Neutrosophic logic in energy efficiency and the circular economy: uncertainty modeling in power grids

Abstract

: This study addresses the challenge of uncertainty, variability, and indeterminacy in smart 
grid energy management by applying neutrosophic logic as a novel optimization and detection 
framework. A computational methodology was developed to integrate renewable energy 
generation, battery storage, and consumption under neutrosophic modeling, comparing its 
performance with classical, fuzzy, and machine learning approaches. The neutrosophic economic 
dispatch model enabled improved generation scheduling resilience, optimized battery degradation 
prediction, and optimized charging cycles. In parallel, a neutrosophic detection mechanism was 
designed to identify energy losses, anomalous consumption, and potential fraud in near real-time. 
The case study results demonstrate that the neutrosophic approach significantly reduced operating 
costs (USD 8,500 versus USD 15,000–20,000 for other models), maximized the economic benefit of 
actual detections (USD 940, the highest among the tested models), and yielded the most favorable 
net balance (−USD 7,560). These results indicate that neutrosophic models outperform traditional 
and fuzzy approaches in both cost efficiency and system reliability. 

DOI: 10.5281/zenodo.17078978