Integrated Photovoltaic Power to Hydrogen and Refueling （IPp2HR）systems effectively utilize solar energy resources,providing green hydrogen for hydrogen-powered transportation and other industries.They are a promising pathway for green hydrogen demonstration.However,current research on IPp2HR systems either overlooks the operational constraints of purification or focuses solely on day-ahead scheduling.Traditional purification systems use fixed operational sequences to dry crude hydrogen,which conflicts with the flexible,variable-load operation required to accommodate renewable energy fluctuations.To address this,a bi-level energy management method is proposed to improve IPp2HR system efficiency.First,a comprehensive model covering power to hydrogen,purification,storage,and refueling is developed.The purification process is transformed into a Mixed-Integer Linear Programming （MILP）model using the Big-M method and integrated into the scheduling framework.Second,a bi-level energy management framework is designed,combining day-ahead and rolling scheduling with real-time control.The day-ahead and rolling stages determine the on/off of electrolyzers based on PV forecasts and hydrogen demand,while the real-time stage adjusts power deviations to enhance PV utilization and operational benefits.A case study based on a hydrogen refueling station in Northeast China validates the proposed method.Results show that considering the purification heating and cooling logic prevents high-cost hydrogen caused by the inability to shutdown at high temperatures.The bi-level framework effectively coordinates day-ahead,rolling,and real-time stages,improving both PV utilization and operational profitability.

With the rapid development of mobile energy storage systems （MESS），their importance in power system dynamic response,renewable energy integration,and emergency power supply has become increasingly prominent.However,challenges such as multi-objective resource allocation,path optimization under transportation-grid coupling constraints,and planning-scheduling coordination remain unresolved.Traditional methods struggle to address these issues due to computational complexity and insufficient dynamic adaptability.In contrast,artificial intelligence （AI）algorithms,leveraging data-driven technologies like reinforcement learning （RL）and graph neural networks （GNN）， have achieved breakthroughs in dynamic scheduling,collaborative optimization,and security-economy trade-offs.This paper systematically analyzes AI applications in MESS planning and scheduling,summarizes the advantages of deep reinforcement learning （DRL）in uncertainty decision-making and swarm intelligence （SI）algorithms in distributed coordination,and identifies research gaps in battery state of charge （SOC）modeling and cross-domain collaborative scheduling.Furthermore,an AI-empowered innovative framework for MESS planning and scheduling is proposed, offering theoretical foundations and practical pathways to enhance the resilience,economy,and low-carbon transition of power systems.

How to achieve efficient and precise control of multi-band radiation properties is a common scientific challenge in military camouflage,aerospace,solar energy and other fields.Conventional radiation property control often uses inefficient trial-and-error optimisation of functional groups or micro-nanostructures,which is time-consuming, laborious and difficult to obtain the best radiation properties.The emergence of machine learning has overturned the traditional optimisation methods and greatly improved the efficiency of radiation property optimisation and design by simulating the brain's learning and thinking.In this paper,machine learning algorithms in radiation property regulation are discussed in detail,and their advantages and challenges in terms of accuracy,scalability and efficiency are evaluated；the advanced results of the fusion of machine learning and radiation property directional regulation are summarised in a systematic way,including forward radiation response prediction and material directional optimal design；and finally,the hot spots of the research on the combination of radiation property regulation and machine learning and the direction of future development are explored.By reviewing the existing literature,this paper provides a reference for the design and application of radiation property directional regulation and machine learning algorithms, and makes suggestions for further optimisation and innovation of radiation property directional regulation.

The use of electric hydrogen generation to consume the wind power abandoned in the integrated energy system with high percolation rate is an effective method to save energy and reduce carbon,but there exists the problem of improper power distribution of electric hydrogen generation array operation,which leads to the serious imbalance of the life span of each single tank,and greatly reduces the life span of the whole system of electric hydrogen generation, which needs to be solved urgently.The paper proposes a multi-timescale regulation strategy for the integrated energy system that takes into account the rotational start/stop of the electric hydrogen array.In the day-ahead phase,the rotational start/stop strategy of the electric hydrogen array is designed to equalise the system life depreciation；in the intra-day scheduling phase,the economic and low-carbon objective is to ensure the supply of the load demand；and in the real-time phase,the day-ahead real-time purchased power deviation is offset by the flexible use of the energy storage,so as to minimize the impact of the stochastic volatility of the lower-level integrated energy system on the power grid.The real-time phase,the energy storage is used to flexibly offset the day-ahead-real-time power purchase deviation to minimise the random volatility of the lower-level integrated energy system on the grid.Finally,engineering examples are presented to verify the economic,low-carbon and reliability advantages of the strategy.

Application of hydrogen-enriched combustion in natural gas generator unit could reduce CO2 emission and promote transformation development for low-carbon in Chinese electric power industry.In this paper,a simplified model of combined cycle using hydrogen-enriched natural gas was established for a 9FA gas-steam combined cycle generator unit.Variations of performance,carbon emission and their influences on power generation economy were all investigated under different hydrogen-enriched ratio and different ambient temperature.The results showed that：Hydrogen-enriched combustion in combined cycle lead a decrease of cycle efficiency and a significantly reduction of CO2 emission.When hydrogen ratio was increased from 0 to 30%，the revenue of generator unit decreased by 52.98%under computational conditions,which significantly affected the economy of combined cycle unit.Cycle performance was better at a higher ambient temperature,and the changing trend was maintained after the introduction of hydrogen.

为给电力系统规划提供精准数据支持，提出一种改进自适应噪声完备集合经验模态分解（Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise,ICCEMDAN）和庥雀搜索算法（Sparrow Search Algorithm,SSA）改进长短期记忆神经网络（Long-Short Term Memory neural network,LSTM）的空间负荷预测方法。首先，应用箱形图离群点检测法对电力地理信息系统中Ⅰ类元胞历史负荷的离群点进行检测及校正；其次，运用ICCEMDAN技术将校正后的I类元胞负荷时间序列分解为不同频率和幅值的模态分量；然后，针对每个模态分量分别建立各自的LSTM模型，并利用SSA对各LSTM模型的参数进行优化，将得到的所有模态分量结果线性重构，得到目标年的基于I类元胞空间负荷预测结果；最后，应用空间电力负荷网格化技术，转化I类元胞的空间负荷预测结果为Ⅱ类元胞预测结果，并以幅值大小和空间分布两个维度评价预测精度。算例分析结果表明，文中所提出方法能够提升空间负荷预测精度。

Aiming at the uncertainty of distributed photovoltaic （PV）power generation and the overall low utilization rate of the equipment,which leads to the problem of rising cost faced by distribution network planning,a grid planning method considering the utilization rate of distributed PV equipment is proposed in the paper.By using information entropy to extract scenarios from PV output data,a set of typical scenarios is obtained.Based on these scenarios,a joint optimization model of distributed PV storage operation-planning is developed in the paper:at the upper level,the distributed PV and storage are selected and sited with the objective of minimizing the investment and construction cost and maximizing the utilization rate of distributed PV；at the lower level,the distributed PV power and storage are optimized with the objective of minimizing the cost of discarded light,network loss,operation and maintenance,and purchased power,and the planning model solves the optimization problem.In the lower layer,the distributed PV power and storage charging/discharging power in each time period are optimized with the objective of minimizing the abandoned light cost,network loss cost,operation and maintenance cost,and purchasing power cost,and a modified particle swarm algorithm is used as a method for solving the planning model.Finally,the IEEE 33 node system is used as an example for scenario analysis,and the results show that the proposed method can improve the utilization rate of PV equipment,improve the stability of distribution network operation,and reduce the comprehensive cost.

The high proportion of renewable energy networking,represented by wind energy,has brought new challenges to the power system.Hydrogen energy storage technology is an effective way to smooth out fluctuations in renewable energy power and improve the economic and low-carbon performance of comprehensive energy systems.On the basis of analyzing the power regulation capability of a high proportion wind power interconnection system,it is pointed out that wind hydrogen coupling can reduce system wind abandonment and power shortage.The worst-case scenario cost is an important indicator for evaluating the operational status of a system under uncertain factors.Based on uncertain scenarios,a stochastic p-robust optimization method combining basic stochastic optimization and robust optimization is proposed to ensure stable operation of the system in the worst-case scenario.Taking into account both economic and environmental benefits,a unit commitment optimization model with dual objectives of expected cost and carbon trading cost was established under p-robust constraints.The results of the example show that the stochastic p-robust optimization method effectively reduces the expected cost of the system.The established unit combination optimization model can flexibly optimize the output of multi energy systems based on different objective weights,reduce abandoned wind power,and improve wind power utilization.

This paper proposes a capacity configuration method for a photovoltaic hydrogen storage coupling system that takes into account the flexibility constraints of distribution network operation,in response to the problems of high proportion of photovoltaic access leading to voltage exceeding limits,branch power imbalance,and high curtailment rate in the distribution network.Firstly,based on the improved K-means clustering algorithm,load scenarios are divided, and on the basis of considering voltage and power factors,as well as constraints such as Distflow's flow model and second-order cones of line voltage and current,distribution network flexibility indicators are established from both spatial and temporal perspectives；Secondly,taking into account constraints such as flexibility and power balance,an optimization configuration objective function is constructed with the goal of minimizing the cost of electricity per kilowatt hour；Then,an optimization operation strategy for the photovoltaic hydrogen storage coupling system based on net power conditions is proposed,and an improved particle swarm optimization algorithm is used to solve the optimization configuration model.Finally,the effectiveness of the optimization configuration method proposed in this paper is verified through a case study of the actual grid structure of the glass Kezi substation area in Jiaohe City,Jilin Province.

In order to meet the real-time requirements of the new power system for transient stability emergency control,a transient stability generator tripping control method based on generator current and angular frequency response characteristics is proposed.Firstly,the relationship curves between current and angular frequency are drawn when the system is stable and unstable,and the relationship between current and angular frequency and transient stability is studied.The key characteristics of power angle stability and power angle instability are extracted,and the transient power angle stability criterion based on I-ωresponse characteristics is constructed.Secondly,the slope characteristics of the I-ω relationship curve are studied,and the relationship between the slope of the relationship curve and the transient stability under different proportion of generator tripping control is explored.Based on the generator rotor motion equation,the relationship between the slope of the relationship curve and the amount of generator tripping control is derived,and a calculation method of emergency generator tripping control based on the slope of the relationship curve is proposed.After that,the power angle instability criterion is used as the starting criterion of emergency control,and the generator tripping index considering the influence of generator power angle and kinetic energy contained in the rotor is defined.The fast selection of the generator tripping control location is realized, and a reasonable allocation method of generator tripping control quantity is given.Finally,the proposed method is simulated in the classical second-order one machine infinite bus system and the New England 10-machine 39-bus system with wind turbines,and the effectiveness of the proposed method is verified.

The production of "green hydrogen"by electrolyzing water from offshore wind power is an important technological direction for promoting the consumption of new energy and achieving deep decarbonization in the power and chemical industries.With the shift of offshore wind power hydrogen production from nearshore hydrogen transmission to offshore hydrogen transmission,utilizing existing offshore oil and gas platforms and pipelines for centralized hydrogen production from offshore wind power is one of the main directions for obtaining"green hydrogen"in the future.However,the design and application of centralized hydrogen production equipment for offshore wind power are constrained by problems such as small insulation margin and difficult optimization design of medium voltage and high-frequency transformers.The article proposes an intermediate frequency isolated offshore wind power centralized hydrogen production equipment based on Modular Multilevel Matrix Converter （M3C）to address the above issues.The equipment uses an M3C converter in the front stage and a 12 pulse thyristor rectifier in the rear stage to achieve intermediate frequency isolation and avoid insulation design difficulties.The high current stress of the thyristor enables high-power hydrogen production,and its key parameters are optimized.Finally,a simulation platform for the proposed hydrogen production equipment was built using MATLAB/Simulink simulation software to verify its effectiveness.

In order to adapt to the "dual carbon"transformation goal of future electric power development in Jilin Province,considering the role of multiple influencing factors under the new situation,it is necessary to integrate social and carbon emission related influencing factors to improve the accuracy of power demand forecasting.In the current context,the existing models are still facing challenges in terms of stability and accuracy of electricity demand forecasting.In order to address these challenges,firstly,multiple factors affecting power demand are analyzed through system dynamics model.Based on rigorous correlation analysis,key indicators that have a significant impact on power demand are further screened.Six strongly related indicators,namely permanent population,industrial added value,total energy consumption,low-carbon index of energy consumption structure,per capita GDP and GDP,were determined, and the introduction of carbon emission indicators was increased,highlighting the innovative attention in the "double carbon"aspect.Then,Particle Swarm Optimization （PSO）was used to optimize the key parameters of the Support Vector Machines （SVM）model,and the PSO-SVM power demand prediction model was constructed.The problem that the existing model is easy to fall into the local optimal solution is overcome.The effectiveness of the PSO-SVM model is verified by comparison with the traditional SVM model,BP model and the optimized PSO-BP model.In power forecasting,the model not only has high accuracy,but also shows a faster training speed.Finally,the forecast model is applied to the power demand forecast of Jilin Province from 2023 to 2028，which provides a strong support and reference for power planning and decision-making.

Under the goal of "dual carbon"，virtual power plant is an effective vehicle for optimizing multi-regional resource allocation and increasing renewable energy penetration.Against this background,the paper proposes a coordinated and optimal scheduling strategy for virtual power plants that considers the participation of waste incineration under the stepped carbon trading mechanism.First,a new power system structure including multiple power plants and multiple energy storage is constructed from the system structure.In order to fully explore the potential of power generation and gas production in waste incineration power plants,an analytical study is carried out for dry and wet waste electrical cogeneration,and a mathematical model of waste incineration power plants is established.Secondly, the joint operation mode of power-to-gas and carbon capture is adopted,and a carbon capture-power-to-gas-hydrogen fuel cell subsystem model is constructed to formulate the joint operation strategy of multiple power plants and multiple energy storage.Again,the carbon trading mechanism is introduced,and a laddered carbon trading calculation model is constructed and analyzed for the price base price,interval length and price growth rate in the model.Finally, with the objective function of minimizing the sum of thermal power cost,purchased energy cost,carbon emission cost, equipment maintenance cost and scenery cost,the coordinated optimal scheduling model of virtual power plant is established,and the model is optimally solved by using the CPLEX solver of Matlab software in multiple scenarios.

The configuration of energy storage power station on the grid side can effectively increase the peak shaving capacity of the system and the amount of wind and light consumption.However,the investment cost of electrochemical energy storage power station is high.How to reasonably configure the energy storage capacity is an important basis for improving efficiency and expanding application scenarios.From the perspective of the grid side,this paper proposes an optimal configuration method of energy storage capacity considering equivalent life loss and multi-dimensional benefits.Firstly,the life parameters of energy storage battery are analyzed,and the equivalent life loss model of energy storage is established to increase the adaptability of the model to the real scene.Secondly,the annual cost function of system operation cost and energy storage investment operation and maintenance is quantitatively calculated.At the same time,the income of peak-valley price difference of energy storage on the grid side,the income of auxiliary peak regulation and the income of delaying equipment transformation are taken into account.Finally,the constraint relationship between the equivalent life loss and the energy storage operation strategy is embedded into the model to solve the optimal configuration capacity of the energy storage side and the optimal charging and discharging operation strategy of the energy storage battery.The simulation results show that the model can effectively improve the economy of energy storage power station in the application scenario of this paper.

Grid-forming virtual synchronous generator （GFVSG）has certain virtual inertia and virtual damping support capabilities by introducing the rotor motion equation of synchronous generators,but it inevitably introduces active-power dynamic oscillation problems into the GFVSG grid-connected parallel systems.As one of the important improvement measures to effectively solve the active-power dynamic oscillation problems existing in the GFVSG grid-connected/parallel systems,transient damping methods have recently attracted widespread attention and have achieved rich theoretical research as well as practical application results.This paper analyzes the working principle and main role of transient damping methods in GFVSG control,summarizes the typical implementation methods and research status of transient damping methods,and analyzes,summarizes,and discusses the research prospects,possible challenges may be faced,and key technical problems that need to be overcome in the future of transient damping methods.

The accuracy of wind power prediction has a significant impact on the operation of the power system.This paper proposes a wind power ultra short term prediction method based on kernel principal component analysis combined with attention mechanism using short-term and short-term memory neural networks.This method performs kernel principal component analysis to reduce the dimensionality of all features in the wind farm dataset.And the Attention mechanism is introduced,using LSTM to allocate more attention to feature elements that have a significant impact on the power at the prediction time,in order to achieve more accurate prediction results.The experimental results show that the proposed prediction model can effectively achieve ultra short term prediction of wind power,and has higher prediction accuracy compared to traditional BP neural networks and LSTM networks.

In the context of dual carbon,technologies such as Carbon Capture and Storage （CCS）and Power-to-Gas（P2G）are the key to realizing low-carbon economic operation of the Integrated Energy System （IES）。important means.In order to take into account the low-carbonization and economic benefits of IES,this paper proposes a low-carbon IES optimal dispatch model including CCS-P2G.First,at the technical level,IES combines a carbon capture power plant with a solution storage and a two-stage power-to-gas device,and analyzes the linear relationship between carbon dioxide mass and solution volume and CCS operating energy consumption and total output to further simplify the CCS model.At the same time,the conventional hydrogen storage tank model is improved,reducing the computational burden required.Secondly,at the market mechanism level,the paper introduces a carbon trading mechanism and a wind power trading mechanism.Finally,an optimal scheduling strategy based on minimizing the total operating cost of IES as the objective function is proposed.Different scenarios were set up for comparative analysis to verify the effectiveness of the scheduling plan.

In the context of carbon peaking and carbon neutrality,various industries in China are flourishing and their dependence on energy is increasing.New clean energy is gradually replacing fossil energy with its clean and pollution-
free advantages.However,due to the power fluctuation and intermittency of new energy photovoltaic power generation, and generally working at maximum power,it is unable to provide or absorb additional energy to respond to grid frequency events.At the same time,a large number of new energy and power electronic equipment are connected to the grid,leading to a sharp decline in the system's anti-interference ability.Therefore,in order to solve the above problems,this article uses energy storage devices to suppress the power fluctuations of photovoltaic power generation, improve the utilization rate of solar power generation,and improve the traditional second-order synchronous machine control of inverters.A first-order transient voltage control is introduced to simulate the third-order model of synchronous machines,and a joint active support control strategy for photovoltaic energy storage is proposed to provide better voltage frequency support for the power grid.The superiority of active support for photovoltaic energy storage is verified through simulation.

With the increase of wind power penetration rate,the response ability of doubly-fed wind turbines to grid frequency gradually weakens,which has a huge impact on the frequency stability of the system.The independent frequency regulation capability of the doubly-fed wind turbines is currently insufficient to meet the frequency deviation requirements of the system,and it will result in high wind power permeability and low energy utilization rate.Therefore, energy storage equipment will be installed on the grid side of the doubly-fed wind turbines to form a wind storage joint system to participate in the primary frequency regulation of the system.In the article,a variable coefficient wind storage joint system based on the rotor speed and state of charge （SOC）is proposed to participate in the primary frequency regulation control strategy by utilizing the rotor kinetic energy of the wind turbine and the output of the energy storage equipment to jointly undertake the primary frequency regulation power demand.The doubly-fed wind turbine responds to the virtual inertia link by releasing or absorbing its own rotor kinetic energy,and dynamically adjusts the virtual inertia coefficient through its own rotor speed,andthe energy storage device dynamically adjusts the virtual droop coefficient based on its own state of charge to participate in the frequency response droop process.Finally,by building a simulation model to compare the frequency modulation effects of variable coefficient method,fixed coefficient method, and wind power independent frequency modulation under step load disturbance and continuous load disturbance,it is verified that the control strategy in the article can effectively reduce system frequency deviation.At the same time,the doubly-fed wind turbine can fully utilize its inherent rotor kinetic energy,and the energy storage equipment can also output smoothly,alleviating its overcharging and discharging problems,andimprove its service life.

The pipeline transportation system in thermal power plants is a critical infrastructure for the conveyance of liquids or gases,and the safety of the system's pipelines is of paramount importance.This paper,in conjunction with the current state of research both domestically and internationally,provides a comprehensive review of the hardware and software methods for detecting leaks in energy supply pipelines.Hardware methods for pipeline leak detection rely on sensor measurements,which are suitable for detecting small flow leaks but are costly and cannot provide continuous monitoring.Software methods for pipeline leak detection utilize computer analysis,which are more cost-effective, capable of rapid leak detection,but require a substantial amount of historical data and real-time sensor data.This paper also summarizes and analyzes the technical limitations of various pipeline leak detection methods and provides an outlook on future research directions.To enhance the efficiency and accuracy of leak detection,it is necessary to integrate multiple technical methods.Furthermore,the development of leak detection technology should be directed towards integration,intelligence,and automation,improving the stability of real-time data transmission and the precision of computational accuracy.

Battery energy storage systems （BESS）with bidirectional fast response capabilities can provide dynamic frequency responses to electricity grids,alleviating imbalances caused by fluctuating renewable power outputs.In order to ensure the economic effectiveness of BESS participating in frequency response services,it is necessary to reasonably optimise BESS capacity configurations together with operating strategies.From the perspective of the UK's Dynamic Moderation frequency response service market,this paper develops a closer-to-real-time energy management for BESS through dynamic adjustment of operational baselines so as to ensure that BESS comply with the market's State of Energy Management Rules （SoEMRs）and have sufficient energy footroom and headroom to completely cope with low-and high-frequency events.Furthermore,the techno-economic operation of BESS throughout its service life is simulated and translated into an equivalent annual annuity which is maximised to determine the best BESS capacities and operating strategy variables.Simulation results show that the optimised BESS can fully respond to all the frequency events and follow the SoEMRs for the majority of the time.The paper provides deep insights into the energy storage-friendly frequency response service markets in the UK that protects the benefits of energy-limited participants,which have reference significance and practical values for the development of ancillary service markets and the operation of BESS in China.

As an effective mechanism to achieve China's dual carbon goals,the impact of carbon emission rights allocation has become a crucial factor that needs to be considered in power quantity balancing.To address the issue of ineffective allocation of carbon emission rights resources under existing methods in the power industry,this study proposes an uncertainty power quantity balancing model under a carbon emission rights allocation scheme based on data envelopment analysis.Firstly,an analysis of carbon emission rights allocation policies is conducted,and a carbon emission rights allocation method based on data envelopment analysis is proposed.Secondly,considering the uncertainty introduced by the high proportion of renewable energy grid integration,a power quantity balancing model that incorporates carbon emission rights allocation is developed.The model is transformed into a solvable deterministic model using robust optimization methods based on multi-segment interval uncertainty sets.Finally,simulation results on the HRP-38 system demonstrate that the carbon emission rights allocation method based on data envelopment analysis can reduce carbon emission costs and effectively allocate carbon emission rights resources.This research provides technical support for formulating carbon emission rights allocation schemes in power quantity balancing analysis.

Because the scheme of energy storage unit inside the wind turbine has the advantages of flexibility and controllability,it is widely used in the field of fault ride through.However,the difference of energy storage unit is not considered in the previous analysis,which may cause power imbalance during the fault period and endanger the safe and stable operation of the system.To address this issue,a permanent DC fault ride-through coordinated control strategy based on precise control of wind farm energy storage is proposed.Firstly,the structure of the system,the energy storage control strategy,and the configuration of energy storage capacity are explained.Then,considering that one pole of the bipolar MMC-HVDC system still has the ability to operate normally when the other polar exits,the fault is divided into self-absorption and non-self-absorption cases according to the size of the unbalanced power.In the case of self-absorption,the unbalanced power is transferred to non-fault poles.In the case of non-self-absorption,the unbalanced power is precisely distributed to the internal energy storage units of the wind turbines based on the different State of Charge （SOC）levels.This ensures power balance in the system while reducing the differences between energy storage units.The capacity constraint of the energy storage units is addressed by the stepwise cut-off method,which ensures that the power balance is maintained when an internal energy storage unit is removed from operation.Finally,the effectiveness of the proposed fault ride-through scheme is verified through model simulation using the PSCAD/EMTDC platform.

Based on the inception mechanism of lightning upward leader from wind turbine blade,the critical inception height （CIH）is defined.Around obtained CIH and proportion of CIH,an assessment method of triggered lightning ability of multi-wind turbines based on CIH is proposed.Physical simulation model of lightning strike of wind turbine is established,the assessment method of triggered lightning ability of multi-wind turbines was applied to assess the ability of multi-wind turbines under different numbers,sizes,and thundercloud heights.The research shows that proposal of relevant assessment method provides important support for exploring triggered lightning ability of multi-wind turbines.Under different numbers and sizes of wind turbines,compared to single wind turbine,triggered lightning ability of multi-wind turbines shows a weakening trend.When height of thundercloud drops to a certain value,triggered lightning ability of multi-wind turbines will be stronger than that of single wind turbine when height of thunderclouds is higher.In addition,in scenario of multi-wind turbines,a decrease in number of wind turbines or an increase in size of wind turbines will lead to an enhancement in triggered lightning capability of multi-wind turbine.At the same time, lower height of thunderclouds is,greater enhancement of triggered lightning ability of multi-wind turbines is.The relevant conclusions will provide theoretical support and necessary reference for assessment of triggered lightning ability of multi-wind turbines under different conditions.

Miniaturized modular power supplies hold considerable significance in domains such as telecommunications,automotive engineering,aerospace technology,and data processing systems.By elevating the operating frequency of circuits,the size of passive components can be diminished,thereby enhancing the system's overall power density.This paper explores a half-bridge LLC resonant converter configuration,delving into its fundamental working principles and distinctive characteristics while aligning system parameters with specific project requirements.Recognizing the effect of leakage inductance on the transformer's secondary side under high-frequency conditions,an optimized circuit model is proposed.To ensure soft-switching attributes,the parameter calculation methodology has been meticulously refined.A prototype leveraging Gallium Nitride （GaN）technology was developed for empirical validation.It delivers a rated output power of 300 W,operates at a switching frequency of 1 MHz,sustains a nominal input voltage of 48 V,and outputs a voltage of 12 V.The system achieves an efficiency of 95.6%at full load, substantiating the accuracy and reliability of the theoretical analysis presented herein.

In recent years,with the rapid expansion of ultra-high voltage （UHV）long-distance overhead transmission networks and the continuous extension of power infrastructure coverage,the frequency of ice disasters has surged significantly.Chain fault events such as conductor breakage and tower collapse have occurred frequently,posing severe challenges to the secure and stable operation of power systems.To mitigate these impacts,it is crucial to enhance power system resilience during ice disasters.This involves calculating ice thickness on transmission lines using weather forecasts and micro-terrain data,determining the total load on lines and towers,and assessing the change in line failure rates based on design strengths.System operating states are simulated to construct resilience indices and evaluate system resilience.Enhancement methods are applied in pre-disaster,during-disaster,and post-disaster stages to improve system resilience.

With the rapid development of new energy vehicles,V2X Vehicle to Everything）technology has become an effective means for vehicle-grid-load interconnection and energy sharing.As the core component of V2X technology,the bidirectional DC-DC converter is a key device for energy interaction.Faced with the significant voltage fluctuations of power batteries,how to maximize weighted efficiency over a wide voltage range,reduce the number of components,and enhance power density has always been the goal pursued in the development of V2X bidirectional converters.This paper focuses on wide-range gain bidirectional quasi-single-stage isolated DC-DC converters,which summarizes and reviews the existing research from three aspects:converter topology,modulation strategy,and control.The paper also identifies the shortcomings and challenges of the current research.

In the face of large-scale development and utilization of new energy such as wind power and photovoltaic, the problem of insufficient flexibility of power system operation has become increasingly prominent.With the continuous advancement of electric energy transformation,the continuous innovation of power technology and the wide application of distributed generation technology,the load side is developing rapidly towards the trend of digitization,intelligence and activeness.Among them,temperature control loads such as air conditioning and electric heating show great adjustable potential.It is necessary to sort out the current research progress and future direction of temperature control load participating in grid auxiliary service technology from different angles.Firstly,the challenges faced by the active frequency control of the power grid under the new power system are summarized.Combined with the control framework of different frequency modulation mechanisms,the principles and characteristics of each control method of the temperature control load participating in the frequency modulation of the power grid are described in detail,and the advantages and disadvantages of different methods are analyzed.Secondly,the performance and application scenarios of single temperature control load and aggregation model are evaluated.Finally,the main problems and technical methods of air-conditioning load participating in different auxiliary services such as primary frequency modulation,secondary frequency modulation and underfrequency load shedding are summarized,so as to promote the temperature-controlled load to become an important part of power system frequency modulation in the future.

Based on the principle of coherent Doppler velocimetry,a wind-measuring lidar system with 3D scanning function is developed.By constructing the three-wave beam scanning mode and the speed azimuth display algorithm, the dynamic reconstruction of 3D wind field in the atmospheric boundary layer is realized.The synchronous observation test of ground-based radar and 3D laser radar was carried out in Lankao Plain area of Henan Province,and the linear regression model and timing analysis method were used to compare the horizontal wind speed,wind direction and 140m radial wind speed at the 280m height layer.The experimental results show that the horizontal wind speed measurement shows significant linear correlation；the wind direction data maintain high consistency （R2=0.908），but there is local directional deviation；the characteristics of radial wind speed has good synchronization （R2=0.982）。The 3D radar system shows the technical advantages of second-level refresh rate and sub-meter-level spatial resolution,which can accurately capture the low-altitude jet current and wind shear phenomenon.This study verifies the measurement reliability of 3D laser wind measurement technology in flat terrain,and provides a high-precision detection method for micro-site location and wake effect assessment of wind farms.

With the high development of energysystem interconnection and energy transaction marketization,the regional interconnection of Multi-Integrated Energy System（MIES）makes the energy utilization efficiency of Integrated Energy System （IES）more efficient and the economic benefits more considerable.Firstly,this paper constructs the energy sharing architecture of MIES cooperation alliance under the background of multi-energy market, and establishes the power and backup point to point （P2P）transaction model between MIES.Secondly,the uncertainty of new energy output,the risk of electricity price and reserve price fluctuation are analyzed.In this paper,the conditional value-at-risk （CVaR）theory is used to construct the risk cost function and incorporate it into the comprehensive operation cost model.Finally,the Alternating Direction Method of Multipliers （ADMM）is selected for distributed solution,and the correctness and rationality of the model are verified by an example analysis.The minimization of MIES operating cost and the maximization of payment income are realized,which reflects the influence of different conditional risk aversion coefficients on MIES.

In recent years,with the application of multilevel power amplifier in high precision field,the total harmonic distortion （THD）has become an important index in high-precision fields.Firstly,this paper introduces the application of multilevel power amplifier in the field of high precision and the harmonic problems caused by it.At the same time, the root of total harmonic distortion caused in a multilevel power amplifier system is elucidated.Then,the main literature is classified according to the means used to suppress total harmonic distortion,and the advantages and disadvantages of different harmonic suppression methods in topology,modulation strategy and multimodal control are summarized.In addition,the principle and characteristics of the new theory and method of harmonic suppression are emphatically expounded.Finally,a summary of THD suppression methods for multilevel power amplifiers was provided, highlighting research ideas for increasing the number of voltage levels and response speed,etc.

In the integrated energy system,the electrical and thermal systems are connected through coupling elements The violation of the node variables of any subsystem may lead to unstable and unsafe operation of the entire integrated energy system.To this end,the static voltage and air pressure safety and stability margin indicators of the integrated energy system and strategies to improve the security of the integrated energy system are proposed.First,a model of the electrical and thermal system in the integrated energy system is constructed,and the coupling hub adopts the energy hub model；secondly,the alternating solution method of Newton-Raphson method is used to solve the multi-energy flow equation of the integrated energy system；next,the static voltage and pressure safety are given Margin range and related safety strategies:Based on the given safety margin index,use the sensitivity method to analyze the safety margin of state variables such as node voltage and air pressure under load disturbance to determine the weak links of the system；finally,select an appropriate strategy to Ensure that the system's node voltage and node air pressure meet safety margin requirements after load fluctuations.The calculation example analysis shows that the method proposed in this paper to determine system weak links is more efficient,and the proposed strategy can help improve the system security of the integrated energy system and enable it to operate reliably.

With the wide application of power monitoring system,the management of cyberspace assets is becoming more and more complex,facing the problems of various data and unknown classification.To solve the above problems, the research on the construction and prediction recognition method of the cyberspace asset portrait of the power monitoring system was proposed.It proposes a prediction recognition method combined with MLP_LSTM model,which constructs a preliminary portrait of assets through asset information collection and feature extraction.Then,MLP is used to perform the nonlinear mapping of features,and LSTM model is introduced to capture the time series information of assets to achieve more accurate prediction and recognition.The simulation experiments show that,compared with the traditional method,the proposed method not only significantly improves the management efficiency and security,but also further improves the accuracy of prediction and identification through the introduction of MLP_LSTM model,which provides strong technical support for the intelligent management of cyberspace assets of the power monitoring system.

The modular design and parallel optimization control of the DC microgrid distributed power supply system significantly enhance system stability and power expansion capabilities.However,due to the dynamic parameter cross-coupling characteristics of the bidirectional isolated converter parallel system,new challenges are brought to system modeling and stability analysis.Therefore,based on the unified dynamic model of the Dual Active Bridge （DAB）converter,a parallel integral droop control modeling method for multi-energy converters is proposed.The simulation results show that the proposed modeling method can accurately predict the step disturbance response,verifying the accuracy of the model.

The "dual carbon"goal propels the quick growth of new energy,and the large-scale wind power is connected to the grid via the traditional high-voltage direct current transmission （LCC-HVDC），which is the main way of wind power development and utilization.Subsynchronous oscillation is mostly caused by an inappropriate interaction between direct drive wind farms and LCC-HVDC,however there are many different causes that might cause it.In this article,the sub-synchronous oscillation problem of direct-drive wind farm via LCC-HVDC transmission system is addressed,and the impedance model of direct-drive wind turbine,DC transmission system and Point of Common Coupling （PCC）port is constructed by perturbation determination method.Based on the impedance analysis method,a stability criterion applicable to the AC/DC system is proposed to analyze the dominant factors affecting the stability domain of the system and the influence of each device on the impedance characteristics of the system,and the influence law of the control parameters on the impedance characteristics of the system is revealed.The results show that a decrease in the proportional coefficient and an increase in the integral coefficient of the rectifier side controllers of the direct drive wind farm GSC and LCC-HVDC will lead to negative resistance characteristics in the impedance of LCC-HVDC and wind turbine ports,resulting in negative damping characteristics in the parallel impedance composed of the direct drive wind farm and LCC-HVDC,indicating the risk of sub synchronous oscillation in the system.Finally, the time domain simulation of PSCAD/EMTDC platform is carried out to further verify the influence of control parameters on system stability.

At present,in the formulation of the in-plant operation strategy of pumped-storage power plants,there are problems such as not distinguishing the power characteristics of the same type of units,reducing the number of start-stops of the units,and the units working in the near-vibration range.In order to solve the above problems,this paper proposes an operation strategy of units in a pumped-storage power station based on unit combination optimization.On the basis of distinguishing the operating characteristics of units of the same type,optimization is carried out with the goal of minimum water consumption.List the unit combinations in the dispatching period,carry out the priority sorting with the goal of the least water consumption,and filter by the unit start and stop constraints.Based on this,the unit combination scheme in each dispatching period is obtained,and the power allocation of each unit is determined according to the screening results.The simulation results show that the strategy in this paper is effective in reducing water loss and improving the overall efficiency of pumped-storage power stations.

Extreme disasters may cause large-scale energy supply problems in the electricity-gas integrated energy system,resulting in power outages and gas outages.Existing fault scenario screening methods mostly focus on single fault scenarios and lack modeling of the cascading fault propagation mechanism in the electricity-gas coupled system,resulting in insufficient robustness prediction of the evaluation results for extreme disasters.This paper constructs a cascading failure model for the electricity-gas integrated energy system,considers the fault propagation mechanism of power transmission lines and natural gas pipelines,constructs a dynamic propagation model of cascading failures based on Markov decision process,and uses the proximal policy optimization algorithm to efficiently search and optimize disaster scenarios.Finally,a cascading failure model for the electricity-gas integrated energy system is built based on the IEEE 30-node power grid and 20-node gas grid,and the PPO algorithm training process is tested.The example shows that this method can identify serious fault scenarios and fault propagation paths and ensure good convergence,thereby improving the emergency response capability of the electricity-gas integrated energy system when it is impacted.

Current deep learning architectures,particularly Transformer-based models,have demonstrated superior performance in power system transient stability assessment.However,conventional Transformers exhibit insufficient localized feature extraction capability for transient data characteristics.To address this limitation,we propose a Swin Transformer-based transient stability evaluation framework for power systems.By replacing the fixed block-based self-attention mechanism with a hybrid windowing approach that integrates non-overlapping local windows and shifted windows,our method enables synergistic computation of local-global attention patterns.This architecture effectively captures multi-grained features from power system transient data while improving predictive accuracy.Furthermore,our framework incorporates attention mechanism-guided key component identification through adaptive focus allocation, where attention weight distributions are analyzed to establish correlations with system instability modes.This not only enhances model interpretability but also optimizes computational efficiency.Notably,the proposed model exhibits linear computational complexity with respect to feature map dimensions,contrasting with the quadratic complexity inherent in traditional Transformers.Simulation results on the IEEE 10-machine 39-bus system demonstrate that our approach outperforms conventional deep learning and machine learning methods in stability assessment accuracy while maintaining lower computational costs compared to standard Transformer architectures.