Search Results (246)

The expansion of green hydrogen requires technologies that are both manufacturable at a GW-to-TW power scale and adaptable for decentralized, renewable-driven energy systems. Recent advances in proton exchange membrane, alkaline, and solid oxide electrolysis reveal persistent bottlenecks in catalysts, membranes, porous transport layers, bipolar plates, sealing, and high-temperature ceramics. Emerging fabrication strategies, including roll-to-roll coating, spatial atomic layer deposition, digital-twin-based quality assurance, automated stack assembly, and circular material recovery, enable high-yield, low-variance production compatible with multi-GW power plants. At the same time, these developments support decentralized hydrogen systems that demand compact, dynamically operated, and material-efficient electrolyzers integrated with local renewable generation. The analysis underscores the need to jointly optimize material durability, manufacturing precision, and system-level controllability to ensure reliable and cost-effective hydrogen supply. This paper outlines a convergent approach that connects critical-material reduction, high-throughput manufacturing, a digitalized balance of plant, and circularity with distributed energy architectures and large-scale industrial deployment. Full article

Plasma-assisted nitrogen fixation is emerging as a promising alternative to the dominant industrial method of the Haber–Bosch (H–B) process, which is energy-intensive and environmentally detrimental. Nonthermal plasma technology represents a cutting-edge innovation with the potential to revolutionize nitrogen fertilizer (N-fertilizer) production, offering a more sustainable approach by operating under mild conditions, making it suitable for decentralized N-fertilizer production. Toward the goal, in this study, we demonstrate our development and test of a novel nonthermal plasma system for continuous on-site production of N-fertilizer. This technology results in a product of aqueous N-fertilizer on-site, from only air, water, and electricity without carbon emissions, directly applicable to plants, bypassing costly and hazardous multiple steps in the production and transportation of the industrial N-fertilizers. Full article

Rapid integration of renewable energy sources poses a serious problem to the functionality of microgrids since they are characterized by underlying uncertainties and variability. This paper proposes a multi-stage approach to energy management to overcome these issues in a virtual power plant that combines heterogeneous microgrids. The solution is based on multi-agent deep reinforcement learning to coordinate internal energy pricing, microgrid scheduling, and virtual power plant-level energy storage system management. The proposed model autonomously learns the optimal dynamic pricing strategies based on load and generation dynamics, which is efficient in dealing with operational uncertainties and maintaining microgrid privacy due to its decentralized structure. The efficiency of the proposed solution is tested on comparative simulations based on real-world data, which prove the superiority of the framework to the traditional operation modes, which are isolated microgrids and the energy sharing scenarios. The findings prove that the suggested solution has a dual beneficial impact on both virtual power plant operators and involved microgrids, as it leads to profit enhancement and, at the same time, system stability. This process facilitates the successful balancing of conflicting interests among the stakeholders at a time when the operation is low-carbon. The study offers an overall solution to dealing with complicated multi-microgrids and brings substantial changes in the integration of renewable energy, as well as the distributed management of energy resources. The framework is a scalable model that can be used in the future perspective of power systems with high-renewable penetration to address both economic and operational issues of the contemporary energy grids. Full article

Maximum power point tracking (MPPT) under partial shading is a nonconvex, rapidly varying control problem that challenges multi-agent policies deployed on photovoltaic modules. We present Fuzzy–MAT3D, a fuzzy-augmented multi-agent TD3 (Twin-Delayed Deep Deterministic Policy Gradient) controller trained under centralized training/decentralized execution (CTDE). On the theory side, we prove that differentiable fuzzy partitions of unity endow the actor–critic maps with global Lipschitz regularity, reduce temporal-difference target variance, enlarge the input-to-state stability (ISS) margin, and yield a global $L_{\infty }$$\gamma$-contraction of fixed-policy evaluation (hence, non-expansive with $\kappa =\gamma <1$). We further state a two-time-scale convergence theorem for CTDE-TD3 with fuzzy features; a PL/last-layer-linear corollary implies point convergence and uniqueness of critics. We bound the projected Bellman residual with the correct contraction factor (for $L^{\infty }$ and $L^2\left(\rho \right)$ under measure invariance) and quantified the negative bias induced by $min\{Q_1,Q_2\}$; an N-agent extension is provided. Empirically, a balanced common-random-numbers design across seven scenarios and 20 seeds, analyzed by ANOVA and CRN-paired tests, shows that Fuzzy–MAT3D attains the highest mean MPPT efficiency (92.0% ± 4.0%), outperforming MAT3D and Multi-Agent Deep Deterministic Policy Gradient controller (MADDPG). Overall, fuzzy regularization yields higher efficiency, suppresses steady-state oscillations, and stabilizes learning dynamics, supporting the use of structured, physics-compatible features in multi-agent MPPT controllers. At the level of PV plants, such gains under partial shading translate into higher effective capacity factors and smoother renewable generation without additional hardware. Full article

This article deals with the design of a technically, legislatively, and economically balanced sewerage system for the municipality of Ropice, which has long lacked a central sanitary sewer system. On the basis of the analysis of the territorial conditions, hydro-technical calculations, and legislative requirements, two potential solutions are compared—a decentralized domestic WWTP and a central separate sewerage system with a treatment plant. The final concept favors the central solution in order to ensure operational reliability, sustainability, and the possibility of using grants. This study provides a model example of an applicable solution for rural settlements with similar wastewater management problems. Full article

The spatial configuration of Waste-to-Energy infrastructure plays a decisive role in determining the environmental and economic performance of municipal solid waste (MSW) management systems. This study applies a Life Cycle Assessment methodology to evaluate the environmental implications of centralized and decentralized siting strategies for Refuse-Derived Fuel utilization in Greece. Two alternative scenarios were modeled: (i) a centralized approach based on six large WtE plants as proposed by the Greek Ministry of Environment and Energy (gr. YPEN), and (ii) a decentralized approach involving smaller, regionally distributed units located closer to Recycling and Recovery Facilities. Using the SimaPro software and the ReCiPe method, environmental impacts were quantified across categories including global warming potential, acidification, eutrophication, and particulate matter formation. The results indicate that the decentralized scenario yields substantial environmental advantages, with reductions ranging from 33% to 45% across all impact categories and displaying a 35% decrease in CO₂-equivalent emissions compared to the centralized scenario. Economic analysis confirms these findings, showing a 31% reduction in total transport and emissions-related costs due primarily to minimized long-distance and maritime transport. The study concludes that decentralized RDF-to-energy systems offer a more balanced and sustainable pathway, enhancing operational flexibility, lowering environmental burdens, and improving social acceptance. These results underscore the importance of integrating spatial and logistical parameters in national WtE planning to align with EU waste hierarchy principles and circular economy objectives. Full article

Septic wastewater, or septage, represents a specific type of wastewater with a high concentration of organic matter and significant variability in composition, which places increased demand on its treatment. With the increasing pressure for decentralized solutions for small areas with no established sewage infrastructure, technologies that can ensure stable operation of the treatment plant are coming to the fore. This paper compares the technologies used for septic wastewater treatment, i.e., sequencing batch reactor (SBR), membrane bioreactor (MBR), and aerobic granular sludge reactor (AGS). For the AGS technology, a trial run of a selected wastewater collection plant is carried out. Full article

The incorporation of cattle slurry in soil in short-rotation-cycle poplar cultivations can be a win–win strategy, insofar as a main feedstock derived from local intensive dairy cattle breeding can be used as a natural fertilizer and in bioenergy produced in the same region. The circularity of this process can contribute to boosting local socio-economic value. In this context, this work involved the installation of a poplar SRC plantation with a density of 5330 trees ha⁻¹ in a 4000 m² moderately fertile flat site, which was formerly used as a vineyard. Mechanical dosages of slurry of 0, 26.6, 53.2, and 106.5 Mg ha⁻¹, designated as treatments T0, T1, T2, and T3, were applied three times per year during 2019, 2020, and 2021. The variables quantified were related to plant growth, biomass productivity and mass balances of K, P, Cu, Zn, Mg, and N, and organic matter in the whole soil, plant, and slurry system during the first rotation cycle. For treatments T0 and T1, all these seven chemical components showed positive balances in the system, with cumulative demand by soil and biomass being higher than cumulative supply by slurry. Negative balances occurred for P with T2 and T3 and for Zn with T3, so that an overall condition of nutrient saturation of the whole system was not achieved. A no-slurry application, or at most a moderate application equivalent to T1, in the second rotation cycle should therefore be prescribed to allow a nutrient equilibrium status to be achieved through internal seasonal recycling mechanisms. The biomass average productivities ranged from 6.1 to 11.8 Mg ha⁻¹ y⁻¹, peaking under treatment T2, and are within the typical values for a first rotation cycle for poplar SRCs. The biomass fuel quality was not affected by the slurry treatments. A good performance of plant total height and growth in diameter at breast height suggested that poplar trees were not stressed by the applied slurry. Only treatment T1 could assure that cattle CO₂-eq methane emissions were overall equilibrated by the carbon sequestration from poplar cultivation, with an absence of climatic-warming impacts. Treatments T2 and T3 could only partially minimize that impact, which would always exist. Globally, this site-specific analysis showed that, under moderately fertile conditions, controlled cattle slurry fertilization of poplar SRC cultivations, which would assure a long-term steady-state equilibrium, can be a viable option to contribute to decentralized production of bioenergy in rural communities. Full article

In the Northern Hemisphere, annual waves of influenza disease with varying degrees of spread and severity are observed each winter. With wastewater-based surveillance (WBS), including both centralized (one wastewater treatment plant, WWTP) and decentralized (three sewers) sampling, we aimed to detect differences in influenza viral copy numbers in wastewater over time, to investigate (sub)-community transmission within a city. A total of 313 grab/spot and composite samples were collected in Munich, Germany, during three consecutive influenza seasons (2022/23, 2023/24, and 2024/25) and were analyzed for influenza A virus (IAV) and influenza B virus (IBV) nucleic acids using digital droplet PCR (ddPCR). IAV and IBV wastewater copy numbers and citywide reported influenza cases showed strong correlations in both sampling approaches, suggesting the decentralized approach to be a reliable indicator of infection trends across the city. The three influenza seasons analyzed differed significantly in terms of their seasonal distribution, for example, exhibiting a strong co-circulation of IAV and IBV only in the 2024/25 season. Only with wastewater analysis, we reveal a reporting delay of influenza A cases at the beginning of the 2023/24 season. Higher influenza copy numbers were detected in sewer samples compared to the WWTP influent, likely due to viral decay. The study underscores the potential of influenza WBS to enable detection of seasonal onset early, identify local transmission patterns, and reveal underreporting in routine surveillance systems. Full article

Today, vaccines play a crucial role in ensuring personal safety and are the most effective method for preventing related diseases. The ages over which vaccines are efficacious, from infancy to the old, is of utmost importance. With the recent outbreak of COVID-19 in 2019, the demand for vaccines and their usage has significantly increased. This surge in demand has led to issues such as vaccine counterfeiting and related problems, which have raised concerns among the public regarding vaccine administration. As a result, this has also resulted in a lack of trust in vaccine manufacturing companies and raised doubts about production processes. To address these concerns, this study proposed a vaccine production supervision system with Internet of Things (IoT) device based on blockchain. By utilizing IoT devices, vaccine-sensitive production data can be collected and encrypted and leaks that could lead to great benefit losses for vaccine manufacturing companies can also be prevented. This system adopts a digital signature technique to import immutable characteristics to the data, offering conclusive evidence in case any issues occur with the vaccine in the future. Finally, the system also integrates with the Inter Planetary File System (IPFS) with a blockchain solution, storing manufacturing plant vaccine production records in a secure, publicly accessible, and decentralized storage space, and also enabling public verification. Full article

Modern electrical vehicles (EVs) are equipped with sizable batteries that possess significant potential as energy prosumers. EVs are poised to be transformative assets and pivotal contributors to the virtual power plant (VPP), enhancing the performance and profitability of VPPs. The number of household EVs is increasing yearly, and this poses new challenges to the optimization of VPP operations. The computational cost increases exponentially as the number of decision variables rises with the increasing participation of EVs. This paper explores the role of a large number of EVs as prosumers, interacting with a VPP consisting of a photovoltaic system and battery energy storage system. To accommodate the large quantity of EVs in the modeling, this research adopts the decentralized control structure. It optimizes EV operations by regulating their charging and discharging behavior in response to pricing signals from the VPP. A two-stage optimization framework is proposed for VPP-EV operation using a reinforcement algorithm and gradient-based programming. Action masking for reinforcement learning is explored to eliminate invalid actions, reducing ineffective exploration, thereby accelerating the convergence of the algorithm. The proposed approach is capable of handling a substantial number of EVs and addressing the stochastic characteristics of EV charging and discharging behaviors. Simulation results demonstrate that the VPP-EV operation optimization increases the revenue of the VPP and significantly reduces the electricity costs for EV owners. Through the optimization of EV operations, the charging cost of 1000 EVs participating in the V2G services is reduced by 26.38% compared to those that opt out of the scheme, and VPP revenue increases by 27.83% accordingly. Full article

Among the players for achieving the Sustainable Development Goals (SDGs) defined in the United Nations 2030 Agenda, global energy transition plays a pivotal role. Among the emerging strategies, energy sharing mechanisms, such as peer-to-peer (P2P) trading, virtual power plants (VPPs), energy communities, and local energy markets are widely recognized for their potential to increase energy justice, resilience, and sustainability. These models redistribute energy production and consumption responsibilities among users, fostering decentralization, democratization, and inclusivity in energy systems. This review synthesizes current literature on energy sharing and evaluates their contributions to specific SDGs, particularly SDG 7 (Affordable and Clean Energy), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action). Furthermore, the paper discusses regulatory frameworks, technological enablers, and socio-economic barriers to implementation. It concludes with policy recommendations for promoting energy sharing schemes as effective tools in the global pursuit of sustainable development. Full article

High-renewables grids are planned in min but judged in milliseconds; credible studies must therefore resolve both horizons within a single model. Current adequacy tools bypass fast frequency dynamics, while detailed simulators lack multi-hour optimization, leaving investors without a unified basis for sizing storage, shifting demand, or upgrading transfers. We present a two-layer Hierarchical Model Predictive Control framework that links 15-min scheduling with 1-s corrective action and apply it to Germany’s four TSO zones under a stringent zero-exchange stress test derived from the NEP 2045 baseline. Batteries, vehicle-to-grid, pumped hydro and power-to-gas technologies are captured through aggregators; a decentralized optimizer pre-positions them, while a fast layer refines setpoints as forecasts drift; all are subject to inter-zonal transfer limits. Year-long simulations hold frequency within ±2 mHz for 99.9% of hours and below ±10 mHz during the worst multi-day renewable lull. Batteries absorb sub-second transients, electrolyzers smooth surpluses, and hydrogen turbines bridge week-long deficits—none of which violate transfer constraints. Because the algebraic core is modular, analysts can insert new asset classes or policy rules with minimal code change, enabling policy-relevant scenario studies from storage mandates to capacity-upgrade plans. The work elevates predictive control from plant-scale demonstrations to system-level planning practice. It unifies adequacy sizing and dynamic-performance evaluation in a single optimization loop, delivering an open, scalable blueprint for high-renewables assessments. The framework is readily portable to other interconnected grids, supporting analyses of storage obligations, hydrogen roll-outs and islanding strategies. Full article

Coastal Bangladesh faces severe drinking water scarcity due to salinity intrusion. To address this challenge, the study assesses the socio-technical and economic factors shaping the performance of small-scale reverse osmosis (RO) desalination plants through field audits, household surveys, stakeholder interviews, and water quality analysis. Community acceptance was evaluated using the Theory of Planned Behavior (TPB). Feedwater was highly contaminated, with average TDS 3732.63 mg/L, hardness 636.36 mg/L, iron (Fe) 3.23 mg/L, and turbidity 14.63 NTU. Despite this, RO systems demonstrated strong performance, achieving removal efficiencies of 95.15% for salts, 95.95% for hardness, and 91.67% for alkalinity, with an average recovery rate of 37.25% (range: 20–60%). Treated water met WHO and Bangladesh standards, with mean concentrations of TDS (195.54 mg/L), Fe (0.21 mg/L), arsenic (0.0085 mg/L), and turbidity (1.09 NTU). However, inadequate operator training and a lack of maintenance threaten sustainability. Energy consumption increased by 0.1 kWh/m³ per 1000 mg/L rise in salinity, while financial constraints hinder membrane replacement. TPB analysis revealed positive attitudes and perceived behavioral control as key adoption drivers. Untreated brine discharge (mean TDS 12,900 mg/L) posed significant environmental risks. This study provides micro-level insights to inform policy and strengthen the sustainability of decentralized RO systems in climate-vulnerable coastal regions. Full article

With the characteristic of “decentralized distribution and local power supply”, small hydropower (SHP) in China has become a core means of solving the problem of insufficient power supply in rural and remote mountainous areas, effectively promoting the improvement of local livelihoods. However, for a long time, SHP has had many problems, such as irrational development, old equipment, and poor economic efficiency, resulting in some rivers with connectivity loss and reduced biodiversity, etc. The Chishui River Watershed is an ecologically valuable river in the upper reaches of the Yangtze River. As an important habitat for rare fish in the upper reaches of the Yangtze River and the only large-scale tributary that maintains a natural flow pattern, the SHP plants’ dismantling and ecological restoration practices in the Chishui River Watershed can set a model for regional sustainable development. This paper adopts the methods of literature review, field research, and case study analysis, combined with the comparison of ecological conditions before and after the dismantling, to systematically analyze the effectiveness and challenges of SHP rectification in the Chishui River Watershed. The study found that after dismantling 88.2% of SHP plants in ecologically sensitive areas, the number of fish species upstream and downstream of the original dam site increased by about 6.67% and 70%, respectively; the natural hydrological connectivity has been restored to the downstream of the Tongzi River, the Gulin River and other rivers, but there are short-term problems such as sediment underflow, increased economic pressure, and the gap of alternative energy sources; the retained power stations have achieved the success and challenges of power generation and ecological management ecological flow control and comprehensive utilization, achieving a balance between power generation and ecological protection. Based on the above findings, the author proposes dynamic monitoring and interdisciplinary tracking research to fill the gap of systematic data support and long-term effect research in the SHP exit mechanism, and the results can provide a reference for the green transition of SHP. Full article