Abstract:In response to the exist problems such as the lack of accuracy in load forecasting leading to large errors in contracted power purchases,and the ambiguous market boundaries leading to duplication in assessment and settlement when load aggregators organize demand-side resources to participate in the peaking market and the electricity energy market,a load aggregator potential calculation and peaking strategy based on the longitudinal modified autoregressive integrated moving average (ARIMA) model is proposed. Firstly,the longitudinal modified ARIMA forecasting algorithm is applied to forecast the load baseline for obtaining the model of peak regulation potential of load aggregators,thus exploring the adjustable capacity of demand-sideresources to provide a database for power market trading. Secondly,the load deviation assessment method of electric energy market and peak shaving market is formulated,and the load aggregator peak shaving model considering the deviation assessment is constructed with the goal of maximizing the monthly rolling time domain comprehensive settlement income. Finally,the proposed method is analyzed based on the monthly historical load data of load aggregators in a typical region. The results show that the proposed load aggregator peak shaving strategy considering load deviation assessment can improve the peak shaving revenue of aggregators by about 23.7% and reduce the load aggregator peak-to-valley difference of about 10%,which verifies the rationality and effectiveness of the method.

Abstract:As more and more controllable loads are connected to the power grid,air conditioning loads (ACLs) can be used as flexible loads to participate in load shaving and accommodate the fluctuation caused by renewable energies because of its characteristics of fast response,large potential adjustment power,cold storage and heat storage. In the actual aggregated process of ACLs,the changes of external conditions such as outdoor temperature,temperature of ACLs and number of ACLs will have a certain effect on the aggregated model. However,the time-varying characteristic of the aggregate ACLs' external model (AAEM) is not be considered in the most of existing control methods. A data-driven-based AAEM and its corresponding load tracking control strategy are proposed. Based on the cost function of individual ACLs considering thermodynamic characteristics,the data-driven-based AAEM is established by using neural network. By this way,computational complexity of calculation AAEM is reduced. The load tracking control strategy considering the data-driven-based AAEM can effectively reduce the number of times of switching and the total cost. The simulation results verify the effectiveness of this method.

Abstract:Given the practical issues of the traditional power system's insufficient operational flexibility in the face of changing residential power load and source-side output,demand response can effectively improve the flexibility,safety and economic benefits of system operation. The value of demand response is especially noticeable meanwhile the refined assessment of demand response potential is an important basic support. A method is proposed about evaluating aggregate demand response potential in the absence of historical demand response data based on Gaussian mixture model. Firstly,the typical data are selected through two-stage clustering of households and similar days to improve data representativeness. Then the Gaussian mixture model is introduced to accurately explore the probability distribution of household electricity consumption behavior and calculate individual households' demand response potential. Finally,the bottom-up weighted aggregation is implemented to evaluate the aggregate demand response potential under multiple confidence scenarios. According to empirical analysis,this method can mine hourly information of residential demand response potential from historical electricity consumption data,which can reflect the distribution of power load and demand response potential. Comparative analysis is used to validate the validity of typical data selection by two-stage clustering.

Abstract:Reasonable signal allocation strategy and effective signal tracking control method are the keys to using aggregate electric vehicles (AEVs) combined with thermal power units to perform the control,improve the quality,and enhance the economy in frequency regulation. Therefore,a frequency regulation control strategy with the participation of AEVs is proposed based on variational mode decomposition (VMD) and double-layer model predictive control (MPC). Firstly,the coordinated optimization control structure of AEVs combined with traditional thermal power units is designed for frequency regulation. The models for thermal power units and load frequency control are established. The AEVs are converted into virtual frequency regulation units,and the load frequency control model of single-area multi-unit with the participation of AEV is constructed. Then,the frequency regulation signal is decomposed into intrinsic mode functions with different frequency components using VMD. The high-frequency components and the low-frequency components are integrated as the frequency regulation signals of AEVs and thermal power units respectively. Optimal redistribution and tracking control of frequency regulation signals within AEVs and thermal power units are realized by double-layer MPC,respectively. Finally,the proposed control strategy is verified by the simulations,and the results show that it can adjust the system frequency effectively and keep a balance between the economy and dynamic performance in frequency regulation.

Abstract:In response to the problem that the factors affecting room temperature and its influence on load modeling and the problems of user comfort and energy consumption expenditure when rigidly bundling residential integrated energy system (RIES) and users are not fully considered in the energy management of RIES,the RIES energy management optimization model and its solution method are proposed in the paper for the participation of cooling and heating loads in tiered subsidy and electric loads in the tariff-type integrated demand response. Firstly,the discrete building heat balance equation is obtained by comprehensively considering the factors affecting the room temperature,and the mathematical model of the flexible but not fixed cold,heat and electricity loads of the building is established. Secondly,a tiered subsidy for cold and heat load participation and a tariff-type integrated demand response mechanism for electric load participation should be established. Then,taking into account of RIES's cost of purchase energy from the outside,cost of affording integrated demand response (IDR),and profit of selling energy to the users,an optimization model for optimizing energy management is established that maximizes RIES's net profit with consideration a series of operation constraints of the components and the system. The Cplex is used to solve the linearized model. Finally,a simulation example shows that the residential integrated energy system optimization strategy that takes into account the comprehensive demand response can coordinate the resources on both sides of supply and demand,thus improving the economic benefits of the system and users.

Abstract:Using thermostatically controlled load (TCL) as a frequency regulation resource is an effective means of maintaining power grid frequency stability caused by the high proportion integration of renewable energy power generation into the power grid. A primary frequency control strategy is proposed for the participation of TCL in regulation based on dynamic droop control. The dynamic droop control model is constructed to control the participation of TCL aggregators in frequency regulation by adjusting the droop control coefficient in real time, while considering the average state of temperature of TCL,the capacity for frequency regulation and the rate of change of system frequency. In this condition,the off state of TCL is locked for regulation up,vice versa the on state is locked for regulation downward. Therefore,the frequency can quickly return near its rated value. At the same time,to ensure the user's comfort,the priority ranking list dispatch method on the state of temperature is used to determine the order of TCL for frequency regulation. Finally,simulations on the Matlab/Simulink platform show the effectiveness of the proposed strategy in improving frequency quality and the user's comfort.

Abstract:Modular multilevel converter (MMC),which is composed of a large number of submodules (SM) connected in series, is one of the most promising converters in high voltage field. The open-circuit fault and short-circuit fault of the SM's power switch seriously affect the reliability of the MMC,and it brings great challenges to the stable operation of the MMC. Therefore,in order to quickly detect the faulty SM,a fault detection method of the SM's power switch in the MMC based on Luenberger observer is proposed. Firstly,the fault characteristic of the SM is analyzed,and the model of Luenberger observer is established according to the mathematical relation of the SM capacitor voltage change. Then,the estimated capacitor voltage is calculated by Luenberger observer,and the detection of the power switch fault is realized by comparing the estimated capacitor voltage and the measured capacitor voltage. Finally,the simulation model of the MMC system based on the PSCAD/EMTDC and the experiment platform in the laboratory are respectively built. The simulation and experiment results show that the open-circuit and short-circuit fault of the SM can be detected correctly and effectively,which verifies the validity and feasibility of the proposed method,but each SM needs to be monitored.

Abstract:Accurate calculation of harmonic impedance is the premise of harmonic control and reasonable division of harmonic responsibility. The existing harmonic impedance estimation methods should meet the conditions that the background harmonic fluctuations are small and the customer harmonic impedance is much larger than the utility harmonic impedance. However,the use of a large number of power electronics in power system makes those conditions are not be satisfied. Therefore,a utility harmonic impedance estimation method based on mutual information and data optimization is proposed. Firstly,the utility harmonic currents are solved by independent component analysis (ICA),and the data segments with small mutual information between the harmonic currents at the point of common coupling (PCC) and the utility harmonic currents are selected. Finally,the harmonic impedance of the screened data segment is estimated using the characteristic of zero covariance between the harmonic current at the PCC and the harmonic voltage on the utility. The effectiveness of the proposed method is tested by simulation and actual case analysis. Compared with existing methods,the proposed method is more accurate and widely applicable when the customer harmonic impedance is not much larger than the utility harmonic impedance.

Abstract:The problem that the early capacity planning of microgrid in data center is unreasonable and cannot adapt to the operation characteristics of data center has not been solved. At the same time,in order to improve the power supply economy and renewable energy consumption capacity of the microgrid in data center,a bi-level optimal configuration model of the microgrid capacity in data center taking into account the load characteristics is proposed in this paper. Scenario reduction-based selection method is used to deal with the uncertainty of renewable energy and the computational complexity caused by a large number of scenarios. The corresponding load scheduling strategies are proposed according to the characteristics of different loads together with their flexibility. The problem of capacity planning for different microgrid resources,including energy storage system,photovoltaic and wind turbine,is solved by using non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ) and Gurobi. Finally,the conpromise optimal soulation is obtained by the fuzzy multi-attribute decision-making approach. The simulation results show that the proposed approach can reduce the construction costs,operation costs and carbon emissions of data center microgrids. Besides,the satisfaction of data center operators is improved.

Abstract:The accurate estimation of inertia is the premise of analyzing the security and stability of the system frequency,but the existing methods can not quantitatively evaluate the effect of virtual inertia on the equivalent inertia of the power system. In view of this,an inertia estimation method of power system with virtual inertia response of wind power is proposed. Firstly,the theoretical expression of equivalent inertia of power system including virtual inertia response of wind power is derived. Secondly,the phasor measurement unit (PMU) is used to obtain the active power and frequency data at the node of the power generation device. Thirdly,the active power output of the power generation device is taken as the input of the identification model,and the frequency disturbance is taken as the output. Using controlled autoregressive (CAR) model and time-varying forgetting factor recursive least squares (TFF-RLS) algorithm evaluated the equivalent inertia of the whole network under different wind power proportions. Finally,the feasibility and applicability of the proposed method are verified by an improved IEEE-10-machine 39-node system. Compared with the traditional identification method,the accuracy of the inertia estimation of the proposed method is improved,and it is suitable for the time-varying inertia estimation of the new energy power system.

Abstract:The flexible DC line protection based on the double-ended method with large communication and long action time is greatly affected by factors such as noise,which makes it difficult to set. Based on this,a pilot protection method of flexible DC line based on Jaccard similarity integration criterion is proposed. Firstly,the fault characteristics of voltage and current change rate in the case of internal and external faults of flexible DC lines are analyzed,and the conversion relationship between analog quantities and logical quantities is constructed respectively. Then a Jaccard similarity model based on the comparison of logical quantities under the 0.5 ms data window is proposed. The integrated criterion is constructed with high similarity to realize fault type identification, and fault starting and fault pole selection criteria are not required. Finally,the double-ended longitudinal protection scheme based on the comparison of logical quantities realizes the rapid protection of the flexible DC line. The scheme is easy to be implemented,because the protection principle of that is simple with fast action speed. Using the four-terminal flexible straight model built by PSCAD/EMTDC, the protection effectiveness in various scenarios such as different fault types, high-resistance grounding,and noise interference inside and outside the zone were verified.

Abstract:Compared with full-bridge modular multilevel converter (MMC),the hybrid MMC composed of half bridge sub-module and full bridge sub-module has the low cost and high DC fault ride-through capability. The DC fault transient analysis is the basis of device selection and proportioning design of hybrid MMC. In order to analyze the transient characteristics of hybrid MMC after DC side fault, the equivalent fault models of DC pole-pole short circuit during the non-blocking DC fault ride-through in rated operation and step-down operation are established. The dynamic switching process of each bridge arm sub-module of hybrid MMC during DC fault ride-through is analyzed. The transient process before the switching of the non-blocking DC fault ride-through control strategy is equivalent to the uncontrollable sub-module capacitor discharge process,while the transient process after switching the control strategy is equivalent to the current limiting process with the initial energy storage of the inductor and the reverse voltage source. The analytical calculation method of the short-circuit current on the DC side of hybrid MMC is also given in this paper. Finally,the effectiveness of the model and calculation method proposed in this paper is verified by the PSCAD/EMTDC simulation platform,which can provide a reference for the optimal design of hybrid MMC.

Abstract:In recent years,offshore wind power has developed rapidly. It is the most effective way to transmit the wind power far away from the coast through the voltage source converter based high voltage direct current (VSC-HVDC) transmission system. The offshore wind power is usually transmitted by cable,which makes the fault characteristics of VSC-HVDC transmission system more complex than that of overhead transmission system. Based on a symmetrical monopole topology of two-terminal VSC-HVDC offshore wind power transmission project,the mathematical model of the transmission system which contains cables and VSC-HVDC system is simplified. The fault characteristics under typical faults such as single-phase grounding of AC system at converter valve side and single pole grounding of DC cable line are analyzed. Based on the superposition principle,the fault mechanism is analyzed in detail. According to the fault sources of different fault types,different fault circuits are equivalent. The complex influence of the significant capacitance effect of long-distance cables on the fault characteristics of VSC-HVDC systems is obtained. A real time digital simulation model of offshore wind power transmission system through VSC-HVDC is built. The fault mechanism is verified through simulation analysis.

Abstract:Deploying edge computing nodes on the demand side can effectively reduce the pressure of data transmission and storage of the power network and improve the quality of electric power service. At present,the deployment location of edge nodes is mostly determined from the dimension of grid topology,and the service scope of nodes is defined by the grid method. The working process among nodes is independent. Therefore,the flexibility of the location and capacitydetermination of edge nodes is low, and it may cause waste of equipment computing resources.Therefore,an edge computing node deployment method considering task migration is proposed in this paper. Firstly,an edge computing architecture considering task migration is proposed based on the characteristics of edge devices and the spatial characteristics of residential areas. Secondly,feature data is formed according to spatial information and load characteristics of residential nodes. Then the number,address and service scope of nodes are determined by using the improved density peak analysis algorithm. Finally,a heuristic algorithm is designed to realize the task migration among the edge nodes to ensure the balanced utilization of computing resources of nodes and improve the stability of the system. A residential area in Nanjing is taken as an example to design simulation experiments. The results show that the proposed edge nodes deployment method can effectively reduce the data transmission costs of residential nodes. Also,the task migration algorithm can effectively balance the computing resources among edge devices and improve execution efficiency of edge computing services.

Abstract:Aiming at the problem of insufficient sensitivity of existing fault location methods when single-phase grounding fault occurs in resonant grounding system of active distribution network,a fault location algorithm based on Manhattan average distance and cosine similarity is proposed. Firstly,the neutral point grounding method of distributed generator (DG) is defined and the influence of DG access is analyzed. Secondly,the transient zero-sequence current at both ends of each section of the fault feeder is decomposed by wavelet packet. Then the amplitude similarity is calculated by Manhattan average distance,and the waveform difference is compared based on cosine similarity. As a result,a comprehensive similarity criterion is constructed,and the fault section can be distinguished by comparing with the set threshold. Finally,the simulation model is built in DIgSILENT PowerFactory. Simulation result shows that the proposed method can locate faults accurately under different fault locations,different fault moments and different transition resistances.

Abstract:Intelligent distributed protection and control is a promising route towards flexible and safe operation of the medium-voltage distribution network with widespread access to distributed energy resources. A fundamental premise of distributed decision-making is that each smart terminal unit (STU) can identify the topology of the feeder and track its changes. A distributed topology identification algorithm with high fault tolerance based on peer-to-peer communication is proposed in this paper. The STU configured at the looped network node requires no pre-set static topology of the feeder group,but only relies on local measurement and information exchange with neighboring STUs. Through rule judgment,it can realize the dynamic tracking and monitoring of the complete topology and open-loop mode of the feeder group,which reduces the configuration requirements of the algorithm on the terminal. Meanwhile,the method only needs each STU to exchange the local measurement and judgment information,which reduces the requirement of communication. Test examples show that the proposed method is reasonable and effective,and it can significantly improve the tolerance of topological identification to measurement errors by combining local measurement mutual checking and contralateral connectivity predictive correction.

Abstract:Since cables laying in the tunnel have high load capacity and convenient maintenance,they have been widely used in the urban power grid. In order to make full use of transmission capacity,a phase sequence optimization method of tunnel multi-circuit cables based on an improved genetic algorithm and multi-physical field simulation is proposed. Firstly,considering the electromagnetic environment,heat dissipation environment and the cross-bonding grounding mode,an electromagnetic-heat-flow-circuit multi-physical field coupling model of tunnel cables is established. Secondly,the memory population is set up in the genetic algorithm to lessen the invocations of the finite element model and improve the calculation efficiency. Finally,an improved genetic algorithm is applied to the phase sequence optimization of cables in which minimizing the maximum temperature of cable cores is considered as the objective function and the cable temperature of each loop not exceeding 90 ℃ as its constraint condition. After optimization,the total sheath circulating loss of the cables decreases by 11.14%,and the maximum temperature of the cores decreases by 2.15%. The results show that the optimization of phase sequence is conducive to improving the heat dissipation of the tunnel cables,and the improved genetic algorithm greatly decreases the optimization times.

Abstract:A way to improve high-temperature mechanical behavior and reduce conductivity of direct-current cable insulation material is introduced by using low-crosslinked linear low density polyethylene (LLDPE). LLDPE and low density polyethylene (LDPE) with different dicumyl peroxide (DCP) content are analyzed. The mechanical properties of LLDPE and LDPE with DCP are assessed by hot-set test,dynamic mechanical analysis (DMA) and tensile test. The DC conductivity and DC breakdown strength of these materials are also tested. The results show that crosslinked LLDPE behaves better than LDPE does in elongation in the range from 0.7 wt.% to 2.0 wt.% DCP addition,and corssslinked LLDPF meets the requirements of HVDC cable insulation for crosslinked polyethylene (XLPE) elongation with 0.7 wt.% DCP addition. In this condition,LLDPE with 0.7 wt.% DCP addition is chosen to be a substitute for traditional XLPE for the purpose of minimizing by-products. DMA and tensile test results verify that LLDPE with 0.7 wt.% DCP addition has higher Young's modulus and elongation at break than traditional XLPE does. DC conductivity and DC breakdown experiments show that LLDPE with 0.7 wt.% DCP addition has low conductivity,good temperature stability of conductivity and DC breakdown strength at the temperature range from 30 ℃ to 90 ℃. As the crosslinking by-products in the actual cable are difficult to be removed completely and unevenly distributed, it seriously affects the long-term safe operation of the cable. The low crosslinked LLDPE is recommended as the replacement of the traditional XLPE for the insulation material in HVDC cable insulation system,so as to reduce DC conductivity and enhance the temperature stability of conductivity while meeting high temperature mechanical properties.

Abstract:In view of the existence of single-phase grounding fault arc suppression in the non-effective grounding system of distribution network,the combination of additional active compensation and arc suppression coil is often used to suppress the grounding fault arc,and the performance of active compensation system control strategy directly determines the arc suppression performance. An active arc suppression scheme based on model predictive control (MPC) is designed. Firstly,the principle of active arc suppression using injection current mode is analyzed. Then,the active arc suppression system topology of three-cascaded H-bridge multilevel inverter is adopted,and the cost function is optimized. The active arc suppression closed-loop control system based on MPC is designed. Compared with the active arc suppression closed-loop control system based on proportional integral (PI) control,the control system proposed can achieve accurate tracking of multiple harmonic currents without parameter tuning,which effectively compensates the grounding current. Simulation and experimental results show that the proposed scheme can suppress the grounding fault current more effectively and meet the requirements of reliable arc suppression in different scenarios.

Abstract:To accurately describe operational electric vehicle (EV) drivers' irrational charging decision-making behaviors,a decision-making model for charging of operational EVs based on adapted cumulated prospect theory (ACPT) is established. Firstly,considering factors including arriving time,battery power remaining and psychological safety electricity,the charging demand models according to different mixes of peak and valley electricity tariffs is constructed. Then,a variable heterogeneous reference point model for the risk-preference-based ACTP is proposed with consideration of drivers' differences in psychological perception of arriving time and battery power remaining. Finally,the charging decision is evaluated based on the cumulative prospect values of the operational EV. Simulations are implemented and the results show that under the premise of a psychologically safe power level,owners with weaker psychologically perceived value will charge in advance instead of delaying charging. By combining risk preference and psychologically perceived value,the charging decision-making model proposed by this paper can explain irrational decision-making behaviours of operational EV drivers more accurately.

Abstract:Wind power generations are widely used in power system as a type of clean renewable energy. However, the random fluctuation of wind power output has a negative effect on the power quality of power system. The energy storage system has been applied to suppress the voltage and power fluctuation by wind power access to power system because of its flexible bidirectional regulation ability. In this paper,a multi-objective energy storage optimal allocation model is established based on system voltage deviation,daily active power loss and total energy storage access capacity as the objective function. A beetle antennae search-improved multi-objective particle swarm optimization (BAS-IMOPSO) algorithm which is formed by combining BAS and IMOPSO is used to solve the model,and the optimal energy storage allocation scheme is selected in Pareto solution set by using the technique of order preference by similarity to ideal solution based on information entropy. The proposed model has been applied to IEEE 33-node distribution system. The simulation results show that the energy storage system optimized by BAS-IMOPSO algorithm has significantly higher ability to reduce voltage deviation and active power loss of distribution network than MOPSO algorithm does,and it can effectively improve the power quality with the ability of peak load shifting. The model shows the effectiveness of the proposed BAS-IMOPSO algorithm.

Abstract:Lightning is one of the main causes of voltage sags in power grid. Accurate estimation of the severity of voltage sags caused by lightning can provide a basis for developing optimal management plans and siting sensitive users. In this paper,a data-driven self-learning estimation method for the severity of voltage sags is proposed. Firstly,based on the mechanism of voltage sags caused by lightning,the parameters involved in mining are selected by the monitoring information in lightning location system and power quality monitoring system. Secondly,the influence of discretization results on the accuracy of rules is reduced,and the number of discretization intervals for different parameters is determined by using discretization evaluation indexes. Then,to solve the problem of low efficiency of mining algorithm when the grid database changes dynamically,the incremental learning-based association rule mining algorithm to continuously update the mined rules,which gives it the ability of self-learning. Finally,a weighted Euclidean distance based on the integrated assignment method is proposed to evaluate the severity of voltage sags in real scenarios. The results of the empirical analysis by monitoring data of a regional power grid and simulation data of IEEE 30-node prove that the method in this paper can accurately mine valuable rules in reality and realize the severity assessment of voltage sags of the concerned nodes.

Abstract:On-load tap changers (OLTC) have complex mechanical and electrical structures,which are the key component for the on-load voltage regulation of transformers. Currently,due to the sample data which are not easy to be labeled,it is difficult to effectively train the OLTC mechanical fault diagnosis models based on vibration signals. To improve the fault diagnostic accuracy for OLTC with limited labeled data,a fault diagnosis method based on Bayesian optimization-convolutional ladder networks (BO-ConvLN) is proposed in this paper. Firstly,the ladder networks are used as a semi-supervised learning method for the feature extraction of vibration signals,which is guided by a large amount of unlabeled data,leading to the enhanced diagnostic ability of ladder networks only with a small amount of labeled data. Then,the fully-connected layers are replaced by convolutional operators in the ladder networks to better extract the features of non-stationary vibration signals. Furthermore,Bayesian optimization is used to optimize the high-dimensional hyperparameters of ladder networks,witch significantly improves the diagnostic accuracy of the model within limited time cost. The experiment results show that the diagnostic accuracy for the three types of faults,namely transmission shaft jams,poor switch lubrication,and top cover looseness,is 91.67% with a label count of only 40,which demonstrates the effectiveness of BO-ConvLN in the fault diagnosis.

Abstract:Aiming at the problem of poor control effect of grid-side converter of doubly-fed induction generator due to load change and filter parameter perturbation,a double closed-loop control strategy of grid-side converter based on extended state observer (ESO) and sliding mode control is proposed. The inner loop adopts ESO-based sliding mode direct power control with power as the state variable,and the outer loop adopts ESO-based sliding mode control with voltage square as the state variable. Using ESO to estimate the system state variables and lumped uncertainties including unmodeled dynamics,load variation and filter parameter perturbation of the system,the sliding mode control method can be designed without the accurate mathematical model of the system to realize the robust control of grid-side converter in a complex environment. In addition,the power difference feedforward link is introduced to reduce the impact of the nonlinearity of the outer loop sliding mode control when the load changes. Finally,two examples of load charge and filter parameter perturbation are simulated,and the results show that the proposed control strategy has stronger robustness in the complex environment than traditional vector control and sliding mode control.

Abstract:New energy power generation devices are mostly located in weak power grid areas,where the grid voltage harmonic content is high. Affected by the grid voltage harmonics and switching characteristics,the current of the grid-connected inverter is prone to distortion,which affects the system stability. To solve this problem,a selective harmonic current suppression method based on passivity-based control is proposed for three-phase grid-connected inverters in this paper. Firstly,the Euler-Lagrange (EL) mathematical model of the three-phase grid-connected inverter is established,and the current loop passivity-based controller is designed. Then,combined with the multiple reference frame (MRF) method,an error voltage compensation loop is introduced to independently control the harmonic current. Finally,a simulation model of the system is built and a comparative simulation study is performed with the conventional proportional integral (PI) control and passivity-based control. The simulation results show that the proposed control method which has the advantages of passivity-based control,can effectively suppress the harmonic current of the grid-connected inverter and reduce the design requirements of the filter,thus improving the adaptability of the grid-connected inverter to the weak grid.

Abstract:A multi-objective prevention strategy for grid cascading failures based on the screening of vulnerable branches is proposed in this paper for the phenomenon of cascading failures triggered by line faults in power systems. Firstly,an improved line safety index and system safety index are proposed,and the Thiel entropy index is introduced to assess the vulnerability of each line in the power system to quantify the impact on grid operational safety after a line fault being withdrawn from the operation. Then,several branches that have a seriously negative impact on grid operational safety after an initial fault being withdrawn from the operation are screened according to the line vulnerability ranking to establish a set of expected incidents. Finally,a cascading failures prevention and control model for power systems is established which takes into account the system safety index and grid voltage stability,as well as the asility of coping with various initial fault scenarios. The model is solved by using the non-dominated sorting genetic algorithm-Ⅱ (NSGA-Ⅱ). The simulation analysis based on the IEEE 39-node system shows that the proposed prevention strategy leads to a safe and reasonable generator output solution,and it demonstrates the importance of line load factor differences in the identification of vulnerable lines.

Abstract:For the problem that the abnormal circulation of bipolar double twelve-pulse ultra high voltage direct current (UHVDC) line permanent grounding fault can not be effectively isolated,an optimized scheme for suppressing the abnormal fault circulation is proposed. Firstly,the influencing factors of abnormal circulating current value for DC line permanent grounding fault are analyzed. Secondly,combined with the existing removal strategies of DC line fault in China,the causes of abnormal circulation are analyzed,which are caused by restarting the high-end valve group with communication condition,unsuccessful restart with communication condition or without communication condition after DC line grounding fault happens. Then,a circulating current suppression scheme for DC line permanent ground fault based on pole isolation and blocking after shifting phase 90° strategy is proposed accordingly. Finally,the simulation model is established through real time digital system (RTDS) to verify the effectiveness of the improved scheme. The results show that the scheme proposed in this paper can effectively solve the abnormal circulation problem of DC line permanent grounding fault under different working conditions.

Abstract:A large number of new energy units represented by wind power and photovoltaics are connected to the grid,making accurate calculation and verification of short-circuit current difficult. Given the phase mapping and the influence of electrical components (components between new energy units and grid) from the unit port to the grid-connected point,such as box transformer,collecting line,main transformer and transmission line are not considered when constructing the short-circuit current mapping model of new energy grid-connected point in the latest researches,an improved engineering grid short-circuit current calculation method that takes into account the phase characteristics of new energy sources and the influence of components between new energy units and grid is proposed. Firstly,combined with the national operation regulations,a supplementary theoretical modeling of the port voltage to short-circuit current phase mapping of new energy units is proposed. Secondly,the model is processed by engineering,and an iterative calculation method is proposed to extrapolate the obtained mapping back to the point of coupling. Then,the engineered short-circuit current amplitude-phase mapping model is applied to the existing local iterative calculation to obtain an improved calculation method. Finally,the new energy grid-connected model is built in the PSCAD simulation software to verify the accuracy of amplitude-phase mapping theory of new energy unit port voltage to short-circuit current and the effectiveness of iterative calculation theory of extra polating the unit port mapping model back to the point of coupling. On this basis,the mapping model is further verified by experiments in IEEE 39-node system. The results show that the proposed improved calculation method can improve the calculation accuracy of short-circuit current to a certain extent.

Abstract:The existing of transmission line icing may lead to the collapse of the transmission tower and disconnection of the transmission line,which seriously threatens the safe and stable operation of power grid. In this paper,aiming at the typical icing lines in Guizhou,the simulation model of 500 kV tower-line system is established by finite element simulation method,and the simulation analysis of different icing thicknesses and different wind speeds under uniform icing is carried out. The weak point position rules of 500 kV transmission tower are obtained by counting 25 groups of simulation results. Then,based on the axial stress and node displacement of the weak components of the transmission tower, the operational risk assessment analysis of the transmission tower is carried out,and the operational risk state of the transmission tower is divided. Furthermore,the effect analysis of two kinds of reinforcement measures is carried out,and the relationship between axial stress and node displacement at different weak points of the transmission tower before and after reinforcement is obtained. The results show that the weak points of the 500 kV transmission tower are mainly distributed at the ground bracket of the tower head,the joint of the upper and lower curved arms, the bottle neck and the body of the tower. Under uniform icing and wind load,the axial stress and node displacement of key components increase nonlinearly. The critical expressions of safety,warning and dangerous state of the transmission tower are fitted. The reinforcing effect of increasing the cross-sectional area of components is better than that of changing the angle steel structure with weak points. The axial stress and joint displacement of the transmission tower at the weak point have no obvious change before and after reinforcement when changing the angle steel.