OPTIMAL SCHEDULING AND MANAGEMENT OF A SMART CITY WITHIN THE SAFE FRAMEWORK

Abstract

This paper proposes an enhanced cyber secure energy and data transaction framework for the optimal operation and management of the smart city. Recently, the concept of smart city within the power systems has taken the center stage. Although the power system full monitoring and accessibility is guaranteed through the smart city concept, the risk of cyber-attacks to the system has been promoted, severely. With this in mind, in this paper an effective smart city model including the smart grid, smart transportation systems (STSs) that consist of the metro and electric vehicles (EVs), microgrid and smart energy hub (EH) is presented. In the proposed model, an improved directed acyclic graph (DAG) approach is represented in order to enhance the security of data transaction within the smart city. In this approach, a security layer is added to the blockchain which will prevent the cyber hackers access to the system information. An effective energy management schedule is also developed in this paper. To do so, an intelligent priority selection (IPS) based on advanced math operators is provided to allocate the metro-owned charging stations (MCSs), optimally. Furthermore, the unscented transform (UT) is utilized to handle the uncertainty of the system parameters. The results showed that the proposed IPS could improve the method CPU time over 75% compared to other well-known meta-heuristic methods in the area. Moreover, the results showed that the proposed framework has remarkably reduced the run time and increased the accuracy of the solution compared to the other metaheuristic algorithms.