Transient Stability Constrained Optimal Power Flow Based On Symplectic Geometric Algorithm

Optimal Power Flow (OPF) is one of the widely adopted tools for power system planning, operation and control. Due to the rapid increase of electricity demand and the deregulation of electricity markets, power systems tend to operate closer to stability boundaries and, as a consequence, resulting in serious damage to national economics and security. In order to ensure the safe and stable of power system, it is necessary to study transient stability constrained optimal power flow (TSCOPF), to seek the strategy of preventive control and emergency control for power system.TSCOPF suffers from the curse of dimensionality as well as unacceptable computational cost. Motivated by the need to perform time domain simulation for online purposes, this paper proposes the Gauss-Legendre Runge-Kutta method to discrete the swing equations of generators which are converted to a Hamiltonian system, making it possible for the application of symplectic integration techniques. The method is with good numerical stability and simple structure. Under the same precision, the step size of the method is6times that of the trapezoidal method. In order to guaranty the robustness of the algorithm, improve the computational efficiency and reduce the memory usage, the combination of reduced-space approach with primal-dual interior point method is used to solve the problem.Numerical simulations on the five systems from WSCC-9to X-3301buses confirmed the validity of the proposed method. Under the condition of large-step, it can keep the higher numerical accuracy, which will improve the computing speed over10times. The proposed method has potentially broad application in power system.