Health monitoring and analysis of photovoltaic (PV) systems are critical for optimizing energy efficiency, improving reliability, and extending the operational lifespan of PV power plants. Effective fault detection and monitoring are vital for ensuring the proper functioning and maintenance of these systems. PV power plants operating under fault conditions show significant deviations in current-voltage (I-V) characteristics compared to those under normal conditions.
View Article and Find Full Text PDFElectric furnaces play an important role in many industrial processes where precise temperature control is essential to ensure production efficiency and product quality. Traditional proportional-integral-derivative (PID) controllers and their modified versions are commonly used to maintain temperature stability by reacting quickly to deviations. In this study, the real PID plus second-order derivative (RPIDD) controller is introduced for the first time for industrial temperature control applications, which is a novel alternative that has not yet been investigated in the literature.
View Article and Find Full Text PDFThe rapid global adoption of electric vehicles (EVs) necessitates the development of advanced EV charging infrastructure to meet rising energy demands. In particular, community parking lots (CPLs) offer significant opportunities for coordinating EVs' charging. By integrating energy storage systems (ESSs), renewable energy sources (RESs), and building prosumers, substantial reductions in peak load and electricity costs can be achieved, while simultaneously promoting environmental sustainability.
View Article and Find Full Text PDFAn energy material has been developed using a one-step chemical reduction method, incorporating silver nanoparticles (AgNPs) that encapsulate micro-sized silicon (mSi) flakes. SEM investigation revealed complete encapsulation of silicon flakes by AgNP's dendritic structure, EDX confirmed the deposition of Ag on Si flakes. Raman spectroscopy confirmed the formation of silver and silicon oxides.
View Article and Find Full Text PDFThe integration of Electric Vehicles (EVs) into power grids introduces several critical challenges, such as limited scalability, inefficiencies in real-time demand management, and significant data privacy and security vulnerabilities within centralized architectures. Furthermore, the increasing demand for decentralized systems necessitates robust solutions to handle the growing volume of EVs while ensuring grid stability and optimizing energy utilization. To address these challenges, this paper presents the Demand Response and Load Balancing using Artificial intelligence (DR-LB-AI) framework.
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