A method for predict photovoltaic probability

A probabilistic forecasting and photovoltaic technology, applied in forecasting, data processing applications, instruments, etc., can solve problems such as the difficulty of predicting the photovoltaic output of photovoltaic power station systems

Active Publication Date: 2019-02-22
HUAZHONG UNIV OF SCI & TECH +3
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Problems solved by technology

[0003] In view of the defects of the prior art, the purpose of the present invention is to provide a photovoltaic power probability prediction method, which ai

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  • A method for predict photovoltaic probability
  • A method for predict photovoltaic probability
  • A method for predict photovoltaic probability

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[0087] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0088] In order to solve the problem that the photovoltaic output is difficult to predict due to the randomness of the output of the photovoltaic power station system, the present invention provides a method for predicting the probability of photovoltaic power. The specific method flow is as follows figure 1 shown, including the following steps:

[0089] Step 1: Collect historical data of photovoltaic power plants and decompose the sequence of photovoltaic output

[0090] The collected historical data of the photovoltaic power station includes: the historical output data of the same photovoltaic p...

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Abstract

The invention discloses a photovoltaic probability prediction method, which comprises the following steps: (1) collecting historical data of a photovoltaic power station and performing sequence decomposition on the historical output data; (2) randomly generating input layer-Hidden layer weight and offset; (3) Setting the expected coverage rate of probability prediction interval; (4) Training the network to determine the hidden layer Weights of the output layer; (5) inputting data to obtain output prediction interval. As that historical output of the photovoltaic power station is taken as a model input, the invention solves the influence of the randomness of the mount position of the photovoltaic array and the use time of the photovoltaic array on the conversion efficiency, and improves theprediction accuracy; Decomposition of historical data can more effectively distinguish the influence of different factors on output and enhance the characteristics of data. Introducing the idea of limit learning machine ELM, the training speed is greatly improved while the precision is guaranteed; Quantile regression is used to predict the probability of photovoltaic output interval, which has astronger reference value for the formulation of dispatch plan.

Description

technical field [0001] The invention belongs to the technical field of electrical engineering, and more specifically relates to a photovoltaic probability prediction method. Background technique [0002] With the global energy shortage and environmental protection issues becoming more and more prominent, the utilization of renewable energy has attracted extensive attention. As an important form of renewable energy, photovoltaic power generation is one of the power generation methods with the most large-scale development conditions and commercial development prospects in renewable energy. At present, large-scale photovoltaic power generation systems have been built in large numbers at home and abroad. However, since the output of the photovoltaic power generation system is affected by the intensity of solar radiation and weather factors, the change of its power generation is a non-stationary random process. At the same time, due to the diurnal periodicity of sunlight, photov...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06N3/04
CPCG06Q10/04G06Q50/06G06N3/045
Inventor 文劲宇李明杨艾小猛姚伟盛万兴马骏钮彬
Owner HUAZHONG UNIV OF SCI & TECH
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