Forecasting Electricity Demand

Requirements Clarification & Assessment

1. Objective Definition:

   • Primary Objective: Develop a predictive model to forecast the annual electricity demand for a town, ensuring an optimal balance between supply and demand.
   • Constraints: Avoid power outages due to under-supply and minimize financial waste from over-supply.

2. Data Requirements:

   • Historical Electricity Consumption Data: Daily or monthly data for the town spanning several years to capture trends and seasonality.
   • Weather Data: Temperature, humidity, and other relevant weather factors that impact electricity usage.
   • Demographic Data: Population size, household numbers, and average household size.
   • Economic Indicators: Data on economic activities that might influence electricity consumption.

3. Seasonality and Trends:

   • Seasonal Patterns: Identify seasonal variations such as increased demand in winter (heating) and summer (cooling).
   • Long-term Trends: Understand any long-term growth or decline in electricity usage over the years.

4. Stakeholder Input:

   • Engage with stakeholders (e.g., utility company officials) to understand their priorities, risk tolerance, and any specific requirements or constraints they have.

5. Performance Metrics:

   • Define metrics like Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and others to evaluate model performance.