# On-Demand Charging Management Model and Its Optimization for Wireless Renewable Sensor Networks
###### Abstract  
Nowadays, wireless energy transfer (WET) is a new strategy that has the potential to essentially resolve energy and lifespan issues in a wireless sensor network (WSN). We investigate the process of a wireless energy transfer-based wireless sensor network via a wireless mobile charging device (WMCD) and develop a periodic charging scheme to keep the network operative. This paper aims to reduce the overall system energy consumption and total distance traveled, and increase the ratio of charging device vacation time. We propose an energy renewable management system based on particle swarm optimization (ERMS-PSO) to achieve energy savings based on an investigation of the total energy consumption. In this new strategy, we introduce two sets of energies called emin (minimum energy level) and etthresh (threshold energy level). When the first node reaches the emin, it will inform the base station, which will calculate all nodes that fall under ethresh and send a WMCD to charge them in one cycle. These settled energy levels help to manage when a sensor node needs to be charged before reaching the general minimum energy in the node and will help the network to operate for a long time without failing. In contrast to previous schemes in which the wireless mobile charging device visited and charged all nodes for each cycle, in our strategy, the charging device should visit only a few nodes that use more energy than others. Mathematical outcomes demonstrate that our proposed strategy can considerably reduce the total energy consumption and distance traveled by the charging device and increase its vacation time ratio while retaining performance, and ERMS-PSO is more practical for real-world networks because it can keep the network operational with less complexity than other schemes. energy consumption; particle swarm optimization; wireless energy transfer; energy renewable management system; wireless renewable sensor networks 2022222384 20222384 20222384 20222384 2022384 20222384 20222384 20222384 2022384 2022384 2022384 2022384 2022384 2022384 2022384 2022384 2022384 2022384 202384 202384 20  
network. Therefore, it is essential to restore the energy of sensor nodes to equilibrate and extend the network lifetime [4]. At present, there are three categories of solutions existing for the energy replenishment of the sensor nodes, namely energy harvesting [5], wireless energy transfer (WET) [6] and sensor node replacement [7]. Several researchers have used energy harvesting techniques to empower the energy supply towards the sensor nodes, such as solar energy [8] and wind energy [9]. However, due to the variations and changes in the natural environment, the collection rate of energy harvesting techniques is difficult to predict, and its time-varying nature makes it unreliable. Moreover, the replacement of the sensor node is either expensive or it is impracticable due to the dangerous environment. The wireless energy transfer technology has made a breakthrough, by resolving the energy bottleneck of wireless sensor networks and extending their lifetime [10]. The combination of wireless energy transfer and a wireless sensor network is called a wireless renewable sensor network (WRSN). A wireless rechargeable sensor network concerns a WSN that is replenished by wireless energy for sensor nodes using wireless energy transfer techniques. In Ref. [11], the most recent development in WET technology provides valuable knowledge for powering sensor nodes. In contrast to other energy harvesting strategies, WET has several advantages, including immunity from a strict source and receiver management, highly efficient energy transfer, resistance to environmental circumstances (dirt, chemicals and air) and small device size [12]. One of the classic solutions to the mobile charging problems is the traveling salesman problem (TSP) charging protocols [13].