Initial Data Ingestion & Anomaly Model Selection

Your first task is to simulate or acquire a dataset representing BESS operational telemetry (e.g., voltage, current, temperature, state of charge, power output) over several months, including periods with simulated anomalies (e.g., abnormal temperature spikes, rapid voltage drops). Develop a data preprocessing pipeline. Based on this, select and implement an initial time-series anomaly detection model (e.g., Isolation Forest, LSTM Autoencoder) using a suitable Python library.