Greenhouse Gas

Reduced peak CO2 generation

Integral Analytics is a leader in estimating the expected CO2 reductions from energy conservation, demand response and renewable energy sources.

DSMore’s approach to valuing avoided carbon emission?

A Greenhouse Gas Emission (GHG) worksheet is embedded inside the standard DSMore calculation engine.  Carbon emission results can be valued at the same time as normal DSM valuations.

• Explicitly addresses varied emissions savings due to weather uncertainty, load savings variability and variable plant dispatch decisions throughout the year.
• Relies on utility integrated planning estimates (IRP or other) to match supply-side resources with proposed demand-side activity.
• Values GHG emissions from recognized sources including traded markets and avoided emissions compliance technologies.
• Additional user set up is required, related to supply stack importing and review of default carbon emissions per plant or region.
• Compatible with recognized GHG protocols and reporting standards.
  
  

DSMore reports expected tons reduction in CO2 generation and the associated $/Ton value of CO2 reductions attributed to conservation, demand response and renewable supply resources. The model uses the regional expected forward resource mix displacing marginal generation as demand resources are deployed. The results are consistent with a typical dispatch order. Conservation, demand response and renewable resource displace CO2 emissions differently. Conservation programs operate all hours of the year and when different supply resources are “following the load”. These may include base-load coal resource or gas fired combined cycle resources. Demand response programs initially displace expensive combustion turbine gas resources. The initial hours represent those top hours of the year when gas generation operates at the margin. As the number of hours deployed increases, coal or combined cycle generation eventually becomes the marginal source of energy. Because coal fired generation has higher CO2 emissions than gas generation, the initial hours have relatively low avoided emissions benefits and later hours have relatively high avoided emissions benefits.

The results are reported as total tons reduced and the $/ton benefit. In order to determine the value of a ton of CO2, the model relies on traded CO2 market data where available consistent with standard practice. Using the results of a dynamic load control program as an example, the total tons reduced per participant for a Medium Residential rate class is shown in the chart below. The results indicate that the CO2 reductions increase as the percent reduction and hours deployed increase. The results are consistent with the marginal deployment of supply resources. During the initial hours, gas generators are supplying the grid. Moving down the supply stack, eventually coal becomes the marginal fuel. The chart identifies the intersection of gas and coal marginal fuel. Gas supply has relatively less CO2 than Coal, and therefore the majority of CO2 benefits will occur during those hours when coal is the marginal fuel supply. At 500 hours deployed and 10% reduction the results indicate that the program can provide up to 3,565 marginal lbs of CO2 reduction.