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Panos Seferlis
Researcher at Aristotle University of Thessaloniki
Publications - 164
Citations - 2971
Panos Seferlis is an academic researcher from Aristotle University of Thessaloniki. The author has contributed to research in topics: Organic Rankine cycle & Renewable energy. The author has an hindex of 25, co-authored 153 publications receiving 2416 citations. Previous affiliations of Panos Seferlis include McMaster University.
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Power management strategies for a stand-alone power system using renewable energy sources and hydrogen storage
TL;DR: A stand-alone power system based on a photovoltaic array and wind generators that stores the excessive energy from renewable energy sources (RES) in the form of hydrogen via water electrolysis for future use in a polymer electrolyte membrane (PEM) fuel cell is currently in operation at Neo Olvio of Xanthi, Greece.
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Optimum design and operation under uncertainty of power systems using renewable energy sources and hydrogen storage
TL;DR: A systematic design approach is proposed that enables the simultaneous consideration of synergies developed among numerous sub-systems within an integrated power generation system and the uncertainty involved in the system operation.
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Toward Optimum Working Fluid Mixtures for Organic Rankine Cycles using Molecular Design and Sensitivity Analysis
TL;DR: In this paper, a Computer-Aided Molecular Design (CAMD) method for the synthesis and selection of binary working fluid mixtures used in ORC is presented. But the method consists of two stages, initially seeking optimum mixture performance targets by designing molecules acting as the first component of the binaries.
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Systematic Methods for Working Fluid Selection and the Design, Integration and Control of Organic Rankine Cycles—A Review
TL;DR: A review of emerging approaches with a particular emphasis on computer-aided design methods is presented in this article, where a number of approaches have been developed that address the systematic selection of efficient working fluids as well as the design, integration and control of ORCs.
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A two-layered optimisation-based control strategy for multi-echelon supply chain networks
TL;DR: A two-layered optimisation-based control approach for multi-product, multi-echelon supply chain networks with independent production lines is presented and exhibits good dynamic performance under both stochastic and deterministic demand variations.