Photovoltaic power generation power prediction method based on parallel computation

A technology of photovoltaic power generation and prediction method, which is applied in the field of wind power generation, can solve problems such as large amount of data, and achieve the effects of improving operation efficiency, improving calculation efficiency and speed, and high accuracy

Active Publication Date: 2018-11-06
SHANGHAI UNIVERSITY OF ELECTRIC POWER
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Problems solved by technology

In the process of using the multi-point geostatistical method, the probability information of the training image is copied to the area to be predicted,

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  • Photovoltaic power generation power prediction method based on parallel computation
  • Photovoltaic power generation power prediction method based on parallel computation
  • Photovoltaic power generation power prediction method based on parallel computation

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[0043] The present invention will be described in detail below with reference to the drawings and specific embodiments. This embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation mode and specific operation process are given, but the protection scope of the present invention is not limited to the following embodiments.

[0044] This embodiment proposes a method for predicting photovoltaic power generation based on parallel operation, including the following steps:

[0045] The 3D pattern library training step is to construct and store training images on the host side according to the photovoltaic power generation environment data, and build a 3D pattern library by processing the data events of the training images in parallel on the client side;

[0046] Photovoltaic power prediction step is to establish a photovoltaic power generation prediction area on the host side, use the three-dimensional pattern library to tra...

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Abstract

The invention relates to a photovoltaic power generation power prediction method based on parallel computation. The method comprises the following steps: the three-dimensional mode library training step: a training image is constructed on the host side and stored according to the photovoltaic power generation environmental data, the data event of the training image is captured and a three-dimensional mode library is established on the client side through parallel processing; and the photovoltaic power generation power prediction step: a photovoltaic power generation prediction area is established on the host side, the unknown nodes in the wind power prediction area are traversed by using the three-dimensional mode library and the prediction result of the photovoltaic power generation poweris obtained on the client side through parallel computation. Compared with the methods in the prior art, the prediction method has the advantages of high prediction accuracy and low computational burden and high prediction speed and can be widely applied to the field of photovoltaic power generation.

Description

technical field [0001] The invention relates to the field of wind power generation, in particular to a method for predicting photovoltaic power generation based on parallel computing. Background technique [0002] Renewable energy may gradually replace fossil energy and become an energy source for sustainable development of mankind. Among them, solar energy is the energy source with the largest amount of resources and the most widespread distribution among renewable energy sources. Photovoltaic power generation is an effective way to utilize solar energy, but the output power of photovoltaic power generation system has the characteristics of discontinuity and uncertainty. There are many factors that affect the power of photovoltaic power generation, among which meteorological factors are the biggest factor affecting the power of photovoltaic power generation. Since the intensity of solar radiation is closely related to factors such as season, geographical location, atmosph...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06K9/62H02J3/38
CPCH02J3/383G06Q10/04G06Q50/06G06F18/22Y02E10/56Y02E10/76
Inventor 张挺
Owner SHANGHAI UNIVERSITY OF ELECTRIC POWER
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