Improved modelling of electric loads for enabling demand response by applying physical and data-driven models:project RESPONSE

Accurate load and response forecasts are a criticalenabler for high demand response penetrations and optimizationof responses and market actions. Project RESPONSE studies anddevelops methods to improve the forecasts. Its objectives are toimprove 1) load and response forecast and optimization modelsbased on both data- driven and physical modelling, and theirhybrid models, 2) utilization of various data sources such assmart metering data, weather data, measurements fromsubstations etc., and 3) performance criteria of load forecasting.The project applies, develops, compares, and integrates variousmodelling approaches including partly physical models, machinelearning, modern load profiling, autoregressive models, andKalman-filtering. It also applies non-linear constrainedoptimization to load responses. This paper gives an overview ofthe project and the results achieved so far