IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2022i1p106-d1011166.html
   My bibliography  Save this article

Optimal Location and Sizing of Distributed Generators and Energy Storage Systems in Microgrids: A Review

Author

Listed:
  • Luis Fernando Grisales-Noreña

    (Department of Electrical Engineering, Faculty of Engineering, Universidad de Talca, Curicó 3340000, Chile
    These authors contributed equally to this work.)

  • Bonie Johana Restrepo-Cuestas

    (Facultad de Ingenierías, Instituto Tecnológico Metropolitano, Medellín 050028, Colombia
    These authors contributed equally to this work.)

  • Brandon Cortés-Caicedo

    (Facultad de Ingenierías, Instituto Tecnológico Metropolitano, Medellín 050028, Colombia
    These authors contributed equally to this work.)

  • Jhon Montano

    (Facultad de Ingenierías, Instituto Tecnológico Metropolitano, Medellín 050028, Colombia
    These authors contributed equally to this work.)

  • Andrés Alfonso Rosales-Muñoz

    (Facultad de Ingenierías, Instituto Tecnológico Metropolitano, Medellín 050028, Colombia
    These authors contributed equally to this work.)

  • Marco Rivera

    (Department of Electrical Engineering, Faculty of Engineering, Universidad de Talca, Curicó 3340000, Chile
    Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK
    These authors contributed equally to this work.)

Abstract

This article reviews the main methodologies employed for the optimal location, sizing, and operation of Distributed Generators (DGs) and Energy Storage Systems (ESSs) in electrical networks. For such purpose, we first analyzed the devices that comprise a microgrid (MG) in an environment with Distributed Energy Resources (DERs) and their modes of operation. Following that, we examined the planning and operation of each DER considered in this study (DGs and ESSs). Finally, we addressed the joint integration of DGs and ESSs into MGs. From this literature review, we were able to identify both the objective functions and constraints that are most commonly used to formulate the problem of the optimal integration and operation of DGs and ESSs in MGs. Moreover, this review allowed us to identify the methodologies that have been employed for such integration, as well as the current needs in the field. With this information, the purpose is to develop new mathematical formulations and approaches for the optimal integration and operation of DERs into MGs that provide financial and operational benefits.

Suggested Citation

  • Luis Fernando Grisales-Noreña & Bonie Johana Restrepo-Cuestas & Brandon Cortés-Caicedo & Jhon Montano & Andrés Alfonso Rosales-Muñoz & Marco Rivera, 2022. "Optimal Location and Sizing of Distributed Generators and Energy Storage Systems in Microgrids: A Review," Energies, MDPI, vol. 16(1), pages 1-30, December.
    • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:106-:d:1011166
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/1/106/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/1/106/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fernando Postigo Marcos & Carlos Mateo Domingo & Tomás Gómez San Román & Rafael Cossent Arín, 2020. "Location and Sizing of Micro-Grids to Improve Continuity of Supply in Radial Distribution Networks," Energies, MDPI, vol. 13(13), pages 1-21, July.
    2. Gao, Xiaoxia & Yang, Hongxing & Lu, Lin, 2014. "Study on offshore wind power potential and wind farm optimization in Hong Kong," Applied Energy, Elsevier, vol. 130(C), pages 519-531.
    3. Fathy, Ahmed & Ferahtia, Seydali & Rezk, Hegazy & Yousri, Dalia & Abdelkareem, Mohammad Ali & Olabi, A.G., 2022. "Optimal adaptive fuzzy management strategy for fuel cell-based DC microgrid," Energy, Elsevier, vol. 247(C).
    4. David Barbosa de Alencar & Carolina De Mattos Affonso & Roberto Célio Limão de Oliveira & Jorge Laureano Moya Rodríguez & Jandecy Cabral Leite & José Carlos Reston Filho, 2017. "Different Models for Forecasting Wind Power Generation: Case Study," Energies, MDPI, vol. 10(12), pages 1-27, November.
    5. Luis Fernando Grisales-Noreña & Oscar Danilo Montoya & Jesús C. Hernández & Carlos Andres Ramos-Paja & Alberto-Jesus Perea-Moreno, 2022. "A Discrete-Continuous PSO for the Optimal Integration of D-STATCOMs into Electrical Distribution Systems by Considering Annual Power Loss and Investment Costs," Mathematics, MDPI, vol. 10(14), pages 1-16, July.
    6. Phi-Hai Trinh & Il-Yop Chung, 2021. "Optimal Control Strategy for Distributed Energy Resources in a DC Microgrid for Energy Cost Reduction and Voltage Regulation," Energies, MDPI, vol. 14(4), pages 1-19, February.
    7. Mahmoud Elshenawy & Ashraf Fahmy & Adel Elsamahy & Shaimaa A. Kandil & Helmy M. El Zoghby, 2022. "Optimal Power Management of Interconnected Microgrids Using Virtual Inertia Control Technique," Energies, MDPI, vol. 15(19), pages 1-30, September.
    8. Qiu, Jing & Zhao, Junhua & Yang, Hongming & Wang, Dongxiao & Dong, Zhao Yang, 2018. "Planning of solar photovoltaics, battery energy storage system and gas micro turbine for coupled micro energy grids," Applied Energy, Elsevier, vol. 219(C), pages 361-369.
    9. Camilo Andres Mora & Oscar Danilo Montoya & Edwin Rivas Trujillo, 2020. "Mixed-Integer Programming Model for Transmission Network Expansion Planning with Battery Energy Storage Systems (BESS)," Energies, MDPI, vol. 13(17), pages 1-22, August.
    10. Wu, Di & Ma, Xu & Huang, Sen & Fu, Tao & Balducci, Patrick, 2020. "Stochastic optimal sizing of distributed energy resources for a cost-effective and resilient Microgrid," Energy, Elsevier, vol. 198(C).
    11. Arul Rajagopalan & Karthik Nagarajan & Oscar Danilo Montoya & Seshathiri Dhanasekaran & Inayathullah Abdul Kareem & Angalaeswari Sendraya Perumal & Natrayan Lakshmaiya & Prabhu Paramasivam, 2022. "Multi-Objective Optimal Scheduling of a Microgrid Using Oppositional Gradient-Based Grey Wolf Optimizer," Energies, MDPI, vol. 15(23), pages 1-24, November.
    12. Adnan Ahmad & Asif Khan & Nadeem Javaid & Hafiz Majid Hussain & Wadood Abdul & Ahmad Almogren & Atif Alamri & Iftikhar Azim Niaz, 2017. "An Optimized Home Energy Management System with Integrated Renewable Energy and Storage Resources," Energies, MDPI, vol. 10(4), pages 1-35, April.
    13. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Multi-objective optimization of energy arbitrage in community energy storage systems using different battery technologies," Applied Energy, Elsevier, vol. 239(C), pages 356-372.
    14. Bianco, Vincenzo & Manca, Oronzio & Nardini, Sergio, 2009. "Electricity consumption forecasting in Italy using linear regression models," Energy, Elsevier, vol. 34(9), pages 1413-1421.
    15. Oscar Danilo Montoya & Walter Gil-González & Edwin Rivas-Trujillo, 2020. "Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids," Energies, MDPI, vol. 13(9), pages 1-20, May.
    16. Oscar Danilo Montoya & Walter Gil-González & Luis Grisales-Noreña & César Orozco-Henao & Federico Serra, 2019. "Economic Dispatch of BESS and Renewable Generators in DC Microgrids Using Voltage-Dependent Load Models," Energies, MDPI, vol. 12(23), pages 1-20, November.
    17. Luis Fernando Grisales-Noreña & Carlos Andrés Ramos-Paja & Daniel Gonzalez-Montoya & Gerardo Alcalá & Quetzalcoatl Hernandez-Escobedo, 2020. "Energy Management in PV Based Microgrids Designed for the Universidad Nacional de Colombia," Sustainability, MDPI, vol. 12(3), pages 1-24, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Víctor M. Garrido-Arévalo & Walter Gil-González & Oscar Danilo Montoya & Harold R. Chamorro & Jorge Mírez, 2023. "Efficient Allocation and Sizing the PV-STATCOMs in Electrical Distribution Grids Using Mixed-Integer Convex Approximation," Energies, MDPI, vol. 16(20), pages 1-19, October.

    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. Jhony Guzman-Henao & Luis Fernando Grisales-Noreña & Bonie Johana Restrepo-Cuestas & Oscar Danilo Montoya, 2023. "Optimal Integration of Photovoltaic Systems in Distribution Networks from a Technical, Financial, and Environmental Perspective," Energies, MDPI, vol. 16(1), pages 1-19, January.
    2. Lorenc Malka & Ilirian Konomi & Ardit Gjeta & Skerdi Drenova & Jugert Gjikoka, 2020. "An Approach to the Large-scale Integration of Wind Energy in Albania," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 327-343.
    3. Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021. "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers 2021-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Lim, Juin Yau & Safder, Usman & How, Bing Shen & Ifaei, Pouya & Yoo, Chang Kyoo, 2021. "Nationwide sustainable renewable energy and Power-to-X deployment planning in South Korea assisted with forecasting model," Applied Energy, Elsevier, vol. 283(C).
    5. Fitsum Salehu Kebede & Jean-Christophe Olivier & Salvy Bourguet & Mohamed Machmoum, 2021. "Reliability Evaluation of Renewable Power Systems through Distribution Network Power Outage Modelling," Energies, MDPI, vol. 14(11), pages 1-25, May.
    6. A. Azadeh & M. Saberi & A. Gitiforouz, 2013. "An integrated fuzzy mathematical model and principal component analysis algorithm for forecasting uncertain trends of electricity consumption," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(4), pages 2163-2176, June.
    7. Ruixiaoxiao Zhang & Geoffrey QP Shen & Meng Ni & Johnny Wong, 2020. "The relationship between energy consumption and gross domestic product in Hong Kong (1992–2015): Evidence from sectoral analysis and implications on future energy policy," Energy & Environment, , vol. 31(2), pages 215-236, March.
    8. Pollini, Nicolò, 2022. "Topology optimization of wind farm layouts," Renewable Energy, Elsevier, vol. 195(C), pages 1015-1027.
    9. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Optimal energy management in all-electric residential energy systems with heat and electricity storage," Applied Energy, Elsevier, vol. 254(C).
    10. Meng, Ming & Niu, Dongxiao, 2011. "Modeling CO2 emissions from fossil fuel combustion using the logistic equation," Energy, Elsevier, vol. 36(5), pages 3355-3359.
    11. Zhu, Xiaoxun & Liu, Ruizhang & Chen, Yao & Gao, Xiaoxia & Wang, Yu & Xu, Zixu, 2021. "Wind speed behaviors feather analysis and its utilization on wind speed prediction using 3D-CNN," Energy, Elsevier, vol. 236(C).
    12. Hanif, Sarmad & Alam, M.J.E. & Roshan, Kini & Bhatti, Bilal A. & Bedoya, Juan C., 2022. "Multi-service battery energy storage system optimization and control," Applied Energy, Elsevier, vol. 311(C).
    13. Vitale, F. & Rispoli, N. & Sorrentino, M. & Rosen, M.A. & Pianese, C., 2021. "On the use of dynamic programming for optimal energy management of grid-connected reversible solid oxide cell-based renewable microgrids," Energy, Elsevier, vol. 225(C).
    14. Vincenzo Bianco & Annalisa Marchitto & Federico Scarpa & Luca A. Tagliafico, 2020. "Forecasting Energy Consumption in the EU Residential Sector," IJERPH, MDPI, vol. 17(7), pages 1-15, March.
    15. Yang, Yang & Xue, Dingyü, 2016. "Continuous fractional-order grey model and electricity prediction research based on the observation error feedback," Energy, Elsevier, vol. 115(P1), pages 722-733.
    16. Piotr Krawczyk & Anna Śliwińska, 2020. "Eco-Efficiency Assessment of the Application of Large-Scale Rechargeable Batteries in a Coal-Fired Power Plant," Energies, MDPI, vol. 13(6), pages 1-16, March.
    17. Zhang, Yijie & Ma, Tao & Elia Campana, Pietro & Yamaguchi, Yohei & Dai, Yanjun, 2020. "A techno-economic sizing method for grid-connected household photovoltaic battery systems," Applied Energy, Elsevier, vol. 269(C).
    18. Ren, Guorui & Wan, Jie & Liu, Jinfu & Yu, Daren, 2019. "Characterization of wind resource in China from a new perspective," Energy, Elsevier, vol. 167(C), pages 994-1010.
    19. Tao Xu & He Meng & Jie Zhu & Wei Wei & He Zhao & Han Yang & Zijin Li & Yuhan Wu, 2021. "Optimal Capacity Allocation of Energy Storage in Distribution Networks Considering Active/Reactive Coordination," Energies, MDPI, vol. 14(6), pages 1-24, March.
    20. Jeziel Vázquez & Elias J. J. Rodriguez & Jaime Arau & Nimrod Vázquez, 2021. "A di/dt Detection Circuit for DC Unidirectional Breaker Based on Inductor Transient Behaviour," Sustainability, MDPI, vol. 13(16), pages 1-18, August.

    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:106-:d:1011166. 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.