The high proportion of new energy, the high degree of power electronics, and the high degree of load freedom in the new-type power system bring with complex and changeable topologies and dynamic characteristics. The power balance and stable operation of new-type power systems will face more severe challenges in the situations with weak grid strength and large source-load fluctuations. However, electrochemical energy storage having rapid response and flexible configuration can effectively improve the dynamics characteristics of new-type power systems as well as play a supporting role in multiple time scales. This paper has summarized the research status of conventional energy storage technologies and discussed the technical advantages and application prospects of electrochemical energy storage in new-type power systems. Moreover, the active support capacity and optimal configuration of electrochemical energy storage in new-type power systems have been studied with considering the dynamic characteristics of new power systems and the demand for power and energy balance. This paper will guide the use of electrochemical energy storage to maintain safe and stable operation of new-type power systems.

 With the rapid development of my country's wind power industry, the service life of wind turbines has been extended, and the failure rate and maintenance costs have increased accordingly. Using artificial intelligence algorithms to mine wind power big data and achieve condition monitoring and fault diagnosis of wind turbines has important practical significance for improving the quality and efficiency of the wind power industry, and has gradually become a research hotspot in recent years. This article introduces the characteristics of the wind turbine supervisory control and data acquisition system and vibration signal data, and explains the framework of the intelligent algorithm for wind turbine condition monitoring and fault diagnosis. Relevant research results are summarized, and the challenges and development trends faced by wind turbine condition monitoring and fault diagnosis technology are prospected.

The accurate prediction of wind power is of great significance for China to achieve the goal of 'carbon peak and carbon neutrality '.Traditional wind power prediction methods often ignore the long-term dependence and spatial correlation in time series data, resulting in inaccurate prediction results. In order to solve this problem, this  paper  proposes  a  model  combining  Convolutional  Block  Attention    Module（CBAM）and Long  Short-Term Memory（LSTM）.Firstly , CBAM is used to extract the characteristics of wind power time series data and the spatial characteristics contained in numerical weather prediction. This module can adaptively learn important features in time and space. Then, the extracted features are input into the LSTM layer structure for power prediction. In order to verify the effectiveness of the proposed method, a data set of a wind farm in Jilin Province, China is used for verification. The experimental results show that compared with other power prediction methods used in this paper, the mean absolute error（MAE）of the proposed method is reduced by an average of 2.67%.The coefficient of determination（R-Square,R2）increased by an average of 23 %The root mean square error（RMSE）decreased by 2.69% on average.

Under the demand of long-distance and large-capacity delivery of new energy, the flexible high voltage direct-current, HVDC） transmission technology with modular multilevel converter, MMC） as the core has been rapidly developed in China, and gradually deeply integrated with the traditional high voltage AC power grid to form a highly electronic AC-DC hybrid power system. However, compared with the traditional AC power grid, MMC and other power electronic devices significantly broaden the response bandwidth of the series-parallel system, aggravate the interaction between power grid devices, and frequently cause broadband oscillation from several Hz to several thousand Hz in HVDC projects that have been put into operation, which seriously affects the power supply safety. Modeling and stability analysis have become the key requirement in AC-DC hybrid power system. In this paper, the methods of mathematical modeling and model simplification of MMC are summarized, which provides reference value for future mathematical modeling technology of MMC.

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.

 Multi-load forecasting in integrated energy systems is crucial for the operation and scheduling of the system. Traditional forecasting models have not fully captured the long-term dependencies in time series or considered the coupling relationships between multiple loads, limiting improvements in forecasting accuracy. To address the challenges of multi-load forecasting in integrated energy systems, this paper proposes a forecasting model that integrates Seasonal Trend Decomposition and Crossformer. Initially, the original load data is decomposed into three sub-sequences using seasonal trend decomposition. Then, by employing a dimension-segmented embedding method and a two-stage attention mechanism, the model extracts cross-time and cross-dimensional correlations of multi-load data. Finally, a hierarchical encoder-decoder structure is utilized to generate forecasting results. Comparative experiments on real load datasets demonstrate that the model proposed in this paper has higher accuracy compared to other comparison models.

With the large-scale distributed generation connected to the distribution network, the timing mismatch between its output and load demand makes it difficult to absorb new energy in the power supply area. For this reason,an optimal allocation method of power supply regional source-load-storage is proposed to improve the capacity of new energy consumption. Taking the distributed power supply, energy storage and controllable load in the power supply area of the distribution network as the configuration object, the energy storage and controllable load transfer strategy is constructed, and the two-layer optimal allocation model of source, load and storage in the power supply area is established. The optimization goal of the upper model is to achieve the maximum absorption of distributed power. The optimization objective of the lower model is to minimize the peak-valley difference of the expected net load in the power supply area. In view of the difference between DG and load output time series, LHS technology is adopted to deal with it, and intelligent optimization algorithm is used to solve the model. Taking the power supply area topology of a city as an example, an example is given to prove the rationality and effectiveness of the method.

Accurate wind power prediction is of great significance for the safe and stable operation of the power system. In view of the problems of unreasonable cluster division in cluster prediction and difficult to effectively improve the accuracy in short-term prediction, this paper proposes a short-term wind power cluster power prediction method based on Fuzzy C-means （FCM）and I Transformer-time convolutional network （Temporal Convolutional Network, TCN）.First, divide subclusters based on FCM clustering algorithm, and then use the advantages of I Transformer-TCN model dual feature extraction to model each subcluster. Finally, this method was applied to a wind power cluster in Jilin Province, China, and the RMSE decreased by 10.8%on average compared with other methods, which verified the effectiveness of this paper.

Energy storage has bidirectional fast power throughput and flexible layout, customized control strategy can be an effective means of power flow control in power system. Aiming at the short-term overload problem of local transmission and transformation equipment caused by source load fluctuation or component failure in a high proportion of new energy power system, a power flow decentralized coordinated optimal control strategy based on large-scale energy storage is proposed. Firstly, based on the impact energy of energy storage and the weight coefficient of each branch, the comprehensive control sensitivity is proposed, the controllable energy storage nodes with weak off-limit control effect on to be adjust branch were eliminated to realize the optimization of controllable energy storage nodes. Secondly, the dynamic optimization model is constructed with the goal of minimizing the total control cost, and the dynamic optimization model is transformed into a linear optimization model by using the big M method, the purpose is to consider the energy storage capacity adjustment and the minimum number of equipment involved in adjustment, and to develop an optimal control strategy.Finally, the effectiveness and rationality of the proposed strategy are verified based on the improved IEEE RTS24 bus system.

In order to improve the heating capacity and peak regulation capacity of generation units, the low-pressure cylinder zero output technology has attracted more and more attention. Based on a 300 MW pure condensing unit, the thermal system model was built by Ebsilon software and the system modeling after heat supply transformation was carried out. The thermal economy changes of the unit before and after the low-pressure cylinder zero output were compared and analyzed. The heat supply, power generation performance and standard coal consumption of the low-pressure cylinder zero output unit under different layout schemes of draining system of heat network were simulated under multiple working conditions. The results show that the minimum standard coal consumption of power supply is reduced by 31.63 g/（kW·h）。In each draining system layout scheme, the maximum heating extraction steam is 638.26 t/h, the minimum electrical load rate is 23.05%， and the minimum standard coal consumption for power supply is 161.30 g/（kW·h）。This research can provide useful guidance for the optimal arrangement of draining system and efficient operation of the low-pressure cylinder zero-output units.

 With the increasing proportion of new energy generation and the continuous expansion of power grid scale, the capacity of DC transmission system is constantly improving, and DC power grid with different voltage levels is the inevitable trend of future development. In this context, DC/DC converter, as the key equipment of DC power network, plays an important role in multi-voltage level interconnection scenarios. In this paper, the existing modular high-voltage and large-capacity DC/DC converters are summarized, classified and compared, then the topology, working principle and characteristics of the current modular high-voltage and large-capacity DC/DC converters are expounded, and the applicable scenarios of different converters are put forward according to their characteristics. Finally，suggestions for future research directions are put forward.

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 

Coal combustion coupled biomass power generation is an effective way to improve biomass utilization and reduce carbon emissions of thermal power plants. In order to explore the influence of six kinds of coal in Northeast China, such as corn stalks, Jingxi anthracite, Xishan lean coal, Longfeng Xizhong coal, Shenhua coal, Yima bituminous coal and Fengguang lignite ， on the heat transfer characteristics of furnace under different mixing ratios, a mathematical model of the influence of biomass mixed with coal on heat transfer characteristics of furnace is established in this study, and is verified its reliability. Secondly, taking a 1 000 MW ultra supercritical pressure boiler of a power plant as the research object, the heat transfer characteristics of the boiler were analyzed and calculated, and the effects of six kinds of mixed fuels on the furnace flue gas volume, furnace outlet flue gas temperature, water wall heat transfer flow, flame blackness in the furnace, average heat load of water wall, average furnace flame temperature and theoretical combustion temperature under different mixing ratios were analyzed. The results show that the mixed fuel composed of Jingxi anthracite and corn straw has the highest theoretical combustion temperature. Affected by the calorific value of the mixed fuel after mixing, with increase of mixing proportion, flue gas volume, heat transfer flow of water wall, average heat load of water wall and average temperature of furnace flame of the six mixed fuels show a downward trend.The work provides a theoretical basis for coal-fired power generation with high proportion of mixed biomass coupled combustion.

 During the ice melting process of the transmission line DC ice melting short circuit control system, the detachment of the ice coating causes the displacement and stress changes of the cantilever combining mechanism, resulting in structural instability, detachment of the moving contact and insulation failure. The analysis of the vibrational properties and the experimental investigation of the ice detachment were carried out. First, the Lagrange equation and the assumed mode method are used to create the mathematical model of the ice-shedding vibration of the combined cantilever mechanism of the ice-melting system, taking into account factors such as different ice-shedding conditions, parameter attributes, vibration directions, and the internal coupling relationship of the structure. Second, the finite element model of the ice melting system is created to perform simulation analyses. The results of the mathematical model are compared with the results of the finite element simulation analysis under the same working conditions. It is found that the maximum relative errors of displacement and tension of the cantilever combination mechanism are 5.89% and 4.62% ，respectively. The rationality of the hypothesis and the accuracy of the mathematical model are checked. Finally, the on-line vibration monitor is installed on the ice melting system, and the ice melting system vibration displacement test is performed to further verify the accuracy of the mathematical model.

At present, due to the increase in the penetration rate of renewable energy generated by wind power and photovoltaic power generation in China, the problem of lack of flexible resources is becoming increasingly prominent, and the volatility and uncertainty of new energy power generation such as wind power and photovoltaic power generation lead to greater pressure on the peak regulation and supply security of the power grid, and the power market mechanism has not been fully constructed, the market-oriented mechanism of electricity price is not mature enough, and the demand-side response resources have not been actively mobilized. With the continuous increase of the number of electric vehicles in China, and the disorderly access of electric vehicles will cause the adverse impact of “peak on peak"， so it is reasonable to arrange electric vehicles to participate in demand response in an orderly manner. Secondly, the ways in which electric vehicles participate in demand are explored, and the participation in demand response in the form of aggregators is determined. Then, the orderly charging and discharging strategy of electric vehicle aggregators is designed, the idea of electric vehicle load aggregators participating in demand response is proposed, and the trading mechanism of demand response is constructed. Finally, with the goal of benefiting electric vehicle users, electric vehicle load aggregator platform and power grid, the upper and lower limits of electric vehicle charging and discharging are formulated, and numerical simulation is used to verify them.

The high proportion of renewable energy such as wind power connected to the grid is a necessary path for the green and low-carbon transformation of the power system under the "dual carbon "goal, but it also brings enormous pressure to the safe operation of the power grid. Therefore, a game theory based integrated energy system（IES）optimization scheduling strategy for carbon capture is proposed in the article. Firstly, a comprehensive energy system carbon cycle optimization model was constructed to promote wind power consumption. Then, a two-layer game scheduling strategy with Stackelberg game was constructed and proved to be balanced. Finally, the improved differential evolution algorithm is used to solve the two-layer game model to meet the convergence speed requirements of the scheduling model.

 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.

 Vienna rectifier is the most common front part of the charging module of automobile DC charging pile, and the stable operation of the front system directly affects the running state of the whole charging module, so the fault diagnosis of Vienna rectifier is very important. In view of the open-circuit fault characteristics of Vienna rectifier's power switch and electrolytic capacitor, in this paper, a Complementary ensemble empirical mode decomposition （CEEMD） and Particle swarm optimization are proposed. PSO optimizes the diagnostic method of Random forest （RF） algorithm. This method takes the input current as the original signal, analyzes the waveform characteristics of the open-circuit fault of the core device, and uses CEEMD method to decompose the fault current signal. On this basis, the fault feature vector is constructed, and the extracted feature vector is input into the particle swarm optimization random forest model to identify the fault state. The Vienna rectifier simulation model is built to verify the feasibility and superiority of the proposed method. The simulation results show that the method has a good diagnosis result, the diagnosis rate reaches 93.8% and the diagnosis time is shortened. It has practical significance for the fault diagnosis of automobile DC charging pile.

The transmission tower-line systems are wind-sensitive structures, which can cause severe damage by wind-induced vibration. Therefore, it is necessary to apply control techniques to mitigate the damage. In this study, a novel SMA damper is used to control the wind-induced vibration of the transmission tower-line system. A finite element model of the system is developed using finite element software. Based on MATLAB software, a linear auto regressive filter method is adopted to simulate the time series samples of random fluctuating wind loads. According to the damping principle and working mode of the SMA damper, six different layout schemes are designed and their wind-induced vibration responses are analyzed respectively. The time series of the tower top acceleration and displacement under different schemes are obtained, and the wind loads with three different wind speeds are simulated to further analyze the damping effects under different schemes. A parameter analysis of the damper is conducted according to its structure and material, changing the spring stiffness, lead block thickness, and SMA wire material of the damper, and their effects are analyzed respectively. The results indicate that； among the schemes, arranging dampers on the tower head has the best effect on controlling the tower top displacement, and arranging dampers along the tower body has the best effect on controlling the tower top acceleration. The optimal damping effect is achieved when the spring stiffness is 500 N/mm, and the optimal damping effect is achieved when the lead block thickness is 7 mm.

 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.

In the power market clearing mode of traditional transmission and distribution network separation decision, there are some problems, such as high node electricity price and insufficient consumption capacity of wind power resources.in order to coordinate the imbalance between transmission and distribution network resources and information, the characteristics of power market under transmission and distribution cooperative decision-making are analyzed, and the double-layer clearing mode of Transmission system operator （TSO） and Distribution system operator （DSO） power market is constructed. The lower-level DSO decision is transformed into an equilibrium constraint by using the KKT （Karush-Kuhn-Tucker） condition, and through the dual programming of the second-order cone and the linearization of the lower-level KKT, it is transformed into a single-layer decision model with Mathematical program with equilibrium constraints （MPEC）。 The experimental results show that the model successfully mobilizes the resources of the transmission and distribution side, reduces the market clearing price, improves the economy of the system, and has a positive impact on the operation of the power system and market coordination.

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 flexible DC grid is one of the effective solutions to solve the problem of large-scale new energy transmission and consumption, the DC circuit breaker is an important device for realizing the DC side fault isolation of the flexible DC grid, however, the current limit part of existing topology are less coordinated with the commutation part. Therefore, this paper proposes a multi-port circuit breaker topology with capacitors as current limiting and commutation parts. Through the cooperation of current limiting capacitor and commutation capacitor, the circuit breaker can complete current limiting and accelerate the commutation. In addition, the operation principle of the circuit breaker in the typical DC side fault is analyzed, the relationship between the voltage and current stress of the circuit breaker during operation, the energy consumption of the arrester and the parameters of system and circuit breaker is analyzed, and the design basis of circuit breaker parameters is given. Finally, the breaking and reclosing of the proposed circuit breaker are simulated and verified in PSCAD/EMTDC, and compared with the existing topology, which proves the feasibility of the proposed DC circuit breaker topology.

Under the background of the "carbon peaking and carbon neutrality" goals and the construction of new power systems, the proportion of distributed energy resources in the distribution network has been increasing year by year. However, new energy generation is random and intermittent, and with the increasing peak-to-valley difference of loads, it is difficult to satisfy the demand for peak load following with only traditional generation resources. With the development of demand response technology, it has become possible to regulate flexible resources on the load side. There is an urgent need to explore the adjustable potential of controllable loads, analyze their regulation capability qualitatively and quantitatively from the perspective of the system, and establish their external characteristic models so as to be precisely dispatched. In this paper, research is carried out on inverter air conditioners on the customer side. First, the load model and control method of inverter air conditioners are clarified；then the qualitative assessment of the regulation potential of inverter air conditioner aggregation is carried out；then, according to different regulation scenarios, the external characteristic model of inverter air conditioner aggregation is established；and finally, the example verification is carried out in the active power distribution network. The result shows that the inverter air conditioner aggregation has similar external characteristics and regulation potential as the traditional generator, and can effectively participate in the optimization of the active distribution network scheduling.

 For a multi-source integrated system incorporating wind, fire, and storage, the wind power output exhibits uncertainty. There is a discrepancy between the predicted and actual power of the wind turbine during specific time periods. When the actual output of the wind turbine fails to meet the scheduled power in the dispatch plan, it leads to a significant reduction in the economic efficiency of the system. To address this issue, this paper proposes a two-layer optimization strategy that considers wind power prediction errors and demand-side response. The upper-level model aims to minimize the overall operating cost of wind power, thermal power, and dispatchable loads, utilizing an Improved Particle Swarm Algorithm（IPSO）to formulate optimal scheduling strategies for thermal power and dispatchable loads. Subsequently, the Gibbs method is employed to sample the probability density function of the maximum output prediction error of the wind turbine, obtaining a certain amount of samples and determining the power deficit for each sample in the upper-level power sources. The lower-level model aims to minimize the overall operating cost of energy storage and interruptible loads. It employs linear programming to offset the power deficits from the upper-level sources, thereby formulating the lower-level model's power dispatch strategy. With a large number of sampled scenarios, the proposed two-layer optimization strategy's economic and effective nature is validated by comparing the expected value and variance of the total cost function values for each sample.

Power-type energy storage and energy-type energy storage can be combined in a certain proportion to form a hybrid energy storage system, which can significantly enhance the power output of the energy storage system. In order to fully utilize the advantages of hybrid energy storage in participating in the primary frequency regulation of wind farms and consider economic factors, a capacity optimization configuration method based on variation mode decomposition is proposed. Firstly, a mathematical model is established with the objective of maximizing the net benefits of the hybrid energy storage system. Next, the power demand signal is decomposed into high-frequency power demand and low-frequency power demand using the variation mode decomposition method. Finally, taking a 100 MW wind farm in the Northeast as a case study, based on power demand data for a typical day, considering constraints such as energy storage charging and discharging power and state of charge, the objective model is solved using the quantum particle swarm algorithm. The results show that the optimized energy storage configuration scheme can effectively improve the economic viability of hybrid energy storage for assisting the primary frequency regulation of wind farms.

 In the context of "dual-carbon"，in order to further enhance the economic and environmental benefits of integrated energy system, the paper proposes a low-carbon optimal scheduling methodology for IES under the reward-penalty ladder-type carbon trading mechanism, taking into account a photovoltaic power plant with heat recovery device and integrated demand response. Optimal scheduling method. Firstly, the IES architecture for the joint operation of a photovoltaic power plant with heat recovery device and a cogeneration unit with carbon capture is constructed on the source side, and the operation principle of the two stages of power-to-gas conversion is analysed to establish a model of power-to-gas conversion equipment taking into account the waste heat recovery. Secondly, considering the flexible characteristics of the three loads of electricity, heat and gas on the customer side, an integrated demand response model for electricity, heat and gas is established on the load side. Finally, the carbon trading mechanism is introduced to further reduce the carbon emissions of the system,s o as to construct a low-carbon optimal dispatch model of the integrated energy system with the goal of minimising the total operating costs of the system, including the energy purchase cost, operation and maintenance cost, and the carbon trading cost, during the scheduling cycle. The results of the analyses show that the proposed method not only improves the operating potential of the units, but also effectively reduces the total system operating costs and carbon emissions.

 Proton exchange membrane（PEM）water electrolysis hydrogen production technology is one of the main methods for producing green hydrogen, but its hydrogen production efficiency is influenced by many factors.Considering the influence of input power on the hydrogen production efficiency of electrolyzers, this paper introduces an integrated energy system optimization model that accounts for the variability in electrolyzer efficiency. Firstly, the coupling relationship between hydrogen production efficiency and electrolyzer input power is studied. Utilizing historical data analysis, a correlation curve is established to depict the relationship between electrolyzer power and hydrogen production efficiency. Secondly, by combining the stepwise carbon trading mechanism with the green certificate trading mechanism, a carbon-green certificate trading mechanism is proposed. Subsequently, a comprehensive energy system optimization dispatch model is developed, which takes into account the fluctuation in hydrogen production efficiency and incorporates considerations regarding hydrogen energy green certificates, with the primary objective of minimizing the total system cost. Finally, through case analysis, the effectiveness of the proposed model in reducing the total operating cost of the system is verified.

 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.

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.

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.

 Conductor icing seriously affects the safety of power grid operation, the local collision coefficient is a key indicator to characterize the growth rate of transmission conductor ice cover, the traditional steel core aluminum stranded wire or its simplified cylindrical model of the growth of the ice cover characteristics of the previous analysis, the aluminum conductor composite core （ACCC），as a new type of conductor that is developing rapidly, the local collision coefficient and the growth process of the ice cover has rarely been studied. First realized the numerical simulation of ice cover growth based on the commercial finite element software Fluent, and verified the validity of the simulation method by comparing with the simulated test results. Subsequently, using the validated numerical simulation method, a comparative study of the ice cover growth characteristics of the ACCC refined model and the simplified circular conductor model was carried out to simulate the distribution of droplet collision coefficients on the surfaces of the two, and the effects of different median diameters of the raindrops and the change of the wind speed on the collision coefficients were discussed, and the icing ice shapes of the ACCC model were obtained. The results show that: the local collision coefficient of ACCC model is significantly smaller than that of round model when the wind speed is low, at the early stage of ice-covering, the ice shape is very significantly affected by the surface configuration of conductor, when the surface of conductor is completely wrapped by the ice-covering, the resistance coefficient of the round model is 15.3%lower than that of the ice shape of ACCC model as a whole, and it shows galloping instability under each wind attack angles. The results of the study are valuable for obtaining the growth characteristics of ACCC ice cover and understanding the disaster mechanism of ice cover on conductors with different surface configurations.

 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.

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.

 In this paper, a new type of bi-fluid photovoltaic/thermal roof module without cover is proposed. By combining the water-cooling duct of tube-plate with the air-cooling duct of baffle-plate, the water capacity of the component is reduced and the air outlet temperature is increased, and the supply of hot water and hot air for the module is realized. By building a performance test bench with a stable testing environment, the temperature difference between the inlet and outlet of the module and temperature of the module with solar irradiance and working fluid flow was studied, and the all-day thermal and electrical performance of the module was analyzed. The results show that the module has an obvious cooling effect. The electrical efficiency of water cooling and air cooling modes can reach up to16.80%and 17.62%.It has high all-day comprehensive performance and the all-day primary-energy saving efficiency is up to 74%.

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.

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 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.

 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.