Multiattribute utility analysis with imprecise information : an enhanced decision support technique for the evaluation of electric generation expansion strategies

Multiattribute decision making (MADM) methods have been widely used in electric utility decision problems. This paper presents an enhanced MADM method to support the evaluation of electric generation expansion strategies. The analytical hierarchy process (AHP) is incorporated into the construction procedure of linear additive utility models to facilitate the process of eliciting single utility functions and weighting parameters. The composite utility variances are estimated accounting for individual errors from inaccurate attribute measurements and inconsistent subjective judgments. To support the decision analysis with imprecise information, an appropriate confidence interval is defined to determine the likely range of estimated utility values. Such practice could help the decision maker gain insight into how the imprecise data may affect their choice toward the best solution and how a set of acceptable alternatives may be identified.

[1]  R. Campo,et al.  Decision Framework for New Technologies: A Tool for Strategic Planning of Electric Utilities , 1987, IEEE Transactions on Power Systems.

[2]  Mainak Mazumdar,et al.  Stochastic models for power generation system production costs , 1996 .

[3]  Emerson M. Pugh,et al.  The analysis of physical measurements , 1966 .

[4]  Saifur Rahman,et al.  A statistical representation of imprecision in expert judgments , 1991, Int. J. Approx. Reason..

[5]  F. B. Vernadat,et al.  Decisions with Multiple Objectives: Preferences and Value Tradeoffs , 1994 .

[6]  James Davidson,et al.  A multi-attribute evaluation framework for electric resource acquisition in California , 1991 .

[7]  Narayan S. Rau,et al.  The variance of production cost , 1990 .

[8]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[9]  Luis G. Vargas.  Utility Theory and reciprocal pairwise comparisons: The Eigenvector Method , 1986 .

[10]  I. F. A. S. Member,et al.  Multiple Attribute Decision Analysis with Imprecise Information , 1989 .

[11]  Jayant Kumar,et al.  A decision analysis approach to the transaction selection problem in a competitive electric market , 1996 .

[12]  Ricardo D. Kamenetzky.  THE RELATIONSHIP BETWEEN THE ANALYTIC HIERARCHY PROCESS AND THE ADDITIVE VALUE FUNCTION , 1982 .

[13]  R. L. Keeney,et al.  Decisions with Multiple Objectives: Preferences and Value Trade-Offs , 1977, IEEE Transactions on Systems, Man, and Cybernetics.

[14]  B. Hobbs,et al.  Multicriteria methods for resource planning: an experimental comparison , 1994 .

[15]  Mainak Mazumdar,et al.  Stochastic models for power generation system production costs , 1995 .

[16]  Mainak Mazumdar,et al.  Monte Carlo stochastic simulation of electric power generation system production costs under time-dependent constraints , 1995 .

[17]  Mark Gershon,et al.  Techniques for multiobjective decision making in systems management , 1986 .

[18]  Jeffrey P. Harris,et al.  Evaluating energy and non-energy impacts of energy conservation programs: A supply curve framework of analysis , 1990 .

[19]  Amulfo de Castro.  A technique for multi-attribute utility expansion planning under uncertainty :with focus on incorporating environmental factors into the planning process , 1995 .