Transmission Expansion Planning under Uncertainty for Investment Options with Various Lead-Times

Abstract

Investment options of transmission expansion planning (TEP) involve different lead times according to their length, technology, and environmental and social impacts. TEP planners can utilize the various lead times to deal with the risk of uncertainty. This paper proposes a novel framework for TEP under an uncertain environment, which includes investment options with various lead times. A multi-stage model is developed to reflect the different lead times in the planning method. The level of demand uncertainty is represented using a relative standard deviation. Demand uncertainty in the presented multi-stage model and its influence on the optimal decision are studied. The problem is formulated as a mixed integer linear problem to which stochastic programming is applied, and the proposed framework is illustrated from case studies on a modified Garver's six-bus system. The case studies verify the effectiveness of the framework for TEP problems with a mathematically tractable model and demonstrates that the proposed method achieves better performance than other methods when the problems involve investment candidates with various lead times under uncertain conditions.