Search Results (1,103)

The district heating system (DHS) can provide flexibility to the electrical power system (EPS) in the coordinated dispatch of an integrated power and heat system (IPHS). To exploit the energy storage capacity of the DHS and support the flexible IPHS operation, it is essential to characterize the flexible operation region (FOR) of the DHS. This paper proposes an FOR characterization method for the DHS, based on a Farkas-cut outer approximation algorithm (FCOAA). The FOR characterization is formulated as a polyhedral projection problem. Within the FCOAA-based framework, the feasible cut generation model is constructed as a bilinear programming problem, which is relaxed by using the normalized multiparametric disaggregation technique (NMDT) and converted into a mixed-integer linear programming (MILP) problem. Numerical simulations on a 6-bus/6-node IPHS are carried out to validate the proposed method, and key factors influencing the flexibility of the DHS are analyzed. Full article

This study introduces an integrated Life Cycle Assessment–Multi-Criteria Decision Analysis–Nash Equilibrium (LCA–MCDA–NE) framework to assess the feasibility of hydrogen energy storage (HES) in Philippine island grids. It starts with a cradle-to-gate LCA of hydrogen production across various electricity mix scenarios, from diesel-dominated Small Power Utilities Group (SPUG) systems to high-renewable configurations, quantifying greenhouse gas emissions. These impacts are normalized and integrated into an MCDA framework that considers four stakeholder perspectives: Regulatory (PRF), Developer (DF), Scientific (SF), and Local Social (LSF). Attribute utilities for Maintainability, Energy Efficiency, Geographic–Climatic Suitability, and Regulatory Compliance inform a 2 × 2 strategic game where net utility gain (Δ) and switching costs (C₁, C₂) influence adoption behavior. The findings indicate that the baseline Nash Equilibrium favors non-adoption due to limited utility gains and high switching barriers. However, enhancements in Maintainability and reduced costs can shift this equilibrium toward adoption. The LCA results show that meaningful decarbonization occurs only when low-carbon generation exceeds 60% of the electricity mix. This integrated framework highlights that successful HES deployment in remote grids relies on stakeholder coordination, reduced risks, and access to low-carbon electricity, offering a replicable model for emerging economies. Full article

This study evaluated low-cost food waste anaerobic digestion (FWAD) designed for African urban informal settlements, where electricity and process control are limited. Eight small-scale reactors were operated under varying mixing, pH control, and temperature conditions to assess the feasibility of stable operation with minimal input. Results showed no significant difference in methane yield between continuously mixed and minimally mixed (48-hourly) systems, nor between reactors with continuous pH dosing and those adjusted every 48 h (ANOVA p > 0.05 for all comparisons). The highest mean methane yield, 0.267 L CH₄ g VS⁻¹, was achieved by the minimally mixed reactor with 48-hourly pH control at 30 °C, while the controlled reactor at 37 °C produced a comparable 0.247 L CH₄ g VS⁻¹. Total methane production was similar at both temperatures, although gas generation was faster during the first 24 h at 37 °C. Compared to gas recovery achieved by extended batch operation following semi-continuous feeding, 58–73% of total methane was produced within the 48-h cycle, suggesting conversion could increase by 30–40% with extended liquid retention. Microbial analyses showed compositional differences but consistent performance, indicating functional redundancy within the microbial consortia. These results confirm the capacity of FWAD for stable, efficient biogas production without continuous energy input. Full article

Renewable energy sources account for approximately one-quarter of the total electric power generating capacity in the United States. These sources increase system complexity, with potential negative impacts caused by their inherent variability. A microgrid, a decentralized local grid, offers an excellent solution for integrating these sources into the system’s generation mix in a cost-effective and efficient manner. This paper presents a comprehensive fault tree analysis for the reliability assessment of microgrids, ensuring their safe operation. In this work, fault tree analysis of a microgrid in grid-tied mode with solar, wind, and battery energy storage systems is performed, and the results are reported. The analyses and calculations are performed using the Relyence software suite. The fault tree analysis was performed using various calculation methods, including exact (conventional fault tree analysis), simulation (Monte Carlo simulation), cut-set summation, Esary–Proschan, and cross-product. Once these analyses were completed, the results were compared with the ‘exact’ method as the base case. Critical risk measures, such as unavailability, conditional failure intensity, failure frequency, mean unavailability, number of failures, and minimal cut-sets, were documented and compared. Importance measures, such as marginal or Birnbaum, criticality, diagnostic, risk achievement, and risk reduction worth, were also computed and tabulated. Details of all cut-sets and the probability of failure are presented. The calculated importance measures would help microgrid operators focus on events that yield the greatest system improvements and maintain an acceptable range of risk levels to ensure safe operation and improved system reliability. Full article

The widespread adoption of Electric Vehicles (EVs) is critically dependent on the deployment of efficient charging infrastructure. However, existing facility location models typically treat charging duration as an exogenous parameter, thereby neglecting the traveler’s autonomy to make trade-offs between service time and energy needs based on their Value of Time (VoT). This study addresses this theoretical gap by developing a heterogeneous network design model that endogenizes both charging mode selection and continuous charging duration decisions. A bi-objective optimization framework is formulated to minimize the weighted sum of infrastructure capital expenditure and users’ generalized travel costs. To ensure computational tractability for large-scale networks, an exact linearization technique is applied to reformulate the resulting Mixed-Integer Non-Linear Program (MINLP) into a Mixed-Integer Linear Program (MILP). Application of the model to the Hubei Province highway network reveals a convex Pareto frontier between investment and service quality, providing quantifiable guidance for budget allocation. Empirical results demonstrate that the marginal return on infrastructure investment diminishes rapidly. Specifically, a marginal budget increase from the minimum baseline yields disproportionately large reductions in system-wide dwell time, whereas capital allocation beyond a saturation point yields diminishing returns, offering negligible service gains. Furthermore, sensitivity analysis indicates an asymmetry in technological impact: while extended EV battery ranges significantly reduce user dwell times, they do not proportionally lower the capital required for the foundational infrastructure backbone. These findings suggest that robust infrastructure planning must be decoupled from anticipations of future battery breakthroughs and instead focus on optimizing facility heterogeneity to match evolving traffic flow densities. Full article

It is crucial to understand the market structure and the formation of the electricity mix in the context of the increasingly widespread and global introduction of renewable energy sources as primary energy sources. Due to the cyclical nature of energy production from RES, a long-term plan for seasonal storage is mandatory for smooth and effective energy transition. The stability of the energy system remains a key requirement, especially due to the dynamic changes in the generation, consumption, and pricing of energy resources. This article aims to present the concept that, in the absence of a properly structured and balanced market, thermal power plants prove to be flexible and reliable power sources that can be quickly integrated into the energy system at critical moments when maintaining the grid balance is difficult (such as during peak hours of solar generation). Full article

This study critically examines the sectoral dynamics of renewable energy (RE) adoption across the EU-27 from 1990 to 2023, addressing the persistent gap between electricity generation and end-use sectors. Utilizing Eurostat energy balance data, the research employs a robust multi-methodological framework. We apply the Logarithmic Mean Divisia Index (LMDI) decomposition to isolate driving factors, and the Self-Organizing Maps (SOM) of Kohonen to cluster countries with similar transition structures. Furthermore, the Method of Moments Quantile Regression (MMQR) is used to estimate heterogeneous drivers across the distribution of RE shares. The empirical findings reveal a sharp dichotomy: while the share of renewables in the electricity generation mix (RES-E-Renewable Energy Share in Electricity) reached approximately 53.8% in leading member states, the aggregated share in the transport sector (RES-T) remains significantly lower at 9.1%. This distinction highlights that while power generation is decarbonizing rapidly, end-use electrification lags behind. The MMQR analysis indicates that economic growth drives renewable adoption more effectively in countries with already high renewable shares (upper quantiles) due to established market mechanisms and grid flexibility. Conversely, in lower-quantile countries, regulatory stability and direct infrastructure investment prove more critical than market-based incentives, highlighting the need for differentiated policy instruments. While EU policy milestones (RED I–III-) align with progress in power generation, they have failed to accelerate transitions in lagging sectors. This study concludes that achieving climate neutrality requires moving beyond aggregate targets to implement distinct, sector-specific interventions that address the unique structural barriers in transport and thermal applications. Full article

The construction sector generates a substantial proportion of Australia’s total solid waste, underscoring the urgent need for sustainable and circular resource management approaches to mitigate environmental impacts. This study evaluates the environmental performance and circularity potential of construction and demolition waste (C&DW) management across five Australian states. Three representative building cases were modelled using both national-average and state-specific recycling rates and electricity generation mixes. A Life Cycle Assessment (LCA) was conducted to compare two end-of-life pathways: landfill and recycling. Key parameters, including transport distance and substitution ratio, were also examined to assess their influence on carbon outcomes. The results show that regional variations in electricity generation mix and recycling rate have a strong influence on the total Global Warming Potential of C&DW management. States with cleaner electricity grids and higher recycling rates, such as South Australia, exhibited notably lower recycling-related emissions than those relying on fossil-fuel-based power. The findings highlight the importance of incorporating regional characteristics into sustainability assessments of C&DW management and provide practical insights to support Australia’s transition toward a circular and low-carbon construction industry. Full article

To address the voltage instability in distribution networks with a high penetration of renewable energy, a multi-objective optimal scheduling method is proposed based on an enhanced static voltage stability margin ratio (SVSMR). The SVSMR_d index suitable for complex distribution networks is constructed by analytical derivation and equivalent impedance correction, and the distributed access characteristics of distributed power generation are considered. Based on the simulation analysis of the PS_CAD simulation platform, the effectiveness and engineering applicability of the SVSMR_d index are compared in the multi-energy station distribution network scenario, and the calculation results of SVSMRF and SDSCR are used to verify it. A multi-objective mixed-integer optimisation model is constructed, with the objective function encompassing electricity purchase cost, network loss cost, and energy storage revenue, and the lowest value of the SVSMR_d index of various new energy nodes is used as the optimisation object to carry out stability targets. Based on the epsilon constraint method, a Pareto frontier solution set is generated through example analysis, which has non-dominant characteristics. The results of the example analysis show that the proposed method can effectively reduce the operating cost, ensure the voltage stability margin of the system, and realise the collaborative optimisation of source–network–load–storage resources. This paper provides a new idea and method for the optimal operation of the distribution network, and optimises the distribution network under a high proportion of new energy access in the distribution network. Full article

Phosphorus is an essential resource for numerous industrial applications. However, its uneven global distribution makes Europe heavily dependent on imports. Recovering phosphorus from waste streams is therefore crucial for improving resource security. The FlashPhos project addresses this challenge by developing a process to recover phosphorus from sewage sludge, in which phosphorus-rich slag is produced in a flash reactor and subsequently reduced in a Submerged Arc Furnace (SAF). In this process, approximately 250 kg/h of sewage sludge is converted into slag, which is further processed in the SAF to recover about 8 kg/h of white phosphorus. This work focuses on the development of a computational model of the SAF, with particular emphasis on slag behaviour. Due to the extreme operating conditions, which severely limit experimental access, a numerically efficient three-dimensional CFD model was developed to investigate the internal flow of the three-phase, AC-powered SAF. The model accounts for multiphase interactions, dynamic bubble generation and energy sinks associated with the reduction reaction, and Joule heating. A temperature control loop adjusts electrode currents to reach and maintain a prescribed target temperature. To further reduce computational cost, a novel simulation approach is introduced, achieving a reduction in simulation time of up to 300%. This approach replaces the solution of the electric potential equation with time-averaged Joule-heating values obtained from a preceding simulation. The system requires transient simulation and reaches a pseudo-steady state after approximately 337 s. The results demonstrate effective slag mixing, with gas bubbles significantly enhancing flow velocities compared to natural convection alone, leading to maximum slag velocities of 0.9–1.0 m/s. The temperature field is largely uniform and closely matches the target temperature within ±2 K, indicating efficient mixing and control. A parameter study reveals a strong sensitivity of the flow behaviour to the slag viscosity, while electrode spacing shows no clear influence. Overall, the model provides a robust basis for further development and future coupling with the gas phase. Full article

Water electrolysis using electricity generated from renewable sources is a promising approach for producing green hydrogen. However, this process requires the development of electrocatalysts that are not only highly active and durable but also low-cost. Considerable efforts are being directed toward discovering and optimizing such materials, and this study contributes to the ongoing research in this area. In this work, three novel LaMnO₃ perovskite–graphene oxide hybrids—namely LaMnO₃/GO, Ag-doped LaMnO₃/GO, and Pd-doped LaMnO₃/GO—were synthesized and investigated for their electrocatalytic activity in water electrolysis under strongly alkaline conditions. To the best of our knowledge, these hybrid materials have not been previously reported in the context of electrocatalytic water splitting. Among the electrodes fabricated and tested for the hydrogen evolution reaction (HER), the one based on a catalyst ink containing Pd-doped LaMnO₃/GO mixed with carbon black showed the best performance, achieving a low overpotential of 0.385 V at a current density of −10 mA/cm². It also demonstrated good stability in the alkaline electrolyte and exhibited a Tafel slope of 0.34 V. These findings highlight the potential of the studied materials as effective and previously unreported electrocatalysts for water splitting. Full article

The heat generated by electrical cables during operation dissipates through the duct and surrounding encasement concrete into the adjacent soil. Consequently, the thermal conductivity of the encasement concrete is critical for the overall heat dissipation efficiency and thermal stability of the cable system. To address this, a high-thermal-conductivity concrete was developed by incorporating steel slag powder, graphite powder, and graphite particles. This study systematically investigated the effects of mineral admixture content, graphite powder dosage, and the replacement ratio of conductive aggregates on the thermal conductivity, mechanical properties, and workability of the concrete. Additionally, the economic performance was evaluated against conventional C25 concrete using value engineering methodology. The results demonstrate that the proposed concrete exhibited significantly improved thermal performance compared to ordinary concrete. Notably, with a 10% replacement of aggregates by graphite particles, the 28-day thermal conductivity increased by 106.16% relative to the control mix. Simultaneously, the compressive strength reached 25.1 MPa, ensuring sufficient mechanical integrity. Furthermore, the value coefficient of the developed concrete was 18.31% higher than that of conventional C25 concrete. These findings highlight the material’s potential in power engineering and energy-efficient construction, providing a valuable reference for material design in these fields. Full article

It has become an urgent problem to deal with the uncertain influence caused by the high proportion of new energy connected to the grid and improve the consumption level of new energy in the background of the new power system. Based on the constantly updated predicted information of wind power, photovoltaic power, and load power, a multi-time-scale coordinated scheduling model for a multi-energy complementary power generation system integrated with a high proportion of new energy, including an electricity-to-hydrogen system, is proposed. The complex nonlinear factors in the operation cost of thermal power and pumped storage power generation were converted into a mixed integer linear model for solving the problem. The results show that the participation of the pumped storage units in the power grid dispatching can effectively alleviate the peak regulation and reserve pressure of the thermal power units. The electricity-to-hydrogen system has the advantages of fast power response and a wide adjustment range. Pumped storage plant, together with the electricity-to-hydrogen system, enhances the flexible adjustment ability of the power grid on the power side and the load side, respectively. The coordinated dispatch of the two can take into account the safety and economy of the power grid operation, maintain the power balance of the high-proportion new energy power generation system, and effectively reduce green power abandonment and improve the consumption level of clean energy. Full article

The rapid advancement of energy collection and storage systems (ECSSs) is fundamentally reshaping global energy markets and accelerating the transition toward low-carbon energy systems. This study provides a comprehensive assessment of the economic benefits and systemic effects of advanced ECSS technologies, including photovoltaic-thermal (PV/T) hybrid systems, advanced batteries, hydrogen-based storage, and thermal energy storage (TES). Through a mixed-methods approach combining techno-economic analysis, macroeconomic modeling, and policy review, we evaluate the cost trajectories, performance indicators, and deployment impacts of these technologies across major economies. The paper also introduces a novel economic-mathematical model to quantify the long-term macroeconomic benefits of large-scale ECSS deployment, including GDP growth, job creation, and import substitution effects. Our results indicate significant cost reductions for ECSS by 2050, with battery storage costs projected to fall below USD 50 per kilowatt-hour (kWh) and green hydrogen production reaching as low as USD 1.2 per kilogram. Large-scale ECSS deployment was found to reduce electricity costs by up to 12%, lower fossil fuel imports by up to 25%, and generate substantial GDP growth and job creation, particularly in regions with supportive policy frameworks. Comparative cross-country analysis highlighted regional differences in economic effects, with the European Union, China, and the United States demonstrating the highest economic gains from ECSS adoption. The study also identified key challenges, including high capital costs, material supply risks, and regulatory barriers, emphasizing the need for integrated policies to accelerate ECSS deployment. These findings provide valuable insights for policymakers, industry stakeholders, and researchers aiming to design effective strategies for enhancing energy security, economic resilience, and environmental sustainability through advanced energy storage technologies. Full article

Climate change and increasing greenhouse gas emissions are driving the global transition to clean energy, with solar energy experiencing the fastest growth among renewable sources in 2024. Solar PV for energy generation in Kenya is gaining momentum as the country moves towards achieving 100% clean energy by 2030. As solar PV penetration in the grid grows, it is necessary to evaluate its impact on system costs to inform policy decisions on capacity expansion options in the Least-Cost Power Development Plan (LCPDP). This study investigates the effect of large-scale solar PV expansion on electricity costs using the Open-Source Energy Modelling System (OSeMOSYS), a modular, bottom-up capacity expansion model. Four scenarios were developed to assess different levels of solar PV penetration: business-as-usual (BAU), moderate-solar-PV expansion (MSPV), high-solar-PV expansion (HSPV), and very-high-solar-PV expansion (VHSPV). The results indicate that, while overall solar PV expansion significantly contributes to decarbonising Kenya’s electricity mix by displacing fossil-based generation, it also increases annual investment obligations and, consequently, total system costs. The system-levelised cost of electricity (LCOE) is shown to rise by 0.2%, 5.7%, and 14.0% under MSPV, HSPV, and VHSPV, respectively, compared to BAU. Analysing the various cost components against sustainability indicators reveals that the least-cost scenario is BAU while the most favourable scenario based on sustainability indicators is VHSPV, which performs best across technical, environmental, and institutional dimensions but less favourably on economic and social aspects, thereby highlighting a trade-off between sustainability and cost minimisation, at least in the short term. Full article