Intelligent prediction method for power generation power of distributed power supply

A technology of distributed power and power generation, applied in forecasting, data processing applications, character and pattern recognition, etc., can solve problems such as forecast error errors, and achieve the effect of improving forecast accuracy and global search capabilities.

Pending Publication Date: 2019-07-02
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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Problems solved by technology

The research of photovoltaic power generation is dedicated to the optimization of distribution network and reliability evaluation. The prediction of distributed...

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  • Intelligent prediction method for power generation power of distributed power supply
  • Intelligent prediction method for power generation power of distributed power supply
  • Intelligent prediction method for power generation power of distributed power supply

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Embodiment Construction

[0030] The embodiments will be described in detail below in conjunction with the accompanying drawings.

[0031] On the basis of considering many meteorological factors such as temperature, humidity, light intensity, and light time, the present invention proposes an intelligent prediction method for distributed power generation power, including:

[0032] Step 1: Sample data preprocessing.

[0033] Collect sample data including historical daily wind speed, wind direction, etc., and then normalize the meteorological factors of the data. The formula is as follows:

[0034]

[0035] After normalization, the value of each variable is between [0,1], eliminating the influence of dimension.

[0036] Step 2: Optimizing by fruit fly optimization algorithm.

[0037] On the basis of preprocessing the sample data, the model training data and test data are separated, the fruit fly algorithm is introduced, the parameters of the fruit fly algorithm are initialized, and the fruit fly algo...

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Abstract

The invention belongs to the technical field of power load prediction, and particularly relates to an intelligent prediction method for power generation power of a distributed power supply, which comprises the following steps of: 1, acquiring meteorological sample data including historical daily wind speed and wind direction, and performing normalization processing; 2, dividing the sample data into model training data and inspection data, and performing iterative optimization by using a fruit fly algorithm; step 3, introducing an immune algorithm to optimize parameters of the fruit fly algorithm; 4, using an immune-Drosophila optimization algorithm optimized by immune algorithm to optimize a support vector machine, and establishing an optimized support vector machine prediction model; and5, verifying the effectiveness of the support vector machine prediction model, and obtaining a final prediction result. Through optimization of the immune algorithm, the problem that the fruit fly algorithm is trapped in local optimum is avoided, the global search capability of the algorithm is effectively improved, and the SVM regression prediction precision of the model is improved.

Description

technical field [0001] The invention belongs to the technical field of electric load forecasting, and in particular relates to an intelligent forecasting method for distributed power generation power. Background technique [0002] Distributed power generation refers to the use of various available and dispersed energy sources, including renewable energy sources (solar energy, biomass energy, small wind energy, small hydropower, etc.) and locally accessible fossil fuels (mainly natural gas) for power generation. functional technology. It has increasingly become an important supplement to the power grid due to its advantages such as flexible power generation, high energy utilization rate, and low environmental pollution. It has developed rapidly at home and abroad in recent years. Among them, distributed photovoltaic power generation refers to a distributed power generation system that uses photovoltaic modules to directly convert solar energy into electrical energy. It is m...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06K9/62
CPCG06Q10/04G06Q50/06G06F18/2411
Inventor 许晓敏袁程浩王珂珂李偲
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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