A Critical Review of Energy Projections
3.2. IIASA: Energy in a Finite World 1. Description
3.2.1.1. Source and objective
Source: Haefele et al., 1981. Energy in a finite world. Voll: Paths t o a sustainable future, a summary and analysis. Vo12: A global systems analysis, the technical report.
Report by the Energy Systems Program Group of the International Institute of Applied System Analysis (IIASA). Program leader: Wolf Haefele. Ballinger Publishing Company, Cambridge, Massachusetts.
Objective: Study of the global and long-term development of the energy system, exploration of possible energy futures, especially the transition t o post-fossil systems.
3.2.1.2. Scale and resolution
Time scale: Standard time frame of 50 years, 1980
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2030. Base year: 1975 Space scale: GlobalTime resolution: Iteration intervals of 5 years
Spatial resolution: Division of the world in seven groupings, selected for their economic and energy similarities, and not so much for geographic proximity
Region 1: NA North America
Region 2: SU/EE Soviet Union and Eastern Europe Region 3: WE/JANZ Western Europe, Japan, Australia, New
Zeeland, South Africa, Israel Region 4: LA Latin America
Region 5: Af/SEA Africa, South and Southeast Asia Region 6: ME/NAf Middle East and Northern Africa
Region 7: C/CPA China and Centrally Planned Asian Economies
Fuel disaggregation: Seven fuels are considered in this study. Oil, Gas, Coal (conventional/synfueIs), Nuclear (Light Water Reactor/Fast Breeder Reactor), Hydroelectricity, Solar, Renewables (biogas, geothermal, commercial wood)
3.2.1.3. Exogenous v a r i a b l e s a n d key a s s u m p t i o n s
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Market penetration of fuels and new technologies-
Efficiencies of energy use-
Imports and exports-
Potential labor force-
Cost/buildup rates of energy producing facilities-
Institutional variables (productivity, capital-output) Output (derived variables, results):-
Aggregate final energy demands in macrosectors-
Regional and global primary energy production, fuel mix-
Energy-
GDP elasticities-
Total required capital investments-
Potential market for final energy forms-
Contribution of new technologies-
Shadow prices of fuels and electricity-
Socioeconomic and environmental impacts (indirect investments, water-, energy-, land-, material-, manpower- requirements, climate, risks)Main scenario assumptions:
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Continuity, no jumps and surprises in evolution (wars, technological break- throughs)-
Modest population and economic growth-
Match demand and supply, no gaps-
Only economic and resource- and energy-related constraints are considered. Politi- cal, social and environmental constraints are recognized, but were not applied explicitly-
The US dollar and other monetary units have constant (1975) value, inflation aspects of the energy problem are neglected-
Temporal frame assumptions: Three time phases (IIASA, 1981, Vol 2, p.9) Present phase: 198G2000, oil supply problemFirst transition phase: 2000-2030, moving from clean and cheap oil t o different energy carriers Ultimate trans. phase: 2030-xxxx, moving to a sustainable
energy supply system
3.2.1.4. A p p r o a c h The modeling techniques:
MEDEE: end use approach
MESSAGE: linear programming optimization model
IMPACT: energy oriented dynamic input-output model MACRO: aggregated economy model
Description of the model structure:
The three of IIASA energy models are connected by an information flow between the models, in what has been described as a loop of models (Figure 3.2). The demand for final energy in each of the seven world regions is evaluated in the demand model MEDEE, which is driven by population and economic growth (exogenous). The supply model MES- SAGE then determines the optimal cost conversion system and calculates the required primary energy, taking into account resource availability, technological, environmental and other relevant constraints. The economic and other impacts of these energy supply strategies are evaluated in the model IMPACT (only interpretative results, no direct feed- back links), and the macroeconomic issues are assessed in the aggregated economy model MACRO (which, in the end, was never applied). This whole procedure is iterated region by region, taking into account interregional energy trade, until a globally consistent energy demand and supply pattern evolves.
Scenario Definition
r---
(economic, popu-I I
r
I I I
I
I Economic Structure,
Energy Demand Lifestyles,
I Technical Effic~encies
I
1
I
I Secondary Fuel Mix
and Substitutions
Product~on Limits
for each world region
---I---
/
; ] ,
Interregional Energy Trade
Formal mathematical models
(-1
Assumptions, judgments, manual calculations-+ Direct flow of information (only major flows shown)
--- Feedback flow of information (only major flows shown)
Figure 3.2 IIASA's set of energy models: a simplified representation
Consistency checks are also carried out on the information flow between the models in each step of iteration. This is because the models are not "hard-wired" together, but rather allow for human judgement. All the inputs and outputs are examined to be sure that credible results appear a t all steps.
Final energy demand model MEDEE
MEDEE is an end-use-approach energy demand model that evaluates the influence on energy demand of social, economic, technological and policy changes. This model is only a calculation tool interrelating the major determinants of both useful and final energy demand. Although it contains many variables and relations, its structure is quite transparent and simple.
The energy sector is disaggregated into a multitude of end use categories. For each category the useful energy demand is related to a set of determining factors which can be macroeconomic aggregates, physical quantities or technological coefficients. These general scenario parameters must be disaggregated in terms of economic structure (set of indus- trial products), demographic structure (economic growth, lifestyles) and technological structure (energy intensiveness, efficiency, market penetration). A macroeconomic module translates the socioeconomic scenario assumptions into specific activity levels of the end use categories. Final energy demand is then calculated for each category in three other modules (household/services, industry, transportation) using activity levels and techne logical determinants. Because of the high level of disaggregation, few structural assump tions are built in the model.
MEDEE does not deal directly with the problem of interfuel substitution because this problem is treated within the supply model MESSAGE. For competing final energy sources no market penetration is modeled; it has to be introduced exogenously. Energy demand is also not related directly to energy prices by means of elasticity coefficients
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this approach is considered inapplicable for making energy predictions because it uses pri- marily trend analysis and trend extrapolations from the past. Price-energy relations are used in the scenario writing process as expert-opinion-based background information for modifying past trends.
Primary energy demand model MESSAGE
A number of primary energy sources and their associated conversion technologies are considered to calculate the primary energy demand from the secondary energy demand assessed in MEDEE. The MESSAGE model has an objective function which is the sum of discounted costs of capital, operating, maintenance and fuels (primary energies). This function is minimized by the optimization model. The conversion model takes account of costs, availability and quality of resources, buildup rates, and energy production capaci- ties. Emission constraints and pollutant concentration constraints (Krypton, GOz) were available but neither used nor binding in the model.
Economic and environmental impacts model IMPACT
IMPACT is an energy oriented dynamic input-output model that calculates the fol- lowing:
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Direct and indirect capital investments in energy system development-
Investment in energy system development-
Required energy-related indirect capital investments, materials, equipment and services-
Direct and indirect 'WELMM" requirements (non energy resources), i.e. Water (mining, energy production), Energy (for construction), Land (for power plants and mining capacities), Materials (for construction), Manpower-
Impacts on climate ( C 0 2 , Waste heat, changes in surface characteristics due to large scale solar power ~ l a n t s )-
Risks of energy technologies for human health. Risk estimation, risk evaluation, risk management, valued as costs-
Time constraints for market penetration (Marchetti)Macroeconomic model
MACRO
This aggregated economy model would have supplied the economic input values for MEDEE after integrating the capital requirements for the energy sector in the overall economy. This model finally was not used, because the group had difficulties in integrat- ing it with the rest of the model set (compatibility of aggregation levels).
3.2.1.5. M o d e l results
Figures 3.3 and 3.4 show the input assumptions for Population and GNP per capita and the results for primary energy per GNP, which is an important measure for efficiency, total primary energy supply and primary energy per capita. These values are plotted in energy systems. It captures long-term slowly changing macro-economic characteristics, structural changes on regional and global level. Thus the model is able t o capture the effects on the energy sector of investment policies, technological changes, lifestyle pat- terns, structural changes in the economy like the transition to a postindustrial phase and development policies/strategies for LDC's. The model provides global and regional final energy demand, primary energy production and fuel mixes. It models the evaluation of energy supply, conversion and distribution systems and incorporates impacts of alterna- tive strategies on resources, economy (capital, cost) and some on environment (land use, water use, C 0 2 emissions). competing land uses between non-commercial energies and agriculture or the impacts of extensive use of biomass fuels cannot be considered. This flaw holds true for most of the
Pop c;rjp/'r=~lp Et-(j/C;r.I F
Tot erg
Erg,/Cnp
Figure 3.3 Factor increase in the IIASA model
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high-
Pop*
G N P , ~ = U ~+ Ery/GrJP