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- MakaleAçık Erişim2026Scopus SJRQ1Real-time photovoltaic voltage data-driven dynamic green s-box generation framework for smart grid security
Aydın, Yılmaz; Garipcan, Ali Murat; Özkaynak, Fatih
In this study, a dynamic substitution box (s-box) generation method is proposed using real-time voltage data obtained from photovoltaic (PV) panels as an environmentally sensitive entropy source. These data, affected by environmental conditions such as solar radiation and temperature, exhibit irregular and unpredictable temporal behavior, offering strong potential for cryptographic randomness generation. In this context, the 0–1 test, Kolmogorov Entropy (KE), scale-index analysis, and the National Institute of Standards and Technology (NIST) SP 800-22 test suite are applied to PV voltage data collected at 1-minute intervals, experimentally confirming their chaotic dynamics and high-entropy characteristics. Following appropriate preprocessing and nonlinear mathematical transformations, the validated data are utilized to generate 8-bit s-box structures. The cryptographic strength of the generated s-boxes is quantitatively evaluated using standard security metrics, including nonlinearity (NL), Differential Probability (DP), Linear Probability (LP), Strict Avalanche Criterion (SAC), and Bit Independence Criterion (BIC). The findings reveal that PV data can serve as a functional resource not only for energy monitoring but also for randomness-based cryptographic construction. This approach enables lightweight cryptographic solutions for resource-constrained edge devices requiring <1 KB of memory and supports context-aware data security in renewable energy infrastructures.
- MakaleYalnız künye2022Scopus SJRQ2A mathematical programming model for facility location optimization of hydrogen production from renewable energy sources
Derse, Onur; Göçmen, Elifcan; Yılmaz, Ebru; Erol, Rızvan
Fossil fuels are the primary energy sources and meet the global energy demands. However, environmental and health problems related with these sources boosted the demand for renewable energy sources. Hydrogen, as an energy carrier has a growing potential for solving these problems. In this article, a mathematical programming model that integrates the production, storage and transportation, safety, location, and staff assignment decisions is presented considering minimization of costs. Although most of the studies focus on location, distribution, storage decisions of hydrogen energy networks, the article also includes production, safety and staff assignment decisions to make this problem more practical. Furthermore, we also investigate the set covering constraint will ensure that each region is covered by minimum number of the hydrogen facilities. The developed model ensures a balance between location, distribution, storage, production, safety and staff decisions by installing two production facilities by assigning total 9 warehouses, 22 tank trucks, 12100 km pipeline, 35 staffs under distance constraint 2000 km in regions 1 and 5. The computational results indicate that the proposed model produces effective solutions for the coverage to all region and minimum total cost for real-case situations.
AtıfScopus20WoS16OpenAlex29
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