple payback period for ferric chloride was 60.7 months (discounted: 64.1 months), with a positive median NPV (USD 7925) under a 12% p.a. discount rate. Sensitivity analysis showed that the investment is most sensitive to oil price: a 20% drop in oil price leads to a negative NPV (−USD 21,727). Despite this risk, the project provides environmental compliance and waste-to-value benefits. The study demonstrates that ferric chloride enables effective oil extraction from poultry wastewater, but proper exhaust design is essential to maintain oil quality. Future work should focus on standardized test durations (≥72 h) and automated monitoring to reduce variability. Full article

Industrial decarbonisation requires the large-scale integration of renewable energy into energy-intensive processes traditionally characterised by limited flexibility, high heat demands, and strong dependence on fossil fuels. In this context, energy storage, encompassing thermal and electrical storage as well as hydrogen as an energy carrier, emerges as a key enabling solution to reconcile variable renewable supply with industrial process demands. This paper proposes a dynamic techno-economic framework linking sectoral energy profiles to storage sizing and economic performance in industrial renewable integration. Storage technologies are assessed with hydrogen emerging as a long-duration buffer and a solution for decarbonising high-temperature heat. A representative industrial plant with 5 GWh/year energy demand and an 80%/20% thermal-to-electric load split is analysed under increasing solar-to-load ratios (20–60%), with storage technologies evaluated both individually and in hybrid configurations. Results demonstrate that hybrid battery–hydrogen configurations systematically outperform single-technology solutions. Yearly energy cost reductions reach 16.6–33.8% at 20% renewable penetration, 30.0–49.6% at 40%, and 43.4–62.8% at 60%, with advantages over the best standalone option increasing on average from 13.5% to 28.0% as renewable availability rises. Overall, the study identifies scale-dependent feasibility thresholds and highlights small and medium-sized industrial plants as the most actionable deployment context under current technological and market conditions. Full article

This review examines current research and development directions in thorium-based nuclear fuel cycles and reactor systems, including innovative and modular reactor concepts being investigated in several nuclear-producing countries. The analysis considers the feasibility of integrating thorium-containing fuels into both existing and emerging reactor technologies. Particular attention is paid to the potential use of thorium-based fuels in pressurized water reactors (PWRs) as transitional platforms that can enable gradual introduction in thorium without requiring immediate deployment of entirely new reactor architectures.This study synthesizes representative quantitative results reported in the recent literature, including neutronic performance metrics, conversion ratio estimates, and fuelbehavior characteristics of mixed Th–U oxide fuels under typical operating conditions. These results are evaluated together with broader system-level considerations, such as fuelcycle closure potential, materials performance, and technology readiness across different reactor classes.A comparative assessment of light water reactors (LWRs), heavy water reactors (HWRs), and molten salt reactors (MSRs) demonstrates that each platform offers distinct advantages and limitations for thorium deployment. While LWR systems provide the most realistic near-term pathway for partial thorium introduction within the existing nuclear infrastructure, HWR and MSR concepts offer more favorable conditions for efficient thorium utilization and potential Th–U fuelcycle closure. These reactor classes are currently being explored within national research and development programs focused on advanced and modular nuclear technologies.By integrating neutronic analysis, materials considerations, fuelcycle strategies, and techno-economic factors, this review provides a system-level perspective on the research and development of innovative thorium reactor concepts and outlines realistic pathways for their gradual implementation in evolving nuclear energy systems. Full article

Microsieving-based advanced primary treatment (APT) has attracted increasing attention as an approach for restructuring carbon and energy flows within wastewater treatment plants (WWTPs). Unlike previous work that has often addressed individual microsieving technologies or specific recovery routes separately, this review provides a unified framework for comparing drum screens (DSs)/drum filters (DFs), cloth disc filters (CDFs), and rotating belt filters (RBFs) with conventional primary sedimentation (PST) in terms of separation mechanisms and pollutant capture. On this basis, it further discusses recent progress in energy and resource recovery from primary screenings, together with their relevance to energy demand reduction and carbon redistribution in WWTPs. Current limitations arise at two levels. Microsieving technologies remain constrained by mesh fouling and limited control over selective pollutant capture, while plant-wide evidence remains insufficient, particularly regarding techno-economic assessment of recovered products and life cycle assessment of full plant performance after replacing primary sedimentation. Future work should therefore focus on targeted process optimization and plant-wide evaluation of economic and environmental feasibility. Full article

The increasing penetration of renewable energy sources (RES) introduces significant variability and instability in modern power systems, creating a growing need for advanced and coordinated energy storage solutions. However, a key unresolved challenge remains the integrated modeling and optimal sizing of hybrid energy storage systems (ESS) that combine technologies with different temporal characteristics under high RES penetration. This study addresses this challenge by developing a unified techno-economic and physical–mathematical framework for hybrid ESS integrating lithium-ion (Li-ion), vanadium redox flow batteries (VRFB), and hydrogen (H₂) technologies. Unlike conventional approaches that treat storage technologies independently or use simplified hybrid representations, the proposed framework jointly considers dynamic energy balance, degradation-aware lifecycle behavior, and multi-criteria cost optimization. The model was implemented using Python 3.10-based simulation tools and evaluated under renewable penetration scenarios of 30%, 50%, and 70%. The results indicate that increasing RES penetration leads to higher power fluctuations, reaching ±15–20% at 50% RES and ±20–25% at 70% RES. The optimized hybrid system achieves an overall efficiency of up to 92%, reduces total system cost to approximately 450 USD/kWh, and extends operational lifetime to 25 years, demonstrating a balanced techno-economic performance compared to standalone storage technologies. The proposed framework addresses this gap by coupling dynamic energy balance analysis with degradation-aware techno-economic optimization, enabling coordinated allocation of storage functions across short-, medium-, and long-duration timescales. In this way, the study not only evaluates hybrid storage performance, but also provides a practical decision-support framework for renewable-dominated power systems, particularly in the context of Kazakhstan’s energy transition. Full article

Uncertainties in generation and dynamic load behavior provide new problems for radial distribution systems (RDS) caused by the growing integration of renewable distributed generators (RDGs), including solar photovoltaic (PV) systems and wind turbines (WTs), as well as electric vehicle charging stations (EVCS). This article offers a thorough techno-economic evaluation of how to best distribute RDG resources (solar PV, wind, and EVCS) inside a 28-bus distribution test system in India, taking into account generation volatility due to the seasons. Optimization of installation and operating costs, enhancing voltage stability, and decreasing active power loss are done all at once using a new Catch Fish Optimization Algorithm (CFOA). Integrating beta and Weibull distributions, respectively, into the probabilistic modeling of solar irradiance and wind speed allows for economic analysis to adhere to recognized approaches from contemporary multi-objective optimization frameworks. The simulation findings confirm that the proposed CFOA-based placement method improves economic efficiency, decreases energy loss, and increases system performance. Full article

Water scarcity is a global phenomenon, and Pakistan is no exception to it. This study aims to assess the techno-economic efficiency of the irrigation system for guava orchard and melon crop in the Hafizabad District of Punjab province in Pakistan. The study has employed efficiency theory for a comparative analysis of modern and high-efficiency irrigation methods in contrast to old traditional methods of irrigation to estimate differentiating impacts on technical efficiency (TE), economic efficiency (EE), water productiveness, and crop yield. The mixed method approach is exercised on data collected from 108 stratified farmers (large, medium and smallholders) using structured surveys and qualitative insights. Beta-regression models using Cauchit link function are applied to translate determinants of TE/EE by taking into account predictor factors such as farming experience, operational costs and water productivity. Results show that solar irrigation systems have significantly better performance than the conventional system by having better TE and EE scores than conventional system performance. Farming experience and water productivity also have positive effects on efficiencies. Results also show that solar systems increase water productivity, lower costs and increase guava and melon productivity to a significant extent, which in turns aid in reducing the effects of salinity and evaporation in arid conditions. The overall finding supports and emphasizes solar’s supremacy for sustainable horticulture. Findings highlight the importance of incentivizing solar adaptation and agrivoltaic integration in Pakistan to ensure sustainable agriculture in water-stressed areas such as Punjab for food security and resource conservation for the production of guava and melons. Full article

Croatia hosts one of the most intensive recreational boating activities in the Mediterranean, with over 134,600 registered vessels along 5835 km of Adriatic coastline. This paper presents an AI-driven simulation framework for evaluating electrification pathways for the Croatian recreational vessel fleet. A key contribution is the explicit treatment of the AIS data gap: recreational vessels in Croatia are not required to carry AIS transponders, so synthetic operational profiles calibrated from manufacturer specifications and verified economic data are used instead. Six machine learning architectures are compared for vessel energy demand forecasting, with a proposed Transformer-based model achieving the best simulated performance. Fleet-weighted Monte Carlo simulation across three electrification scenarios suggests that an AI-optimised hybrid configuration can, subject to use intensity, reduce per-vessel CO₂ emissions by up to 56.8% relative to conventional engines. Techno-economic analysis shows payback periods ranging from over 15 years for low-use private owners to 7–9 years for charter operators, supporting targeted incentive design. The framework is intended to be transferable to other Mediterranean coastal regions facing comparable data and operational constraints. Full article

This study presents a comprehensive and systematic integrative review of Neighborhood-Level Energy Hubs (NLEHs) as pivotal enablers of sustainable and resilient urban energy systems. In response to accelerating climate pressures, rapid urbanization, and the decentralization of energy production, NLEHs are conceptualized as multi-carrier platforms that enable coordinated energy generation, storage, conversion, and exchange at the neighborhood scale. Utilizing a PRISMA-informed methodology to synthesize 125 core studies, the review systematically evaluates recent advances across five interconnected dimensions: conceptual foundations, system typologies, energy flow architectures, urban integration, and optimization paradigms. Unlike conventional reviews, this study explicitly bridges the critical gap between techno-economic optimization and socio-environmental priorities. A key novelty is the proposed mathematical integration of energy justice and Social Life Cycle Assessment (S-LCA) directly into optimization algorithms (e.g., MILP and MPC) as dynamic constraints and penalty terms. Particular emphasis is placed on participatory governance models, lifecycle sustainability metrics, and digitalization tools such as AI-driven energy management systems and urban digital twins. The analysis further reveals critical research gaps, highlighting a stark geographic dichotomy between high-tech, market-driven NLEHs in the Global North and resilience-oriented hybrid microgrids in the Global South, alongside the lack of adaptive regulatory frameworks. By proposing a unified Cyber–Physical–Social perspective, this study provides actionable insights for planners, policymakers, and researchers to support the development of scalable, inclusive, and context-sensitive NLEH implementations. Ultimately, the paper contributes to redefining neighborhood-scale energy systems as not only efficient and low-carbon infrastructures, but also as socially equitable, globally scalable, and institutionally adaptive components of future smart cities. Full article

Microbial lipids have emerged as a promising sustainable alternative to plant- and petroleum-derived oils, with applications spanning biofuels, oleochemicals, nutraceuticals, and specialty materials. Significant advances in metabolic engineering and strain development have increased lipid production capacity across diverse microorganisms. Numerous reviews have summarized the biological and metabolic advances in this field, highlighting significant progress in metabolic engineering and strain development that has increased lipid production capacity across diverse microorganisms. However, translating these gains into economically viable industrial processes remains a major challenge. This review examines process engineering strategies for microbial lipid production across the full bioprocessing pipeline, from laboratory-scale strain evolution to industrial-scale operation. We discuss recent developments in adaptive laboratory evolution, systems-guided strain optimization, and robustness engineering, emphasizing their implications for process performance. Key bioprocess parameters—including substrate selection, nutrient limitation strategies, reactor design, oxygen transfer, and process control—are critically evaluated for their impact on lipid yield, productivity, and scalability. Furthermore, downstream processing considerations and techno-economic constraints are analyzed in the context of large-scale implementation. By integrating strain-level innovations with process engineering principles, this review highlights current bottlenecks, emerging solutions, and future directions for achieving efficient and scalable microbial lipid biomanufacturing. Full article

Poultry litter represents a promising feedstock for biogas production through anaerobic digestion (AD), offering potential benefits for both on-farm energy supply and organic waste management. This opportunity is particularly relevant in resource-constrained countries, where limited access to reliable energy and inadequate waste management remain critical challenges. This study investigates the integration of poultry litter-based biogas production into a decentralized energy system supplying a poultry farm and a nearby household in Yaoundé, Cameroon. A techno-economic optimization framework based on mixed-integer linear programming is used to determine the cost-optimal configuration of the energy system. The results show that anaerobic digesters are only selected when constraints on poultry litter disposal are introduced. Total annual system costs increase from approximately 2680 EUR·y⁻¹ in the unconstrained scenario to 3720 EUR·y⁻¹ when up to 50% of the poultry litter is valorized locally through AD. Increasing biogas production primarily substitutes liquefied petroleum gas (LPG) used for heating and progressively reduces electricity purchases from the grid. Overall, the analysis indicates that anaerobic digestion is currently not economically competitive when evaluated solely on energy supply benefits, mainly due to the high capital cost of digesters. However, when waste management objectives or external investment support are considered, poultry litter-based biogas systems can contribute to integrated energy–waste management strategies and support circular resource use in small-scale agricultural systems. Full article

Metallurgical-grade silicon (MG-Si) is an important source material for many industrial applications, including the manufacture of alloys, solar photovoltaics, and electronics. The process to refine raw materials into MG-Si is energy-intensive, with the predominant method of submerged-arc furnaces requiring energy consumption of approximately 11–13 kWh/kg Si. Recent research has discussed promising methods for reducing the energy required for the silicon production process, including the use of molten-salt electrolysis (MSE), a technique that offers potential savings in energy consumption without requiring carbon inputs for the process. This paper presents a techno-economic study of a potential industrial-scale MSE plant for MG-Si production to evaluate the trade-offs between capital and operating costs of the system. Capital costs are sourced from recent MG-Si plants and an existing cost model developed for MSE processes that includes the size of the plant and the operating temperature among its inputs. The results show that MSE technology has the potential to be an economically cost-competitive option for MG-Si production if the technology successfully scales to industrial production and matures enough to allow for financing costs similar to that of a comparably sized submerged-arc furnace plant. Full article

The increasing emphasis on sustainable and decentralized energy has elevated microgrids as a central element of modern power systems. By integrating renewable energy sources, advanced energy storage technologies, and intelligent control strategies, microgrids enhance efficiency, stability, and flexibility and play a vital role in creating resilient and adaptable energy networks. This review provides a comprehensive analysis of Energy Management Systems (EMSs) in microgrids, distinguishing between planning-oriented tools for techno-economic evaluation and control-oriented platforms for real-time operation and optimization. Hierarchical control architectures spanning primary, secondary, and tertiary levels are examined, highlighting their roles in frequency and voltage regulation, load sharing, and economic dispatch. Optimization techniques for EMSs are analyzed across deterministic, stochastic, metaheuristic, and artificial intelligence/machine learning methods, addressing objectives, constraints, uncertainties, and multi-timeframe decision-making. AI-based methods, including supervised learning, deep learning, and reinforcement learning, are highlighted for their ability to enhance predictive control, system autonomy, and operational efficiency, despite their computational demands. Future trends emphasize AI-based predictive control, deep learning for energy forecasting, multi-microgrid coordination, hybrid energy storage management, and cybersecurity enhancements. Overall, an intelligent EMS, combined with innovative technologies, is critical for developing resilient, scalable, and sustainable microgrid solutions that meet the evolving demands of modern energy systems. Full article

Wheat processing generates large volumes of co-products, particularly wheat bran (WB) and wheat germ (WG), which remain underutilized despite their high content of dietary fiber, phenolic compounds, bioactive peptides, and lipophilic antioxidants. Although their composition and processing have been widely investigated, an integrated and application-oriented evaluation of these fractions remains limited. This review provides a structured and critical analysis of WB, raw and defatted WG, and wheat germ oil (WGO), linking composition, processing strategies, and functional performance within a unified framework. Conventional and emerging technologies, including enzymatic hydrolysis, fermentation, thermomechanical treatments, and supercritical CO₂ extraction, are discussed in terms of selectivity, impact on techno-functional properties, and scalability. An evidence-grading approach is introduced to distinguish bioactivities supported by chemical assays, cell-based models, animal studies, or human data, enabling a more rigorous interpretation of health-related effects. Across applications, these co-products have been incorporated into food systems and related sectors, primarily showing improvements in nutritional composition, oxidative stability, and product performance under experimental conditions. However, translation to an industrial scale remains constrained by techno-economic limitations, regulatory requirements, and stability challenges. This work highlights the need for integrated processing strategies aligned with industrial feasibility to support the development of sustainable cereal biorefineries. Full article