Search Results (3,574)

Against the backdrop of global decarbonization in energy-intensive industries, the primary aluminum sector has become a critical field for deep industrial decarbonization due to its high electricity consumption, large share of indirect carbon emissions, and complex mitigation pathways. This challenge is particularly salient in regions endowed with abundant renewable resources while hosting concentrated industrial electricity demand, where coordinated mitigation across technological upgrading and energy system transformation has broad practical relevance. Using Xining in Qinghai Province, China, a renewable-rich region, as an illustrative case, this study systematically examines the major carbon mitigation pathways in the primary aluminum industry, including mining, alumina production, electrolytic cell retrofitting, power system coordination, and carbon capture, utilization, and storage (CCUS). A multi-objective optimization model is developed to minimize marginal abatement costs (MAC) while maximizing technological application performance, and the sequential unconstrained minimization technique (SUMT) is employed to optimize mitigation pathways under short-, medium-, and long-term scenarios. The results show that, in the short term (before 2030), emission reduction mainly relies on improvements in electrolysis efficiency, leading to a mitigation pattern dominated by reductions in electricity consumption per unit of output. In the medium term (before 2035), the pathway shifts from isolated process optimization to a coordinated strategy combining process upgrading with power decarbonization, exhibiting a structural mitigation pattern driven by synergy between the production side and the energy side. In the long term (before 2060), the pathway evolves toward a stage dominated by energy system reconfiguration and carbon utilization. With high shares of renewable electricity integration, DC power supply configurations, and energy storage support, primary aluminum production is expected to achieve deep decarbonization on the power side. This study provides a transferable analytical framework and policy-relevant insights for the low-carbon transition of energy-intensive industries in renewable-rich regions. Full article

The global transition toward renewable energy has intensified interest in dispatchable low-carbon sources that can support reliability-critical infrastructure in smart grid systems. Data centers represent one of the fastest-growing electricity loads globally, yet their compatibility with biomass-based energy systems as a dispatchable renewable source within smart grid architectures remains poorly understood. This study presented a comprehensive review of biomass power generation, data center energy management, and smart grid integration, drawing on a corpus of 347 peer-reviewed sources. A staged analytical design separated demand characterization from supply evaluation, ensuring that data center energy requirements emerged independently of supply-side assumptions. Using Latent Dirichlet Allocation topic modeling validated with BERTopic and VOSviewer network analysis, the study identified four distinct thematic clusters and found no single topic spanning data center reliability requirements, biomass supply dynamics, and smart grid integration simultaneously, a pattern that points to an underexplored cross-domain space in the literature. A demand–supply–grid alignment framework was introduced to illustrate compatibility conditions across temporal resolution, reliability requirements, and grid management dimensions. The alignment framework and illustrative simulation developed here are offered as analytical starting points to guide future engineering and empirical investigation rather than as demonstrations of operational readiness. An illustrative application demonstrated that biomass feedstock logistics constraints create persistent availability gaps at data center operational timescales, suggesting that supply chain resilience and grid-mediated buffering are likely necessary conditions for viable integration, a proposition that warrants empirical validation through full-scale engineering studies. The findings indicate that integration constraints reflect temporal and operational misalignment rather than technological infeasibility, providing a new analytical perspective for evaluating renewable energy integration in reliability-critical digital Full article

This study examines the relationship between governance quality and carbon intensity in Saudi Arabia over the period 2002–2024, with particular attention to the role of structural reform and institutional change. Using an autoregressive distributed lag (ARDL) framework, the analysis distinguishes between long-run equilibrium relationships and short-run adjustment dynamics in a resource-dependent economy undergoing economic transition. The long-run results indicate that capital formation significantly increases carbon intensity, suggesting that economic expansion and investment activities remain closely tied to carbon-intensive production structures and fossil-based industrial development. Renewable energy exhibits a modest mitigating effect, implying that recent progress in energy diversification has contributed to emissions efficiency, although its overall impact remains limited relative to the scale of hydrocarbon dependence. Governance does not display a robust independent long-run effect on carbon intensity. However, the interaction between governance and the post-2016 reform period is associated with lower carbon intensity, indicating that institutional quality becomes more effective when supported by broader structural transformation and policy reform initiatives. Short-run dynamics further suggest that improvements in governance may initially coincide with higher emissions intensity during transitional phases of economic adjustment and infrastructure expansion. The findings highlight that governance influences environmental performance not in isolation, but through its interaction with structural diversification, energy transition, and reform-oriented institutional change in a resource-dependent economy. Full article

The decarbonisation of the building sector represents a key challenge for the European energy transition, particularly in the heating segment, which is still largely dependent on fossil fuels. In this context, data centres (DCs) offer a promising opportunity as local sources of recoverable waste heat. This study investigates the use of data centre waste heat for building heating through a comparative annual energy analysis applied to two building typologies in a Mediterranean climate (Italy): a residential building and a school. Three scenarios are considered: non-integrated scenario S0 (data centre with its own cooling system and buildings with gas-fired boilers), non-integrated scenario S1 (data centre with its own cooling system and buildings with air-to-water heat pumps), and integrated scenario S2 (data centre cooling system coupled with the buildings through waste heat recovery and heat pump technology). A theoretical 300 kW data centre was considered as the waste heat source. The integrated scenario significantly improves system performance. In the residential case, the seasonal COP increases from 2.15 to 4.50, reducing electricity consumption from 289.5 MWh to 128.9 MWh. In the school case, the COP increases from 2.51 to 8.00, with electricity consumption decreasing from 161.3 MWh to 49.1 MWh. These improvements lead to reductions in non-renewable primary energy demand of up to 63% and 79% for the residential and school buildings, respectively, compared to the baseline scenario. The results demonstrate that data centres can act as decentralised thermal sources, supporting the transition towards low-carbon and Nearly Zero-Energy Buildings. Full article

To address the issues of high energy consumption, high carbon emissions, and the waste of associated energy (AE) in coal mine production, which severely hinder global sustainable development goals, this paper proposes a novel low-carbon economic collaborative optimal scheduling model for a coal mine integrated energy system (CMIES) oriented towards sustainable energy transitions. First, a refined utilization model for AE encompassing coal mine gas, ventilation air methane (VAM), and mine groundwater (GW) is constructed, and a tiered carbon emission trading mechanism (TCET) is introduced to constrain carbon emissions and promote ecological sustainability. Second, a concentrated solar power (CSP) plant is integrated to break the rigid “power determined by heat” constraint of a traditional combined heat and power (CHP) unit, thereby enhancing the system’s scheduling flexibility and renewable energy integration. Meanwhile, abandoned mines are retrofitted into solvent storage tanks to construct an integrated flexible carbon capture system (IFCCS), achieving sustainable reuse of mining wastelands. Finally, to tackle the multi-source, heterogeneous uncertainties on both the source and load sides, a hybrid risk assessment method combining information gap decision theory (IGDT) and conditional value at risk (CVaR) is proposed. Case study results demonstrate that, compared to traditional energy supply modes, the proposed model reduces carbon emissions and total costs in the mining area by 66.04% and 15.97%, respectively. This significantly improves resource utilization efficiency and ecological benefits, providing a highly viable pathway for the sustainable development and clean transition of coal mine operations. Furthermore, the proposed hybrid assessment method can effectively assist decision-makers in achieving a refined trade-off between operating costs and system robustness under varying risk preferences. Full article

South Africa remains one of the world’s most coal-dependent electricity systems, with coal accounting for 81.57% of generation in 2023. Despite policy interventions to diversify the energy mix, structural change is slow to emerge. This study provides the first integrated, empirically calibrated forecast of South Africa’s coal-to-clean-energy transition using a unified modelling architecture that combines structural break analysis, Bayesian estimation, and an enhanced Monte Carlo simulation with dynamic volatility (10,000 stochastic pathways). The findings confirm a permanent structural break in 2011 that coincided with the implementation of REIPPPP, following which coal began a statistically significant and sustained decline of approximately 0.7–0.75% points per year. The simulation produced a full probability distribution for the transition year (2053) when coal share falls below 50%. This demonstrated that long-term uncertainty rises faster than linearly and that, under current conditions, deep decarbonisation milestones are unattainable before mid-century. Policy scenario experiments also demonstrated that accelerating the annual decline rate necessitates coordinated, synergistic policy portfolios rather than isolated interventions. These findings provide a transparent, uncertainty-explicit forecast of South Africa’s transition trajectory, as well as a decision-relevant evidence base for planning, regulation, and equitable transition implementation. Full article

The assessment of humanity’s ecological footprint has become increasingly critical in contemporary discourse due to growing environmental challenges. This study examines the economic evaluation of the ecological footprint with a particular focus on forest ecosystem services and food productivity. Using harmonized secondary data from FAOSTAT, EUROSTAT, the World Bank, and IPBES, the analysis covers selected developed and emerging economies, including the European Union, the United States, China, Brazil, and other representative countries. This study investigates the macroeconomic implications of natural capital degradation by applying a panel data econometric model to European Union countries over the period 2010–2023. Moving beyond descriptive approaches, the research formulates and tests three hypotheses linking biodiversity, environmental pressure, and green transition variables to economic performance. Using harmonized data from Eurostat and Statista, the study employs a fixed-effects regression framework to estimate the impact of biodiversity indicators, greenhouse gas emissions, renewable energy share, and environmental protection expenditures on GDP per capita. The results demonstrate that biodiversity preservation and resource efficiency are positively associated with economic performance, while environmental degradation—proxied by greenhouse gas emissions—exerts a statistically significant negative effect. Additionally, the findings confirm that investments in renewable energy and environmental protection contribute to long-term economic stability. By providing a transparent data structure, explicit variable operationalization, and reproducible econometric specification, the study offers an original empirical contribution to ecological economics and addresses the limitations of prior literature that relied primarily on descriptive synthesis. Full article

The escalating global demand for renewable energy has positioned solar photovoltaics (PV) as a critical technology for achieving net-zero emissions. However, PV efficiency is strictly limited by thermal degradation, where elevated operating temperatures significantly reduce power output and accelerate material aging. This review systematically evaluates the integration of advanced phase change materials (PCMs) as a passive thermal management solution. We analyze the transition from material-level innovations—including nano-enhanced PCMs, 3D conductive frameworks, and shape-stabilization—to system-level hybrid architectures such as liquid—PCM, heat pipe-fin, and thermoelectric generator (TEG) integrations. Synthesis of recent empirical data (2024–2026) demonstrates that optimized PCM composites can achieve PV temperature reductions of up to 32 °C and electrical efficiency enhancements exceeding 19%. Furthermore, techno-economic assessments reveal that these systems can reduce the levelized cost of energy (LCOE) by 5–15% and achieve energy payback times as short as 1.5 years. Finally, this paper identifies critical research gaps in long-term outdoor durability, AI-driven predictive modeling, and sustainable bio-based encapsulation, providing a strategic roadmap for the commercialization of next-generation solar thermal management systems. Full article

This study evaluates the demand dynamics of the 20 leading strategic destinations in the global tourism market by modeling the interactions between traditional macroeconomic determinants and climate-linked environmental sustainability indicators. The primary objective is to assess the predictive capacity of physical and structural environmental factors—including water stress, air pollution, renewable energy adoption, and sanitation infrastructure—relative to established economic metrics like GDP per capita. Employing non-parametric predictive frameworks on a panel dataset of 400 observations (2000–2019), the empirical analysis suggests that tree-based ensemble models, notably Extra Trees (90.54%) and CatBoost (84.75%), yield higher predictive accuracy than conventional multiple linear regression (73.97%). Interpretations derived from cooperative game theory via SHAP analysis suggest that environmental determinants may serve as important predictive drivers of tourism demand. Specifically, variables such as water stress (28.20%), renewable energy share (27.12%), and sanitation infrastructure carry substantial predictive weight, whereas the benchmark macroeconomic indicator (2.30%) exerts a relatively marginal influence within the model architecture. These findings imply that environmental sustainability metrics may capture international tourism demand variations more effectively than traditional economic variables. The results suggest that acute environmental vulnerabilities may be associated with reduced tourism inflows, potentially reflecting limitations in destination sustainability thresholds. Broadly, the evidence is consistent with the notion that contemporary global tourism demand may be increasingly interdependent with ecological resilience and low-carbon transition policies. It is important to note that the findings reported here reflect predictive associations derived from machine learning models and should not be interpreted as evidence of causal relationships. Full article

The mitigation of anthropogenic climate change caused by fossil fuel combustion is a critical global challenge that necessitates a transition to renewable energy systems. Bioethanol represents a major renewable fuel, but first-generation production relies on edible feedstocks, which raises concerns regarding food security. Consequently, research is shifting toward second-generation bioethanol produced from abundant non-edible lignocellulosic biomass sources. This review comprehensively examines the potential of Candida krusei (synonyms: Pichia kudriavzevii, Issatchenkia orientalis) to serve as an alternative biocatalyst for second-generation bioethanol production. Compared with the first-generation bioethanol-producing yeast Saccharomyces cerevisiae, C. krusei exhibits superior physiological traits, such as thermo, acid, and inhibitor tolerances, enabling the utilization of several lignocellulosic feedstocks. This review summarizes the taxonomic and physiological characteristics of C. krusei, describes case studies on bioethanol production, and discusses strategies for reducing production costs. Furthermore, the technical and biosafety challenges associated with the industrial deployment of C. krusei are critically examined, including xylose metabolism limitations, scale-up constraints, and the management of its opportunistic pathogenic nature. A life cycle assessment perspective suggests that the unique physiological properties of C. krusei contribute to reducing greenhouse gas emissions and energy consumption throughout the entire production process, from pretreatment to downstream ethanol recovery. Full article

The global transition to a diversified renewable energy portfolio requires reliable assessment of predictable marine energy resources. This study develops a high-resolution, three-dimensional Regional Ocean Modeling System (ROMS) to quantitatively evaluate theoretical tidal current energy resources in the Bohai and Yellow Seas. The model, configured with fine-scale bathymetry and forced by harmonic tidal constituents, is validated against tide gauge and Acoustic Doppler Current Profiler (ADCP) observations. Multi-year simulations reveal pronounced spatial heterogeneity in tidal current energy distribution. Rather than treating resource assessment as a single power density mapping exercise, this study combines annual mean theoretical power density, peak theoretical power density, threshold-dependent effective flow duration, effective water depth, current directionality, and vertical velocity structure to characterize resource intensity, temporal persistence, and vertical deployability. The results identify distinct hydrodynamic resource regimes. High theoretical resource intensity is concentrated west of Laotieshan Cape and east of Chengshantou, where cumulative annual effective flow duration exceeds 5000 h and short-term instantaneous theoretical power density can reach approximately 10 kW/m² and 8 kW/m², respectively. These peak values indicate strong local tidal acceleration but should be interpreted together with annual mean power density and effective flow duration. In contrast, the northern Jiangsu coastal area exhibits lower peak intensity but relatively persistent moderate flow conditions. The results provide a hydrodynamic resource basis for preliminary site screening and for guiding subsequent turbine-performance, wake/array, environmental, grid accessibility, and techno-economic assessments. Full article

In the global transition toward low-carbon power systems with high renewable energy penetration, pumped storage has emerged as a strategic cornerstone for modern power grids. However, the collaborative planning of pumped storage and backbone-grids faces critical challenges, including the lack of explicit quantification of the resilience value of pumped storage and the coarse treatment of N-1 connectivity constraints. This paper proposes a bi-objective resilient backbone-grid planning approach that integrates the pumped-storage hub effect, aiming to minimize total life-cycle costs and the system resilience mismatch index. The proposed framework incorporates network connectivity, N-1 connectivity (edge connectivity ≥ 2), and dual-scenario power flow security as rigid constraints. Furthermore, a three-stage constrained evolutionary algorithm TER-NSGA-II is developed. During the N-1 connectivity reinforcement phase, the max-flow min-cut theorem is employed to achieve precise validation and guidance for edge-connectivity enhancement. Case studies on the IEEE 118-bus system, together with extended validation on the IEEE 300-bus system, show that the proposed method can explicitly quantify the resilience value of pumped storage, obtain Pareto solutions that balance economy and resilience under strict edge-connectivity constraints, and demonstrate competitive overall performance in terms of solution-set quality, feasible-domain search stability, and scalability compared with NSGA-II and the more recent NSGA-III/NG benchmark. Full article

Digital twins (DTs) in the energy sector are operational-data-driven models of assets, installations, and networks. Their value grows alongside renewable expansion, electronic communications, and stricter resilience requirements for critical infrastructure. This study evaluates DT applications in Poland’s energy transition, identifying regulatory and cybersecurity determinants required for safe, scalable use. The methodology combines an international literature review, regulatory assessment, and qualitative desk research focusing on DT projects across four Polish energy groups: Enea, Energa, PGE, and Tauron. Each case is assessed using a DT maturity and governance framework covering scope, data coupling, decision support, and security posture. The study identifies four primary deployment types: (1) operational network twins for distribution system operators leveraging SCADA/ADMS, GIS, and state estimation; (2) AI-driven asset performance twins for wind turbines and CHP plants; (3) flexibility twins for hydropower system services; and (4) immersive training twins for the offshore wind sector. Main constraints include data quality, interoperability, fragmented data access regulations, and expanded cyber-attack surfaces from OT/IT convergence. DTs aid spatial planning, mitigating location and land use conflicts. Recommendations emphasize harmonized data governance, cybersecurity-by-design, special determinants, and the creation of regulatory sandboxes to support DT implementation within critical energy infrastructure. Full article

This study presents a field-validated, scenario-based two-layer dispatch framework for sustainable rural electrification, demonstrated at the Khlong Ruea hybrid microgrid (50 kW micro-hydro, 20 kWp PV, 48 kWh LiFePO₄ BESS, 48 kW diesel) in Chumphon Province, southern Thailand. The framework combines an offline mixed-integer linear program (MILP) with scenario-based uncertainty handling (k-medoid clustering, N = 8; CVaR penalty at α = 0.9) and an operator-assisted execution layer implementing source transitions via manual changeover switches. A Fluke 435 IEC 61000-4-30 Class-A field campaign with stationary block-bootstrap inference (B = 2000 resamples, 10 min blocks) documented substantial power quality improvements under BESS supply: the three-phase average THD-V reduced from 5.4% to 2.9% with 95% confidence intervals that do not overlap between the two supply modes; the THD-I dropped from 55.8% to 4.9% (Phase A; 91.2% reduction; three-phase average 64.0% → 7.8%); the voltage unbalance fell from 0.86% to 0.03%; and the displacement power factor improved from 0.92 to 0.95. IEEE Std 1459-2010 decomposition reveals that 93% of the non-fundamental apparent power under diesel supply is attributable to current-distortion volt-amperes (Dᵚ = 4737 VA vs. 283 VA under BESS). A composite power quality index confirms that diesel operation fails the IEEE 519-2022 current-distortion limits while BESS supply satisfies all EN 50160 and IEEE 519-2022 thresholds (PQI: 0.75 vs. 3.89). A 365-day closed-loop simulation confirmed an 18.4% reduction in annual operating cost and a 27.6% reduction in diesel runtime relative to a rule-based baseline, while maintaining LPSP at or below 0.53%. Techno-economic projection from field-verified HOMER inputs reduced the levelized cost of electricity from approximately 0.69 USD/kWh (diesel-only) to 0.36 USD/kWh for the proposed PV + BESS + Hydro + Diesel configuration, which retains diesel as a low-utilization backup at a near-100% renewable energy share. The same configuration delivered a 47.9% net present cost advantage over diesel-only operation and a 12.8 t (82%) annual CO₂ reduction. Manual source-transfer interruptions of 1–3 min are fully characterized, and a cost-estimated ATS + SCADA upgrade roadmap is defined. Full article

Against the backdrop of global green and low-carbon energy structural transition, renewable energy represented by photovoltaic power has emerged as a critical strategy for safeguarding energy security and mitigating climate change. As typical energy-intensive infrastructures, wastewater treatment plants (WWTPs) suffer from excessive energy consumption and substantial carbon emissions. In this study, a distributed photovoltaic power generation system is deployed at WWTPs to alleviate on-site power demand, and its economic and environmental benefits are quantitatively analyzed via PVsyst software simulation. The simulation results indicate that the overall system efficiency reaches 83.3%, with an annual average power generation capacity of 825,500 kW·h. Annually, the proposed system can save 275.17 tons of standard coal, and correspondingly reduce carbon dioxide emissions by 687.92 tons, sulfur dioxide emissions by 20.64 tons and nitrogen oxide emissions by 10.32 tons, thereby realizing synergistic enhancement of economic and environmental performances. This work offers a feasible engineering reference for promoting the modernized transformation of WWTPs toward energy self-sufficiency and low-carbon operational modes. Full article