A Secured and Authenticated State Estimation Approach to Protect Measurements in Smart Grids

Many sectors are in vital requirement to the electric power supply. So, any interval in electric power will affect the operation as well as the ecosystem. Cyber-attacks in power system are focusing on smart grids (SGs) vulnerabilities to cause a partial or total blackout. The main security challenges in the network security of the SG are false data injection (FDI) attacks. The attacker tries to modify the transmitted measurements in FDI attacks via SG objects like smart meters and buses. A well-designed protection scheme for SG authentication is still a daunting task. State estimation (SE) is a significant feature for detecting errors in modern SGs, which provides contributions to both management and control of power grids. A new architecture to solve the problem of FDI attacks is proposed in this study. First, the sensors capture measurements from power grids and encrypt them using an elliptical curve cryptography algorithm. Then, the measurements transmitted to a centralised aggregator, which is responsible for the results of SE. Second, after obtaining the measurements, the aggregator estimates the state using the least-squares weighted SE method with the aid of an improved particle swarm optimisation algorithm. All requests received by the control server are authenticated to ensure that requests are sent from an approved aggregator. The given architecture solves a significant issue of FDI attacks. The proposed architecture conducted on the IEEE 14-bus system. The findings show a positive performance in terms of minimising the estimation error.