Dissertation: Introduction

I.    Introduction

As developed countries seek to modernize their electric utility grids, whether for the sake of cost savings, the environment, energy security, grid stability, or some combination thereof, many utility companies have started to implement or consider the use of large-scale energy storage (ES) systems to meet present and future demand. Careful consideration of present and future grid scenarios and issues such as inefficiencies in traditional non-renewable energy generation (Dell and Rand 2001), the intermittency of renewable energy sources (Pickard et al 2009), the increased use of distributed generation technologies (Bayod-Rújula 2009), and the introduction of plug-in electric vehicles (EVs) (Verhaegh et al 2010) provide a number of opportunities to implement energy management ES systems that reduce the overall greenhouse gas (GHG) emissions of a grid thereby lessening the region’s impact on anthropogenic climate change.

Sims et al (2007) explain that energy use currently accounts for 70 percent of global GHG emissions and of this 40 percent is used to produce electricity. Furthermore, approximately two-thirds of electricity is generated through the combustion of fossil fuels (i.e. coal, lignites, natural gas, and oil), which creates direct GHG emissions (Sims et al 2007). As a result, comprehensive attempts to mitigate anthropogenic climate change will likely involve addressing electricity generation and use in some form or another.

While a number of energy simulation studies have examined some combination of traditional generation, intermittent generation, and ES systems, the majority of recent studies appear to have optimized their results for financial gain (e.g. Aguado et al 2009, Benitez et al 2008, and Crampes and Moreaux 2010); however, optimizing a system for financial gain will likely result in inefficiencies with regard to GHG emissions (Voorspools and D’haeseleer 2000). Thus, with the issue of global climate change in mind, there is a distinct need to consider situations optimized to reduce GHG emissions.

The objective of this study is to assess the potential near-term impact on greenhouse gas emissions of a large-scale implementation of energy storage systems on an electric utility grid in a region with a fully developed grid system. To this end, technical data has been collected and a scenario-based computer simulation has been developed to model the electricity generation and consumption as well as the GHG emissions associated with the inclusion various types and amounts of ES technologies on an electric utility grid. 

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