Congestion management in electricity markets with uncertain infeeds and commitment decisions

Congestion management is crucial to maintain an efficient and reliable power system operation, and thus it is an important task for any transmission system operator. Different congestion management approaches are currently implemented by different TSOs. In this paper, we consider two market schemes. The first one considers the transmission constraints both on a day-ahead (DA) basis and in real-time (RT). This scheme is relevant to centralized markets. The second market scheme considers the transmission constraints only in RT, and is relevant to decentralized markets. We quantitatively compare the congestion management in these market schemes, in a power system with thermal and wind generation, as we vary (i) the share of thermal units, (ii) the wind penetration level, and (iii) the congestion level. For this purpose, we formulate a DA and a RT market model. The DA market is formulated as a two-stage stochastic optimization problem, and the RT market is formulated as a stochastic optimization problem with receding horizon that uses short-term wind power scenarios. We demonstrate the performance of the proposed scheme in the IEEE 24-bus Reliability Test System. The results show that as the share of inflexible units increases, and when congestion occurs, it is more efficient to implement the congestion management in the DA market. However, in systems with a large share of flexible units, the two congestion management schemes achieve similar results.