Search Results (87)

The safe and stable operation of coal-fired generating units is of critical strategic importance for ensuring the reliable supply of power systems. However, the fault evolution of industrial thermal systems exhibits the characteristics of strong nonlinearity and a long incubation period, coupled with the extreme scarcity of key fault samples (Few-shot) in actual production, which severely limits the engineering application of traditional data-driven diagnostic methods. Existing deep learning models, which are highly dependent on massive and balanced labeled data, not only struggle to overcome the overfitting bottleneck in scenarios with scarce fault samples, but also frequently introduce severe label noise (Label Noise) by ignoring the physical incubation period of faults, resulting in the degradation of the model’s decision boundary. To address the above challenges, this paper proposes a novel fault diagnosis framework integrating multi-scale spatiotemporal feature engineering and the Tabular Prior-Data Fitted Network (TabPFN). Starting from the physical mechanism of the system, this paper develops a dynamic label cleaning strategy based on multivariate statistical deviation, which accurately defines the fault divergence point to eliminate the noise in the incubation period. The constructed multi-scale spatiotemporal feature engineering integrating first-order difference and sliding window statistics can effectively map the transient mutation and steady-state evolution trend of the system. The introduced pre-trained TabPFN model based on the Transformer architecture, relying on its Bayesian inference capability and in-context learning (In-Context Learning) mechanism, can realize parameter-tuning-free and efficient classification for scarce samples. Experiments based on high-fidelity dynamic simulation data from GE Steam Power show that under the strict setting of limiting the training set to only 2000 samples, the proposed method achieves a comprehensive diagnostic accuracy of up to 99.29% and an F1-score of 0.9929 for seven typical operating conditions. Multi-dimensional comparative experiments and ablation studies confirm that the proposed framework comprehensively outperforms six mainstream baseline models, including XGBoost and SVM, in terms of precision, recall, and anti-interference robustness, and also delivers outstanding performance when benchmarked against deep learning models. This provides a brand-new theoretical perspective and technical paradigm for equipment health management in the context of industrial big data. Full article

Currently, heating supply in rural areas of China still predominantly relies on conventional coal-fired heating, which suffers from poor thermal insulation performance and severe environmental pollution. To address the issues of energy waste and environmental pollution associated with traditional heating methods in rural China, this study selects a detached rural residential building in Jilin City as the research object. A building thermal load calculation model incorporating phase-change material (PCM) walls and dynamic simulation models for five clean heating coupling systems are developed using TRNSYS software, so as to analyze the influence of PCM placement at different positions within the wall assembly on the building’s thermal load, as well as the technical and economic performance of the five heating systems. The results show that, when PCM is placed on the inner side of the building envelope, the peak heating load is reduced from 15,234.2 W to 11,266.5 W, and the cumulative heating load drops from 33,744.3 kWh to 25,688.9 kWh. Compared with the conventional PV (photovoltaic) system, the PVT (photovoltaic–thermal) system achieves an 11% improvement in power generation efficiency. Among the five clean heating systems, the PVT–ground-source heat pump system exhibits the lowest energy consumption, while the PVT–biomass boiler system records the highest energy consumption. Based on life-cycle cost analysis, the PVT–biomass boiler system delivers the optimal economic performance, with a equivalent annual cost of 9285.48 CNY. Full article

Thailand has committed to achieving net-zero greenhouse gas (GHG) emissions by 2050, requiring a fundamental transformation of its energy system. This study developed an integrated energy modelling framework by coupling the Low-Emission Analysis Platform (LEAP) with the Next Energy Modelling System for Optimisation (NEMO) to evaluate Thailand’s long-term energy transition under three scenarios: Business as Usual (BAU), Current Policy Scenario (CPS), and Net Zero 2050 (NZ2050). The novelty of this study lies in integrating sectoral energy demand modelling; least-cost electricity system optimisation; GHG emissions accounting; and system cost assessment within a single framework to evaluate the technical, environmental, and economic implications of decarbonisation pathways. The results show that demand-side GHG emissions increase to 370.7 MtCO₂eq by 2050 under BAU, while current policies reduce emissions to 137.6 MtCO₂eq but remain insufficient to achieve Thailand’s climate targets. In contrast, the NZ2050 scenario lowers demand-side GHG emissions to 27.23 MtCO₂eq (a 93% reduction relative to BAU) through extensive electrification; a 59% improvement in energy intensity; accelerated renewable energy deployment; coal phase-out by 2045; and the deployment of carbon capture, utilisation and storage (CCUS), and bioenergy with carbon capture and storage (BECCS). Residual transport emissions are reduced to 23 MtCO₂eq and offset through carbon removal measures. On the supply side, least-cost optimisation reduces power-sector emissions to 2.9 MtCO₂eq while lowering electricity generation costs by approximately 47% through an optimised renewable-based generation mix. The findings demonstrate that Thailand’s net-zero target is technically feasible and economically viable; the integrated LEAP–NEMO framework provides a robust decision-support tool for national energy planning and other emerging economies pursuing cost-effective net-zero transitions. Full article

Electricity spot markets with time-of-use pricing create hour-by-hour variations in the economic value of thermal adjustments, requiring coal-fired units to adapt cold-end operation to real-time price signals. However, the nonlinear coupling between circulating water flow and condenser backpressure remains insufficiently characterized across the full operating envelope, and existing optimization strategies target steady-state heat consumption without accounting for the time-varying economic value of identical thermal adjustments under spot pricing. This study develops a quasi-steady-state thermodynamic–economic model that links real-time electricity prices with the nonlinear heat-transfer response of the circulating water system. The model enables the adaptive selection of pump combinations and blade-opening angles by balancing marginal pump power savings against marginal turbine output losses under time-of-use price signals. Using actual electricity spot market data from Zhejiang Province, simulations under different seasonal conditions show clear economic gains. The maximum hourly saving reaches 2190.79 CNY during summer negative-price periods, which is about 5.3 times higher than that in winter, while backpressure deviations remain within 12.5% of the design value. The seasonal disparity is governed by the initial heat exchange driving force, a fundamental thermodynamic property amplified by the negative-price superposition effect. The framework establishes a physical basis for market-responsive cold-end regulation across seasonal and load conditions, supporting the economic dispatch of coal-fired units in spot market environments. Full article

Vibration energy technology holds promise for self-powered miniature wireless sensor devices in underground coal mines. This study proposes a magnetically coupled bistable composite-beam wind energy harvester (BCBWEH) to enhance the response threshold for harvesting weak ambient wind energy. A nonlinear magnetic model based on magnetic dipoles is established, and the system’s dynamic equations are formulated using the lumped parameter method. Numerical simulations analyze the effect of magnetic spacing on static bifurcation, and discuss the influences of initial static position, wind excitation, and magnetic moment on the system’s dynamic behavior; experimental results validate the accuracy of the numerical predictions. By adjusting the magnetic spacing under the same level of excitation, the system’s motion can transition from single-well oscillation to efficient inter-well vibration. When the initial position lies closer to the shallower potential well, relatively small wind excitation can trigger large-amplitude inter-well vibrations, thereby increasing output power. This study offers guidance for optimizing structural configurations and tuning design parameters of piezoelectric energy harvesters based on composite-beam architectures. Full article

Diesel-powered equipment is widely used in underground coal mines for auxiliary transportation, material handling, and equipment relocation because of its long operating endurance, convenient refueling, and strong adaptability to complex operating conditions. However, carbon monoxide (CO) emissions from such equipment can accumulate locally under restricted ventilation, idling, and frequent start–stop operation, thereby threatening occupational health and mine safety. This review focuses on CO purification technologies for diesel-powered mining equipment. The operating characteristics and influencing factors are analyzed, and different technical routes are compared, including in-cylinder control, wet scrubbing, adsorption, non-thermal plasma (NTP), and catalytic oxidation. Recent advances in noble-metal catalysts, transition-metal and CeO₂-based reducible oxide catalysts, and single-atom catalyst (SAC) design strategies are summarized. Research progress in exhaust aftertreatment systems is also discussed. Overall, CO purification for diesel-powered mining equipment requires coordinated optimization of low-temperature activity, safety-oriented thermal management, flow resistance, and long-term operational stability. Future research should focus on structured catalytic units, durability under coupled exhaust conditions, online monitoring, and field validation to improve the compatibility of CO purification systems with underground mining conditions. Full article

To alleviate grid peak-shaving pressure from high-penetration renewable energy integration, coupling thermal energy storage (TES) with coal-fired power plants is an effective approach for enhancing operational flexibility. This paper systematically investigates the peak-shaving performance of a coal-fired unit integrated with molten salt storage and heat pump storage systems, focusing on load response characteristics, peak-shaving capability, and the influence of discharge strategies on thermodynamic performance under various rated turbine heat acceptance (THA) conditions. The results indicate that, under identical peak-shaving capacity, the molten salt system exhibits greater storage capacity, which increases with rising THA levels, whereas the heat pump storage capacity remains largely THA-independent. Regarding discharge strategies, replacing high-pressure extraction steam achieves the fastest ramp rate and largest incremental power output, introducing steam into the intermediate-pressure cylinder yields the slowest response but highest round-trip efficiency, and replacing low-pressure extraction steam delivers the smallest peak-shaving capacity and lowest round-trip efficiency. Although TES integration slightly reduces thermal efficiency due to heat exchange losses, this trade-off is justified by significant flexibility improvement, demonstrating clear engineering value for high-renewable grids. Full article

High-temperature corrosion severely impairs the service life of boiler heating tubes and threatens the safe and economical operation of thermal power units. With diversified fuels (coal, biomass and refuse-derived fuels) and continuously elevated operating parameters (steam temperature exceeding 620 °C for ultra-supercritical units), boiler heating surfaces are exposed to increasingly complex corrosive environments. High-temperature oxidation, sulfidation, chlorination, molten salt hot corrosion and deposit-induced multi-factor coupled corrosion coexist and exacerbate each other. This paper adopts a four-dimensional analytical framework of “mechanisms–technologies–materials–evaluation” to systematically summarize relevant research progress. From the perspective of corrosion mechanisms, the evolution of understandings from single high-temperature oxidation to multi-factor coupled corrosion is reviewed. In terms of surface coating technologies, seven mainstream processes including HVOF/HVAF spraying, plasma spraying, cold spraying, laser cladding and weld overlay are compared in terms of preparation characteristics and engineering applicability. For coating materials, twelve material systems such as NiCr alloys, MCrAlY, cermets, Fe-based amorphous/nanocrystalline alloys and high-entropy alloys are evaluated for their corrosion resistance under diverse service conditions. As for monitoring and evaluation, this work introduces full-range corrosion management technologies covering electrochemical monitoring, non-destructive testing, numerical simulation and life assessment. Finally, the paper discusses the application prospects of gradient coating design, AI-assisted material screening and digital twin technology, and points out key research gaps including long-term service reliability verification of coatings and quantitative prediction models for multi-factor coupled corrosion. Full article

Chemical absorption is currently the most mature technology for carbon capture from flue gas in coal-fired power plants. The selection of the amine solution system and process optimization directly determine the energy consumption of carbon capture and are critical to the large-scale implementation of the amine process. In this study, a composite amine solution of N-methyl-diethanolamine-piperazine-water (MDEA-PZ-H₂O) was selected as the CO₂ absorbent. Aspen HYSYS (14.0) software was used to establish a typical process model for CO₂ capture from flue gas in coal-fired power plants. Using single-factor sensitivity analysis, key process parameters in the typical carbon capture process—including amine solution composition, flue gas inlet temperature, lean liquid temperature, and gas-to-liquid ratio—were optimized. Based on the process optimization, this study conducted integrated energy-saving optimization by optimizing the temperature distribution in the absorption tower (achieved through the integration of inter-stage cooling in the absorption tower) and regeneration energy savings (achieved through the coupling of the Mechanical Vapor Recompression (MVR) process). The results indicate that the carbon capture system integrating the inter-stage cooling process with the MVR energy-saving process reduces the energy consumption per unit of carbon captured by 15.15% compared to a typical process system. This demonstrates that the integration of multiple energy-saving processes with the recovery of flue gas and CO₂ waste heat recovery within the system is an effective approach to reducing the energy consumption per unit of carbon capture. Full article

In summer 2022, Sichuan suffered an unprecedented compound heatwave-drought, cut-ting hydropower output and forcing a rapid coal-fired power ramp-up to secure supply, driving elevated emission intensities in its power sector. However, the fluctuations in power generation from thermal power and hydropower are significantly influenced by policy and economic factors. In meteorological-electrical coupling research, it is necessary to isolate the disturbances caused by major non-meteorological factors such as policy and economics on power generation to identify the true role of meteorological conditions. Therefore, this study proposes the “squeeze verification method,” which indirectly verifies the numerical confidence of the power time series variable under non-extreme weather conditions: by integrating CRU meteorological data, WIND energy data, and public environmental data, the ARIMA model is applied to quantify the power shortage amount caused purely by meteorological factors after stripping off the economic factors of policies in July–September 2022, which totaled 33,142 GWh, as well as the increase in thermal power generation, which amounted to 6806 GWh. Using localized emission factors, we calculated implicit emission increases: NO_x dominated pollutant growth, while extra CO₂ emissions accounted for 8.16% of annual power-sector carbon emissions. This study further uncovered synergistic environmental risks tied to emergency coal-fired power generation. These risks include elevated air pollutant and CO₂ emissions, aggravated ozone pollution, and a reinforced positive feedback loop that intensifies the extreme weather cycle. Finally, we propose targeted preventive strategies to mitigate these cascading environmental risks and ensure the sustainable development of the energy system. Full article

Wireless links in underground coal mines suffer from severe attenuation, blockage, and limited spatial coverage. To improve link quality under these conditions, we study a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted system with multiple movable antennas (MAs) installed at the base station (BS) panel. Unlike prior models that assume a continuous movement box, we explicitly account for practical panel constraints: mechanical supports and RF feed lines partition the BS panel into non-overlapping irregular feasible subregions. This turns the BS-side antenna-positioning task into a mixed-integer nonlinear program (MINLP). We formulate a joint optimization problem that couples BS beamforming, STAR-RIS transmission/reflection coefficients, BS-side MA positions, and MA-to-subregion assignment with collision-avoidance constraints. To solve it, we adopt a block coordinate descent (BCD) framework: successive convex approximation (SCA) for beamforming, semidefinite relaxation (SDR)-based updates for STAR-RIS coefficients, and a penalty-based continuous relaxation for MINLP handling. The MA solver further integrates Hungarian initialization, cross-region jump updates, and reassignment corrections to escape poor local subregions. Simulation results in coal mine channel settings show that the proposed method yields a 66.7% sum-rate gain over fixed-antenna baselines and reduces required transmit power by 16.8 dB at the target-rate operating point. Compared with a regular-region BS-MA baseline, the irregular-partition design achieves an additional 5.6 dB power saving, demonstrating the practical value of hardware-aware geometry modeling. Full article

To improve the low-carbon economic operation of integrated energy systems under wind power uncertainty, this paper develops an optimal scheduling model for an integrated energy system coupling oxygen-enriched combustion with hydrogen–ammonia–carbon utilization pathways. The proposed framework integrates oxygen-enriched combustion, electrolysis-based hydrogen production, methanation, hydrogen fuel cells, ammonia synthesis, urea synthesis, captured CO₂ utilization, reward–penalty ladder-type carbon trading, and IGDT-based wind power uncertainty scheduling. A deterministic scheduling model is first established to minimize the total operating cost, and Information Gap Decision Theory is then introduced to formulate risk-averse and opportunity-seeking scheduling strategies under wind power uncertainty. Simulation results show that, compared with the post-combustion carbon capture scenario and the conventional coal-fired scenario, the proposed system reduces the total operating cost by 3.37% and 8.03%, respectively, and reduces the wind curtailment cost by 40.2% and 57.0%, respectively. Compared with the post-combustion carbon capture scenario, carbon emissions are reduced by 17.7%. The hydrogen–ammonia–urea chain generates approximately 15.68 × 10⁴ CNY of urea revenue and improves carbon resource utilization. Under an IGDT deviation factor of 0.03, the risk-averse strategy increases the total operating cost by approximately 10.30 × 10⁴ CNY to enhance operational robustness, while the opportunity-seeking strategy reduces the total operating cost by approximately 10.30 × 10⁴ CNY and decreases carbon emissions by 19.6 t. These simulation results verify the effectiveness of the proposed scheduling framework under the designed case study. The proposed framework can improve the low-carbon economy, renewable energy accommodation, carbon resource utilization, and adaptability to wind power uncertainty of the studied integrated energy system. Full article

This study presents a comparative thermodynamic assessment of molten salt thermal energy storage (MSTES) integrated with a 330 MW subcritical coal-fired power plant. Different charging and discharging configurations based on main steam, reheat steam, and hybrid steam extraction are evaluated using HITEC salt. Thermodynamic performance is rigorously assessed via exergy analysis and equivalent round-trip efficiency. The findings indicate that system configuration exerts a substantial influence on performance: the HITEC scheme H-C5-D1 achieves an optimal balance, attaining a round-trip efficiency of 44.0% and a peak-shaving capacity of 33.4 MW. Exergy analysis identifies molten salt heat exchangers as the main source of exergy destruction, governed primarily by the steam-salt temperature difference and throttling effects. HITEC salt is advantageous in medium- and low-temperature applications. Increasing main-steam utilization in hybrid schemes enhances round-trip efficiency and storage capacity, though this comes at the cost of increased heat exchanger investment. Overall, the MSTES system significantly enhances both operational flexibility and thermal efficiency of coal-fired units. Full article

Coal-fired power units remain integral to electricity supply in many regions while facing increasingly stringent environmental expectations. Bridging reliable generation with sustainability requires more than end-of-pipe controls; it demands continuous intelligence embedded in plant operations. This study introduces an industry-oriented monitoring framework that transforms historical operational records into actionable foresight, enabling on-the-fly orchestration of combustion conditions to anticipate sulfur oxide (SOx) concentrations. Leveraging 919 empirical data points collected in 2019 from Unit 8 of the Taichung Thermal Power Plant, the framework integrates robust data governance, targeted feature curation, and a neural network-based analytics core. Eight process variables—sulfur content, coal feed rate, fixed carbon, grinding rate, calorific value, excess air, air flow, and boiler efficiency—emerge as the most influential drivers through systematic selection and feature importance attribution. The resulting forecasting module exhibits near-perfect alignment with observed emissions (R² = 0.99), enabling near-real-time guidance for setpoint adjustments and facilitating compliance strategies under varying load and fuel-quality conditions. Beyond accuracy, the system is architected for scalability and portability, aligning with Industry 4.0 paradigms by coupling continuous sensing, data-driven decision support, and stakeholder transparency. By reframing emission oversight as a proactive, intelligent service rather than a static reporting function, the proposed approach advances operational resilience, regulatory compliance, and community trust, with direct implications for resource efficiency and circular economy initiatives across heavy industry. The framework reduces potential SOx emissions and improves energy utilization efficiency under varying operational conditions. This approach contributes to environmental sustainability by enabling proactive emission reduction and cleaner production practices. It supports regulatory compliance and aligns with global sustainability goals, including SDG 7 and SDG 13. Full article

To improve the flexibility of coal-fired power units and support renewable energy integration, molten salt thermal storage has been widely considered a promising retrofit option. However, under unified operating conditions, the comparative effects of different heat-release pathways and steam extraction ratios on flexibility, full-cycle thermodynamic performance, and economic performance have not been sufficiently clarified. In this study, a thermodynamic model of a 600 MW subcritical coal-fired power unit coupled with a two-tank molten salt thermal storage system was established in Ebsilon and validated against the design heat-balance data under typical load conditions, with maximum relative deviations of 0.06% for power output, 0.95% for main steam flow rate, and 1.24% for heat consumption rate. Three representative heat-release pathways were comparatively investigated under identical heat-storage conditions, with steam extraction ratios ranging from 2% to 18%. The results show that increasing the extraction ratio raises the thermal storage capacity from 9.762 to 84.636 MWh and enhances the downward peak-shaving capability, but weakens the full-cycle thermodynamic performance. Among the three schemes, Scheme 2 exhibits the strongest upward peak-shaving performance, with upward peak-shaving energy increasing from 2.893 to 24.395 MWh, and also yields the highest annual net profit (0.546–4.342 million CNY). Scheme 3 exhibits the best full-cycle thermal and exergy efficiencies, with full-cycle thermal efficiency of 42.76–41.56% and full-cycle exergy efficiency of 38.34–37.27%. In addition, Schemes 1 and 2 show significantly higher round-trip efficiencies than Scheme 3, with Scheme 2 becoming more advantageous at higher extraction ratios. Scheme 1 exhibits the shortest static payback period (7.12–7.63 years) and the highest internal rate of return (12.77–11.65%). These results indicate that the three schemes have distinct advantages in peak-shaving performance, full-cycle thermodynamic performance, and economic performance, and provide a comparative basis for engineering selection and parameter optimization of molten-salt-based flexibility retrofits in coal-fired power units. Full article