.png){kind=icon}
Return
Variable Resource Dispatch Through Do-Not-Exceed Limit
.png){kind=icon}
PRE
AI
DOI：10.1109/TPWRS.2014.2333367.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Due to the variability of renewable resources, the ISO tries to identify do-not-exceed (DNE) limits, which are the maximum renewable generation ranges that the power system can accommodate without sacrificing system reliability. The problem is formulated as an optimization problem whose objective is to find the largest operating ranges of variable resources such that the system remains feasible under any generation realizations within the range. Computing the DNE limits can be conceptually translated into finding the largest uncertain set of a robust optimization problem. Depending on the assumptions on how the system responds to the uncertainty of renewable resources, three alternative approaches are developed to convert the nonstandard robust optimization problem into linear programming, bilinear programming and two-stage robust optimization problems, respectively. Although the linear programming problem is easier to solve as compared to the other two alternatives, its resulting DNE limits are the most conservative. Therefore, the trade-off needs to be considered when deciding which approach is the most appropriate in real-time operation. A 5-bus system and the ISO New England power system are used to test the proposed approaches.
Keywords:
Adaptive policy
affine policy
economic dispatch
robust optimization
uncertainty
variable resources
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.2
Papers:
1.1W
Citations:
5.0W
Organization
No organization information available
Cited Papers
ShareSaveUnderstanding the Effect of Side Reactions on the Recyclability of Furan–Maleimide Resins Based on Thermoreversible Diels–Alder Network.png)
Polymers
OAAI
PolymersIF0
OAAIShareSaveModeling Approaches for Computational Cost Reduction in Stochastic Unit Commitment Formulations
PREAI
ShareSaveShareSave
ShareSaveShareSave
View more