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Article Citation - WoS: 1Citation - Scopus: 1Normalized Thermodynamic Model for Intermittent Energy Systems and Application To Solar-Powered Adsorption Cooling Systems(int Center Applied thermodynamics, 2011) Taylan, Onur; Baker, Derek K.; Kaftanoglu, BilginA new normalized model is developed to quantify and explore trends in coincidence of supply and demand in generic intermittent energy systems as key design and operating parameters are varied. This novel model is applied to seasonal-transient simulations for a solar-thermal powered adsorption system with and without heat recovery to investigate the coincidence between the solar-supplied cooling power and cooling load in terms of seasonal solar and loss fractions. Additionally, the system's basic performance trends are investigated as a number of parameters are varied. Results for the conditions explored include the following. The solar fraction increases and the loss fraction decreases with increases in storage capacity, and both fractions decrease with increases in maximum bed temperature. The required evacuated tube collector area is smaller than the flat plate collector area while the required mass of adsorbent is independent of collector and adsorption cycle types. Simulation results also show the effects of operating conditions and several design parameters on the system's COP.Article Citation - WoS: 5Citation - Scopus: 6Deployment and Implementation Aspects of Radio Frequency Fingerprinting in Cybersecurity of Smart Grids(Mdpi, 2023) Awan, Maaz Ali; Dalveren, Yaser; Catak, Ferhat Ozgur; Kara, AliSmart grids incorporate diverse power equipment used for energy optimization in intelligent cities. This equipment may use Internet of Things (IoT) devices and services in the future. To ensure stable operation of smart grids, cybersecurity of IoT is paramount. To this end, use of cryptographic security methods is prevalent in existing IoT. Non-cryptographic methods such as radio frequency fingerprinting (RFF) have been on the horizon for a few decades but are limited to academic research or military interest. RFF is a physical layer security feature that leverages hardware impairments in radios of IoT devices for classification and rogue device detection. The article discusses the potential of RFF in wireless communication of IoT devices to augment the cybersecurity of smart grids. The characteristics of a deep learning (DL)-aided RFF system are presented. Subsequently, a deployment framework of RFF for smart grids is presented with implementation and regulatory aspects. The article culminates with a discussion of existing challenges and potential research directions for maturation of RFF.
