Rapid QSTS Simulations for High-Resolution Comprehensive Assessment of Distributed PV
Open accessAbstract
The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modeling and impact analysis. Unlike conventional scenario-based studies, quasi-static time-series (QSTS) simulations can realistically model time-dependent voltage controllers and the diversity of potential impacts that can occur at different times of year. However, to accurately model a distribution system with all its controllable devices, a yearlong simulation at 1-second resolution is often required, which could take conventional computers a computational time of 10 to 120 hours when an actual unbalanced distribution feeder is modeled. This computational burden is a clear limitation to the adoption of QSTS simulations in interconnection studies and for determining optimal control solutions for utility operations. The solutions we developed include accurate and computationally efficient QSTS methods that could be implemented in existing open-source and commercial software used by utilities and the development of methods to create high-resolution proxy data sets. This project demonstrated multiple pathways for speeding up the QSTS computation using new and innovative methods for advanced time-series analysis, faster power flow solvers, parallel processing of power flow solutions and circuit reduction. The target performance level for this project was achieved with year-long high-resolution time series solution…
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Time series simulation techniques for HC calculation are computationally complex, expensive, and time-consuming.
“However, these simulation techniques are computationally complex, expensive, and time-consuming, and this has led to the development of faster methods to speed up the time series-based HC calculation simulations [81].”
From Methods and Tools for PV and EV Hosting Capacity Determination in Low Voltage Distribution Networks—A Review (2023) · cites this paper as [81]
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Umoh, V., Davidson, I., Adebiyi, A., & Ekpe, U. (2023) · Energies · doi:10.3390/en16083609 · Cited by 71 · see citing works
Impact of Electric Vehicle customer response to Time-of-Use rates on distribution power grids
Birk Jones, C., Vining, W., Lave, M., Haines, T., Neuman, C., Bennett, J., & Scoffield, D. R. (2022) · Energy Reports · doi:10.1016/j.egyr.2022.06.048 · Cited by 69 · see citing works
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- Authors
- Sandia National Laboratories (SNL-CA), L., Broderick, R., USDOE Office of Energy Efficiency and Renewable Energy (EERE), R. P. O. S. E. T. O., (NNSA), U. N. N. S. A., Sandia National Laboratories (SNL-NM), A., National Renewable Energy Laboratory (NREL), G., Georgia Institute of Technology, A., CYME International T&D, Q. (., Electric Power Research Inst. (EPRI), K., Reno, M., Lave, M., Azzolini, J., Blakely, L., Galtieri, J., Mather, B., Weekley, A., Hunsberger, R., Chamana, M., Li, Q., Zhang, W., Latif, A., Zhu, X., Grijalva, S., Zhang, X., Deboever, J., Qureshi, M., Therrien, F., Lacroix, J.-S., Li, F., Belletete, M., Hebert, G., Montenegro, D., & Dugan, R.
- Affiliations
- Sandia National Laboratories California (US)
- National Laboratory of the Rockies (US)
- Georgia Institute of Technology (US)
- Electric Power Research Institute (US)
- CYME International T&D, Quebec (Canada)
- ORCID
- Published
- 2021-03-01
- OpenAlex
- W3160135091
- Cited by
- 8
- References
- 0
- Citations by year
- 2023: 3 · 2022: 3 · 2021: 2
- Type
- report
- Language
- en
- Open access
- green
- www.osti.gov
- Locations
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Funders
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
- USDOE National Nuclear Security Administration (NNSA)
- DOE (NA0003525, AC04-94AL85000)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid and Power Systems
- Keywords
- quasi-static time-series simulation, distributed photovoltaic generation, computational efficiency, parallel computing, circuit reduction, distributed energy resources, time series analysis
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