Load curve decomposition based load modeling method for commercial load and resident load

Abstract

The invention provides a load curve decomposition based load modeling method for a commercial load and a resident load. The method comprises the following steps: decomposing a load curve, calculating the proportion of each load in total quantity, and calculating a static load equivalent parameter, a dynamic load equivalent parameter and power distribution network system impedance. The invention provides the load curve decomposition based load modeling method for the commercial load and the resident load. The method overcomes the defects of a traditional statistics comprehensive method and can help to rapidly, conveniently and accurately model for a resident load station, by adopting a load model generated according to the method provided by the invention, the accuracy of simulating calculation of a power grid is increased, and the safe, reliable and economical operation of the power grid is guaranteed.

Description

technical field [0001] The invention relates to a modeling method, in particular to a load modeling method for commercial and residential load types based on load curve decomposition. Background technique [0002] Power system digital simulation has become the main tool for power system planning and design, dispatching operation and analysis research. The mathematical model of each component of the power system and the mathematical model of the whole system constituted by it are the basis of power system digital simulation. The accuracy of the model is directly related to Influence simulation results and decision-making schemes based on them. The model and parameters used in the simulation are important determinants of the accuracy of the simulation. At present, the detailed mathematical models and modeling techniques of generators, excitation systems, speed control systems, transformers, and transmission lines have been well developed. The electric load model is still rela...

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Problems solved by technology

[0006] (2) As time goes by, the actual load power, load composition, and network structure may change. If you want to do it once and for all after conducting a survey and statistical modeling work on the load, it is difficult to meet the accuracy requirements;

[0007] (3) The survey work needs to count the load composition and parameters of thousands of users, the workload is huge, and it is difficult to obtain accurate statistical results

[0013] (3) The daily load varies greatly with time

From all the load curves, the smaller the load, the more likely the above problems will occur, and the worse the change regularity of the curve

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