Load prediction method based on industry-classified power utilization characteristic analysis

Abstract

The invention discloses a load prediction method based on industry-classified power utilization characteristic analysis, and the method comprises the following steps: S1, dividing power users into industry power utilization users and resident power utilization users, dividing the resident power utilization users into residence community users and small-capacity public transformers; S2, identifyingsaturated users and unsaturated users in industrial power utilization users and residential district users by using a load saturation identification technology; S3, taking the average load value of the saturated users as a future prediction value in recent three years; carrying out typical growth pattern analysis on unsaturated users and installation users; S4, summarizing and counting the natural growth rate of the small-capacity public transformer; S5, calculating the coincidence rate in the industry and the coincidence rate between the industries respectively; and S6, summarizing all typesof loads to obtain a whole-region load prediction result. Classification prediction is carried out on the basis of power utilization growth characteristic analysis of mass user load data, and then the simultaneous rates of all levels are applied to summarize and calculate the total load prediction result of the area.

Description

technical field [0001] The invention relates to the field of electric load characteristics research, in particular to a load forecasting method based on the analysis of industry-specific power consumption characteristics. Background technique [0002] Power quantity forecasting is related to power system dispatching and operation, production and operation plan formulation, and grid planning. Accurate power quantity forecasting results can avoid grid risks and help improve system security, stability, and grid investment benefits. At present, there are three main categories of short-term power load forecasting methods for power supply enterprises: [0003] 1) Trend extrapolation method. It is mainly based on regression analysis, exponential smoothing and other models, using time and electric power as parameters to fit the model, and calculating the model value according to the time development as the future forecast value; [0004] 2) A prediction method based on the interna...

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Problems solved by technology

[0006] The first type of method involves few variables and few data points, but the data has hysteresis and relies more on the prediction model itself; the second type of method relies on general experience for the prediction of power economic correlation indicators, which cannot well meet the needs of cities. Specific development reality; the third type of method, the traditional load characteristics do not match the rich information of existing users, and the accuracy can no longer meet the actual increasingly refined work requirements

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