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.

[1]  Jean-François Toubeau,et al.  Machine learning-assisted outage planning for maintenance activities in power systems with renewables , 2022, Energy.

[2]  Goran Strbac,et al.  Selecting decision trees for power system security assessment , 2021 .

[3]  M. G. Rabbani,et al.  Influence of Large Scale Solar Power on Stability of East West Interconnector System of Bangladesh Power System , 2021, 2021 5th International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT).

[4]  M. G. Rabbani,et al.  Small Signal Stability and Transient Stability improvement of Bangladesh Power System using TCSC, SVC and TCSC, STATCOM based series shunt compensator , 2021, 2021 International Conference on Science & Contemporary Technologies (ICSCT).

[5]  Matthijs J. Warrens,et al.  The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation , 2021, PeerJ Comput. Sci..

[6]  D. Franković,et al.  Enhanced Contingency Analysis—A Power System Operator Tool , 2021, Energies.

[7]  Mohamed I. Mosaad,et al.  Optimal Reliability Study of Grid-Connected PV Systems Using Evolutionary Computing Techniques , 2021, IEEE Access.

[8]  Sherif S. M. Ghoneim,et al.  Near-Optimal PI Controllers of STATCOM for Efficient Hybrid Renewable Power System , 2021, IEEE Access.

[9]  Mohamed I. Mosaad,et al.  Reliability Support of Undependable Grid Using Green Energy Systems: Economic Study , 2021, IEEE Access.

[10]  Sam Yang,et al.  Power Grid Contingency Analysis with Machine Learning: A Brief Survey and Prospects , 2020, 2020 Resilience Week (RWS).

[11]  Jan-Hendrik Menke,et al.  Evaluating Machine Learning Models for the Fast Identification of Contingency Cases , 2020, Applied AI Letters.

[12]  Xiangfei Meng,et al.  Decision Tree for Online Voltage Stability Margin Assessment Using C4.5 and Relief-F Algorithms , 2020, Energies.

[13]  Atul Kumar,et al.  Contingency Ranking for Security Analysis of Power System Network with Incorporation of STATCOM , 2020, 2020 International Conference on Electrical and Electronics Engineering (ICE3).

[14]  Abdullah M. Al-Shaalan,et al.  Contingency selection and ranking for composite power system reliability evaluation , 2020 .

[15]  Arif Nur Afandi,et al.  Performance Index Analysis (PIA) for N-1 Contingency Transmission in 150 kV Electricity System , 2019, 2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE).

[16]  Hwachang Song,et al.  A Reactive Power Compensation Strategy for Voltage Stability Challenges in the Korean Power System with Dynamic Loads , 2019, Sustainability.

[17]  Yacine Rezgui,et al.  Tree-based ensemble methods for predicting PV power generation and their comparison with support vector regression , 2018, Energy.

[18]  Yacine Rezgui,et al.  Predictive modelling for solar thermal energy systems: A comparison of support vector regression, random forest, extra trees and regression trees , 2018, Journal of Cleaner Production.

[19]  Dongbo Zhao,et al.  Load Modeling—A Review , 2018, IEEE Transactions on Smart Grid.

[20]  Florian Schäfer,et al.  Contingency Analysis of Power Systems with Artificial Neural Networks , 2018, 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm).

[21]  Muhammad Quamruzzaman,et al.  Steady State Voltage Vulnerability and Stability Limit Analysis of Bangladesh Power System Using STATCOM as a Shunt Compensator , 2018, 2018 4th International Conference on Electrical Engineering and Information & Communication Technology (iCEEiCT).

[22]  Muhammad Quamruzzaman,et al.  Comparison Between TCSC, SVC and TCSC, STATCOM Based Compensation on East-West Interconnectors of Bangladesh Power System , 2018, 2018 4th International Conference on Electrical Engineering and Information & Communication Technology (iCEEiCT).

[23]  S. Rigatti.  Random Forest. , 2017, Journal of insurance medicine.

[24]  Deepak Joshi,et al.  Contingency analysis of power system by using voltage and active power performance index , 2016, 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES).

[25]  S. V. Nagaraj,et al.  Review of , 2013, SIGACT News.

[26]  Michael Negnevitsky,et al.  A random forest-based approach for voltage security monitoring in a power system , 2015, 2015 IEEE Eindhoven PowerTech.

[27]  Babu Narayanan,et al.  POWER SYSTEM STABILITY AND CONTROL , 2015 .

[28]  F. Wen,et al.  Risk-based security-constrained economic dispatch in power systems , 2013 .

[29]  Claus Leth Bak,et al.  An overview of decision tree applied to power systems , 2013 .

[30]  A. H. Chowdhury,et al.  Application of TCSC and SVC in damping oscillations in Bangladesh Power System , 2012, 2012 7th International Conference on Electrical and Computer Engineering.

[31]  N. N. Bengiamin,et al.  On reactive power compensation , 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.