In order to analyze the influence of harmonics on the stability of line commutated converter based high voltage direct current(LCC-HVDC)system.It is urgent to establish an accurate model of LCC-HVDC considering harmonic coupling.Based on the theory of harmonic state space(HSS),an impedance model of 12-pulse LCC is established considering frequency coupling effect and control system.The constructed AC/DC harmonic impedance model can match the sweep frequency results in a wider frequency band.Finally,the correctness of the proposed LCC-HSS impedance model is verified by comparing the PSCAD electromagnetic transient simulation results with the HSS impedance model calculation results.The LCC-HSS impedance modeling method improves the accuracy of mathematical modeling for LCC converter stations and can adapt to impedance modeling of LCC converter stations in various modes,providing a more accurate model for stability analysis and parameter optimization of LCC systems.
In response to the demand for green and low-carbon development, China is vigorously promoting the construction of large-scale renewable energy bases. The system of transmitting renewable energy through VSC-HVDC is receiving more and more attention. In such a system, renewable energy devices usually adopt grid-following control, while VSC-HVDC adopts grid-forming control. However, the synchronous stability mechanism of this high-proportion or even 100% power electronic system is still unclear. This paper establishes a synchronization model for grid-following and grid-forming devices, focusing on the role of phase-locked loops and virtual synchronous generator loops in synchronization. Then, the small-signal stability of the system is analyzed, and the operating area that ensures stable operation is derived. The operating states with instability risks are proposed for both renewable energy devices and VSC-HVDC. Finally, the conclusions are verified by PSCAD simulation.
Kunliulong hybrid multi-terminal UHVDC project is the first hybrid multi-terminal UHVDC project in the world, which is more flexible than the traditional two-terminal DC operation mode. Meanwhile it also increases the complexity of control and protection strategy. Since it was put into operation, there have been several abnormal operations, and the reliability of its "first set" control and protection system and equipment needs to be further improved. This paper analyzes the "6.9" valve-controlled abnormal events of Kunliulong UHVDC in detail. After that,the paper sorts out the configuration of control and protection functions and UHVDC response, and creatively proposes to increase the detection and application of valve-controlled abnormal events. This strategy can accurately and quickly detect the valve-controlled pulse loss or pulse delay fault, improve the risk identification and resistance ability of UHVDC control and protection system in this condition. The result shows that the improvement effectively increase the reliability and stability of this hybrid multi-terminal UHVDC project. It also provide reference and guidance for the subsequent functional design of this kind project.
In the context of the large-scale connection of distributed photovoltaic(PV)to the power system,in order to make use of the complementary characteristics of the distributed pumped storage power plant with other energy source output and maximize the output of combined PV-pumped storage system to meet the scheduling requirements while reducing the abandoned PV power,the output models for distributed photovoltaic and distributed pumped storage units that are more in line with the actual operation condi-tions are established.On this basis,a joint scheduling model of PV and pumped storage is developed and a deterministic transforma-tion approach is used to solve the scheduling model with random variable prediction errors in the objective function.The Euclidean distance is introduced as a measure of the matching degree of the scheduling curve.Finally,example simulation results show that the proposed strategy can make the distributed PV output better meet the scheduling demand with the cooperation of pumped storage,which promotes the system's consumption of distributed PV power.
Aiming to study the distribution characteristics of local wind fields in coastal region with transmission lines during the landfall of Typhoon Nida,the mesoscale meteorological model WRF and the microscale CFD model WindSim are used to design three simulation schemes,including mesoscale simulation based on WRF,microscale simulation based on WindSim,and mesoscale and microscale coupled simulation based on WRF and WindSim.Numerical simulation experiments are carried out and compared with measured data from LiDAR,so as to valify the applicability and accuracy of the different models.The results show that the WRF-based mesoscale simulation can better reproduce the temporal variation of meteorological fields during the landfall of Typhoon Nida period,and the WindSim-based microscale simulation can better reflect the topographic effects of the wind field at a spatial resolution of 10～100m in a specific wind direction.The mesoscale and microscale coupled simulation based on WRF and WindSim can not only correct the topographic effect bias of WRF alone,but also improve the boundary conditions and atmospheric stability of WindSim alone,and have the ability to simulate the three dimensional wind field with complex terrain during typhoon impact with higher accuracy of simulation results.
With the widespread application of sensing elements and communication devices in power systems,modern power systems have become a cyber-physical integration system which is highly dependent on the communication networks.The improvement of informationization degree not only enhances the real-time perception and dynamic control capability of the system,but also increases the risk of cyber attacks on power systems.The frequent cyber attacks in recent years have sounded the alarm for the international community.At present,the research on cyber attacks in China and abroad is mainly focused on the modeling,defense and evalua-tion.The research on the entire process influence of cyber attack is still in its infancy.This paper analyzes the impact of cyber attack on typical power system scenarios of generation,transmission,distribution and user side.Firstly,the physical characteristics and structure of each scenario are modeled,and the vulnerability of the scenario subject to cyber attacks is evaluated after that.Then the response of the system under the cyber attack and the destructive effect of the cyber attack are analyzed.Finally,the existing research is summarized and prospected.
In multi-terminal DC distribution system,due to the diversity of operating points and the complexity of impedance environ-ment,it is often difficult to provide sufficient improvement effect of stability by the active damping control with single point configuration in the converter station.In order to meet the multi-source configuration requirements of active damping in complex system,this paper takes the phase-shifted full-bridge DC converter as the research object from the perspective of load.On the basis of establishing the average equivalent circuit,the reduced-order impedance model and the transformation relation between input side and output side parallel impedances in low-frequency range,the origin of active damping control strategy using input voltage feedforward is traced,and the active damping control strategy of output voltage feedback is proposed.Finally,the dual-terminal DC distribution system is taken as the application abject,the accuracy of the reduced-order impedance model for the phase-shifted full-bridge DC converter and the effectiveness of the active damping strategy are verified by the time-domain simulation results,the small-signal eigenvalue trajectories and hardware-in-the-loop experiments.
The global environment is facing enormous challenges,coupled with the significant consumption of fossil fuels leading to an energy crisis.Electric vehicles(EVs)are highly popular in the market due to their green,efficient and low consumption characteristics.Firstly,starting from two aspects:never considering the output of new energy and considering the output of new energy,this paper combs and analyzes the research status of orderly charging of EVs.Secondly,the optimization strategies for orderly charging of EVs are summarized from four areas:optimization hierarchy,optimization algorithms,vehicle to grid(V2G)technology and charging station location selection.Then two domestic and foreign V2G demonstration projects are listed.Finally,a summary of the research on orderly charging of EVs is provided,and future applications are prospected.
With the acceleration of smart grid construction,the requirements for extracting and analyzing the parameter information of power system to ensure the safe and stable operation of power system are getting higher.At present,a large number of overhead distribution line current in distribution system is difficult to achieve effective non-contact detection.To solve this problem,a non-contact three-phase overhead distribution line current detection method based on magnetic field inversion is proposed.Firstly,the inversion optimization model of line current is established according to the inverse magnetic field problem.Secondly,the non-dominated sorting genetic algorithm(NSGA-Ⅲ)with reference point mechanism is used to solve the model.The optimal solution that meets the requirements of decision makers is selected by combining the technique for order preference by similarity to ideal solu-tion(TOPSIS)method,and the fitting curve is drawn and the characteristic parameters are extracted.Finally,the simulation analysis and experiment are used to verify the effectiveness and accuracy of the proposed inversion method.
Aiming at the disproportionate characteristics of wildfire disasters near the transmission lines in time and space distribution,a method to assess the spatial-temporal distribution of wildfire risk in transmission line corridors is proposed based on dynamic Bayes-ian Network.Firstly,the data of 17 wildfire-related factors in three categories including anthropogenic,meteorologic,vegetation and geographical factors are collected.The important factors are screened by the random forest algorithm to reduce the input data dimen-sion and model complexity.Then,a Bayesian network model is applied to eliminate the complex coupling relationship between fac-tors,and on this basis,the monthly time scale dynamic Bayesian network wildfire risk assessment model is established.Compared with the Bayesian network model,the factors of the last time is incorporated to the dynamic Bayesian network to improve assessment accuracy.Next,the time scale is further refined,and it is found that with the decrease of time scale,the evaluation effect of the model is gradually improved.The accuracy of the dynamic Bayesian model reaches 86.39%on the 3-day timescale.Finally,the dynamic Bayesian network model is used to draw the distribution map of wildfire risk in Guangdong Province during the Qingming Festival in 2022,which provides the basis for the prevention of wildfires in the power grid.
In order to cope with the increasingly severe power inspection task of transmission lines under the new situation of"Carbon Peak and Carbon Neutral",as well as the lack of consideration for the existing research on multi-objective joint power inspection and the lack of practical scenarios in which unmanned aeriel vehicles(UAVs)can hover and wait.This paper proposes a cooperative inspection path planning method for vehicle-mounted UAVs based on the"graph theory"theory,considering the joint power inspec-tion of power towers and power lines with multiple targets.Firstly,considering the characteristics related to UAV arc routing and inspection vehicle node routing in power inspection,combined with the improved Chinese mailman problem,the discrete tower split-ting arc algorithm is designed to quickly obtain a better preliminary planning scheme for cooperative inspection paths,and the impact on the results under different strategies and natural disaster conditions in different scenarios are compared and analyzed.Secondly,considering that the initial planning scheme is not a global optimal solution,this paper designs a simulated annealing algorithm that is consistent with this study to further optimize the preliminary planning scheme.Finally,the effectiveness and practicality of the path planning method are verified by arithmetic examples.
The comprehensive tripping strategy and quasi three-phase tripping strategy are adopted for the double-circuit transmission lines on the same tower,which may trip all the phases of the double-circuit transmission line during line faults,and result in large-area generator tripping and load shedding of weakly stable systems including wind power and photovoltaic,which worsens the transmis-sion environment of the power grid and seriously reduces the operation stability of the power system.In response to this issue,a quasi two-phase tripping strategy suitable for cross-line grounding faults in double-circuit transmission lines on the same tower is proposed,which can reduce the tripping probability of all phases of double-circuit transmission lines and provide a stable coupling source for the fault phase.Firstly,the topology analysis method is used to establish models for the comprehensive tripping strategy and quasi three-phase tripping strategy of transmission lines,and the impact mechanism of the tripping strategy on fault property determination is analyzed.Secondly,considering the consistency of transmission continuity and fault nature judgment,a quasi two-phase tripping strategy suitable for cross-line faults on double-circuit transmission lines on the same tower is proposed.Finally,the correctness and feasibility of the quasi two-phase trip strategy are verified through PSCAD/EMTDC simulation experiments.
When the ultra-short term power error reported by wind farms to the dispatching center is relatively serious,a huge obstacle is brought to large-scale grid connection of wind power and the competitiveness of wind power is seriously affected.A wind storage combined output model is proposed that uses the energy storage system to track the wind power prediction curve.Firstly,the ultra-short term prediction of wind power is carried out through long and short term neural network.Furthermore,the economic impact of the construction cost of the whole life cycle of the energy storage system and the penalty cost of the error of the forecast curve reported by the wind farm after the introduction of the energy storage system is considered through the combined output of wind and energy storage.Finally,the wind storage joint dispatching plan is determined.Based on the measured data of a wind farm in Jilin Province,this paper compares the economic cost and wind power utilization of wind storage farms under different tracking modes.The simulation results show that the power generation cost of the wind storage joint generation model proposed in this paper is 0.2316 yuan/kWh,which is 22.67%lower than that of the non-storage mode.At the same time,the wind power utilization rate is increased by 17.48%.The root mean square error is reduced by 0.07 and the mean absolute error is reduced by 0.08.The results show that the strategy proposed can effectively reduce the wind power grid-connected power error and improve the wind power utilization rate while ensuring the economy of the wind storage power station.
The hybrid microgrid is composed of AC subgrid,DC subgrid and energy storage subgrid.The integrated three-port topol-ogy structure is applied to the hybrid microgrid as a bridge connecting the AC/DC subgrid and energy storage subgrid.A hybrid microgrid power cooperative control strategy based on integrated three-port is proposed in this paper.In view of the complicated operation control problem caused by the power coupling of the hybrid microgrid,a power cooperative control strategy is designed in combination with the microgrid structure to ensure the reliable operation of the microgrid.The strategy includes three underlying control strategies:source and load balance control within the subgrids,power mutual aid control between grids,and power sharing control of energy storage units considering the state of charge of the energy storage.In addition,a segmented control strategy based on normalized AC frequency and DC voltage is designed to realize the combination and switching of the above three strategies to adapt to the change of different microgrid operation scenarios.The power cooperative control strategy does not require a communica-tion link and improves the overall operation reliability of the hybrid microgrid.Finally,the proposed control strategy is simulated and verified by MATLAB/Simulink,which proves the effectiveness of the scenario adaptive power cooperative control strategy.
After the VSC-HVDC transmission system based on modular multilevel converter(MMC)is connected to the power grid,high-frequency resonance may occur,which further leads to the implementation of blocking logic protection for VSC-HVDC converter station,which will have a serious impact on the AC main grid.Therefore,the study of VSC-HVDC high-frequency resonance and its suppression scheme has a significant role in improving engineering safety and reliability.Firstly,the harmonic impedance of Guangdong Power Grid's planning AC power grid in 2025 is scaned by HISCAN software,and the generalized Nyquist criterion is used to conduct a comprehensive investigation of the high-frequency oscillation risk points in the Guangdong power grid system.Then,the established electromagnetic transient model is used for time-domain simulation to evaluate and validate the high-frequency oscillation of the VSC-HVDC transmission system.Finally,relevant suppression strategies are proposed to address the potential high-frequency resonance points in the system to address the oscillation risk.
A demand response resource aggregation optimization model and method under invitation mode is proposed from the perspective of load integrators.Firstly,based on the actual situation of demand response transactions in some provinces and regions in China,the mode of day-ahead invitation response and the aggregation agent mechanism of load integrators for users are analyzed.Then,based on the mechanism conditions for organizing,assessing,and compensating for the demand response of the day-ahead invitation,and taking into account the characteristics of user resource response,effective response capacity authentication,and the impact of the revenue and assessment cost allocation ratio between load integrators and users,an aggregation optimization model is constructed to better adapt to the needs of load integrators for making day-ahead invitation response decisions.Aiming at the nonlinear coupling relationship of decision variables in the model,intermediate variables and logical constraints are introduced for linearization processing,which is then transformed into a mixed integer programming problem to reduce the difficulty of solving.The analysis of numerical examples shows that the aggregation optimization of different types of response resources can help to improve the expected returns of load integrators in the day-ahead invitation response,and can provide more detailed information for the analysis of the limit capacity of load integrators to compatible with different quality resources,which verifies the effectiveness of the model and method.
The power flow calculation model based on deep learning can directly fit the mapping relationship between the initial value of the system power flow and the result of the power flow,and the calculation speed is extremely fast and the ill-posed power flow problem is not generated.However,the existing deep learning power flow calculation methods are mostly based on regression models,which can't identify whether the power flow converges,resulting in false system power flow distribution still mapped to the input non-convergent power flow samples.To solve this problem,a power flow analysis method based on graph multi-task learning network is proposed,power flow analysis is performed on the input case combined with the physical characteristics of the power system.Finally,the proposed model is comprehensively simulated on the IEEE 14-node system,and 10 000 system samples contain-ing different network topologies are generated.The simulation experiment verifies that the computational time of the proposed model is about a quarter of that of the Newton-Raphson method,and the accuracy of power flow convergence judgment reaches 98.81%,the calculation accuracy of power flow distribution calculation reaches 98.58%,and the effectiveness of the improvement in graph convolution and graph pooling is verified by comparative experimental ablation experiments.
Real-time and accurate voltage measurement data is the basis for constructing a transparent power grid.The non-contact measurement technology has the advantages of safety,convenience and low cost,and has become a realistic basis for widespread deployment.A flexible voltage probe based on the principle of capacitive coupling is designed in this paper,and the sampling circuit's impact on the probe voltage division is analyzed,and a method using 2 probes to figure out the wire voltage to be measured utilizing the different output is proposed.The simulation and experimental results show that the proposed method can measure the wire voltage without damaging the insulation sheath.In laboratory environment,the amplitude measurement error of steady power frequency voltage is less than 2%,and the phase measurement error is less than 0.2 °.
Charge modules are the most critical component of automotive DC charging piles. Considering that the open circuits of core devices such as power switches and electrolytic capacitors. A fault diagnosis method based on wavelet packet transform and SSA-BP neural networks was proposed. The method took the output voltage of the charging module as the original signal， firstly rejected its DC component through pre-processing， decomposed the processed signal into wavelet packets， then calculated the energy of each sub-band signal， obtained the initial feature vector through normalisation， and finally input the DC component and the normalised feature vector as the final fault feature quantity into the SSA-BP neural network， and then output the classification results to achieve fault diagnosis.In order to verify the feasibility and superiority of this method，a two-stage simulation model with an output of 15kW was built under different operating conditions. Experiments showed that this method could effectively improve fault diagnosis accuracy with diagnosis rate of 93.85%. And it has practical guiding significance for fault diagnosis of automobile DC charging pile.
The construction of virtual power plant （VPP） provides an effective way to exploit the flexibility of power grids in mega-cities， but the existing researches and practices are still unable to support the organic coordination between VPPs and regional unified power markets under the dual carbon goal. This paper comprehensively summarizes the current status of the VPP constructions and market mechanisms， and deeply analyzes the technical challenges of VPPs in mega-cities participating in the regional power market. Based on the construction needs of regional power market and future power system， the research directions of key supporting technologies such as secure grid connection， operation control， low-carbon dispatching， support systems， etc.， for VPPs are further proposed. In addition， the future development prospects are prospected. It is expected this work can provide references to promote the secure， orderly and sustainable development for regional markets， power grids and VPPs， and promote the construction of new power systems in mega-city power grids.
