Contingency analysis and adoption of STATCOM in highly renewable energy penetrated Western Grid of Bangladesh

Abstract

All the countries are in needs of renewable energy (RE) penetration into their power system. As Bangladesh power system (BPS) depends on fossil fuel by 99% of its total generation capacity, it is very much focusing on having RE. In its Western grid, it has planned to install 55 MW wind turbine generator (WTG) and 100 MW solar photovoltaic generator (SPVG). It is expected that the system will be upset from stability perspective. To increase the power system security, contingency analysis is needed. But the power system operation parameters are always variable, with conventional load flow method, it is impossible to carry out contingency analysis according to such variations in parameters. So, this present work adopts machine learning (ML) to predict the contingency analysis by determining the performance indices (PI) with variable operating conditions in a quick time. Decision tree (DT), random forest (RF) and extra tree (ET) methods based supervised learning will be used to predict the result for the contingency analysis. Comparison among these methods will be carried out to get the most suitable one. Also, due to RE penetration, the system will be vulnerable to voltage due to reduction in reactive power. Adoption of static synchronous compensator (STATCOM) will help to reduce the voltage stress of the system. Effective location of it is very essential, so that it can enhance the voltage stability. In this paper, modal analysis technique will be used to find out the optimal location for a STATCOM and to calculate the enhancement in stability.

Keywords

• Renewable energy
• power system security
• contingency analysis
• STATCOM
• modal analysis
• eigenvalue