Recent region load predicting method based on S-type curve

Abstract

The invention discloses a recent region load predicting method based on an S-type curve. The method includes the steps that business expansion data are collected and arranged; a business expansion capacity conversion coefficient is calculated; a business expansion development curve is drawn and corrected; a target annual newly increased load is calculated, and a predication result is adjusted. According to the recent region load predicting method based on the S-type curve, the defect that a traditional macro method can not be suitable for specific region planning can be overcome, in combination with region economic development conditions, the S-type growth curve theory is applied to business expansion engineering consulting of a power enterprise, the rule that the reported installation increased capacity is gradually converted into the actual load within the next years is searched for, which is beneficial to improving the precision of local region load prediction, and more detailed and accurate reference bases can be provided for power distribution system optimizing and planning.

Description

technical field [0001] The invention belongs to the technical field of urban distribution network planning and optimization, in particular to an S-shaped curve-based regional load forecasting method in the near term. Background technique [0002] In the basic theory of the S-shaped growth curve, special points such as the saturation value and inflection point of the curve characteristics have been used in urban planning. There are also relevant literature and data support for the theory that the urban load development conforms to the S-shaped growth curve. [0003] At present, the existing load forecasting methods can be divided into three categories, one is the classic forecasting method, including the unit consumption method, the proportional coefficient growth method, etc.; the other is the traditional forecasting method, such as the trend extrapolation method and the regression model forecasting method; Prediction methods, such as intelligent algorithms such as artificia...

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Problems solved by technology

The above method is more effective for mid- and long-term load forecasting of distribution networks. However, since regional distribution network planning often involves the development of a region or users in the past one or two years, its load characteristics are not consistent with the business expansion of local users in recent years. Content is closely related to development and utilization, so the above-mentioned macro-methods have certain limitations in solving such problems

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