Time sequence probability modeling method for output power of solar photovoltaic power supply

Abstract

The invention discloses a time sequence probability modeling method for output power of solar photovoltaic power supply and belongs to the technical field of probability modeling for output power of the power supply of an electric power system. The time sequence probability modeling method comprises the following steps of: firstly inputting measured data of the output power of the photovoltaic power supply and daily power output begin-end time by utilizing a computer through a program; then estimating a probability density function of the daily power output begin-end time of the photovoltaic power supply based on a nonparametric kernel density estimation theory, and generating a random sample; and then sequentially estimating the probability density function of the output power of the photovoltaic power supply at each time based on nonparametric kernel density estimation and conditional probability theories, and generating a random sample. The time sequence probability modeling method provided by the invention has the advantages of simplicity, strong practicality, high estimation accuracy, strong commonality, and convenience in popularization and application. The time sequence probability modeling method can be widely used for establishing a time sequence probability model of the output power of the photovoltaic power supply in the electric power system.

Description

technical field [0001] The invention belongs to the technical field of probabilistic modeling of the output power of a power system power supply, in particular to a probabilistic modeling method for the output power of a solar photovoltaic power supply (photovoltaic power supply for short) in a power system. Background technique [0002] There are a large number of uncertain factors in the power system, such as the random fluctuation of power output power and load, the change of network operation mode, etc. In recent years, with the large-scale grid-connected operation of green energy sources with random fluctuations in output power, such as wind power and solar photovoltaic power (referred to as photovoltaic power), the uncertainty of the power system has further increased. Therefore, accurately simulating the probability distribution characteristics of the output power of green energy such as photovoltaic power sources is the basis for evaluating the ability of the power s...

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Problems solved by technology

However, the main disadvantages of this method are: 1) This method assumes that the start time and stop time of the daily power output of photovoltaic power sources are fixed, and this assumption will bring large errors, because it is affected by uncertain factors such as the rising and setting time of the sun. The influence of photovoltaic power supply, the moment of starting and stopping output power of photovoltaic power supply in a day is random and uncertain; 2) This method needs to assume parameter distribution to simulate the randomness of photovoltaic power supply output power, but the selection of parameter distribution depends on subjective experience, The theoretical basis is not sufficient, which will bring large errors, and the selected parameter distribution does not always give satisfactory results, that is, the probability that the selected parameter distribution may be applicable to the output power of photovoltaic power sources in some areas 3) This method considers that the random changes in the output power of photovoltaic power sources at each time are independent of each other, and does not take into account the correlation between the output power of photovoltaic power sources at each time, so it cannot be accurately realized Accurate simulation of the output power of photovoltaic power supply at each time and the probability distribution of daily output power

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