研究目的
To perform key parameter identification and optimization on a solar power plant containing many photovoltaic panels to improve the accuracy of the traditional electromagnetic transient simulation.
研究成果
A novel key parameter identification and optimization method for PV power plant based on genetic algorithm is proposed and validated through simulation tests. The method improves the accuracy of the simulation by identifying and optimizing key parameters.
研究不足
The complexity of the electromagnetic transient model and the diversity of integrated power electronic devices suppliers make the parameters of PV not as accurate as conventional synchronous generators.
1：Experimental Design and Method Selection:
A scheme of key parameter identification is proposed, and an optimization method based on genetic algorithm is established.
2：Sample Selection and Data Sources:
A PV station containing an array of 29×3 cells is tested on the platform CloudPSS.
3：List of Experimental Equipment and Materials:
Not explicitly mentioned.
4：Experimental Procedures and Operational Workflow:
Two kinds of disturbances are designed (large and small disturbances) to identify key parameters. Hybrid simulation method is used to link simulation results and obtained waveform.
5：Data Analysis Methods:
Principle component analysis (PCA) is used for parameter dominance identification, and genetic algorithm (GA) is used for parameter optimization.
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