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Application of internet of things (IOT) for optimal energy management in distribution system using hybrid strategy: a SPOA-RBFNN strategy

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Abstract

This paper presents optimal energy management for distribution system with Internet of Things (IOT) using hybrid system. The proposed hybrid system is joint performance of Student Psychology Optimization Algorithm (SPOA) and Radial Basis Function Neural Network (RBFNN) and therefore called SPOA-RBFNN strategy. The main objective of the research work is the optimal energy management through the framework of internet of things and the reduction of costs. In the proposed system, the distribution system is interconnected through the data acquisition module is an IOT object with a unique IP address resulting at large wireless mesh network of devices. The framework collects the RES and load data through centralized server. The collected data is processed by the SPOA-RBFNN strategy. In addition, the proposed system is in charge for meeting the supply and energy demand. This proposed technique reduces the overall system operating costs and increases energy security. Finally, the proposed model is run on the MATLAB/Simulink platform and its performance is compared with other systems.

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  1. Department of Electrical and Electronics Engineering, Kakatiya Institute of Technology and Science, Warangal, India

    B. Vijay Kumar

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Correspondence to B. Vijay Kumar.

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Vijay Kumar, B. Application of internet of things (IOT) for optimal energy management in distribution system using hybrid strategy: a SPOA-RBFNN strategy. J Ambient Intell Human Comput 14, 3947–3961 (2023). https://doi.org/10.1007/s12652-022-04463-y

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