An Effective LSTM-DDPM Scheme for Energy Theft Detection and Forecasting in Smart Grid. (arXiv:2307.16149v2 [cs.LG] UPDATED)

Energy theft detection (ETD) and energy consumption forecasting (ECF) are two
interconnected challenges in smart grid systems. Addressing these issues
collectively is crucial for ensuring system security. This paper addresses the
interconnected challenges of ETD and ECF in smart grid systems. The proposed
solution combines long short-term memory (LSTM) and a denoising diffusion
probabilistic model (DDPM) to generate input reconstruction and forecasting. By
leveraging the reconstruction and forecasting errors, the system identifies
instances of energy theft, with the methods based …

addresses challenges detection energy forecasting grid security smart solution system systems theft