Park load prediction method and system based on park portrait

Abstract

The invention provides a park load prediction method and system based on a park portrait. The park short-term load prediction model combining a convolutional neural network model and a long-short memory model is adopted, the risk that a single model falls into a local minimum value in the training process is effectively avoided, the combined models can give full play to respective advantages, andthe load prediction precision is improved.

Description

technical field [0001] The invention relates to the technical field of load forecasting, in particular to a method and system for park load forecasting based on park portraits. Background technique [0002] Accurate park load forecasting is an important prerequisite for safe, stable and economical operation of power systems. The digitalization trend in the energy industry also provides the necessary conditions for the application of artificial intelligence technology. At the same time, the rapid development of machine learning also provides a new solution for load forecasting. Among them, user portrait technology based on machine learning methods has been widely used in many fields, including precision marketing, precision advertising platform, information flow push, various recommendation systems, etc. In the power system, the application of portrait technology can be used in forecasting problems, electricity market Remarkable results have been achieved in marketing and m...

AI Technical Summary

Problems solved by technology

However, the current combination of deep learning and the energy field is still limited, and there is a risk of falling into a local minimum during model training

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