Time-series analysis of photovoltaic distributed generation impacts on a local distributed network
Open accessAbstract
Increasing penetration level of photovoltaic (PV) distributed generation (DG) into distribution networks will have many impacts on nominal circuit operating conditions including voltage quality and reverse power flow issues. In U.S. most studies on PVDG impacts on distribution networks are performed for west coast and central states. The objective of this paper is to study the impacts of PVDG integration on a local distribution network based on real-world settings for network parameters and time-series analysis. PVDG penetration level is considered to find the hosting capacity of the network without having major issues in terms of voltage quality and reverse power flow. Time-series analyses show that distributed installation of PVDGs on commercial buses has the maximum network energy loss reduction and larger penetration ratios for them. Additionally, the penetration ratio thresholds for which there will be no power quality and reverse power flow issues and optimal allocation of PVDG and penetration levels are identified for different installation scenarios.
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Compared to residential and industrial load profiles, a higher reduction of losses was observed in the case of PV systems supplying commercial loads, mainly due to the coincidence of demand and PV generation.
“Compared to residential and industrial load profiles, a higher reduction of losses was observed in the case of PV systems supplying commercial loads.This was mainly due to the coincidence of demand and PV generation.”
From Methods and Tools for PV and EV Hosting Capacity Determination in Low Voltage Distribution Networks—A Review (2023) · cites this paper as [75]
The Distributed Residential Installation section says loss reduction was smaller than with distributed commercial PV, and the Conclusion attributes the commercial result to better alignment of demand with solar irradiance. The paper does not report a separate industrial-PV installation comparison, so the claimed advantage over industrial loads is not established. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThe time series method typically uses 24-h generated time series data profiles based on average demand and generation values, least consumption and highest generation values, or grid-dependent scenarios of PV generation and load consumption.
“The time series profiles depend on the availability of requisite data, hence it typically uses 24-h generated time series data profiles based on average demand and generation values [31], least consumption and highest generation values [31], or some grid-dependent scenarios of PV generation and load consumption [29,75].”
From Methods and Tools for PV and EV Hosting Capacity Determination in Low Voltage Distribution Networks—A Review (2023) · cites this paper as [75]
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Impact of widespread photovoltaics generation on distribution systems
Thomson, M., & Infield, D. G. (2007) · IET Renewable Power Generation · doi:10.1049/iet-rpg:20060009 · Cited by 350 · cited 1× · see citing works
“These voltage fluctuations and rises result in increased voltage regulator and tap operations, which significantly decrease their lifetime of use [8].”
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Research works printed but not linked: 16
- S. Kann, M. Shiao, S. Mehta, C. Honeyman, and N. Litvak, "US solar market insight report: 2013 year-in-review-Executive summary," Boston, MA, 2014.
- F. Katiraei and J. Aguero, "Solar PV Integration Challenges," IEEE Power Energy Mag., vol. 9, no. 3, pp. 62-71, May 2011.
- M. H. Athari and Z. Wang, "Modeling the uncertainties in renewable generation and smart grid loads for the study of the grid vulnerability," in 2016 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2016, pp. 1-5.
- M. E. Baran, H. Hooshyar, Z. Shen, and A. Huang, "Accommodating High PV Penetration on Distribution Feeders," IEEE Trans. Smart Grid, vol. 3, no. 2, pp. 1039-1046, Jun. 2012.
- J. R. Aguero and S. J. Steffel, "Integration challenges of photovoltaic distributed generation on power distribution systems," in 2011 IEEE Power and Energy Society General Meeting, 2011, pp. 1-6.
- H. Cheung, A. Hamlyn, L. Wang, C. Yang, and R. Cheung, "Investigations of impacts of distributed generations on feeder protections," in 2009 IEEE Power & Energy Society General Meeting, 2009, pp. 1-7.
- G. W. Chang, Y. H. Chen, L. Y. Hsu, Y. Y. Chen, Y. R. Chang, and Y. D. Lee, "Study of Impact on High PV-Penetrated Feeder Voltage Due to Moving Cloud Shadows," in 2016 International Symposium on Computer, Consumer and Control (IS3C), 2016, pp. 1067-1070.
- M. Farhoodnea, A. Mohamed, H. Shareef, and H. Zayandehroodi, "Power quality impact of grid-connected photovoltaic generation system in distribution networks," in 2012 IEEE Student Conference on Research and Development (SCOReD), 2012, pp. 1-6.
- A. Dubey, S. Santoso, and A. Maitra, "Understanding photovoltaic hosting capacity of distribution circuits," in 2015 IEEE Power & Energy Society General Meeting, 2015, pp. 1-5.
- A. Khoshkbar-Sadigh and K. M. Smedley, "The necessity of time-series simulation for investigation of large-scale solar energy penetration," in 2015 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2015, pp. 1-5.
- M. A. Cohen and D. S. Callaway, "Effects of distributed PV generation on California's distribution system, Part 1: Engineering simulations," Sol. Energy, vol. 128, pp. 126-138, 2016.
- M. A. Cohen, P. A. Kauzmann, and D. S. Callaway, "Effects of distributed PV generation on California's distribution system, part 2: Economic analysis," Sol. Energy, vol. 128, pp. 139-152, 2016.
- C. A. Hill, M. C. Such, D. Chen, J. Gonzalez, and W. M. Grady, "Battery Energy Storage for Enabling Integration of Distributed Solar Power Generation," IEEE Trans. Smart Grid, vol. 3, no. 2, pp. 850-857, Jun. 2012.
- M. H. Athari and M. M. Ardehali, "Operational performance of energy storage as function of electricity prices for on-grid hybrid renewable energy system by optimized fuzzy logic controller," Renew. Energy, vol. 85, pp. 890-902, 2016.
- A. Medina, J. C. Hernandez, and F. Jurado, "Optimal Placement and Sizing Procedure for PV Systems on Radial Distribution Systems," in 2006 International Conference on Power System Technology, 2006, pp. 1-6.
- S. Kucuksari, A. M. Khaleghi, M. Hamidi, Y. Zhang, F. Szidarovszky, G. Bayraksan, and Y.-J. Son, "An Integrated GIS, optimization and simulation framework for optimal PV size and location in campus area environments," Appl. Energy, vol. 113, pp. 1601-1613, 2014.
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Umoh, V., Davidson, I., Adebiyi, A., & Ekpe, U. (2023) · Energies · doi:10.3390/en16083609 · Cited by 71 · see citing works
- Authors
- Athari, M. H., Wang, Z., & Eylas, S. H.
- Affiliations
- Virginia Commonwealth University (US)
- Venue
- 2017 IEEE Manchester PowerTech
- Publisher
- IEEE
- Published
- 2017-06
- Pages
- 1-6
- OpenAlex
- W2622481183
- Cited by
- 38
- References
- 1
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 4 · 2023: 5 · 2022: 6 · 2021: 2 · 2020: 6 · 2019: 6 · 2018: 4 · 2017: 2
- FWCI
- 6.96
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- U.S. Department of Energy
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Power Quality and Harmonics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Keywords
- distributed photovoltaic generation, distribution networks, hosting capacity, voltage quality, reverse power flow, photovoltaic penetration, power loss reduction, commercial buildings, time series analysis
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