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Under the 'dual-carbon' goal, industrial parks, as the most important and extensive carriers of industrial systems, must undergo low-carbon transformation. In this context, this paper establishes a bi-level optimal dispatching model of low-carbon industrial park considering flexible scheduling of high-energy-consuming enterprises' production workshops. The model fully exploits the flexible adjustment ability of high-energy-consuming enterprises, obtains the optimal low-carbon scheduling plan of the park by flexibly adjusting the production scheme of high-energy-consuming enterprises to realize the coordinated operation of the industrial park and high-energy-consuming enterprises. Firstly, the upper layer establishes an optimal scheduling model with the objective of minimizing the total operating cost, taking into account carbon trading and tradable green certificate costs. Then, the lower layer focuses on the flexible scheduling problem of the high-energy-consuming enterprise's production workshops within the industrial park, aiming to minimize the maximum completion time and cost. The cost savings achieved by enterprise scheduling at the operational layer are used as subsidies. The upper and lower layers continuously coordinate and schedule plans to achieve the optimal objective. Finally, the feasibility and effectiveness of the proposed model are verified through case studies. The proposed approach not only reduces production costs and improves production efficiency but also effectively promotes load balancing, realizing the low-carbon operation of the industrial park.

Iron-based soft magnetic composites have the characteristics of high magnetic permeability, high magnetic induction strength and low iron loss. It is of great significance to study the vibration and noise characteristics of this material reactor for the design of vibration and noise reduction. In this paper, based on the finite element simulation model, the vibration and noise distributions of the reactors under normal operating conditions are calculated and analyzed through the magnetic field-structure-acoustic multiphysics coupling. The noise measurement system of the reactor is built, and the noise signals of the silicon steel core, hybrid iron core, and iron-based soft magnet core reactor are measured separately for experimental verification. The results show that the noise of the hybrid iron core and iron-based soft magnetic core reactors is significantly lower than that of silicon steel reactors. The hybrid reactor is least affected by current changes The simulation data shows that the magnetostriction to Maxwell force noise ratio of silicon steel core reactor is 1.15. Magnetostriction occupies the largest proportion. The main reason for the low noise of iron-based soft magnetic core reactor is that the magnetostrictive effect is negligible.

The access of wind power reduces the carbon emissions of the power system from the generation side, and the introduction of demand response to eliminate wind abandonment provides a new idea for carbon reduction from the load side. Considering wind power and demand response comprehensively, based on the theory of carbon emission flow of power system, a day-ahead and day-in two-stage low carbon optimal dispatching method for power grid is proposed. Firstly, the carbon emission flow theory of power system is analyzed, and the node carbon potential model of load side is established. Then, the flexible load is divided into two types, transferable load and reducible load. Based on the carbon potential model of load nodes, the response mechanism of calling these two types of loads to reduce carbon is designed. On this basis, the source load coordination day-ahead optimal scheduling model considering low-carbon and economic is established. Based on model predictive control, the day-ahead optimal scheduling model is solved, and the day-ahead scheduling results are changed through feedback correction. Finally, the simulation results of the improved PJM-5 node system and IEEE 300-node system show that the proposed optimal scheduling method can effectively promote the flexible load to absorb wind power, and reduce wind abandonment, and achieve the goal of load side carbon reduction.

Rural areas with weak distribution networks often suffer from a lack of energy supply reliability, which makes it difficult to widely implement multi-energy complementary systems connected to large-scale photovoltaic. Energy storage systems, as a link to the integration of new energy systems, can effectively improve the reliability of energy supply in such areas. To this end, a cooperative and optimal configuration strategy for rural multi-energy complementary system (RMES) energy storage for weak distribution networks is proposed. Firstly, the RMES architecture including biomass waste energy conversion system is clarified. Secondly, an energy storage configuration evaluation criterion is proposed using the cost of supply deficiency loss of the system as a judgment basis. Finally, the RMES multi-energy storage cooptimal allocation model is established to take into account the total life cycle cost of energy storage. The model is decoupled and transformed into a two-layer optimization model with two stages of planning operation, and solved by a hybrid strategy combining particle swarm algorithm and Gurobi solver. The analysis of the algorithm shows that the proposed energy storage configuration evaluation criteria effectively motivate RMES to deploy energy storage. In addition, the developed multi-variate energy storage configuration model enables RMES to show better economic and environmental benefits, and is superior in improving system reliability.

Against the backdrop of rapid growth in electric vehicle holdings, there is a growing demand for the construction of electric vehicle (EV) charging stations. To improve the charging station operation economy, an optimal scheduling method of EV charging stations with access to shared energy storage is proposed. Firstly, the operation modes of distributed energy storage and shared energy storage are analyzed, and the two-layer optimal scheduling model of EV charging station considering different operation modes of energy storage is constructed by taking the lowest annual investment cost and annual operating cost of charging station as the upper level objective function and the lowest typical daily operation cost as the lower level objective function. Secondly, three EV charging stations with differentiation are simulated and different energy storage operation modes in multiple scenarios are compared. Sensitivity analyses are then conducted on this basis for the effects of shared energy storage service fees and EV discharge losses on dispatching results. Finally, the example shows that shared energy storage access has a positive effect on reducing the operating costs of charging stations, and that reasonable pricing of the energy storage services and the cost of EV discharge losses can reduce the operating costs of charging stations.

At present, with the vigorous development of power Internet of Things, how to sustain and supply energy for a long time has become a technical problem that tens of thousands of sensors need to face. Triboelectric nanogenerator (TENG), as a new high efficiency energy supply technology, has a very broad application prospect in the field of sensor self-power supply. In this paper, based on the working principle of triboelectricity, a multi-layer elastic TENG energy harvesting device for transmission line breeze vibration is designed by using the vertical contact of the multi-layer elastic structure to separate the TENG, and the transmission line breeze vibration state is simulated by the output performance test platform of the vibration energy collector. The basic electrical characteristics of energy collectors at different frequencies and amplitudes are tested, and combined with power management strategies, a self-power supply system for vibration energy acquisition for transmission line breeze vibration is constructed, which realized efficient acquisition and conversion of wide-band vibration energy and completed energy supply for commercial sensors. Finally, the validity and feasibility of the vibration energy collection device designed in this paper are verified by the vibration reduction model of the transmission line. The vibration energy acquisition self-power supply system designed in this paper can effectively convert the broadband vibration energy of the transmission line into electric energy, and has the characteristics of simple structure and good economy, which can provide a new solution to solve the power supply problem of sensors for power Internet of Things.

Pumped hydro storage (PHS) is the most mature storage technology with the largest installed capacity. However, its power regulation rate is slow, and its adjustment flexibility is relatively lacking. Electrochemical storage, which is currently the fastest developing storage equipment, provides capability of flexible power regulation. A photovoltaic-battery-pumped hybrid energy storage system is constructed in this paper. The goal is to improve the flexibility of PHS by utilizling the complementary characteristics of different storage facilities. The power regulation capability of the unit based on the power oscillation interval description of pumped storage is described, and further defines the flexibility of PHS according to the regulation of single unit and the unit-commitmen of multiple units. Considering the flexibility enhancing constraints and the demand to improve the operational lifespan of PHS, a capacity optimization strategy for the battery in hybrid energy storage system is established. A case study is conducted using a PHS in Shandong province as an example. The findings reveal that configuring an electrochemical energy storage system with a rated power equal to 10% of the PHS capacity can improve the flexibility of the storage system by about 40%, and reduce generation start-up times by 14%. However, under the current electricity pricing structure, the peak-valley price gap needs to surplus 0.5 yuan per kW·h for the electrochemical storage facility to become profitable.

With the large-scale integration of wind power into the grid, the inertia and disturbance resistance of the power system are gradually declining, leading to an increasingly prominent frequency stability issue. An adaptive frequency support control strategy for wind farms based on rotor kinetic energy is proposed. Firstly, a participation factor is proposed, which determines the degree of wind farm participation in frequency support based on the average rotor speed of the wind farm and adaptively adjusts the inertia response parameters and frequency droop control parameters of wind farms. Based on the real-time available rotor kinetic energy of wind turbines, the frequency modulation power of wind farms is dynamically allocated. The frequency support ability of wind turbines with more rotor kinetic energy is fully utilized and excessive participation of low-speed wind turbines is avoided in frequency modulation. After the frequency support is completed, a staged rotor speed recovery method is used to restore the rotor speed of the wind turbines. Simulation results show that the proposed strategy can adaptively adjust the active output power based on the operating status of the wind farms and the available rotor kinetic energy of the wind turbines while achieving effective support for the system frequency and avoiding secondary frequency drop.

Aiming at the problem of insufficient accuracy in wind power prediction caused by the lack of target meteorological forecast data, a wind power prediction method based on spatial correlation and Stacking ensemble learning is proposed in this paper. Firstly, the spatial correlation between the target wind farm and adjacent meteorological stations is analyzed. The delay time is determined based on the extreme points of the correlation coefficient, and a wind speed time-shift dataset is constructed. Secondly, the Stacking ensemble method is used to integrate multiple algorithms to predict the wind power of the target wind farm from multiple data observation perspectives. It leverages the complementary advantages of different algorithms, enhancing overall generalization ability. Additionally, it can effectively balance search time and model performance by adopting the particle swarm optimization algorithm to search for model hyperparameters. Finally, the effectiveness and accuracy of the proposed method have been verified by the measured data from a wind farm in East China. The results show that it can effectively improve the wind power prediction accuracy in the case of missing data by considering the information bias at different locations with the data input and prediction models.

Lithium ion batteries are widely used in chemical energy storage systems. However, due to their inherent heat generation characteristics, thermal runaway has become a major safety hazard for chemical energy storage power plants. Therefore, optimizing the design of a battery thermal management system to effectively avoid thermal runaway is crucial for the safe operation of chemical energy storage systems. A new type of parallel serpentine flow channel liquid cooling plate with both series turn back and parallel branch structures is designed. Through simulation experiments, the effects of the flow channel structure of the liquid cooling plate, the layout of the liquid cooling system, and the inlet flow velocity of the coolant on the maximum temperature, temperature uniformity, and inlet and outlet pressure drop are studied to optimize the liquid cooling system. The results show that, under the same coolant inlet flow rate, the maximum temperature of the new channel is reduced by 0.284 9 K, and the temperature difference within the module is reduced by 0.466 3 K compared with the traditional parallel flow channel. The inlet and outlet pressure drop is reduced by 40.18% compared with the traditional serpentine flow channel. Based on the parallel serpentine flow channel liquid cooling plate, the optimal layout scheme for the liquid cooling system is the injection of coolant at the two split ports and the staggered arrangement of the liquid cooling plate. Different liquid cooling plates have different flow velocity settings. The inlet flow velocity of the two liquid cooling plates is set to 0.1 m/s, and the inlet flow velocity of the central liquid cooling plate is set to 0.2 m/s. Compared with the same flow velocity of 0.2 m/s for the four plates, the temperature difference within the battery module group is reduced by 13.62%, the inter column temperature difference is reduced by 82.59%, and the energy consumption is reduced by 44.87%, achieving an optimization effect of 'cost reduction and efficiency enhancement'. A reasonable flow channel structure, staggered cold plate layout, and differentiated inlet flow rate design can optimize the liquid cooling system of battery modules and increase the safety of battery module operation.

Developing offshore wind power is an important measure to achieve the goal of 'dual carbon'. DC submarine cables are important devices in offshore wind power transmission projects, and the research on the ampacity of submarine cables plays an important role in promoting the large-scale development of offshore wind power. In recent years, the research on the ampacity of high-voltage DC submarine cables has considered relatively single marine environmental factors, and the limitation of temperature difference of insulation layer has not fully be considered. The article establishes an electric-thermal-current coupling model of the 500 kV DC submarine cable and the seawater system. Under different laying methods for single and bipolar submarine cables, the effects of vertical ocean currents (currents flowing perpendicular to the length direction of the cable) flow velocity, limitation of temperature difference of insulation layer and the the different spacing of the bipolar cables on the ampacity are studied. The results show that considering the temperature difference limitation 20 ℃ of the insulation layer comprehensively has a smaller ampacity compared with the situation only considering the temperature limitation 70 ℃ of the wire core, and direct burial laying has a smaller impact on the ampacity compared to any other laying method. It is also found that the ampacity of bipolar submarine cables increases with the increase of the distance between the two poles. When the flow rate is 0.1 m/s, the vortex have a small improvement effect on the ampacity of the submarine cable. The electric field flips around a temperature difference of 6 ℃ in the insulation layer. The research results can provide important guidance and reference for the selection of laying methods, and even for the prediction or evaluation of ampacity.

Accurate short-circuit fault current calculation is important for device selection, parameter design and protection research of flexible DC grid. To solve the problem that existing fault current calculation methods do not consider the pole-to-pole coupling of DC lines, a short-circuit fault current calculation method based on phase-mode transformation is proposed. First, the equivalent fault models of the converter station and DC line are established. Then, the phase-mode transformation is used to achieve electrical decoulping of positive and negative poles, and the node impedance matrix of the DC grid in the mode-domain is obtained. Subsequently, combining the fault boundary conditions of the DC grid, the fault current of the DC grid is calculated in the complex frequency-domain, and the fault current in the time-domain is obtained by using vector fitting. Finally, the proposed fault current calculation method is verified by PSCAD/EMTDC. The simulation results show that the proposed method can accurately calculate the DC fault currents after the DC fault occurs and before the converter station blocks.

Permanent magnet synchronous motor (PMSM) has been widely used in industry due to the advantages of high efficiency, high power density and high reliability. In this paper, a finite-control-set model-free predictive current control (FCS-MFPCC) based on extended control set is proposed for permanent magnet synchronous motor drives. At first, the mathematical model of PMSM is analyzed and the principle of finite-control-set model predictive current control (FCS-MPCC) is elaborated. Then, the traditional FCS-MFPCC based on linear extended state observer (LESO) is introduced. In order to tackle the issue of dissatisfactory steady-state performance of the traditional FCS-MFPCC, a control-set extension method based on the discrete space vector modulation (DSVM) is utilized, by which, the number of voltage vectors can be increased to 25. Following this, a fast optimization strategy is proposed to solve the problem of high computation burden caused by the extended control set. The principle and procedure of implementation of the strategy is explained in detail. Finally, the effectiveness and superiority of the proposed control strategy are verified by comparing the traditional and the proposed FCS-MFPCC methods based on a 500 W PMSM experimental test rig. The results show that the proposed control strategy can significantly enhance the steady-state performance of the system. The total harmonic distortion of stator current can be reduced from 10.07% to 6.48%.

Virtual power plants, as a comprehensive energy network with multi-energy flow interconnection, have become an important player in China's accelerated pursuit of its dual carbon goals. However, it is difficult to coordinate internal resources with low-carbon emission when facing challenges such as tight coupling of multi-energy flows, subjectivity of traditional carbon trading model parameters and difficulty of online optimization with high-dimensional dynamic parameters. To address these issues, this paper proposes a virtual power plant multi-energy low-carbon dispatching method that integrates the attention mechanism (AM) and soft actor-critic (SAC) algorithm. Firstly, based on the random carbon flow characteristics of virtual power plants, an improved stepped carbon trading mechanism based on Bayesian optimization is established for dynamic parameters. Next, an economic benefit and carbon emission-based objective function is constructed for the decoupling model of multi-energy flows in virtual power plants. Considering the high-dimensional nonlinearity and real-time updating of weight parameters in this model, the improved SAC deep reinforcement learning algorithm with integrated attention mechanism is used to solve it in a continuous action space. Finally, simulation analysis and comparative experiments are conducted to verify the feasibility of the proposed method and its efficiency compared with SAC algorithm.

With the gradual increase of the proportion of renewable energy in the power system, the risk of frequency fluctuation in the power system increases. Flywheel and lithium battery can complement each other as hybrid energy storage applied in the primary frequency regulation of the grid, effectively solving the problem of system frequency fluctuation. In order to give full play to the respective frequency regulation advantages of flywheel and lithium battery, a primary frequency regulation (PFR) strategy for battery-flywheel hybrid energy storage based on adaptive state of charge (SOC) is proposed. Firstly, a weight allocation PFR is proposed, containing three control methods, namely, positive and negative virtual inertia control and virtual droop control. Secondly, the parameters of the PFR are corrected by using the SOC of the doubly-fed flywheel and the Li-ion battery, so as to improve the PFR capability of hybrid energy storage near the threshold of SOC. Finally, the control strategy of the hybrid energy storage with the other control strategies is compared with that of this paper in simulation under the frequency regulation scenarios. The results show that the SOC fluctuation range of the energy storage system of the strategy proposed in this paper is minimum. The battery will not be overcharged and overdischarged, and the system frequency fluctuation is kept no more than ±0.2 Hz, which proves that the proposed strategy can improve the frequency stability of the grid.

The advantages of fast charging speed and high efficiency of DC charging piles make the connection and cutting of electric vehicle (EV) loads relatively frequent. However, as a DC system, DC charging pile has the characteristics of low inertia and weak damping. In order to reduce the impact of EV load connection and cutting on the DC side voltage disturbance, a DC charging pile control method based on improved virtual inertia (VI) control is proposed. This paper firstly introduces VI control by analogy with virtual synchronous machines (VSM) technology. Secondly, the VI control is improved by using command filter backstepping integral sliding mode (CFBISM) control, in which the integral sliding mode (ISM) control is used to optimize the VI control to enhance the robustness of the system, and the command filter backstepping control is used to reconfigure the key parameters to avoid the computational inflation of the controller, while the ISM control is used to improve the current inner loop to further enhance the control effect. The stability of the proposed control strategy is then demonstrated by the Lyapunov stability criterion. Finally, through comparative simulation, it is verified that the DC-side voltage fluctuation can be limited within 2 V, the dynamic response speed is improved by about 0.1 s, and the perturbation of the key parameters in the steady state is limited to about 1 V, thus the superiority of the fast response speed and good robustness of the control proposed in this paper are verified by simulation.

In order to improve the orderly control and flexible adjustment capabilities of large-scale distributed power sources connected to the distribution network, it is currently an effective method to reasonably divide the distributed power sources into clusters and use the cluster as the basic unit for regulation. To this end, a distributed power cluster partitioning method that considers the adjustable capacity and response speed of flexible resources is proposed. Firstly, the modularity index and the active power balance index are proposed to characterize the structural and power balance capability of clusters. Secondly, based on the analysis of the cluster's flexible response capability, and in view of the problem that it is difficult to quantify the impact of the flexible resource response capacity and response speed on the adjustment capability, it is proposed to take the cumulative area of deviation between the response curve of cluster output and the net load curve as the indicator of the flexible response capability of clusters, and the influence of the allocation of energy storage capacity on the delineation of clusters is also taken into account. Then, a cluster division objective function that comprehensively considers the modularity index, active power balance index, cluster flexible response capability index and energy storage unit allocation index is proposed, and this function is solved using an improved adaptive genetic algorithm. Finally, the proposed method is verified in the improved IEEE 33-node system and IEEE 69-node system. The results show that the cluster partitioning method based on the proposed comprehensive performance index can improve the cluster flexible response capability by more than 20% on the basis of ensuring the structural strength of the cluster, which verifies the effectiveness and superiority of the cluster partitioning method proposed in this paper.

In severe convective weather, transmission lines are prone to lightning strikes, wind swings, rain flashes and other faults that threaten the safe operation of the power grids. To overcome the problem that the existing nowcasting cannot fully meet the demand for refined weather forecasts for transmission line risk warning, a deep-learning-based nowcasting model of severe convective is constructed in this paper. The model is built by using meteorological radar echo image, assimilated data of wind speed and rainfall, lightning location data of the power grid and it is used to carry out early warning of transmission line risks. First, an long short-term memory (LSTM) network-based forecasting model of severe convective meteorological elements is constructed by taking the meteorological radar echo and its time-series extrapolation data as inputs, and assimilated data of wind speed and rainfall, lightning density, lightning current intensity as outputs. Then, combined with the wind, rain, and lightning forecast output from the model, the risk of wind swing, lightning strike, and tower collapse in the transmission corridor grid is evaluated. The fault probability of the transmission line is calculated in a comprehensive way for risk early warning. Finally, a case of successful early warning of severe convective weather processes in a province in September 2023 is demonstrated, which demonstrates the ability of the proposed method to improve the risk early warning capability of transmission lines under severe convective weather.

A virtual power plant (VPP) is proposed to aggregate various resources to participate as a whole in both electricity and carbon trading markets. As the scale of VPPs continues to expand, they are transitioning from being price takers to price makers. To this end, this paper treats the VPP as a price maker and proposes a bi-level bidding strategy in the day-ahead electricity market, considering the impact of carbon trading. Firstly, an introduction and analysis of the day-ahead electricity market mechanism, considering carbon trading, are provided. Secondly, based on the Stackelberg game theory, a bi-level bidding model in the day-ahead electricity market is established with the VPP as the bidding entity. The upper-level model aims to maximize the anticipated profit of the VPP, while the lower-level model aims to minimize the system's clearing cost. Considering the uncertainty in wind farm output predictions within the VPP, operators are provided with two bidding strategies: risk-averse and opportunity seeker strategies based on the information gap decision theory (IGDT). Then, utilizing the strong duality theory, the Karush-Kuhn-Tucker (KKT) optimality conditions, and the big-M method, the bi-level model is simplified into a mixed-integer linear programming problem for resolution. Finally, an example is provided to illustrate the optimal bidding strategy and operation plan for the VPP, along with an analysis of how uncertainty in wind farm output predictions within the VPP affects the expected profit of the VPP. The example shows that VPPs can influence market prices through strategic bidding decisions. After considering carbon trading, the expected revenue of the VPP increased by 5.1% compared to the scenario without carbon trading.

In the future new power system, the multi-agent trusted transaction and information security in the virtual power plant (VPP) will be complex and challenging. The features of blockchain technology, such as information security, distribution decision, smart contract and tamper-proof, provide a new idea for VPP multi-subject trusted transaction. This paper focuses on the benefits maximization formed by multi-aggregator inside VPPs and the efficiency of trusted transaction matching. Firstly, according to the different demands of transaction subjects, a master and multi-slave hierarchical interactive control architecture is established to integrate blockchain technology with multi-agent system. Secondly, a credible transaction matching mechanism is designed under the demand of multi-aggregator peer to peer transaction, and non-cooperative game model is introduced to ensure the interests of multi-aggregator subjects. Then, the blockchain-based distributed particle swarm optimization algorithm proposes a consensus algorithm improved by delegated proof-of-authority (DPoA) to improve the security of the transaction. Finally, the rationality and feasibility of the strategy proposed in this paper are verified by an example analysis, which effectively enhances the matching efficiency and security of multi-agent transactions.

In view of the problems of less interaction between source-load entities, high carbon emission intensity, low wind-solar power consumption capacity, and poor overall operating efficiency of the regional integrated energy system (RIES), an optimization method is proposed for the economic low-carbon operation of the RIES taking into account the demand response of electricity-gas-thermal prices. Based on the common commodity attributes of electricity, natural gas, and thermal energy and the dispatchable value of multiple flexible loads, a price-demand response model of electric-gas-thermal is established, which effectively enhances the incentive effect of price signals on load participation in demand response. To fully tap into the low-carbon potential of the system, stepped carbon trading is introduced to improve the actual carbon emission model. With the minimum system operation cost as the optimization goal, the influence of different operation modes on the economy and low carbon of the system is studied. The case study results show that the operation optimization model of price demand response and stepped carbon trading can achieve economic low-carbon system operation and wind-solar power consumption capacity while achieving peak-shaving and valley-filling.

Overhead ground wire (OGW) is an important equipment to prevent transmission wire from being struck by lightning. When OGW is struck by lightning, the sliding motion of arc root causes different damage mechanism. Therefore, it is necessary to analyze the sliding motion of arc root first, so as to provide data support of sliding displacement for the research of damage mechanism. In this paper, the sliding motion model of arc root along OGW is established based on the arc chain modeling method. By analyzing the main influence range of the electromagnetic force, the space boundary of modeling is narrowed, so the calculation amount is greatly reduced. Then, the model is verified by the needle-wire discharge experiment in the laboratory. Finally, based on the established model, the factors affecting the sliding displacement of arc root are analyzed, including thermal buoyancy, return stroke and continuous current. The results show that the effect of thermal buoyancy can be ignored under the action of return stroke. The sliding displacement of arc root is positively correlated with the wavelength time, but not with the wave head time. However, under the action of continuous current, thermal buoyancy affects the evaluation result of arc root sliding displacement, and the maximum error is more than 25%.

Before putting into operation, ultra-high voltage transformers need to undergo strict handover tests to ensure their safe and reliable operation. The grading capacity of the grading ring on the transformer will affect the accuracy of the handover test. When there are problems with high altitude environments or grading ring structures, their grading ability will change. It is particularly important to study and design grading rings that can have good grading ability in different situations. This article first uses COMSOL software to build a three-dimensional model of the withstand voltage test circuit of a 500 kV transformer. Secondly, the influence of changes in the pipe diameter and ring spacing of the equalizing ring on the equalizing capacity of the equalizing ring is studied. Finally, the variation of equalizing capacity of the equalizing ring in a rough state is studied. It is found that as the diameter of the equalizing pipe and the ring diameter increase or the distance between the rings decreases, the equalizing ability of the equalizing ring will be enhanced, with the greatest impact brought by the change in pipe diameter. When the grading ring has a rough surface, its grading ability will significantly decrease. Among them, the grading ability decreases most significantly when adhering to conical particles, and decreases least when concave, indicating that the smoother the surface of the grading ring, the better the grading ability. This study can provide some assistance for the design of grading rings for high altitude ultra-high voltage transformers.

With the development of new power systems, the protection and control tasks of distribution networks have become increasingly complex. When intelligent terminals are employed to handle these tasks, the requirements for balancing resource supply and demand have become move stringent. Therefore, a collaborative task allocation method for protection and control intelligent terminals (PCIT) in distribution networks considering elastic allocation of resources is proposed in this paper. Firstly, the technical architecture of multi-terminal collaboration is elaborated, and the container-based elastic resource model and task processing model within the terminal are established. Secondly, a two-layer model is proposed to optimize the cooperative assignment of protection control tasks among terminals and the elastic scheduling of resources. The implicit enumeration method is used to solve the model, so as to give full play to the flexibility of resources and improve the performance of task processing. Finally, the arithmetic example verifies the feasibility and advancement of the proposed method. The occupancy rate of computing resources of each intelligent terminal is reduced by about 28.85%, and the average processing delay of tasks is reduced by about 4.12%.

In the context of the dual-carbon goal, virtual power plants, microgrids and other forms of prosumers have emerged on a large scale. Energy sharing among multiple prosumers can improve the overall economic efficiency and new energy consumption. A collaborative operation mechanism for energy sharing among multiple prosumers under the weak centralization model is proposed. The mechanism considers the data privacy of each prosumer. Firstly, an internal scheduling model of prosumers with multiple distributed resources is constructed. The model considers the volatility and randomness of load demand and new energy output, quantifying the risk of uncertainty based on conditional value at risk (CVaR). Then, a weakly centralized tariff iteration mechanism for multiple prosumers is proposed, which uses the supply and demand relationship to guide the tariff update. Meanwhile, considering the privacy protection of prosumers, the power data aggregation method is designed based on Paillier homomorphic encryption algorithm and secret sharing principle. The method is able to obtain the system supply and demand information while ensuring the privacy of all parties. Finally, the effectiveness and rationality of the mechanism proposed in this paper is verified by an arithmetic example, and the overall cost of multiple prosumers is reduced by 12.6% after energy sharing.

Abstract The authors present the multi‐physical field performances comparative research for a 30 kW, 30,000 r/min high‐speed permanent magnet motor (HSPMM) when the motor is powered by the sinusoidal pulse width modulation (SPWM) voltage inverter and sinusoidal voltage source, respectively. Firstly, electromagnetic performances including torque, voltage and current of the HSPMM with different driving methods are compared and analysed by the finite element method (FEM). Considering the effects of high operation frequency, power losses of the HSPMM with different driving methods under full‐load conditions are calculated and compared with the skin effect and the proximity effect considered for HSPMM winding copper loss estimation. Based on the above analysis, a prototype driven by the SPWM voltage inverter is manufactured, with its electromagnetic and thermal performances tested and verified. In addition, several influencing factors of the HSPMM rotor eddy current loss are studied, with their effects on the HSPMM under different driving methods further analysed and compared as well. A novel equivalent power supply method is proposed to effectively save the calculation time with a negligible error. Finally, in order to further improve the heat dissipation capacity of the HSPMM, a novel cooling method is intensively studied with its influencing factors further analysed. The cooling effect of the novel cooling method and the temperature of the motor components are verified and calculated by the computational fluid dynamics (CFD) method.

Abstract Large‐scale design optimisation techniques enable the design of high‐performance electric machines. Electromagnetic 3D finite element analysis (FEA) is typically employed in optimisation studies for accurate analysis of axial flux permanent magnet (AFPM) machines, which require extensive computational resources. To reduce the computational burden, a FEA‐based mathematical method relying on the geometric and magnetic symmetry of coreless AFPM machines is proposed to estimate the machine performance indicators using the least number of FEA solutions, thereby significantly lowering the running time. This method is generally applicable to AFPM machines with low saturation effects and cogging torque as exemplified for a printed circuit board (PCB) stator coreless AFPM machine. To further reduce the computation time, a systematically simplified equivalent 3D FEA model for planar PCB coils integrated with this machine is also proposed. The practical implementation of the introduced method is elaborated based on an example optimisation study, and an analytical method for fast design scaling is also discussed. The results of the proposed approach are compared with detailed transient FEA results, and a prototype 26‐pole PCB stator coreless AFPM machine was also used to validate the results experimentally.

Abstract Machine acoustics is an important area of research impacting the quality and comfort of human life. With increased levels of electrification and the wider use of electric motors, the contribution of motor drives towards quieter acoustic systems becomes increasingly important. This paper presents a novel acoustic improvement method involving the use of acoustic waves generated from High Frequency Injection to perform Active Noise Control. Although High Frequency Injection has been used widely in the domain of sensorless motor control, its acoustic generation process has been so far perceived as a negative by‐product. This paper presents the analysis and experimental results from the application of the proposed method to the Helicopter Electro‐Mechanical Actuation System. Considering the extensive use of motor drives in a number of industries, the proposed practice of High Frequency Injection Active Noise Control can have a significant impact to future applications.

Abstract Accurate calculation of equivalent circuit parameters is a prerequisite for accurately calculating the large‐capacity synchronous condenser parameter model. Due to its special transient operating conditions, the high transient magnetic saturation effect during operation causes the non‐linearity and time‐varying of the equivalent circuit parameters. The field mutual leakage reactance is the critical factor affecting the field current, and the time‐varying of the equivalent circuit parameters is closely related to the field current. However, the existing equivalent circuit parameter calculation methods considering field leakage reactance cannot achieve time‐varying parameters. A calculation method of time‐varying equivalent circuit parameters based on a back propagation neural network algorithm is proposed, which solves the calculation problem of time‐varying equivalent circuit parameters considering field mutual leakage reactance. Then, a 300MVar condenser is taken as the research object, and the proposed method is used to simulate the different operating conditions of the condenser and verified by the finite element method and experiment. The results show that the method improves the calculation accuracy of the equivalent circuit parameter model, reduces the calculation time, and applies to different operating conditions.

Abstract The paper suggests a design and optimisation approach for a consequent‐pole line‐start permanent magnet motor (CPLSPM) with flexible pole arc coefficients and high utilisation of rare‐earth (RE) materials, without the need for a variable frequency drive. The presence of dual‐sided slots and adjustable pole arc coefficient sets CPLSPM apart from other types of motors, making the analysis of its cogging torque more complex. Taking into account the double‐sided slotted and flexible adjustable pole arc coefficient, a cogging torque and airgap flux density model was established, and the influence of the pole arc coefficient on the characteristics of the cogging torque and airgap flux density of CPLSPM was analysed. The authors conduct multidimensional optimisation considering the coupling of multiple parameters to obtain a CPLSPM with minimal RE material usage, low cogging torque and excellent start‐up and steady‐state performance. Finite element simulation data are presented to validate the factors affecting the cogging torque and the feasibility of the proposed less‐magnetic CPLSPM design. Finally, a prototype of a 750 rpm/2.2 kW CPLSPM is built, and performance testing is carried out for comparison, and applied to submersible mixers.

Abstract The use of rare earth elements (REE) in permanent magnets (PMs) raises problems in several domains. The supply chain of these is fragile, the prices have shown volatility and its manufacturing has a bigger impact on climate change when compared to the manufacturing of other PMs. Instead, ferrite PMs have been researched as an alternative. This alternative shows a relatively higher demagnetisation risk when compared to REE PMs. Thus, a detailed study on permanent demagnetisation during winding faults is crucial. The authors use the finite element method to evaluate different machine designs, developed under mechanical constraints, and explore several strategies to mitigate permanent demagnetisation. Also, the importance of avoiding permanent demagnetisation is changed gradually in the optimisation process. The results show that the protection of the PM and performance optimisation are irreconcilable goals. It also highlights the impact of the stator design in decreasing demagnetisation. Additionally, it is shown that the classic notion of avoiding demagnetisation is an ineffective strategy for designing high‐performance machines with ferrite magnets, and instead, it should be integrated into the optimisation process and weighted according to the application demands.

Abstract Despite being a well‐known problem, bearing faults are still one of the major challenges that the industry face. The growing use of voltage source inverters imposed the alertness of possible bearing damage due to their high‐frequency signals. The aim of this paper is to investigate the effect of capacitive discharges on a rolling element bearing to obtain a series of faulty bearings with different deterioration levels. An ageing test bench is built to generate bearing roughness using Electric Discharge Machining. The purpose is to study the effect of operation conditions, such as frequency of drive, amplitude of shaft voltage, radial load level as well as rotational speed, on the capacitive discharge occurrence within the bearing. Having the desire to further understand this phenomenon, the influence of each parameter on the discharge activity and the discharge waveform is analysed. A worst‐case scenario is conducted and applied to a series of bearings. Finally, the bearing damage is examined, and a quantitative fault detection method is presented based on a microscopic inspection of the bearing's surface.

Abstract In order to address the issues of complexity, high cost, large volume, and low reliability associated with traditional H‐bridge cascaded converters when operating under high voltage, high capacity, and dual electric motor loads, the authors propose the utilisation of a nine‐switch converter as an alternative to the conventional H‐bridge converter for implementing cascaded multilevel converters in dual electric motor drive systems. After conducting an analysis and research on the topology and operational control strategy of cascaded multilevel converters based on the nine‐switch converter, a design is presented using six individual nine‐switch converter units to develop a cascaded multilevel converter capable of driving two 3 MW asynchronous electric motors at a 6 kV voltage level. Simulation verification is performed, and a scaled‐down prototype is built for experimental validation. The results demonstrate that, in comparison to traditional H‐bridge cascaded converters, the proposed cascaded multilevel converter can effectively drive dual electric motors at the same or different frequencies while reducing the number of switches to 1/4, the total transformer windings to 1/2, and Direct Current‐side capacitors to 1/6. This improvement enhances system reliability, portability, and load adaptability, thus offering increased versatility in dual electric motor drive applications.

Abstract A mathematical model of co‐axial magnetic gears is given for the prediction of magnetic field distribution and the magnetic forces. The modelling approach is based on the separation of variables method (SVM), Sturm–Liouville problem, and spectral analysis. This method is computationally more efficient and has the ability to account for finite permeability of magnetic saliency. An finite element method (FEM) validation is performed for a case study, and the results are observed to be almost matched. The computational time of the analytical model has been almost in the same order of that of the FEM for a specified rotor position (both in a matter of a second or less); however, when 100 number of rotor positions were accounted in the simulation, the computational time of FEM was increased to 82 s, while the computational complexity of SVM was almost unaffected.

Abstract A systematic definition of an aircraft generator's “available power” (used to supply loads on its DC bus) is given, which is defined in the context of constraints on transient and steady‐state performance. Using a geometric, data‐driven approach, such a characterisation has been achieved, and a new method, called Power availablE Estimation Tool (PEET), has been developed to determine in real‐time whether a given load can be fulfilled at a given time while maintaining power quality. This is an important problem, especially for safety critical electrical systems such as more electric aircraft, for which it is imperative to know a priori whether an added load will result in voltage variations outside of allowed values. PEET is introduced and its conceptual framework is formalised. Lastly, it provides simulation results that illustrate its performance. The results show that the PEET method produces reliable a priori estimates of power availability, and that this can be achieved within time frames that make it applicable in a real‐time implementation.

In order to analyze the loss, temperature rise and the mechanical structural response under the combined magnetic tension and thermal stress of the stator core, the electromagnetic-temperature-stress coupling calculation for the stator core of a synchronous generator is carried out in this paper. Firstly, the core loss and the magnetic pull per unit area are theoretically deduced, followed by an analysis of the core's temperature rise characteristics. On this basis, the mechanical structure response of the core under the coupling excitation of magnetic pull and non-uniform thermal load is obtained. Then, a three-dimensional finite element model of the CS-5 synchronous generator is established. This model calculates the magnetic pull per unit area, loss curve and temperature distribution of the stator core. Furthermore, the deformation, strain and stress of the stator core under the simultaneous action of magnetic tension and thermal load are obtained. The results show that the stator slot temperature is highest when the generator runs stably. The deformation at the groove is largest and the stress at the bottom of the groove is higher. Finally, the temperature rises of the end face, inside slot and outside circle of the stator core are monitored in real-time by thermocouples and a temperature monitor. The measured temperature distribution of the stator core is in good agreement with the finite element simulation results, verifying the effectiveness of the electromagnetic-temperature-stress coupling method. In this paper, the temperature distribution of the stator core and the mechanical structural response distribution of the stator core under magnetic and thermal coupling excitation are obtained, providing a technical reference for the reverse optimization design of the generator structure and the prevention of stator core deformation.

Overhead transmission lines are the significant component of electric power system, where the over current can be coupled with the transient electromagnetic field or excitations (such as high-altitude electromagnetic pulse). As the coupling path of strong electro-magnetic interference, overhead transmission lines cause serious interference to the power system. Among the existing modelling methods, the classical transmission line theory may generate large error when dealing with the high-frequency coupling problem, where the cross dimension of the transmission line is not electrically small. Numerical full-wave method (such as moment of method) which relies on the grid subdivision with low efficiency when dealing with long transmission lines. Moreover, the number of cables is usually large in electric power system, and the ground are considered as the lossy ground. Therefore, to address the above mentioned problems, an asymptotic method is proposed to calculate the high-frequency coupling current along overhead transmission lines in electric power system. Based on the asymptotic theory with high calculation efficiency, the scattering and reflection process are introduced to quantify higher-order model components. In addition, the arbitrary number of wires, arbitrary parameters of the ground and different excitations are considered to derivate the current expression. Finally, the validity and reliability of the proposed method are tested using the full-wave simulation and antenna irradiation experiment. The proposed method can quickly calculate high-frequency coupling current, which can provide theoretical basis and data support for protection and electromagnetic effect study of overhead transmission lines.

Integrated energy systems enable the complementary utilization of various forms of energy. With the rapid increase in installed capacity of distributed generations, their intermittency and randomness have posed significant challenges to the operational efficiency and safety of the system. To address the impact of uncertainties in both energy supply and demand on the economic scheduling of building integrated energy systems, this study first models the operational characteristics of each subsystem, including the power grid, natural gas network, and various coupled equipments. Next, a thermal cell model of the building users is constructed based on the quantitative relationship among temperature, thermal radiation, and thermal load. Then, a day-ahead optimization scheduling model for the building integrated energy systems is established with the objective of minimizing the operating cost. A chance-constrained programming approach is employed to convert the non-linear scheduling model into a mixed-integer second-order cone programming problem easy to solve. Finally, simulation analysis is conducted in the Python environment using the CPLEX solver. The results demonstrate that the proposed model and solution method are capable of effectively characterizing and addressing uncertainty risks in the system, facilitating the consumption of renewable energy, and improving the economic efficiency of system operation.

The multi-uncertainty of source and load poses significant challenges to the optimal scheduling of 'source-load-storage' integrated microgrid. However, a limitation of the traditional optimization model is its one-sidedness and use of a single time scale, which can result in suboptimal scheduling outcomes. Striking a balance between reliability and economy presents a considerable obstacle, as does coordinating the relationship between uncertainty analysis methods and varying time scales. Based on the data-driven multi-discrete scene distribution robust method, a two-stage distributed robust day-ahead optimal scheduling model of microgrid is proposed, which is solved by column and constraint generation algorithm. By combining the improved distributed robust optimization uncertainty method with a multi-time scale scheduling strategy and model predictive control theory, the accuracy of the scheduling can be enhanced. This is achieved through the gradual refinement of the scheduling time scale and reduction of the prediction period length. The day-ahead-day multi-time scale rolling optimization scheduling model is established to minimize the generation cost and adjustment cost, while also exhibiting a high degree of resilience to system uncertainties. Combined with the simulation analysis of the example, the proposed model has demonstrated advantages in incorporating new energy sources, reducing operating costs, and balancing considerations of safety and economy.

If a subsequent commutation failure occurs in the line commutated converter-based high voltage direct current (LCC-HVDC) transmission system, it will have a seriously negative impact on the safe and stable operation of the AC-DC hybrid power grid. Aiming at the problem of commutation failure during the current deviation control stage in the fault recovery process of the LCC-HVDC system, the relationship between current deviation control parameter and commutation failure is analyzed theoretically. It is found that to avoid commutation failure at this stage, the DC voltage and AC commutation voltage at the inverter side of the LCC need to meet certain constraints. These constraints are directly affected by the current deviation control parameter. Based on the theoretical analysis results, a current deviation control parameter tuning method is proposed, which can improve the control requirements for DC voltage recovery speed and degree during the fault recovery process of the system. The method makes it easier for the system to meet the stable operation constraints between DC voltage and AC commutation voltage, thereby reducing the probability of subsequent commutation failure. Finally, the CIGRE standard test model in the PSCAD/EMTDC simulation platform is used to verify the correctness of the theoretical analysis and the effectiveness of the parameter tuning method.

When applying the fault enumeration method to evaluate the reliability of the whole transmission and distribution network composed of transmission network and flexible interconnected distribution network, apart from analyzing the influence of internal faults of the transmission network and distribution network on their respective power supply reliability, the interaction between the transmission network and distribution network should also be considered under the fault scenario. Based on existing independent reliability evaluation algorithms for the transmission network and distribution network, the reliability evaluation method for the whole transmission and distribution network is proposed in this paper. The proposed method in this paper can account for the interrelation between the operation states of the transmission network and the distribution network under the fault condition. The node load reduction after the failure of the transmission network is refined into the optimized load cutting scheme of the distribution network. While improving the accuracy of the reliability evaluation results of the transmission network, the load loss of the distribution network caused by the failure of the transmission network is included in the reliability evaluation of the distribution network. In addition, the load loss caused by internal faults of the distribution network and its influence on the reliability of the transmission network are included in the reliability evaluation of the transmission network. For the whole transmission and distribution network, the reliability index of the transmission and distribution network is calculated by the analytical method based on fault enumeration. The validity of the reliability evaluation model is verified by the results of the numerical analysis.

In order to improve the flicker suppression performance of static var compensator (SVC) in response to impact loads such as DC electric arc furnace, a SVC rolling predictive control method based on the improved Takagi-Sugeno (TS) fuzzy algorithm is proposed. Firstly, the electrical model of DC electric arc furnace is established and its reactive power characteristics are simulated and analyzed. Then, an improved method of range adaptive correction is proposed to address the issue of abnormal output set to 0 when the classical TS fuzzy prediction algorithm is applied to fluctuating loads. This method can eliminate the outliers caused by the application mechanism of a class of algorithms, so as to improve the reliability and accuracy of TS fuzzy algorithm for reactive power prediction of fluctuating loads. Finally, based on the model training time constraint, a reactive power half-cycle rolling predictive control model is established to predict the reactive power 10 ms in advance. It is competent to improve the lag characteristics of the traditional SVC control system response. The simulation results show that the average flicker improvement rate of the proposed method increases by 54.17% compared with the traditional SVC control method, and the suppression effect of flicker phenomenon is significantly improved.

In order to solve the problems of system peaking and consumption caused by the integration of large-scale new energy sources into the grid, this paper analyzes the source-load-storage peaking capacity and its complementarities, so as to tap the system's peaking capacity and promote new energy consumption. Firstly, taking into account the peaking pricing and compensation for ancillary services for thermal power, energy storage and electric vehicles, the peaking cost sharing and compensation mechanism is analyzed and a deep peaking model is established. Secondly, considering the uncertainty and correlation of wind power, a typical wind power sequence based on kernel density estimation and Frank Copula function is generated and a step-type demand response model is established to realize the graded compensation of the response amount. Then, it is possible to improve the response enthusiasm of demand-side users. Finally, with the objective of minimizing the total operating cost, a joint source-load-storage peak-peaking optimization model considering uncertainty and pricing compensation is constructed, and the improved IEEE 30-node system is used as an example for analysis. The results show that the proposed model can increase the system's peak-shaving capability and renewable energy consumption level by utilizing the flexible peak-shaving potential of resources on the three sides of source, load, and storage.

Under the background of the new power system, it is important to make full use of the distributed generation in the distribution network to achieve carbon peaking and carbon neutrality goals. With the wide access of distributed power sources, there is bi-directional power flow between the transmission and distribution networks. If the transmission and distribution networks still follow the traditional equivalence method for optimal power calculation, accurate results will not be obtained. Therefore, a transmission-distribution-network-coordinated optimal power flow model is established. The node tearing method is used to decouple the coupling variables of the transmission network and distribution networks. On this basis, the iterative form of the model with immobile points is obtained by mathematical derivation. The traditional heterogeneous decomposition algorithm only uses the latest calculation results for iterative computation. Hence, combining with the Anderson acceleration idea in mathematics, the heterogeneous decomposition algorithm based on Anderson acceleration is proposed by using the historical iteration values to optimize the iterations of immobile points. It is demonstrated by numerical experiments that, the established model can fully utilize the initiative of the distribution networks and reduce carbon emissions. The proposed algorithm has high accuracy. In addition, compared with the heterogeneous decomposition algorithm, its convergence performance is significantly improved.

The rational utilization of the complementarity between new energy sources can smooth out the fluctuation of their power output, and the consideration of complementarity in new energy planning can make the new energy planning layout more rational. Based on this, the paper considers the complementarity of new energy outputs and investigates the optimal planning method of new energy system taking into account the source-load matching. The positive correlation between new energy output and load is utilized to maintain the dynamic balance between new energy output and load. Firstly, based on the idea of source-load matching, an equalization index describing the degree of closeness between the new energy output and the load, and a consistency index describing the degree of positive correlation between the new energy output and the baseline load output are proposed. Then, a multi-region new energy optimization planning model considering the source-load matching is established, and a constraint on the equilibrium degree of the new energy output and the load matching is introduced to ensure the consistency of the change characteristics of the two. Finally, a case study is conducted to analyze the power grids of four regions in the northern part of China. The results show that the new energy optimization planning considering the source-load matching can consider the new energy consumption rate and penetration rate comprehensively, and provide a solution for the new energy planning layout considering the complementarity of new energy output.

In order to explore the economic and carbon reduction benefits of photovoltaic-storage-charging integrated stations and achieve reasonable configuration of internal components, a multi-objective optimization configuration method for stations that takes into account economic and low-carbon aspects is proposed. Firstly, based on the functions and requirements of each module in the charging station, the sources of carbon emissions generated by station is explored, and a mathematical model for the cost and carbon emissions of each module in the station is established. Then, with the goal of minimizing the annual investment and operating cost of the system and carbon emissions, a multi-objective particle swarm optimization algorithm based on three-black-hole capturing strategy is used to optimize the configuration of various modules of stations in different load scenarios, and the optimal configuration plan for each component module of the station under three scenarios is obtained. The comparative results show that the method proposed in this article can effectively reduce the cost and carbon emissions during planning and operation, and improve the economic and environmental benefits of stations. Finally, the technique for order preference by similarity to ideal solution is used to provide a compromise optimization plan for the optimal scenario, which can provide reference for the current investment and construction of photovoltaic-storage-charging integrated stations.

Strong corrosive active sulfur in the mineral insulating oil has been considered to be the main culprit to induce the insulation failures of oil-immersed power equipment. In order to protect the oil-paper insulation from sulfur corrosion, active sulfur is cleared in the refining process of crude oil. Some inactive sulfur with high antioxidant is still retained in the mineral oil to improve the oxidation stability of oil. However, the activation of inactive sulfur under the operating condition of oil-immersed power equipment is not gained attention. This paper focuses on the reaction mechanism of winding corrosion induced by non-active thiophene sulfide in mineral insulating oil. The thermal pyrolysis products of thiophene sulfide are investigated by the material phase analysis method, and the activation energy changes of thiophene sulfide at different heating rates are analyzed in combination with the pyrolysis kinetics analysis method, and the experimental study of inactive thiophene sulfide under the action of oil paper insulation thermal field is carried out. The results of gas chromatography, mass spectrometry and Fourier transform infrared spectroscopy show that the main activation product of thiophene sulfide (thiophene, benzothiophene, dibenzothiophene) during pyrolysis is H2S, which is highly corrosive and volatile. The thermogravimetric and differential thermogravimetric curves of thiophene sulfides are basically the same at different pyrolysis rates, and thiophene is the most prone to pyrolysis, followed by benzothiophene and dibenzothiophene. Under the condition of low temperature superheating of oil paper insulation, due to the continuous accumulation of system energy, the inactive thiophene sulfide will be activated and then generate low molecular highly corrosive sulfide, which intensifies the corrosivity of oil products and leads to sulfur corrosion of oil paper insulation.

Aiming to address the problems of high cost, large size and complex structure of the traditional back-to-back three-level converter, this paper proposes a new dual-port three-level converter topology. This new topology reduces the number of switching devices and optimizes the system size through device multiplexing. Firstly, the operating principle of the proposed converter topology is analyzed in detail, outlining the six effective switching states, current flow paths, and corresponding dual-port output levels of the single leg, while also discussing and the voltage stresses of each switching device. Secondly, a level-shifting pulse width modulation for the proposed converter topology is investigated and designed, and the effect of modulating wave overlap is avoided by adding DC offsets. Thirdly, the key problems of the modulation scheme under both the common frequency and different frequency operation modes, such as the modulation regime range and phase angle difference constraints are analyzed. The principles for selecting DC offsets and constraint range of two-port modulation system in each operating mode are introduced. Finally, the different operating modes are verified using the DSP-FPGA-Typhoon HIL 402 experimental platform. The experimental results show that level-shifting pulse width modulation with DC offsets makes the output power quality of the converter better and the harmonic content lower on the premise of achieving stable output of voltage and current for the proposed converter topology.

When the earth faults occur in different phases of two feeders connected to the same bus in the resonant grounding system, the conventional fault line selection devices are inaccurate. To address the difficulties of fault line selection in the earth faults that occurred in different phases of two feeders connected to the same busbar for resonant grounding system, the line zero-sequence admittance is calculated by the zero-sequence current at the first end of the line and the zero-sequence voltage of the bus. The analysis of the fault characteristics indicates that, the zero-sequence admittance amplitude in faulty lines is larger than that in the non-faulty line, and this characteristic also appears in the high-impedance grounding faults. Based on the ratio of zero-sequence admittance amplitude, a fault line selection method for earth faults occurring in different phases of two feeders connected to the same bus in a resonant grounding system is proposed. The difference in zero-sequence admittance amplitude between fault and non-fault lines is used to establish a line selection criterion, which allows all fault lines to be selected. The results simulated by PSCAD confirmed that the proposed method works effectively, with high accurary. This method is not affected by the fault location and the compensation degree of the arc suppression coil, and it can also withstand high fault resistances.

The zero-value piece of insulator string can be detected by measuring its electric field strength. The traditional way is always by measuring the electric field distribution curve of the whole string to judge out the zero-value piece position, which is inefficient and difficult to operate in field. In this paper, an improved method of identifying zero-value insulator by just measuring the partial electric field of insulator unit is proposed. Firstly, the simulation model of insulator string zero-value unit detection is established, and the partial electric field distortion characteristic caused by zero-value piece is analysed. Then the partial electric field variation criterion for zero-value identifying is obtained basing on the simulation result. Finally, the identification method is verified by designing the detection device and carrying out the point to point zero-value piece evaluating experiments. The results show that the point to point zero-value insulator detection can be realized using the three-array-probe electric field measuring method. The length of the array should be larger than the length of the electric field distortion interval, which can be taken as 130 mm for the research object in this paper. The identification criteria is that the deviation between probe 1 and 3 is less than 10%, and the deviation between probe 2 and the average is less than 50% at the same time. When detecting zero-value piece at the high-voltage and medium-voltage end, the best position for the sensor device identification is directly facing the steel foot, while for the low-voltage end, the best position is facing the shed edge. The results of the study can provide theoretical support for the intelligent operation and maintenance of external insulation in power transmission and distribution.