Hybrid Model-Based Method for Predicting Power Generation of Photovoltaic Cells in Short Time Scale
A hybrid model and photovoltaic cell technology, applied in the direction of forecasting, data processing applications, system integration technology, etc., can solve the problem of not paying attention to the data characteristics of photovoltaic cell power generation, limiting the efficiency and reliability of microgrid energy management, and the prediction effect is not good Ideal and other issues, to achieve safe and reliable energy management, improve prediction accuracy, and accurate prediction models
Active Publication Date: 2022-04-01
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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However, the existing methods do not pay attention to the data characteristics of photovoltaic cell power generation in short time scales, so the prediction effect is not very ideal, and cannot meet the needs of existing energy management, which greatly limits the efficiency and reliability of microgrid energy management. sex
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[0019] Such as Figure 1 to Figure 3 As shown, the present invention provides a hybrid model-based short-time scale photovoltaic cell power generation prediction method, and its technical solution will be described in detail below in conjunction with specific embodiments.
[0020] First of all, the method of the present invention is based on statistical methods and machine learning methods, so a huge amount of meteorological data sets at different times of the same forecast location are required And the corresponding photovoltaic power generation data set [Y(t)]. We divide these data into two parts, one part is training data, and the other part is evaluation data, and both parts must be guaranteed to contain a large amount of data.
[0021] In order for the data to fit our predictive model, all the data is first preprocessed. Meteorological data is preprocessed as In the form of , the photovoltaic power generation data is preprocessed into the variation of photovoltaic po...
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The invention discloses a hybrid model-based short-time-scale photovoltaic cell power generation prediction method, which includes the following steps: step 1, constructing a hybrid prediction model according to data characteristics; step 2, solving the linear regression coefficient and nonlinearity under each weather type Function; step 3, obtain the required forecast t according to the weather station data 0 The meteorological variable data at the moment and the meteorological variable data at the previous moment and the photovoltaic cell power generation Y(t 0 -δ t ), get the corresponding linear regression coefficient and nonlinear function according to its weather type, and substitute it into the mixed model to calculate the prediction result. This method can significantly improve the prediction accuracy and improve the energy management efficiency of the microgrid.
Description
technical field [0001] The invention relates to a method for predicting the power generation of photovoltaic cells, in particular to a method for predicting the power generation of photovoltaic cells on a short time scale based on a hybrid model in a micro-grid environment. Background technique [0002] Renewable energy is inexhaustible and inexhaustible energy. For the sustainable development of human society, countries all over the world have turned their attention to renewable energy, and solar power is the main use of renewable energy. It is a smart The main components of the grid. A key goal of smart grid efforts is to greatly increase the utilization of environmentally friendly renewable energy, and microgrid technology is a key technology to achieve this goal, but the uncontrollability of renewable energy generation has brought challenges to our microgrid energy management. Difficulties have caused serious impacts and threats to the economical, safe, and stable opera...
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IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06Y04S10/50Y02E40/70Y02A30/00
Inventor 王愈沈寅星陈新徐放
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS