Advanced computational methods for security constrained financial Transmission Rights

Financial Transmission Rights (FTRs) are financial insurance tools to help power market participants reduce price risks associated with transmission congestion. FTRs are issued based on a process of solving a constrained optimization problem with the objective to maximize the FTR social welfare under power flow security constraints. Security constraints for different FTR categories (monthly, seasonal or annual) are usually coupled and the number of constraints increases exponentially with the number of categories. Commercial software for FTR calculation can only provide limited categories of FTRs due to the inherent computational challenges mentioned above. In this paper, first an innovative mathematical reformulation of the FTR problem is presented, which dramatically improves the computational efficiency of optimization problem. After having re-formulated the problem, a novel non-linear dynamic system (NDS) approach is proposed to solve the optimization problem. The new formulation and performance of the NDS solver is benchmarked against widely used linear programming (LP) solvers like CPLEX™. Tests are performed on both standard IEEE test systems and large-scale systems using data from the Western Electricity Coordinating Council (WECC). The NDS is demonstrated to be comparable, and in many cases outperforms the widely used CPLEX algorithms. The proposed formulation and NDS based solver are easily parallelizable, enabling further computational improvement.