Analyzing harmony and discord among optimal building controllers responding to energy, cost, and carbon reduction objectives

Optimization and control of building thermal energy storage holds great potential for unlocking demand-side flexibility. As information regarding grid operations become available, grid-interactive building controls inherently become a multi-objective problem. Typical multi-objective optimization frameworks often introduce greater complexity and are less favorable for achieving widespread adoption. With the goal of easing deployment of advanced building controls and aiding the building-to-grid integration, this work aims to evaluate the trade-offs and degrees of sub-optimality introduced by implementing single-objective controllers only. We formulate and apply a single-objective, model predictive control (MPC) framework to individually optimize building thermal storage assets of two types of commercial buildings, informed by future grid scenarios, around energy, economic, environmental and peak demand objectives. For each day, we compare the building's performance in every category as if it had been controlled by four separate single-objective controllers. We reveal the level of harmony that exists between these simple single-objective problems and quantify the potential loss in three of the objectives if the optimal control problem were to respond to only one of the grid signals. Results show that on most days, the carbon and energy controllers retained most of the savings in energy, cost, and carbon. Trade-offs were observed between the peak demand controller and the other objectives, and during extreme energy pricing events. These observations are further discussed in terms of their implications for the design of grid-interactive building incentive signals and utility tariffs.