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Real-time combined heat and power operational strategy using a hierarchical optimization algorithm

Existing attempts to optimize the operation of combined heat and power (CHP) systems for building applications have two major limitations: the electrical and thermal loads are obtained from historical weather profiles; and the CHP system models ignore transient responses by using constant equipment efficiencies. This article considers the transient response of a building combined with a hierarchical CHP optimal control algorithm to obtain a real-time integrated system that uses the most recent weather and electric load information. This is accomplished by running concurrent simulations of two transient building models. The first transient building model uses current as well as forecast input information to obtain short-term predictions of the thermal and electric building loads. The predictions are then used by an optimization algorithm (i.e. a hierarchical controller that decides the amount of fuel and of electrical energy to be allocated at the current time step). In a simulation, the actual physical building is not available and, hence, to simulate a real-time environment, a second, building model with similar but not identical input loads are used to represent the actual building. A state-variable feedback loop is completed at the beginning of each time step by copying (i.e. measuring, the state variable from the actual building and restarting the predictive model using these ‘measured’ values as initial conditions). The simulation environment presented in this article features non-linear effects such as the dependence of the heat exchanger effectiveness on their operating conditions. The results indicate that the CHP engine operation dictated by the proposed hierarchical controller with uncertain weather conditions has the potential to yield significant savings when compared with conventional systems using current values of electricity and fuel prices.