Decentralized Multiparametric Model Predictive Control for Domestic Combined Heat and Power Systems

In an effort to provide affordable and reliable power and heat to the domestic sector, the use of cogeneration methods has been rising in the past decade. We address the issue of optimal operation of a domestic cogeneration plant powered by a natural gas, internal combustion engine via the use of explicit/multiparametric model predictive control. More specifically, we take advantage of the natural division of a combined heat and power (CHP) cogeneration system into two distinct but interoperable subsystems, namely) the power generation subsystem and the heat recovery subsystem, in order to derive a decentralized, two-mode model predictive control scheme that specifically targets the production of either electrical power or usable heat at a given time. We follow our recently developed PAROC framework for the design of the controllers, and we apply it in a decentralized manner. We show how the CHP system can efficiently operate in both modes of operation through closed loop validation of the control scheme against a high-fidelity CHP process model.