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PV-Augmented-NILM-Datasets

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 This repository contains synthesized photovoltaic (PV) augmented datasets for Non-Intrusive Load Monitoring (NILM). The toolkit enables researchers to create realistic scenarios of residential solar energy integration into public datasets (such as REDD and UK-DALE) to evaluate disaggregation algorithms under renewable energy conditions.
-This work was presented in the paper "[Energy Injection Identification enabled Disaggregation with Deep Multi-Task Learning](https://huggingface.co/papers/2508.14600)".
 ## Overview

 This repository contains synthesized photovoltaic (PV) augmented datasets for Non-Intrusive Load Monitoring (NILM). The toolkit enables researchers to create realistic scenarios of residential solar energy integration into public datasets (such as REDD and UK-DALE) to evaluate disaggregation algorithms under renewable energy conditions.
+This work was presented in the ACM e-Energy 2026 paper "[Energy Injection Identification enabled Disaggregation with Deep Multi-Task Learning](https://huggingface.co/papers/2508.14600)".
 ## Overview