The management of electricity grids requires the supply and demand of electricity to be in balance at any point in time. To this end, electricity suppliers have to nominate their electricity bids on the day-ahead electricity market such that the forecasted supply and demand are in balance. At the intraday-level, mismatches between the forecasted and actual supply and demand can be compensated for by reserve capacity or by real-time demand response. In this context, there are three ways to minimize the cost of electricity supply. A first one is to predict electricity demand profiles associated to local consumers equipped with smart metering devices as accurately as possible. A second one is to minimize the procurement costs of electricity by shifting flexible loads from peak to off-peak hours. This can be done by offering consumers time-of-use (ToU) variable electricity tariffs as an incentive to shift their demand. A third one is to minimize the imbalance costs resulting from mismatches between forecasted supply and demand, by real-time demand response. Smart control of HVAC equipment with embedded model predictive control (MPC) can be used in that context. They have to be provided with dynamic building simulation models. The first part of this study provides typologies of Smart Grid Energy ready Buildings within the context of the Belgian building stock. A typical new residential building is considered, equipped with an air-to-water heat pump that supplies either radiators or a floor heating system. Different occupancy profiles are considered as well as three heating control strategies guaranteeing equivalent thermal comfort. The flexibility is assessed according to a cost-weighted electricity consumption of the heat pump. The impact of building thermal mass storage on the electricity consumption is also evaluated. A ranking of the building characteristics affecting its flexibility is deduced as well as recommendations to avoid overconsumption associated to energy storage. The second part of this study assesses the flexibility potential of these Smart Grid Energy Ready Buildings within the context of the Belgian day-ahead electricity market. Flexibility will be quantified in terms of load volumes shifted and in terms of procurement costs avoided. The methodology implemented considers both the energy supplier and the end-user. On the electricity suppliers’ side, a ToU-price profile is determined based on an analysis of the day-ahead electricity prices in Belgium (Belpex power exchange, 2008-2012). On the consumers’ side, this ToU-profile serves as an input for the local heat pump controller. This controller uses MPC to determine the heat pump power profile for the next day such that thermal comfort is guaranteed at minimal energy cost. The study will be generalized to the intraday and real time markets in future work
