Photovoltaic power generation power prediction method based on multi-cluster ESN (Echo State Networks) neural network
A technology of photovoltaic power generation and neural network, which is applied in the field of photovoltaic power generation power prediction based on multi-cluster ESN neural network, can solve the problems of cumbersome training process and no qualitative analysis of prediction results, and achieves high prediction accuracy, fast training speed and good performance. performance effect
Active Publication Date: 2018-10-26
CHONGQING UNIV
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However, they have shortcomings such as cumbersome training process, and there is no qualitative analysis of the prediction results
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[0049] The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings; it should be understood that the preferred embodiments are only for illustrating the present invention, rather than limiting the protection scope of the present invention.
[0050] figure 1It is an overall flowchart of a photovoltaic power prediction method based on multi-cluster ESN neural network, which includes three parts. The difference between the predicted results and the measured results is evaluated; figure 2 Flowchart of the generation process for multi-cluster structures; image 3 It is a multi-cluster ESN neural network structure, where the network includes an input layer, a reserve layer and an output layer; Figure 4 For the different input-output model diagrams of the 1-hour short-term forecast model, a multi-cluster ESN neural network forecast model considering the temperature and humidity measurements and the periodic ch...
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The invention discloses a photovoltaic power generation power prediction method based on a multi-cluster ESN (Echo State Networks) neural network, and belongs to the field of photovoltaic power generation. The method comprises the following steps that: firstly, constructing a multi-cluster ESN neural network, and adopting an improved ESN, i.e., the multi-cluster ESN; secondly, establishing a multi-cluster ESN neural network prediction model, adding corresponding historical 24-step lagging information in an input layer when the prediction model is established, and analyzing the influence of the24-step lagging information on the accuracy of the prediction model; and finally, evaluating the prediction performance of the multi-cluster ESN neural network. A prediction result is independently subjected to quantitative analysis and qualitative analysis for guaranteeing the reliable and efficient operation of a photovoltaic power generation system and the safe dispatching of a power grid.
Description
technical field [0001] The invention relates to the technical field of photovoltaic power generation system power forecasting, in particular to a photovoltaic power generation power forecasting method based on a multi-cluster ESN neural network. Background technique [0002] In recent years, with the increase of global energy demand, renewable energy sources (such as wind energy and solar energy) have received extensive attention, among which solar energy has the advantages of being renewable, non-polluting, safe and reliable. Due to its easy availability, government support and continuous development of technology, large-scale photovoltaic (Photovoltaic, PV) systems have been widely used all over the world. However, the power generation of photovoltaic systems is affected by many uncontrollable factors, such as temperature, humidity, wind speed, wind direction, solar radiation intensity, seasonality, etc., which make the power generation of photovoltaic systems highly nonli...
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IPC IPC(8): G06Q10/04G06Q50/06G06N3/04
CPCG06Q10/04G06Q50/06G06N3/044Y04S10/50Y02E40/70
Inventor 伍洲黎倩毛明轩
Owner CHONGQING UNIV