BTM DER Load Forecasting

What is BTM DER?

BTM = Behind-the-Meter (at your home) DER = Distributed Energy Resources (solar panels, batteries, EV chargers)

Think of it: Your home has solar panels that generate power, a battery that stores it, and an EV charger that uses it. The net load (what you buy from the grid) changes constantly.

The Problem

Why is forecasting hard?

1. High Variability - Solar output changes with clouds, EV charging is random, battery discharge is unpredictable 2. Limited Data - New installations don't have years of history 3. Complex Patterns - Multiple components interact (solar reduces load, EV increases it, battery smooths peaks) 4. Anomalies - Unusual events (parties, industrial processes) break normal patterns

Why Does It Matter?

- Grid Stability - Grid operators need accurate forecasts to balance supply/demand

• Cost Savings - Better forecasts help optimize battery charging/discharging
• Renewable Integration - As more homes get solar, forecasting becomes critical

  Solution: Compare 4 Methods

  This paper tests which forecasting method works best:

• ARIMA - Classical statistical method
• SVM - Machine learning approach
• ANN - Shallow neural network
• LSTM - Deep learning with memory