Presence Of Exogenous Variables Research Articles

Occupant plugload management for demand response in commercial buildings: Field experimentation and statistical characterization

Commercial buildings account for approximately 35% of total US electricity consumption, of which nearly two-thirds is met by fossil fuels resulting in an adverse impact on the environment. This adverse impact can be mitigated by lowering energy consumption via control of occupant plugload usage in a closed-loop building environment. In this work, we conducted multiple experiments to analyze changes in occupant plugload energy consumption due to incentives and/or visual feedback. The incentives entailed daily monetary values between $5 and $50 administered in a randomized order and the visual feedback consisted of a web-based dashboard aimed at increasing the energy awareness of participants. Experiments were performed in government office and university buildings at NASA Ames Research Park located in Moffett Field, CA. Autoregressive models were constructed to predict expected plugload savings in the presence of exogenous variables. Analysis of the data revealed modulation of plugload energy consumption can be achieved via visual feedback and incentive mechanisms suggesting that occupant-in-the-loop control architectures may be effective in the commercial building environment. Our findings indicate that the mean energy reduction due to visual feedback in office and university environments were ~9.52% and ~21.61%, respectively. By augmenting the visual feedback in the university environment with a monetary incentive, the mean energy reduction was found to be ~24.22%

Prediction of air pollutants PM10 by ARBX(1) processes

This work adopts a Banach-valued time series framework for component-wise estimation and prediction, from temporal correlated functional data, in presence of exogenous variables. The strong-consistency of the proposed functional estimator and associated plug-in predictor is formulated. The simulation study undertaken illustrates their large-sample size properties. Air pollutants PM10 curve forecasting, in the Haute-Normandie region (France), is addressed by implementation of the functional time series approach presented.

Three-stage DEA models for incorporating exogenous inputs

In this paper, we discuss three-stage models that control for exogenous, non-discretionary inputs in data envelopment analysis. In a recent article in this journal, Monte Carlo analysis was employed to compare and contrast alternative DEA models that measure efficiency in the presence of exogenous variables. The methodology for comparison was flawed, calling into question the results presented. We introduce new second-stage models and compare and contrast them with simulated data.

Frisch on testing of business cycle theories

An important identifying assumption for business cycle models is contained in the mathematical form of the model, which determines the nature of its possible movements. Tinbergen's and Frisch's original understanding of business cycle theories was that of a closed model, containing only endogenous variables. Differential equation models possessed the necessary features for identifying such a theory. However, in Tinbergen's later work for the League of Nations, the models consisted only of difference equations. Frisch showed that the close relationship between the observed movement and the mathematical model was lost in the transformation from differential to difference equations, for such models could only be identified in the presence of exogenous variables.