Investigating the Impacts of Modeling Variables- A Case Study with Smart Grid Demand Response

AbstractWhen modeling and simulating a novel system to be designed, a modeler defines design variables, i.e., those parameters pertaining to the system to be realized, as well as modeling & simulation variables (M/SV), i.e., parameters regarding how the system (as an abstraction of reality) should be modeled and simulated. In this paper, the authors examine the influence of M/SV for a specific case of the conceptual design of a demand response (DR) program. DR is a proposed Smart Grid capability that can be implemented by a utility into an electricity distribution grid. M/SV considered include simulation time-step, number of electricity consumers, and seed variables used in modeling stochastic behavior. The influence of these variables on the ability of the DR simulation environment to produce accurate load curves and peaks is analyzed. For some M/SV, is shown that increased fidelity offers diminishing returns on greater computation time. Quantification of the influence of M/SV is used to support discussion and to identify important considerations when modeling large scale DR past the conceptual design stage