1999
DOI: 10.1287/mnsc.45.10.1289
|View full text |Cite
|
Sign up to set email alerts
|

Planning Electric Power Systems Under Demand Uncertainty with Different Technology Lead Times

Abstract: Demand uncertainty is a key concern of electric utility planners. While the greater use of short lead time technologies provides one possible way to deal with this problem, it is not clear how they are best deployed. The approach taken in this paper is to examine a capacity mix model that explicitly accounts for differences in technology lead times. Key results that are obtained include the characterization of the optimal solution and the development of a new set of technology screening criteria. In practice, … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
7
0

Year Published

2001
2001
2020
2020

Publication Types

Select...
8

Relationship

0
8

Authors

Journals

citations
Cited by 18 publications
(7 citation statements)
references
References 20 publications
0
7
0
Order By: Relevance
“…Previous research on uncertainty in energy markets has focused primarily on uncertainty with respect to demand evolution (e.g., Gardner, 1996;Gardner and Rogers, 1999), fuel and CO 2 price development (e.g., Roques et al, 2006;Patino-Echeverri et al, 2009), portfolio and risk management (e.g., Morales et al, 2009;Gröwe-Kuska et al, 2003) and renewables expansion, both regarding short-term (e.g., Nagl et al, 2012;Swider and Weber, 2006;Sun et al, 2008) and long-term uncertainties (e.g., Fürsch et al, 2012b).…”
Section: Methodsmentioning
confidence: 99%
“…Previous research on uncertainty in energy markets has focused primarily on uncertainty with respect to demand evolution (e.g., Gardner, 1996;Gardner and Rogers, 1999), fuel and CO 2 price development (e.g., Roques et al, 2006;Patino-Echeverri et al, 2009), portfolio and risk management (e.g., Morales et al, 2009;Gröwe-Kuska et al, 2003) and renewables expansion, both regarding short-term (e.g., Nagl et al, 2012;Swider and Weber, 2006;Sun et al, 2008) and long-term uncertainties (e.g., Fürsch et al, 2012b).…”
Section: Methodsmentioning
confidence: 99%
“…Other results in the literature either ignore supplier heterogeneity e.g., Allaz and Vila 1993 or competition among suppliers e.g. Gardner and Rogers, 1999.…”
Section: Overview Of Wkz Results and Extensionsmentioning
confidence: 99%
“…In effect we recognize that there is a continuum of strictly different future demand scenarios, but think most planners would agree that a smaller number of "characteristically different" scenarios can still meaningfully represent the future. The use of SP to deal with such uncertainty is wellknown [10,14] and it has been used to solve capacity planning problems in the electric utility and semiconductor industries [15][16][17] but not yet to our knowledge in optical network transport planning in general and with only one exception has not yet been applied to network design with builtin survivability assurances.…”
Section: Types Of Demand Uncertaintymentioning
confidence: 99%
“…Note that the nominal forecast can itself be arbitrarily certain-in many applications of this model it can represent the current actual demand pattern. Because the number of significantly different demand scenarios for long-term planning is typically in the order of tens (i.e., Level II model) [5][6][7][8][9][13][14][15][16][17][18][19][20][21][22][23][24][25][26], the more general stochastic integer program can in practice be represented as an integer program of the deterministic equivalent form, for which standard solvers can be used. The two-part span-restorable capacity design (TP-SR) is as follows:…”
Section: Two-part Span-restorable Design (Tp-sr) Without Modularitymentioning
confidence: 99%