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Nishant Narayan

Researcher at Delft University of Technology

Publications -  22
Citations -  454

Nishant Narayan is an academic researcher from Delft University of Technology. The author has contributed to research in topics: Battery (electricity) & Photovoltaic system. The author has an hindex of 11, co-authored 21 publications receiving 287 citations.

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Integrating a photovoltaic storage system in one device: A critical review

TL;DR: This critical literature review serves as a guide to understand the characteristics of the approaches followed to integrate photovoltaic devices and storage in one device, shedding light on the improvements required to develop more robust products for a sustainable future.
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Estimating battery lifetimes in Solar Home System design using a practical modelling methodology

TL;DR: A practical, non-empirical battery lifetime estimation methodology specific to the application and the available candidate battery choices that can potentially help SHS designers in estimating battery lifetimes and therefore making optimal SHS design choices.
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Harvesting Roadway Solar Energy—Performance of the Installed Infrastructure Integrated PV Bike Path

TL;DR: In this paper, the authors highlight the operational challenges and performance parameters using the first-year measured data and show that the theoretically predicted energy yield is compared with the measured energy yield, and theoretical proof is offered that it is not unreasonable to expect an annual energy yield in the upwards of 150kWh/m $2$ with solar road energy harvesting technology.
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Exploring the boundaries of Solar Home Systems (SHS) for off-grid electrification: Optimal SHS sizing for the multi-tier framework for household electricity access

TL;DR: An optimal SHS sizing methodology is presented that minimizes the loss of load probability (LLP), excess energy dump, and battery size while maximizing the battery lifetime.
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Stochastic load profile construction for the multi-tier framework for household electricity access using off-grid DC appliances

TL;DR: This study culminated in devising a stochastic, bottom-up load profile construction methodology with sample load profiles constructed for each tier of the MTF, which exhibits several advantages like scalability and adaptability for specific regions and communities based on community-specific measured or desired electricity usage data.