Optimal Operation of Nearly Zero Energy Buildings using Mixed Integer Linear Programming

This paper proposes a deterministic mixed integer linear programming model for the optimal operation of an energy system providing thermal and electrical energy for a residential and commercial nearly zero energy building. The space heating and space cooling demand of the buildings is simulated using a resistive-capacitive model within a quadratic program respectively. Thermal energy for space heating, space cooling and domestic hot water is buffered in thermal energy storage systems. A dual source heat pump provides thermal energy for space heating and domestic hot water, whereas space cooling is covered by an underground ice storage. The environmental energy sources of the heat pump are ice storage or wind infrared sensitive collectors. The collectors are further used to regenerate the ice storage. Further space heating demands are covered by a combined heat and power unit, which also produces electricity. Photovoltaic panels produce electrical energy which can be stored in a battery storage system. The electrical energy system is capable of selling and buying electricity from the public power grid. A mixed integer linear programming model is developed to minimise the operation cost of the combined commercial and residential nearly zero energy building over a scheduling horizon of 24h. The developed model is tested on two typical days, which are representative for the summer and winter season. Furthermore, it is investigated how external incentives such as varying electricity prices impact the optimal scheduling of the energy system.