Search Results (2,095)

In the context of the global shift toward sustainable energy systems and circular economy strategies, anaerobic digestion is a well-established biotechnology for the valorisation of organic residues, the production of biogas as a renewable energy carrier, and the generation of nutrient-rich digestate. This study aimed to evaluate the stability and methane yield of a two-stage co-digestion process using a substrate mixture developed based on the actual feedstock composition of a full-scale agricultural biogas plant. The daily feed mixture consisted of maize silage (8.2%), sugar beet pulp (4.9%), cellulose pulp (6.6%), distillery stillage (38.6%), corn syrup (6.4%), cattle slurry (22.5%) and sterilised animal by-products (12.8%). Digestate was recirculated separately as part of the reactor operation. Laboratory-scale experiments were conducted in a two-stage anaerobic digestion system operated at 42 °C and 50 °C. The physicochemical properties of the substrates and digestate were determined, biogas quantity and composition were monitored, and the microbial community structure was assessed using 16S rRNA gene amplicon sequencing. The process remained stable throughout the experimental period, with pH values ranging from 8.23 to 8.53, alkalinity between 2600 and 2940 mg CaCO₃/dm³, and a VFAs/alkalinity ratio of 0.17–0.93. Despite ammonium nitrogen concentrations reaching 4346 mg N-NH₄⁺/L, no clear concurrent reduction in gas or methane production was observed. Methane accounted for approximately 70–80% of the biogas produced. The overall specific methane yield reached 346.4 NL CH₄ kg⁻¹ VS added. 16S rRNA gene amplicon sequencing revealed a diverse microbial community containing taxa previously associated with hydrolysis, fermentation and syntrophic interactions, including Proteiniphilum and Syntrophaceticus. The results demonstrate stable process performance and methane production in this site-specific laboratory-scale case study based on the feedstock composition and process configuration of a full-scale agricultural biogas plant. Full article

Floricultural residues represent a substantial and largely unvalorised organic stream in Europe, yet their anaerobic digestion has received limited attention. This study benchmarked the biochemical methane potential and degradation kinetics of Gerbera spp. flower residues (FRs), non-marketable apples (AW) and pig slurry (PS) under mesophilic batch conditions in mono-digestion and in five co-digestion mixtures. Mono-digestion yielded 362.5 ± 4.1 mL_CH4·g_VS⁻¹ for FR, constrained by lignocellulosic recalcitrance and a high extractive content, and 320.9 ± 39.2 mL_CH4·g_VS⁻¹ for AW, whose dispersion reflects the heterogeneity of non-marketable fruit; PS yielded 437.7 ± 2.6 mL_CH4·g_VS⁻¹ and supplied the alkalinity that both plant residues lacked. The highest yield was obtained for the ternary mixture COAD_5 (0.30 PS, 0.45 AW, 0.25 FR on a VS basis), reaching 472.8 ± 8.6 mL_CH4·g_VS⁻¹. This corresponds to a 29.1% increase over the theoretical additive potential (synergy index: 1.29 ± 0.07) and a gain of 8.0% over pig slurry mono-digestion. Once uncertainties were propagated, demonstrable synergy was confined to COAD_5 and to the binary mixture COAD_4. All treatments remained stable, with final pH between 7.40 and 7.86 and VFA-to-alkalinity ratios below 0.11. Kinetic modelling distinguished two regimes: first-order behaviour for the hydrolysis-limited and slurry-dominated substrates, and Modified Gompertz behaviour for the sugar-rich mixtures. Applied to the project site, these yields correspond to a preliminary gross scenario of the order of 481,000 Nm³ CH₄·yr⁻¹. The results establish that floricultural residues can be integrated into livestock-based anaerobic digestion without compromising process stability. Full article

Renewable energy and energy storage stations require frequent updates of monitoring and control logic across heterogeneous devices and changing operating strategies. This paper proposes a rule graph-based reference architecture that combines low-code logic configuration, graph–model semantic binding, and microservice-oriented functional decomposition. A component status matrix separates the target architecture from the implemented subset. The runnable subset comprises a minimal FastAPI backend, REST/WebSocket telemetry interfaces, an in-process queue, and stateful rule evaluators; gateway, authentication, external message bus, time-series database, visual editor, and industrial protocol services remain design-level elements. Beyond the original single-rule example, a priority-ordered multi-device rule is implemented for cooperative BESS dispatch, communication/topology blocking, low-SOC protection, frequency-based load shedding, backup request, and five-sample recovery release. Existing local network benchmarks are complemented by a 600-step software-in-the-loop trace with scripted telemetry fluctuations and communication quality faults and by 500 in-process ASGI timing samples at each of the four point levels. The trace produced no safety dispatch or protected device violations. P99 application path latency ranged from 1.1962 to 5.5287 ms, but one 75.3065 ms outlier exceeded a 50 ms reference deadline, demonstrating that the Windows/FastAPI path is not deterministic. No industrial controller, hardware-in-the-loop facility, field data, or engineer usability study was used. Accordingly, the paper makes no claim of industrial real-time readiness or measured development effort reduction. Full article

Maritime routes ensure connectivity between nations, carrying a vast flow of goods across borders, while ports serve as the critical junctions within this network, managing a wide spectrum of commodities from raw materials to finished goods. Ports also generate employment across numerous sectors and underpin a broad range of allied industries. A seaport is a maritime facility equipped with docks, cranes, and storage infrastructure for international trade, where ships load and unload cargo, containers, and passengers. Key functions of seaports include customs processing, warehousing, and vessel services, with major global hubs such as Shanghai, PSA Singapore, DP World, and Rotterdam handling immense volumes of cargo each year. In contrast, Bangladesh’s ports, Chittagong, Mongla, and Payra, play a vital role in sustaining regional commerce. Today, ports are widely recognized as essential capital infrastructure and prime movers of economic activity. Smart ports are automated facilities that leverage advanced digital technologies, including sensors, big data analytics, artificial intelligence (AI), machine learning (ML), deep learning (DL), augmented reality (AR), digital twins, the Internet of Things (IoT), and various automation systems, to optimize overall operational efficiency. These tools streamline cargo movement while embedding sustainable practices to protect the environment. Beyond operational gains, smart ports deliver faster, more advanced services to all stakeholders involved in port operations, including shipping companies, customs agencies, local communities, and other relevant parties. Renewable energy sources, electric vehicle charging stations, onshore power supply, and smart logistics infrastructure are among the defining sustainability features of smart ports in the present-day context. This study examines the current status and future development trajectory of Bangladesh’s sea ports in relation to the broader global imperative toward smart port transformation. Full article

Nature-based solutions (NBSs) are central to urban climate-neutrality strategies, but their implementation still lags behind policy ambition. One reason is that most NBS benefits are public goods and rarely generate direct revenue, so we know far less about the institutional and financial conditions needed to deliver them than about their ecological performance. This paper develops a business model framework linking NBS interventions to financing and governance configurations, applying established NBS typologies and the Pestoff Triangle of state, market, and community provision to thirteen interventions across eleven sites in the Railway District of Thessaloniki, Greece. The interventions are organised into five business model categories: public space greening, private space upgrades, public–private hybrids, building retrofits, and renewable energy. Their financing logic is shaped less by intervention type than by ownership structure and stakeholder configuration. To address this gap, we followed category-specific blended finance strategies combining grants, private investment, regulatory incentives, and community resources, underpinned by stewardship-oriented governance. The findings suggest that scaling NBSs depends less on technical readiness than on institutional capacity to match financing and governance to local ownership and stakeholder contexts, offering a pathway from climate-neutrality strategy to implementable urban regeneration. Full article

Sustainable energy management in grid-connected AC microgrids is investigated through a comparative assessment of centralized, distributed, and decentralized multi-agent-system-based load management control architectures integrating photovoltaic (PV) generation and battery energy storage system. A sustainability-oriented rule-based load scheduling strategy is implemented to efficiently utilize available renewable energy while maintaining grid power consumption within the prescribed demand limits and ensuring priority support for critical loads. Multi-agent-system (MAS)-based load agents coordinate centralized, distributed, and decentralized load management operations. The control architectures are evaluated under identical load profiles, PV generation patterns, and demand-limit constraints to ensure a fair comparison of sustainability-oriented energy management performance. Their resilience is further assessed under agent failures, communication losses, and delays. The comparative analysis employs sustainability-oriented performance metrics, including load served percentage, load curtailment percentage, demand-limit violation duration, and PV utilisation, to assess reliable energy delivery, demand-side efficiency, grid compliance, and effective renewable-energy utilisation. The results reveal distinct architectural trade-offs in sustainable energy management: decentralized control offers greater resilience to agent failures and achieves the highest average load-served percentage (64.83%) and lowest demand-limit violation duration (40.61 ms). Distributed control provides enhanced coordination and priority-based load management, with intermediate performance (64.10%, 41.17 ms), whereas centralized control is constrained by single-point failures and scalability, exhibiting the lowest performance (58.52%, 43.33 ms). PV utilisation remains approximately 99% across all architectures, indicating near-complete utilisation of available solar generation for load supply and battery charging with minimal curtailment. Full article

Ukraine’s renewable electricity transition combines decarbonisation with wartime resilience and post-war reconstruction. This study examines the relationship between installed renewable capacity and realised electricity generation using a structured institutional diagnostic; a same-year 2023 benchmark with Poland, Romania, and Slovakia; the capacity-realisation index (CRI); the capacity-deficit ratio (CDR); and the exploratory k-means clustering of 42 European electricity systems. The clustering model uses four non-overlapping 2023 capacity variables—renewable hydropower, onshore wind, solar PV, and bioenergy—while treating pure pumped storage separately as a flexibility characteristic. Renewables accounted for 24.8% of Ukraine’s installed electricity capacity and 18% of generation in 2023, yielding a CRI of 0.73, compared with 0.59 in Poland, 0.76 in Romania, and 0.68 in Slovakia. Ukraine therefore does not exhibit uniquely weak capacity–generation alignment within the selected benchmark. Nevertheless, the summer 2024 CDR of 19.2% and Energy Community scores of 72% for decarbonisation, 56% for markets, and 26% for energy security document substantial system stress. In the exploratory k = 3 solution (silhouette = 0.645), Ukraine belongs to a 33-case cluster and lies 0.563 standardised units from its centroid. The combined evidence is consistent with, but does not prove, constraints related to settlement discipline, grid evacuation, balancing, project bankability, and wartime security. Policy priorities include audited arrears resolution, financeable auctions and PPAs, curtailment and war-risk provisions, targeted grid reinforcement, competitive flexibility procurement, and solar-plus-storage systems for critical facilities. Full article

Offshore wind farm (OWF) development raises concerns regarding potential conflicts with local fisheries and marine ecosystems. This study investigated the spatiotemporal dynamics of gillnet and trawl fisheries in the coastal waters off Changhua, Taiwan, across various development phases. (2016–2024). Spatial analysis revealed distinct operational patterns: gillnet fleets operated within and adjacent to wind farms, while trawl activities were concentrated in northern offshore waters, largely avoiding the development zone. The gillnet fishery demonstrated a significant increase in Income Per Unit Effort (IPUE), suggesting that local fishers successfully employed adaptive strategies. The IPUE of the trawl fishery indicated a slightly lower value during this period. These findings indicate that current OWF development has historically coexisted with gillnet fisheries without causing economic loss. The catch composition of gillnet fisheries remained stable, dominated by Silver croaker and Pharaoh cuttlefish. The species diversity indices of both fisheries showed a stable to increasing trend driven by seasonal variability rather than construction impacts. The habitat-driven shift in community structure was observed within the wind farm zone (gillnet fisheries), where the dominance of benthic species (e.g., Flatfish) transitioned toward reef-associated taxa (e.g., Spotted catfish, Black Sea bream). This indicates that the turbine foundations may function as artificial reefs, supporting a more complex assemblage. Nevertheless, the observed habitat alterations highlight the necessity for long-term monitoring to ensure the sustainable symbiosis of renewable energy expansion and marine resource conservation. Full article

Advancements in rechargeable batteries and environmental awareness campaigns have highlighted the importance of electric vehicles (EVs) in recent times. The influx of EVs has posed challenges in almost all areas of technology, including demand-side management (DSM). Extra generating units are switched ON to meet the resultant higher electricity demand, thus reducing the sustainability of the system. To overcome this challenge, effective DSM techniques integrating renewable energy sources are proposed to efficiently utilize the existing generating capacity. The primary goal is to fairly distribute available resources among smart homes and EV owners using the Shapley value and tau value. In this work, two scenarios are examined. First, a community energy storage (CES) approach is adopted to maximize CES revenue, reduce the grid peak-to-average ratio (PAR), and minimize electricity costs. Second, a coordinated group of EVs is utilized to minimize the impact of charging loads during peak hours while concurrently reducing EV charging costs. Simulation results show a reduction in the grid PAR from 2.468 to 1.799, or 27.1%, together with an average reduction of approximately 3% in the electricity cost of participating smart homes. In the EV scenario, optimal scheduling reduces total charging expenditure by 24.8% and lowers the system peak by 2.65% relative to uncoordinated charging of the same fleet, with the total cost distributed among the vehicles by the Shapley value. Benchmarking against a proportional-to-demand rule shows that the tau-value allocation coincides with proportional sharing, whereas the Shapley allocation shifts 4.2% of the allocation away from the household contributing most to the system peak. The framework provides a fair and individually rational cost allocation layer for community-scale peer-to-peer energy markets. Full article

Renewable energy communities (RECs) are increasingly recognised as important instruments for accelerating the transition towards decentralised, low-carbon energy systems. However, technological progress and supportive policies alone cannot ensure their success, as participation depends largely on citizens’ behavioural readiness. This study investigates the behavioural determinants of participation in renewable energy communities by extending the Theory of Planned Behaviour (TPB) with four motivational dimensions: environmental, economic, technical, and social. A quantitative cross-sectional survey of 174 household electricity users in Slovenia was analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings show that environmental and economic motivations were positively associated with Attitudes, Technical Motivation was positively associated with Perceived Behavioural Control, and Social Motivation was positively associated with Subjective Norms. These TPB constructs are positively associated with behavioural readiness to participate in renewable energy communities. A supplementary exploratory multi-group analysis suggested possible differences between prosumers and conventional consumers. Prosumer status reflected individual household renewable electricity production and not verified REC membership, while Behavioural Readiness captured prospective stated intention and willingness rather than observed participation. However, because the prosumer subgroup comprised only 15 respondents, these group-specific patterns should be interpreted cautiously and require confirmation in larger and more balanced samples. The study extends the Theory of Planned Behaviour by integrating a multidimensional motivational framework and conceptualises participation in renewable energy communities as a socio-technical behavioural process. The findings provide empirically informed insights for policymakers, municipalities, and renewable energy community developers seeking to support citizens’ behavioural readiness to participate in renewable energy communities. Full article

The energy transition requires efficient management of decentralized resources, in which Renewable Energy Communities (RECs) play an increasingly important role. However, the variability of solar generation and the unpredictability of consumption create complex balancing challenges. To address the limitations of existing planning tools—which often rely on synthetic profiles or small-scale validations—this study presents a data-driven Digital Twin-inspired simulation framework The unique contribution of this work lies in the combination of three elements: the use of high-resolution sub-hourly smart-meter data, the application of a novel demographic filtering methodology to accurately isolate permanent community load profiles, and the integration of an AI-driven N-HiTS (Neural Hierarchical Interpolation for Time Series) forecasting model. The framework was implemented using the PyECOM simulation engine and applied to the Culatra Island Energy Community, Portugal, processing empirical data from 338 dwellings. Multiple scenarios were evaluated, including demand flexibility, photovoltaic (PV) expansion, and battery energy storage (BESS) deployment. The baseline scenario revealed a substantial dependence on the external grid, with a Self-Sufficiency (SS) rate of 12.51%. Expanding PV capacity by 200 kWp increased SS to 32.1% but generated significant energy surpluses. The optimal configuration, integrating a 600 kWh BESS, increased SS to 37.3% while restoring the Self-Consumption (SC) rate to 99.8%. Furthermore, the integrated N-HiTS predictive model achieved a coefficient of determination of 0.64 under highly variable weather conditions. Ultimately, the results demonstrate the critical value of combining empirical simulation, optimized storage sizing, and advanced forecasting techniques to support robust REC planning. Full article

This study analyses household energy consumption patterns and the main energy-related challenges in the rural communities of San Sebastián de Yuluc and Sumaypamba, Ecuador, within the framework of sustainable community energy planning. A quantitative descriptive approach was adopted, based on structured household surveys and statistical analyses using descriptive statistics, nonparametric correlations, and mean comparisons. The results show that electricity consumption in both communities remains below the national household average, while liquefied petroleum gas remains the dominant cooking energy source. Firewood is still used by a portion of households, whereas the adoption of active solar energy systems is practically non-existent. Significant differences in electricity consumption were identified across communities, as were heterogeneous consumption patterns associated with household equipment and living conditions. In Sumaypamba, a strong positive correlation was found between electricity and gas consumption, suggesting complementary rather than substitutive energy use. The findings reveal limited infrastructure, unequal access to modern energy technologies, and a persistent dependence on non-renewable fuels. These results provide evidence to inform local energy transition strategies focused on rural electrification, energy efficiency, and renewable microgeneration to improve energy access, sustainability, and community resilience. Full article

Standalone DC microgrids offer a promising solution for providing reliable and sustainable electricity to remote communities in developing countries. However, the intermittent nature of solar and wind resources, combined with continuously varying load demand, presents considerable operational challenges in maintaining real-time power balance, stable DC bus voltage, and ensuring reliable continuous supply. Therefore, there is dire need for user-friendly control solutions tailored to the specific needs of isolated communities. As such, this paper presents a coordinated control and power management strategy for an isolated hybrid solar–wind–battery integrated DC microgrid for rural electrification applications. A comprehensive mathematical model of the standalone DC microgrid incorporating photovoltaic generation, wind energy conversion, battery storage, bidirectional DC-DC conversion, and common DC bus dynamics is developed at the very first stage of the proposed coordinated control framework. The framework utilizes principal local device loops and a secondary dynamic power management strategy to ensure efficient renewable power extraction, dynamic source–storage–load coordination, stable DC bus voltage, and real-time energy management within the developed standalone DC microgrid. It is worthwhile to mention that, instead of using synthesized or online available wind speed and solar irradiance data, this research utilized real-time recorded metrological data obtained from the Mehran University Jamshoro, Pakistan. The obtained results establish a stable DC bus voltage regulation within acceptable operating limits, continuous power balance, seamless bidirectional battery operation, and safe battery state-of-charge (SoC) management to prevent deep discharging or overcharging, thus ensuring reliable operation. The overall performance confirms the technical robustness, operational flexibility, and practical suitability of the proposed standalone hybrid DC microgrid architecture for its resilient operation and rural electrification applications. Full article

This paper presents the design, control, and validation of a solar photovoltaic (PV)-powered DC microgrid (MG) integrated with a battery energy storage system (BESS), which was studied at laboratory scale as a step towards remote electrification in resource-constrained regions. An Adaptive Neuro-Fuzzy Inference System (ANFIS)-based maximum power point tracking (MPPT) algorithm is implemented to maximise solar energy extraction under varying irradiance. An Adaptive Power Management (APM) framework is proposed to maintain DC bus stability when the BESS is unavailable to support the bus—a condition that may arise from battery degradation, sensor or communication failures, converter malfunctions, protection trips, or physical damage. In this work, BESS unavailability is represented at the system level as the withdrawal of BESS support; the individual fault mechanisms that may cause it are not separately modelled. The APM operates across three hierarchical layers—monitoring, decision, and control—and reuses only the voltage and current measurements already present in the MG, requiring no additional sensing. The system is evaluated under three operating scenarios: (i) intermittent renewable generation; (ii) varying load demand; (iii) stochastic fluctuations in both irradiance and load. During BESS unavailability, the APM activates prioritised adaptive load shedding or PV generation curtailment as appropriate, preserving critical loads and preventing DC bus overvoltage. In the scenarios studied, the APM reduces worst-case voltage sag from 35.9% to 2.4% and worst-case swell from 53.51% to 0.14%, while maintaining BESS State of Charge (SOC) within 20%–80% during normal operation. Compared with the conventional Perturb and Observe (P&O) and Incremental Conductance (INC) methods, the ANFIS-based MPPT achieves a mean point-wise tracking and conversion efficiency of 99.46%, a 1.78% improvement and a 0.86% improvement, respectively, which were corroborated by independent energy-based assessments (1.76% and 0.92%), with voltage deviations of 2.34% and oscillations of only 0.57 V peak-to-peak. Lyapunov-based analysis establishes asymptotic stability of the DC bus voltage in the BESS-regulated operating modes under stated assumptions. The proposed control strategies are validated through MATLAB/Simulink (R2025b) simulations and laboratory-scale experimental results, with the latter demonstrating coordinated PV–BESS–converter operation and bus voltage regulation. Full article

The decreasing cost of renewable energy sources has encouraged their development for isolated power systems capable of supplying electricity to remote communities while reducing dependence on fossil fuels. Among the available alternatives, wind energy combined with battery energy storage and hydrogen production technologies represents a promising solution for improving energy sustainability. However, the intermittent nature of wind power and the limited storage capacity of batteries create challenges in maintaining power balance and efficiently utilising surplus renewable energy. Conventional energy management strategies often lack a coordinated mechanism for distributing excess power according to the battery operating condition. This paper proposes a state-of-charge (SOC)-based power management strategy for an isolated wind power system operating under grid-forming (GFM) control. The proposed controller adjusts the converter voltage reference according to the battery SOC and coordinates the operation of the battery energy storage system (BESS), an electrolyser, and a dump load (DL). In this way, excess wind power is progressively redirected to hydrogen production and, when necessary, to the DL. The proposed strategy improves the utilisation of surplus renewable energy, supports hydrogen production, prevents battery overcharging, and maintains stable voltage and frequency operation under different operating conditions. Simulation results validate the proposed approach. Full article