Towards automated demand-side management for commercial enterprises

Abstract

Recently, electricity demand-side management programs have gained increasing attention, both, in academic research and industrial practice. Their benefits include reducing and shifting peak electricity demand, deferring the construction of transmission & distribution infrastructure through reduction of energy demand, facilitating the integration of renewable energy into the power grid thereby supporting the reduction of greenhouse gas emissions and cutting the dependency on oil & gas reserves. Since the commercial sector, specifically supermarkets, are responsible for a significant portion of the total electricity consumption, supermarkets have a major role to play in the adoption of these active demand-side management policies. The success of these demand-side management programs relies heavily on the participation of consumers. With this in mind, this research aims to improve the efficacy of demand side management programs for supermarkets by holistically adopting a building automation & control strategy that simultaneously considers building thermodynamics, building control variables, occupant comfort preferences, and dynamically changing electricity prices. The focus of the research is towards developing effective supervisory control strategies for HVAC, lighting and refrigeration building energy systems. A whole-building energy simulation model of a supermarket building is considered and simplified mathematical relationships representing the occupant comfort are developed. While conventional control systems for buildings tend to neglect the system interactions, this research presents a novel effort towards developing optimal control laws for each of the three building energy systems on a zonal level that consider the coupling effects between these systems. These control strategies, along with hourly day-ahead electricity prices and weather data, are used to model the energy performance of supermarkets and ultimately make initial conclusions to the appropriateness of the automated control methodology. It was found that, under the assumptions, the developed supervisory control has the potential for realizing about 14% average peak load reduction while reducing the average daily energy consumption by 12% for a typical supermarket, resulting in an average daily energy cost reduction of about 14%.

Date of Award	Dec 2012
Original language	American English
Supervisor	Amro M. Farid (Supervisor)