The Research Of The Relationship Between Bus Load Forecasting And System Load Forecasting

As two branches of power system load forecasting, bus load forecasting and system load forecasting are closely related yet distinct. Dealing with the relationship between bus load forecasting of Hunan Power220KV and its locally administered level system load forecasting, this thesis fills the blank on the research of the relationship of the two.Bus load forecasting can adopt the method of system load forecasting. However, if bus load forecasting is affected by factors such as bus load power, load transfer, traditional direct predication method would fail because of its large fluctuation and less regularity. Indirect bus load forecasting method is proposed in this thesis. First net supply load is changed into ideal electrical load in supply area, then ideal electrical load is taken as historical load and by utilizing system load algorithm to forecast, primary prediction result is obtained. Then the values of impact factors of that day are obtained and separated from the primary prediction result and the net bus forecasting load is indirectly obtained. Case is given to demonstrate that compared with direct forecasting method which takes net bus supply load as historical load, this method can raise the accuracy rate of the bus load forecasting with the small powers or load transfer in supply area.Bus load forecasting is the refinement of system load forecasting. Although the sum of buses load forecasting can be dealt with the predictive value of system load forecasting, the predictive results is far less accurate than that of the system load forecasting because of the low accuracy of the bus load forecasting and the sum of the error. This paper presents a bus load forecasting revision method based on load forecasting. The value difference between the bus load forecasting and load forecasting would determine the necessity of the revision. The expected value and variance of the bus load forecasting in this time period of the similar days will tell the range of the revised bus load forecasting. Using the least square approximation, LINGO is applied to solve the linear programming problem. The example demonstrates that the method can raise accuracy rate of the bus load forecasting.The research on the relationship between bus load forecasting and system forecasting will improve the accuracy of the two load forecasting, reduce standby power as well as energy consumption, while promote security and stability of the grid, providing new method to power system load forecasting.