Study And Realization Of The Medium And Long Term Load Forecasting Methods In Distribution Network

Load forecasting is an important research content of power system planning and running, and is a premise for reliable supplying and economic running, and also is the basis of power system planning and construction. Exact degree of load forecasting shall directly affect rationality of investment, network layout and running.Because the medium and long term load forecasting in distribution network is affected by many uncertain factors, up to now, no methods can obtain the satisfying forecasting results at all instances. So at the time of practical forecasting, choosing many forecasting methods according to the actual instance, and checking forecasting results of different method, finally forecasting results are confirmed.This thesis firstly gives a summarization for load gross and distribution forecasting. Then a thorough research into grey forecasting method and combined forecasting method in load gross forecasting is carried through. And the classified-divisional load density method in load distribution forecasting is applied to project, at the same time a discussion on correlative content of emulation method is gone along. Finally each method is realized with computer program, and practical software for load forecasting in distribution network is developed.Load gross forecasting belongs to stratagem forecasting. It makes the electric power or load of the whole planning region as forecasting object. Its results decide the urban demand for electric power and the supplying capacity of urban distribution network in the future. The results of load gross forecasting have important guidance significance for ascertaining the location of power supply and generating planning. It is the important basis of distribution network planning.Through the research into modeling mechanism of grey forecasting method, the shortages of grey mechanism are found and some improved measures are put forward. Through the pretreatment and optimization to historical load data, the ability of grey forecasting dealing with fluctuant load data is strengthened, and the application range and forecasting precision are also enhanced. By using equally dimensional, new information's grey model for forecasting, new information is used in the forecasting, which not only overcomes the shortcoming that the math model is changeless in simplegrey forecasting method; but also makes use of the advantage of the high precision in-m-short term grey forecasting. So it satisfies the request for the medium and long term load forecasting. By improving, the applicable range of the common grey model is extended, and the precision of the common grey model is enhanced. The improved model is compared with the common grey model by calculation example, which shows that the improved model has the advantages of small error and high precision. The calculation example proves that the improved grey model is a good forecasting method.Aiming at the shortage of usually adopting linear combination based upon proportion for single forecasting model in combined forecasting model, namely requiring forecasting models errors that take part in combined forecasting to keep stabilization, but the forecasting results errors are not usually well-proportioned in power load forecasting. The combined forecasting model based upon artificial neural network is presented, which makes use of the shaping of artificial neural network for complicated non-linear system, automatically adjusts the proportion for forecasting models by network training. At the same time, to escape the disadvantages that the combined forecasting model based upon artificial neural network is established using conventional language, such as complicated in structure, longer in training. Establishing combined forecasting model using artificial neural network on the basis of MATLAB toolbox. This model is not only simpler in programming, but also quicker in convergence. The calculation example shows that this method can greatly improve forecasting precision, has extensive application perspective in power...