Cloud Based Optimization for Real-Time Voltage Stability Enhancement Using IoT

Voltage stability in a power system plays a crucial role to ensure reliable and uninterrupted operation. The voltage stability of the transmission line is influenced by line reactance, receiving-end reactive power and sending-end bus voltage. Voltage Stability Indices, which quantify these variables and provide a value to do quantitative analysis and decision on voltage stability. In this paper, suitable voltage stability enhancement actions are identified by solving an optimization problem where the cumulative voltage stability index of the grid is minimized using Genetic Algorithm. Initially, the proposed algorithm is tested on IEEE 5 Bus System with shunt, series, and shunt and series compensation with the objective to improve the voltage stability index. Later, to ensure the self-healing capability, the proposed optimization technique is implemented on the real-time IEEE 5 Bus Scaled down power system. The real-time information of the system is made available in the cloud using Internet of Things(IoT). The optimization based on Genetic Algorithm proposed is developed in the cloud. The decisions to enhance voltage stability through compensation by the algorithm are automatically incorporated into the system using cloud and edge based IoT technology. Edge is used to implement the compensation decision taken in cloud at various buses of the power system. The proposed architecture with optimization based decision is tested on a scaled down model of the IEEE 5-bus system. The results indicate that the proposed algorithm significantly enhances the voltage stability.