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This paper proposes the data mining method of voltage sag severity based on DHP algorithm and replaceable coefficient to assess the risk of voltage sag. The DHP (Direct Hashing and Pruning) is served to mine the relationship between voltage sag characteristic attribute (VSCA) in the fault scenario and the voltage sag severity (VSS) of node. Using direct hash pruning technology, frequent item sets can be found quickly and mining efficiency can be improved. The association rules are matched with the actual fault scenarios through replaceable coefficients to get the VSS of actual fault scenarios. Finally, the effectiveness and accuracy of this method are verified by simulation and examples.

Power quality monitoring involves multiple types of interrelated data information, and the relationship between data entities is complex and dense, so graph database is more suitable for storage. Based on graph database and power graph computing platform, a power quality monitoring and visualization system based on the graph database is proposed. The power grid spatial data, real-time data of power grid users and equipment, and geographic environment data of power grid topology and its connection are stored through the graph database, so as to calculate the power graph related to power quality monitoring. Through the human-machine interface of the graph database query design, the multi-directional multi-angle visual display of power quality monitoring applications such as voltage sag location and voltage sag risk assessment are carried out.

In recent years, the key work of power grid company is to provide voltage sag management service for high-precision and sensitive load. The current voltage sag treatment scheme mainly determines the capacity of the standby power supply through the equipment tolerance assessment, and the treatment cost is too high. In this paper, the configuration method of voltage sags control device is put forward, and the comprehensive benefit evaluation index system of power quality control for power user’s is established, the quality problem of a large number of products caused by voltage sags in the customer’s production line is solved, and the unnecessary economic loss is reduced. The research results presented in this paper effectively reduce the equipment trip, production process interruption, reduce user’s loss, improve product quality.

It is necessary to evaluate the reliability of the system's operation after grid-connected offshore wind power, to comprehensively evaluate and further improve the reliability of the grid including the receiving end of offshore wind power, which is beneficial the receiving power grid with large-scale offshore wind power runs safely and stably. Improve the power supply reliability of the offshore wind power receiving terminal. Considering the harsh operating conditions of offshore wind power, the frequent occurrence of extremely bad weather such as typhoons on the eastern coast, and the mutual influence of certain situations are frequent and involve a wide range, which brings serious harm to the offshore wind power connect system. At the same time, offshore wind power maintenance has poor accessibility, high maintenance costs, and reduced the reliability level of offshore wind power systems. In addition, when offshore wind power is connected to the receiving power grid through a combination of high-voltage AC and DC, it will have complex interactions with multi-level AC and multi-type DC external incoming calls, which may expand the scope and depth of the fault. Therefore, it is necessary to take into account the effects of severe weather at sea, offshore wind power maintenance plans, and various complex interactions to conduct a more comprehensive and in-depth study of the reliability assessment of offshore wind power connect to the power grid.

Typhoon disaster can result in wind farms shutdown. With the large-scale integration of wind farms in power system, the wind farms shutdown may affect the operation of power system, causing the power shortage and voltage violation. In this paper, a shutdown risk assessment method is proposed to evaluate the risk of wind farms operation under typhoon disaster. Firstly, the distribution of forecast error of wind power under typhoon conditions is analyzed according to the historical data and is established as T distribution. Next, the real-time shutdown probability of wind farms is generated by the known cumulative error distribution. Then, the shutdown cost of wind farms are expressed by the cost of shedding load after wind power exiting, which is solved by particle swarm optimization method. Finally, the adjusted IEEE-33 node system with wind farms are adopted to verify the effectiveness of proposed method.

Most of the small-size hydropower stations are runoff hydropower stations and their output is determined by the upstream water supply. Consequently, the rainfall brought by typhoons will lead to the increment of runoff, increasing the output of small-size hydropower stations. The uncertain increment of the output of small-size hydropower stations will bring adverse effects on the security of power system, such as the voltage over-limit and the power overload of transmission lines. In this paper, a risk assessment method is proposed to assess the shutdown risk of small-size hydropower station under typhoon disaster. Firstly, Monte Carlo Method is employed to calculate the probabilistic load flow of power system with small-size hydropower station and the probability of node voltage over-limit and branch power overload is set to be the shutdown probability of small-size hydropower station. Secondly, the cost of load shedding which is optimized by Adaptive Particle Swarm optimization (APSO) algorithm is set to be the shutdown cost of small-size hydropower station. Finally, the IEEE-33 bus system is used to assess the shutdown risk of small-size hydropower station under typhoon disaster.

Ultra-high-power arc furnace is the main equipment of modern smelting. It is very important to accurately model it in order to understand the time-varying and non-linear of arc and realize the targeted research of power quality. In this paper, a new model of ultra-high-power electric arc furnace for the study of low-frequency and non-stationary inter-harmonics is proposed. Firstly, according to the law of conservation of energy, a static model of an ultra-high-power arc furnace is established. Then, based on the static arc model and the chaotic theory, a dynamic mathematical model of ultra-high-power electric arc furnaces is established to describe the characteristics of inter-harmonic emission between low-frequency and non-stationary. Finally, the feasibility and correctness of the model is verified in Matlab/Simulink simulation environment. The simulation results show that the model of the ultra-high-power electric arc furnace proposed in this paper can accurately reflect the operation characteristics of ultra-high-power electric arc furnace in practical industrial applications, and can reveal the low-frequency non-stationary inter-harmonic emission characteristics of the ultra-high-power electric arc furnace. In addition, it reflects the influence of ultra-high-power electric arc furnace equipment on the stability of distribution network.

This paper starts from the power demand side, which proposes a time-sharing peak-valley pricing method for power users. Firstly, the OCHNN-Kmeans algorithm is adopted for the clustering of power load curves. This algorithm can overcome the disadvantages of K-means clustering instability. The use of OCHNN-Kmeans to cluster power consumer load data can meet the high-dimensional characteristics of power load data. On the other hand, the calculation speed of this algorithm is relatively fast and can be used in the practical application of power industry; According to the clustering results, typical user load data are extracted from each type of electricity consumers. The parameters of peak-to-peak, peak-flat, and valley-bottom load transfer rates were estimated using the constrained least-squares method. The estimated load value after the peak-to-valley time-of-use electricity price is changed, the estimated load value is fine-tuned in combination with the electricity price elasticity matrix, and the design optimization example is used to formulate optimal time-average peak-to-valley prices for different classes; finally, the domestic south is combined. An empirical analysis of the real data of a city provides that the development of specific time-of-the-hour peak-valley tariffs for different power users can reduce the electricity cost of demand-side power users, enable peak load-filling of load curves, and increase the efficiency of energy use. Meet the diverse needs of power users.

With the increasing of electric vehicles (EVs) users, a large amount of reserve charging infrastructure have to be deployed in distribution systems to the uncertain charging demand, which may lead to redundant investment. In order to reduce unnecessary investment and optimize the plan of charging station and distribution network, a multi-objective planning model is proposed. The objectives of planning model include the benefits of both distribution network and EV user. The proposed method has been verified on a modified 54-bus distribution and 19-node road system. The results shows that the proposed model can give collaborative plan, and ensure the benefits of both the distribution side and user side.

The fast charging and discharging characteristics of energy storage technology provides an effective way to solve the problems of peak clipping and valley filling on the grid side, large-scale access to renewable energy on the power generation side, and stable operation of isolated networks. In view of the economics of current energy storage equipment, there is still no good evaluation method. The life cycle cost is proposed as an indicator to evaluate the economics of energy storage equipment. The dynamic and static model of the energy storage system is established. Taking a demonstration work as an example, the calculation is carried out. It correctly displays the long-term cost advantage and efficiency advantage of the equipment in the whole operation process and provides a decision-making basis for the comprehensive evaluation of the economics of energy storage equipment.

The battery energy storage system (BESS) is developing from the demonstration project to the stage of business promotion Due to the unsound Economic benefit evaluation, which restricts the large-scale promotion and construction of BESS. This paper establishes the life cycle cost and income model of BESS and uses the dynamic investment payback period, net present value (NPV), internal rate of return (IRR) and other economic indicators to analyze the economy of offshore wind power with BESS in reducing forecast deviation penalty. At the same time, aiming at stimulating the enthusiasm of the wind farm to allocate energy storage, we studied the improvement of the penalty rules of wind power forecast deviation. The research results can provide an engineering economic reference for the investment decision of BESS.

Dynamic Time Warping(DTW) algorithm has strong resistance to synchronous error. Aiming at the similarity and asynchrony of meteorological factor, a method of applying DTW to photovoltaic power prediction is proposed. The meteorological factors which have great influence on photovoltaic power generation are selected by Pearson correlation coefficient method. Based on the DTW algorithm, the similarity of meteorological factors between the predicting days and the historical days can be measured. Through weighted calculation of similarity, the similar days are used to obtain training data of Partial Least Squares(PLS) prediction model. The simulation study on a photovoltaic power station verifies the correctness and effective of the proposed prediction method. The results show that the prediction model has great forecasting accuracy and certain feasibility and practicability.

After Xiamen VSC-HVDC Project is put into operation, it can improve the power supply capacity and reliability of Xiamen Power Grid.But at the same time,it also brings new problems to the operation of the power grid, among which the short-circuit current problem is particularly prominent.In the preliminary analysis of power grid operation, using the short- circuit current program (PSD-SCCP) commonly used in domestic power grid simulation analysis to calculate to be found that:VSC-HVDC will provide a large short-circuit current when the AC grid is short-circuited, causing the short-circuit current levels of multiple 220kV busbars of the Xiamen Power Grid to approach or exceed 50kA, which brings greater pressure on the adjustment and arrangement of the grid operation mode.Therefore, it is necessary to study the true level of the impact of Xiamen VSC-HVDC on the short-circuit current of the AC grid based on the actual control logic of the Xiamen VSC-HVDC project, in order to propose more accurate short-circuit current suppression measures to achieve bipolar operation of Xiamen VSC-HVDC.

In order to accurately evaluate the impact of voltage sag on both utility and customer, a data mining analysis method based on improved FP-growth algorithm and AHP algorithm is proposed. The proposed method selects and classifies voltage sag characteristics and combines voltage sag severity level to construct a data mining analysis framework. The improved FP-growth algorithm is used for data mining on voltage sag events to improve the efficiency of mining. The association rule matching model is constructed by AHP algorithm for evaluating the voltage sag severity level, which improves the accuracy of the evaluation results. Finally, a practical example verifies the practicability of the proposed method.

VSC-HVDC has been widely used at home and abroad, but there is no clear conclusion about the characteristics and calculation method of the short-circuit current contributed by VSC-HVDC during the AC Short-Circuit Fault near the converter station. The calculation methods in the field of short-circuit current engineering have not been unified, and the adaptability and error of different methods have not been analyzed in detail. Through electromagnetic transient simulation, this paper analyzes the transient characteristics of VSC-HVDC contribution short-circuit current, and combs the key influencing factors of VSC-HVDC contribution short-circuit current. Finally, taking a VSC-HVDC system in China as an example, the adaptability of the commonly used short-circuit current algorithm is analyzed. It is verified that the existing engineering algorithms have made great progress compared with the original. However, compared with the electromagnetic transient refined simulation, there is still a large error in the calculation results of individual nodes under some control modes / fixed values.

Thepaper studies the effect of automatic generation control(AGC) on power frequency based on the full dynamic simulation. First modeling of AGC for the full dynamic simulation according to the three components of AGC, which is calculation of area control error (ACE), simulation of control strategy, and calculation of generating power regulation. Second the effect of key-parameters of AGC including dead band, transient frequency-deviationon and rate of generating power regulation on power frequency is studied by simulating. Finally, the paper takes Fujian power as an example to analyze the effect of AGC on under-frequency loading shedding(UFLS) by the serious faults and study on the coordination control between AGC and UFLS.

In recent years, with the development of distributed generation(DG) technologies, a large number of DG are connected to the distribution network, however, the output of DG is intermittent and random. Considering the timing characteristics of DG and loads, this paper establishes a generalized power optimal configuration model of energy internet which takes power purchasing cost, investment cost, operation and maintenance cost, network loss cost, fuel cost and government subsidies comprehensive cost as the objective functions. The invasive weed optimization(IWO) based on cloud model is used to solve the model. The model and the algorithm proposed in this paper are simulated by IEEE 13 nodes to verify its validity.

In order to analyze interaction between wind farm and electric power system, research transient voltage characteristics of large-scale wind farm in system fault and after fault, and realize large-scale wind farm fault ride through, it is necessary to build wind turbine modeling suitable for large electric power system simulating calculation program. Various power system simulators are used in many research institutes and power operators home and abroad, and there are different processing methods for wind turbines and wind farms modeling designed for different research purposes, as well as different running characteristics with different wind turbine manufacturers and technical specifications, so whole process simulation under multiple working conditions shall be realized by carrying out corresponding work. Based on basic theory of wind power generation, this paper analyzes structure and characteristics of double fed induction generator (DFIG), researches models of its mechanical system, electric system and other main constituents, and gives basic requirements and characteristic simulation of wind turbine modeling with transient response characteristics under multiple working conditions.