Powel Demand provides energy consumption forecast for a specific area or group of consumers based on meteorological observations and forecasts of temperature, wind speed (optional) and solar radiation (optional) and historical consumption.
The difficulties of forecasting the market demand for electricity are well known to participants in the energy market. The financial penalties for inaccurate forecasts can be large, as the market is highly intolerant to imbalances. Meeting contract obligations on power delivery depends on reliable forecasting methods and tools.
More accurate electricity demand forecasts
The main benefit of more accurate electricity demand forecasts is reduced imbalance power and as a consequence lower cost in the imbalance market.
"Powel Demand is a robust model with a long track record, being successfully used in regions with many different climate conditions," says Product Manager, Beate Sæther.
Electricity is the only commodity that is produced and consumed simultaneously; therefore, it must always be a perfect balance between supply and consumption in the electricity power market. Market players must independently be able to predict the future market demand and the behaviour of the other players, as a basis for their own bids, contracts and commitments.
"The price for introducing imbalances can be a heavy burden both on the supply side and on the demand side. An accurate forecasting tool can therefore save the players in the electricity power market for a lot of money," says Sæther.
Imbalances caused by changing weather conditions
Imbalances between supply and demand are normally caused by changing weather conditions, abnormal prices or special events like accidental shutdown of large plants or grid outages, various consumption during holidays or simply by inaccurate forecasts. The system operator will have to cover up for the imbalance by charging the players responsible for it.
Powel Demand is a "self- learning" and stateful model based on Kalman filter technology. The model is combining historical information about energy consumption correlated to variations in weather parameters (temperature, wind speed and sun radiation) and patterns in consumer behaviour related to variations over day/night, weeks, seasons and holidays (movable, fixed and independent).
Integrated with a powerful time series management system
The model can be used to forecast other energy sources such as gas consumption if the consumption is weather driven. The period of forecasting is normally for as long as the weather forecast is significantly reliable, typically 7-14 days. Electricity demand forecast is calculated and stored as time series with resolution normally ranging from 15 minutes to one-hour intervals.
Powel Demand is integrated in the Smart Energy portfolio with a powerful time series management system and a user friendly, process-oriented user interface designed for process automation.