Energy harvesting in wireless sensor network with efficient landmark selection using mobile actuator

Shawahna, Ahmad; Haque, Md. Enamul; Tozal, Mehmet Engin

doi:10.1109/syscon.2017.7934761

Cited by 3 publications

(1 citation statement)

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“…As a result of the unpredictable nature of energy collecting, managing energy supplies is a difficult endeavour. Wind and solar energy harvesting systems [10][11][12][13] use prediction as a well-known approach of managing renewable resources. In contrast, several contemporary WSNs that harvest energy lack a smart approach for judiciously utilizing the management and harvesting systems.…”

Section: Introductionmentioning

confidence: 99%

Hybrid RSA-ROA Scheduling Algorithm for Minimization of Power Loss and Improving the Renewable with Sustainable Energy Harvesting in Power System

Anitha¹,

Sangtani

Bansal

et al. 2022

Advances in Materials Science and Engineering

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Recently, it has been very common for wireless sensor networks (WSNs) to be used in several applications (surveillance, home automation, and vehicle tracking), as well as in environmental monitoring and wildlife tracking. A typical sensor node has a limited amount of battery life. To overcome this, one method is to use an energy harvesting device to recharge the batteries of sensor nodes. Energy reaping WSNs still lack intelligent strategies for intelligently using both energy organization and harvesting systems, though. To maximize the harvesting of renewable energy sources (RES) and minimize power scheme losses, this study provides an optimal generation scheduling strategy for a power scheme combined with distributed generation (DG) and sustainable energy storage systems (ESSs). The major goal of this work is to make it possible to use RES in a power system while still maintaining a profit. By using ESS management, we are able to get the most out of our renewable energy resources and maximize our harvesting potential. It is also possible to reduce operating losses in the power system by scheduling ESS and controlled generation at the optimal times. Near global optimal solutions are sought using a hybrid algorithm combining Reptile Search Algorithm and Remora Optimization Algorithm (RSA-ROA). The power system operational restrictions are taken into account when formulating and evaluating the optimization issue. It has been tested in a variety of circumstances to see if the proposed strategy is effective. The proposed model has 0.260 J of remaining energy, when the number of rounds is 5000, but the existing techniques have only 0.110 J and 0.045 J for the same number of rounds.

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Section: Introductionmentioning

confidence: 99%