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This paper proposes a new method for an optimal control of the heating system at the building scale. This control is a new approach of energy planning that aims to decrease the heating consumption/expenses over a defined prediction horizon while respecting the occupants’ thermal comfort. It employs a simplified building thermal model to simulate the building thermal behavior taking into consideration the weather predictions. This approach is based on the application of Monte Carlo method, i.e., a random generator for the heating system scenarios. The aim is to determine the optimal heating plan for the prediction horizon that fulfills the constraints regarding the thermal comfort of occupants and the minimization of the energy consumption/expenses together with achieving a load shedding. [ABSTRACT FROM AUTHOR]

Abstract: Trigeneration systems, also known as Combined Heat, Cooling and Power (CHCP) systems, are interesting alternatives to supply different energy services in urban districts and in large buildings, particularly in warm areas such as Mediterranean countries. These systems can provide substantial benefits from economic, energetic, and environmental viewpoints, since the cogenerated heat can be used for heating in winter as well as cooling in summer with an absorption refrigerator. This paper develops an optimization model using Mixed Integer Linear Programming (MILP) to determine the type, number and capacity of equipment in CHCP systems installed in the tertiary sector as well as to establish the optimal operation mode for the different plant components on an hour-by-hour basis throughout the year. The objective function to be minimized is the annual total cost. The optimization model considers the legal constraints imposed to feed the surplus autogenerated electricity into the grid at a regulated feed-in tariff. The optimization model is applied to design a system providing energy services for a hospital located in the city of Zaragoza (Spain). The effects of the financial market conditions and energy prices in the optimal structure of the system are analyzed. [Copyright &y& Elsevier]