Grid Load Forecasting & Optimization

Demand volatility has risen sharply with distributed solar, electric vehicles and changing consumption patterns, while forecasting methods have not kept pace.

• 1Volatile demand driving systematic over-procurement of generation and capacity
• 2Imbalance penalties and emergency purchases when forecasts miss
• 3Legacy statistical methods unable to absorb weather, solar and EV signals

CloudGate builds probabilistic load forecasting on Azure Machine Learning, blending weather forecasts, calendar and seasonality effects, historical consumption and distributed generation signals into hierarchical forecasts from system down to feeder level.

• Probabilistic hierarchical forecasting from system to substation and feeder level
• Weather, calendar, solar generation and EV charging signals in the feature set
• Confidence intervals enabling reserve sizing to a stated risk appetite

Typical outcomes for this solution pattern, not the results of a named client engagement.