Members of Committee for an assessment on advanced energy technologies

1. Utility Analysis of Future Power Generation Based on the Choice ExperimentJapan-US Workshop onFusion Power Plants and Related Advanced Technologies with participation of EUMarch 5-7, 2008 at UCSD , USRyoji Hiwatari*, Kunihiko Okano, Yoshiyuki Asaoka, Kohji NaganoCentral Research Institute of Electric Power Industry(CRIEPI)Yuichi OgawaHigh Temperature Plasma Center, the Univ. of Tokyo Takaaki KatoFaculty of Environmental Engineering, The University of Kitakyushu Kenji TobitaNaka Fusion Energy Establishment, JAEATakayoshi NorimatuInstitute of Laser Engineering Osaka UniversityCommittee for an assessment on advanced energy technologiesOrganized by CRIEPI

2. Members of Committee for an assessment on advanced energy technologies Y. Ogawa (University of Tokyo, Chairman)K. Okano, Y. Asaoka, R. Hiwatari K. Nagano, T. Nanahara, N. Goto (CRIEPI)K. Itou (The Institute of Energy Economics, Japan) T. Kato (University of Kitakyushu)R. Oomori (Toyota Central R&D Labs., Inc.)) S. Konishi, Y. Oomura (Kyoto University) K. Itou (Kyushu University)K. Tokimatsu, T. Oosumi (Research Institute of Innovative Technology for the Earth) H. Suzuki (University of Tokyo)T. Norimatsu, H. Azechi (ILE, Osaka University)K. Tobita (Japan Atomic Energy Agency)A. Sagara (National Institute of Fusion Science)A. Hibiki (National Institute for Environmental Studies)

3. Summary (1) • There is no single energy system to satisfy all the three aspects of sustainability, i.e. energy, economy, and environment. Hence, the well-balanced combination, i.e. best-mix, of several energy sources should be pursued • The key to choose a best-mix of energy systems is how to evaluate and compare quantitatively the merits and the demerits of each energy system. • In this study, a methodology to evaluate the merits and demerits of energy technology is developed based on the conjoint analysis technique.

4. Summary (2) • Utility values for energy abundance, environmental load (i.e. CO2 emission), stability of supply, sense of security, and other features as well as economic performance, are estimated from several thousands of choice experiments • Difference of utility between gender, generations, and specialists on energy systems is discussed, and how to apply those utility values to energy development is proposed.

5. Contents • Choice experiment and Conjoint analysis • Concept of conjoint analysis • Attribute and its levels on the future electric generation system for choice experiment • Choice experiment applied in this study • Results • Utility values and those reproducibility • Difference between gender, generations in general public • General public v.s. specialists on energy system • Application of utility values • Development priority from the public viewpoint • Education tools (risk communication)

6. Concept of the conjoint analysis • The conjoint analysis is one of techniques to survey on public opinions. • Profile Cards, where various attributes of the target product or concept are listed, are used. • The respondents choose the most preferable Profile Card from the set of the Cards (two or more) which are shown in each question. • -> Choice Experiment • The utility-function for the figure of merit on the individual attribute can be determined through a kind of statistical treatment. Example: a choice of your personal computer • Profile example • Pentium D 3.0GHz • 512MB • 10GB • 98000 Yen • HP, Slim type, etc Attributes*CPU speed*RAM size*Hard-disk capacity*Price*Brand image, design etc.

7. Attributes for Electric Generation System (1)

8. Attributes for Electric Generation System (2) Further consideration on waste and time (e.g. when does a new energy system becomes available ?) is required.

9. Electricity expense in Japan Electricity expense in Japan No impact to health Some fatalities Impact at accident Impact at accident Choice Experiment on Future Electric Generation System Partial profile method of 3 attributes, which are chosen from all 8 attributes at random for each question, has been used. The levels of hidden attributes are assumed to be equal. 30 questions per person. The number of respondents is 1300. Then we got 39,000 answers.

10. Choice Probability from Utility Values Utility value of A　ＵA = [a1iX1i + a2iX2i + a3iX3i + a4iX4i + -----]A Xki is the i-th level value for the attribute k.aki is the coefficients for the effect-function at level i Logit modelThe probability of choosing card-A of Lth question is

11. Contents • Choice experiment and Conjoint analysis • Concept of conjoint analysis • Attribute and its levels on the future electric generation system for choice experiment • Choice experiment applied in this study • Results • Utility values and those reproducibility • Difference between gender, generations in general public • General public v.s. specialists on energy system • Application of utility values • Development priority from the public viewpoint • Education tools (risk communication)

12. Distribution of respondents- public - <n=1349>

13. Resource 100 times as large as petroleum has a same effect to resource distributed in most of country. The increment of effect by “every country” is small. An effect reduction due to 200$ increment in cost can be canceled by an increment of effect due to a reduction of CO2 emission by half. Comparison between 1st (262persons) and 2nd (1349persons) shows the clear reproducibility Results and Reproducibility of Utility Values In this method, the differential of effects for every attributes can be compared each other.

14. Male’s utility for resource distribution is lager. Utility effects for Impact the worst accident case is clearly different between Male and Female Female Male Difference between Gender

15. Utility effects of over 60’s on CO2 emission is clearly larger than that of 10 and 20’s Over 60’s 10・20’s Utility effects for Impact the worst accident case is also clearly different between 10 and 20’s and over 60’s 10・20’s Over 60’s Difference between Generations

16. Distribution of respondents – specialists - <n=352>

17. Utility effects of specialists on CO2 emission is clearly larger than that of general public specialists Utility effects for Impact the worst accident case is also clearly different between specialists and general public. This is partially because 97% of specialists are Male, however, that is not enough to explain the difference. public public specialists Male Difference between public and specialists

18. Contents • Choice experiment and Conjoint analysis • Concept of conjoint analysis • Attribute and its levels on the future electric generation system for choice experiment • Choice experiment applied in this study • Results • Utility values and those reproducibility • Difference between gender, generations in general public • General public v.s. specialists on energy system • Application of utility values • Development priority from the public viewpoint • Education tools (risk communication)

19. Choice Probability from Utility Values Utility value of A　ＵA = [a1iX1i + a2iX2i + a3iX3i + a4iX4i + -----]A Xki is the i-th level value for the attribute k.aki is the coefficients for the effect-function at level i Logit modelThe probability of choosing card-A of Lth question is

20. Baseline Improvement on resource Improvement on electricity expense How to take public preference into account • Assume the baseline of a new energy system( In this case, all utility effects are Zero) • Consider the improvement of each attribute from the baseline to the best level. • Effectiveness on public preference is shown as the choice probability

21. public Public v.s. Specialists 45% 55% specialist 25% 75% Choice Probability - Public v.s. Specialists - • Good in CO2 emission • Good in Impact in the worst accident case

22. Summary • There is no single energy system to satisfy all the three aspects of sustainability, i.e. energy, economy, and environment. Hence, the well-balanced combination, i.e. best-mix, of several energy sources should be pursued • The key to choose a best-mix of energy systems is how to evaluate and compare quantitatively the merits and the demerits of each energy system. • In this study, a methodology to evaluate the merits and demerits of energy technology is developed based on the conjoint analysis technique. • Utility values for energy abundance, environmental load (i.e. CO2 emission), stability of supply, sense of security, and other features as well as economic performance, are estimated from several thousands of choice experiments • Utility difference between gender, generations, and specialists on energy system is discussed, and how to apply those utility values to energy development is proposed.

23. Utility value and effective functions -1 Utility value of A　ＵA = [a1iX1i + a2iX2i + a3iX3i + a4iX4i + -----]A Xki is the i-th level value for the attribute k.aki is the coefficients for the effect-function at level i Logit modelThe probability of choosing card-A of Lth question is Person N’s choices: A A B A B ------------ (total 30 answers) Probability of this phenomenon : PA1PA2PB3PA4PB5-------------------- All respondents The likelihood function L = P[P PA ・ P PB ] N: Number of respondents N Choice A Choice B

24. Utility value and effective functions - 2 Utility value of A　ＵA = [a1iX1i + a2iX2i + a3iX3i + a4iX4i + -----]A The likelihood function L = P[P PA ・ P PB ] We get a lot of data-set for (UA, X1i,X2i,X3i,X4i,----), (UB, X1i,X2i,X3i,X4i,----)and the result of respondent’s choice. A set of aki’s which give the largest likelihood, can be determined by maximizing the function L. The effect-function for the attribute k is shown as a line graph by a plot of {akiXki }.