Load Forecasting Method for Vertical Federated Learning Park Based on Compressed Sensing
With the increasing importance of park load forecasting,in order to satisfy the data security and privacy protection needs between power enterprises and users,this paper proposes a vertical federated learning park load forecasting method based on compressed sensing.The method utilizes the compressed sensing technique to downscale the gradient,which effectively reduces the amount of transmitted data.Experimental results show that compared with the traditional federated learning method,the method in this paper significantly reduces the communication consumption while maintaining the model accuracy.In addition,the method effectively protects the privacy of the data and provides a safer cooperation environment between power enterprises and users.
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