Abstract
Considering the correlation and nonlinear characteristics of multiple types of loads in the integrated energy system, grey relation analysis (GRA) and long short term Memory (LSTM) neural network are selected to establish the short-term load prediction model of the integrated energy system. The model uses GRA method to analyze the coupling between multiple types of loads and the meteorological factors, and then obtains the load forecast results through the LSTM prediction model. Finally, a practical example is given to verify the validity of the model.
Export citation and abstract BibTeX RIS
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.