Uncertainty in developing supervisory demand-side controls in buildings: A framework and guidance

Abstract

Successful demand-side control depends on the accuracy of the prediction of the power demand. This prediction should express margins of expected ranges of the power demand. Therefore, uncertainty is an unavoidable ingredient that has to be explicitly considered when evaluating performance of demand-side control. However, there is at present neither serious attention to system uncertainty nor to human-introduced uncertainty in developing the supervisory controls of building and HVAC&R systems. There is, in fact, neither a commonly shared terminology nor an agreement on a generic typology of uncertainty. Apart from introducing a common terminology and typology of uncertainty, this study provides a conceptual framework for systemic management of uncertainty, along with a process of developing the supervisory demand-side controls. This study reviews relevant uncertainty sources. Surveyed sources are classified according to the typology, and then encoded into the uncertainty matrix as part of the framework. The uncertainty matrix is used for a priori uncertainty assessment that enables model developers to identify, articulate, and prioritize critical uncertainty; it is a crucial step for gathering more adequate identification and for proper treatment of uncertainty before developing a significant model. The a priori uncertainty assessment identified that heuristic uncertainty and scenario uncertainty tend to introduce higher risks for the demand-side control in meeting its objectives. Upon this assessment, this study suggests a theoretical guide to manage and reduce risks due to uncertainty: heuristic uncertainty can be preventable if models are constructed through the formal modeling framework; physical uncertainty including both scenario uncertainty and statistical uncertainty can be compiled into model in order to render the model immune to uncertainty. • Uncertainty is an unavoidable complication for performance of the demand-side control. • Neither a commonly shared terminology nor typology of uncertainty is available. • A priori uncertainty assessment gathers more adequate identification of uncertainty. • A priori uncertainty assessment also suggests proper treatment of uncertainty. • This study presents a general guide to manage and reduce the risk due to uncertainty.