New modified algorithm: θ-turbulent flow of water-based optimization

Naderipour, Amirreza; Davoudkhani, Iraj Faraji; Abdul‐Malek, Zulkurnain

doi:10.1007/s11356-021-16072-x

Cited by 7 publications

(1 citation statement)

References 58 publications

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“…Later studies consider in energy gathering from remote system have consolidated a count of features of such systems that run from physical layer security [13][14][15][16][17] to cognitive radio systems 18,19 and nonorthogonal numerous get to. 20,21 An IoT sensor works in a battery-free way, in this way, expanding the system quality and decreasing the operating system.…”

Section: Introductionmentioning

confidence: 99%

Optimal energy management in smart grid with internet of things using hybrid technique

Nayak¹,

Kumar²

2022

Energy & Environment

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This paper proposes an energy management system (EMS) in smart grid based on Internet of Things (IoT) configuration using hybrid approach. The proposed approach is joint execution of Multi-fidelity meta-optimization and Turbulent Flow of water based optimization (TFWO), hence it is known as M2FWO technique. The main objective of this proposed EMS is to better manage power with the resources of Smart Grid by constantly monitoring data from the IoT-based communication framework. Here, each home device is connected to data acquisition module is utilized to facilitate the demand response (DR) growth for energy management system in smart grid. The framework collects DR from every smart home device and then transmits the data to the centralized server. The transmitting data is enabled by M2FWO method. The smart grid IoT framework enhances the feasibility of these networks makes better use of obtainable resources. The proposed system is in charge to satisfy the total supply with energy requirement. Finally, the proposed model is stimulated on MATLAB/Simulink site, then the efficiency is examined with existing methods.

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