**1. Introduction**

294 Sustainable Growth and Applications in Renewable Energy Sources

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In recent years, energy consumption and associated Greenhouse Gas (GHG) emissions and their potential effects on the global climate change have been increasing. Climate change and global warming has been the subject of intensive investigation provincially, nationally, and internationally for a number of years. While the complexity of the global climate change remains difficult to predict, it is important to develop a system to measure the amount of GHG released into the environment. Thus, the purpose of this chapter is to demonstrate how several methods can accurately estimate the true GHG emission reduction potential from renewable technologies and help achieve the goals set out by the Kyoto Protocol reducing fuel consumption and related GHG emissions, promoting decentralization of electricity supply, and encouraging the use of renewable energy technologies.

There are several methods in estimating emission factors from facilities: direct measurement, mass balance, and engineering estimates. Direct measurement involves continuous emission monitoring throughout a given period. Mass balance methods involve the application of conservation equations to a facility, process, or piece of equipment. Emissions are determined from input/output differences as well as from the accumulation and depletion of substances. The engineering method involves the use of engineering principles and knowledge of chemical and physical processes (EnvCan, 2006). In Guler (2008) the method used to estimate emission factors considers only the total amount of fuel and electricity produced from power plants. The previous methodology does not take into consideration the offset cyclical relationship, daily and yearly, between electricity generated by renewable technologies. It should be noted that none of the methods mentioned above include seasonal/daily adjustments to annual emission factors. Specifically, the proposed research would include analyzing existing methods in calculating emission factors and attempt to estimate new emission factors based on the hourly electricity demand for the Province of Ontario.

In this Chapter, several GHG emission factor methodology was discussed and compared to newly developed monthly emission factors in order to realize the true CO2 reduction potential for small scale renewable energy technologies. The hourly greenhouse gas emission factors based on hour-by-hour demand of electricity in Ontario, and the average Greenhouse Gas Intensity Factor (GHGIFA) are estimated by creating a series of emission factors and their corresponding profiles that can be easily incorporated into simulation

Analysis of Time Dependent Valuation of Emission Factors from the Electricity Sector 297

they both operate at constant load and fossil generating plants are typically used to handle fluctuations in electricity demand throughout the day. The GHGIFA estimate is based on the generation mix for the Province of Ontario (nuclear, hydro, coal, etc.) and is not adequate to account for most of the GHG emissions from the electricity generation sector, which mainly come from fossil generating stations. Therefore, in order to estimate and phase out fossil completely, a different emission factor needs to be developed. In response to this, a second intensity factor (GHGIFM) was developed. The GHGIFM intensity factor was calculated by dividing the net fossil fuel plant electricity production by the total equivalent CO2 emissions. The value estimated for 1993 was 903.7 t/GWh (Guler et al., 2008). This emission factor assumes that all electricity consumption is provided by fossil plants. This would be beneficial if trying to replace all fossil plants with renewable technologies. However, both of

Renewable technologies (solar and wind) have become an accepted form of generating electricity and heat in the Province of Ontario. There are many advantages in using solar and wind energy such as taking advantage of an abundant source of free energy (sun and wind), as well as being an effective method in reducing GHG emissions. However, the electricity produced by a renewable technology, such as a photovoltaic (PV), or micro-wind turbine and the availability of solar and wind energy, changes throughout the day. Therefore, an hourly GHG emission factor is needed to truly understand the impact that renewable technologies have on emissions since there is a divergence between when

Some of these renewable technologies that are being used in the residential and commercial sectors include photovoltaic, micro-wind turbines, ground source heat pumps, and advance solar thermal technologies. Continuous improvement of these technolgies have promoted the development of hybrid homes. The combination of several of these technologies together will result in end-use energy savings and GHG emission reductions. However, prior to implementing any of these technologies, it is necessary to have an accurate estimation of the true reduction potential of GHG emission factors in order to have a clear understanding of

Currently, Environment Canada uses fuel consumption data from the electricity sector in order to estimate emissions. However, this method can be simplistic and time consuming as well as difficult to use due to the unavailability of certain types of data. Moreover, this method only provides an annual average emission factor which does not reflect the cyclic behaviour of emission factors throughout the day. In 2005, Time Dependent Valuation (TDV) was introduced as a viable method to provide the aformentioned data (MacCracken, 2006). This method was adopted by California as an energy efficient standard for residential and non-residential buildings. Time dependent valuation views energy demand differently depending on the time of use (MacCracken, 2006). California has been able to determine the societal impacts of time of use energy consumption. As a result, this method of analysis would allow for a more accurate representation of the potential reduction of GHGs by using

This following sections will discuss existing emission factor methodolgy and introduce

the methodologies neglect to show hourly changes in emission factors.

**4. GHG emission factor methodologies** 

electricity can be generated and when it is required.

renewable technologies.

monthly TDV emission factor methodology.

the saving potentials associated with renewable technologies.

software (Gordon & Fung, 2009). The use of regionally specific climate-modeled factors, such as those identified, allowed for a more accurate representation of the benefits associated with GHG reducing technologies, such as photovoltaic, wind, etc. This chapter will demonstrate that using Time Dependent Valuation (TDV) emission factors provide an upper limit while using hourly emission factors provide a lower limit. These factors based on hour-by-hour electricity demand data for the Province of Ontario will provide renewable technology researchers with the tools necessary to make informative decisions concerning the selection of renewable technologies.
