Abstract:Gas-steam combined cycle units couple various energy systems into multi-energy systems, such as electricity, heat and air-conditioning.The application of electricity-to-gas (P2G)technology helps to eliminate wind abandonment and further strengthens the coupling between power system and natural gas system.In this paper, the principle of abandoning wind in P2G and the start-stop control strategy of P2G equipment are discussed, and the gas storage and gas-electricity coupling system model of natural gas pipeline is established, and the multi-energy system cooperative optimal dispatching model considering natural gas-electricity coupling operation is constructed.Finally, through numerical simulation, the wind abandonment effect of multi-energy system considering natural gas-electricity coupling and the relationship between gas storage capacity of natural gas pipeline network and P2G allocation capacity are analyzed.The research shows that the abandoned wind can be further eliminated by making full use of the gas storage capacity of natural gas pipeline network, and the larger the gas storage capacity of pipeline network, the smaller the P2G capacity of system configuration.

Abstract:In order to solve the problems of reliability, safety and frequent false alarms in the current operation of the online monitoring system of converter station, a system based on the ubiquitous power IoT advanced technology is reconstructed in this paper.By constructing the platform layer, the system is connected to the IoT management platform and the enterprise mid-station, which realizes the fusion sharing of DC device operation data, reduces the cloud data storage pressure and improves the system service response.Secondly, the intelligent terminal based on the edge computing framework to realize the safe access and ubiquitous connection of various online monitoring devices is designed.The device is deployed as an edge computing node, integrating the algorithm of deep learning to realize the station-side data acquisition, storage, analysis and anomaly identification, which improves the accuracy of the alarm and system operation reliability.Therefore, the optimization of the online monitoring system architecture of the converter station based on the ubiquitous power IoT provides a typical application model for subsequent engineering practice.

Abstract:The paper constructs a deep learning fault classification model for fault diagnosis using a Sparse Restricted Boltzmann Machine(Sparse-RBM)based on the deep learning(DP)theory, in order to synthesize multi-dimensional information, determine transformer defects quickly and accurately, and solve the problem that multi-dimensional information fusion weights are difficult to determine.Combined with the multi-dimensional monitoring of large transformers, a transformer fault diagnosis method based on multi-dimensional information fusion and deep believe network is proposed.The method can utilize the massive unlabeled multi-dimensional monitoring data of the transformer as the learning sample, and only needs a small amount of tagged data for auxiliary optimization.The trained model can make an accurate fault diagnosis of the transformer body state according to the real-time online multi-dimensional monitoring data of transformers.The diagnosis test of a 220 kV main transformer in a city is carried out.The test results show that the accuracy of the method proposed in the paper is improved by 4% compared with the existing one.

Abstract:In view of the complex and changeable power consumption behavior of users under the background of power big data and the difficulty in analysis, a classification and analysis method of power consumption behavior of users based on undercomplete auto-encoder is proposed.Firstly, the data of intelligent electricity meters are encoded by an undercomplete auto-encoder to extract the features of the original data, and the back-propagation (BP)neural network is used to classify and analyze the user′s electricity consumption behavior.Then, the optimal coding ratio is selected, and the typical user electricity characteristics are taken as the input of the neural network to improve the classification accuracy.Finally, a simulation experiment is carried out on smart meters in Ireland data sets, compared with directly using the BP neural network analysis, the proposed method not only can improve the accuracy of detection, help electric power company to better grasp the power law of auxiliary demand response, but also can significantly reduce the running time of the algorithm.

Abstract:Traditional photovoltaic power station photovoltaic array generally adopts RS485 bus communication network, there are many disadvantages such as large construction workload, network difficulty, and difficult maintenance.Wifi, Zigbee and 4G are mature wireless communication technologies, which have been applied in the field of photovoltaic power generation.However, there are problems such as complicated technology, low communication rate and high cost respectively.In order to solve these problems, a new bluetooth 5.0 technology is introduced, which has the characteristics of simple implementation, high communication rate and good economy.On the basis of the analysis of the existing bluetooth network, this paper puts forward a PV power station wireless mesh network scheme, gives the detailed specific networking process and feasible routing algorithm.The analysis and calculation demonstrate the scheme has smaller communication time delay, good anti-interference and high safety, provides a new solution for photovoltaic power station network.

Abstract:Aiming at the current limitation which is only a single model is used in the optimization of PI controller parameters in HVDC systems, a method to tune the parameters is given.According to the transfer function model built firstly, the stability boundary locus is plotted.Then the small-signal model of system is established.After verifying the correctness of the model, the region which accords with the asymptotic stability of the system is found.Finally superpose the set satisfying the stability margin, and then the PI parameter set address both of the performance requirements is found out.The electromagnetic transient model is built and simulated in PSCAD/EMTDC.The results show that the stability margin and asymptotic stability of the system can be taken into account by this tuning method.

Abstract:The optimal allocation of independent microgrid capacity is an important link in the planning and construction of microgrid.This paper presents a new quantum inspired gravitational search algorithm based on levy flight for independent microgrid systems including wind power generation, photovoltaic power generation and battery.On the basis of ensuring the reliability of power supply and the consumption of new energy, a model for optimizing the capacity of independent microgrid was established.The global optimization ability of the quantum gravity search algorithm was enhanced by introducing the dynamic adjustment strategy of contraction and expansion coefficient and levy flight.The model proposed in this paper is used for simulation analysis, and compared with the results of other gravitation search algorithms and particle swarm optimization algorithms, the results show that the proposed algorithm has high solution accuracy and stability, and can ensure the economic and reliable operation of the independent microgrid system.

Abstract:A novel unified power quality conditioner (UPQC)and its control strategy for the fault ride-through operation of photovoltaic (PV)power station is present in this paper.The output voltage of PV station can be controlled to its rated value with the novel compensator under high grid voltage condition.The compensator could also compensate the grid harmonic voltage under various operation conditions, which can minimize the response time of phase-locked-loops embedded in the control loop of grid-tied PV inverter.The compensator helps the PV station output reactive power for enhancing the low voltage ride through performance.Moreover it absorbs reactive power from the grid in high voltage condition to support the grid voltage recovery, which could comprehensively improve the fault ride-through operation of photovoltaic power station.Furthermore, the performance of proposed compensator system with a 100 MW grid-tied PV station has been verified by Matlab/Simulink.

Abstract:Demand response(DR)has obtained more methods with a growing number of distributed energy storage systems(ESSs)tied to the grid on the demand side.Responsible capacity of ESSs is one significant aspect of DR ability of the demand side.The article proposes a method to identify the responsible capacity of ESSs in the distribution grid to estimate demand side ESSs’responsible capacity under different circumstances.The work considers various DR co-control aims of different kinds of loads and solves the operation strategy of ESS and changeable loads by particle swarm optimization, then calculates the responsible capacity of ESSs.The results show that load structure and distributed power outputs have an impact on the responsible capacity, to achieve the balance between security and reliability of power system operation and efficiency of ESSs, proper capacity allocation should take control objective into account.

Abstract:In a power grid with fluctuating voltage, the electric spring transfers it to the non-critical load in the target of guaranteeing that the electricity consumption varies with the power generation, thus alleviating the tricky problem rising from an unstable new energy generation effectively.However, it is bound to bring about new security risks to the power grid if a lot of non-critical load is applied for enhancing the voltage regulation of the electric spring.At present, there are few studies on the application configuration of electric spring.This paper first explains the basic principles of electric spring and the corresponding adjustment of the line voltage in a regional power grid.Secondly, a mathematical model of application configuration for electric spring is proposed.The model illustrates the quantitative relationship between the input of non-critical load and the reactive power from the electric spring.In addition, a configuration method of electric spring as to the minimum input of non-critical load is also proposed.Finally, the study results show that the minimum-proportion of non-critical load is obtained by this method and it forms an economical and rational configuration, the correctness and effectiveness of the configuration method is verified simultaneously.

Abstract:Under the background of large-scale electric vehicles(EV)integrated into the power grid, in order to coordinate and control the charging and discharging power of EV group,so as to make EV a useful energy storage element which can provide frequency regulation for the power grid, the self-organizing classification method of EV group from the aspect of state-of-charge(SOC)is studied in this paper, and a self-organizing map (SOM)neural network is designed to divide the EV group into several classes in the mathematical space according to the SOC.Based on the clustering results and the SOC level of each EV individuals in different classes, a control method of variable parameter droop frequency regulation for EV charging and discharging control terminal is presented.The simulation results show that by applying the proposed control method, the large-scale EVs integrated into the power grid with different SOC levels will share the peak load and surplus power of the power grid in proportion to their respective capacity, and meet the demand of power gird frequency regulation.

Abstract:One of the obvious differences between the UHVDC with single-layer connection transmission project and the UHVDC with hierarchical connection mode transmission project is latter has two AC filter yard, which will make some differences between both connection mode′s reactive power control strategy, such as DC power runback for unfulfilled ABSMIN filter and block converter for unfulfilled ABSMIN filter.In order to solve the DC power runback control problem for unfulfilled ABSMIN filter caused by UHVDC with hierarchical connection mode, the control strategy that DC power runback for unfulfilled ABSMIN filter in different operation modes of layered side is studied and some methods are proposed to reduce the impact of another normal AC grid, such as changing control mode and reducing power loss of normal layer.The control strategy test by RTDS simulation.The simulation results show that the control strategy can solve the DC power runback for unfulfilled ABSMIN filter control problems caused by UHVDC with hierarchical connection mode.

Abstract:Power system load is a nonlinear, non-stationary time series of load with typical periodicity and randomness.In order to reduce the nonlinearity of the load sequence and improve the prediction accuracy, a lumped empirical mode decomposition method (EEMD)and a modified artificial neural network (GABP)short-term load forecasting method are proposed.Using EEMD to decompose the load sequence into several stationary components of different frequencies, highlighting the local characteristics of the original load data, solving the classification fuzzy problem in EMD decomposition, and using GABP network to predict, solving the problem that BP is easy to fall into the local optimal solution.The appropriate parameters are used to construct different EEMD-GABP prediction models for each component, and the meteorological factors are introduced to predict each component separately, and the final predicted value is obtained after reconstruction.The example shows that the accuracy prediction high stability of load based on EMD-GABP prediction model is higher than that of traditional models such as ARIMA model and SVM model.

Abstract:At present, the research on the judgment of the correctness of relay protection function in intelligent substation focuses on the overall evaluation of protection system or the judgment of the correctness of protection execution process, and lacks the real-time evaluation of the status of various types of protection functions and the logical judgment of the trigger of protection functions.The status of each protection function are classified and evaluated by analyzing the influencing factors and influencing logic of each type of protection function.The correctness of protection function trigger is judged by capturing and analyzing the sampling value with the state of devices.The information sequence generated by the secondary system when the protection function is triggered is sorted out, and the correctness of the protection function execution process is judged by comparing the theoretical sequence with the actual sequence.At the same time, the pre-condition is added to solve the problem of selecting and matching different information sequences when the same protection function triggers.Through the analysis of field examples, it is verified that the method proposed in this paper can provide a theoretical basis for the monitoring of protection status and fault analysis of smart substation.

Abstract:DC-bus voltage stability of multi-micro-source DC microgrid system is an important index of power quality and one of the key factors that confine large-scale application.Aiming to solving the large fluctuation of the bus voltage, a master-slave coordinating control strategy based on the micro turbine as the main coordination unit is proposed.This control strategy making full use of the power regulation function of micro turbine, effectively reduces the fluctuation range of micro grid bus voltage and makes the output voltage more stable.At the same time, it reduces the number of batteries and the number of charges and discharges, and reduces the later maintenance cost of batteries.In this paper, hierarchical control, variable power control and master-slave coordinated control models are built in Matlab/Simulink respectively.By comparing the simulation analysis methods, the advantages of the proposed control strategy in reducing the battery input cost, maintenance cost and stable voltage are verified.

Abstract:Since the Chinese government continuously support the development of new energy vehicles (EVs), the charging process of EVs will generate big data regarding the EVs charging behavior.This paper proposes a big data mining technique based on Random Forest (RF)and Principle Component Analysis (PCA)for EV charging behavior to identify and analyze clusters with different charging characteristics.Then, Dundee′s EV charging data in the January of 2018 is applied to conduct experiments, and respectively obtains the charging behavior clusters of the workdays, weekends and holidays.Finally, the RF algorithm in the EV clustering problem is compared to the Euclidean distance method and the clusters obtained by RF get more convinced characteristics.

Abstract:Aiming at the difficulty of island power supply and water supply, combining seawater desalination system with micro-grid system, based on the principle of priority utilization of wind power and photovoltaic power generation and participation of battery and diesel engine in dispatching, an optimal economic operation scheme of island micro-grid containing seawater desalination is proposed.To solve the problem that the economic operation optimization algorithm of micro grid is prone to fall into the local optimal and difficult to get the lowest operation cost, an improved niche particle swarm optimization algorithm is proposed, which makes asynchronous change adjustment of learning factor and exponential decline of inertia weight, improving the optimization performance of the algorithm in the optimization process.To consider economic returns of desalination isolated micro power system economic operation cost minimum as the objective, optimization mathematical model is set up, and to improve the niche optimization calculation of particle swarm optimization, and does not consider water desalination system of micro grid economic operation optimization result is compared, the results show that the introduction of the seawater desalination system, improve the economic benefit of the system is also verified the proposed improved niche particle swarm algorithm has good optimization ability.

Abstract:In order to solve the frequency estimation problem in unbalanced three-phase power systems, the Complex-valued DFE (CDFE)algorithm is analyzed and improved.The CDFE algorithm is based on the linear prediction of sinusoidal signal, in which the instantaneous squared value of the error function is first defined, and its first derivative is used to track the frequency of the unbalanced three-phase power system.Furthermore, variable step-size CDFE (VSS-CDFE)algorithm is also derived based on the CDFE algorithm by using the steepest descent method.The experimental results show that CDFE algorithm is able to accurately track the frequency in the unbalanced power systems that based on complex-model under white Gaussian measurement noise, and the estimated mean square error (MSE)is also consistent with that obtained by the theoretical analysis.Compared with the traditional CDFE algorithm, the VSS-CDFE algorithm has smaller estimated variance at the same convergence rate.On the other hand, its convergence rate is faster than the conventional CDFE algorithm for a predefined variance requirement.Both algorithms provide unbiased and robust frequency estimates and the VSS-CDFE algorithm is more superior in terms of estimation variances.

Abstract:Due to the power and voltage constraints of the distribution system,the resource of wind power and hydropower is abandoned in microgrid planning to reduce equipment capacity.Thus,in order to make full use of renewable energy,an optimal configuration of effective and friendly grid-connected microgrid with wind-hydropower and storage is proposed.Firstly,the resource of wind power and hydropower is quantized,and the operation and control strategy of microgrid is determined.Then considering operational constraints of microgrid in distribution system,a multi-objective optimization model is established,with considering the costs of investment and operation,abandoned amount of wind power and hydropower,and annual power generation as objective functions.The model is solved by the non-dominated sorting genetic algorithm (NSGA-II).Finally,the technique for order preference by similarity to an ideal solution(TOPSIS)is adopted to choose the best optimal solution from Pareto solution set based on some indices proposed in this paper.The proposed algorithm is applied to a distribution network in Shaoguan county with multi-scenes,and the result shows the proposed model could improve the utilization of renewable energy and ensure the power quality of the distribution system,and verifies the effectiveness of the model and solution strategy.

Abstract:According to the inter-turn short circuit problem of single-phase transformer, the electromagnetic vibration characteristics of different turn-to-turn short-circuit ratios are studied.The electromagnetic coupling principle is used to establish the inter-turn short-circuit state equation of the transformer.The electromagnetic parameters and vibration acceleration changes under different short-circuit ratios are simulated.Under different inter-turn short-circuit faults, the short-circuit winding current direction changes, the amplitude becomes larger, and the un-short winding current changes less; the internal leakage flux increases and the leakage flux in the corresponding area of the short-circuit winding increases significantly; the winding vibration due to the increase of current and leakage flux Intensified; electromagnetic parameters and vibration acceleration are further changed as the proportion of short-circuit between turns is increased.Finally, the inter-turn short-circuit dynamic model experimental platform is built to measure the winding current and vibration acceleration under different inter-turn short-circuit faults at the head end of the transformer.The simulation results and experimental data are compared to verify the validity of the model and the correctness of the conclusions obtained.

Abstract:In view of the problem that the new generation of 300 Mvar Synchronous Condenser has no actual data of loss of excitation operation to support loss of excitation protection's cast or cancel strategy and relay protection setting calculation at present.Through the development of loss-of-excitation protection test in the start-up and commissioning process of a new generation of 300 Mvar Synchronous Condenser.The key data obtained from the loss-of-excitation protection test during the start-up and debugging of a new generation of synchronous condenser are presented.The corresponding relay protection setting adjustment and protection cast or cancel strategy of loss-of-excitation protection in the starting and running stages of synchronous condenser are studied.The loss-of-excitation protection test method in the start-up and debugging project of a new generation of synchronous condenser is described in detail, and the experimental conditions required in the loss-of-excitation protection test process are introduced.Combined with the experiment of rated leading phase operation and complete loss of excitation operation, the maximum leading phase depth, excitation current and terminal voltage of the new generation of condenser are obtained.Through the analysis and research of the data, the recommended setting value of the excitation low voltage setting value of the loss of excitation protection and the on-off strategy of each section of the loss of excitation protection in the start-up stage and operation stage are obtained, which provides a reference for the future production of the condenser.

Abstract:According to the insufficient endurance of rotor UAV in power line inspection, a design of high voltage electric-field induction energy-acquisition based on pulsed power technology is proposed.The inductive electric energy is stored between the high voltage electric field and the overhead ground line by using the airborne conductor of the patrol UAV as a floating electrode.The airborne conductor cascades the gas self-triggering switch and the inductor, and forms an energy-receiving loop with the overhead ground wire.The floating electrode breaks through the switch air gap and discharges to the ground.With the development of air gap discharge, the distributed capacitance between the floating electrode and the power line and the overhead ground line will be quickly divided to suppress the discharge.Therefore, an arc cannot be formed between the air gaps, and the high-frequency stream is injected into the pulse discharge to excite the high-frequency electromagnetic oscillation of the loop.Finally, the electric field induced electric energy output is realized by the electromagnetic mutual inductance.This paper introduces the principles of this design and the theory of inhibition-discharge, analyzes the equivalent energy-gaining circuit and builds a discharge-pulse energy-gaining circuit model.The feasibility of the design is verified through tests on the physical platform.

Abstract:Due to the demand for high-power, high-frequency and high-temperature operating environments, silicon carbide devices have become the representative of next-generation semiconductor devices.However, the spike problem of silicon carbide (SiC)devices has been restricting the development of this new device.The silicon carbide metal oxide Semiconductor Field Effect Transistor (SiC MOSFET)is taken as the research object, and the research on the peak problem is carried out from the aspect of using the silicon carbide device in the inverter, and the SiC is analyzed.The MOSFET generates peaks and oscillations during the switching process.By increasing the RC snubber circuit to optimize the spike and oscillation of the silicon carbide, the RC snubber circuit can be used to reduce the spikes and oscillations generated by the SiC device.Multiple sets of experiments are used to fit the data curve, and the equation relationship between the snubber capacitor and the snubber resistor in the RC snubber circuit is determined.

Abstract:In the wireless power transfer (WPT)system, the received power of the load is sensitive to the change of mutual inductance and resistance.When there is deviation between the receiving coil and the transmitting coil or the change of load equivalent impedance, the received power of the load should be basically stable through effective control.Based on the analysis of the WPT system with DC/DC circuit in the secondary side, the relationship between mutual inductance and load voltage and current, as well as the relationship between duty cycle of DC/DC circuit and load power are given.The stable control strategy of output power by detecting load voltage and current and then adjusting DC/DC circuit is proposed.Finally, through Matlab/Simulink simulation and the establishment of the experimental platform, the paper verifies the effectiveness and correctness of the theoretical analysis and control strategy in this paper.

Abstract:In order to accurately predict the pollution of transmission line insulators in complex environment and to achieve warning of pollution flashover, a method for identification of pollution characteristics of transmission line insulator and pollution prediction based on data driven is proposed.Combined with improved rough set and sample weighting method, a comprehensive quantitative model of insulator pollution characteristics based on PSO-BP neural network, and important characteristics affecting pollution can be quantified.On the basis of identification, a weighted support vector machine based on improved rough set is constructed to predict the pollution of the insulator and identify the risk of pollution flashover.The results show that the method is completely based on data driving and the charac-teristics of insulators with different operating environments and complex data types can be accurately identified.Compared with other methods, the proposed pollution prediction and risk identification method is more accurate and has smaller error due to the importance of the characteristics.The method proposed has good application prospects.

Abstract:In order to cope with the closed environment of the power distribution room, the poor air permeability, the high temperature and solve the problem that the high temperature affects the safe operation of the power equipment, it is necessary to study the prediction model of the temperature change of the power distribution room for temperature regulation and control.The prediction model for temperature variation of power distribution rooms based on grey box theory is proposed, which provides a model basis for automatic control of power distribution room temperature.Firstly, the basic structure of the power distribution room is introduced.Then the thermoelectric model of the power distribution room is obtained according to the physics knowledge of heat transfer, dynamics and thermoelectric similarity theory.Next, using the time series of relevant data, the unknown physical parameters in the model is estimated based on the gray box method.Meanwhile, the rationality of the model is verified through their auto-correlation matrix.Finally, the one-step and six-step predicted temperature values of the model are compared with actual temperature values.The results not only show that the model can better describe the thermodynamic characteristics of power distribution room, also indicate that it is consistent with the actual temperature changes in the distribution room.