电力系统负荷预测及方法(外文翻译)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 systematic 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 Planning1.IntroductionLoad forecasting 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) forecast.Electricity demand projections decision generation, transmission and distribution system, the sic 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 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 of2.1 Unit Consumption ActOutput 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 the appropriate value of the product unit consumption or unitconsumption. Judging from China's 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 arc: The method is simple, short-torn load forecasting effective. Disadvantages arc: 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 extrapolationWhen the power load in accordance with time-varying present same kind of upward or 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 this trend will extend to the future, we assigned the value of the variable t need to, you can get the corresponding tune series of the future value of the moment. This is the trendextrapolation.Application of the trend extrapolation method has two assumptions: (1) assuming there is no step Change in 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 method is to select the trend model arc 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 method's advantages arc: 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 MethodElasticity coefficient is the average growthrate of electricity consumption to GDP ratio of between, according to the gross domestic product growth rate of coefficient of elasticity to be planning with the end of the total electricity consumption. Modules of elasticity law is determined on power development from a macro with the relative speed of national economic development, which is a measure of national economic development and an important parameter in electricity demand. The advantages of this method arc: The method is simple, easy to calculate. Disadvantages arc: need to do a lot of detailed research work.2.4 Regression Analysis MethodRegression estimate is based on past history of load data, 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, nonlinear regression and other regressionprediction models. Among them, linear regression for the medium-torn toad forecast. Advantages arc: 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 and 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 notbe the specific grid construction plan.2.5 Time Series AnalysisThe 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 of the mathematical expression of load forecasting type, to predict the future load. Time series are mainlyautoregressive AR (p), moving average MA (q) and self-regression and n3oving average ARMA (p, q) and so on. The advantages of these methods arc: the historical data required for less, work less. 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 methodGray prediction is a kind of a system 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 optimization model for two kinds of gray.Ordinary gray prediction model is an exponential growth model, when the electric load in strict accordance with exponentiallygrowing, 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 largo, does not meet actual needs. And the gray model optimization can have ups and downs of the original data sequence transformed into increased exponentially increasing regularity changes in sequence, greatly improving prediction accuracy and the gray model method of application. Gray Model Law applies to short-torn load forecast. Gray predicted advantages: smaller load data requirements, without regard to the distribution of laws and do not take into account trends, computing convenient, short-term forecasts of high precision, easy to test. Drawbacks: First, when the data the greater the degree of dispersion, namely, the greater the gray level data, prediction accuracy is worse; 2 is not very suitable for the long-term power system to push a number of years after the forecast.2.7 Delphi MethodThe Delphi method is based on the special knowledge of direct experience, research problems of judgment, a method for prediction of, also called experts investigation. Delphi method has feedback, anonymity and statistical characteristics. Delphi method advantage is:(1) can accelerate prediction speed and save prediction Cost; (2)can get different but valuable ideas and opinions; (3)suitable for long-term forecasts in historical data, insufficient or unpredictable factors is particularly applicable more. Detect is: (1)the load forecasting far points area may not reliable;(2)the expert opinions sometimes may not complete or impractical.2.8 Expert System ApproachExpert system prediction is stored in the database over the past tow years, even decades, the Hourly load and weather data analysis, which brings together experienced staff knowledge load forecasting, extract the relevant rules, according to certain rules, load prediction.Practice has proved that accurate load forecasting requires not only high-tech support, but also need to reconcile the experience and wisdom of mankind itself: Therefore, you need expert systems such technologies. Expert systems approach is a non-quantifiable human experience translated into a better way But experts systems analysis itself is a time-consuming process, and some complex factors (such as weather factors), even though aware of its load impact, ht}t to accurately and quantitatively determine their influence on the load area is also very difficult. Expert system for forecasting method suitable for medium and long-term load forecast. The advantages of this method: (1)can bring together multiple expert knowledge and experience to maximize the ability of experts; (2) possession of data, information and mort factors to consider a more comprehensive and beneficial to arrive at mart accurate conclusions. The disadvantage is that: (1)do not have the self-learning ability, subjectto the knowledge stored in the database limits the total; (2) pairs of unexpected incidents and poor adaptability to changing conditions2.9 Neural Network MethodNeural network (ANN, Artificial Neural Network) forecasting techniques to mimic the human brain to do intelligent processing, a large number of non-structural. non-deterministic laws of adaptive function. ANN used in short-term load forecasting and long-term load forecast than that applied to be mart appropriate. Because short-term load changes can be regarded as a stationary random process. And long-term load forecasting may be due to political, economic and other major fuming point leading to a mathematical model-based damage. Advantages arc:(1) to mimic the human brain, intelligence processing; (2}a large number of non-structural. non-adaptive function of the accuracy of the law; (3)with the information memory, self-learning, knowledge, reasoningand optimization of computing features. The disadvantage is that:(1) the determination of the initial value can not take advantage of existing system information, easily trapped in local minimum of the state; (2) neural network learning process is usually slow, poor adaptability to sudden events.2.10 Optimum Combination Forecasting MethodOptimal combination has two meanings: First, several forecasting methods from the results obtained by selecting the appropriate a0cight in the weighted average; 2 refers to the comparison of several prediction methods, choose the best or the degree of preparation and the standard deviation of the smallest prediction model forecast. For the combined forecasting method must also noted that the combined forecast is a single forecasting model can not completely correct to describe the changes of the amount predicted to play a role. One can fully reflect the actual law of development of the model predictions agree well with the combination forecasting method than predictedgood results. This method has the advantage: To optimize the combination of a wide range of information on a single prediction model, consider the impact of information is also mart comprehensive, so it can effectively improve the prediction. The disadvantage is that: (1) the weight is difficult to determine; (2) all possible factors that play a role in the future, all included in the model, to a certain extent, limit the prediction accuracy improved.2.11 Wavelet analysis and forecasting techniquesWavelet analysis is a time-domain-frequency domain analysis method, it is in the time domain and frequency domain at the same time has good localization properties, and can automatically adjust according to the signal sampling frequency of high and low density, it is cast' to capture and analysis of weak signals and signal, images of any small parts. The advantage is: Can the different frequency components gradually refined using a sampling step, which can be gathered in any of the details of the signal, especially for singular signal is very sensitive tothe treatment well or mutation weak signals, their goal is to a signal information into wavelet coefficients, which can easily be dealt with, storage, transmission, analysis or for the reconstruction of the original signal. These advantages determine the wavelet analyses can be effectively applied to load forecasting issues.3. ConclusionLoad forecasting is the electric power system scheduling, real-time control, operation plan and development planning, the premise is a grid dispatching departments and planning departments must have the basic information. Improve load forecasting technology level, be helpful for program management, reasonable arrangement of the electricity grid operation mode for the maintenance plan and the crew, to section coal, fuel-efficient and reduce generating cost, be helpful for formulate rational power construction planning of the power system, improve the economic benefit andsocial benefit. Therefore, the load forecast has become a power system management modernization realization of the important content.电力系统负荷预测及方法摘要：负荷预测在电力系统规划和运行方面发挥的重要作用，具有明显的经济效益，负荷预测实质上是对电力市场需求的预测。