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Heat accumulation electric boiler and clean energy prediction matching and consumption control method

A technology of clean energy and control methods, applied in prediction, neural learning methods, genetic rules, etc., can solve problems such as inflexible consumption methods, insufficient consumption capacity, and low consumption efficiency

Active Publication Date: 2017-10-17
STATE GRID CORP OF CHINA +1
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Problems solved by technology

[0006] In view of the above existing problems, the present invention proposes a distributed heat storage electric boiler consumption clean energy system based on the fuzzy Bayesian neural network prediction model, which is to solve the existing inflexible consumption methods, low consumption efficiency and low consumption capacity. Insufficient problem

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  • Heat accumulation electric boiler and clean energy prediction matching and consumption control method
  • Heat accumulation electric boiler and clean energy prediction matching and consumption control method
  • Heat accumulation electric boiler and clean energy prediction matching and consumption control method

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Embodiment Construction

[0070] The specific embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0071] Based on the fuzzy Bayesian neural network prediction model, the distributed thermal storage electric boiler absorbs clean energy control method and device, such as figure 1 shown

[0072] Step 1, collect sample data

[0073] The forecast of photovoltaic power plant curtailment includes two types of parameters: meteorological factors and photovoltaic power plant curtailment data; in order to improve the accuracy of forecasting photovoltaic power plant curtailment under different meteorological factors, meteorological factors and photovoltaic power plant curtailment include sunny and cloudy days. There are 365 sets of data in one year of days, cloudy and rainy (snow) days; the sample data is divided into training sample data and test sample data, which are sample pairs composed of sample input and expected output;

[0074] In order...

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Abstract

The invention discloses a heat accumulation electric boiler and clean energy prediction matching and consumption control method, and the method comprises the steps: collecting weather factor data and photovoltaic energy curtailment data, and obtaining a training sample set through normalization processing; 2, designing a fuzzy Bayesian neural network model comprising an input layer, a hidden layer and an output layer, and selecting an excitation function, a training function, and a learning function; 3, applying the obtained optimal network prediction model in a distributed photovoltaic power generation system, so as to obtain the photovoltaic energy curtailment quantity of a photovoltaic power station under the different weather factor conditions; 4, giving consideration to an economic performance index under the condition that the photovoltaic energy curtailment quantity of the photovoltaic power station is predicted, and enabling a distributed heat accumulation electric boiler to extremely consume the photovoltaic energy curtailment quantity through the reference of the predicted photovoltaic energy curtailment quantity and an index which enables the combined operation benefit of the photovoltaic power station and the heat accumulation electric boiler and environment benefit. The method solves problems that a conventional consumption mode is not flexible, is low in consumption efficiency, and is not sufficient in consumption capability.

Description

technical field [0001] The present invention relates to the field of new energy consumption, and specifically adopts a distributed thermal storage electric boiler system to accommodate new energy. Background technique [0002] my country is rich in solar energy resources. In addition to meeting the power generation needs of photovoltaic power plants, it is also facing a large number of solar abandonment problems. The consumption of new energy is conducive to energy saving of the power grid, improving economic benefits and promoting the long-term development of power companies. [0003] Due to the uncertainty of meteorological environment information, geographical conditions, astronomical and other factors, the output of solar photovoltaic power generation system is a random variable with non-stationary, instant change and dynamic characteristics, which has strong volatility, weak anti-interference ability, intermittent and Uncontrollable distributed energy resources with pe...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06N3/04G06N3/08G06N3/12
CPCG06N3/08G06N3/126G06Q10/04G06Q50/06G06N3/043G06N3/048Y02W30/82
Inventor 赵庆杞杨东升温锦刘鑫蕊李大爽徐斌杨宝渠庞永恒秦佳
Owner STATE GRID CORP OF CHINA
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