Short-term photovoltaic power prediction method based on VMD-IPSO-GRU

A power prediction and photovoltaic technology, applied in prediction, ICT adaptation, biological neural network model, etc., can solve problems such as inability to fully exploit geographic information photovoltaic module installation parameters

Pending Publication Date: 2021-02-09
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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Problems solved by technology

[0008] Since photovoltaic power is affected by many factors, the above method mainly performs simple fitting of meteorological factors and historical photovoltaic power dat...

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  • Short-term photovoltaic power prediction method based on VMD-IPSO-GRU

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Embodiment Construction

[0073] The present invention proposes a short-term photovoltaic power prediction method based on VMD-IPSO-GRU. The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0074] First of all, because the photovoltaic power time series is affected by many factors, the process of photovoltaic power generation is random and unstable, which brings huge impact and challenges to the safe operation of the power system. The invention decomposes the historical photovoltaic power time series into subsequences of different frequencies through variational mode decomposition (VMD), fully excavates the geographic information and component parameters contained in the photovoltaic sequence data, separates the signal and noise of the original data, and reduces nonlinearity The complexity and non-stationarity of the strong time series improve the accuracy of short-term photovoltaic power forecasting.

[0075] Secondly, when per...

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Abstract

The invention discloses a short-term photovoltaic power prediction method based on VMD-IPSO-GRU, and belongs to the technical field of photovoltaic power generation and grid connection. Firstly, a historical photovoltaic power time sequence is decomposed into sub-sequences with different frequencies through variational mode decomposition, geographic information and component parameters contained in photovoltaic sequence data are fully mined, and signals and noise of original data are separated; secondly, main meteorological factors influencing photovoltaic output are determined through Spearman and Pearson correlation coefficients; and finally, gating cycle unit network models are established for the sub-sequences decomposed by the VMD respectively, and the GRU nerve is optimized through an improved particle swarm algorithm and an adaptive moment estimation algorithm, thereby improving the network convergence rate and the data fitting effect, accurately and efficiently finishing short-term photovoltaic power prediction, and avoiding errors caused by manual parameter adjustment.

Description

technical field [0001] The invention relates to the technical field of photovoltaic power generation and grid connection, in particular to a short-term photovoltaic power prediction method based on VMD-IPSO-GRU. Background technique [0002] With the rapid development of the global new energy power generation industry, solar energy is widely used due to its unique advantages of safety, efficiency and wide distribution, and the total installed capacity of photovoltaics in the world is increasing year by year. The process of photovoltaic power generation is random and unstable, and is easily affected by factors such as the environment and weather, which brings huge impact and challenges to the safe operation of the power system. Accurate short-term photovoltaic power forecasting can not only improve the operational efficiency of photovoltaic power plants, but also help dispatching departments to formulate efficient and intelligent real-time dispatch plans, while ensuring safe ...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06N3/04G06N3/00G06K9/62
CPCG06Q10/04G06Q50/06G06N3/006G06N3/045G06F18/214Y02A90/10
Inventor 张海波贾鹏云
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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