A Flow-Based Model for Conditional and Probabilistic Electricity Consumption Profile Generation and Prediction

arXiv:2405.02180v1 Announce Type: new
Abstract: Residential Load Profile (RLP) generation and prediction are critical for the operation and planning of distribution networks, particularly as diverse low-carbon technologies are increasingly integrated. This paper introduces a novel flow-based generative model, termed Full Convolutional Profile Flow (FCPFlow), which is uniquely designed for both conditional and unconditional RLP generation, and for probabilistic load forecasting. By introducing two new layers--the invertible linear layer and the invertible normalization layer--the proposed FCPFlow architecture shows three main advantages …

abstract arxiv carbon consumption convolutional cs.lg cs.sy distribution diverse eess.sy electricity flow generative low networks novel paper planning prediction profile technologies type