The DOI matches its Crossref record.
Practical Data-Driven Methods to Improve the Accuracy and Detail of Hosting Capacity Analysis
Abstract
Distributed energy resource (DER) hosting capacity of distribution feeders is commonly analyzed with scenario-based methods assuming specific load conditions. For feeders with existing DER, additional processing is necessary to capture conditions of these DERs, that can impact hosting capacity indicators. Only modeling min/max scenarios for the load and DER may not represent realistic worst-case scenarios and may lead to under- or over-estimating the hosting capacity. This paper proposes a method based on historical data that determines a set of scenarios which captures worst-case conditions and enables accurate determination of hosting capacity values. This paper also proposes a probabilistic hosting capacity analysis method that provides valuable information for robust system planner decisions.
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High-resolution time series simulation techniques are computationally complex and expensive.
“However, these simulation techniques are computationally complex, expensive,”
From Methods and Tools for PV and EV Hosting Capacity Determination in Low Voltage Distribution Networks—A Review (2023) · cites this paper as [79]
High-resolution time series simulation better accounts for the stochastic nature of solar PV generation and load demand and captures PV variations at smaller time frames.
“High-resolution time series simulation was introduced in [79,80] to better account for the stochastic nature of solar PV generation and the load demand and to capture PV variations at smaller time frames.”
From Methods and Tools for PV and EV Hosting Capacity Determination in Low Voltage Distribution Networks—A Review (2023) · cites this paper as [79]
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Research works printed but not linked: 8
- 2010, Distribution Test Feeders, IEEE org
- bolognani, 2015, On the Existence and Linear Approximation of the Power Flow Solution in Power Distribution Networks, IEEE Trans Power Syst, pp
- kersting, 2012, Distribution System Modeling and Analysis
- peppanen, 2017, Assessing Energy Storage Accommodation Limits to Aid in Distribution Planning and Operation, IEEE PES General Meeting, 1
- 2017, Distribution Resource Integration and Value Estimation (DRIVE), CEDR Knoxville TN
- newlander, 2016, Distribution Reources Plan - Demonstration A - Enhanced Integration Capacity Analysis, San Diego CA
- qureshi, 0, A Fast Scalable Quasi-Static Time Series Analysis Method for PV Impact Studies using Linear Sensitivity Model, IEEE Trans Sustain Energy (Early Access), 1
- smith, 2016, Defining a Roadmap for Successful Implementation of a Hosting Capacity Method for New York State, Palo Alto CA EPRI Report ID 3002008848
Cited by
Sorted by citations
Umoh, V., Davidson, I., Adebiyi, A., & Ekpe, U. (2023) · Energies · doi:10.3390/en16083609 · Cited by 71
Metadata
- Authors
- Deboever, J., Grijalva, S., Peppanen, J., Rylander, M., & Smith, J.
- Affiliations
- Georgia Institute of Technology (US)
- Electric Power Research Institute (US)
- Venue
- 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC)
- Publisher
- IEEE
- Published
- 2018-06
- Pages
- 3676-3681
- OpenAlex
- W2902087321
- Cited by
- 13
- References
- 0
- Citations by year
- 2025: 1 · 2023: 3 · 2022: 2 · 2021: 3 · 2020: 2 · 2019: 2
- FWCI
- 2.79
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- World Conference on Photovoltaic Energy Conversion (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Thermal Analysis in Power Transmission
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
- Keywords
- hosting capacity, distributed energy resources, distribution feeders, scenario-based assessment, worst-case scenario, historical data, power system planning, loading conditions
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