Application of model predictive control to heating and cooling of off-grid shelters

Abstract

An increasing concern at off-grid forward operating bases (FOBs), disaster relief camps, refugee aid camps and other encampments is the rising cost of supplying and sustaining shelters to accommodate the occupant(s). This is due to high risk burdened costs of liquid fuel deliveries, needed for local electricity generation in remote, and often hostile regions, where such contingency bases are located. A significant part of the non-combat mission related energy consumption in such bases is towards the heating and cooling of shelters. The Environmental Control Unit (ECU) for a shelter, consisting of the components and controls of a packaged terminal air conditioner & heat pump, is operated with a simple set-point temperature control. For such shelters, more efficient use of energy can be accomplished by applying a model predictive control (MPC) approach to the ECU. MPC selects the most fuel efficient operation of the shelter ECU, based on shelter size, materials and construction, internal thermal loads, weather profile, including wind speed, solar insolation, infiltration, and ground coupling. The thesis demonstrates a first-of-its-kind, more energy-efficient and more thermally comfort application of the MPC approach on an Alaska soft shell shelter, equipped with an ECU, by performing a combination of MATLAB and EnergyPlus modeling.