IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2022i1p394-d1019077.html
   My bibliography  Save this article

State of the Art Monte Carlo Method Applied to Power System Analysis with Distributed Generation

Author

Listed:
  • Tiago P. Abud

    (Graduate Program in Electrical and Telecommunications Engineering (PPGEET), Federal Fluminense University (UFF), Niterói 24210-240, RJ, Brazil)

  • Andre A. Augusto

    (Graduate Program in Electrical and Telecommunications Engineering (PPGEET), Federal Fluminense University (UFF), Niterói 24210-240, RJ, Brazil)

  • Marcio Z. Fortes

    (Graduate Program in Electrical and Telecommunications Engineering (PPGEET), Federal Fluminense University (UFF), Niterói 24210-240, RJ, Brazil)

  • Renan S. Maciel

    (Electrical Engineering Department, Federal University of Technology—Parana (UTFPR), Apucarana 86812-460, PR, Brazil)

  • Bruno S. M. C. Borba

    (Graduate Program in Electrical and Telecommunications Engineering (PPGEET), Federal Fluminense University (UFF), Niterói 24210-240, RJ, Brazil)

Abstract

Traditionally, electric power systems are subject to uncertainties related to equipment availability, topological changes, faults, disturbances, behaviour of load, etc. In particular, the dissemination of distributed generation (DG), especially those based on renewable sources, has introduced new challenges to power systems, adding further randomness to the management of this segment. In this context, stochastic analysis could support planners and operators in a more appropriate manner than traditional deterministic analysis, since the former is able to properly model the power system uncertainties. The objective of this work is to present recent achievements of one of the most important techniques for stochastic analysis, the Monte Carlo Method (MCM), to study the technical and operational aspects of electric networks with DG. Besides covering the DG topic itself, this paper also addresses emerging themes related to smart grids and new technologies, such as electric vehicles, storage, demand response, and electrothermal hybrid systems. This review encompasses more than 90 recent articles, arranged according to the MCM application and the type of analysis of power systems. The majority of the papers reviewed apply the MCM within stochastic optimization, indicating a possible trend.

Suggested Citation

  • Tiago P. Abud & Andre A. Augusto & Marcio Z. Fortes & Renan S. Maciel & Bruno S. M. C. Borba, 2022. "State of the Art Monte Carlo Method Applied to Power System Analysis with Distributed Generation," Energies, MDPI, vol. 16(1), pages 1-24, December.
    • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:394-:d:1019077
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/1/394/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/1/394/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mo, Huadong & Sansavini, Giovanni, 2019. "Impact of aging and performance degradation on the operational costs of distributed generation systems," Renewable Energy, Elsevier, vol. 143(C), pages 426-439.
    2. Thomas T. D. Tran & Amanda D. Smith, 2019. "Stochastic Optimization for Integration of Renewable Energy Technologies in District Energy Systems for Cost-Effective Use," Energies, MDPI, vol. 12(3), pages 1-26, February.
    3. Ehsan, Ali & Yang, Qiang, 2019. "State-of-the-art techniques for modelling of uncertainties in active distribution network planning: A review," Applied Energy, Elsevier, vol. 239(C), pages 1509-1523.
    4. Razavi, Seyed-Ehsan & Rahimi, Ehsan & Javadi, Mohammad Sadegh & Nezhad, Ali Esmaeel & Lotfi, Mohamed & Shafie-khah, Miadreza & Catalão, João P.S., 2019. "Impact of distributed generation on protection and voltage regulation of distribution systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 157-167.
    5. Sajjad Haider & Peter Schegner, 2021. "Simulating the Impacts of Uncontrolled Electric Vehicle Charging in Low Voltage Grids," Energies, MDPI, vol. 14(8), pages 1-25, April.
    6. Zakaria, A. & Ismail, Firas B. & Lipu, M.S. Hossain & Hannan, M.A., 2020. "Uncertainty models for stochastic optimization in renewable energy applications," Renewable Energy, Elsevier, vol. 145(C), pages 1543-1571.
    7. Talari, Saber & Shafie-khah, Miadreza & Osório, Gerardo J. & Aghaei, Jamshid & Catalão, João P.S., 2018. "Stochastic modelling of renewable energy sources from operators' point-of-view: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1953-1965.
    8. Mehigan, L. & Deane, J.P. & Gallachóir, B.P.Ó. & Bertsch, V., 2018. "A review of the role of distributed generation (DG) in future electricity systems," Energy, Elsevier, vol. 163(C), pages 822-836.
    9. Zubo, Rana.H.A. & Mokryani, Geev & Rajamani, Haile-Selassie & Aghaei, Jamshid & Niknam, Taher & Pillai, Prashant, 2017. "Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1177-1198.
    10. Jin-Sol Song & Ji-Soo Kim & Barry Mather & Chul-Hwan Kim, 2021. "Hosting Capacity Improvement Method Using MV–MV Solid-State-Transformer," Energies, MDPI, vol. 14(3), pages 1-12, January.
    11. Paweł Pijarski & Piotr Kacejko, 2021. "Voltage Optimization in MV Network with Distributed Generation Using Power Consumption Control in Electrolysis Installations," Energies, MDPI, vol. 14(4), pages 1-21, February.
    12. Rigo-Mariani, Rémy & Chea Wae, Sean Ooi & Mazzoni, Stefano & Romagnoli, Alessandro, 2020. "Comparison of optimization frameworks for the design of a multi-energy microgrid," Applied Energy, Elsevier, vol. 257(C).
    13. Samar Fatima & Verner Püvi & Ammar Arshad & Mahdi Pourakbari-Kasmaei & Matti Lehtonen, 2021. "Comparison of Economical and Technical Photovoltaic Hosting Capacity Limits in Distribution Networks," Energies, MDPI, vol. 14(9), pages 1-23, April.
    14. Stavros Lazarou & Vasiliki Vita & Christos Christodoulou & Lambros Ekonomou, 2018. "Calculating Operational Patterns for Electric Vehicle Charging on a Real Distribution Network Based on Renewables’ Production," Energies, MDPI, vol. 11(9), pages 1-15, September.
    15. Hemmati, Reza & Ghiasi, Seyyed Mohammad Sadegh & Entezariharsini, Azam, 2018. "Power fluctuation smoothing and loss reduction in grid integrated with thermal-wind-solar-storage units," Energy, Elsevier, vol. 152(C), pages 759-769.
    16. 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.
    17. Quan Li & Xin Wang & Shuaiang Rong, 2018. "Probabilistic Load Flow Method Based on Modified Latin Hypercube-Important Sampling," Energies, MDPI, vol. 11(11), pages 1-14, November.
    18. Luis Fernando Grisales-Noreña & Daniel Gonzalez Montoya & Carlos Andres Ramos-Paja, 2018. "Optimal Sizing and Location of Distributed Generators Based on PBIL and PSO Techniques," Energies, MDPI, vol. 11(4), pages 1-27, April.
    19. Hasan, Kazi Nazmul & Preece, Robin & Milanović, Jovica V., 2019. "Existing approaches and trends in uncertainty modelling and probabilistic stability analysis of power systems with renewable generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 168-180.
    20. Sherif M. Ismael & Shady H. E. Abdel Aleem & Almoataz Y. Abdelaziz & Ahmed F. Zobaa, 2019. "Probabilistic Hosting Capacity Enhancement in Non-Sinusoidal Power Distribution Systems Using a Hybrid PSOGSA Optimization Algorithm," Energies, MDPI, vol. 12(6), pages 1-23, March.
    21. Ahmadian, Ali & Sedghi, Mahdi & Fgaier, Hedia & Mohammadi-ivatloo, Behnam & Golkar, Masoud Aliakbar & Elkamel, Ali, 2019. "PEVs data mining based on factor analysis method for energy storage and DG planning in active distribution network: Introducing S2S effect," Energy, Elsevier, vol. 175(C), pages 265-277.
    22. Ross,Sheldon M., 2011. "An Elementary Introduction to Mathematical Finance," Cambridge Books, Cambridge University Press, number 9780521192538, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jie Zhu & Buxiang Zhou & Yiwei Qiu & Tianlei Zang & Yi Zhou & Shi Chen & Ningyi Dai & Huan Luo, 2023. "Survey on Modeling of Temporally and Spatially Interdependent Uncertainties in Renewable Power Systems," Energies, MDPI, vol. 16(16), pages 1-19, August.
    2. Àlex Alonso-Travesset & Helena Martín & Sergio Coronas & Jordi de la Hoz, 2022. "Optimization Models under Uncertainty in Distributed Generation Systems: A Review," Energies, MDPI, vol. 15(5), pages 1-40, March.
    3. Asaad Mohammad & Ramon Zamora & Tek Tjing Lie, 2020. "Integration of Electric Vehicles in the Distribution Network: A Review of PV Based Electric Vehicle Modelling," Energies, MDPI, vol. 13(17), pages 1-20, September.
    4. Md Tariqul Islam & M. J. Hossain, 2023. "Artificial Intelligence for Hosting Capacity Analysis: A Systematic Literature Review," Energies, MDPI, vol. 16(4), pages 1-33, February.
    5. Yao, Hongmin & Qin, Wenping & Jing, Xiang & Zhu, Zhilong & Wang, Ke & Han, Xiaoqing & Wang, Peng, 2022. "Possibilistic evaluation of photovoltaic hosting capacity on distribution networks under uncertain environment," Applied Energy, Elsevier, vol. 324(C).
    6. Costa, Vinicius Braga Ferreira da & Bonatto, Benedito Donizeti, 2023. "Cutting-edge public policy proposal to maximize the long-term benefits of distributed energy resources," Renewable Energy, Elsevier, vol. 203(C), pages 357-372.
    7. Ibrahim Mohamed Diaaeldin & Mahmoud A. Attia & Amr K. Khamees & Othman A. M. Omar & Ahmed O. Badr, 2023. "A Novel Multiobjective Formulation for Optimal Wind Speed Modeling via a Mixture Probability Density Function," Mathematics, MDPI, vol. 11(6), pages 1-19, March.
    8. Gust, Gunther & Schlüter, Alexander & Feuerriegel, Stefan & Úbeda, Ignacio & Lee, Jonathan T. & Neumann, Dirk, 2024. "Designing electricity distribution networks: The impact of demand coincidence," European Journal of Operational Research, Elsevier, vol. 315(1), pages 271-288.
    9. Bartolini, Andrea & Mazzoni, Stefano & Comodi, Gabriele & Romagnoli, Alessandro, 2021. "Impact of carbon pricing on distributed energy systems planning," Applied Energy, Elsevier, vol. 301(C).
    10. Stavros Lazarou & Vasiliki Vita & Lambros Ekonomou, 2018. "Protection Schemes of Meshed Distribution Networks for Smart Grids and Electric Vehicles," Energies, MDPI, vol. 11(11), pages 1-17, November.
    11. Pereira, Luan D.L. & Yahyaoui, Imene & Fiorotti, Rodrigo & de Menezes, Luíza S. & Fardin, Jussara F. & Rocha, Helder R.O. & Tadeo, Fernando, 2022. "Optimal allocation of distributed generation and capacitor banks using probabilistic generation models with correlations," Applied Energy, Elsevier, vol. 307(C).
    12. Jude Suchithra & Duane Robinson & Amin Rajabi, 2023. "Hosting Capacity Assessment Strategies and Reinforcement Learning Methods for Coordinated Voltage Control in Electricity Distribution Networks: A Review," Energies, MDPI, vol. 16(5), pages 1-28, March.
    13. Mahesh Kumar & Amir Mahmood Soomro & Waqar Uddin & Laveet Kumar, 2022. "Optimal Multi-Objective Placement and Sizing of Distributed Generation in Distribution System: A Comprehensive Review," Energies, MDPI, vol. 15(21), pages 1-48, October.
    14. Rahim, Sahar & Wang, Zhen & Ju, Ping, 2022. "Overview and applications of Robust optimization in the avant-garde energy grid infrastructure: A systematic review," Applied Energy, Elsevier, vol. 319(C).
    15. Zhan, Weipeng & Wang, Zhenpo & Zhang, Lei & Liu, Peng & Cui, Dingsong & Dorrell, David G., 2022. "A review of siting, sizing, optimal scheduling, and cost-benefit analysis for battery swapping stations," Energy, Elsevier, vol. 258(C).
    16. David Calvachi & Luis Tipán & Manuel Jaramillo, 2023. "Localization and Sizing of Distributed Generation through a Genetic Algorithm to Improve Voltage Profile Using Ecuadorian Standards," Energies, MDPI, vol. 16(10), pages 1-19, May.
    17. Wei Sun & Sam Harrison & Gareth P. Harrison, 2020. "Value of Local Offshore Renewable Resource Diversity for Network Hosting Capacity," Energies, MDPI, vol. 13(22), pages 1-20, November.
    18. Zhang, Jianhua & Ballas, Dimitris & Liu, Xiaolong, 2023. "Neighbourhood-level spatial determinants of residential solar photovoltaic adoption in the Netherlands," Renewable Energy, Elsevier, vol. 206(C), pages 1239-1248.
    19. Eslami, Ahmadreza & Negnevitsky, Michael & Franklin, Evan & Lyden, Sarah, 2022. "Review of AI applications in harmonic analysis in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    20. Ziad M. Ali & Ibrahim Mohamed Diaaeldin & Shady H. E. Abdel Aleem & Ahmed El-Rafei & Almoataz Y. Abdelaziz & Francisco Jurado, 2020. "Scenario-Based Network Reconfiguration and Renewable Energy Resources Integration in Large-Scale Distribution Systems Considering Parameters Uncertainty," Mathematics, MDPI, vol. 9(1), pages 1-31, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:394-:d:1019077. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.