Model LoadFor - Electricity Demand Forecasting
LoadFor™ is a software solution for forecasting of electricity load (demand). The solution is a self-learning and self-calibrating system. It is based on machine learning and uses weather forecasts and historical demand data to automatically produce very accurate electricity load forecasts. Like SolarFor™, LoadFor™ is both applicable on an individual portfolio basis and on a country-wide scale. To learn more about LoadFor™ on a country-wide scale, see Total Forecast.
An accurate electricity load forecast enables efficient planning and operation of both production and distribution as well as trading of electricity. Accurate load forecasts are essential for transmission and distribution system operators to operate the power grid efficiently and reliably. Efficiently in order to reduce cost of standby capacity and reliably to avoid brownouts and blackouts.
Electricity traders and power retailers need accurate electricity load forecasts to predict power prices, purchase sufficient electricity for their customers and avoid imbalance fees and penalties. LoadFor™ automatically forecasts electricity load and requires minimal effort from the client.
- Automatically and accurately forecasts electricity load in a geographical area or for a portfolio of electricity consumers
- Increases security of supply for electricity customers
- Easy and inexpensive to install, maintain and operate
- Reliable, stable and high availability with a proven operational track record
- Low maintenance with minimal interference and interaction required from the client
- Highly flexible. Can be configured to various power grids and customer portfolios
Based on input data, LoadFor™ automatically identifies and takes the systematic behavior of electricity consumers into account. This means that LoadFor™ continuously adapts to the actual situation by continuously monitoring the consumption and adapts to changes, such as:
- Changes in consumer behavior
- Changes in the number of consumers
- Changes in the meteorological models
- Changes in the physical characteristics of the power grid
The self-learning mechanism has the benefit, that LoadFor™ will identify the impact of any changes by itself and quickly adapt.
Electricity load forecasting can be complicated by the fact that the dynamics of buildings in some geographic regions affect the cooling or heating demand on an hourly basis. LoadFor™ system automatically applies an optimal smoothing effect which solves this issue, such that the physical properties of the underlying energy system are modelled correctly and the forecast shows the appropriate response to changes in temperature or sun irradiation.
Optionally, LoadFor™ can be deployed in combination with MetFor™ (ENFOR™ service for locally optimized weather forecast) to obtain a more accurate local weather forecast, which will result in superior electricity load forecast accuracy.
LoadFor™ is provided as an integrated service from the ENFOR™ platform which contains a data collection and validation module. The data collection and validation module collects the necessary data, ensures that the necessary data is available and contains a toolbox for automatic detection and correction of missing and/or erroneous measurements. The module then feeds the validated data into the core LoadFor™ module which then provides the forecasts.
The ENFOR™ platform also provides LoadFor™ with data integration modules through either FTP, SFTP or web-services such that LoadFor™ can be seamlessly integrated with various data sources.
LoadFor™ can be installed locally on customer systems or hosted by ENFOR™ as a service. It is also possible to get a customized support and maintenance agreement from ENFOR™ or one of the partner companies.