5.5 Key Attributes of the Energy Economy Model – CIMS

Getting to 2050: Canada's Transition to a Low-emission Future — Advice for Long-term Reductions of Greenhouse Gases and Air Pollutants

Key Attributes

The CIMS model, developed by the Energy and Materials Research Group at Simon Fraser University, simulates the technological evolution of fixed capital stocks (mostly equipment and buildings) and the resulting effect on costs, energy use, emissions, and other material flows. The stock of capital is tracked in terms of energy service provided (square metre [m2] of lighting or space heating) or units of physical product (metric tonnes of market pulp or steel). New capital stocks are acquired as a result of time-dependent retirement of existing stocks and growth in stock demand. Market shares of technologies competing to meet new stock demands are determined by standard financial factors as well as behavioural parameters from empirical research on consumer and business technology preferences. CIMS has three modules – energy supply, energy demand, and macro-economy – which can be simulated as an integrated model or individually. A model simulation comprises the following basic steps:

• An exogenous base-case macroeconomic forecast initiates model runs. If the forecast output is in monetary units, these must be translated into forecasts of physical product and energy services.
  
• In each time period, some portion of existing capital stock is retired according to stock lifespan data. Retirement is time dependent, but sectoral decline and changing input costs can also trigger retirement of some stocks before the end of their natural lifespans. The output of the remaining capital stocks is subtracted from the forecast energy service or product demand to determine the demand for new stocks in each time period.
  
• Prospective technologies compete for new capital stock requirements based on financial considerations (capital cost, operating cost), technological considerations (fuel consumption, lifespan) and consumer preferences (perception of risk, status, comfort), as revealed by behavioural-preference research. Market shares are a probabilistic consequence of these various attributes.
  
• A competition also occurs to determine whether technologies will be retrofitted or prematurely retired. This is based on the same type of considerations as the competition for new technologies.
  
• The model iterates between the macro-economy, energy supply and energy demand modules in each time period until equilibrium is attained, meaning that energy prices, energy demand and product demand are no longer adjusting to changes in each other. Once the final stocks are determined, the model sums energy use, changes in costs, emissions, capital stocks and other relevant outputs.

The key market-share competition in CIMS can be modified by various features depending on the evidence about factors that influence technology choices. Technologies can be included or excluded at different time periods. Minimum and maximum market shares can be set. The financial costs of new technologies can decline as a function of market penetration, reflecting economies of learning and economies of scale. Intangible factors in consumer preferences for new technologies can change to reflect growing familiarity and lower risks as a function of market penetration. Output levels of technologies can be linked to reflect complementarities. Personal mobility provides an example of CIMS' operation. The future demand for personal mobility is forecast for a simulation of, say, 30 years and provided to the energy demand module. After the first five years, existing stocks of personal vehicles are retired because of age. The difference between forecast demand for personal mobility and the remaining vehicle stocks to provide it determines the need for new stocks. Competition among alternative vehicle types (high and low-efficiency gasoline, natural gas, electric, gasoline-electric hybrid, and eventually hydrogen fuel cell) and even among alternative mobility modes (single-occupancy vehicle, high occupancy vehicle, public transit, cycling and walking) determines technology market shares. The results from personal mobility and all other energy services determine the demand for fuels. Simulation of the energy supply module, in a similar manner, determines new energy prices, which are sent back to the energy demand module. The new prices may cause significant changes in the technology competitions. The models iterate until quantity and price changes are minimal, and then pass this information to the macro-economic module. A change from energy supply and demand in the cost of providing personal mobility may change the demand for personal mobility. This information will be passed back to the energy demand module, replacing the initial forecast for personal mobility demand. Only when the model has achieved minimal changes in quantities and prices does it stop iterating, and then move on to the next five-year time period.

CIMS' technology data are collected and reviewed in collaboration with the Canadian Industrial Energy End Use Data Analysis Centre (CIEEDAC), an independent data collection and analysis agency co-funded by the Canadian federal government and industry associations and the other residential, commercial and transportation sectors DACs across Canada. CIMS' technology competition behaviour parameters are researched and established in cooperation with the Energy and Material Research Group of Simon Fraser University; the key parameters in CIMS are set using revealed and stated preference discrete choice studies, and literature review where necessary.

Key Scenario Assumptions

Several key scenario assumptions were required to run CIMS for this project. These include the following:

• The population and economic growth forecasts. The growth forecasts are based on Natural Resource Canada's Canadian Economic Outlook (CEO) 2006 and Informetrica Ltd. long-run population forecast. Besides overall output, the assumptions about industrial structure were taken from CEO 2006.
  
• Starting energy prices for natural gas, electricity, coal, gasoline and other refined petroleum products. Theses are directly taken from the CEO 2006, except for coal, which is from the United States Energy Information Administration (EIA). We also adjusted coal price to reflect regional markets.
  
• The costs of carbon capture and storage (CCS). CCS technology, while proven for other applications, has not yet been implemented on a large scale. All the CCS cost information is based on the IPCC (2007).
  
• The presence and absence of international trading in emissions credits, and their clearing price. These scenario conditions have very large impacts on the final results.
  
• The world clearing price of crude oil. We used the EIA price, which was US$45/barrel in 2000 out into the future.
  
• The world price of oil stays high enough to support growth in oil sands. Oil sands growth is a major component of Canada's future emissions, and is highly contingent that the world oil price remains above about US$35/barrel over the entire forecast period.
  
• The world, including the United States, is also imposing carbon emission pricing. Implicit in our macroeconomic assumptions is that our trading partners and competitors are also experiencing significant carbon emission pricing, removing the incentive to switch to other suppliers. If we were imposing carbon emission pricing alone, the macro effects would have been stronger. The remaining macroeconomic response represents the overall substitution by consumers of our carbon intense products away from carbon intense goods.
  
• The energy end-use and supply technology options in CIMS represent a reasonable prediction of the set that could make up a significant portion the energy-using capital stock during the forecast period. In other words, the model is not missing technological options that could take over a significant portion of the capital stock between now and 2050. While it is certain new technologies will emerge that do not currently exist in CIMS, especially under the influence of carbon emission pricing, these must first pass through the stages of invention, refinement, commercialization, and finally purchase before they can constitute a significant portion of the capital stock.
  
• In the policy scenarios an infinite amount of capital is available at the going interest rate (a commonly held assumption for Canadian Computable General Equilibrium models), and wage rates are unaffected.

Please visit the Energy and Materials Group website for further documentation of CIMS, www.emrg.sfu.ca.

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