Simulation approach to improve power analysis network for integration of distributed generation

Abstract

The capability of the classical network to support the level penetration of Distribution Generation (DG) has been present to analysis how to achieve a better integration of flexible demand of Electrical Networks(Mesh and Radial systems). Based on this analysis, two simulation algorithms have been proposed to reduce CPU time and memory, can help the grid operator to assess power situation and increase penetration level of DG.Firstly, It deals with an algorithm developed for power load flow studies in electrical power systems using Schur complement method. By dividing Jacobian matrix into two separated matrices with reasonable computation time, It could be avoided divergence of the solution. A next step that was applied concerned Data Compression for the Simulated algorithms conceived to study load flow calculation in electrical power systems. Real time monitor of grids required less computation time in calculation of power system analysis. It proposed an algorithm based on Run Length Encoding (RLE) method where no zero values are included. Matlab results obtained by applying these algorithms match the analytical approaches. Results have been compared with Newton Raphson and Fast Decoupled methods in term of influence of convergence properties and it's efficiency. These methods have been implemented and tested on several IEEE bus test systems.

Improved newton-raphson with schur complement methods for load flow analysis

“…The Schur complement technique is a procedure to eliminate the interior variables in each subdomain and derive a global, reduced in size and linear system involving only the interface variables. Schur method can be used to separate the unknown variables in interface unknown variables and sub-domain internal unknown variables meaning that the off-diagonal effects can be reduced or eliminated [19]. This algorithm has been applied successfully to reduce computation time of load flow iterations, memory required and convergence strategy.…”