**6.2 Annual time dependent valuation emission factors**

300 Sustainable Growth and Applications in Renewable Energy Sources

Monthly TDV NGHGIFA = Monthly Time Dependent Valuation New Greenhouse Gas

The hourly and average values obtained for the monthly TDV NGHGIFA were compared for

The following test case provides an example on how the different GHG emission factors can be used to demonstrate the cyclic behaviour of emission factors througout the day, month, season, and year. In addtion, the test cases also show the beneficial attributes associated

Transient System Simulation Tool (TRANSYS) building energy simulation software can be used to perform highly complex thermal analysis, HVAC analysis and electrical power flow

Tse et al. (2008) performed simulations, using TRANSYS, which included the use of PV on the computational model for a townhouse that would be built in the Annex area in Toronto. TRANSYS was used to simulate and help optimize the performance of the home, as well as the different systems that would be implemented. The systems that were analyzed consist of a solar domestic hot water system, a photovoltaic system (6.25 kW), and a ground source heat pump. Hourly annual simulations were run to demonstrate the potential electricity contribution and emission savings from PV. This data has been utilized in combination with the hourly, seasonal and monthly TDV emission factors discussed in the previous sections to

The results for the NGHGIFA for the years 2004, 2005, and 2006 are shown in Table 2

Annual 208 221 189 Winter 248 231 196 Spring 164 205 164 Summer 174 241 214 Fall 244 205 190

Table 2 shows a large variance between emission factors throughout the year and from year to year. Clearly, the use of hourly data is necessary to accurately estimate the GHG

**2004 2005 2006** 

estimate the reduction potential of GHG emissions by the use of PV technology.

**Season NGHGIFA (g of CO2/kWh)** 

Table 2. Hourly annual and seasonal average GHG emission factors

reduction potential from renewable technologies.

Where,

i = day number j = hour number

simulations.

**6. Results** 

Intensity Factor (g CO<sup>2</sup> /kWh) N = number of days in the month

the years 2004, 2005, and 2006.

**5. Test case scenario** 

with renewable technologies.

**6.1 Hourly GHG emission factors** 

(Gordon & Fung, 2009).

Table A-1 in Appendix A shows the annual TDV emission factors (Gordon & Fung, 2009). It can be observed that emissions throughout the day vary considerably. It should be noted that the maximum TDV values for the years 2004, 2005, and 2006 occurred at 1 p.m.

Table 3 shows the annual average TDV GHG emission factors. These values were obtained by using the annual TDV GHG emission factors in Table A-1 in Appendix A.


Table 3. Annual average TDV GHG emission factors
