.png){kind=icon}
返回
Risk-constrained bidding strategy with stochastic unit commitment
.png){kind=icon}
PRE
AI
DOI：10.1109/TPWRS.2006.887894.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper develops optimal bidding strategies based on hourly unit commitment in a generation company (GENCO) that participates in energy and ancillary services markets. The price-based unit commitment problem with uncertain market prices is modeled as a stochastic mixed integer linear program. The market price uncertainty is modeled using the scenario approach, Monte Carlo simulation is applied to generate scenarios, scenario reduction techniques are applied to reduce the size of the stochastic price-based unit commitment problem, and postprocessing is applied based on marginal cost of committed units to refine bidding curves. The financial risk associated with market price uncertainty is modeled using expected downside risk, which is incorporated explicitly as a constraint in the problem. Accordingly, the proposed method provides a closed-loop solution to devising specific strategies for risk-based bidding in a GENCO. Illustrative examples show the impact of market price uncertainty on GENCO's hourly commitment schedule and discuss the way GENCOs could decrease financial risks by managing expected payoffs.
Keyword:
bidding strategy
mixed integer programming
risk
stochastic price-based unit commitment
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.2
论文数:
1.1W
被引数:
5.0W
机构
暂无机构信息
引用论文
Incidence of Hepatitis C Infection among Prisoners by Routine Laboratory Values during a 20-Year Period.png)
PLoS ONE
OAAI
PLoS ONEIF0
OAAI分享收藏分享收藏Linear complementarity models of Nash-Cournot competition in bilateral and POOLCO power markets
PREAI
分享收藏
查看更多内容