A Novel Approach for Dynamic Congestion Management in Open Power Markets

This paper presents a novel approach for dynamic congestion management (DCM) in an unbundled power system. In the DCM model, the objective function is constructed using the cost of the generation increment and an algebraic nonlinear programming is formulated. To establish the linear inequality of transmission limit constraints and transient stability constraints, generator shift factor and trajectory sensitivity are calculated, with which the nonlinear programming problem transforms into a linear programming. Hence, sequential quadratic programming is employed to assess the generation rescheduling for minimizing the objective function. A case study of DCM is performed on the 10-generator New England test system. Comparison between the proposed DCM and static congestion management (SCM) model verifies the validity of the model and the effectiveness of the method.