Photovoltaic power generation output power tracking algorithm based on genetics algorithm improved RBF-BP neural network

Abstract

The invention discloses a photovoltaic power generation output power tracking algorithm based on a genetics algorithm improved RBF-BP neural network. By building an RBF-BP neural network, an error absolute value between predicted output and expected output of photovoltaic power generation output power is taken as the fitness, and then a genetics algorithm is adopted for selecting, intersecting and mutating data acquired by photovoltaic power generation equipment in order to find out an individual corresponding to the optimal the fitness. The photovoltaic power generation output power tracking algorithm disclosed by the invention combines the advantages that an RBF neural network is high in rate of convergence, good in heap sort performance and the BP neural network is high in self-learning and self-adaptive capabilities, and has the characteristics of better generalization performance, higher rate of convergence, higher prediction precision and the like.

Description

technical field [0001] The invention relates to a tracking algorithm of output power of photovoltaic power generation, in particular to a tracking algorithm of output power of photovoltaic power generation based on an improved RBF-BP neural network based on a genetic algorithm. Background technique [0002] As the problem of environmental pollution caused by traditional energy consumption has become increasingly prominent, the utilization of renewable energy has attracted widespread attention. Photovoltaic power generation, as an emerging form of renewable energy, has broad development prospects and commercial value. Therefore, it has received more and more attention. Large-scale photovoltaic grid-connected power generation is the mainstream trend of photovoltaic power generation systems, and large-scale photovoltaic grid-connected systems have been applied. [0003] Photovoltaic power generation, like wind power generation, is a fluctuating and intermittent power source. ...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the defects of poor RBF generalization ability and BP neural network training results that are easily misled by incorrect training sample sets, the present invention proposes an improved RBF-based genetic algorithm that can efficiently and accurately predict the output power of photovoltaic power generation. Output Power Tracking Algorithm of Photovoltaic Power Generation Based on BP Neural Network

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