Abstract
This paper focused on solving electricity generation expansion planning problems where there are uncertainties associated with the electricity demand forecasts. The electricity expansion plans are long-term commitments and affects people's living conditions and business prosperity deeply. Therefore it is reasonable that the decision makers may be risk averse. In this paper, mathematical models are developed to incorporate the risk aversion into the generation expansion planning problems. We use the conditional-value-at-risk and maximum regret as risk measures and the results shows that the investment plans are affected when the risk is considered.
| Original language | English |
|---|---|
| Pages (from-to) | 309-317 |
| Number of pages | 9 |
| Journal | International Journal of Electrical Power and Energy Systems |
| Volume | 73 |
| DOIs | |
| Publication status | Published - Dec 1 2015 |
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Keywords
- Conditional-value-at-risk
- Electricity demand uncertainty
- Generation expansion
- Maximum regret
- Risk aversion
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering
Cite this
Mean-risk stochastic electricity generation expansion planning problems with demand uncertainties considering conditional-value-at-risk and maximum regret as risk measures. / Tekiner-Mogulkoc, Hatice; Coit, David W.; Felder, Frank.
In: International Journal of Electrical Power and Energy Systems, Vol. 73, 01.12.2015, p. 309-317.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Mean-risk stochastic electricity generation expansion planning problems with demand uncertainties considering conditional-value-at-risk and maximum regret as risk measures
AU - Tekiner-Mogulkoc, Hatice
AU - Coit, David W.
AU - Felder, Frank
PY - 2015/12/1
Y1 - 2015/12/1
N2 - This paper focused on solving electricity generation expansion planning problems where there are uncertainties associated with the electricity demand forecasts. The electricity expansion plans are long-term commitments and affects people's living conditions and business prosperity deeply. Therefore it is reasonable that the decision makers may be risk averse. In this paper, mathematical models are developed to incorporate the risk aversion into the generation expansion planning problems. We use the conditional-value-at-risk and maximum regret as risk measures and the results shows that the investment plans are affected when the risk is considered.
AB - This paper focused on solving electricity generation expansion planning problems where there are uncertainties associated with the electricity demand forecasts. The electricity expansion plans are long-term commitments and affects people's living conditions and business prosperity deeply. Therefore it is reasonable that the decision makers may be risk averse. In this paper, mathematical models are developed to incorporate the risk aversion into the generation expansion planning problems. We use the conditional-value-at-risk and maximum regret as risk measures and the results shows that the investment plans are affected when the risk is considered.
KW - Conditional-value-at-risk
KW - Electricity demand uncertainty
KW - Generation expansion
KW - Maximum regret
KW - Risk aversion
UR - http://www.scopus.com/inward/record.url?scp=84930006602&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84930006602&partnerID=8YFLogxK
U2 - 10.1016/j.ijepes.2015.05.003
DO - 10.1016/j.ijepes.2015.05.003
M3 - Article
AN - SCOPUS:84930006602
VL - 73
SP - 309
EP - 317
JO - International Journal of Electrical Power and Energy Systems
JF - International Journal of Electrical Power and Energy Systems
SN - 0142-0615
ER -