Probability constrained optimisation model for transmission expansion planning considering the curtailment of wind power

Abstract

The curtailment of wind power has caused huge economic losses and needs to be considered on the stage of transmission expansion planning (TEP). Based on the superquantile theory, the authors use the buffered failure probability to handle the events of wind power curtailment. This new measurement offers several advantages including clear concept, simple calculation, and flexibility. Moreover, the authors form a novel convex relaxation model of the TEP problem. A tri-level approximation algorithm is developed to solve the proposed probability constrained model. The numerical study verifies the performance of the proposed algorithm and demonstrates the advantages of the proposed model over deterministic TEP. Sensitivity analysis is performed to identify the influence of different thresholds in probability constrained TEP problem.

Keywords

• convex programming
• risk analysis
• probability
• power transmission economics
• sensitivity analysis
• power transmission planning
• failure analysis
• wind power plants
• power generation economics
• approximation theory
• probability constrained tep problem
• sensitivity analysis
• numerical study
• probability constrained optimization model
• economic losses
• deterministic tep
• tri-level approximation algorithm
• novel convex relaxation model
• wind power curtailment
• buffered failure probability
• superquantile theory
• transmission expansion planning