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Probabilistic Methodology for Calculating PV Hosting Capacity in LV Networks Using Actual Building Roof Data

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  • Miha Grabner

    (Faculty of Electrical Engineering, University of Ljubljana, Tržaška c. 25, 1000 Ljubljana, Slovenia
    Electric Power Research Institute Milan Vidmar, Hajdrihova 2, 1000 Ljubljana, Slovenia)

  • Andrej Souvent

    (Electric Power Research Institute Milan Vidmar, Hajdrihova 2, 1000 Ljubljana, Slovenia)

  • Nermin Suljanović

    (Electric Power Research Institute Milan Vidmar, Hajdrihova 2, 1000 Ljubljana, Slovenia)

  • Andrej Košir

    (Faculty of Electrical Engineering, University of Ljubljana, Tržaška c. 25, 1000 Ljubljana, Slovenia)

  • Boštjan Blažič

    (Faculty of Electrical Engineering, University of Ljubljana, Tržaška c. 25, 1000 Ljubljana, Slovenia)

Abstract

There has been an increasing trend of integrating photovoltaic power plants (PVs). One of the important challenges for distribution system operators is to evaluate the total installed power of a PV that a particular network can host (or PV hosting capacity) while keeping voltage and element constraints within required limits. The major drawback of the existing methods for calculating PV hosting capacity is that they use the same installed power of the PV systems for all simulated PVs, as these methods do not use external data sources about building roofs. As a consequence, this has a significant impact on the final accuracy of the results. This paper presents a probabilistic methodology for calculating the PV hosting capacity in low voltage (LV) networks. The main contribution of this paper is the improved modeling of PV generation using actual building roof data when calculating the PV hosting capacity, as every building is treated according to its actual solar potential. Monte Carlo simulations with incorporated stochastic consumption and PV generation models are utilized for load flow calculations of the actual LV network. The simulation results presented in this paper prove that the proposed methodology increases the accuracy of the final PV hosting capacity calculations.

Suggested Citation

  • Miha Grabner & Andrej Souvent & Nermin Suljanović & Andrej Košir & Boštjan Blažič, 2019. "Probabilistic Methodology for Calculating PV Hosting Capacity in LV Networks Using Actual Building Roof Data," Energies, MDPI, vol. 12(21), pages 1-15, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:21:p:4086-:d:280506
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    References listed on IDEAS

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    1. Daniel-Leon Schultis, 2019. "Comparison of Local Volt/var Control Strategies for PV Hosting Capacity Enhancement of Low Voltage Feeders," Energies, MDPI, vol. 12(8), pages 1-27, April.
    2. Freitas, S. & Catita, C. & Redweik, P. & Brito, M.C., 2015. "Modelling solar potential in the urban environment: State-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 915-931.
    3. Tiago E. C. de Oliveira & Pedro M. S. Carvalho & Paulo F. Ribeiro & Benedito D. Bonatto, 2018. "PV Hosting Capacity Dependence on Harmonic Voltage Distortion in Low-Voltage Grids: Model Validation with Experimental Data," Energies, MDPI, vol. 11(2), pages 1-13, February.
    4. Syahrul Nizam Md Saad & Adriaan Hendrik van der Weijde, 2019. "Evaluating the Potential of Hosting Capacity Enhancement Using Integrated Grid Planning modeling Methods," Energies, MDPI, vol. 12(19), pages 1-23, September.
    5. Benoît Bletterie & Serdar Kadam & Herwig Renner, 2018. "On the Classification of Low Voltage Feeders for Network Planning and Hosting Capacity Studies," Energies, MDPI, vol. 11(3), pages 1-23, March.
    6. Emilio J. Palacios-Garcia & Antonio Moreno-Muñoz & Isabel Santiago & Isabel M. Moreno-Garcia & María I. Milanés-Montero, 2017. "PV Hosting Capacity Analysis and Enhancement Using High Resolution Stochastic Modeling," Energies, MDPI, vol. 10(10), pages 1-22, September.
    7. Ismael, Sherif M. & Abdel Aleem, Shady H.E. & Abdelaziz, Almoataz Y. & Zobaa, Ahmed F., 2019. "State-of-the-art of hosting capacity in modern power systems with distributed generation," Renewable Energy, Elsevier, vol. 130(C), pages 1002-1020.
    8. Ammar Arshad & Verner Püvi & Matti Lehtonen, 2018. "Monte Carlo-Based Comprehensive Assessment of PV Hosting Capacity and Energy Storage Impact in Realistic Finnish Low-Voltage Networks," Energies, MDPI, vol. 11(6), pages 1-14, June.
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    Cited by:

    1. Samar Fatima & Verner Püvi & Matti Lehtonen, 2020. "Review on the PV Hosting Capacity in Distribution Networks," Energies, MDPI, vol. 13(18), pages 1-34, September.
    2. Vincent Umoh & Innocent Davidson & Abayomi Adebiyi & Unwana Ekpe, 2023. "Methods and Tools for PV and EV Hosting Capacity Determination in Low Voltage Distribution Networks—A Review," Energies, MDPI, vol. 16(8), pages 1-25, April.
    3. Magdalena Bartecka & Grazia Barchi & Józef Paska, 2020. "Time-Series PV Hosting Capacity Assessment with Storage Deployment," Energies, MDPI, vol. 13(10), pages 1-20, May.
    4. Yilin Xu & Jie He & Yang Liu & Zilu Li & Weicong Cai & Xiangang Peng, 2023. "Evaluation Method for Hosting Capacity of Rooftop Photovoltaic Considering Photovoltaic Potential in Distribution System," Energies, MDPI, vol. 16(22), pages 1-23, November.

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