DocumentCode :
3407855
Title :
A technique to incorporate new information in evaluating generation alternatives
Author :
Rahman, Saiful ; Shrestha, Govinda
Author_Institution :
Bradley Dept. of Electr. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA
fYear :
1991
fDate :
7-10 May 1991
Firstpage :
77
Lastpage :
83
Abstract :
Generation alternatives are characterized by fuel prices, system load characteristics and generating system characteristics. The utility planner has to look at these alternatives from the viewpoints of utility dispatchability, operational availability, fuel diversity, environmental impact, financial viability of the offerer and the security of the contract. The task of evaluating these generation alternatives is complex and often unmanageable, not only because there are so many factors but also because quantitative information is not available for many of them. The method of interdependent data analysis (IDA) is applied to estimate the impact of attributes which are not fully analyzed. The IDA technique uses theory of statistics to model judgments and experience as applied to decision making. In this process the attributes characterizing various generation alternatives are ranked using pairwise comparison. The effect of incorporating the environmental impact on several generation alternatives is analyzed using IDA. It is shown that this technique can provide good estimates of the impact of a factor not previously considered
Keywords :
economics; electric power generation; electricity supply industry; energy resources; power system planning; statistical analysis; decision making; dispatchability; electric power generation; electric utilities; energy resources; environmental impact; financial viability; fuel diversity; fuel prices; generation alternatives; interdependent data analysis; load characteristics; model; operational availability; pairwise comparison; power system planning; statistics; AC generators; Availability; Character generation; Costs; Data analysis; Decision making; Fuels; Power industry; Process planning; Statistical analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Industry Computer Application Conference, 1991. Conference Proceedings
Conference_Location :
Baltimore, MD
Print_ISBN :
0-87942-620-9
Type :
conf
DOI :
10.1109/PICA.1991.160658
Filename :
160658
Link To Document :
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