Improved Sequential Quadratic Programming Approach for Optimal Distribution Generation Deployments via Stability and Sensitivity Analyses

摘要

Integrating distributed generation into an electric power system has an overall positive impact on the system. This impact can be enhanced via optimal distributed generation placement and sizing. In this article, the location issue is investigated through stability and sensitivity analyses. Distributed generation rating, on the other hand, is formulated as a non-linear optimization problem subject to high non-linear equality and inequality constraints. Sizing the distributed generation optimally is performed using a modified sequential quadratic programming method. The sequential quadratic programming is improved by incorporating the fast and flexible radial power flow routine, which was developed in an earlier work, to satisfy the power flow requirements. The proposed equality constraints satisfaction approach drastically reduces computational time requirements. This hybrid method is compared with conventional sequential quadratic programming, and the results are in favor of the proposed technique. The approach is designed to handle optimal single and multiple distributed generation placement and sizing with specified and unspecified power factors. A 69-bus distribution system is used to investigate the performance of the proposed approach.