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Current Situation and Prospects of the Low-Carbon Development of Thermal Power in China AI Introduction
Abstract：ObjectivesThe thermal power industry in China accounts for more than 40% of CO2 emissions, and its low-carbon transformation is the key to achieving the goal of carbon neutrality. Therefore, this study analyzes the current low-carbon development status of thermal power in China and proposes targeted carbon reduction governance pathways accordingly.MethodsFocusing on the actual situation of low-carbon development in the thermal power industry, this study analyzes core indicators such as installed capacity, proportion of power generation, unit structure, and carbon emission intensity, and combines with the current status of technology application and industrial layout to propose carbon reduction governance pathways. These pathways include accelerating the orderly phase-out of small coal-fired power units with high energy consumption and low efficiency, adjusting the structure of small coal-fired power units for efficiency improvement and energy conservation, and driving the comprehensive upgrading of the low-carbon transformation of the coal power industry; building a source carbon reduction pathway based on the co-firing of biomass energy and green-based fuels (green ammonia/green hydrogen), improving the closed-loop quality control chain of coal entering the furnace, and promoting the replacement with low-carbon and efficient coal-fired power units; and accelerating the deployment of R&D applications such as carbon capture, utilization and storage (CCUS) to achieve large-scale removal and conversion of CO2.ConclusionsThe proportions of installed capacity and power generation of thermal power in China are declining rapidly, the unit structure continues to be optimized, and the carbon emission intensity per unit of thermal power continues to decrease. However, gas-fired power accounts for a relatively low proportion in thermal power and improves slowly. The proposed governance pathways effectively promote the low-carbon transformation of the thermal power industry and provide theoretical support and practical reference for improving energy structure optimization and realizing the carbon neutrality goal. Additionally, the technical bottlenecks of green hydrogen/green ammonia in aspects such as storage, transportation, and economic efficiency urgently need to be overcome. The obstacles of CCUS in cost, efficiency, and large-scale application need to be addressed, and regional differences in resource endowment should be considered to coordinate and promote the overall optimization of the national energy structure.Keywords：thermal power;low-carbon development;energy conservation and efficiency improvement;source co-firing;carbon capture, utilization and storage (CCUS)94|57|1<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08Study on Degradation Performance of Mixed Amine Absorbent for Carbon Capture From Coal-Fired Flue Gas AI Introduction
Abstract：ObjectivesThe stability of chemical absorbents is key to the stable operation of chemical absorption carbon capture systems. Therefore, the oxidative and thermal degradation of a novel mixed amine absorbent BA-1 is investigated, along with the evaluation of anti-degradation agents.MethodsThe thermal degradation behavior of BA-1 is investigated using a thermal degradation experimental device under different temperatures (100, 120, and 140 ℃) and CO2 loading concentrations (0-1.5 mol/L). Meanwhile, the oxidative degradation performance of BA-1 is assessed at 65 ℃ under a pure oxygen atmosphere using an oxidative degradation experimental device. The degradation rate and degradation products of BA-1 are analyzed using cation and anion chromatography techniques. The antioxidant effects of 2,5-dimercapto-1,3,4-thiadiazole (DMTD), chelating agent E-1, sodium sulfite (Na2SO3), and acetaldehyde oxime (AAO) are tested.ResultsThe degradation of BA-1 is mainly caused by oxidative degradation. After the addition of E-1, Na2SO3, and AAO, the degradation rate of BA-1 is effectively suppressed. When 0.3% of E-1 is added, the degradation rate of BA-1 over 24 days is only 22.5%, with the degradation inhibition rate reaching 53.8%. The primary degradation products include formate, acetate, oxalate, and nitrate ions. The yield of oxidative degradation products is more than ten times that of thermal degradation products, further confirming that oxidative degradation is the main degradation mechanism of the BA-1 absorbent.ConclusionsThe degradation of mixed amine absorbents is mainly caused by oxidative degradation, and the addition of chelating agents can effectively mitigate absorbent degradation during industrial applications.Keywords：carbon capture;greenhouse gas;mixed amine absorbent;thermal degradation;oxidative degradation;antioxidant;carbon capture, utilization and storage (CCUS)38|22|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08Carbon Emission Sensitivity Analysis of Coal-Fired Power Plants Based on Life Cycle Assessment AI Introduction
Abstract：ObjectivesTo accurately calculate the carbon emissions of coal-fired power plants, combined with the actual production conditions of such plants, a refined life cycle carbon emission accounting study is carried out using a “cradle-to-gate” approach. The proportion of carbon emissions in each stage and its sensitivity characteristics are analyzed.MethodsTaking 4 typical 600 MW supercritical units as examples, a detailed calculation of the refined carbon emissions containing the entire stages of raw material acquisition, raw material transportation, power production, and waste disposal is based on the life cycle assessment method.ResultsThe carbon emissions from upstream stages, like raw material acquisition and transportation, account for 9.4% of the total emissions, with coal mining contributing the largest share, accounting for 5.77% of the total emissions. If the energy consumption in the coal mining stage is reduced by 5% and 10%, the carbon emissions over the life cycle of each unit can be reduced by 0.289% and 0.577%, respectively. The adoption of carbon capture technology can reduce the power plant carbon emissions by 78.8% to 82.3% under different scenarios.ConclusionsAs the main part of carbon emissions in the whole process of power production, coal combustion can reduce the coal consumption of unit power generation/supply by changing the combustion mode, improving the boiler efficiency and reducing the loss. The overall carbon emissions could be effectively reduced by the adoption of carbon capture technology. Although carbon capture increases energy consumption to a certain extent, it achieves a high carbon capture rate. The use of high-efficiency and low-energy carbon capture technology is a key means to reduce the carbon emissions of power plants.Keywords：coal-fired power plants;carbon emission reduction accounting;life cycle assessment;CO2 capture53|23|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08Thermodynamic Analysis of Heat Absorption Temperature Difference of Supercritical CO2 Recompression Cycle AI Introduction
Abstract：ObjectivesTo reduce the amount of molten salt in molten salt thermal energy storage tower-type solar thermal power generation systems, it is necessary to increase the heat absorption temperature difference of supercritical CO2, thereby enhancing the heat absorption and release temperature difference of the molten salt, therefore, modeling and analysis are carried out for the endothermic temperature difference of supercritical CO2.MethodsA supercritical CO2 recompression cycle model is established in EBSILON, and combined with theoretical derivation to analyze the heat absorption temperature difference of the main heater (ΔT1) and the reheater (ΔT2). A combination of theoretical analysis and simulation is employed to investigate in detail the effects of parameters such as the maximum cycle temperature, minimum cycle temperature, total cycle pressure ratio, high-pressure turbine pressure ratio, and shunt coefficient on the heat absorption temperature difference of supercritical CO2.ResultsIncreasing the maximum cycle temperature, and decreasing the minimum cycle temperature, total cycle pressure ratio, high-pressure turbine pressure ratio, and shunt coefficient can increase the main heater heat absorption temperature difference ΔT1. Increasing the maximum cycle temperature, total cycle pressure ratio, and high-pressure turbine pressure ratio can increase the reheater heat absorption temperature difference ΔT2. When the maximum cycle temperature increases, both ΔT1 and ΔT2 increase. Data show that when the maximum cycle temperature rises from 400 ℃ to 700 ℃, ΔT1 increases from 122.13 ℃ to 182.81 ℃, and ΔT2 increases from 54.47 ℃ to 67.23 ℃.ConclusionsBy adjusting cycle parameters, the heat absorption temperature difference of the supercritical CO2 recompression cycle can be effectively improved, thereby optimizing system performance. The results provide a theoretical basis for further optimization of the supercritical CO2 recompression cycle.Keywords：supercritical CO2 recompression cycle;main heater;heat absorption temperature difference;reheater;cycle parameters;solar thermal power generation;molten salt44|17|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08Performance Analysis of Ammonia-Doped Combustion in Micro Gas Turbine Combustion Chamber AI Introduction
Abstract：ObjectivesAiming at the problem of high carbon emission of micro gas turbine in distributed energy, this study investigates the combustion characteristics of a 10 kW micro gas turbine combustion chamber under ammonia-blended conditions.MethodsCFD simulations coupled with the detailed Okafor mechanism are conducted to analyze the effects of varying ammonia blending ratios and global equivalence ratios on combustion efficiency, NO and CO emissions.ResultsAs the ammonia ratio increases from 0 to 1.0, the fluid velocity in the combustion chamber outlet increases from 62.27 m/s to 63.69 m/s, and the total pressure recovery coefficient decreases from 97.81% to 97.18%. Additionally, CO mass fraction significantly decreases to near 0, while the NO mass fraction increases from 1.16×10-4 to 3.68×10-4, indicating that ammonia reduces CO emissions but increases NO formation. Combustion efficiency slightly declines from 98.14% to 97.64%. The equivalence ratio has a notable impact on performance and emissions, with lower NO emissions at low equivalence ratios, NO emissions peaking at an equivalence ratio of 1.0, and decreasing under fuel-rich conditions, though combustion efficiency also declines.ConclusionsThe application of methane/ammonia mixtures requires a balance among total pressure recovery coefficient, NO and CO emissions, and combustion efficiency. Further design optimization is needed to achieve efficient and low-emission combustion performance.Keywords：micro gas turbine;methane/ammonia fuel mixture;combustion characteristics;pollutant emissions;numerical simulation;ammonia blending ratios;equivalence ratio13|7|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08Study of Water Wall Flow Distribution and Mass Outlet Temperature Distribution in Ultra-Supercritical Boiler Based on Pot-Furnace Coupling AI Introduction
Abstract：ObjectivesWater wall over-temperature tube burst under deep peaking is one of the key problems facing the safe operation of boilers. A coupled boiler-furnace simulation method is proposed.MethodsThe heat flow distribution on the water wall surface under each operating condition is obtained by numerical simulation of combustion. Then, a calculation model of the mass side is established on the basis of Modelica, so as to study the distribution of water wall flow rate and the temperature distribution of the mass outlet of a 660 MW ultra-supercritical boiler.ResultsThe errors of key parameters of water wall outlet mass are all within 3%, which verifies the reliability of the model. The spiral water wall flow distribution shows negative flow characteristics at high loads and positive flow characteristics at ultra-low loads. Vertical water wall always shows negative flow characteristics, and the maximum temperature difference of the vertical water wall outlet mass is 37.60 ℃ at 100% turbine heat acceptance (THA), and increases to 138.33 ℃ and 141.27 ℃ at 40% THA and 30% THA, respectively. The (ultra) low load vertical water wall outlet mass temperature of the front and rear walls is high and the temperature difference is large, while the outlet mass temperature of the left and right side walls is low and the temperature difference is small.ConclusionsThe research results can provide a reference for the safe operation of the boiler under deep peaking.Keywords：thermal power generation;boiler safety;flow distribution;working fluid temperature;hydrodynamics;boiler-furnace coupling;deep peaking19|13|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08Low-Load Stable Combustion Technology of 600 MW Supercritical Low-Calorific Value Lignite Octagonal Tangentially Fired Boiler AI Introduction
Abstract：ObjectivesWith the high proportion of new energy generation units connected to the power grid, higher requirements are put forward for the deep peak shaving capacity of traditional thermal power units. However, low-calorific value lignite boilers are difficult to burn stably under low-load conditions, so they need to be optimized and adjusted according to the actual situation.MethodsBy changing the combustion organization to compress the height of the flame center and improve the flame filling degree, combined with optimized operating parameters, stable combustion of the boiler under low-load conditions can be achieved. To predict the stable combustion effect, a comprehensive model of flow, heat transfer, mass transfer and combustion is established to study the combustion characteristics of a 600 MW supercritical low-calorific value lignite octagonal tangentially fired boiler at different loads (from 100% to 35%).ResultsThrough local centralized coal feeding and operating No. 1, 3, 4, 5 and 7 coal mills, the minimum stable combustion load of a 600 MW supercritical octagonal tangentially fired boiler with a moisture content of 50% and a calorific value of 8.85 MJ/kg can reach 35%, and the NOx concentration at the furnace outlet does not change significantly under various loads.ConclusionsOptimizing local centralized coal feeding and coal mill operation modes can solve the problem of difficult stable combustion of low-calorific value lignite boilers under low-load conditions, and improve the deep peak shaving capacity of power plants.Keywords：thermal power units;octagonal tangentially fired boiler;deep peak shaving;low-load stable combustion;numerical simulation;low-calorific value lignite;combustion characteristics21|12|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08Numerical Simulation of Combustion of Waste Textile Pyrolysis Products in a 660 MW Coal-Fired Boiler AI Introduction
Abstract：ObjectivesThe waste textile pyrolysis products coupled with coal-fired power generation can not only increase the treatment capacity of waste textiles and reduce power production costs, but also contribute positively to carbon emission reduction in coal-fired power plants. Therefore, numerical simulation of combustion is carried out for this process route.MethodsA grid model of a coal-fired boiler is constructed, and the reaction mechanisms of pure coal combustion and pyrolysis gas combustion are coupled. On this basis, the grid independence and model rationality are validated, and the combustion numerical simulation is carried out with the three operating parameters of mass flow rate of waste textile pyrolysis products, overfire air ratio, and pyrolysis gas inlet position as independent variables.ResultsIn the three parameters have complex and significant influences on fly ash carbon content and NOx mass concentration at the furnace outlet.ConclusionsConsidering the safety, economic, and environmental performance of this process route, it is recommended to maintain the overfire air ratio at around 31% when the heat blending ratio of pyrolysis char and pyrolysis gas is lower than 10% and blended outside the furnace. As for the mass flow rate of waste textile pyrolysis products and the pyrolysis gas inlet position, appropriate values should be determined according to actual conditions and demand.Keywords：coal-fired boiler;waste textile;solid waste coupling;pyrolysis char;pyrolysis gas;co-firing;overfire air;numerical simulation24|14|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08
Power Generation and Environmental Protection
Regional Power Grid Automatic Generation Control Strategy Considering Energy Storage Participation AI Introduction
Abstract：ObjectivesTo address the coordination issue of frequency regulation resources such as energy storage, coal-fired units, and gas-fired units for area regulation requirement (ARR) allocation in power grids, a control strategy considering energy storage participation in regional power grid automatic generation control (AGC) is proposed.MethodsFirst, the regulation requirements of the regional power grid are divided into four zones: normal, sub-emergency, emergency, and dead zones. Then, based on large-scale energy storage ARR allocation, the regulation power of energy storage in AGC is calculated, and a balanced distribution strategy for state of charge (SOC) among energy storage stations is optimized. Finally, a priority rule is designed to prioritize energy storage system response under emergency conditions, ensuring effective coordination of frequency regulation resources.ResultsCase analysis with actual data from a specific region shows that this strategy outperforms traditional AGC methods in terms of control performance standard (CPS) indicator and frequency control accuracy, verifying the effectiveness of the proposed strategy.ConclusionsThis strategy effectively addresses the coordination of multiple control resources in frequency regulation, provides strong support for enhancing power grid stability and frequency regulation performance, and is of great significance for improving the reliability and stability of power grid operation.Keywords：regional power grid;energy storage system;power system;automatic generation control (AGC);frequency regulation resources;state of charge (SOC);regulation requirement;control strategy23|11|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08Optimal Planning of Electric Vehicle Charging Station Based on Spatio-Temporal Distribution Prediction of Charging Demand AI Introduction
Abstract：ObjectivesIn order to solve the mismatch between charging demand and supply caused by the rapid growth of electric vehicles, and the problems of high user dissatisfaction and great impact on the power grid caused by unreasonable planning of electric vehicle charging station (EVCS), a multi-objective EVCS optimal planning method based on the prediction of the space-time distribution of electric vehicle charging demand is proposed.MethodsFirst, the road network data is obtained through the OpenStreetMap open-source website, and it is visualized using QGIS software to establish a road network topology model. On this basis, a dynamic road network model including road grade, traffic flow, speed, and other parameters is established. Second, the road network nodes are divided into functional areas using point of interest data, and the spatiotemporal distribution of charging demand is predicted based on the analysis of relevant factors affecting the prediction of charging demand, the establishment of an energy consumption model and the judgment of charging demand. Third, the multi-objective EVCS planning model is established with the minimum comprehensive cost of EVCS, user dissatisfaction, and grid voltage fluctuation as the objective functions. Finally, the planning model is applied to the actual region, and the fast convergence multi‑objective equilibrium optimizer with archive evolution path (FC-MOEO/AEP) is used to optimize the model.ResultsThe proposed EVCS optimal planning model is feasible in the actual region, and the charging demand prediction model can accurately predict the charging demand distribution in the actual region, which provides the necessary data support for the reasonable planning of EVCS to a certain extent.ConclusionsThe proposed planning method provides a reference for the layout of EVCS and the participation of electric vehicles in power grid dispatching, and achieves a tripartite win-win situation among investors, electric vehicle users, and the power grid.Keywords：electric vehicle;dynamic road network;charging demand;spatio-temporal distribution forecasting;charging station planning29|10|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08Multi-User Short-Term Load Prediction Method Based on Frequency-Domain Enhanced Transformer AI Introduction
Abstract：ObjectivesLoad prediction is crucial for power system planning and operation. However, the high proportion of new energy increases source-load uncertainty, leading to greater volatility in the load of new-type power systems, which makes it more difficult to accurately predict multi-user load. To improve the accuracy of short-term load forecasting in new power systems, a multi-user short-term load prediction method based on frequency-domain enhanced Transformer is proposed.MethodsThe encoder in the Transformer is used to capture the feature information of multi-load sequences. The frequency-domain information is obtained by the discrete cosine transform (DCT), and the channel attention mechanism is used for data enhancement. The decoder in the Transformer is used to integrate the feature information which is then fed into the fully connected layer to obtain the prediction data. To verify the superiority of the proposed method, the Electricity dataset is used for case analysis, and a comparative analysis is conducted between the proposed method and five commonly used load forecasting methods.ResultsCompared with the traditional Transformer load prediction model, the error of the proposed method is reduced by 21.8%.ConclusionsThe proposed method demonstrates excellent accuracy and stability, showing feasibility for practical applications.Keywords：power load forecasting;new energy;source-load uncertainty;deep learning;Transformer model;discrete cosine transform;channel attention mechanism;data enhancement29|13|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08Resilience Enhancement Strategies for Integrated Energy Systems Against False Data Injection Attacks AI Introduction
Abstract：ObjectivesThe openness of the network makes integrated energy systems vulnerable to cyber attacks, focusing on the resilience enhancement of integrated energy systems (IES) against false data injection attacks (FDIA).MethodsA resilience enhancement framework is developed for IES under FDIA, and a system resilience assessment method is established, with the inclusion of both security and economic factors. Based on the analysis of energy flow and information flow attack mechanisms, an FDIA detection method for energy flow is proposed using continuous wavelet transform (CWT) and convolutional neural network (CNN). Additionally, an FDIA detection method for information flow is developed using CWT and general regression neural network (GRNN) model. The effect of FDIA on system scheduling is further analyzed, and an optimized scheduling model is established to enhance system resilience after experiencing cyberattacks.ResultsCompared with strategies without detection models, the resilience enhancement strategy incorporating CWT+GRNN detection models demonstrates better performance, with a 22.79% improvement in security and reliability, a 12.89% increase in operational economy, and a 19.82% higher resilience level. The resilience enhancement strategy incorporating detection models achieves performance levels close to those of normal operation without cyberattacks.ConclusionsThe proposed resilience enhancement strategy for IES based on CWT+GRNN detection model significantly improves system resilience after FDIA, bringing the system performance close to its normal operation level.Keywords：electricity-heat-gas;integrated energy system(IES);false data injection attack(FDIA);attack detection;optimized scheduling;resilience enhancement10|9|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08Improved Frequency Regulation Control Strategy of Wind Power Considering Random Fluctuation Characteristics of Source-Load AI Introduction
Abstract：ObjectivesLarge-scale wind power integration leads to a decrease in grid inertia, and the fluctuating power of wind turbines combined with random fluctuation of load under turbulent wind speed aggravates the frequency fluctuation in the power grid. Therefore, a wind power control strategy is proposed based on the comprehensive fluctuation of source-load, considering their random fluctuation characteristics.MethodsA mechanistic analysis is conducted to address the issue where traditional droop control strategy fails to provide reasonable power in response to source-load fluctuations at different levels, leading to poor frequency regulation performance. Based on the predicted turbulent wind speed and load fluctuations, a comprehensive variation of source-load is constructed. A frequency regulation control strategy based on the comprehensive variation of source-load is proposed, which involves feedforward correction of the active power reference value of the wind turbine to improve the wind turbine’s participation in grid frequency regulation.ResultsThe results of MATLAB simulation and wind turbine experimental platform show that this strategy improves the responsiveness of wind turbine frequency regulation to wind speed fluctuation, and demonstrates a significant advantage in terms of average frequency deviation and degree of frequency drop under random source-load fluctuations.ConclusionsThis strategy effectively improves the issue between the wind turbine’s own operation and its participation in frequency regulation under source-load fluctuations, and is of significant importance for improving the frequency regulation capability of power grids with a high proportion of renewable energy.Keywords：dual carbon;wind power;droop control;primary frequency regulation;turbulence characteristics;source-load fluctuation20|10|1<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08
New Power System
Low-Carbon Economic Scheduling of Virtual Power Plants With Hydrogen-Blended Gas and Liquid-Storage CCS Coupled P2G AI Introduction
Abstract：ObjectivesIn the process of achieving the “dual carbon” goals, virtual power plants, as a new energy management system, can enhance the flexibility and energy efficiency of the power grid. Issues such as the failure of coupling between power-to-gas (P2G) and carbon capture system (CCS), low energy utilization efficiency, high volatility of renewable energy, and insufficient incentives from emission reduction policies have affected the economic viability of virtual power plants. Therefore, an optimized scheduling model that balances low-carbon and economic considerations is proposed based on liquid storage CCS and gas hydrogen blending equipment.MethodsFrom the two perspectives of innovative low-carbon equipment and carbon trading policy, mathematical models are first established for the liquid-storage carbon capture system coupled with power-to-gas equipment, gas turbines, electric heating furnaces, and energy storage equipment. Secondly, tiered carbon trading prices are designed for different carbon emission levels, and price compensation factors and price growth factors are introduced to incentivize virtual power plants to reduce emissions. Optimized scheduling strategies with economic and low-carbon objectives as the target functions are proposed. Finally, the model is processed using a linearization method for efficient solution. Case analysis sets different hydrogen blending ratio scenarios, different coupled equipment scenarios, and different carbon trading mechanism scenarios to validate the effectiveness of the proposed model.ResultsCompared with the virtual power plant before modification, variable hydrogen blending operation and the liquid-storage P2G-CCS coupling equipment reduce operating costs by 6.21% and 12.62%, respectively, and the tiered carbon trading price reduces carbon emissions of the virtual power plant by 12.96%.ConclusionsThe proposed scheduling model can effectively achieve low-carbon emissions, enhance wind power integration capability, and reduce operating costs of virtual power plants.Keywords：virtual power plants;low-carbon scheduling;carbon capture;tiered carbon trading;hydrogen-blended gas15|9|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08- Abstract：ObjectivesDuring the electric vehicle (EV) charging guidance process, users have different preferences in selecting charging stations, resulting in different selection criteria, which affects their participation in optimal scheduling. Therefore, considering user habits in selecting charging stations and the conflicts of interest between users and charging aggregators, an EV charging guidance strategy that incorporates target charging station selection habits is proposed.MethodsSelf-organizing feature mapping (SOFM) is used for user profiling, and Shapley additive explanations (SHAP) are utilized to determine the optimal profiling results. Secondly, the entropy weight method is applied to determine the weights of time cost and economic cost for each type of user during the charging station selection process. Based on the weight results, user economic cost and time cost are normalized into user satisfaction. Then, users are guided to charge based on their user satisfaction.ResultsThe example shows that compared with the shortest path The numerical example shows that compared with the shortest path algorithm, this strategy significantly improves user satisfaction in selecting charging stations and the profit per unit time of charging piles. Additionally, this strategy is less affected under different traffic conditions.ConclusionsThis strategy effectively addresses the impact of user charging decision preferences on charging guidance, which is of great significance for improving user charging benefits and reducing charging congestion.Keywords：electric vehicle (EV);decision preferences;user profiling;charging guidance;economic cost;time cost;satisfaction14|9|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08
Virtual Power Plant
Research on Optimization of Control Strategy for Energy Storage Systems Considering Battery State of Charge AI Introduction
Abstract：ObjectivesDistributed energy storage systems exhibit slow state of charge (SOC) equalization and low current distribution accuracy due to inconsistency in the SOC and capacity among battery cells. To address these issues, a control strategy for energy storage systems that considers SOC for energy storage units with different capacities is proposed.MethodsThe strategy improves droop control by integrating the SOC difference with the droop coefficient using an inverse tangent nested power function. The variable acceleration factor in the droop coefficient is dynamically adjusted according to the SOC difference to achieve better equalization. Additionally, virtual voltage and DC bus voltage compensation are incorporated to achieve accurate output current distribution while ensuring bus voltage stability.ResultsThe optimized variable acceleration factor reduces the SOC equalization time by approximately 50% compared to the fixed acceleration factor. The output current remains consistent with the capacity ratio without compromising SOC equalization performance.ConclusionsThis control strategy improves SOC equalization speed and output current distribution accuracy among energy storage units with different capacities.Keywords：distributed energy storage system;microgrid;battery;state of charge;droop control;variable acceleration factor;equalization speed;voltage compensation19|12|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08Research Progress on Compressed Air Energy Storage and Hydrogen Energy Coupling Systems AI Introduction
Abstract：ObjectivesCompressed air energy storage-hydrogen energy (CAES-HE) coupling systems show prominent advantages in the fields of low-carbon energy transition, the construction of new-type power systems, large-scale peak shaving of the power grid, and large-scale hydrogen consumption. To clarify the current research status of the CAES-HE coupling systems, identify the key scientific and technological issues that need to be addressed, and outline future development directions, a review of relevant studies in this field is conducted.MethodsThe technical routes and characteristics of different CAES-HE coupling systems are analyzed. The key scientific and technological issues that need to be addressed in different coupling systems, along with their current research status, are summarized. On this basis, the future development directions of CAES-HE coupling systems are discussed.ResultsCurrently, four types of CAES-HE coupling systems with different technical routes and characteristics have been proposed. To promote the large-scale development of different CAES-HE coupling systems, research and breakthroughs are still needed in areas including the development of new coupling processes, key common technologies for hydrogen production and storage, hydrogen gas turbine technology, methanation reaction mechanisms, and reactor optimization.ConclusionsCAES-HE coupling systems are one of the most promising development directions in the future, and promoting their large-scale deployment and engineering implementation requires in-depth research and collaborative efforts across multiple disciplines and fields.Keywords：compressed air energy storage;liquid air energy storage;hydrogen energy;system coupling;energy storage21|11|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08
Energy Storage
Performance Analysis of Wind-to-Heat Unit Coupled With Solar Photovoltaic Thermal System AI Introduction
Abstract：ObjectivesWith the proposal of the “dual carbon” goals, China is continuously promoting the adjustment and optimization of the energy structure to achieve the green transformation and sustainable development of the energy industry. To further diversify the forms of renewable energy utilization, it is necessary to investigate the coupled system of wind-to-heat unit and solar photovoltaic thermal (PV/T) technology.MethodsMathematical models of each component are established in MATLAB/Simulink. The operating characteristic curves of the wind-to-heat unit from cut-in wind speed to rated wind speed are simulated. The variation trends of the outlet water temperature of the solar PV/T module with ambient temperature under different solar radiation intensities, and the performance curves of the wind-to-heat unit coupled with the solar PV/T system, are analyzed.ResultsThrough the simulation of the heat production of the wind-to-heat unit coupled with the solar PV/T system within one day in winter, the results demonstrate that the system can adequately meet the thermal load of users, and the electric energy generated by the solar PV/T module is also available for use.ConclusionsThe system effectively improves the overall utilization efficiency of clean energy, provides a new solution for the efficient utilization of clean energy, and offers a reference for the further optimization of energy structure and green transformation.Keywords：clean energy;wind energy;solar energy;wind-to-heat unit;photovoltaic thermal (PV/T);heat supply;coupling system;performance analysis20|10|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08Thermal Performance Simulation of Solar Thermal Power Tower System Based on Supercritical CO2 Brayton-Organic Rankine Cycle AI Introduction
Abstract：ObjectivesThe supercritical CO2 (SCO2) Brayton cycle offers higher power generation efficiency compared with conventional steam Rankine cycles, which has good application prospects in solar power generation (SPT). Therefore, the thermodynamic performance of an SCO2 Brayton cycle-based SPT system for solar thermal power generation is studied.MethodsA recompression SCO2 Brayton cycle (SCRBC), known for its high thermoelectric conversion efficiency, is employed as the top cycle, while an organic Rankine cycle (ORC) is served as the bottom cycle to recover waste heat from the SCRBC. A simulation model for the SCRBC/ORC-based SPT system (SCRBC/ORC-SPT) is developed using Matlab. Among six initially selected ORC working fluids, R600 is chosen as the bottom cycle working fluid for the SCRBC/ORC-SPT system. From a thermodynamic perspective, the impact of key parameters on the thermodynamic performance of the SCRBC/ORC-SPT system is analyzed. With the goal of maximizing system power generation efficiency, a genetic algorithm is applied for global parameter optimization.ResultsThe system efficiency first increases and then decreases with the increase in the split ratio and turbine inlet pressure, indicating the existence of optimal split ratio and optimal cycle pressure ratio that yield the best thermodynamic performance of the system. Moreover, the optimal split ratio exhibits a monotonically increasing trend with the increase in cycle pressure ratio. Increasing the turbine inlet temperature and lowering the main compressor inlet temperature can effectively enhance the system’s power generation efficiency to some extent.ConclusionsThe maximum power generation efficiency and exergy efficiency obtained by the optimized SCRBC/ORC-SPT system are 34.19% and 36.80%, respectively, which are effectively improved by 4.31% compared with the SCRBC-SPT system. The findings provide theoretical support for enhancing the power generation efficiency of conventional SCO2 Brayton cycle-based SPT systems and promoting the application of SCO2 Brayton cycle power generation technology.Keywords：solar power tower (SPT);supercritical CO2 (SCO2);Brayton cycle;organic Rankine cycle (ORC);combined cycle;thermal performance simulation;parameter optimization15|11|1<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08
New Energy
Research on Fault Tolerance Mechanism for Scientific and Technological Innovation in Power Industry AI Introduction
Abstract：ObjectivesTo serve the national major strategy of “carbon peaking and carbon neutrality”, the power industry needs to promote the transformation of energy structure through scientific and technological innovation. Scientific and technological innovation in the power industry is characterized by high investment, long cycle, and strong uncertainty, making it imperative to establish a fault tolerance and error correction mechanism that “encourages innovation and tolerates failure”.MethodsThe theoretical foundation for fault tolerance and liability exemption is established by integrating multidisciplinary theories and drawing on international experience. In terms of institutional design, the four-element model for liability determination—consisting of “object, objective aspect, subject, and subjective aspect”—is adapted to characteristics of the power industry, and three-type classification is proposed: legitimate motivation type, minor liability type, and procedural rectification type. On this basis, a complete institutional system is constructed, covering a two-step identification method, a list of specific circumstances, and full-process procedures.ResultsThe fault tolerance and liability exemption mechanism can alleviate researchers’ concerns about innovation, stimulate the vitality of participating entities, and play a positive role in promoting scientific and technological innovation in the power industry.ConclusionsThe research findings effectively balance the safety of state-owned assets and the tolerance for innovation risks, provide an operable fault tolerance and liability exemption scheme for scientific and technological innovation in the power industry, and offer a solid institutional guarantee for accelerating the construction of a clean, low-carbon, safe, and efficient new energy system.Keywords：power industry;scientific and technological innovation;fault tolerance and error correction;liability exemption and reduction;carbon emission10|9|0<HTML><L-PDF> <WORD> <Meta-XML>Updated：2026-06-08
Innovation Management
