Search Results (478)

High wind-power penetration increases balancing requirements in integrated energy systems (IESs), while solvent-storage-assisted carbon capture power plants (CCPPs) and electric vehicle (EV) aggregators provide complementary flexibility at different timescales. This paper proposes an electric–carbon dual time-shift coordinated dispatch approach coupling carbon-energy shifting with vehicle-to-grid (V2G) electrical-energy shifting. First, a reduced-order model represents the dominant thermal inertia and short-term response of solvent regeneration. Second, EV availability uncertainty is characterized by Monte Carlo sampling, with quantile-based power and mobility-energy envelopes incorporated into aggregate SOC and mobility constraints together with a throughput-based battery-degradation cost. Finally, a 15-min mixed-integer linear programming model integrating power-to-gas, hydrogen-blended combined heat and power, thermal storage, and tiered carbon trading is solved using CPLEX. Compared with the baseline, the proposed coordinated dispatch strategy reduces operating cost from USD 77.19 × 10⁴ to 58.65 × 10⁴, net carbon emissions from 5841.71 to 2742.46 tCO₂, and the wind-curtailment rate from 42.98% to 1.15%. Specifically, relative to the same system without EV–V2G coordination, incorporating EV–V2G further reduces operating cost and net carbon emissions by 0.93% and 3.93%, respectively, while lowering the wind-curtailment rate from 4.23% to 1.15%, corresponding to a 72.8% relative reduction. Frequency-band analysis shows that the CCPP and electrolyzer provide the two largest contributions to low-frequency balancing, at 42.85% and 30.02%, respectively, whereas EV–V2G and CHP provide the two largest contributions to higher-frequency balancing, at 45.37% and 23.71%, respectively. The main limitations are the reduced-order regenerator model, fleet-level EV aggregation without distribution-network constraints, and fixed equipment capacities. Full article

Power-to-Methane (PtM) offers a promising route for storing surplus renewable electricity by converting H₂ and CO₂ into CH₄. However, the performance and optimization of CO₂ biomethanation under low organic concentrations are unexplored—a scenario common in areas with abundant curtailed wind/solar power but limited organic waste. To address this gap, this study systematically optimized three key process parameters in a continuous stirred-tank reactor (CSTR). Increasing agitation intensity from 80 to 160 rpm raised the volumetric methane production rate (VMP) by 13.8% and the gas–liquid mass transfer coefficients ($k_{l}a$) by 53.8%, achieving a peak CH₄ content of 94%. A VMP of 1.07 L CH₄·L⁻¹·d⁻¹ was obtained when the gas recirculation rate was raised to 1200 mL·min⁻¹. The optimal H₂/CO₂ ratio was 4:1, maintaining stable pH (7.31–7.51) and low volatile fatty acids (VFAs). Microbial analysis revealed that enhanced mass transfer was strongly associated with the enrichment of hydrogenotrophic methanogens (especially Methanobacterium, up to 74.8% relative abundance) and a reduced relative abundance of acetoclastic methanogens (Methanosaeta < 2%), and hydrolytic/acidogenic bacteria (e.g., Firmicutes, Bacteroidota, Cloacimonadota), suggesting a potential trade-off between the dominance of the hydrogenotrophic pathway and overall microbial functional diversity. Overall, this study demonstrates that a CSTR can achieve efficient CO₂ biomethanation under low organic concentrations through integrated optimization of agitation, gas recirculation, and feed ratio. The results provide critical data support for PtM deployment in regions with high renewable energy surplus but limited organic waste, enabling grid-to-gas energy storage, industrial CO₂ utilization, and carbon emission reduction. Full article

Park-level integrated energy systems with high shares of wind and photovoltaic power face pronounced seasonal source–load mismatches, renewable energy curtailment, and low-carbon operation challenges. This paper proposes a capacity planning method considering seasonal salt-cavern hydrogen storage and adaptive representative days. An electricity–heat–cooling–hydrogen coupled system is established by integrating renewable generation, conventional conversion units, short-term storage, electrolyzers, fuel cells, and salt-cavern hydrogen storage, together with waste-heat recovery and tiered carbon trading. To represent interseasonal hydrogen transfer under representative-day modeling, a seasonal hydrogen inventory formulation based on weighted net hydrogen changes is developed, considering cushion gas, storage bounds, injection and withdrawal efficiencies, and flow-rate limits. A season-specific adaptive K-medoids method based on CRITIC evaluation is further proposed to determine the number of representative days, while zero-weight extreme days are introduced to verify capacity feasibility under boundary conditions. The optimization objective is to minimize annualized total cost. Case studies show that removing seasonal hydrogen storage increases total system cost by 23.63%, raises wind and photovoltaic curtailment from 1.81% to 13.09%, and increases carbon emissions by 13.74%. The proposed method improves economic, renewable-energy-utilization, and low-carbon performance. Full article

Smart energy meters are widely deployed electronic terminals. Under large-scale deployment and long-term operation, their life cycle carbon emissions can become significant. Based on the life cycle assessment (LCA) framework, this review critically examines the life cycle carbon-emission characteristics and mitigation pathways of smart energy meters. Particular attention is given to system boundaries, data requirements, stage-specific hotspots, and cross-stage trade-offs. Representative studies indicate that use-stage electricity can account for approximately 70.1–88.5% oflife cyclee GWP. However, the dominant stage varies with electricity mix, service life, product configuration, and assessment boundary. Accordingly, mitigation priorities should include reducing operating power and communication demand, lowering the embodied carbon of printed circuit boards (PCBs), printed circuit board assemblies (PCBAs), and key electronic components, extending reliable service life, and improving end-of-life recovery. This review also distinguishes direct meter-level emissions from indirect system-level benefits. Key future needs include standardized accounting rules, component-level carbon data, anlife cyclele-based mitigation assessment. Full article

Magnesium oxychloride (MOA) adhesive plywood represents a novel inorganic matrix panel technology that eliminates organic volatile compounds from the adhesive system and avoids high-temperature hot pressing, potentially offering significant carbon footprint advantages. This study presents a comparative life cycle carbon footprint assessment of conventional urea–formaldehyde (UF) plywood and MOA plywood manufactured in China, using 1 m³ of a finished panel as the functional unit under a cradle-to-grave system boundary, comprising the production stage (Modules A1–A3)—explicitly including forestry operations (silviculture, felling, extraction/forwarding, loading and log haulage) and veneer manufacture within Module A1, now reported as a disaggregated inventory and delimited in a system boundary diagram—and the end-of-life stage (Modules C2–C4), evaluated across three end-of-life (EOL) scenarios: incineration, landfill, and mechanical recycling. Foreground data (process energy, adhesive formulation, transport distances) are metered/primary data collected over a full production year at a single large-scale plywood plant in Suqian, Jiangsu; background data are from ecoinvent v3.9.1 (cut-off), characterised with IPCC AR6 GWP100. Results indicate that MOA plywood generates approximately 253 kg CO₂-e/m³ at the production stage (A1–A3), compared with 301 kg CO₂-e/m³ for UF plywood, a reduction of 15.8% (47.5 kg CO₂-e/m³). Contribution analysis attributes virtually the entire gap to process energy (steam 65.7%, electricity 34.3%), while adhesive raw materials and inbound transport cancel to within rounding, demonstrating that the advantage is a process energy rather than a green chemistry phenomenon. A parameter-specific one-at-a-time analysis and a 200,000-run Monte Carlo simulation with triangular distributions show no reversal of the UF–MOA ranking in any of the 200,000 realisations within the adopted uncertainty ranges, with an approximately 56 kg CO₂-e/m³ median advantage (5th–95th percentile of about 31–85). Under EOL incineration, MOA plywood retains a substantial advantage even after the newly quantified burden of flue gas HCl neutralisation (13.3 kg CO₂-e/m³) and inorganic residue management (0.9 kg CO₂-e/m³) arising from the chloride content of the Sorel cement binder are charged to the MOA system. Under landfill, both products behave similarly, as wood carbon dynamics dominate. A break-even analysis shows that the service life of MOA plywood would have to fall below 25.3 years (against a 30-year reference) for its cradle-to-gate advantage to be erased. These findings clarify the lifecycle trade-offs of inorganic adhesive plywood and provide actionable data for environmental product declarations and procurement frameworks. Full article

With the increasing penetration of wind and photovoltaic generation, microgrids are playing an increasingly important role in promoting renewable energy accommodation, enhancing operational flexibility, and enabling low-carbon energy management. However, the strong uncertainty of renewable generation and load demand, together with the coupling effects of electricity, hydrogen, and carbon markets, poses significant challenges to the optimal planning and operation of microgrid energy storage systems. To address these issues, this paper proposes a bi-level optimal sizing framework for an electric–hydrogen hybrid energy storage system (EHH-ESS) in a microgrid under multi-market coupling. First, typical wind–solar–load scenarios are generated using a Wasserstein generative adversarial network with gradient penalty (WGAN-GP), so as to capture the stochastic characteristics and temporal correlations of renewable generation and load demand. Then, a multi-market coupling index (MCI), integrating electricity price, hydrogen price, and carbon price signals, is constructed to characterize time-varying economic and low-carbon operating incentives and to guide coordinated dispatch decisions. On this basis, a bi-level multi-objective optimization model is established. The upper level determines the optimal capacities of battery storage, electrolyzers, fuel cells, and hydrogen tanks, while the lower level performs hourly coordinated operation of the microgrid under multi-market conditions. The model considers annual equivalent total cost, renewable energy curtailment rate, and carbon emissions as objective functions, and is solved using the NSGA-III algorithm. Compared with the no-storage benchmark, the proposed scheme improves the annual operating economics and renewable-energy accommodation under the studied market conditions. The proposed method significantly reduces annual operating cost and improves renewable energy accommodation. However, under the current carbon price and grid emission factor settings, the optimal economic solution increases carbon emissions relative to the baseline, indicating a trade-off between economic arbitrage and low-carbon operation. Full article

The decarbonization of maritime transportation requires shipboard energy systems to coordinate conventional generators, renewable energy sources, energy storage devices, and thermal energy units under voyage-dependent operating constraints. This paper develops a configurable hybrid multienergy ship system for coordinated electrical and thermal energy scheduling. The proposed framework functionally separates the propulsion subsystem from the service and thermal subsystem while retaining system-level coordination among photovoltaic generation, wind generation, diesel generators, micro gas turbines, energy storage batteries, and thermal energy units. A convolutional neural network is employed to provide short-term photovoltaic power forecasts for day-ahead scheduling. The resulting scheduling problem simultaneously considers voyage completion, power balance, equipment operating limits, ramp-rate constraints, battery charging and discharging restrictions, operating costs, and pollutant emission treatment costs. The nonlinear operating logic is reformulated as a mixed-integer optimization problem and solved using CPLEX. A representative coastal voyage case study is used to evaluate the proposed framework. The results demonstrate that the method can coordinate multiple shipboard energy sources, satisfy the prescribed electrical and thermal demands, and provide a set of Pareto-optimal solutions describing the trade-off between operating cost and emission-related cost. The proposed framework provides a system-level scheduling approach for supporting the economic and low-carbon operation of hybrid multienergy ships under increasingly stringent maritime emission reduction requirements. Full article

Carbon pricing is jurisdictional, while proof-of-work cryptocurrency mining is a highly mobile electricity load. We examine whether daily power-sector emissions display a cross-regional and distributional pattern consistent with short-run emissions displacement. Using daily observations covering calendar years 2019–2025 (with a boundary observation on 1 January 2026; N = 2550 after transformation and cleaning), we estimate quantile regressions for the EU27, the Russian Federation and the rest of the world using the interaction between Bitcoin returns and European carbon-allowance returns. The focal Russian lower-tail interaction is positive (q10 beta = 0.0662); OLS and dynamic specifications remain positive, and a 1000-replication pairs bootstrap gives p = 0.0077. The association survives a trading-day-only sample, calendar and persistence controls, and a seven-lag specification, while randomised-carbon and non-power-sector placebo outcomes are null. However, the coefficient loses conventional significance without Winsorisation, the May-2021 Chinese-ban timing prediction is not supported, and a direct EU27-minus-Russia substitution diagnostic is null. Quantile-on-quantile estimates place the largest Russian Bitcoin-return coefficients in high-carbon-price, low-emission states, but remain descriptive. Because the design does not observe mining capacity moving across jurisdictions and the available full-sample Russian emissions series is national rather than subnational, the evidence supports a leakage-consistent operational association rather than proof of physical relocation or a broad causal effect of EU carbon pricing. Full article

High-solar-reflectivity cladding materials are widely promoted to reduce cooling demand and mitigate urban heat island effects. However, in cold and mixed climates, their overall energy and carbon performance remains uncertain due to potential winter heating penalties and embodied carbon trade-offs. This study presents a comparative evaluation of energy use, annual operational carbon emissions, and material-level embodied carbon for high-reflectivity cladding applied to commercial buildings across representative Canadian climate zones. Dynamic simulations were conducted in EnergyPlus using a standardized warehouse archetype in Montreal, Toronto, and Vancouver, representing cold continental, mixed continental, and marine climates. Roof and wall solar reflectivity (albedo) was varied from 0.2 (baseline) to 0.8 (high reflectivity), while other envelope properties remained constant. Increasing reflectivity reduced annual cooling demand by approximately 15% in Montreal and Toronto and 20% in Vancouver, with the largest reductions during peak summer periods. However, reduced winter solar heat gains produced heating penalties, increasing total annual energy use by 1% in Montreal, 0.5% in Toronto, and less than 0.5% in Vancouver. Operational greenhouse gas emissions were calculated by converting simulated annual electricity and natural gas use into CO₂-equivalent emissions using provincial grid emission factors and combustion factors consistent with Environment and Climate Change Canada reporting. The results demonstrate the strong influence of regional energy supply on operational carbon outcomes. A cradle-to-gate (A1–A3) life cycle assessment quantified embodied carbon of representative cladding materials using Environmental Product Declarations and North American databases. Embodied carbon varied considerably: product-specific steel cladding manufactured in low-carbon electricity regions showed global warming potential as low as 1.76 kg CO₂e/kg, compared with industry averages exceeding 2.4 kg CO₂e/kg. Rather than performing a complete whole-life carbon assessment, this study comparatively evaluates annual operational carbon emissions and material-level embodied carbon to improve understanding of the energy and carbon implications of high-solar-reflectivity cladding materials in representative Canadian climates. The results demonstrate that climate conditions, envelope thermal performance, regional energy supply, and manufacturing pathways influence the environmental performance of cool envelope strategies. Full article

To alleviate renewable energy curtailment and the high operating costs arising from the temporal and spatial mismatch of distributed generation, this paper develops a cross-park dispatch optimization approach for power systems under the joint participation of carbon trading and green certificate trading (GCT). The proposed approach aims to improve system flexibility and economic performance in coordinated multi-park operation. Specifically, adjustable resources in different parks are dispatched in a coordinated manner, and the total comprehensive operating cost is taken as the optimization objective. In addition, the Alternating Direction Method of Multipliers (ADMM) is adopted to determine inter-park electricity trading prices and exchanged power in a distributed framework. Furthermore, an asymmetric bargaining model is introduced to distribute the cooperative benefits, ensuring a balance between fairness and incentive compatibility. Simulation results demonstrate that inter-park electricity interaction reduces generation costs by 5.29%. The integration of carbon and green certificate trading further reduces costs by 7.4%. After asymmetric bargaining-based benefit allocation, the operating costs of parks with higher contributions decrease by up to 10.34%. The results conclude that the proposed strategy effectively leverages the complementary advantages of multi-park resources and optimizes the synergy between carbon markets, green certificate markets, and physical dispatch. Full article

Hydrogen is not intrinsically low-carbon; its environmental value depends on how, where, and with which energy system it is produced. This PRISMA 2020 systematic review synthesizes 28 peer-reviewed life cycle assessment (LCA) studies on major hydrogen production pathways, including steam methane reforming, electrolysis, biomass-based routes, thermochemical cycles, and emerging photoelectrochemical systems. Unlike reviews focused only on carbon intensity, this study jointly evaluates environmental performance, economic feasibility, and technology readiness to identify where apparent advantages remain robust and where they disappear under real deployment conditions. The evidence shows that renewable-powered electrolysis can deliver the lowest greenhouse gas emissions when supported by additional low-carbon electricity, but the same technology can lose its climate benefit in fossil-dominated grids. Biomass and emerging routes diversify supply options but introduce water, land, material, and maturity trade-offs that are often underrepresented in policy narratives. Regional conditions, especially grid carbon intensity and resource availability, explain much of the variation observed across studies. The review also identifies persistent methodological gaps, including inconsistent system boundaries, limited dynamic grid modelling, weak treatment of indirect land use effects, and insufficient accounting for system-level benefits from flexible electrolysis. Overall, the findings support performance-based carbon intensity standards, region-specific deployment strategies, and more transparent LCA methods capable of capturing hydrogen’s role in integrated energy systems. Full article

With the rapid expansion of global trade, the environmental impacts of port operations have attracted increasing attention. This study develops a mixed-integer programming (MIP) model to identify low-carbon energy mix replacement pathways for yard trucks (YTs), aiming to minimize total cost under low-carbon constraints while accounting for both economic and environmental performance. In the proposed model, the carbon emission cost is separated into transport and idling components to reflect differences in emissions across vehicle operating states. An electric YT (ET) replacement discount coefficient is introduced to quantify the reduction in the effective service capacity of ETs under port operating conditions. The practical significance of the proposed methodology is demonstrated through a case study. The results show that the optimized scheme reduces carbon intensity per unit throughput by 46% over the 15-year planning period, with an average annual decline of 4%. The results also reveal a staged transition pathway: diesel YTs (DTs) are gradually phased out, liquefied natural gas YTs (LNGTs) serve as an interim option, ETs are rapidly deployed and assume a dominant role, and hydrogen fuel cell YTs (HFCTs) increase steadily in the later stages. This study also includes various sensitivity tests, which illustrate that although the magnitude of total cost may vary across different scenarios, the overarching direction of transition remains robust. These findings can inform the formulation of energy mix optimization strategies for YTs. Full article

Coordinating energy transactions with carbon allowance management is difficult in a multi-energy-coupled integrated energy system (IES) because seasonal carbon information and hourly operation are handled on different timescales. This study develops a multi-timescale low-carbon economic dispatch framework that integrates carbon–energy trading, low-carbon demand response, seasonal carbon-pressure signals, and preference-weight selection. The case study is a park-level electricity–heat–gas–cooling IES comprising two renewable generation technologies, five conversion technologies, five storage technologies, four end-use load types, and external electricity and gas interfaces. Four 24 h profiles—one for each season—are combined into a 96 h representative horizon. Historical renewable-output and load data are used to derive seasonal carbon-pressure signals, which are embedded in electricity, heat, and gas prices. Cooling demand is treated separately through a fuzzy thermal-comfort response. An outer IGA searches the economic preference weight, while CPLEX solves the hourly dispatch problem for each candidate. The selected economic and carbon-emission weights are 0.62 and 0.38, respectively. Compared with the conventional scenario, the complete framework reduces carbon emissions from 1052.92 t to 970.24 t and operating cost from CNY 1,103,420.84 to CNY 900,485.52, corresponding to reductions of 7.85% and 18.39%. In practical terms, the framework converts seasonal carbon-management information into hourly decisions without relaxing explicit comfort limits. The reported gains apply to the modeled 96 h representative horizon and should not be interpreted as annual performance. Full article

High-energy-consuming and high-emission industries have made enormous contributions to economic development, but their carbon emissions are also substantial. To achieve the “dual carbon” goals as early as possible, this study takes Hainan Province, China, as the study area and employs the LMDI method to decompose the factors influencing carbon emissions. The Tapio model is also used to analyze the decoupling relationship between the driving factors and carbon emissions. The results show the following: (1) Carbon emissions in Hainan Province from 2007 to 2022 exhibited an overall upward trend, with an average annual growth rate of 5.75%. Various oil products accounted for an average share of over 40.11%, but the share of electricity increased, while that of oil decreased. The sectors, ordered from the highest to lowest carbon emissions, are: industry > transportation > residential > agriculture, forestry, animal husbandry, and fishery. (2) The decomposition results indicate that economic output, energy structure, and population size have positive effects on carbon emissions, while energy intensity and industrial structure have negative effects. At the sectoral level, the energy structure factor has a negative effect only on the transportation sector, and positive effects on all other sectors. The energy intensity factor has negative effects on all sectors except “other sectors” and the residential sector, with a cumulative contribution of 2003.65 × 10⁴ tonnes of carbon emissions. The industrial structure factor has negative effects on carbon emissions across all sectors, with a cumulative contribution of 1568.23 × 10⁴ tonnes. The economic output factor promotes emissions in all sectors, with a cumulative increase of 5787.35 × 10⁴ tonnes, of which 2740.88 × 10⁴ tonnes are from the industrial sector. The population factor also promotes emissions across all sectors, with a cumulative contribution of 549.21 × 10⁴ tonnes. (3) The decoupling model analysis shows that from 2007 to 2008, the decoupling state was predominantly an unfavorable negative decoupling. From 2008 to 2010, it shifted to a favorable positive decoupling, but from 2010 to 2011 it returned to an unfavorable negative decoupling. From 2011 to 2022, the decoupling index declined from 1.43 to 0.13, indicating an overall favorable weak decoupling state. (4) The decoupling effects of individual influencing factors reveal that in the 2007–2008 period, the carbon emission decoupling index was mainly composed of the energy intensity effect and the economic output effect. In the 2012–2013 period, the energy structure effect did not change significantly and remained in a weak decoupling state, while the energy intensity effect declined markedly, changing the decoupling state from weak to strong decoupling. The industrial structure effect remained in a strong decoupling state. In 2017–2018, the economic output effect changed from an expansive coupling state to a weak decoupling state, while the other effects all showed relatively favorable positive decoupling states. In 2021–2022, all effects exhibited favorable positive decoupling states, among which the energy structure and energy intensity effects showed strong decoupling. Finally, this study provides a case study for the development of Hainan as a Free Trade Port, a tourism island, a petroleum- and aviation-fuel-intensive province, and a pilot ecological civilization zone. Full article

With the explosive growth in demand for artificial intelligence and computing power, the energy consumption of data centers has sharply increased, making their green and low-carbon operation an urgent need. Shared energy storage (SES), as a flexible regulation resource, can effectively facilitate renewable energy consumption and reduce system costs. However, existing research mostly regards data center loads as rigid loads, ignoring the elastic scheduling potential of latency-insensitive computing tasks, and lacking a game decision-making model from the perspective of SES operators to provide strategies for data center SES transactions. Therefore, this study constructs a SES trading optimization model that takes into account the flexibility of computing power. The upper-level targets profit maximization for the SES operator by optimizing charge and discharge strategies and service pricing, while the lower level minimizes the total energy cost of each computing center by jointly optimizing computing task scheduling and energy storage utilization plans. Finally, a bi-level Stackelberg game-based optimization model is constructed to solve the SES dispatch and, achieve benefit coordination between SES and computing center. The simulation results indicate that using SES without implementing load shifting cannot optimize the total cost of the computing power center, offering only storage revenue. Only by integrating SES with load shifting can a significant cost reduction be realized. The model presented in this article resulted in an SES revenue of 2605.34 yuan and a 3.14% reduction in computing center costs. This study provides a theoretical basis and decision-making support for shared energy storage participation in the computing power market and contributes to accelerating the coordinated development of computing power and electricity systems. Full article