Search Results (1,285)

Forests, as the largest terrestrial carbon sink, play a critical role in mitigating climate change. Accurately estimating forest vegetation carbon storage and identifying its drivers are essential for evaluating regional carbon sink functions and supporting carbon neutrality policies. However, long-term carbon storage estimation that simultaneously captures spatial non-stationarity and separately quantifies aboveground and belowground carbon pools at the provincial scale remains limited, and the spatial differentiation drivers and the temporal change drivers of carbon storage have rarely been disentangled through pixel-wise attribution. This study aimed to estimate forest vegetation carbon storage in Jiangxi Province, China, from 1990 to 2024, and to separately quantify the drivers of its spatial differentiation and the contributions of climate change and human activities to its temporal changes. A geographically weighted regression (GWR) model was constructed using field measurements and multi-source remote sensing data; the geographical detector and partial correlation analysis were applied for spatial differentiation attribution, and pixel-wise residual analysis was used for temporal change attribution. The results showed that: (1) total carbon storage fluctuated between 553.95 and 839.78 Tg C over the 35-year period and exhibited a significant increasing trend, with a cumulative carbon sequestration of approximately 122 Tg C; (2) the belowground carbon pool increased disproportionately (net gain 79.32 Tg C) compared with the aboveground pool (42.20 Tg C); (3) precipitation and solar radiation were the dominant drivers of the spatial differentiation of carbon storage; and (4) climate change contributed approximately 60% and human activities approximately 43% to the temporal changes in total carbon storage. These findings provide a scientific basis for delineating forest carbon sink conservation zones and formulating differentiated forest management strategies in subtropical China. Full article

This study develops an inventory model for deteriorating products within a dual-warehouse system under carbon tax regulation. The framework is motivated by supply chains for perishable goods where storage constraints, product deterioration, environmental costs, and financing decisions arise simultaneously. The model considers an owned warehouse and a rented warehouse with higher holding cost, where the rented facility is utilized first. To capture realistic operational conditions, the model integrates time-dependent holding costs, trend-based demand, preservation technology investment to reduce deterioration, and a two-tier trade credit scheme. Carbon tax is incorporated as an environmental cost component, while preservation technology directly influences the deterioration rate, creating a trade-off between investment and waste reduction. The proposed model is examined through numerical analysis based on parameter settings representative of perishable products such as organic dairy items. The objective is to determine the optimal replenishment cycle time, preservation investment, and order quantity that minimize the total cost within the dual-warehouse system. Numerical results indicate an average optimal cycle time of approximately 0.57 years, preservation investment of about 1.32 dollars, and order quantity near 459 units. The average total cost is around 1056 dollars, with a minimum observed cost of approximately 964 dollars. The findings highlight the significant impact of preservation technology and carbon taxation on profitability and sustainability. Full article

Urban wetlands serve as vital spatial platforms for ecological restoration, carbon sequestration enhancement, and public environmental education; however, systematic research on their carbon sequestration benefits and the mechanisms linking these benefits to spatial design and public participation remains limited. Taking Nanjing Yuzui Wetland Park as a case study, this paper conducts a comprehensive assessment of plant community carbon sequestration benefits, spatial structural variations, and public ecological awareness by integrating official tree species data, field measurement data, the i-Tree Eco model, and questionnaire surveys. The results indicate that Yuzui Wetland Park already possesses a solid foundation for carbon sequestration, with a total carbon sequestration benefit of $48,777.38 and an average carbon sequestration benefit per tree of $24.63. Salix babylonica and Ulmus pumila L. are the primary contributors to current carbon sequestration, while Ginkgo biloba demonstrate strong long-term carbon storage potential, suggesting a clear division of labor among different tree species in short-term carbon fixation and long-term carbon storage. At the same time, significant differences exist between the native areas within the wetland and the peripheral roadside areas in terms of tree species composition, community structure, and carbon sequestration performance, indicating that spatial zoning is a key factor influencing the carbon sequestration benefits of urban wetlands. By integrating i-Tree Eco-based carbon assessment with questionnaire data, this study identifies a perceptual gap between the carbon-sink performance of Yuzui Wetland Park and public recognition of its ecological functions. The model results show measurable carbon-sequestration benefits and differentiated contribution patterns among tree species: Salix babylonica and Ulmus pumila L. contribute mainly to current carbon storage, while Ginkgo biloba shows long-term carbon-storage potential. The questionnaire results indicate that respondents recognized the wetland primarily through recreational and landscape functions, with lower recognition of carbon sequestration and water purification. These findings provide the basis for translating carbon-sink assessment into spatial visualization, environmental interpretation, and participatory landscape design. The study indicates that the optimization of urban wetlands should not be limited to plant selection and ecological calculations but should further integrate carbon sink assessment with spatial design and public participation to enhance the perceptibility, communicability, and practicability of wetland ecological value. Full article

Under international climate governance frameworks, including the Paris Agreement, the global decarbonization process has accelerated, imposing more stringent requirements on power system flexibility and low-carbon operation. Against this backdrop, pumped storage power stations, characterized by high flexibility and rapid response capability, serve as large-scale energy storage solutions that can replace thermal power for peak shaving, thereby enhancing renewable energy integration and delivering significant carbon reduction benefits in multi-energy complementary systems. A carbon reduction calculation model is developed within the framework of the Chinese Certified Emission Reduction (CCER) trading mechanism to quantify the annual contributions of pumped storage to carbon reduction. Using a Fractional-Order Gray Model (FGM) optimized via Particle Swarm Optimization (PSO), future carbon market prices are forecasted, facilitating a robust economic evaluation. The findings reveal that, over its lifecycle, pumped storage could achieve a total carbon reduction of approximately 23.27 million tons of CO₂, yielding approximately 7.981 billion CNY in carbon reduction value, with an initial 7-year CCER inclusion period contributing 254.0787 million CNY in carbon credits. It provides critical economic and policy insights, supporting the design of advanced power systems that position pumped storage as a central regulatory asset in carbon reduction strategies. Full article

National forest parks play an important role in maintaining the integrity of ecosystems, the sustainability of biodiversity, and the improvement of ecological service functions. Aboveground carbon storage (AGC) is an important indicator for evaluating forest ecosystem functions. Qianjiangyuan–Baishanzu National Park, located in the southern part of Lishui City, serves as a typical representative of the mid-subtropical evergreen broad-leaved forest ecosystem. It is characterized by high biodiversity and serves as a concentration area for rare and endangered species. Therefore, assessing the spatiotemporal dynamics of forest AGC in the typical subtropical forests of Qianjiangyuan–Baishanzu National Park is of great scientific significance. Taking Qianjiangyuan–Baishanzu National Park as a case study, this research utilized three periods of Landsat satellite remote sensing data (2009, 2014, and 2019) alongside contemporaneous ground-based AGC survey samples. Feature variables were extracted and subsequently screened using the Boruta algorithm. There were three algorithms, including least squares (LS), support vector regression (SVR), and random forest (RF), constructed to estimate forest AGC. The optimal AGC estimation model was selected, and the spatiotemporal variation characteristics of forest AGC within the national park were systematically analyzed. Research has shown that (1) texture features are important parameters for constructing forest AGC estimation models, accounting for up to 71%, with the 7 × 7 window having the greatest impact. (2) All three models can achieve high accuracy in estimating the forest AGC and its spatial distribution in Qianjiangyuan Baishanzu National Park. Among them, the RF model has the highest overall accuracy in estimating forest AGC, with a training set R² of 0.938, RMSE of 5.550 Mg/ha, rRMSE of 12.517%, a test set R² of 0.954, RMSE of 4.653 Mg/ha, and rRMSE of 10.087%. (3) The distribution of forest AGC in Qianjiangyuan Baishanzu National Park shows significant spatial heterogeneity, with higher carbon storage in the central, southern, and southeastern regions, while the northern region has relatively lower carbon storage. From 2009 to 2019, the forest AGC in the Qianjiangyuan–Baishanzu National Park exhibited a steady annual increase, with AGC density rising from 37.64 Mg/ha to 66 Mg/ha and total AGC stock increasing from 2.16 Tg C to 4.36 Tg C. These findings provide precise data support and a scientific basis for decision-making regarding differentiated ecological carbon enhancement and functional zone management within the national park. Full article

The Mugan Syncline in northeastern Yunnan represents a significant relay area for shale gas exploration in China. However, due to the combined effects of tectonic superimposition and sedimentary heterogeneity, systematic investigations into the intervals hosting high-quality shales and the coupling relationships among microfacies, reservoir quality, and gas-bearing properties remain insufficient. The core objective of this study is to establish a high-resolution microfacies framework and to quantitatively elucidate the multi-parameter coupling mechanisms by which microfacies control organic matter enrichment, pore development, and gas storage capacity in this structurally complex, basin-margin setting. By integrating core observations, thin-section petrography, scanning electron microscopy (SEM), whole-rock X-ray diffraction (XRD), total organic carbon (TOC) analysis, trace-element geochemistry, and well-logging data, we establish a stratigraphic subdivision and cross-well correlation framework for the Wufeng (WF) Formation and the Long11 submember. Furthermore, a lithofacies (microfacies) identification scheme based on a “TOC + siliceous (quartz + feldspar)–carbonate–clay” ternary classification is applied. The results reveal the following: (1) Based on the locally developed erosional contact at the boundary between the Longmaxi (LMX) Formation and the underlying Guanyinqiao Formation, the WF Formation in the study area can be subdivided into two submembers, whereas the Long11 submember comprises four sublayers. The thicknesses of the Long11-1 through Long11-3 sublayers range from 21.42 to 25.47 m, exhibiting a subtle northward-thickening trend. In contrast, the Long11-4 sublayer displays a relatively uniform thickness and high stratigraphic continuity of shale deposition. (2) Based on TOC content and ternary mineral composition, the shales are classified into four lithofacies associations and sixteen lithofacies subtypes. The main favorable microfacies assemblages are identified as high-carbon siliceous/calcareous shale (C-1), high-carbon calcareous/siliceous mixed shale (M-1), carbon-rich argillaceous siliceous shale (S-3), and high-carbon siliceous/argillaceous mixed shale (M-2). (3) High-quality shales (TOC > 2%) are predominantly developed in the upper member of the WF Formation and in the Long11-1 through Long11-4 sublayers. Their lateral distribution is markedly controlled by variations in paleotopography and terrigenous sediment supply. (4) The microfacies exert a synergistic control on shale gas enrichment. Carbon-rich argillaceous siliceous and siliceous-rich microfacies generally correspond to higher TOC contents and better-developed organic-matter pores. Siliceous-rich and mixed microfacies exert a positive influence on pore preservation and rock brittleness. The gas-bearing properties are influenced not only by TOC content but also by pore structure, mineral composition, and tectonic preservation conditions. The findings of this study provide a scientific basis for the prediction of shale gas sweet spots and the optimization of target intervals in the Mugan Syncline and other structurally and sedimentologically complex regions of northeastern Yunnan. Full article

Under the goals of carbon peaking and carbon neutrality and the development of zero-carbon parks, the continuous expansion of distributed photovoltaic (PV) installations has made grid-export constraints increasingly prominent. To investigate their influence on energy storage configuration and system operation, this paper incorporates the grid-export ratio constraint into the planning and scheduling process of a park-level PV-storage-charging system. A bilevel optimization model is established, in which the upper level minimizes the annual total cost (ATC), while the lower level minimizes the annual operating cost (AOC), considering time-of-use electricity prices, PV curtailment penalty, power shortage penalty, and battery degradation cost. The model is solved by a genetic algorithm (GA) and CPLEX. The results show that, for the studied industrial park, the 20% grid-export ratio is an important case-specific turning point under the given PV capacity, load level, electricity price, storage cost, and grid-connection conditions. Compared with the scheme without energy storage, the scheme with energy storage achieves lower PV curtailment and better economic performance. Sensitivity analyses further show that the PV curtailment penalty coefficient, energy storage investment cost, and PV installed capacity affect the optimal storage configuration and system economics. This study can provide a reference for energy storage planning and operation optimization of park-level PV-storage-charging systems under grid-export constraints. Full article

In the context of spot electricity markets, the fluctuation characteristics of node electricity prices play a crucial role in guiding the operational strategies of thermal power plants. However, constrained by the inelastic demand for heat, the strong coupling between electricity and heat in combined heat and power (CHP) units limits their ability to regulate electricity generation. These conditions present considerable difficulties for the economic feasibility and carbon reduction performance of these units, especially with high levels of renewable energy integration and during intensive peak-load shaving operations. In response to these challenges, this paper introduces an optimized dispatch method for renewable energy–electricity–heat coupled systems in thermal power plants with thermal storage, which incorporates the coordinated clearing of nodal electricity prices. First, a spot market clearing mechanism is established based on a DC optimal power flow model, and node electricity price signals reflecting network congestion characteristics are endogenously generated through the Lagrange multiplier of the node power balance constraint. Next, by introducing node injection power as a coupling variable between the grid clearing model and the CHP plant scheduling model, a co-optimization framework with bidirectional feedback between electricity prices and unit output is constructed. In conclusion, the integration of node electricity prices, deep peak-shaving costs, and carbon emission costs into a unified optimization objective leads to the development of a scheduling model for the renewable energy–electricity–heat coupled system, which includes CHP units, thermal storage, and grid interactions. The simulation results show that the proposed method can effectively improve the performance of the electric–thermal coupling system under the condition of a high proportion of renewable energy access. Under the typical daily load and new energy output conditions, the total cost of the system is reduced by about 9.7%, the carbon emission is reduced by about 18.3%, and the peak shaving capacity is increased from 25 MW to 58 MW, thus enhancing the flexible scheduling ability and market adaptability of the heat storage thermal power plant. Full article

Subalpine grasslands (SGs) of the Loess Plateau in China play a crucial role in the global carbon cycle of terrestrial ecosystems. However, the distribution pattern of total carbon stores along an elevation gradient on the SG plants of the eastern plateau remains unclear. In this study, eight typical mountains with one well-developed SG being surveyed as plot for each mountain were selected along an elevation gradient from 1722 m to 2954 m on the east of the plateau. The vegetation area, hydrothermal factors, soil elements, and species composition were analyzed using methods of spatial analysis and a partial least squares structural equation model (PLS-SEM), and these were used to estimate the total carbon stores of different plant functional groups for the entire area of each SG. This study revealed the driving factors of the elevational pattern of plant carbon storage in the SGs. The entire plant carbon storage of the eight SGs was 35,880.98 Mg in total. In addition, the aboveground and belowground carbon storage values both exhibited U-shaped trends along the elevation gradient. Significant minimum values were observed at the mid-elevation regions, ranging from 2305 m to 2673 m. The plant carbon storage was predominantly allocated to the belowground portions (accounting for 72.3% of the total carbon storage), and this allocation strategy was more pronounced at both low- and high-elevation regions. The carbon storage proportion among the different plant functional groups was the largest for forbs (average in 2348.85 Mg, accounting for 52%), medium for sedges (average in 1982.81 Mg, accounting for 44%), and the smallest for grasses (average in 153.47 Mg, accounting for 4%). The plant species diversity promoted carbon accumulation in the sedges and forbs, while the soil total phosphorus exhibited an inhibitory effect. In the PLS-SEM, hydrothermal factors (total effect = −0.8107) and species diversity (total effect = 0.4969) were the primary drivers of the plant carbon storage elevational pattern in the SGs, while the soil properties (total effect = −0.3501) and biomass (total effect = 0.0697) effects did not reach statistical significances. Therefore, the plant carbon storage distribution pattern along the elevation gradient was driven by hydrothermal factors and species diversity on the SGs of the eastern plateau. The plants such as forbs and sedges might play more important roles in improving regional plant carbon storage in high-elevation grasslands, through interactions with hydrothermal factors. Full article

Carbon taxes and credits (CT&C) accelerate global deployment of carbon capture, utilization and storage (CCUS) technologies to enable energy transition. This study investigates the economic performance and resilience of floating gas-to-wire with CCUS (f-GTW-CCUS), deployed at the wellhead of stranded CO₂-rich offshore oil and gas reservoirs. The f-GTW-CCUS platform integrates a natural gas combined cycle power plant with monoethanolamine post-combustion capture (PCC-MEA), producing low-carbon electricity (23 kgCO_2e/MWh, competitive with renewables) while monetizing captured CO₂ via enhanced oil recovery (EOR). The mass and energy balance data from the proposed process configuration were obtained in the literature. Critically, f-GTW-CCUS operates on wellhead-sourced in situ-associated gas, eliminating exposure to volatile natural gas markets, and achieves a levelized cost of electricity (LCOE) of USD 67.15/MWh. Monte Carlo analysis (10,000 Gaussian iterations, 30-year lifetime, 10% discount rate, three CT&C scenarios, namely, low/medium/high) is used to quantify economic feasibility across three stochastic variables: oil, natural gas, and electricity prices, starting in the 5th year. The results demonstrate the following: (1) Case A (f-GTW without CCUS) remains economically infeasible (NPV < 0) under all price volatility scenarios due to insufficient electricity-only revenue and carbon taxation penalties; (2) Case B (f-GTW-CCUS with immediate CCUS deployment) maintains positive NPV across all scenarios, with EOR monetization contributing 43% of total revenue; (3) the critical CCUS deployment-delay threshold is 6 years under high carbon taxation, extending to 10 years when carbon credits are included. Gate-to-gate environmental assessment (carbon intensity, water footprint, land transformation) shows f-GTW-CCUS superiority versus alternative power systems, with minimal water–land nexuses due to offshore desalination. An empirical consistency assessment based on the 2026 geopolitical energy crisis demonstrates the structural resilience of the f-GTW-CCUS plant: the wellhead sourcing provides resilience to global natural gas price shocks, while the concurrent crude price escalation amplifies EOR revenues by 43–57%, improving project feasibility during commodity disruptions. These findings position f-GTW-CCUS as a critical decarbonization pathway for O&G producers exploiting stranded gas reserves. The technology combines carbon intensity reduction with economic resilience under volatile energy market conditions and mandatory climate policies. Full article

Vehicle-to-grid (V2G) can provide flexibility and storage for low-carbon power systems while supporting sustainable mobility, yet real-world deployment remains largely confined to pilots despite substantial technical progress. This article presents a PRISMA-guided systematic review of 974 V2G/V2X studies published between 2009 and 2025 to explain why implementation lags and how it can be accelerated. Within this corpus, a total of 162 implementation-critical articles are identified and, within these, 95 studies that primarily address non-technical dimensions such as policy, markets, user behavior, and ecosystem coordination. Drawing on full-text coding, a four-domain socio-technical framework is developed that clusters recurring non-technical barriers and enablers into business–economic, governance–policy, social, and infrastructure and ecosystem domains. The analysis reveals (i) a temporal shift from technical dominance to multidisciplinary acceleration after 2021; (ii) distinct regional priorities in which Europe emphasizes regulation and business models, Asia focuses on infrastructure scaling, and the Americas on frequency services and resilience; and (iii) persistent revenue uncertainty, regulatory gaps, user resistance, and grid unreadiness as cross-cutting obstacles. For each domain, concrete transition levers and indicative deployment key performance indicators (KPIs) are derived, such as multi-actor revenue-sharing mechanisms, aggregator recognition in market rules, privacy-by-design user participation models, and targeted bidirectional charging deployment in constrained grids. Synthesizing these insights, three archetypal V2G transition pathways are proposed—regulation-led, infrastructure-first, and service-driven—that reflect regional conditions and offer alternative routes to large-scale adoption. The framework and roadmap provide researchers, policymakers, system operators, and mobility providers with an integrated basis for designing, monitoring, and evaluating V2G policies, business models, and pilots in line with energy system decarbonization goals. Full article

Temperate seagrass carbon-stock data remain limited in northern China, especially for island meadow systems with mapped distribution and repeated field verification. This study quantified standing seagrass ecosystem carbon stocks in the Changshan Archipelago, Dalian, using a standardized field survey covering eight meadow zones, 39 sampling stations, and 323.37 ha of confirmed seagrass area. Plant biomass carbon and sediment organic carbon were assessed, and the 0–100 cm sediment profile was sampled at all stations. The mapped meadows stored 29,305.75 Mg C in total ecosystem carbon. Sediment organic carbon accounted for 28,965.71 Mg C, representing 98.84% of the total stock. Plant biomass carbon contributed 340.04 Mg C, or 1.16%. The area-weighted ecosystem carbon stock per unit area was 90.63 Mg C ha⁻¹. This per-area stock ranged from 52.11 Mg C ha⁻¹ in Xiaochangshan to 209.50 Mg C ha⁻¹ in Haiyang Island. Guanglu Island contained the largest total carbon stock, with 9247.73 Mg C, because of its large meadow area and relatively high per-area carbon stock. The results show how mapped meadow area, sediment carbon dominance, and local sediment setting jointly shape regional carbon-storage patterns. This standardized baseline provides field-based evidence for comparing northern Chinese seagrass meadows with other temperate Zostera systems. The estimates describe standing ecosystem carbon stocks. Annual carbon sequestration rates were outside the scope of the assessment. Full article

Against the backdrop of the global energy transition and decarbonization imperative targets, improving the efficiency of conventional energy systems while simultaneously reducing carbon emissions has become a pressing challenge. To address the widespread problem of insufficient waste heat utilization in combined cooling, heating, and power (CCHP) systems, this study proposes a novel low-carbon-emission CCHP system coupled with heat pump (HP) technology and a monoethanolamine (MEA)-based carbon capture and storage (CCS) subsystem. The HP unit enables cascaded recovery and temperature upgrading of low-grade waste heat from both the flue gas and the CCS regeneration column. A comprehensive five-dimensional evaluation framework—covering energy, exergy, life cycle environmental assessment, economic and exergoeconomic analyses—is established and benchmarked against a conventional low-carbon CCHP reference system. Thermodynamic results show that HP integration raises the overall energy efficiency from 74.25% to 81.22% and the waste heat recovery rate from 73.59% to 89.85%, while simultaneously reducing exergy losses by 365.06 kW and elevating exergy efficiency from 53.95% to 65.07%. Economic analysis reveals that the unit energy production cost decreases from 0.033 to 0.031 $/(kW·h), despite a marginal increase in unit power generation cost. Sensitivity analysis identifies operating hours and interest rate as the dominant cost drivers. Exergoeconomic analysis pinpoints the turbine, the CCS subsystem, and the compressor as contributing 67.02%, 17.11%, and 8.17% of the total exergoeconomic losses, respectively, identifying them as the primary targets for future optimization. These findings provide a theoretical foundation and engineering guidance for the development and deployment of high-efficiency, low-carbon multi-generation energy systems. Full article

Industrial-park integrated electricity–heat–hydrogen energy systems (IEHESs) face a challenging rolling dispatch problem because strong multi-energy coupling, intertemporal storage dynamics, and forecast uncertainty make it difficult to achieve economy, low-carbon operation, and hard-constraint feasibility simultaneously. To address this issue, this paper proposes a graph spatiotemporal world-model-driven rolling model predictive control (MPC) framework, termed GraphWorldModel_MPC, for low-carbon economic dispatch of industrial-park IEHESs. First, a unified graph-based representation is constructed to characterize the topology-aware coupling relationships among the electricity, heat, and hydrogen subsystems. Second, a graph spatiotemporal world model is developed to learn multi-step state transitions, while constraint-aligned physics-consistency terms are incorporated to align the predicted trajectories with multi-energy balance, storage-boundary evolution, and ramping semantics. In addition, the learned dynamics are embedded into a hard-constrained economic MPC framework, and a quantile-based safety-tightening mechanism is adopted to mitigate residual prediction uncertainty and enhance closed-loop feasibility. Case studies on an industrial-park IEHES show that the proposed method achieves an average 24-step normalized root mean square error (NRMSE) of 4.28% and reduces the monthly total operating cost by 6.07%, 3.83%, and 10.79% compared with conventional economic MPC (EMPC), distributionally robust adaptive MPC (DRAMPC), and GRU-MPC, respectively. It also reduces equivalent carbon emissions by 6.89%, 4.52%, and 9.50% relative to these benchmarks, while maintaining zero dispatch violations in the tested monthly horizon. Full article

As the core pillar of international trade, the global shipping industry has seen its carbon and pollutant emissions become a key challenge in global environmental governance. Statistics indicate that ship carbon emissions account for 3% of the world’s total anthropogenic CO₂ emissions, while contributing 20% of global NO_x and 12% of SO₂ emissions, posing a serious threat to coastal ecosystems and public health. In response to the International Maritime Organization (IMO) “Net Zero Framework” and national green shipping policies, the transformation of ship power systems toward low-carbon and zero-carbon operation has become an inevitable trend. This paper systematically reviews the research progress and application status of green energy materials for ships, focusing on the working principles, technical characteristics, and engineering application cases of solar photovoltaic (PV) materials, wind energy utilization technologies, fuel cell materials, and alternative clean energy fuels (e.g., liquefied natural gas (LNG), methanol, and hydrogen energy). It also discusses the integration mode and optimization strategy of multi-energy hybrid power systems. The research findings show that solar photovoltaic technology has achieved large-scale application in coastal ships; hydrogen fuel cells are suitable for long-range ocean navigation scenarios due to their high energy density; LNG and methanol have become the current mainstream alternative fuels, relying on mature infrastructure; and hybrid energy systems can significantly improve power supply reliability and emission reduction efficiency through multi-energy complementarity. Finally, aiming at the existing bottlenecks (e.g., cost, energy storage, and safety) of various technologies, future development directions are proposed. This study provides a reference for the technological breakthrough and engineering practice of green energy power systems for ships and contributes to the realization of the “carbon neutrality” goal in the global shipping industry. Full article