The dynamic integration of Solid Oxide Fuel Cell (SOFC) systems with power electronics presents significant challenges due to the disparate time scales of thermo-electrochemical processes and electronic control systems. This manuscript develops a unified standard thermal resistance-impedance-circuit approach for grid-connected SOFC systems. This approach provides a comprehensive cross-scale dynamic model, coupling the standard thermal impedance (STI) method for SOFC modeling with power regulation circuit for converter and inverter, which constructs the overall system topology and characterizes the transmission and coupling characteristics of various physical parameters within different components, integrating the multi-physical processes, cross-timescale dynamics and inter-disciplined areas to facilitate real-time simulation and control. On this basis, we analyze the dynamic response processes of power electronics equipment, and SOFC systems under varying load conditions. The results show that the power electronics respond in sub-second time frames (0.15-0.5 s), Balance of Plant (BOP) components have intermediate response times (7-9 min), and SOFC stack exhibit slow response times (25-39 min) when the load changes. This unified model visualizes the transfer and coupling properties of physical parameters within different components, highlights the interactions between the slow thermal-electrochemical dynamics and the fast-switching power electronics, then emphasizes the topology's capacity to handle transient states and ensure robust performance. The proposed framework provides a pathway for enhancing computational efficiency, improving power quality, and ensuring operational stability in distributed energy systems.

Against the backdrop of accelerating global carbon neutrality goals, the power system, as a core sector of carbon emissions, faces the critical challenge of precisely planning its low-carbon transition pathway at the provincial level. This study focuses on the chronological production simulation and carbon emission flow calculation methods for provincial power systems, developing a bi-level chronological production simulation model incorporating carbon emission flow computation. The model is validated and analyzed using a case study of Gansu Province, China. Verified with actual data, the maximum relative error of all key indicators does not exceed 4.22 %, confirming the model's reliability and rationality. Furthermore, a multi-scenario analysis is conducted for the planning period of 2026-2030, revealing several operational characteristics: a notable trend of renewable energy replacing thermal power, the critical role of energy storage configuration in the transition, and the continued importance of thermal power in ensuring energy security. Through carbon emission flow analysis, the spatiotemporal distribution patterns of provincial carbon emissions are elucidated, uncovering the carbon reduction potential of various mitigation measures. These include inter-temporal load shifting (with a maximum reduction of 85.54 %), optimized energy storage configuration (a reduction of 45.9 %), and reducing thermal power output in high-carbon areas (a reduction of 14.21 %). The results demonstrate that the model can effectively support the planning of low-carbon transition pathways for provincial power systems.

Multistage latent heat thermal energy storage systems (LHTESS) are an efficient way of storing and utilizing thermal energy due to their faster heat storage and heat release rates and more uniform heat transfer fluid (HTF) outlet temperatures compared to a single-stage system. This paper proposed a three-stage LHTESS filled with phase change material (PCM) in the tube, and constructed the numerical simulation model for comparing the heat storage performance with different placement configurations and highlighting the differences between the proposed system and single-stage LHTESS. Meanwhile, the variations in melting characteristics the heat release performance are analyzed by field synergy theory. The results show that the differences in melting performance of the PCM at each stage in the vertical three-stage LHTESS are greater compared to the single-stage PCM than those observed in the horizontal system. In the horizontal three-stage LHTESS, compared to the vertical system, the complete melting time of the PCM at each stage reduces by 32.1%, 34.3%, and 35.9%, respectively. Meanwhile, the solidification time also reduces by 8.2%, 9.5%, and 7.9%, respectively. Based on the field synergy theory, horizontally placed PCMs at each stage have more intense natural convection and better synergy between velocity gradient and temperature gradient. The horizontal device has an average increase of 15.8% in the synergy angle of each PCM compared to the vertical device, and it has a better heat transfer enhancement effect. This provides a new idea for the design and research of latent heat storage systems.

The optimized geometry design is a key technical tool that can improve Proton Exchange Membrane Electrolysis Cell (PEMEC) overall operational efficiency. In this paper, a PEMEC structure optimization method based on the finite data mapping method is proposed by combining the response surface analysis method with machine learning. An accurate expression of the invisible relationship between the flow channel geometric parameters and the system performance is realized from the limited simulation data. On this basis, a multi-objective particle swarm algorithm can be used to achieve accurate and efficient multi-objective optimization of PEMEC, and finally, a new flow channel structure of PEMEC is obtained. The optimized PEMEC configuration demonstrates 9.75% enhancement in hydrogen production efficiency, accompanied by 27.4% increase in production rate and 23.6% improvement in peak power output. In addition, by introducing the field synergy principle for multi-physical field analysis, the optimized PEMEC improved the temperature uniformity by 18%, the drainage performance by 7.2%, and the average water content in the membrane by 5.38%. The new flow channel structure can effectively enhance the PEMEC electrolysis efficiency and improve the water flooding issues and local hot spot problems.

Accurately analyzing and predicting the dynamic characteristics of heat transfer systems is significant for improving the operating efficiency and stability of industrial and energy systems. This paper develops a novel dynamic model for heat exchangers (HXs) by defining the new concept of virtual dynamic Number of Transfer Unit (NTU) using the Fourier frequency-domain transformation. On this basis, we derive an analytical linear relationship between the inlet and outlet temperatures of the HX to directly characterize its dynamic heat transfer behavior. Moreover, the dynamic heat current models and inlet-outlet temperature relationships of series, parallel, and multi-loop HX networks are derived and provided to describe the dynamic performance. We conduct dual validation of the dynamic model's accuracy through both simulations and experiments, achieving the maximum dynamic response errors for individual HX of less than 0.6% and 0.2%, respectively. By developing a parameter identification algorithm for the heat transfer system and integrating it with a complex heat exchange network experimental system, we further verify that the maximum error in dynamic performance analysis of the heat transfer system using this dynamic model does not exceed 0.4%, thereby demonstrating its accuracy and feasibility for analyzing the dynamic characteristics of heat transfer systems. The proposed model and method can serve as a powerful tool for the accurate analysis and prediction of the dynamic characteristics of heat transfer systems.

Developing Desert-Gobi-Wasteland (DGW) energy bases is critical for scaling up renewable energy deployment and advancing the global energy structure transition. However, the inherent intermittency and volatility of wind and solar power hinder their large-scale integration. Chemical energy carriers (e.g., hydrogen, ammonia, methanol) have emerged as promising solutions for electrical energy storage to address this challenge. This study proposes a novel wind-solar-thermal-storage-hydrogen-ammonia-methanol (WSTS-HAM) integrated energy system for DGW energy bases, aiming to mitigate fluctuations in renewable power output. On this basis, an integrated planning and scheduling model is established to minimize the base's annualized cost and determine the optimal system capacity configuration. An 8760-h annual chronological production simulation is conducted, and system performance is evaluated using two key economic metrics: levelized cost of ammonia (LCOA) and levelized cost of methanol (LCOM). Jiuquan City in Gansu is selected as a case study, where the WSTS-HAM system is analyzed based on local wind and solar resource endowments. Results demonstrate that wind-solar complementarity significantly improves system economic efficiency and identifies an optimal wind-solar ratio that minimizes energy storage capacity requirements, with the minimum LCOA and LCOM reaching 7006.75 CNY/ton and 8949.58 CNY/ton, respectively. Besides, analysis of thermal power phase-out impacts reveals that the system's reliance on battery storage increases, while total system cost and carbon emissions both decrease continuously. Sensitivity analysis indicates that coal price fluctuations exert a greater impact on LCOA than on LCOM, with maximum increases of 2.72% and 2.22%, respectively.

Against the backdrop of accelerating low-carbon transformation in the global steel industry, hydrogen metallurgy has emerged as a pivotal pathway to reduce the industry's heavy reliance on high-carbon emission processes. However, existing hydrogen-based steelmaking systems are commonly constrained by the absence of comprehensive whole-process energy efficiency analysis methods, insufficient cascaded energy utilization, and poor adaptability to renewable energy sources-issues that significantly hinder their industrial application. This study aims to develop an efficient and low-carbon hydrogen metallurgy system by establishing a full-process exergy analysis methodology and cascaded energy recovery technologies to systematically address these critical bottlenecks. Accordingly, three progressively optimized hydrogen metallurgy systems are designed, integrating a holistic exergy analysis approach to enable cascaded energy utilization and enhance system-wide efficiency. The results show that compared with the first system, the exergy efficiency of the third has increased by 35.91 %, reaching 54.61 %. Meanwhile, the third one possesses the capability to integrate large-scale renewable energy (202.41 MW). The operating parameters of the key components are analyzed, and the optimal total thermal conductivity (kA) of the heat exchanger is determined to be 48,000 W/K, with the compressor exhaust pressure being 101.325 kPa. Uncertainty analysis is conducted on the compressor and PEM. It is found that when the motor efficiency fluctuates within a +/- 5 % range, the compressor maintains a stable near-linear response, with its exergy efficiency changing by only 0.57 %. However, the PEM is more sensitive to +/- 5 % changes in reversible voltage, which results in a 7.05 % decrease in its efficiency and a 41.2 % increase in its exergy destruction. This research fills the theoretical gap in system-level energy efficiency diagnosis. It delivers a systematic solution adaptable to renewable energy fluctuations, providing a technically innovative and engineering-feasible pathway for the low-carbon transition of the steel industry.

The intermittent and stochastic nature of renewable energy sources poses stern challenges to the frequency stability of new power system. The flywheel energy storage system (FESS), with its rapid response and high power density, plays a pivotal role in mitigating frequency fluctuations. To improve the performance of the FESS assisting thermal power unit (TPU), a collaborative optimization methodology of the capacity configuration and control strategy for FESS is presented in this paper. Aiming to enhance the primary frequency control (PFC) performance while minimizing the life-cycle cost of the FESS, this paper established a capacity configuration model based on a dynamic adaptive control strategy, in which FESS compensates for the lack of TPU frequency regulation capability and recovery state of charge (SOC) actively. A case study demonstrated that the optimization model proposed is suitable for different frequency scenarios. Furthermore, the results validated that the control strategy which is based on the SOC of FESS and frequency regulation capability of the TPU is economically more attractive compared to traditional strategies. In addition, this study revealed that a FESS with a charge/discharge rate of 7.5 C and rated power of 7.6 MW was appropriate for assisting a 600 MW TPU in PFC.

Solid-state electrolytes have a superior theoretical energy density, higher safety, and longer cycle stability. However, researching solid-state electrolyte materials with high performance remains difficult. Machine learning methods can accurately predict performance, speed up the screening process, reduce expensive and time-consuming experimental trials, and have significant advantages in the optimization and fabrication of solid-state electrolyte materials. This research constructed a solid-state electrolyte database based on existing data, trained a random forest (RF) algorithm model to achieve performance prediction of Na superionic conductor (NASICON) solid-state electrolytes by using only the component information, and analyzed the effect of different components. The optimization results screened and provided the optimal ratio of 61 doping elements, and meanwhile verified the accuracy and optimization of the model prediction results. The effects of different components on the ionic conductivity of solid-state electrolytes, including the descriptors used and types of doping elements, were distinguished. This study provides a reference for the optimization direction of solid-state electrolyte materials and the selection of components, which contribute to the exploration and development of high-performance solid-state electrolyte materials.

Solid Oxide Fuel Cells (SOFCs) are high-efficiency clean cogeneration devices. Accurately characterizing the complex coupling characteristics of heterogeneous energy between the stack and external auxiliary systems is critical for enhancing SOFC energy conversion efficiency. This study integrates heat transfer, mass transfer, and electrochemical processes into a unified energy circuit through standardized thermal resistance and equivalent circuit methods, establishing a cross-scale integrated power flow model for SOFCs. Furthermore, by combining the standard thermal resistance-based entropy generation rate formulation with traditional exergy analysis, parameter interactions and coupling mechanisms can be analyzed without introducing non-device-specific variables. Building upon this foundation, a comprehensive analysis was conducted to evaluate the impacts of SOFC structural and operational parameter variations on both energy and exergy efficiencies. The results demonstrate that increasing the thermal conductivity of the air preheater in the waste heat recovery system yields the most significant improvement in thermal recovery efficiency, achieving a 9

A collaborative analysis of the dynamic and safety characteristics of solid oxide fuel cell (SOFC) is essential for improving their flexibility in regulating combined heat and power and promoting renewable energy consumption. This paper develops a comprehensive dynamic model of the SOFC system by integrating both internal and external multiscale processes, using standard thermal impedance as a basis. Based on this, the proposed dynamic state space model enables real-time updates of the matrix of multi-state quantities and characterizes the key process parameters influencing heat transfer flexibility. Additionally, we optimized the load response process by considering multiple types of safety boundaries and developed a comprehensive and precise control strategy. The results show that the SOFC system can achieve a maximum load variation of approximately 1.4

Accurately capturing the dynamic interactions between the complex heterogeneous energies inside and outside a solid oxide fuel cell (SOFC) is the key to improving energy efficiency and flexibility. This research proposes a standard thermal impedance approach to construct a novel cross-scale dynamic model for the SOFC system by considering the external thermal management subsystem and the internal coupled multi-physics processes of heat transfer, mass transfer, and electrochemical fields. The constructed model realizes the all-round cross-scale dynamic characteristics from internal process to external heat exchange by using characteristic parameters. On this basis, we simulate and validate the proposed model of the SOFC system using Matlab/Simulink platform. The results show that this approach’s feasibility and convenience provide about 67.6% improvement in computational efficiency compared to the verification model. Besides, the parameter sensitivity and dynamic response of the SOFC system is analyzed, including varying inlet temperature, load current, fuel flow rate and operating pressure. The proposed model can provide computational efficiency and high accuracy in analyzing the SOFC system behavior and enabling more precise control strategies.

Energy storage systems, coupled with power sources, are applied as an important means of frequency regulation support for large-scale grid connection of new energy. Flywheel energy storage systems (FESS) are considered short-term energy storage solutions due to their capacity for rapid and efficient energy storage and release. However, the power output characteristic of flywheels is potentially correlated to the state of charge (SOC) in the process of continuous operation while the SOC distribution would be attributed to the output power and duration of the flywheel. This study theoretically developed analytical correlations between SOC distribution and flywheel dynamic characteristics on statistical performance based on a cross-entropy method under wide range sampling scenarios of SOC. The results demonstrate that various operation states of FESS have a disparity effect on the statistical performance of modules. A SOC management and capacity configuration method considering continuous operation states is proposed, and the results illustrate that the capital expenditure of capacity configuration cuts approximately 8.2% attaining the SOC stability under the homogenous frequency regulation scenario. Therefore, capacity configurations of FESS can effectively compensate for the capital loss caused by detrimental SOC so that the cross-entropy correlation method conducted in series has the capacity advantages.

The randomness and volatility of new energy output have led to serious curtailment of wind and solar, and the power system must enhance the capacity of renewable energy integration to cope with this problem. Many countries have established comprehensive market mechanisms, but in China the lack of market mechanisms is a primary factor leading to the low integration of renewable energy. The output of the wind farm matches the characteristics of the spot market. To improve the utilization rate of wind energy, this paper configures appropriate storage capacity for wind farm and considers spot market mechanisms. Under the guidance of making full use of energy storage characteristics, wind farm commands are decomposed and reconstructed, and the energy storage responds to high- and low-frequency commands separately. Based on market trading mechanisms, an objective function for the revenue of a wind-storage system in the spot market is established. The optimization algorithm is then employed under certain constraints to determine the energy storage configuration that maximizes economic benefits. The results indicate that by participating in the spot market with the wind-storage system, the deviation in power output can be reduced by 89.86%, and the average annual net profit can be increased by 47.1%. Additionally, further analysis of factors such as day-ahead (DA) bidding coefficients, energy storage price and market mechanism can further enhance the net profit of the wind-storage system. Results from the simulation model show that energy storage systems can significantly enhance the revenue of wind farms in the spot market. By attracting investment, they facilitate the development of renewable energy stations, thereby contributing to the transformation of the energy structure.

Deep exploration of user-side flexibility resources is crucial for large-scale renewable energy consumption. This paper proposed a typical integrated energy system (IES) that comprehensively includes wind power, photovoltaic, thermal power, combined heat and power, hybrid energy storage, and flexible load and constructed the system's unified power flow model based on the heat current method. On this basis, the regulation capabilities of different typical industrial and residential flexible loads were considered the symmetrical source-type load, which can transfer load and align user demand with the peaks and valleys of renewable energy generation, thus achieving power-energy decoupling. This contributes effectively to renewable energy accommodation capacity when the total electrical energy consumption remains constant. In both typical industrial and residential load scenarios, flexible load reduces integrated costs, increases renewable energy consumption, lowers peak thermal power generation, and decreases the requirement for a battery energy storage system (BESS). Besides, on typical industrial and residential load days, smoothing thermal power generation necessitates 12% and 18% flexible load, respectively, while replacing BESS requires 18% and 23% flexible load, respectively. Therefore, we can obtain the feasible operation ranges of symmetrical source-type load and provide suggestions for configuration capacity design of demand response in integrated energy systems.

New energy resources compromising intermittent and fluctuating natures have been integrated into the power grid on a large scale, and thermal power units are obliged to promote the depth of deep peak shaving and flexible response-ability to cope with this new scenario. The safety, flexibility, and high efficiency of coal-fired units are the ultimate goals of its transformation, and there is a mutual influence and mutual restriction relationship among these indicators. To exploit the flexibility of thermal power units, take into account efficiency and safety, and play a supporting role in the new power system, a control strategy that weighs various indicators needs to be developed. Based on heat flow model and dynamic state space model, and updated matrix in real time, the key process parameters affecting the flexibility of heat transfer can be fully characterized. By using the observed state and calculation, the load response index and the energy efficiency index are optimized under the boundary constraint. The results show that the multi-objective optimization methods can avoid over regulation, reduce the flue gas flow by 3.23%-3.59%, and reduce the fluctuation of state quantity under the premise of satisfying the load response rate, about 2.32%-2.52% away from the safety boundary of the design temperature parameter to achieve the flexibility of frequency modulation, high efficiency of energy transmission and operation safety.

Complete analysis of the dynamic characteristics of the proton exchange membrane electrolytic cell (PEMEC) is significant for its efficient and flexible utilization. To fully reflect the dynamic process including thermo-electric interactions within PEMEC, this paper disassembles this process and simplifies it for representation through a clear diagram of dynamic power flow. On this basis, we proposed a novel combined qualitative and quantitative analytical method for the comprehensive response by defining the evaluating indexes for PEMEC's response performance. Meanwhile, we analyzed the change pattern of dynamic response behavior, response time and the influence of thermo-electric interaction under multi-scenarios, like different voltage abrupt change magnitudes, different cathode operating pressures, and different inlet water temperatures. The results show that the PEMEC has the biggest response behavior with the longest response time under the largest external voltage variation magnitude. Besides, there is the shortest response time and smallest parameters total changes after response when the cathode operating pressure is 15bar Moreover, when the inlet water temperature is 40 degrees C it has the characteristic of quick action time and small response magnitude. The model, analysis method, and findings in this paper provide an effective reference for the operational regulation of PEMEC's thermal and electrical parameters.

Synergizing the relationship between environmental crisis, economic development, and social progress within different regions is of great significance for the green transformation of different regions and industries under the dual-carbon goal. This research provided a novel analytical model of "comprehensive deconstruction-clustering characteristics-regional evolution" based on the Log-Mean Division Index (LMDI) method to address the differences of regions in Chinese provinces. On this basis, different regions are comprehensively analyzed using economic, social, energy, and carbon emission data of Chinese provinces between 2004 and 2019. The carbon emissions of different provinces and cities with different characteristics are also deconstructed and analyzed from multiple perspectives, including energy structure, energy intensity, economic development, and population size. Based on the obtained industrial structure contribution ratio and industrial carbon emission ratio, provinces with similar characteristics were analyzed by region clustering. Moreover, the carbon emission trends of representative typical provincial and municipal industries are studied by considering three industries as the demarcation points. Finally, some energy saving and emission reduction suggestions are proposed from five perspectives, including tertiary industry, secondary industry, energy distribution, industrial distribution, and low GDP, combining with the current popular carbon trading market system.