Method and system for predicting maximum electrical load of electric heating distribution transformer

Abstract

The invention provides a method and system for predicting the maximum electrical load of an electric heating distribution transformer, belongs to the technical field of electrical load prediction. Themethod comprises steps of calculating the daily electricity consumption of all electric equipment according to the types and the number of the electric equipment of a user in combination with the performance parameters of the electric equipment. according to the daily power consumption and the use state of the electric equipment, simulating a random number of starting the electric equipment by using a Monte Carlo algorithm; taking the peak electricity quantity / valley electricity quantity of the daily electricity consumption as a constraint condition, combining a random number, and performingdaily load curve optimization by using a differential evolution algorithm; and performing superposition calculation according to the optimized daily load curves of all the users to obtain the maximumelectrical load of the electric heating distribution transformer. The method improves the load prediction accuracy of the electric heating distribution transformer in the research stage, reduces the calculation amount, improves the planning work quality of the power distribution network, reduces the number of light loads and heavy loads of the electric heating distribution transformer, can accurately reflect the actual condition and planning condition of the medium-low voltage power distribution network, and facilitates the construction and safe operation of the power grid.

Description

Technical field[0001]The present invention relates to the field of electricity load prediction technique, and more particularly to the maximum electricity load prediction method and system for electropically controlled by Monte Carlo simulation-differential evolution algorithm.Background technique[0002]Electricity-controlled change new projects typically select a certain capacity of the transformer according to the load forecast results, and the actual change in the change in the project is 20% -80% after the project is completed. Therefore, the maximum load prediction is safe value and economic value in the research phase.[0003]At this stage, the implementation of cleaning electric heating has contributed to the renovation and new construction of the supporting grid, and an important part of the discharging project is the capacity selection of the distribution transformer. In the selection design phase, the required planned load nominal capacity is greater than the calculated load ...

AI Technical Summary

Problems solved by technology

In the feasibility study design stage, the planned load nominal capacity is required to be larger than the calculated load transformer. This regulation is based on power supply reliability factors. Although it meets the technical requirements, it lacks economic considerations. If the transformer capacity is selected too large, it will cause transformer failure. Light load not only increases system loss and operating costs, but also affects the planning of the upper-level power grid and increases the cost of power grid construction

If the transformer capacity is too small, it will cause the transformer to be overloaded or even overloaded.

[0004] The calculation method of conventional demand forecasting based on load simultaneous rate is simple, and the simultaneous rate calculation method does not accurately consider the randomness of load, and does not specifically analyze the actual situation of power consumption of distribution transformer users. The accuracy of load forecasting based on this method is not high.

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