Dynamic load modeling for bulk load-using synchrophasors with wide area measurement system for smart grid real-time load monitoring and optimization

Abstract

Bulk data modeling in a smart grid dynamic network has been performed using an automated load modeling tool (ALMT), an on-load tap changer, and exponential dynamic load modeling. However, studies have observed that a small parameter variation may lead to considerable variations in measuring grid big data. Therefore, this study presents dynamic real-time load modeling, monitoring, and optimization method for the bulk load. The case study was conducted on Sarawak Energy Berhad (SEB), Malaysia. The grid system's real-time data and load modeling achieved the objectives. Dynamic load model was achieved by using load response in MATLAB Simulink environment. This paper also includes new parameter estimations of the load composition at the selected bus. The simulation results of load models were compared with the recorded data by applying an event of bus tripping time interval. The Least Square Error Method was used to converge the estimated parameter values on load composition and compared with the actual recorded data until optimized load models were achieved. This work is a precious and significant contribution to utility research to identify, monitor, and optimize the most appropriate representation of system loads.