Photovoltaic array online modeling method based on reinforcement learning

Abstract

The invention discloses a photovoltaic array online modeling method based on reinforcement learning. A system for implementing the method comprises a reinforcement learning model actuator (101) of a parameter a, a reinforcement learning model actuator (102) of a parameter Rs, a reinforcement learning model actuator (103) of a parameter Rsh, a reinforcement learning model actuator (104) of a parameter dG, a single-diode model (105), an error calculation module (106), an estimation I-V curve and actual measurement I-V curve characteristic state extraction module (107), a return value calculationmodule (108), a power converter (201) with an I-V curve scanning function, an irradiance sensor (202) and a photovoltaic module temperature sensor (203). Online model parameter extraction and photovoltaic array I-V characteristic curve real-time calculation are realized through the reinforcement learning model actuator, and meanwhile, the model calculation precision and calculation speed are ensured.

Description

technical field [0001] The invention relates to the field of solar photovoltaic power generation, in particular to an online modeling method for photovoltaic arrays. Background technique [0002] As the installed capacity of photovoltaic power plants at home and abroad has increased year by year in recent years, the mathematical modeling of photovoltaic systems, especially photovoltaic arrays, has attracted increasing attention. At present, the mathematical models of photovoltaic arrays mainly use single-diode or double-diode models based on equivalent physical models, and the model parameters Susceptible to environmental influences, conventional model parameter extraction methods are difficult to guarantee model accuracy under different environmental conditions, and cannot consider the reduction of model accuracy caused by photovoltaic system performance degradation, so the current model parameter extraction methods still have limitations; For the photovoltaic array current...

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Problems solved by technology

[0002] As the installed capacity of photovoltaic power plants at home and abroad has increased year by year in recent years, the mathematical modeling of photovoltaic systems, especially photovoltaic arrays, has attracted increasing attention. At present, the mathematical models of photovoltaic arrays mainly use single-diode or double-diode models based on equivalent physical models, and the model parameters Susceptible to environmental influences, conventional model parameter extraction methods are difficult to guarantee model accuracy under different environmental conditions, and cannot consider the reduction of model accuracy caused by photovoltaic system performance degradation, so the current model parameter extraction methods still have limitations; For the photovoltaic array current-voltage (I-V) curve, the meta-heuristic optimization algorithm is used to extract the model parameters. This method has high accuracy but can only guarantee the model accuracy under the current environmental conditions, and the parameter extraction process needs repeated iterative calculations, which is time-consuming and difficult. Guarantee the real-time performance of photovoltaic array online modeling

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