Compared with the conventional power system dominated by the synchronous generators, the renewable-based power system is dominated by the grid-connected inverters and features different dynamics. In recent years, a number of unidentified instability incidents have been frequently reported. The oscillation phenomena arise over a wide frequency range, with the non -linear, time-variant, and complicated dynamics. From the aspects of controller optimization, virtual impedance shaping, and other passivation methods, this paper overviews the impedance passivation methods for grid-following and grid-forming inverters, and summarizes the remaining challenges 

In the face of the continuously increasing global energy demand and the challenge of ecological sustainability, the search for efficient energy conversion methods and the development of energy-saving technologies has become crucial. Phase change materials have become important innovative materials in the fields of energy storage, temperature regulation, and efficient thermal management due to their ability to absorb and release large amounts of latent heat during the solid-liquid transition process. Flexible composite phase change materials, due to their ability to maintain performance under deformation conditions, are considered to have significant application prospects in future smart devices and systems. This article provides an in-depth discussion and evaluation of the research progress, synthesis strategies, and functional development of flexible phase change materials. By analyzing the practical applications of flexible phase change materials in daily life, the potential and possibilities of achieving efficient thermal management and adapting to complex application environments are elucidated. This review provides a systematic theoretical guidance for the future development and further exploration of flexible phase change materials.

 Compared to power systems that use traditional RS485/CAN buses as transmission methods, the new power system has put forward new requirements for the radiation, efficiency, and power of information transmission methods Therefore, the article first introduces common information transmission methods, then elaborates on the principle of information power composite modulation from the essence of power electronics, analyzes the advantages and disadvantages of common digital modulation methods, and finally summarizes the current urgent problems and development prospects. The application of information composite modulation technology is quite extensive. When combined with the current flexible, efficient, and environmentally friendly distributed energy, it can not only improve energy utilization efficiency, reduce energy consumption and emissions, but also promote the development of new power systems and renewable energy, making important contributions to achieving sustainable global energy development.

Permanent magnet synchronous motor has the advantages of high efficiency, high power factor, measurable rotor parameters and good control performance, for which it has been widely concerned and applied in academia and industry. The stator and rotor parameters of permanent magnet synchronous motor can be obtained in real time by online parameter identification technology, which can not only improve the control accuracy of the motor, but also monitor the health state of the motor online. In this paper, the research status of PMSM parameter on-line identification technology is summarized and summarized. On this basis, the key technical challenges of this technology are summarized and analyzed from the aspects of model equation rank shortage, cross saturation effect, inverter nonlinear effect and parameter identification under extreme conditions.

 The permanent magnet synchronous motor （PMSM）drive system is often affected by multi-source disturbances under various operating conditions, leading to a decrease in its control performance. Linear Active Disturbance Rejection Controller （LADRC）has been widely used in PMSM drive systems due to its simple parameter tuning and independent mathematical model. The types of multi-source disturbances present in PMSM drive systems are first explained in the paper, and mathematical models for some disturbances are established. Then, the limitations of traditional LADRC are analyzed, and new types of LADRC proposed in recent years are summarized for different types of disturbances, while algorithm expressions for some of the proposed methods are provided. Finally, the development trend of PMSM drive systems based on LADRC in disturbance rejection control is summarized.

 Multi-energy virtual power plant （MEVPP）aggregates various forms of distributed energy and demand-side flexibility resources including electric and thermal energy. In order to realize the optimal scheduling of MEVPP, in this paper, a MEVPP model including power generation units, heating units, energy storage unit, air conditioning loads cluster, and demand response loads cluster is established, a deep reinforcement learning （DRL）-based optimal scheduling method is proposed for this model, corresponding reward function, state and action spaces are designed. The method is based on the proximal policy optimization （PPO）algorithm, which can regulate distributed energy and demand-side flexibility resources based on environmental information such as forecasted load, wind/light output, outdoor temperature, etc.，and obtain the strategy set of MEVPP optimal scheduling with the objective of minimizing the operating cost. The case study result proves the feasibility of DRL in MEVPP optimal scheduling and the extensibility of the strategy set.

The interconnection of multiple energy sources has gradually become the direction of future power system development, and the optimization and scheduling of multi energy interconnection systems is an important means to cope with the large-scale consumption of new energy connected to the grid. We have established a cost model for the wind solar water fire pumping and storage interconnected system that takes into account the cost of deep peak shaving for thermal power units, and a day ahead optimization scheduling model for the wind solar water fire pumping and storage interconnected system that takes into account the initiative of peak shaving. A hierarchical optimization scheduling model solving method is proposed for the complex structure of multi energy coupled systems. The upper level model aims to minimize the fluctuation of net load and obtain the equivalent load curve；The lower level model, based on the scheduling results of the upper level model, takes the economic optimization of peak shaving operation and the minimum amount of new energy waste as the objective function, taking into account the initiative of peak shaving, to solve the economic scheduling problem of a new energy system that considers the deep peak shaving coal consumption characteristics of thermal power units. The simulation examples show that the constructed model achieves complementary operation of multi energy interconnected systems, improves the deep peak shaving ability of thermal power units, reduces the abandonment rate of new energy and system operating costs.

With the large-scale wind power and photovoltaic power connected to the power grid, the problem of new energy consumption is prominent. In order to alleviate the dilemma of new energy consumption, by analyzing the time series matching relationship between new energy power generation power and regional load, a new energy power generation power quality division model was established, and the impact of new energy power generation power uncertainty on power grid operation regulation and control was quantified, and then an energy storage capacity allocation scheme that could reflect the power uncertainty law of new energy plants and stations was formulated, so as to effectively improve the level of new energy consumption. In this paper, a power quality division model for new energy power generation is proposed. The power quality of new energy power generation is characterized by two dimensions：power fluctuation and power prediction error. Analyze the time series data of new energy power generation power and grid load, as well as the prediction error data, and establish a statistical model. Determine the generation power curve that matches the grid load timing, and establish power quality indicators for new energy power generation.

The intermittency and volatility of high-proportion renewable energy access to the power grid have a significant impact on system stability. Therefore, it is crucial to evaluate and improve the stability of distribution networks with high proportions of renewable energy sources（RES）。This paper proposes a new power grid strength evaluation index, the integrated short circuit ratio （ISCR），which not only considers the interaction between RES, but also considers the impact of energy storage devices （ESD），and can more accurately identify weak links in the power grid. In addition, based on ISCR, a distribution network stability improvement method is proposed to allocate the location and capacity of RES and ESD through a two-level optimization method to enhance system strength and increase the capacity of RES and ESD. In the upper level, the location and capacity of RES are optimized to ensure the maximum ISCR value at the node. In the lower level, the location and capacity of ESD are optimized to ensure that the ISCR value is higher than the critical short circuit ratio （CSCR）to maintain system strength. The location optimization is determined by the ISCR value at the node. The capacity optimization is solved using linear programming methods. Finally, a case study verifies the effectiveness of the proposed optimization method in maintaining grid strength while increasing the capacity of RES and ESD.

With the continuous development and popularization of the park-level integrated energy system, it has become a general trend to connect it to the superior power grid and realize the interaction. In this paper, a two-layer optimization model of connecting multi-park integrated energy system to active distribution network is constructed. At the level of active distribution network, schedulable resources such as link-line power, distributed generation, energy storage equipment, flexible load and electric vehicles are taken into full consideration with the goal of minimum operation cost. At the park level, aiming at minimum total operation cost, the grid-connection situation of multi-type parks connected with each other is considered. Analytical target cascading is used to solve the two-layer model. Through the calculation examples, the proposed model has good economic characteristics and peak cutting and valley filling effect, which fully proves the economy and effectiveness of the proposed model.

 The voltage fluctuation on the low voltage side caused by the distributed generation （DG）in the new distribution network is the key factor affecting the power quality of users.  This paper aims at the voltage regulation problem of the new distribution network, proposes a hierarchical and gradual cooperative voltage regulation control strategy based on on-load regulation transformer （OLTC）and modular distribution transformer （MDT）under the condition of sufficient reactive power. In this strategy, the concept of voltage cross section quality is first proposed and the model in different conditions is given. Then the voltage fluctuation range is divided into three intervals: Interval 1 is the normal region, interval 2 is the slight over-limit region, and interval 3 is the serious over-limit region. Considering the economy and fast response of MDT, the strategy uses MDT as the main adjustment mode and OLTC as the backup adjustment means. Finally, by comparing the effect of voltage regulation with simulation, the rationality of the proposed strategy is verified.

Permanent magnet synchronous motor （PMSM）is often operates at high speed due to its inertia or external propulsion when the power supply is interrupted during operation. It is necessary to estimate the initial position/speed before flying start. The fixed action time and interval time of the traditional zero voltage vector pulse method often reduce the estimation accuracy and even cause overcurrent. Therefore, an adaptive triple zero voltage vector pulses method is studied in this paper, which can adaptively adjust the action time according to the amplitude of the current vector excited by the zero voltage vector pulses and adjust the interval time according to the initial speed estimation twice successively, so as to automatically apply the reasonable zero voltage vector pulses for different PMSM parameters or operating states. The simulation results show that the proposed adaptive triple zero voltage vector pulses method can adaptively adjust the reasonable action time and interval time, so as to improve the reliability of initial position/speed estimation and flying start.

 In order to promote the consumption of wind power, reduce carbon emissions of thermal power units, and solve the problem of low-carbon economic operation of Integrated Energy System （IES），variable oxygen-doped oxygen-enriched combustion technology is introduced in this paper to transform the gas unit. Combined with Liquid Air Energy Storage （LAES），which uses the cold energy of Liquefied Natural Gas （LNG），an optimization strategy of low carbon economy for electric heating gas cooling IES is proposed. Firstly, the IES architecture of variable oxygen-enriched combustion Gas unit, LAES using LNG cold energy, Power To Gas （P2G）equipment, central air conditioner and lithium bromide chiller is constructed, and the mathematical models of each equipment are established. Secondly, the cascade carbon trading mechanism is introduced, and the low carbon economic scheduling model of electric and gas-cooled IES is established with the goal of minimizing the system operating cost. Finally, MATLAB is used to invoke GUROBI solver to solve multiple scenarios, which verifies that the low-carbon economy optimization scheduling strategy proposed in the paper can improve the system's wind power consumption, effectively reduce system operating costs, and achieve carbon emission reduction.

For the future of high power electronics penetration, the stable operation of grid-forming inverters in the power system is crucial. Due to the high inertia and high damping generated by the mechanical rotor and damping winding of the traditional synchronous machine, the inverter may have obvious synchronous frequency resonance problems in the output power after grid connection due to the lack of inertia and damping and the negative damping introduced by coupling, which not only affects the waveform quality, but also leads to transient instability in serious cases. Four methods are proposed and analyzed for this problem, and finally the simulation verification is carried out by Matlab/Simulink 

 With the purpose of reducing the energy consumption of CO2 and promoting the efficiency of power generation, this paper proposes an optimization scheme of double reheat-carbon capture coupled with solar and ORC systems, using the ultra-supercritical double reheat-carbon capture system as the reference system. In this paper, an optimization scheme of double reheat-carbon capture coupled with solar and ORC systems is proposed. The optimized system model is constructed using Ebsilon software. The thermal performance, economics and operational performance of the system were analyzed. The results of the study showed that the thermal efficiency of the optimized system was increased by 4.78%，and the heat consumption was reduced by 1 005 kJ/（kW-h）and coal consumption by 36.50 g/（kW-h）compared to the reference system；the annual operating time of the solar auxiliary system is 60%，and the average coal saving can reach 2.0*104 t .The optimized scheme has better thermal economy and reduced coal consumption for power generation, which provides an optimization idea for CO2 capture and emission reduction.

Spectral beam splitting photovoltaic/thermal （PV/T）hybrid utilization technology breaks the conflict between the low operating temperature of PV cells and their high-grade heat demand and achieves efficient photoelectric efficiency and thermal efficiency. However, the preparation of suitable selective splitting media plays a crucial role in achieving reasonable energy distribution within PV/T devices. In this study, deionized water was chosen as the base liquid, and the combination of noble metal Ag nanoparticles and inorganic CoSO4 was utilized to achieve efficient regulation of the optical properties of splitting liquids. In addition, based on the energy balance method, the electrical and thermal output models of a typical PV/T prototype system were established, and the thermal and electrical output characteristics of the system before and after the optical regulation of the splitting medium were analyzed. The results show that the water-based filter has efficient infrared absorption characteristics. After adding Ag nanoparticles, the splitting medium exhibits a clear absorption peak in the visible light band, with a peak of 435 nm.
After further addition of CoSO4, the absorption peak width of the nanofluid can be expanded, and it also has certain absorption enhancement in infrared.Comparing the influence of the splitting medium on the thermal and lectrical performance of the PV/T system before and after optical regulation, it can be seen that the total absorption characteristics of the splitting medium increase, and the thermal efficiency of the PV/T system shows an increasing trend, but its electrical efficiency decreases. The total exergetic efficiency of the liquid-based splitting PV/T system also increases, exceeding 28%. Efficient regulation of the optical characteristics of the splitting media can achieve a controllable allocation of internal energy in PV/T systems.

In recent years, China has made great efforts to develop new energy power generation mainly based on wind power, especially in the "three North" regions rich in wind resources in China. However, the load demand in these regions is often small and it is difficult to match the installed capacity of wind power. Therefore, there is a large amount of wind abandoning in the "three North" regions of China. In order to solve this problem, this paper introduces a high load scheduling strategy for improving wind power consumption capacity. The load involved in dispatching is two kinds of high load capacity load, namely electrolytic aluminum load and ferroalloy load. According to the operation characteristics and regulation characteristics of the two kinds of high load, the two kinds of high load are classified and the mathematical model is established. Then, according to the different characteristics of the two kinds of load, the mathematical model of day-ahead scheduling and intra-day scheduling is established respectively, and the effectiveness of the proposed scheduling strategy is verified by an example.

Aiming at the problem of poor current loop immunity in the high-speed operation of permanent magnet synchronous motor （PMSM），a harmonic suppression strategy for flux weakening with voltage phase angle regulation is proposed in the paper. Firstly, the small-signal model of the control system is established through linearisation, and then the closed-loop transfer function of the system is obtained to analyse the stability of flux weakening. In order to overcome the problems of low damping coefficient and poor system stability during acceleration, a proportional differential compensation strategy is introduced into the straight-axis current regulator to realise the inner-loop feedback in order to improve the system damping ratio and suppress the system resonance peaks so as to reduce the current oscillations during high-speed operation. Finally, the key parameters of the compensator are determined based on the principle of equivalent internal mode controller and frequency domain analysis.The experimental results show that the method can effectively improve the stability of the current loop and the anti-interference performance of the control system, and significantly reduce the harmonic content of the motor current.

 In the new power system, it is necessary for wind power to actively participate in power grid frequency regulation. How to evaluate the impact of wind power participation in frequency regulation on frequency dynamic characteristics has also become a research hotspot. In this paper, an improved wind turbine pitch control with constant load shedding pitch angle that can reduce the number of pitch actions before the rated wind speed is proposed, and the expression of the difference adjustment coefficient of the wind tur-bine participating in primary frequency regulation under this control is derived. Based on this, the frequency response model of the power system with constant load shedding pitch angle control is constructed, and the analytical expression of the frequency dynamic characteristic index is derived. The influence mechanism of wind speed and initial pitch angle on the adjustment coefficient and frequency dynamic characteristic of the wind turbine is revealed. The accuracy of the frequency equivalent model and the ef-fectiveness and feasibility of the proposed frequency modulation method are verified by the improved IEEE three machine nine-node-system.

With the transformation of the global energy structure and the improvement of environmental protection awareness, as an efficient and environmentally friendly way of energy utilization, the distributed generation system based on new energy is gradually occupying an important position in the power system. With the continuous improvement of the penetration rate of distributed generation system, the equivalent inertia of the power grid continues to decrease, which seriously affects the frequency stability of the power system. As a result, virtual synchronous control has emerged, which can compensate for inertia and equivalent damping of the grid by simulating the dynamic characteristics of traditional rotary synchronous generators. Although the small signal stability control of virtual synchronous machine （Virtual synchronous generators ,VSG）has been widely studied, the influence of its reactive power loop on the transient stability of the large signal of the system still needs to be further studied. In this paper, the influence of the reactive circuit of the grid-connected inverter on its transient stability is analyzed theoretically, and on this basis, three methods that can effectively improve the transient stability of the grid-connected inverter are listed. Finally, the simulation was verified by MATLAB/Simulink platform.

Renewable energy sources such as hydrogen, photovoltaics, and wind energy are important ways to achieve the dual carbon goals and carbon emission control goals. Due to the significant fluctuations in renewable energy generation, the dual risks of load loss and power abandonment are highlighted, which puts higher demands on the flexibility of energy systems. This article proposes a low-carbon scheduling model based on flexibility quantification for a high proportion renewable energy integrated energy system. Firstly, analyze the operational characteristics of flexible resources in multi energy coupled equipment, construct a comprehensive energy system flexible resource model, and combine the utilization and emission of carbon dioxide in system equipment to achieve deep utilization of carbon dioxide within the system；Secondly, considering the source load fluctuation of the system, combined with the quantitative difference in flexibility between the integrated energy system and the power system, the quantitative analysis of energy, power, and slope flexibility of the park system is achieved；Finally, combining the differentiated regulation characteristics of system flexibility resources with the supply-demand differences of system flexibility at different time scales, multi time scale scheduling is carried out to mitigate the flexibility requirements brought about by the uncertainty changes of renewable energy and small time scales of load. This article takes a comprehensive energy industrial park in the south as the experimental background, and uses the method proposed in this article to analyze and schedule, verifying the power and electricity balance of flexible resources at different time scales, which is conducive to improving the flexibility and low-carbon characteristics of the comprehensive energy electricity-gas-heat system.

New energy power generation has received more and more attention and development around the world, among which wind energy is the most common and widely used form of new energy. Wind power prediction has an important influence on the stability, reliability and economy of the power system. In order to improve the accuracy of wind power prediction, we consider the spatial dependence of wind power stations and solve the difficulty of grid prediction in the wind power grid. First, similar wind farms are divided according to their spatial characteristics, and the convergence effect of clusters is used to simplify the number of network grids. Secondly, the meteorological characteristics with the most consistent cluster power fluctuations were extracted, and the spatial characteristics of all wind farms were retained to the maximum extent. Thirdly, the input and output data form is processed to form the network format data in the spatial sense, and is trained and predicted by convolution of long and short-term memory network prediction model. Finally, the method was applied to a large-scale wind power cluster in northeast China to verify its effectiveness. The experimental results show that the proposed method is 0.24%less RMSE and 0.05%lower compared with the ungridded MAE, which effectively improves the accuracy of day-ahead power prediction of wind power cluster.

Partial discharge detection is an important means to evaluate the insulation condition of cross-linked polyethylene power cables. In this paper, a partial discharge online monitoring system for medium voltage XLPE cables is developed, and its working principle, hardware composition, software design and implementation scheme are elaborated in detail. The system comprehensively evaluates the insulation condition of XLPE cables by monitoring the partial discharge signal in the ground wire of XLPE cables. The field operation results show that the system is stable and reliable.

In the energy transition environment, the electric-gas integrated energy system has developed rapidly. However, the increase of complexity also challenges the safe and stable operation of the electric-gas integrated energy system. In order to better evaluate the operational risk between the two, this paper presents a risk assessment method that can reflect the risk of the electric-gas integrated energy system by using digital twin technology. By monitoring and simulating the operating state of the digital twin model, the operational risk of the electric-gas integrated energy system can be evaluated effectively. This method has the advantages of high precision and reliability, and has a wide prospect in practical application. In this paper, the original data of the system during normal operation are calculated by ox method to obtain the operating state of the system voltage, pressure and power flow. Then, the integrated energy system risk index is calculated to generate a database, and finally the calculated index data is evaluated and predicted using CNN-XGBoost technology. The example results show that the method used can improve the accuracy and efficiency of safety risk assessment and prediction of electric-gas system well.

Large-scale cross-season heat storage technology can effectively solve the problem of winter and summer heat imbalance of new energy heating.In this paper,a new type of zonal seasonal heat storage tank is proposed,and the heat dissipation effect and annual thermal efficiency of the heat storage tank under two different storage/release modes are calculated and compared by numerical simulation.The results show that the heat storage tank can maintain high annual thermal efficiency under both storage and release modes.Mode 2 adopts the strategy of "the last one goes first"， although the thermal efficiency of each zone is abandoned,it ensures that at least half of the zones are working under a higher heat utilization rate,and the annual thermal efficiency of the whole heat storage tank can reach 88.25%.Under mode 1，the annual thermal efficiency of the heat storage tank is 87.55%，which is slightly worse than that of mode 2， but it can ensure the stability of the hot water temperature throughout the heating season.

With China vigorously developing green economy and promoting energy conservation and carbon reduction, the mutual utilization of new energy and train braking energy in electrified railway system has been paid more and more attention. In this paper, an electrified railway energy storage allowable scheduling method considering photovoltaic and energy scheduling device is proposed. By integrating photovoltaics into the traditional traction substation, the energy storage and energy dispatching devices cooperate with each other to improve the utilization rate of regenerative braking energy of trains and reduce the electric energy delivered by the grid to the traction power supply system. At the same time, the controllability and flexibility of power supply between source and charge are strengthened. The numerical simulation results show that after the optimization of the proposed method, the power obtained from the traction power supply system to the grid is reduced by 2 500 kWh, which verifies the effectiveness of the proposed method.

Aiming at the problem that the cost of electricity sales companies increases under the deviation power assessment mechanism, a cost control strategy for power sales companies under the transfer of deviation power is proposed. First, the AHP-Logit model is used to analyze the market share of electricity sales companies from two aspects：price factors and non-price factors. Secondly, construct the electricity purchase cost model of the electricity sales company based on the negotiation and bargaining model. Then, a transaction model between power sales companies considering the transfer of biased electricity is established, and the impact of negotiated compensation and transfer of biased power on the cost of power sales companies is revealed, so as to reduce the cost of power sales companies.Finally, the rationality and effectiveness of the method proposed in this paper are verified by an example analysis.

With the increasing proportion of photovoltaic power generation connected to the distribution network, voltage out of limits and fluctuations have become increasingly serious. A voltage coordination control strategy for distribution network zoning is proposed to address this issue. In terms of distribution network zoning, based on the voltage sensitivity index information obtained from day-time power flow calculation, the voltage change index suitable for distribution network zoning is constructed by calculating the changes in the voltage of each node affected by photovoltaic active and reactive power regulation. The regional division of each node is determined based on the criterion that this index meets the voltage change threshold requirements；In terms of voltage coordination control of the zone, a voltage sensitivity control strategy within the zone is adopted to pair nodes and utilize the photovoltaic active and reactive power regulation ability to control all out of limit voltages within the zone to the normal range. Based on this, an interval distributed voltage coordination control strategy is adopted to achieve interval state variable equivalence and optimize the dynamic reactive power compensation of photovoltaic systems between adjacent zones based on the alternating direction method of multipliers （ADMM）algorithm, in order to achieve optimal suppression of expected voltage fluctuations across the entire network. Taking the IEEE 33 node system as an example, numerical analysis is conducted to verify the effectiveness of the proposed strategy.

The theoretical research of flexible DC distribution technology has entered a mature stage, and the imperfection of its line protection method has become an important factor restricting the development of this technology, especially the single-terminal protection with the advantage of fast action, which has weak resistance to high resistance and high sampling rate, still needs to be resolved. In order to solve the above problems, a new method of single-terminal protection for flexible DC distribution lines based on the current-limiting reactor voltage is proposed in this paper by analyzing the characteristics of the current-limiting reactor voltage and its negative rate of change in the time limit current reactor voltage when the metal bipolar short circuit fault occurs in the single-pole symmetrical connection system and the transit-resistance fault occurs. The simulation results show that the method can reliably identify faults in the region within 0.5ms,and can withstand the influence of transition resistance （20）and noise, and requires low sampling rate, which is of practical significance in engineering.

 PIES is a typical complex energy system with complex energy supply equipment and diversified energy coupling mechanism. In order to realize the low-carbon economic operation of PIES, increase the consumption of wind power and solve the problem of low energy utilization efficiency caused by the unreasonable energy use structure of the system, the paper established an electric heating demand response model, fully considering the "quality" and “quantity" of energy, and established a comprehensive energy efficiency model with strong constraint on the carbon emission of the system based on the first and second laws of thermodynamics. According to the principle of cascade utilization, a cascade utilization model containing multiple energy coupling devices is established. Finally, a multi-objective optimization scheduling model of the integrated energy system of the park is established based on the economic cost objective of the system and the comprehensive energy efficiency objective of the system, and the output scheduling of each equipment in the system is realized. The example analysis shows that the optimized scheduling scheme proposed in this paper can not only improve the system's wind power consumption rate and operation economy, but also take into account the low carbon and efficient operation of the system.

 Combined cycle （CC）units have been more and more widely used in the power system due to their high efficiency, low emission, and flexible operation, and have actively participated in the electricity market. In order to study the bidding behavior of the CC unit in the day-ahead electricity market, a bi-level bidding model for the CC unit is proposed in the paper. The upper-level model is the bidding model for the mode-based CC unit. The lower-level model is the day-ahead electricity market clearing model. The CC unit and the independent system operator （ISO）in this model influence each other on the locational marginal prices （LMP）obtained through electricity market clearing. Using the Karush-Kuhn-Tucker （KKT）condition and duality theory, the proposed bi-level optimization model is transformed into a mathematical program with an equilibrium constraint （MPEC）problem. The results show that the bidding strategy proposed in the paper increases the profit of the CC unit in the electricity market by 12.28%and reduces the operating cost of the market by 25.37%，which verifies the effectiveness of the model proposed in the paper.

In the process of achieving the goal of carbon peak and carbon neutrality, in order to achieve environmentally friendly and energy-saving development,electric vehicles have begun to take the stage.With the rapid growth of electric vehicle ownership in the market,the safety problems caused by electric vehicles have gradually begun to emerge.Spontaneous combustion and fire accidents of electric vehicles are common.They have caused serious economic losses and even life hazards to automobile manufacturers,consumers,and operators of charging equipment.The charging safety of electric vehicles has begun to restrict the development of the electric vehicle industry.In this paper, starting from the constant voltage and constant current charging method, through the analysis of the causes of electric vehicle charging faults, a data mining early warning method based on discrete point detection of Gaussian distribution is proposed.The characteristic of outlier detection method is that it can effectively distinguish the data with significant difference from a set of data sets.A large amount of data will be generated during the charging process of electric vehicles. The Gaussian distribution model of normal charging state is obtained by obtaining the data under normal charging.The outlier detection method is used to judge whether the charging of electric vehicles is in a dangerous state, and the charging fault is warned in time. The real-time monitoring and early warning of electric vehicle charging process are realized. The experiment proves that the outlier detection method has good feasibility and accuracy for electric vehicle charging safety early warning .

In complex operating conditions and motion states ,the AC motor system has nonlinear time-varying physical parameters due to factors such as magnetic field coupling and iron core saturation, which weakens the motor control performance and system robustness. To address the above issues, the model-free predictive control strategy utilizes the inherent relationship between variables of the AC motor to construct a data-driven model, thereby eliminating the dependence on physical parameters and eliminating the impact of parameter mismatches. In this paper, combined with the permanent magnet synchronous motordrives, an affine ultra-local model is designed, and a model-free predictive current control strategy is designed. This method uses the least squares algorithmto estimate affine operators online and designs a state compensation mechanism. State compensation gains are selected through the s-approximation consideration to reflect the system motion characteristics in real time. The stability of the method is verified through the analysis of system zeros and poles, and its effectiveness, model adaptability, current quality, and system robustness are verified through experiments.

This article proposes a short-term wind speed prediction method based on improved adaptive noise complete set empirical mode decomposition （ICEEMDAN）and particle swarm optimization （PSO）long and short term memory neural network （LSTM）models. Use ICEEMDAN algorithm to decompose daily wind speed data and calculate corresponding marginal spectra, and screen historical data based on spectral correlation；Using PSO algorithm to optimize LSTM neural network parameters, ICEEMDAN decomposition is performed on the input data, and multiple modal components obtained are predicted using PSO-LSTM. The wind speed prediction results are obtained by overlaying the predicted values of each component. Use the proposed method to predict the wind speed of a domestic wind farm, and verify the effectiveness of the proposed method through comparative analysis.

In the context of facing the increasing number of stakeholders and the physical coupling of the regional integrated energy system, an innovative scheduling strategy is proposed, which takes into account the demand response of multiple parties and adopts a multi-subject game for optimization. First, the actual characteristics of different loads in each microgrid and the response behaviors of users are studied in depth, and a corresponding multi-load integrated demand response model is established. Then, a multi-subject master-slave game model is constructed by taking the system operator as the upper layer leader and the microgrid load aggregator, centralized energy storage plant and wind farm as the lower layer followers. In the upper layer model, the goal is to maximize the system operator's revenue from energy sales, and to determine the unit price of energy sales and compensation price of each microgrid through optimization. And in the lower layer model, it is committed to minimizing the comprehensive cost of all parties, and determines the energy supply of wind farms, the energy output between multiple devices in each microgrid, and the charging and discharging strategies of energy storage plants through optimization. In order to solve this complex problem, the particle swarm algorithm is finally used to solve the upper layer subject model and the Cplex solver is used to solve the lower layer slave model, which interact with each other to finally obtain the equilibrium strategy after the game.

 In order to further analyze the influence brought by the increasingly obvious characteristics of power network electronization, the monitoring of power network operation condition extends to the direction of interharmonics and higher harmonics, and puts forward higher requirements for synchronous wide-frequency measurement. The windowed interpolation spectrum analysis method widely used in synchronous wide-frequency measurement has spectrum leakage, which will lead to large errors when the fundamental frequency is shifted or there are neighboring signals in the signal. To solve this problem, an improved wide-frequency phasor measurement method based on Blackman window all-phase FFT bispectrum line correction is proposed in this paper. The spectrum of wide-frequency signals is analyzed by combining all-phase FFT and Blackman cosine window, and the parameters are corrected by using bimodal spectral lines. This method can effectively improve the suppression effect of spectrum leakage, reduce the interference of adjacent spectrum, and improve the measurement accuracy of wide-frequency signal parameters in complex operating conditions of fundamental wave frequency offset or adjacent spectrum.

Thermoionic converters and thermophotovoltaic converters are two primary solid-state thermoelectric converters capable of operating at extreme temperatures with the potential for high efficiency,making them suitable for ultra-high temperature thermal energy storage applications.Both rely on the transfer of fundamental energy carriers through highly non-isothermal junctions:electrons in thermoionic converters and photons in thermophotovoltaic converters.However,the performance of both converters is constrained by factors such as the Stefan-Boltzmann law and space charge effects,preventing further enhancement.Nevertheless,when the distance between the emitter and absorber is comparable to or less than the thermal radiation characteristic wavelength,the performance of both converters can be significantly enhanced due to the photon tunneling effect generated by evanescent waves and the mitigation of space charge effects.Therefore,it holds significant importance in fields such as waste heat recovery and renewable energy utilization.This paper reviews the research progress of domestic and foreign scholars in the two types of solid-state thermoelectric converters and their hybrid systems,summarizes and analyzes potential future directions and key challenges.

It is the most promising fault isolation method in flexible DC power network to remove faults by DC circuit breaker. At present, the traditional hybrid DC circuit breaker with a large number of fully controlled power electronic devices connected in series by main and branch has many problems such as high cost and technical difficulty. A Thyristor based Capacitor commutation hybrid DC circuit breaker topology （TCC-HDCCB）is proposed. The circuit breaker realizes the functions of two-way fault commutation, cut-off and adaptive reclosing through the combination of thyristor and capacitor, and uses the DC system itself to pre-charge the commutation capacitor, which greatly reduces the cost and control difficulty. In this paper, the topological structure and working principle of TCC-HDCCB are first introduced, and then the selection method of key device parameters is given. Finally, the simulation model of TCC-HDCCB is built in the software platform of PSCAD/EMTDC4.5，and the simulation verification is carried out in the single terminal and four terminal flexible DC power grid. The feasibility of the scheme is verified by comparing the performance and economy with the relevant schemes.

Short-term power load data are characterized by complexity and uncertainty, which often have an uncontrollable impact on the prediction results of the data. When short-term electricity load data are clustered and analyzed using traditional clustering methods, the prediction results will be biased due to characteristics such as the uncertainty of electricity load. In addition, considering that global regression forecasting methods are unable to use different modeling approaches for different parts of the data in the modeling stage, which limits the problem of adaptive capability for different distribution regions or different subsets of features. In this paper, we adopt the density peak clustering algorithm with K-nearest neighbor and weighted similarity to classify the features of short-term electricity load data, and propose a locally weighted linear regression model using K-nearest neighbor to forecast short-term electricity load. The advantages of this model are that it avoids the influence of Euclidean distance on the selection of cluster class centers, reduces the negative influence of global data on local data, avoids the centralized effect of cluster class division, and improves the generalization ability of the model. By comparing with fuzzy C-mean clustering and traditional global regression prediction methods, the model proposed in this paper is more superior for the prediction of real power data.

Based on the unpredictable AC-DC intrusion caused by human error or detection equipment failure in the terminal of secondary screen cabinet of substation relay protection, a new intrusion signal detection method based on generative adversarial network and principal component analysis is proposed to solve the problem of poor quality and small quantity of data samples. Gaussian kernel smoothing is used to preprocess the terminal data to reduce noise interference, and then the cleaned data is amplified through the generated adversarial network （GAN）to meet the subsequent principal component analysis processing and fault detection and identification of AC and DC intrusion signals. The identification accuracy of the proposed method reaches 95%，which realizes the accurate detection of the small sample fault data of the terminal of the secondary screen cabinet.