The Transactions of the Korean Institute of Electrical Engineers A (대한전기학회논문지:전력기술부문A)

The Korean Institute of Electrical Engineers (대한전기학회)
권호 표지

A Study on Diffusion Model of High-Efficient Appliance Considering DSM Rebate Program's Conditions

전력수요관리 보조금 지원조건을 고려한 고효율기기의 확산모형 연구

  • Published : 2002.12.01
Download PDF
⟨ Previous Next ⟩

Abstract

This paper proposed a new diffusion model considering DSM rebate program's support conditions. The proposed method used some aspects of the rebate program such as support qualifications, annual support volume, and support level per appliance as following : The support qualifications were limited as the consumer which can get the rebate program's benefit, the annual support volume was constrained as the fixing budget and the support level per appliance was considered by high-efficient appliance actuality price. This paper also proposed a new method that used neural network as its parameter estimation moth[,4 for the diffusion model. The diffusion model and its parameter estimation method are expected to be able to analyze the diffusion characteristics of high-efficient appliance through the rebate program and the effects of rebate program's support conditions. Also, these will be able to evaluate the impacts and to analyze the cost-effectiveness of Energy Efficiency Demand-Side Management(EEDSM) resources. The case study is performed on the high-efficient lighting appliance rebate program of Korea by using the suggested diffusion model and estimation method and thus verified its validity.

Keywords

References

  1. Bass, F.M. 'A New Product Growth Model for Consumer Durables,' Management Science, 15, 215-227, 1969 https://doi.org/10.1287/mnsc.15.5.215
  2. Dipak C. Jain, Ram C. Rao 'Effect of Price on the Demand for Durables : Modeling, Estimation, and Findings', Jornal of Business & Economic Statistics, Vol.8, No.2, 160-170, April 1990
  3. Shlomo Kalish, 'A New Product Adoption Model with Price, Advertising, and Uncertainty,' Management Science, Vol.31, No.12, December 1985 https://doi.org/10.1287/mnsc.31.12.1569
  4. Robinson, B., and Lakhani, G. 'Dynamic Price Models for New-Product Planning,' Management Science, 21, 1113-1122, 1975 https://doi.org/10.1287/mnsc.21.10.1113
  5. Mark W, Speece, Douglas L, Maclachlan, 'Application of a Multi-Generation Diffusion Model to Milk Container Technology', Technological Forecasting and Social Change Vol.49, 281-295, 1995 https://doi.org/10.1016/0040-1625(95)00006-V
  6. Towhidul Islam, Denzil G. Fiebig 'Modeling the Development of Supply-restricted Telecommunications Markets', Journal of Forecasting, V.20, pp.249-264, 2001 https://doi.org/10.1002/for.801
  7. Jain D, Mahajan V, Muller E. 'Innovation Diffusion in the Presence of Supply restrictions', Marketing Science V10. pp. 83-90, 1991 https://doi.org/10.1287/mksc.10.1.83
  8. Kim Jung-Hoon, Chang Seungchan, Hwang Sung-Wook, Kim Balho, Kim Chang-Seob, 'Development of Demand Side Management(DSM) Monitoring Methodology Considering the Diffusion Process of High Efficient End-Use appliances', ICEE98 Proceeding, Vol. 1,pp. 115-118, 1998.7
  9. Srinivasan, V., and Mason, C.H. 'Nonlinear Least Squares Estimation of New Product Diffusion Models,' Marketing Science, 5, 169-178, 1986 https://doi.org/10.1287/mksc.5.2.169
  10. Schmittlein, D.C., Mahajan, V. 'Maximum Likelihood Estimation for an Innovation Diffusion Model of New Product Acceptance,' Marketing Science, 1, 57-78, 1982 https://doi.org/10.1287/mksc.1.1.57
  11. Jinhong Xie, X.Michael Song, Marvin Sirbu, and Qiong Wang, 'Kalman Filter Estimation of New Product Diffusion Models,' Journal of Marketing Research, Vol.34, pp.378-383, August 1997 https://doi.org/10.2307/3151900
  12. 김진오, 최청훈, 김정훈, 이창호, 김창섭, 'DSM 모니터링을 위한 확산 모형의 계수 추정', 전기학회논문지 48A권 10호, 1999.10
  13. SAS Institute Inc., SAS/ETS User's Guide, Version 8.2 Edition, SAS Institute, Inc., Cary, NC, 2001
  14. 에너지관리공단, DSM 성과계량 및 비용효과분석 연구 최종보고서, pp.9-34, 2000
  15. 한국전력공사, 구조개편 이후의 수요관리 적정투자규모 및 정부차원의 평가방안에 관한 연구 최종보고서, pp.205-218, 2001
  16. 에너지관리공단, 직접부하제어 사업 활성화를 위한 적정 지원금 산정방안 연구 최종보고서, pp.287-327, 2002
  17. D. E. Rumelhart, G. E. Hinton and R. J. Willams, Learning internal representations by error propagation, Parallel Distributed Processing, vol. 1, pp. 318-362, Cambridge, MA: MIT Press, 1986