Transient stability prevention control optimization algorithm based on adjoint sensitivity

Abstract

The invention relates to the technical field of power system preventive control and particularly relates to a transient stability prevention control optimization algorithm based on adjoint sensitivity. The algorithm comprises the steps of (S1) establishing a transient stability constrained optimal power flow (TSCOPF) model with minimum fuel cost of a whole system unit as a target function and witha line power flow constraint, a node voltage constraint, unit power output upper and lower limit constraints, an initial value equation of a system state at the time of failure and a unit power anglestability constraint after the failure as constraints, (S2) converting the process constraint of unit power angle stability after the failure into an integral constraint through constraint transformation, (S3) calculating one-order step information of the integral constraint in step (S2) by using a companion sensitivity analysis method, and (S4) solving a nonlinear optimization problem in step (S2) by using a program frame of an optimization layer and a simulation layer. The method provided by the invention has better convergence and higher computational efficiency compared to other methods in solving a TSCOPF problem.

Description

technical field [0001] The invention relates to the technical field of power system preventive control, in particular to an optimization algorithm for transient stability preventive control based on adjoint sensitivity. Background technique [0002] Modern power systems have higher and higher requirements for stability. Preventive control is the first line of defense for the safe operation of the power system. Its main task is to seek an optimal system operating point by adjusting the output of the generator, so that the system can still ensure its stability when it encounters a fault. [0003] The essence of transient stability preventive control is the optimal power flow problem (TransientStability Constrained Optimal Power Flow, TSCOPF) considering the constraints of system transient stability. Compared with the conventional optimal power flow problem, TSCOPF has added Differential-Algebraic Equations (DAE) to describe the dynamic characteristics of the system. How to de...

AI Technical Summary

Problems solved by technology

[0004] At present, there are mainly the following mainstream methods for dealing with DAE in TSCOPF: 1) Numerical difference dispersion method: that is, using numerical difference formulas such as implicit trapezoidal integration, and applying stability constraints to the state variables of DAE at multiple discrete time points, The full difference method is a typical representative of this type of method. The defect of this method is that it greatly increases the dimension of the optimization problem, and when the system is large, it will face the dilemma of dimensionality disaster; 2) Sequential method: through the DAE Numerical integration is used to calculate the sensitivity of transient stability constraints to the initial value of DAE, and then the gradient optimization method is used to solve the nonlinear optimization problem. However, when complex dynamic component models are considered, the time consumption of numerical integration by this method will increase significantly, among which The multiple shooting method is an improved algorithm of this kind of method, which can improve the calculation efficiency to a certain extent; 3) The method based on energy function: establish a stability criterion based on the transient energy function, so as to convert the prevention and control problem into A conventional nonlinear optimization problem, but the selection of the energy function often faces difficulties

Images