Method for short-term load forecasting of comprehensive subnet accumulation based on forecasting credibility evaluation

Abstract

The invention discloses a method for short-term load forecasting of comprehensive subnet accumulation based on forecasting credibility evaluation. The method includes the steps of historical forecasting error statistics and analysis, time-phased error credibility rating and load forecasting performed by adopting a city comprehensive subnet accumulation method according to the rating. In the method, various city load forecasting results are fully utilized, so that characteristic change rules of load compositions in different regions of a power grid are beneficially grasped by scheduling departments in a deep and refined manner, level-to-level management of the load forecasting is enhanced, and scientization and refinement level of the load forecasting is fully improved.

Description

technical field [0001] The invention relates to the technical field of short-term load forecasting of power systems, in particular to a short-term load forecasting method based on integrated sub-network accumulation based on forecast credibility evaluation. Background technique [0002] The existing load forecasting of large power grids is based on the regular extrapolation of the total load of its own, which generally has the following shortcomings: [0003] 1. The power supply area is large, the load structure is complex, and there are many factors affecting the size and distribution of the load, and it is impossible to consider all the influencing factors one by one; [0004] 2. The large power grid is composed of multiple prefecture-level or district-level subnets, and each subnet has different load characteristics, so it is difficult to count the overall load information of the large power grid; [0005] 3. The sub-networks that make up the large power grid are distrib...

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Problems solved by technology

[0003] 1. The power supply area is large, the load structure is complex, and there are many factors affecting the size and distribution of the load, and it is impossible to consider all the influencing factors one by one;

[0004] 2. The large power grid is composed of multiple prefecture-level or district-level subnets, and each subnet has different load characteristics, so it is difficult to count the overall load information of the large power grid;

[0005] 3. The sub-networks that make up the large power grid are distributed in a wide area, with large weather differences, and the weather forecast of the meteorological station is only for small areas. Therefore, it is impossible to unify the overall weather conditions of a large area or obtain the weather forecast of a large area in advance

[0011] We know that when carrying out load forecasting, we must fully understand the factors that affect the load structure and load size, grasp the proportion of residential load, commercial load and industrial load in the total load, and the distribution of the three loads in time. Forecasting is very critical, and based on the characteristics of the first two large power grids above, we can see that due to the large power supply area, it is difficult for large power grids to obtain accurate information in this regard, which has caused certain difficulties for load forecasting

In addition, in summer or other special periods with large fluctuations in weather conditions, meteorological information plays a vital role in short-term load forecasting. Therefore, it can be seen from the third feature that due to the difficulty of obtaining weather conditions, the short-term The accuracy of load forecasting is difficult to maintain a high level

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