Date of Award

Winter January 2012

Access Restriction

Thesis

Degree Name

Master of Science

Department

Mechanical Engineering

School or College

Seaver College of Science and Engineering

First Advisor

Mel I. Mendelson

Abstract

While on a great precipice of emerging energy technologies, it is necessary to understand how these technologies are most effectively integrated into current end-user systems. At the moment,

36% of California’s energy consumption is demanded from the commercial buildings sector. This report investigates the nature of energy with the state of California through various sources and analysis techniques. Using specific weather and commercial building data, this paper also focuses on the analysis of Commercial Building energy demand modeling for the state’s sixteen weather zones. It is modeled using the Department of Energy’s tool: EnergyPlus and analysis is performed with R and MATLAB data manipulation software. R is utilized for clustering similar demand signal features for the set of demand profiles. MATLAB is utilized for electric cost savings, based on various applicable utility tariffs, using arbitrary storage apparatuses with variable size and efficiency. It was found that savings could be maximized by complex yet adaptive control algorithms and precisely sized apparatuses per building type/location. Electric Utility Providers can simplify the potential solution to energy storage with electricity tariffs, whilst eliminating statewide need for load following and peak power production.

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