LSTM-RNN-FNN Model for Load Forecasting Based on Deleuze’s Assemblage Perspective - Xin, Jie; Wei, Zhenyu; Dong, Yujie; Ni, Wan (Frontiers in Energy Research, 2022)
Reliable load forecasting is essential for electricity generation and even for people's lives. However, existing load forecasting theories cannot match the requirements of complex systems (e.g., smart grids). Deleuze's metaphysical complexity theory is seen as the theoretical foundation for comprehending complex systems, and thus a new perspective based on Deleuze's assemblage concept is given. According to assemblage perspective, electrical load is a quantitative representation of the mutual becomings of people and electricity, and load forecasting is an attempt to control this continuous process of deterritorialization and reterritorialization. We build an LSTM-RNN-FNN model for load forecasting based on the assemblage perspective, and the assessment results demonstrate that the model has high prediction performance. And the performance of adding temperature parameter into the newtork is also tested, while the correlation between temperature and load is not strong enough and may not be suitable for load prediction. The assemblage perspective has significant implications for future load forecasting and potentially smart grid research.