Microgrid short-term load prediction method based on long-term and short-term memory and self-adaptive improvement

Abstract

The invention relates to the technical field of power system scheduling and operation, in particular to a micro-grid short-term load prediction method based on long-term and short-term memory and self-adaptive lifting, which comprises the following steps: step 1, calling historical load data; step 2, integrating the data to obtain a training set and a test set; step 3, performing integrated empirical mode decomposition and adjustment on the training set and the test set, and outputting a training sample set and a test sample set; 4, establishing a combined prediction kernel model, and settinghyper-parameter values; 5, inputting the training sample set, and outputting a prediction result; 6, setting the cycle index N, and entering the step 7 when the actual cycle index is greater than N; if the actual cycle index is smaller than N, entering the step 5; 7, calculating a root-mean-square error, judging whether the root-mean-square error is stable or not, entering the step 9 if the root-mean-square error is stable, and entering the step 8 if not ; 8, adjusting hyper-parameters, and entering the step 5; and step 9, inputting the test sample set, and outputting a prediction result. Themethod is high in prediction precision, small in error, high in adaptability and high in practicability.

Description

technical field [0001] The invention relates to the technical field of power system dispatching and operation, in particular to a short-term load forecasting method for micro-grids based on long-short-term memory and self-adaptive upgrading. Background technique [0002] As a new network structure, microgrid is a group of system units composed of micro power sources, loads, energy storage systems and control devices. Compared with the traditional large power grid, the microgrid is a beneficial supplement, that is, a network structure is formed by multiple distributed power sources and their related loads according to a certain topology, and connected to the conventional power grid through static switches. During the monitoring and operation of the microgrid, if the load change value of the microgrid can be predicted reasonably and accurately, the start-up and shutdown plan and power generation plan of the microgrid can be arranged according to the change, so as to complete t...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the technical problem of low forecasting accuracy due to the high randomness of microgrid load changes, the embodiment of the present invention provides a short-term load forecasting method for microgrids based on long short-term memory and self-adaptive improvement, the

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