Optimal Energy Consumption Forecast for Grid Responsive Buildings: A Sensitivity Analysis

TL;DR

This paper develops a sensitivity analysis methodology to quantify how uncertainties in models and measurements affect optimal energy consumption forecasts for grid-responsive buildings, demonstrated on HVAC systems.

Contribution

It introduces a novel approach for assessing the impact of uncertainties on energy forecasts, aiding better integration of buildings into smart grid operations.

Findings

Sensitivity of energy forecasts to model parameters quantified

Method demonstrated on HVAC system case study

Framework supports improved grid-building energy management

Abstract

It is envisioned that building systems will become active participants in the smart grid operation by controlling their energy consumption to optimize complex criteria beyond ensuring local end-use comfort satisfaction. A forecast of the building energy consumption will be necessary to enable integration between building and grid operation. Such forecast will be affected by parametric and measurement uncertainty. In this paper we develop a methodology for quantifying the sensitivity of optimal hourly energy consumption forecasts to various sources model and measurement uncertainty. We demonstrate the approach for a building heating ventilation and air conditioning (HVAC) system use-case.