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Probabilistic Load Flow for Power Grids With High PV Penetrations Using Copula-Based Modeling of Spatially Correlated Solar Irradiance
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics. (Built Environment Energy Systems Group (BEESG))
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics. (Built Environment Energy Systems Group (BEESG))
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics. (Built Environment Energy Systems Group (BEESG))
2017 (English)In: IEEE Journal of Photovoltaics, ISSN 2156-3381, E-ISSN 2156-3403, Vol. 7, no 6, 1740-1745 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents and applies an improved model for the instantaneous power generation from distributed photovoltaic (PV) systems intended for probabilistic load flow (PLF) simulations. The model combines a probability distribution model for the instantaneous solar irradiance at individual sites with an improved spatial correlation model and uses a Gaussian copula to allow correlated sampling from the distributions for an arbitrary set of distributed PV systems. We show that the model realistically reproduces the spatially distributed clear-sky index over a set of sites, based on comparisons with irradiance sensor network data. We also demonstrate that the probability distributions for system parameters such as customer voltage, substation loading, and power losses, obtained from PLF simulations with the model, differ substantially from those of a nonspatial approach. The results show that spatial irradiance modeling needs to be incorporated in PLF simulations in order not to overestimate the grid impacts of PV systems.

Place, publisher, year, edition, pages
2017. Vol. 7, no 6, 1740-1745 p.
Keyword [en]
Load flow, Load modeling, Photovoltaic systems, Probabilistic logic, Simulation, Copula, photovoltaic (PV), probabilistic load flow (PLF)
National Category
Energy Systems
Research subject
Engineering Science
Identifiers
URN: urn:nbn:se:uu:diva-333352DOI: 10.1109/JPHOTOV.2017.2749004OAI: oai:DiVA.org:uu-333352DiVA: diva2:1156236
Available from: 2017-11-10 Created: 2017-11-10 Last updated: 2017-11-14

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Widén, JoakimShepero, MahmoudMunkhammar, Joakim
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