A Probabilistic Transmission Planning Framework for Reducing Network Vulnerability to Extreme Events

Abstract

The restructuring of electric power industry has brought in plenty of challenges for transmission expansion planning (TEP), mainly due to uncertainties. The commonly used probabilistic TEP approach requires the network to meet an acceptable risk criterion. However, a series of blackouts in recent years caused by extreme weather-related events have raised the concerns about network vulnerability through calculating the expected risk value. In this paper, we have proposed the concept that TEP should be economically adjusted in order to make network less vulnerable to extreme events (EEs) caused by climate change, e.g., floods or ice storms. We firstly give the explicit definitions of economic adjustment (EA) index and adjusted risk value. Then we formulate our model as a risk-based decision making process while satisfying the deterministic ${\rm N}-1$ criterion. The proposed approach is tested on the IEEE 118-bus system. Results based on various risk aversion levels are given and comparison studies with other risk-based TEP approaches have been done. Also, sensitivity analysis of parameter setting has been conducted. According to the numerical results, the proposed risk-based TEP model is a flexible decision-making tool, which can help decision makers make a tradeoff between economy and security.