Search Results (327)

Standalone photovoltaic (PV) systems offer a viable path to decentralized energy access but face limitations during periods of low solar irradiance. While batteries provide short-term storage, their capacity constraints often restrict the use of surplus energy, highlighting the need for long-duration solutions. Green hydrogen, generated via proton exchange membrane (PEM) electrolyzers, offers a scalable alternative. This study proposes a stochastic energy management framework that leverages a Markov decision process (MDP) to coordinate PV generation, battery storage, and hydrogen production under variable irradiance and uncertain load demand. The strategy dynamically allocates power flows, ensuring system stability and efficient energy utilization. Real-time weather data from Goiás, Brazil, is used to simulate system behavior under realistic conditions. Compared to the conventional perturb and observe (P&O) technique, the proposed method significantly improves system performance, achieving a $99.9\%$ average efficiency (vs. 98.64%) and a drastically lower average tracking error of 0.3125 (vs. 9.8836). This enhanced tracking accuracy ensures faster convergence to the maximum power point, even during abrupt load changes, thereby increasing the effective use of solar energy. As a direct consequence, green hydrogen production is maximized while energy curtailment is minimized. The results confirm the robustness of the MDP-based control, demonstrating improved responsiveness, reduced downtime, and enhanced hydrogen yield, thus supporting sustainable energy conversion in off-grid environments. Full article

Managed aquifer recharge (MAR) is a complex and hidden process of storing surplus water under the ground surface and extracting it as, when and where needed. Evaluation of the success of any MAR project is challenging due to uncertainty in estimating the hydrogeological characteristics of the subsurface media. This paper demonstrates the use of a groundwater model (MODFLOW) to evaluate a new, large-scale regional MAR project in the agricultural heartland in Punjab, Pakistan. In this MAR project, flood waters have been diverted to the bed of an abandoned canal, where 144 recharge wells (the wells for accelerating the recharge into the aquifer) have been constructed to accelerate the recharge to the aquifer. The model was calibrated for a period of five years from October 2015 to June 2020 on a monthly stress period and the resulting water levels were simulated till 2035. The water balance components and future response of the aquifer to different scenarios up to 2035 including with and without MAR situations are presented. The model simulations showed that MAR can contribute to the replenishment of the aquifer and its potential for the case study site to contribute significantly to the management of groundwater and to enhance supplies for intensive agriculture. It was further established that MODFLOW can help in the evaluation of effectiveness of a MAR scheme. This study is unique as it evaluates a significantly large MAR project in an area where this practice has not been developed for improving groundwater access for large scale irrigation. The model provides guidelines for decision makers in the region as well as for the global community and livelihood benefits for rural communities. Full article

In the context of the evolving energy landscape, the need to harness renewable energy sources (RESs) has become increasingly imperative. Within this framework, hydrogen emerges as a promising energy storage vector, offering a viable solution to the flexibility challenges caused by the inherent variability of RESs. This work investigates the feasibility of integrating a hydrogen-based energy storage system within an energy community in Barcelona, using surplus electricity from photovoltaic (PV) panels. A power-to-power configuration is modelled through a comprehensive methodology that determines optimal component sizing, based on high-resolution real-world data. This analysis explores how different operational strategies influence the system’s cost-effectiveness. The methodology is thus intended to assist in the early-stage decision-making process, offering a flexible approach that can be adapted to various market conditions and operational scenarios. The results show that, under the current conditions, the combination of PV generation, energy storage, and low-cost grid electricity purchases yield the most favourable outcomes. However, in a long-term perspective, considering projected cost reductions for hydrogen technologies, strategies including energy sales back to the grid become more profitable. This case study offers a practical example of balancing engineering and economic considerations, providing replicable insights for designing hydrogen storage systems in similar energy communities. Full article

This study describes the step-by-step development of a simplified system which can be implemented in industrial facilities with the help of their own surplus of plastic waste, mainly packaging waste, to reach a level of energy autonomy or semi-autonomy. This waste is converted to about 57,500 L of synthetic pyrolysis oil, which can then be used to power industries, being fed into a Combined Heat and Power system. To achieve this goal, the design has hydrocarbon stability at elevated temperature and restricted oxygen exposure, so that they can be converted to new products. Pyrolysis is a key process which causes thermo-chemical changes—ignition and vaporization. The research outlines the complete process of creating a basic small-scale pyrolysis system which industrial facilities can use to generate energy from their plastic waste. The proposed unit processes 360 tons of plastic waste yearly to produce 160 tons of synthetic pyrolysis oil which enables the generation of 500 MWh of electricity and 60 MWh of heat. The total investment cost is estimated at EUR 41,000, with potential annual revenue of up to EUR 45,000 via net metering. The conceptual design proves both environmental and economic viability by providing a workable method for decentralized waste-to-energy solutions for Small and Medium-sized Enterprises. Full article

The proton exchange membrane electrolyzer (PEMWE) has been regarded as a promising technology for converting surplus intermittent renewable energy into green hydrogen through electrochemical water splitting. However, the multiphase mass and charge transport processes with countercurrent flow within the PEMWE create complex structure–property relationships that are difficult to optimize. The interdependent effects of multiple structural parameters on the coupled heat transfer, mass transfer, and charge transfer processes further obscure performance optimization mechanisms. To decouple these phenomena and elucidate the underlying mechanisms, a multiphase one-dimensional mathematical model was developed and experimentally validated. Based on the model, the mass transfer, charge conduction, and heat transfer processes inside the PEMWE have been systematically investigated, with a particular focus on the performance-related parameters of the porous transport layer (PTL). The results reveal that PTL thickness and porosity exhibit opposite effects on activation and ohmic overpotential at an elevated current density. Furthermore, a sharp performance decline occurs when PTL gas permeability falls below the critical threshold. These findings provide quantitative guidelines for multiphysics-informed component optimization in high-performance PEMWEs. Full article

Domestic food waste and agro-industrial by-products (AIBPs) occurring throughout the food chain, including production, processing, and storage, have become a global sustainability concern. Interestingly, this waste and these by-products contain a significant amount of commercially vital bioactive compounds, including polyphenols and carotenoids. Remarkably, discarded by-products such as fruit and vegetable peels contain more bioactive compounds than edible pulp. Thus, valorizing this waste and these by-products for commercially vital bioactive products can solve their disposal problems and help alleviate climate change crises. Additionally, it can generate surplus revenue, significantly improving food production and processing economics. Interestingly, several bioactive extracts derived from citrus peel, carrot pomace, olive leaf, and grape seed are commercially available, highlighting the importance of agro-food waste and by-product valorization. Considering this background information, this review aims to provide holistic information on major AIBPs; recovery methods of bioactive compounds focusing on polyphenols, carotenoids, oligosaccharides, and pectin; microencapsulation of isolated bioactive for enhanced physical, chemical, and biological properties; and their commercial application. In addition, green extraction methods are discussed, which have several advantages over conventional extraction. The concept of the circular bio-economy approach, challenges in waste valorization, and future perspective are also discussed. Full article

In recent years, underground hydrogen storage (UHS) has become a hot topic in the field of deep energy storage. Green hydrogen, produced using surplus electricity during peak production, can be injected and stored in underground reservoirs and extracted during periods of high demand. A profound understanding of the mechanisms of the gas–water two-phase flow at the pore scale is of great significance for evaluating the sealing integrity of UHS reservoirs and optimizing injection, as well as the storage space. The pore structure of rocks, as the storage space and flow channels for fluids, has a significant impact on fluid injection, production, and storage processes. This paper systematically summarizes the methods for characterizing the micro-pore structure of reservoir rocks. The applicability of different techniques was evaluated and compared. A detailed comparative analysis was made of the advantages and disadvantages of various numerical simulation methods in tracking two-phase flow interfaces, along with an assessment of their suitability. Subsequently, the microscopic visualization seepage experimental techniques, including microfluidics, NMR-based, and CT scanning-based methods, were reviewed and discussed in terms of the microscopic dynamic mechanisms of complex fluid transport behaviors. Due to the high resolution, non-contact, and non-destructive, as well as the scalable in situ high-temperature and high-pressure experimental conditions, CT scanning-based visualization technology has received increasing attention. The research presented in this paper can provide theoretical guidance for further understanding the characterization of the micro-pore structure of reservoir rocks and the mechanisms of two-phase flow at the pore scale. Full article

Ecosystem service flows are critical linkages between ecological supply and human demand. As a vital component of ecosystem services, water yield service is essential for human survival and development. Therefore, it is of great significance to explore the supply–demand relationship of water yield service and its spatial flow process. This study investigates the supply–demand dynamics and spatial flow of water yield service in the transnational area of Tumen River (2000–2020), utilizing the InVEST model and the miniature delivery-path-mechanism model. The results show the following: (1) From 2000 to 2020, the supply of water yield service in the Tumen River Basin exhibited a spatial distribution pattern of “low center, high surrounding”, with significant spatial heterogeneity in the distribution of supply and demand. (2) Despite the substantial surplus of water yield service in the study area, the ecosystem service supply–demand ratio (ESDR) shows an overall declining trend. The dominant spatial mismatch type is high-supply–low-demand (HL type) zones, primarily located in mountainous and hilly areas, accounting for over 40% of the total identified pixel types. (3) Driven by economic and social development, the spatial scope of water yield service flow has gradually expanded. Supply-side flows initially increased before declining, while demand-side flows followed the opposite trend. By mapping ecosystem service flows, this study provides a reference and basis for establishing the regional ecological compensation mechanism and promoting integrated water resource management, both of which are crucial for the long-term sustainable development of the basin. Full article

Continuous transformations, which have been observed more and more in recent years, require an increase in the effectiveness of measures in the state regulation of the labour market, which is possible only with a clear understanding and realistic assessment of its condition and existing trends of changes. For this purpose, guided by the data of the Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan, the country’s labour market was monitored, and the key factors that played a significant role in its formation were identified. Using these factors as a basis, vector autoregression (VAR) models were built to analyse dynamic relationships between economic variables. The choice of stationary variables ensured the adequacy of the model, which was confirmed by diagnostic tests such as the ADF test, Jarque–Bera test, and Ljung–Box test. Impulse response functions (IRFs) were used to assess the effect of shocks on each variable and other system variables. All results were visualised as graphs illustrating the dynamics of the impact over ten times. The modelling results showed that the changes are interrelated: shocks to youth unemployment (YUR) have the most significant impact on the total unemployment (UR) and the unemployed population (U), while outward migration (NM) has a short-run effect mainly on the economically active population (EA). The model confirmed that the labour market is indifferent to changes in youth unemployment, a key indicator for forming an effective employment policy. The study’s practical significance lies in its potential to inform the government, international organisations, and business communities about the state of the labour market and the necessary vectors of social policy. This will ensure economic growth and improve citizens’ quality of life in light of the changing nature of the labour market. Full article

This study investigates the socioeconomic determinants governing biomass energy transitions in rural areas of Eastern China through a multiregional spatial analysis. Drawing on time-series data from national and local statistical yearbooks, screened and processed to ensure consistency, the research analyzes evolving rural energy consumption patterns across nine cities in Heilongjiang, Jiangsu, and Guangdong provinces. Biomass energy potential was estimated by integrating crop production and domestic waste data with region-specific residue-to-product ratios, calorific values, and conversion efficiencies. These estimates were further spatialized through GIS-based surplus–deficit modeling to reveal regional disparities in supply–demand balance. The analysis identifies a critical income threshold, whereby lower-income regions exhibit rapid growth in energy consumption until reaching a saturation point around RMB 13,000, while higher-income areas experience continued increases in energy demand beyond the capacity of biomass resources to supply. The findings emphasize that an integrated approach, incorporating agricultural residue and domestic waste utilization, is essential for facilitating sustainable energy transitions, particularly in economically advanced regions. Furthermore, the study develops a scalable framework that integrates socioeconomic and spatial variables into biomass energy planning, underscoring the need for regional transition strategies to address not only resource endowments but also demographic mobility, urbanization dynamics, and income-driven consumption behaviors. Full article

This research provides a comprehensive review of hybrid energy solutions and optimization models for ports and marine environments. It details new methodologies, including strategic energy management and a machine learning (ML) tool for predicting energy surplus and deficits. The hybrid energy module solution for the Port of Avilés was further developed to evaluate the performance of new tools such as the Energy Management Tool (EMTv1), HYbrid for Renewable Energy Solutions (HY4RES), and a commercial model (Hybrid Optimization of Multiple Energy Resources—HOMER) in optimizing renewable energy and storage management. Seven scenarios were analyzed, integrating different energy sources and storage solutions. Using EMTv1, Scenario 1 showed high surplus energy, while Scenario 2 demonstrated grid independence with Pump-as-Turbine (PAT) storage. The HY4RES model was used to analyze Scenario 3, which achieved a positive grid balance, exporting more than imported, and Scenario 4 revealed limitations of the PAT system due to the low power installed. Scenario 5 introduced a 15 kWh battery, efficiently storing and discharging energy, reducing grid reliance, and fully covering energy needs. Using HOMER modeling, Scenario 6 required 546 kWh of grid energy but sold 2385 kWh back. Scenario 7 produced 3450 kWh/year, covering demand, resulting in 1834 kWh of surplus energy and a small capacity shortage (1.41 kWh/year). AI-based ML analysis was applied to five scenarios (the ones with access to numerical results), accurately predicting energy balances and optimizing grid interactions. A neural network time series (NNTS) model trained on average year data achieved high accuracy (R²: 0.9253–0.9695). The ANN model proved effective in making rapid energy balance predictions, reducing the need for complex simulations. A second case analyzed an increase of 80% in demand, confirming the model’s reliability, with Scenario 3 having the highest MSE (0.0166 kWh), Scenario 2 the lowest R² (0.9289), and Scenario 5 the highest R² (0.9693) during the validation process. This study highlights AI-driven forecasting as a valuable tool for ports to optimize energy management, minimize grid dependency, and enhance their efficiency. Full article

The surge in photovoltaic (PV) power generation has made it increasingly difficult to integrate the intermittent PV industry into the power grid while maintaining grid stability. The solution is to use the seasonal surplus of PV electricity to produce “green” hydrogen through water electrolysis and then use the hydrogen as an energy source or as a reactant in chemical processes in the chemical industry to produce value-added products. However, the development of advanced hydrogen storage technologies to ensure the safe handling, transportation, and distribution of H₂ is a major issue. The use of stable liquid organic hydrogen carriers (LOHCs) has emerged as a suitable technology for hydrogen storage. This review highlights prospective LOHC technologies based on reversible catalytic hydrogenation–dehydrogenation cycles of liquid organic molecules for hydrogen storage and release under mild temperature and pressure conditions. The state-of-the-art LOHC systems are critically reviewed, highlighting the most effective heterogeneous catalytic systems. Full article

The long-term rise in energy prices leads to reduced consumption, negatively impacting the efficiency of centralized heat supply systems (CHSS). As a result, it is necessary to address the economically inefficient preparation of hot water (HW) at heat transfer stations (HTS). Within the framework of the “Integrated National Energy and Climate Plan” (NECP), which is valid from 2021 to 2030, the industrial sector is aiming to produce 25% of its electricity from renewable energy sources (RES) by 2030. This target, up from 19.2% in 2018, equates to a value of 27.3%, which is at the technical limit of the Slovak electricity system. This article aims to study the installation of PV panels for domestic hot water (DHW) preparation within the central heat supply system (HTS) process, with the decision depending on the results of an economic return analysis. The estimated investment of EUR 5000 excluding VAT would generate annual savings of EUR 311, resulting in a payback period of approximately 16 years. The main limitation is the low efficiency in winter and no production at night, while in summer, a surplus of electricity can be used for preheating cold water. Full article

Air quality significantly impacts the environment and human living conditions, with direct and indirect effects on the economy. Precise and prompt detection of air pollutants is crucial for mitigating risks and implementing strategies to control pollution within acceptable thresholds. One of the common pollutants is nitrogen dioxide (NO₂), high concentrations of which are detrimental to the human respiratory system and may lead to serious lung diseases. Unfortunately, reliable NO₂ detection requires sophisticated and expensive apparatus. Although cheap sensors are now widespread, they lack accuracy and stability and are highly sensitive to environmental conditions. The purpose of this study is to propose a novel approach to precise calibration of the low-cost NO₂ sensors. It is illustrated using a custom-developed autonomous platform for cost-efficient NO₂ monitoring. The platform utilizes various sensors alongside electronic circuitry, control and communication units, and drivers. The calibration strategy leverages comprehensive data from multiple reference stations, employing neural network (NN) and kriging interpolation metamodels. These models are built using diverse environmental parameters (temperature, pressure, humidity) and cross-referenced data gathered by surplus NO₂ sensors. Instead of providing direct outputs of the calibrated sensor, our approach relies on predicting affine correction coefficients, which increase the flexibility of the correction process. Additionally, a calibration stage incorporating global correlation enhancement is developed and applied. Demonstrative experiments extensively validate this approach, affirming the platform and calibration methodology’s practicality for reliable and cost-effective NO₂ monitoring, especially keeping in mind that the predictive power of the enhanced sensor (correlation coefficient nearing 0.9 against reference data, RMSE < 3.5 µg/m³) is close to that of expensive reference equipment. Full article

This study assesses Queensland’s sugar industry potential for sustainable aviation fuel (SAF) production via biomass-to-liquids (BtL) processes. Using surplus sugarcane bagasse, preliminary estimates suggest that individual mills could support 60–130 MW_th gasifiers, while clustered approaches enable larger capacities. Annual BtL syncrude production could reach 440 mL, increasing to ~1000 mL with additional feedstocks. These findings highlight both the industrial-scale viability of SAF production and the logistical and engineering challenges that must be addressed to align with Australia’s renewable energy and fuel security goals. Full article