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Cong Nam Truong
Researcher at Technische Universität München
Publications - 18
Citations - 607
Cong Nam Truong is an academic researcher from Technische Universität München. The author has contributed to research in topics: Battery (electricity) & Photovoltaic system. The author has an hindex of 8, co-authored 18 publications receiving 487 citations.
Papers
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Economics of Residential Photovoltaic Battery Systems in Germany: The Case of Tesla’s Powerwall
TL;DR: In this paper, the economic benefit of the Powerwall for end-users with respect to various influencing parameters: electricity price, aging characteristics of the batteries, topology of battery system coupling, subsidy schemes, and retrofitting of existing PV systems is analyzed.
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Lithium-ion Battery Cost Analysis in PV-household Application
TL;DR: In this paper, the authors use a multi-parameter economic model which allows profitability estimation for BESS with sensitivity to both technical and economical parameters, such as battery end-of-life criterion, battery ageing behavior, electricity prices and storage investment costs.
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Economic Optimization of Component Sizing for Residential Battery Storage Systems
TL;DR: In this paper, a general method for comprehensive PV-BESS techno-economic analysis and optimization is presented and applied to the state-of-the-art BESS to determine its optimal parameters.
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Evaluation of grid-level adaptability for stationary battery energy storage system applications in Europe
Marcus Müller,Lorenz Viernstein,Cong Nam Truong,Andreas Eiting,Holger C. Hesse,Rolf Witzmann,Andreas Jossen +6 more
TL;DR: Simulation results show that grid challenges, addressed by battery storage systems in low-voltage grids, have positive multiplicative impacts on upper grid levels, reducing local grid demand and lowering power peak stress.
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Analysis and Optimization of Pulse Dynamics for Magnetic Stimulation
Stefan M. Goetz,Stefan M. Goetz,Cong Nam Truong,Manuel G. Gerhofer,Angel V. Peterchev,Hans-Georg Herzog,Thomas Weyh +6 more
TL;DR: In this paper, a nonlinear model of a mammalian axon was used to analyze and optimize the waveform dynamics using a hybrid global-local method, and the optimization objective was to minimize the pulse energy loss.