Researching On Dynamic Optimal Of Active Power In Power Systems

Today, with the development and expansion of the power system and power network, The active power optimal dispatch of electric power system occupies a irreplaceable role. This paper is mainly to explore and study in the field of power system calculation and dynamic active power optimization. The main contents include the power flow calculation, incremental transmission losses, optimal scheduling etc.First of all, the solution of the admittance matrix and the linear equations is improved and optimized in the power flow calculation, the corresponding rapid method is proposed in this paper. Through the example analysis, it proves the feasibility and efficiency of the fast method. Secondly, This paper introduces three methods of rapid flow calculation. Compared with the traditional method, the speed of new method is greatly improved and achieves fast and efficient computation of power flow. And then, This paper introduces two kinds of incremental transmission losses : Rectangular coordinate admittance matrix method and Jacobi matrix method. A brief derivation of these two methods is given and the each algorithm is improved and optimized. Through the comparison of numerical results, the improved algorithm can greatly improve the speed of solving incremental transmission losses, it lays the foundation for the application of dynamic active power optimization. Next, In this paper, the model and classical algorithm of dynamic active power optimization are introduced from the static active power optimization to the dynamic active power optimization. Using the admittance matrix of incremental transmission losses method in dynamic active power optimization, the optimization result is more accurate, the objective function is smaller, and the economic benefit is improved. Finally, the improved algorithm of each part is integrated into the whole dynamic active power optimization process. Compared with the dynamic active power optimization algorithm without improvement, the feasibility and rapidity of the improved algorithm are proved.