Hybrid optimization identification method for model parameters of photovoltaic module

Abstract

The invention discloses a hybrid optimization identification method for model parameters of a photovoltaic module. Based on a single-diode model of a photovoltaic cell, internal parameters of a solar photovoltaic cell panel are determined, and a photovoltaic module five-parameter model is established. Parameter identification is performed on the I-V curve of the solar photovoltaic module by using a particle swarm optimization algorithm and a grey wolf optimization algorithm. In the specific implementation process, particles in a population are arranged at random positions through the particle swarm algorithm, the grey wolf algorithm is used for preventing the particles from falling into local optimum, and the main target is to obtain a set of parameters when the root-mean-square error between experimental data and theoretical data is minimum. The particle swarm-grey wolf hybrid optimization algorithm has the main advantages that the global search capability of the particle swarm algorithm and the local search capability of the grey wolf algorithm are combined, and adaptive inertia weight is adopted in the particle swarm algorithm, so that the optimization iteration speed of the algorithm is ensured. According to the method, the identification precision of the photovoltaic cell parameters is high, and the problem of premature convergence can be effectively avoided.

Description

technical field [0001] The invention belongs to the technical field of photovoltaic power generation, and in particular relates to a hybrid optimization identification method of photovoltaic module model parameters. Background technique [0002] Growing demand for electricity and the need to protect the environment has driven greater focus on renewable sources. Solar energy is considered a critical and promising alternative energy source due to its advantages in terms of availability and cleanliness. Photovoltaic modules are the key components of photovoltaic power plants to transmit energy to the outside world, and reasonable and accurate mathematical modeling methods are an important basis for improving the design concept of photovoltaic modules. As a widely used mathematical model, the single diode model has certain difficulties in extracting photovoltaic module parameters due to the nonlinearity of its output characteristic I-V curve. The meta-heuristic PV module param...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a hybrid optimization identification method of photovoltaic module model parameters to solve the problems of large error and poor robustness in the calculation results obtained by the photovoltaic module model parameter identification method in the prior art

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