1、中文 3420 字 附录 A 外文资料 Power system load forecasting methods and characteristics of Abstract: The load forecasting in power system planning and operation play an important role, with obvious economic benefits, in essence, the electricity load forecasting market demand forecast. In this paper, a systema
2、tic description and analysis of a variety of load forecasting methods and characteristics and that good load forecasting for power system has become an important means of modern management. Keywords: power system load forecasting electricity market construction planning 1. Introduction Load forecast
3、ing demand for electricity from a known starting to consider the political, economic, climate and other related factors, the future demand for electricity to make predictions. Load forecast includes two aspects: on the future demand (power) projections and future electricity consumption (energy) for
4、ecast. Electricity demand projections decision generation, transmission and distribution system, the size of new capacity； power generating equipment determine the type of prediction (such as peaking units, base load units, etc.). Load forecasting purposes is to provide load conditions and the level
5、 of development, while identifying the various supply areas, each year planning for the power consumption for maximum power load and the load of planning the overall level of development of each plan year to determine the load composition. 2. load forecasting methods and characteristics of 2.1 Unit
6、Consumption Act Output of products in accordance with national arrangements, planning and electricity intensity value to determine electricity demand. Sub-Unit Consumption Act； Product Unit Consumption； and the value of Unit Consumption Act； two. the projection of load before the key is to determine
7、 the appropriate value of the product unit consumption or unit consumption. Judging from Chinas actual situation, the general rule is the product unit consumption increased year by year, the output value unit consumption is declining. Unit consumption method advantages are: The method is simple, sho
8、rt-term load forecasting effective. Disadvantages are: need to do a lot of painstaking research work, more general, it is difficult to reflect modern economic, political and climate conditions. 2.2 Trend extrapolation When the power load in accordance with time-varying present some kind of upward or
9、 downward trend, and no obvious seasonal fluctuations, but also to find a suitable function curve to reflect this change in trend, you can use the time t as independent variables, timing value of y for the dependent variable to establish the trend model y = f (t). When the reason to believe that thi
10、s trend will extend to the future, we assigned the value of the variable t need to, you can get the corresponding time series of the future value of the moment. This is the trend extrapolation. Application of the trend extrapolation method has two assumptions: (1) assuming there is no step change in
11、 load； (2)assume that the development of load factors also determine the future development of load and its condition is unchanged or changed little. Select the appropriate trend model is the application of the trend extrapolation an important part of pattern recognition method and finite difference
12、 method is to select the trend model are two basic ways. A linear trend extrapolation forecasting method, the logarithmic trend forecasting method, quadratic curve trend forecasting method, exponential curve trend forecasting method, growth curve of the trend prediction method. Trend extrapolation m
13、ethods advantages are: only need to historical data, the amount of data required for less. The disadvantage is that: If a change in load will cause large errors. 2.3 Elastic Coefficient Method Elasticity coefficient is the average growth rate of electricity consumption to GDP ratio of between, accor
14、ding to the gross domestic product growth rate of coefficient of elasticity to be planning with the end of the total electricity consumption. Modulus of elasticity law is determined on power development from a macro with the relative speed of national economic development, which is a measure of nati
15、onal economic development and an important parameter in electricity demand. The advantages of this method are: The method is simple, easy to calculate. Disadvantages are: need to do a lot of detailed research work. 2.4 Regression Analysis Method Regression estimate is based on past history of load d
16、ata, build up a mathematical analysis of the mathematical model. Of mathematical statistics, regression analysis of the variables in statistical analysis of observational data in order to achieve load to predict the future. Regression model with a linear regression, multiple linear regression, nonli
17、near regression and other regression prediction models. Among them, linear regression for the medium-term load forecast. Advantages are: a higher prediction accuracy for the medium and the use of short-term forecasts. The disadvantage is that: (1) planning level It is difficult years of industrial a
18、nd agricultural output statistics； (2) regression analysis can only be measured out the level of development of an integrated electricity load can not be measured out the power supply area of the loading level of development, thus can not be the specific grid construction plan. 2.5 Time Series Analy
19、sis The load is on the basis of historical data, trying to build a mathematical model, using this mathematical model to describe the power load on the one hand this random variable of statistical regularity of the change process； the other hand, the mathematical model based on the re-establishment o
20、f the mathematical expression of load forecasting type, to predict the future load. Time series are mainly autoregressive AR (p), moving average MA (q) and self-regression and moving average ARMA (p, q) and so on. The advantages of these methods are: the historical data required for less, work less.
21、 The disadvantage is that: There is no change in load factor to consider, only dedicated to the data fitting, the lack of regularity of treatment is only applicable to relatively uniform changes in the short-term load forecasting situation. 2.6 Gray model method Gray prediction is a kind of a system
22、 containing uncertain factors to predict approach. Gray system theory based on the gray forecasting techniques may be limited circumstances in the data to identify the role of law within a certain period, the establishment of load forecasting models. Is divided into ordinary gray system model and op
23、timization model for two kinds of gray. Ordinary gray prediction model is an exponential growth model, when the electric load in strict accordance with exponentially growing, this method has high accuracy and required less sample data to calculate simple and testable etc.； drawback is that for a change in volatility The power load, the prediction error larger, does not meet actual needs. And the gray model optimization can have ups and downs of the
