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来源类型Research papers
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Forecasting of investment behavior for hydrogen-fuelcell infrastructure - Using Agent Based Modeling and Simulation
S. M. Cho
发表日期2011-12-31
出版年2011
语种英语
摘要1. Necessity and Purpose of the Research Every country around the world has been making multidirectional efforts such as developing and distributing green energy and implementing energy-saving policies, for establishment of a sustainable energy supply system in response to energy crisis and climate change. However, among all the alternatives to current forms of energy, establishment of an energy system based on hydrogen is evaluated as the most fundamental one since it can be produced from all kinds of energy sources, can be stored and transported more easily than electricity, and does not cause pollution in the stage of usage. For materialization of Hydrogen Economy, which is a society based on hydrogen, development of technology regarding production and use of hydrogen should be prioritized most of all, and a hydrogen supply infra has to be established as well. However, if commercialization of fuel cell is not guaranteed, nobody can readily take lead in the establishment of the hydrogen infra, because a tremendous amount of financial input is needed for it. However, on the contrary, if the hydrogen supply infra is not established, all the efforts for development and commercialization of fuel cell would come to nothing. We call this problem "chicken and egg" dilemma between commercialization of fuel cell and establishment of the hydrogen supply infra. The key to realization of Hydrogen Economy is resolution of this. Preceding research usually utilized market diffusion model and logistics model to analyze efficient way of establishing the hydrogen supply infra and to suggest effective implementation strategies. Even though these preceding research made significant academic and political contributions, they had a certain limitation in that they lacked in analysis of the interaction between participants of the hydrogen-fuel cell market, which is represented by the "chicken and egg" dilemma and they were not appropriate to analyze the process of market establishment based on such interaction. .Against this backdrop, this research aims at overcoming the limitation of preceding research through utilizing Agent-Based Modeling, ABM, one of the models that can reflect the interaction between market participants and the complexity in the real world as much as possible. Through combination of various methods based on the ABM, the hydrogen-fuel cell market will be predicted and a model that can analyze the behavior of participants of the market will be established. Then, based on the established model, number of hydrogen-fuel cell automobile supply, price of hydrogen-fuel cell automobile, number of hydrogen energy station, amount of hydrogen demand, and so on will be predicted through simulation of different scenarios, to suggest a policy direction for effective establishment of the hydrogen-fuel cell automobile market and the infra for it. 2. Major Content Utilizing the ABM, this research establishes a model that predicts the hydrogen-fuel cell market and analyzes behavior of the market's participants. The model consists of a consumer agent, a car-manufacturing agent, a fuel-supply agent, and a government agent module and each of the modules is interrelated with one another. To map out behavior of each agent in the market, methods of conjoint survey, discrete choice model, and learning curve, etc. were used. Before predicting the hydrogen-fuel cell market based on the established model, scenarios were designed. First, two superordinate scenarios were set according to intensity of government policy regarding hydrogen-fuel cell. The first scenario reflects the policy intensity that is currently implemented by the government and the second scenario is based on an assumption that the government implements stricter policies. Meanwhile, each scenario was again divided into two sub-scenarios, standard leaning rate and alternative learning rate, based on assumption about degree of learning about parts that make up a hydrogen-fuel cell automobile. According to result of the analysis based on the standard leaning rate in the standard scenario, hydrogen-fuel cell will not be commercialized even by 2030, mainly because the government's policy measures are not enough to form an early market. Thanks to the government's procurement project, the price of hydrogen-fuel cell automobile will go down to about ��160 million by 2015, from ��250 million in 2010. However, even though the price declines as such and the government supports 20% of the purchasing price from 2016, the selling price still exceeds ��100 million. Due to such a high price and insufficient accessibility cause by poor projects for infra establishment, hydrogen-fuel cell cars will not be chosen by the consumer agent. As such, an early market is not sufficiently formed and after the point of suspension of the government procurement and infra establishment, the price will stop declining and the vicious circle cannot be overcome. Meanwhile, the result of a simulation based on the standard learning rate of the stricter policy scenario was somewhat different from the standard scenario. The trend will be similar to that of the standard scenario until 2020. However, from about 2023, commercialization of hydrogen-fuel cell cars will pick up momentum. Even after 2020 when the government's procurement and infra establishment projects terminate, the price will consistently decline. This is because formation of an early market by the government succeeded to a certain degree and high purchase aid after it influenced consumer agent's choice. However, even by 2030, competitiveness will hardly be secured without 20% of purchase aid thus, hydrogen-fuel cell cars are expected to barely secure viability in the market. According to the research result based on the standard learning rate, the pace of hydrogen-fuel cell cars' price reduction and the speed of market penetration will be slower than those expected by the domestic industry. Meanwhile, the result of the alternative learning rate simulation based on learning rates of each part of hydrogen-fuel cell cars set at 15%, which is somewhat higher than the standard learning rate, showed a significant difference from that of the standard learning rate. First, different from the standard leaning rate which predicts that the price of hydrogen-fuel cell cars would not dramatically decline even after 2016, the alternative learning rate expects that the price will drastically go down after 2016 and commercialization begins soon. In addition, unlike the standard leaning rate, simulation results of the standard scenario and the stricter policy scenario are not much different. Both scenarios predict that commercialization of hydrogen-fuel cell cars will get momentum around 2017 and even after abolishment of purchase aid around 2023, hydrogen-fuel cell cars can compete with gasoline and diesel cars. The supply outlook for hydrogen-fuel cell car in 2030 showed similar result. As such, learning rate have a big influence on result of simulation so, this research analyzed the sensitivity to learning rate. According to the standard scenario, in case of learning rate below 13%, commercialization of hydrogen-fuel cell car will not take place and in case of learning rate over 15%, timing of full-fledged commercialization does not show a big difference. This means that learning rate over 15% can lead to successful formation of early hydrogen-fuel cell car market with current level of the intensity of policy. According to the stricter policy scenario, with learning rate below 11%, commercialization of hydrogen-fuel cell cars will not take place until 2030 and in case of learning rate over 13%, learning rate has little influence on spread and price of hydrogen-fuel cell cars. This means that with learning rate over 13%, the intensity of policy in the stricter policy scenario can contribute to the formation of the early hydrogen-fuel cell market. To compare those results, in case of 11%-15% of learning rate of hydrogen-fuel cell cars, stricter policy that is set in the stricter policy scenario can contribute to the formation of the early market and in case of learning rate over 15%, intensity of policy in line with that in the standard scenario will be enough. This is considered to be the reason of the similarity between the results of the standard scenario and the stricter policy scenario. Another finding of the sensitivity analysis is that the level of price at the point of beginning of commercialization of hydrogen-fuel cell cars is ��60.000,000 in case of all the scenarios. Therefore, reaching this level of price through demonstration projects, government procurement, and establishment of the infrastructure will be essential for commercialization of hydrogen-fuel cell cars. Meanwhile, the number of hydrogen energy station on expressway, which allows transportation between regions with hydrogen-fuel cell cars is estimated at 6 in 2020, 14 in 2025, and 114 in 2030. Hydrogen energy stations should be installed on the Seoul-Busan line and Seoul-Mokpo line by 2020, on the Daegu-Gwangju line by 2025, and on major expressways around the country by 2030, for effective utilization of hydrogen-fuel cell cars. Cost of establishing such hydrogen infra on expressways is estimated at ��7.4 billion in 2020, ��26.6 billion in 2025, and ��212.9 billion in 2030. The number of necessary tube trailers needed for supply of byproduct hydrogen, the most effective way of producing hydrogen in early stage of establishment of the hydrogen infra, is estimated at 3 in 2020, 11 in 2025, and 52 in 2030. The cost of establishing the hydrogen infrastructure that is needed for transportation of hydrogen is expected to be ��300 million in 2020, ��5.2 billion in 2025, and ��17.9 billion in 2030. 3. Policy Suggestion According to the results of analysis of the scenarios, the intensity of government policy that is currently expected is somewhat insufficient for the formation of the early hydrogen-fuel cell market. Therefore, government policies such as procurement and infra establishment should be intensified for commercialization of hydrogen-fuel cell. However, since new technology such as hydrogen-fuel cell that is in the early stage of market can be highly affected by learning rate in term of price reduction, it should be closely traced and observed for adjustment of the intensity of policy. To this end, cooperation and exchange of information between the government, the academic circles, and the industry is essential. Since the consumer agent is highly sensitive to the price of cars, purchase aid can be a very effective policy measure in the budding stage of the hydrogen-fuel cell automobile market. However, as shown in the standard learning rate in the standard scenario, purchase aid implemented without formation of the early market has no effect at all and a expensive long-term purchase aid can lead to excessive government spending. Thus, first of all, the price of hydrogen-fuel cell cars should be driven down to ��60,000,000, which is the point when the market starts to respond, through technology development, government procurement such as demonstration projects and pilot projects, and projects for infra establishment. After that, strategies of promoting full-scale commercialization through purchase aid and adjusting the rate of aid in response to the price of cars will be effective. The environment and awareness of hydrogen-fuel cell have gone through significant change recently around the world and domestic automobile companies will soon introduce hydrogen-fuel cell cars to the market after resolving most of technological problems of hydrogen-fuel cell cars. However, strategies for market penetration in the future have faced a setback because there is no clear vision or road map for hydrogen-fuel cell cars after 2005. Therefore, a vision and road map that clearly present support measures for hydrogen-fuel cell and hydrogen energy station through thorough review of general factors including prediction of the amount of hydrogen demand and ways of modifying legal system are needed.
URLhttp://www.keei.re.kr/web_keei/en_publish.nsf/by_report_year/4778009DCDFB7194492579AA001C9109?OpenDocument
来源智库Korea Energy Economics Institute (Republic of Korea)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/322644
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GB/T 7714
S. M. Cho. Forecasting of investment behavior for hydrogen-fuelcell infrastructure - Using Agent Based Modeling and Simulation. 2011.
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