Market-based transmission expansion planning under uncertainty

This paper presents a market-based transmission expansion planning model, which seeks to find investment opportunities that will bring more economic benefits than the costs. Benders decomposition method is used to decompose the whole planning problem into a master problem, which makes investment decisions, and a slave problem, which simulates the operation of the electric market. Uncertainties appearing in the planning process are analyzed systematically and classified into random and non-random uncertainties. Monte Carlo simulation method is applied to simulate random uncertainties, while robustness testing method is employed to incorporate nonrandom uncertainties. The case study illustrates the application of the proposed model in a competitive electricity market with double-sided auctions.