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Due to intelligent communication, smart grids have been further developed compared to traditional power grids. In order to compensate for the growing demand for quality of service (QoS) requirements, the cognitive radio sensor network (CRSN) is being adopted. Most of the prevailing methods fail to meet the user's spectrum demand, which causes the delay in data transmission. Hence to improve the spectrum allocation in CRSN, the deep Q-probabilistic algorithm based rock hyraxes swarm optimization (RHSO) is proposed in this work. The channel requested user's id is stored in Q-table that is placed in the sink node. RHSO selects the high priority user from Q-table that search for the early requested user in the Q-table. The vacant channel is detected by a deep probabilistic neural network (DPNN) based on the user request. The DPNN search for vacant channel based on sleeping and active time. The proposed method improves channel allocation with reduced time by using DPNN. The proposed method is implemented in the Matlab platform. The proposed method offers higher throughput of 280 kbps for 25 idle channels by reducing the latency to 2 ms and retransmission probability to 0.01. These performance measures show the efficacy of the proposed method in channel allocation. [ABSTRACT FROM AUTHOR]

Summary: The grid is a platform of distributing the power to the consumers; if an automatic controlling and monitoring are connected with the grid, it referred to as smart grid (SG). Self‐healing is the approach of restoring the unaffected areas without affecting the system performance. The term restoration is if a fault occurs on a distribution system, it must be isolated; after that, it can be reconfigured to restore the unaffected areas. The distribution system cannot work as efficient without the self‐healing approach because it will affect the unaffected areas without any proper reason. This paper proposed a multiagent system with controlled voltage (MAS‐CV) along with self‐healing of wireless sensor network (WSN) with proportional integral derivative (PID) controller in smart grid. At initial, the magnetic flux sensors are placed in the pole transformer for detection of flux leakage. The sensed data are transferred to the distribution grid, where the multiagent system (MAS) is established to carrying out the load restoration process (i.e., self‐healing). Connection agents (CA), monitor agent (MA), main feeder agent (MFA), backup feeder agent (BFA), supporting feeder agent (SFA), and local agent (LA) are the agents presented in the paper. Each agent is communicating via agent communication language (ACL) for the restoration process; after all the loads are restored, the voltage drop of the system is controlled by the proportional integral derivative controller. The simulation results of the proposed method show that the restoration of loads is improved and number of switching is reduced with improved data transmission. Thus, the cost of the proposed method is reduced by the reduced switches. At last, the controlled power from the distribution grid is send to the consumer. [ABSTRACT FROM AUTHOR]