What Are Power Dips?

Voltage sag evaluation method ^[1] refers to the method used to measure the degree of voltage sag. Voltage sags are caused by a short-term sharp increase in grid current. Most voltage sags are caused by lightning strikes and short-circuit faults on transmission lines. Because the frequency of voltage sags is very low, which makes it difficult to monitor and evaluate it, the actual measurement method has low credibility in the indicators obtained during its research period. Due to this obvious deficiency of the measured method, digital simulation is a very effective alternative. Since the power system is essentially a stochastic system, probabilistic modeling and statistical evaluation of the power system through probabilistic simulation methods can evaluate the performance of the power system as a whole and at a macro level. Monte Carlo method is a typical probabilistic simulation method.

Broadly speaking, power quality refers to high-quality power supply. Because people have different perspectives on the problem, there are different understandings about the meaning of power quality. The power department mainly defines the power quality as the qualified rate of voltage and frequency, and uses statistics to show that the power system 99.9% is safe and reliable. Power users simply define power quality as normal power supply to the load. The International Electrotechnical Commission (IEC) proposes the term electromagnetic compatibility (EMC), which points out and emphasizes the interactions and effects between devices and the interactions and effects between power sources and devices. The IEC has also developed a series of standards for electromagnetic compatibility. The technical definition given by the IEEE Technical Coordination Committee: "The concept of qualified power quality means that the power and grounding systems provided to sensitive equipment are suitable for the normal operation of the equipment." The definition of power quality used is: "Cause equipment failure or Malfunctions are all electrical problems in the form of voltage, current or frequency deviations. "The deviations here are broad and even include power supply reliability.

Before there are no clear new standards and specifications that are recognized by all parties, at least the problems related to power quality should be regulated in accordance with existing national standards. There are many types of power quality problems that can occur, mainly various transient processes, long-term voltage changes (overvoltage, undervoltage, continuous power failure), short-term voltage changes (power failure), and sags (sags). ), Voltage imbalance, waveform distortion, interference. Obviously, the existing standards cannot fully describe the power quality. For example, the international standards for voltage sags that have received special attention have not yet been formulated. This standard should be established as soon as possible.

Like other power quality issues, voltage sags are not a new problem. Until the 1990s, with the widespread application of sensitive power electronics in the industry, voltage sags have become the focus of attention in various aspects. Reasons:

(1) The requirements for short-term voltage fluctuations of modern electrical equipment are higher than those of traditional equipment. With the rapid development of high and new technology, especially information technology, electrical equipment and various power electronic equipment based on the management, analysis, detection, and control of computers, microprocessors, and speed regulation drives have been put into use in power systems in large numbers. Voltage fluctuations are more sensitive than general electromechanical equipment, and the requirements for power supply quality are more stringent: no matter the system is in normal steady state or fault transient state, the usability of fundamental wave sine power with small amplitude deviation must be guaranteed, that is, high dynamic Constant characteristics, and even a sudden voltage drop over several cycles will affect the normal operation of these devices, causing huge economic losses. Therefore, modern industry represented by information technology and other high-tech industries poses new challenges to traditional power supply, requiring the system to ensure reliable and constant high-quality power supply even in an unstable state.

(2) The problems caused by voltage sags far exceed other power quality problems, which are mainly determined by the characteristics of voltage sags themselves: (1) Long-distance faults may also cause voltage sags at sensitive load points; (2) The failure of parallel feeders of the same bus will cause the voltage of adjacent feeders to drop sharply; (3) the frequency of occurrence is much higher than other power quality problems. According to reports, user complaints caused by voltage sags account for 80% of the entire power quality problem} '.

(3) Misoperation or interruption of electromechanical equipment. This will cause huge economic losses and serious accidents may result.

(4) The voltage sag has brought a very adverse effect to the user. Because sensitive devices such as programmable controllers (PLCs), speed regulating motors (A SDs), computers, and contactors are extremely sensitive to short-term voltage fluctuations, a sudden voltage drop may trip these sensitive devices or restart the production line. According to the literature [3] statistics: For programmable controllers (PLCs), when the voltage is lower than 81%, the PLC stops working; for some I / 0 devices, when the voltage is lower than 90%, the duration is only a few cycles, it will It is cut off; when the voltage of the DC motor is lower than 80%, it is immediately tripped. According to reports, it takes about $ 50,000 to restart a production line due to a sudden voltage drop; a five-cycle power frequency interruption in a glass product factory caused a loss of about $ 200,000; a 2s power outage in a computing center caused about $ 600,000 in losses . The average loss per event is approximately $ 10,000, and each plant experiences approximately 2025 voltage sags each year [',. It can be seen that the sudden drop in voltage has become a serious factor affecting the normal operation of many devices, especially electronic devices.

(5) In people's daily life, it is also affected by the voltage drop. We are more familiar with the fact that in 1998, 500 sets of escalators were temporarily stopped due to a voltage drop in Hong Kong, which caused injuries to many customers and the social impact was very bad. On November 9, 1999, China Radio International reported that an editor of U.S. Business Weekly had been trapped in an elevator for up to 40 hours, and filed a claim with the office's property management department for serious psychological and physical injuries $ 25 million requirement. The cause of the elevator failure was due to the sudden drop in voltage of the power supply system.

From the above, we can see that the impact of the voltage sag on us cannot be ignored, and we must pay attention to it. Voltage sag has been considered to be one of the most important power quality problems affecting the normal, safe operation of many electrical equipment and the normal production of industrial users. It is currently the main interference affecting the reliability of power supply, and different types, even the same type but different brands The sensitivity of electrical equipment to voltage sags varies widely, which indicates that the harm caused by voltage sags is closely related to the characteristics of the equipment itself and the requirements of users. Therefore, how to eliminate or suppress the effects of voltage sags requires the power supplier , Equipment manufacturers and users work together to solve them. It has received widespread attention in industrially developed countries. Therefore, how to improve the voltage sag will be the key to improve the power supply quality to a whole new level. ^[1]

The study of voltage sags in Europe, America, Japan and other countries began in the early 1990s, and its research work has been quite in-depth, mainly including theoretical research and practical application. The theoretical research work is mainly from the following aspects: the establishment of a voltage sag index system; the determination of the voltage sag standard: the mechanism of the voltage sag, the impact of the voltage sag on user equipment, and the reduction of the voltage sag Technical measures; monitoring techniques, random prediction and statistical analysis of voltage sags; characteristics, classification of unbalanced voltage sags and propagation of voltage sags between different voltage levels; study of voltage sag domains and simulation of voltage sag processes Calculations; the impact of voltage sags on the reliability of power distribution systems; the effects of new compensation devices on voltage sags, etc. Practical applications include product development and software development. Several well-known international companies have already produced their own voltage sag control devices.

Voltage sags are caused by a short-term sharp increase in grid current. Most voltage sags are caused by lightning strikes and short-circuit faults on transmission lines. That is, the current caused by short-circuit faults in the power supply system or the user, various arc discharges, various load shedding, and switching of capacitors has increased dramatically ^[2]

The voltage sag domain refers to a fault point area where a short-term sudden voltage drop caused by a fault in the system prevents the related sensitive load from working normally. The analysis of the voltage sag domain is helpful to guide the optimal installation position of sensitive loads, how to reduce the impact of voltage sags in actual operation, and has important guiding significance for reducing the impact of voltage sags on sensitive loads. For example, sensitive loads can be installed near the power point to reduce the number and duration of voltage dips.

The determination of the voltage sag domain is to find out the range of faults in the system that will cause the voltage on the bus of interest to drop below the set voltage. We can select some sites of the power system for on-site power quality monitoring, determine the sag domain by statistical processing of the collected data, and also make random estimates of the system. In comparison, the former is more accurate, but is limited by the high cost and long monitoring cycle. Random estimation can solve these two problems well, and it can be divided into critical distance method and failure point method. The former is simple and can be calculated even when the system structure is unknown, but it can only calculate the sudden drop amplitude when the line fails, and it cannot take into account fault conditions such as substations and busbars, and it does not take into account that the duration of the sudden drop is sensitive The effect of load; while the fault point method can consider the impact of various fault conditions and various characteristic quantities on the sag domain, but it is relatively repurchasing and has a large amount of calculation.

Because the frequency of voltage sags is very low, which makes it difficult to monitor and evaluate it, the actual measurement method has low credibility in the indicators obtained during its research period. Due to this obvious deficiency of the measured method, digital simulation is a very effective alternative. Since the power system is essentially a stochastic system, probabilistic modeling and statistical evaluation of the power system through probabilistic simulation methods can evaluate the performance of the power system as a whole and at a macro level. Monte Carlo method is a typical probabilistic simulation method ^[2] .

Analysis of voltage sag evaluation method based on Monte Carlo simulation method

The Monte Carlo simulation method is also called random sampling technique or statistical experimental method. It is considered as a relatively accurate method in the current calculation of structural reliability. It is a very important numerical calculation method guided by the theory of probability and statistics due to the development of science and technology and the invention of electronic computers in the mid 1940s. A method that uses random numbers (or more commonly pseudo-random numbers) to solve many computational problems. Monte Carlo method was proposed as an independent method and was first applied in the development of nuclear weapons, and later in financial engineering, macroeconomics, and computational physics (such as particle transport calculations, quantum thermodynamic calculations, aerodynamics Computing) and other fields are widely used. However, the basic idea of the Monte Carlo method is not novel. As early as the seventeenth century Bo worked hard to put forward the idea that frequency determines probability in his works.

The basic principle of the Monte Carlo method: The probability of an event can be estimated from the probability of an event by a large number of experiments. When the sample size is large enough, the frequency of the event can be considered as its probability. Therefore, a large number of random samplings of random variables that affect its reliability can be performed first, and then these sampled values are substituted into a functional function formula to determine whether the structure fails, and finally the structure's failure probability can be obtained from it. From the idea of the Monte Carlo method, it can be seen that this method avoids the mathematical difficulties in structural reliability analysis. Regardless of whether the state function is non-linear and whether the random variable is non-normal, as long as the number of simulations is sufficient, a comparison can be obtained. Accurate failure probability and reliability indicators, accurate results, and easy to program because of simple ideas.

Can be seen from the above. Monte Carlo method for solving problems is based on a probabilistic model. According to the process described by this model, the results obtained through simulation experiments are used as approximate solutions to the problem. When the Monte Carlo method is used to study the voltage sag, the probability distribution model of the fault state variables needs to be established first, and random sampling values of these variables are generated according to these mathematical models to simulate the occurrence of a short-circuit process, thereby obtaining the characteristics of the voltage sag at the load .

The simulation must first establish a probability model. The probability model can be simple and intuitive, or it can be complex and abstract, which depends mainly on the problem to be solved. The complexity of the probability model determines the complexity of Monte Carlo calculations. When probabilistic models are constructed, this probabilistic process must be correctly described. Since various probability models can be regarded as being composed of various probability distributions, the generation of random variables with known probability distributions has become a basic means for implementing Monte Carlo simulation tests. The most basic is a uniform distribution on the probability distribution interval (o) 1>. The random number is a random variable with such a uniform distribution. The so-called random number is a sampling problem from this distribution. The probability model used in this simulation is This basic probability distribution is used many times. Random numbers are a basic tool for implementing Monte Carlo simulation methods.

After constructing a probability model and sampling from it, simulation experiments can be implemented. At this time, a random variable needs to be determined as an estimator of the solution of the required problem. If the expected value of this random variable is exactly the solution to the problem sought, it is called unbiased estimation. In Monte Carlo calculations, the most commonly used is unbiased estimation. Establishing an estimator is equivalent to performing statistical analysis on the results of simulation experiments Get the solution.

t Mathematical model of voltage dip assessment method for fault state change

According to the basic steps of Monte Carlo method, first establish the failure probability model needed to evaluate the reliability of voltage sag. The random variables involved in the fault process mainly include the fault type, fault line, fault location, fault duration, and the moment when the fault occurred.

Voltage Sag Evaluation Method Failure Type

The fault types mainly include single-phase ground, two-phase ground, two-phase fault and three-phase fault. The probability of each type of short circuit is related to the voltage level and weather. Depending on the statistical law of the scene, the probability of their respective occurrence is shown in the following table:

Voltage sag evaluation method Voltage sag probability index

As a relatively special commodity, electric energy also has many characteristics of the commodity, such as being measurable, and its quality can be described by various indicators. However, the quality of this special commodity and general products has special characteristics. It has the following characteristics: it is not entirely dependent on the power production enterprise, and even some quality indicators (such as harmonics, voltage fluctuations and flicker, three-phase Voltage imbalance is often determined by user interference: part of it is caused by unpredictable accidents and external force damage; the second is that power quality is dynamically changing in space and time. These characteristics of power quality indicate that these characteristics of power quality indicate that power quality indicators are suitable for measurement with probability statistics indicators. This study is based on Monte Carlo simulation, through fault calculation, to obtain a series of voltage drop probability indicators of the system and sensitive load points. The quantitative power quality probability index for each load point and the entire system can not only find the weak points in the entire power grid, but also provide a basis for whether to take appropriate measures to improve the power quality.