Extraction of heating control rules from the dynamic programming method for load shifting in energy-efficient building

Abstract : In France, 40 % of buildings are heated with electrical devices causing high peak load in winter. In this context, optimal strategies (under constraints related to comfort and maximum heating power) have been developed using the dynamic programming method in order to shift electricity consumption used for heating, taking advantage of the building thermal mass. However, this exact optimisation method is computationally intensive and can hardly be applied to real-time control. Complementary statistical techniques exist that allow for the extraction of logistic decision models from the optimal control simulation results. These rule extraction techniques model the relationship between explanatory variables and a response variable. In this study, a generalised linear model was used because it is able to mimic the general characteristics of the dynamic programming results with good precision and greatly reduced computational effort (150 times faster than the dynamic programming method).