Market Allocation Model Research Articles

Modeling biomass-based biofuel production and developing a reference energy system for the agricultural sector in Turkey

Objective: In this study, a reference energy system was developed, and biomass-based biofuel production was modeled for the agricultural sector in Turkey. This was aimed at supplying the entire energy requirement of the agricultural sector using agricultural biomass.
 Material and Methods: In the generated model, domestically produced sugar beet, and canola plants were selected as the energy-producing resources. A market allocation model was generated by interfacing the ANSWER software with all of the relevant import and export components.
 Results: The reference energy system was developed in six columns, including energy resources and demands. As a result of the use of domestic resources, the dependence on energy to foreign countries will be reduced and a new source of employment will be generated in this sector. Furthermore, the production and consumption of biofuels are more appropriate both in terms of cost and in terms of greenhouse gas emissions than fossil fuels.
 Conclusion: The energy demand for the entire agricultural sector is met by the energy supplied from domestic bio-sources produced using part of the agricultural land.

Strategic R&D budget allocation to achieve national energy policy targets: the case of Korea

ABSTRACT While recent international negotiations about combating climate change have led governments around the world to invest in R&D in the energy sector, funds allocated to R&D investment have remained limited during global economic downturns and dependent on national economic conditions. A systematic approach and strategic budget allocation are required to achieve various national energy policy targets. In this study, we describe the optimal investment portfolio for achieving energy policy targets in Korea based on three budget allocation criteria: past investment performance, expected future effects and additional investment risk. We outline the analytic hierarchical process by which policy target priorities are set, developing a market allocation model to analyse expected future effects and a system dynamics model to calculate the investment volume. The systematic approach suggested in this study can increase the efficiency of budget spending by helping governments make investment decisions based on clear criteria and the results of our quantitative analysis regarding government investment in R&D.

Strategic R&D Budget Allocation to Achieve National Energy Policy Targets

While recent international negotiations to combat climate change have led governments around the world to invest in R&D in the energy sector, funds allocated to R&D investment are limited during global economic downturns and depending on national economic conditions. A systematic approach and strategic budget allocation is required to achieve various national energy policy targets. In this study, we describe the optimal investment portfolio for achieving energy policy targets in any nation based on three budget allocation criteria: past investment performance, expected future effects, and additional investment risk. We outline the analytic hierarchical process by which policy target priorities are set, developing a market allocation model to analyze expected future effects and a system dynamics model to calculate the investment volume. Then, we apply these models to an example in an empirical analysis. The systematic approach suggested in this study may increase the efficiency of budget spending by helping government makes investment decisions based on clear criteria and the results of a quantitative analysis regarding government investment in R&D.

Sustainability Planning, Environmental Justice and Climate Change: Applications of the Long Island MARKAL Model

As pointed out by many authors, sustainability is often vague and amorphous (See, for example, Dovers, 1989; Faber, et al, 2005; Glavič, et al. 2007). There is a clear need to make analytical and data-driven analyses of established and or proposed plans. MARKAL (MARKet ALlocation model) is an analytical tool that can be used characterize the impacts of sustainability plans at multiple spatial scales: global, national, regional, and local. In this study we apply the Long Island MARKAL model to answer three interrelated issues: 1, the development and incremental improvement of local and regional sustainability plans; 2, the impact of a national carbon tax, as a response to climate change, on sustainability planning conducted at the local level; and 3, the environmental justice implications of sustainability planning when energy sources are altered.

Analysis of the energy and environmental effects of green car deployment by an integrating energy system model with a forecasting model

By 2020, Korea has set itself the challenging target of reducing nationwide greenhouse gas emissions by 30%, more than the BAU (Business as Usual) scenario, as the implementation goal required to achieve the new national development paradigm of green growth. To achieve such a target, it is necessary to diffuse innovative technologies with the capacity to drastically reduce greenhouse gas emissions. To that end, the ripple effect of diffusing innovative technologies on the energy and environment must be quantitatively analyzed using an energy system analysis model such as the MARKAL (Market Allocation) model. However, energy system analysis models based on an optimization methodology have certain limitations in that a technology with superior cost competitiveness dominates the whole market and non-cost factors cannot be considered. Therefore, this study proposes a new methodology for overcoming problems associated with the use of MARKAL models, by interfacing with a forecasting model based on the discrete-choice model. The new methodology was applied to green car technology to verify its usefulness and to study the ripple effects of green car technology on greenhouse gas reduction. The results of this study can be used as a reference when establishing a strategy for effectively reducing greenhouse gas emissions in the transportation sector, and could be of assistance to future studies using the energy system analysis model.

CO2 mitigation model of future power plants with integrated carbon capture and storage in Thailand

Thailand currently relies on natural gas, coal, and oil for electricity production. Natural gas and oil fields are the plentiful domestic energy resources in the Gulf of Thailand, but are projected to be available only in the next decade. Using domestic natural gas would reduce national energy security. Due to its low price, coal will dominate in electricity generation in Thailand. However, more utilization of coal results in increasing CO2 emissions. To comply with the low-carbon society policy of the Royal Thai Government, carbon dioxide capture and storage (CCS) for the future committed power plants in Thailand is introduced and analysed using the market allocation model, a least-cost energy planning tool. In this study, CO2 mitigation scenarios include integrated CCS to new gas- and coal-based power plants, nuclear power and renewable-based power plants and these were introduced as mitigation options. In energy-demand forecasting, share of coal-based plants is projected to increase from 0.72% in 2006 to 14.97% in 2030, while the share of gas-based plants decreases from 79.24 to 53.25% in the same period. This study also presents possible gas and oil fields for storing CO2 in the deep saline aquifer in the Gulf of Thailand. Results show the optimal CO2 incremental cost and revenue when applied with clean development mechanism and feed-in-tariff for renewable energy and the CCS project in Thailand.

Energy System Modeling and Application for Japanese Local Government Using MARKAL Model

Promoting renewable energy and rational energy use at the regional level is one of the most urgent subjects in Japan. In this paper, we demonstrate a local energy system modeling with MARKAL (Market Allocation) model. This model (the regional MARKAL model) is applicable to all types of government (Metropolitan, Prefectural, City, Town and Village) and assumes long-term energy demands and supply composition of each government from 1990 to 2050. The regional MARKAL model follows many of the technology parameters and preconditions of the Japanese MARKAL model (IO-Household and MARKAL model). Meanwhile, peculiarities of each government are defined by the region-specific parameters obtained from the local energy balance table. Finally we applied this model to Kuzumaki Town (Iwate Prefecture) and Hachinohe City (Aomori Prefecture) and evaluated the results such as energy consumption and CO2 emissions. Since there is little experience in energy modeling at the regional level in Japan, this model can be used by local governments as an effective tool in their med- to long-term energy planning.JEL Classification: Q41, Q56, R58

Carbon emission control strategies for China: A comparative study with partial and general equilibrium versions of the China MARKAL model

China's carbon dioxide emissions from fossil fuel combustion had increased with an annual growth rate of 4.36% since 1980, hitting 1 GtC in 2003. The global climate change issue is becoming more and more important and hence to be the fourth challenge for China's future energy development, following energy supply shortages, energy security, and local environmental protection. This paper used three MARKAL (MARKet ALlocation) family models, that is, MARKAL, MARKAL-ED (MARKAL with elastic demand), and MARKAL-MACRO, to study China energy system's carbon mitigation strategies and corresponding impacts on the economy. The models’ structures and the economic feedback formulations used in MARKAL-MACRO and MARKAL-ED are briefly described. The endogenous demands in MARKAL-MACRO and MARKAL-ED enable them to partly satisfy carbon abatement constraints via energy service demand reductions, and the reduction levels for the 30 demand sectors from these two kinds of models for given carbon emission constraints are presented and compared. The impact of carbon mitigation on social welfare from MARKAL and MARKAL-ED, and on GDP, investment and consumption from MARKAL-MACRO are evaluated. The changes in both final and primary energy mix, changes in technology development, as well as marginal abatement costs for given carbon constraints from the three models, are analyzed.

Robust responses to climate change via stochastic MARKAL: The case of Québec

Future patterns of climate change and economic growth are critical parameters in long-term energy planning. This paper describes a multi-stage stochastic programming approach to formulate a flexible energy plan. The plan incorporates multiple future scenarios and provides for mid-course corrections depending upon the actual realizations of future uncertainties. Results are derived from the stochastic version of Extended MARKAL (MARKet ALlocation) model for Quebec, developed for this purpose. The analysis indicates significant savings of overall system cost in using a hedging strategy over any of the perfect foresight ones. With a 50% probability of implementing stringent carbon mitigation measures after 15 years, the emission trajectory takes the middle path till this uncertainty is resolved. Prior to resolution, electricity supply follows the middle path, natural gas and renewable energy tend to follow the low mitigation trajectory, and oil supply approaches the high mitigation trajectory. A set of specialized hedging technologies has been identified, which emerges more competitive in the hedging strategy than in any of the perfect foresight ones. The paper concludes that such treatment of future uncertainties can give insights that are beyond the scope of an analysis based on deterministic scenarios.