Proposed Discoveries Using Neutrosophic Logic towards  Electrical Energy Recovery Systems Administration

A. A. Salam; Mohamed A. Mohamed; Hanan M. Amer; Musallam Matar Jeailan Hzam AlZubi; Huda  E. Khalid

Authors

A. A. Salam Dept. of Math and Computer Sci., Faculty of Science, Port Said Univ., Egypt
Mohamed A. Mohamed Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt;
Hanan M. Amer Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt;
Musallam Matar Jeailan Hzam AlZubi Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt;
Huda E. Khalid University of Telafer, The Administration Assistant for the President of the Telafer University, Telafer, Iraq;

Keywords:

Neutrosophic Logic, Electrical Energy Harvesting, Renewable Energy Supply Management, Uncertainty Control, Hybrid Energy Systems, Predictive Maintenance, Smart Grids; Dynamic Load Balancing; Solar Energy Scheduling; Piezoelectric Systems.

Abstract

This paper analyzes the use of a statistical logic, namely neutrosophic logic,
which addresses vagueness and proximity in optimizing the performance and management
of various energy harvesters such as solar, piezoelectric, and thermoelectric energy
harvesters. The neutrosophic model allows the investigation of uncertainties associated with
environmental conditions (air, water, etc.), the health of the system, and energy demand
while enabling the design of dynamic and adaptive management strategies. We speculate
context examples being delivered of interfaced energy for solar panels, predictive
maintenance monitoring for piezoelectric harvesters, hybrid-energy system administrative
issues, and dynamic load adjusting in bright lattices. This has a beautiful explanation of just
how well analytic proportions are doing responsively right next to stable during this setup
time of the proposed formation in this flush. Such findings on energy types can pave the way
for future empirical lessons that will prompt bringing these concepts to life as well as
improving energy management technologies.

DOI: 10.5281/zenodo.15514432