Temperature–Load Relationship
Temperature drives heating and cooling demand; a simple weather–load model underpins many power forecasts.
Heating and cooling degree days translate temperature into expected demand for electricity and gas.
Load forecasting models often regress demand on temperature, calendar effects, and trend terms.
Weather risk enters portfolios through the sensitivity of load, and hence prices, to temperature deviations.
This curve shows a stylised temperature–load relationship. Heating and cooling slopes translate degrees below or above a comfort temperature into extra demand.
A simple weather–load model says: demand is roughly linear in degree days around a comfort band. Heating and cooling slopes encode how sensitive the system is to cold and heat.
For forecasting and risk you care less about any single temperature realisation, and more about the gradient of load with respect to temperature. That gradient propagates weather uncertainty into load, then into prices, then into portfolio P&L.