Results 11 to 20 of about 308,543 (297)
Fast Quasi-Static Time-Series (QSTS) for yearlong PV impact studies using vector quantization
Solar Energy, 2018 Abstract The rapidly growing penetration levels of distributed photovoltaic (PV) systems requires more comprehensive studies to understand their impact on distribution feeders. IEEE P.1547 highlights the need for Quasi-Static Time Series (QSTS) simulation in conducting distribution impact studies for distributed resource interconnection.
Jeremiah Deboever +3 more
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Energies, 2023 Increasing connection rates of rooftop photovoltaic (PV) systems to electricity distribution networks has become a major concern for the distribution network service providers (DNSPs) due to the inability of existing network infrastructure to accommodate
Jude Suchithra +2 more
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Sensors, 2021 Strain measurements using fibre Bragg grating (FBG) optical sensors are becoming ever more commonplace. However, in some cases, these measurements can become corrupted by sudden jumps in the signal, which manifest as spikes or step-like offsets in the ...
Dominik Johannes Marius Fallais +4 more
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Monte Carlo Based Method for Parallelizing Quasi-Static Time-Series Power System Simulations [PDF]
2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), 2018 Both commercial and open source power system simulators run quasi-static time-series (QSTS) simulations sequentially. For yearlong high-resolution load profiles this sequential execution of load flows incurs long computation times. Parallelizing QSTS simulations on multiple processors is one possible way to reduce the computation time.
Aadil Latif, Barry Mather
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Data-Driven Distribution System Load Modeling for Quasi-Static Time-Series Simulation
IEEE Transactions on Smart Grid, 2020 This paper presents a data-driven distribution system load modeling methodology targeting quasi-static time-series (QSTS) simulation. The proposed methodology is appropriate for modeling down to the level of the customer transformer, and it has three main features: 1) both load pattern diversity and intra-second load variability are considered, 2) the ...
Xiangqi Zhu, Barry Mather
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Advances in OpenDSS smart inverter modelling for quasi-static time-series simulations
CIRED - Open Access Proceedings Journal, 2020 The fleet of smart distributed energy resource (DER) inverters is expected to grow rapidly as a result of growing DER penetration levels and requirements in interconnection standards/rules such as IEEE Std 1547-2018. Smart inverters have the potential to help to maintain and/or enhance grid safety, reliability and customer affordability.
Paulo Radatz +3 more
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IEEE Access, 2022 In this paper, a two-stage equalization topology based on Zero-Voltage Switching Quasi-Resonant Converter (ZVS QRC) is proposed to solve the problems of long equalization time and low energy utilization of series lithium-ion battery packs.
Li Liao +5 more
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Probing microplasticity in small scale FCC crystals via Dynamic Mechanical Analysis [PDF]
, 2016 In small-scale metallic systems, collective dislocation activity has been correlated with size effects in strength and with a step-like plastic response under uniaxial compression and tension.
Adhikari, Rana X +4 more
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Nuclear Engineering and Technology, 2020 The investigation into a full-scale 27 m high, by 6 m wide, thermosyphon loop. The simulation model is based on a one-dimensional axially-symmetrical control volume approach, where the loop is divided into a series of discreet control volumes.
R. Swart, R.T. Dobson
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Predetermined time-step solver for rapid quasi-static time series (QSTS) of distribution systems
2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2017 Distribution system analysis with high penetrations of distributed energy resources (DER) requires quasi-static time-series (QSTS) analysis to capture the time-varying and time-dependent aspects of the system, but current QSTS algorithms are prohibitively burdensome and computationally intensive. This paper proposes a novel deviation-based algorithm to
Matthew J. Reno, Robert J. Broderick
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