Research On The Optimal Power Flow Algorithm With Transient Stability Constraints In Power System

Transient stability preventive control has an important role to ensure the safe and stable operation of power grid, transient stability constrained optimal power flow(TSCOPF) which is the core problem of transient stability preventive control, has been paid more attention by researchers in recent years. With the continuous expansion of power system and the acceleration of power market reform, Safe and stable and economic operation of the power system face unprecedented challenges. The contradiction between safety stability and economy in power system are increasingly highlighted. The study of practical optimization model and efficient algorithm for transient stability preventive control has a certain practical significance and practical value to optimize the operation condition of power grid. In this paper, it establishes a transient stability constrained optimal power flow new fuzzy model which is more suitable for the actual characteristics of the system. Applying collaborative evolutionary ideas to improve the particle swarm optimization(PSO) algorithm construct effective collaborative evolutionary particle swarm optimization algorithm to solve the model. And it puts forward to further accelerate the strategy to improve the efficiency of the algorithm. The research results are as follows:At first, in terms of modeling, it proposes a mathematical method which applies fuzzy set theory to optimal power flow with transient stability constraints, and combining with the practical features of power system, improves the traditional transient stability constrained optimal power flow model. Considering uncertainty of practical transient stability criterion and the margin requirements of voltage constraints. Fuzzy set theory is used to fuzzy the rotor angles constraint,voltage constraint and the objective function,and then,TSCOPF fuzzy model is established by max-min methods.Secondly, for the algorithm, it establishes collaborative evolutionary particle swarm optimization algorithm which is suitable for transient stability constrained optimal power flow as a large-scale nonlinear optimization problem. Running mechanism of collaborative evolutionary algorithm and PSO algorithm were analyzed particularly. It proposes the general framework of collaborative evolutionary algorithm and the improved particle swarm algorithm including adaptive inertia weight and adaptive learning factors. Combining with the advantage of collaborative evolutionary algorithm which has strong global exploring ability, and good convergence performance of simple PSO algorithm, it constructs the collaborative evolutionary particle swarm optimization algorithm which has comprehensive performance.At last, the collaborative evolutionary particle swarm optimization algorithm was applied to solve the TSCOPF fuzzy optimization problem. In order to enhance the efficiency of the optimization algorithm, a the transient stability simulation early terminated strategy and a master-slave parallel technology are applied to the algorithm. the test results on the New England 10-machine system demonstrate the proposed method is effective and feasible.