IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i16p4214-d399234.html
   My bibliography  Save this article

Optimal Design of Isolated Mini-Grids with Deterministic Methods: Matching Predictive Operating Strategies with Low Computational Requirements

Author

Listed:
  • Andrea Micangeli

    (DIMA, Department of Mechanical and Aerospace Engineering, “Sapienza” University of Rome, Via Eudossiana 18, 00184 Rome, Italy)

  • Davide Fioriti

    (DESTEC, Department of Energy, Systems, Territory and Costruction Engineering, University of Pisa, Largo Lucio Lazzarino, 56122 Pisa, Italy)

  • Paolo Cherubini

    (DESTEC, Department of Energy, Systems, Territory and Costruction Engineering, University of Pisa, Largo Lucio Lazzarino, 56122 Pisa, Italy)

  • Pablo Duenas-Martinez

    (MIT Energy Initiative, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA)

Abstract

The lack of electricity access is increasingly concentrated in rural areas of developing countries, in which mini-grids are often a suitable solution; however, given the high risks, it is crucial to minimize costs. This paper aims at analyzing existing methodologies for the optimal design of mini-grids combined with different operating strategies. Typical system operations, like the load-following (LFS) and cycle charging (CCS) strategies, are compared with the more demanding predictive strategies based on Mixed-Integer Linear Programming (MILP). The problem is formulated and solved with Particle Swarm Optimization (PSO), so to simulate traditional and predictive operating strategies. Two reformulations based on the proposed Search Space Update are also detailed and compared with the so-called one-shot MILP model, which is able to con-jointly optimize both the design and the operation of the system, in order to reduce computational requirements with the predictive strategy. The results, tailored with data from a rural mini-grid in Kenya, highlight that heuristic methodologies can perform better than the traditional MILP approach, both in terms of optimality and computational time, especially when advanced operating strategies are considered. Conventional operating strategies (LFS or CCS) appear to be sub-optimal, but require very little computational requirements, which makes them suitable for preliminary designs.

Suggested Citation

  • Andrea Micangeli & Davide Fioriti & Paolo Cherubini & Pablo Duenas-Martinez, 2020. "Optimal Design of Isolated Mini-Grids with Deterministic Methods: Matching Predictive Operating Strategies with Low Computational Requirements," Energies, MDPI, vol. 13(16), pages 1-19, August.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:16:p:4214-:d:399234
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/16/4214/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/16/4214/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ahmad Khan, Aftab & Naeem, Muhammad & Iqbal, Muhammad & Qaisar, Saad & Anpalagan, Alagan, 2016. "A compendium of optimization objectives, constraints, tools and algorithms for energy management in microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1664-1683.
    2. Euan Phimister, Esperanza Vera-Toscano and Deborah Roberts, 2015. "The Dynamics of Energy Poverty: Evidence from Spain," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 1).
    3. Valeria Gambino & Riccardo Del Citto & Paolo Cherubini & Carlo Tacconelli & Andrea Micangeli & Romano Giglioli, 2019. "Methodology for the Energy Need Assessment to Effectively Design and Deploy Mini-Grids for Rural Electrification," Energies, MDPI, vol. 12(3), pages 1-27, February.
    4. Mazzola, Simone & Vergara, Claudio & Astolfi, Marco & Li, Vivian & Perez-Arriaga, Ignacio & Macchi, Ennio, 2017. "Assessing the value of forecast-based dispatch in the operation of off-grid rural microgrids," Renewable Energy, Elsevier, vol. 108(C), pages 116-125.
    5. Moretti, Luca & Astolfi, Marco & Vergara, Claudio & Macchi, Ennio & Pérez-Arriaga, Josè Ignacio & Manzolini, Giampaolo, 2019. "A design and dispatch optimization algorithm based on mixed integer linear programming for rural electrification," Applied Energy, Elsevier, vol. 233, pages 1104-1121.
    6. Goel, Sonali & Sharma, Renu, 2017. "Performance evaluation of stand alone, grid connected and hybrid renewable energy systems for rural application: A comparative review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1378-1389.
    7. Malheiro, André & Castro, Pedro M. & Lima, Ricardo M. & Estanqueiro, Ana, 2015. "Integrated sizing and scheduling of wind/PV/diesel/battery isolated systems," Renewable Energy, Elsevier, vol. 83(C), pages 646-657.
    8. Mandelli, Stefano & Barbieri, Jacopo & Mereu, Riccardo & Colombo, Emanuela, 2016. "Off-grid systems for rural electrification in developing countries: Definitions, classification and a comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1621-1646.
    9. Winkler, Harald & Simões, André Felipe & Rovere, Emilio Lèbre la & Alam, Mozaharul & Rahman, Atiq & Mwakasonda, Stanford, 2011. "Access and Affordability of Electricity in Developing Countries," World Development, Elsevier, vol. 39(6), pages 1037-1050, June.
    10. Erdinc, O. & Uzunoglu, M., 2012. "Optimum design of hybrid renewable energy systems: Overview of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1412-1425.
    11. Siddaiah, Rajanna & Saini, R.P., 2016. "A review on planning, configurations, modeling and optimization techniques of hybrid renewable energy systems for off grid applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 376-396.
    12. Chauhan, Anurag & Saini, R.P., 2014. "A review on Integrated Renewable Energy System based power generation for stand-alone applications: Configurations, storage options, sizing methodologies and control," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 99-120.
    13. repec:aen:journl:eeep4_1_phimister is not listed on IDEAS
    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. Maria Acuna & Carlos Silva & Andrés Tocaruncho & Diana Vargas & Diego Patiño & David Barrera & Johan Peña, 2021. "Operational Planning of Energy for Non-Interconnected Zones: A Simulation-Optimization Approach and a Case Study to Tackle Energy Poverty in Colombia," Energies, MDPI, vol. 14(10), pages 1-16, May.

    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. Akbas, Beste & Kocaman, Ayse Selin & Nock, Destenie & Trotter, Philipp A., 2022. "Rural electrification: An overview of optimization methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    2. Rahmat Khezri & Amin Mahmoudi & Hirohisa Aki & S. M. Muyeen, 2021. "Optimal Planning of Remote Area Electricity Supply Systems: Comprehensive Review, Recent Developments and Future Scopes," Energies, MDPI, vol. 14(18), pages 1-29, September.
    3. García-Villoria, Alberto & Domenech, Bruno & Ferrer-Martí, Laia & Juanpera, Marc & Pastor, Rafael, 2020. "Ad-hoc heuristic for design of wind-photovoltaic electrification systems, including management constraints," Energy, Elsevier, vol. 212(C).
    4. Fioriti, Davide & Pintus, Salvatore & Lutzemberger, Giovanni & Poli, Davide, 2020. "Economic multi-objective approach to design off-grid microgrids: A support for business decision making," Renewable Energy, Elsevier, vol. 159(C), pages 693-704.
    5. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2018. "Battery energy storage system size determination in renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 109-125.
    6. Seyfettin Vadi & Sanjeevikumar Padmanaban & Ramazan Bayindir & Frede Blaabjerg & Lucian Mihet-Popa, 2019. "A Review on Optimization and Control Methods Used to Provide Transient Stability in Microgrids," Energies, MDPI, vol. 12(18), pages 1-20, September.
    7. Tatiana González Grandón & Fernando de Cuadra García & Ignacio Pérez-Arriaga, 2021. "A Market-Driven Management Model for Renewable-Powered Undergrid Mini-Grids," Energies, MDPI, vol. 14(23), pages 1-29, November.
    8. Ridha, Hussein Mohammed & Gomes, Chandima & Hizam, Hashim & Ahmadipour, Masoud & Heidari, Ali Asghar & Chen, Huiling, 2021. "Multi-objective optimization and multi-criteria decision-making methods for optimal design of standalone photovoltaic system: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    9. Abhi Chatterjee & Daniel Burmester & Alan Brent & Ramesh Rayudu, 2019. "Research Insights and Knowledge Headways for Developing Remote, Off-Grid Microgrids in Developing Countries," Energies, MDPI, vol. 12(10), pages 1-19, May.
    10. Moretti, Luca & Astolfi, Marco & Vergara, Claudio & Macchi, Ennio & Pérez-Arriaga, Josè Ignacio & Manzolini, Giampaolo, 2019. "A design and dispatch optimization algorithm based on mixed integer linear programming for rural electrification," Applied Energy, Elsevier, vol. 233, pages 1104-1121.
    11. Moretti, L. & Polimeni, S. & Meraldi, L. & Raboni, P. & Leva, S. & Manzolini, G., 2019. "Assessing the impact of a two-layer predictive dispatch algorithm on design and operation of off-grid hybrid microgrids," Renewable Energy, Elsevier, vol. 143(C), pages 1439-1453.
    12. Ma, Weiwu & Xue, Xinpei & Liu, Gang, 2018. "Techno-economic evaluation for hybrid renewable energy system: Application and merits," Energy, Elsevier, vol. 159(C), pages 385-409.
    13. Bhatt, Ankit & Sharma, M.P. & Saini, R.P., 2016. "Feasibility and sensitivity analysis of an off-grid micro hydro–photovoltaic–biomass and biogas–diesel–battery hybrid energy system for a remote area in Uttarakhand state, India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 53-69.
    14. Joshi, Lalita & Choudhary, Deepak & Kumar, Praveen & Venkateswaran, Jayendran & Solanki, Chetan S., 2019. "Does involvement of local community ensure sustained energy access? A critical review of a solar PV technology intervention in rural India," World Development, Elsevier, vol. 122(C), pages 272-281.
    15. Alexander N. Kozlov & Nikita V. Tomin & Denis N. Sidorov & Electo E. S. Lora & Victor G. Kurbatsky, 2020. "Optimal Operation Control of PV-Biomass Gasifier-Diesel-Hybrid Systems Using Reinforcement Learning Techniques," Energies, MDPI, vol. 13(10), pages 1-20, May.
    16. Syed Ali Abbas Kazmi & Muhammad Khuram Shahzad & Akif Zia Khan & Dong Ryeol Shin, 2017. "Smart Distribution Networks: A Review of Modern Distribution Concepts from a Planning Perspective," Energies, MDPI, vol. 10(4), pages 1-47, April.
    17. Pablo Benalcazar & Adam Suski & Jacek Kamiński, 2020. "Optimal Sizing and Scheduling of Hybrid Energy Systems: The Cases of Morona Santiago and the Galapagos Islands," Energies, MDPI, vol. 13(15), pages 1-20, August.
    18. José Luis Torres-Madroñero & Joham Alvarez-Montoya & Daniel Restrepo-Montoya & Jorge Mario Tamayo-Avendaño & César Nieto-Londoño & Julián Sierra-Pérez, 2020. "Technological and Operational Aspects That Limit Small Wind Turbines Performance," Energies, MDPI, vol. 13(22), pages 1-39, November.
    19. Thirunavukkarasu, M. & Sawle, Yashwant & Lala, Himadri, 2023. "A comprehensive review on optimization of hybrid renewable energy systems using various optimization techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).
    20. Copp, David A. & Nguyen, Tu A. & Byrne, Raymond H. & Chalamala, Babu R., 2022. "Optimal sizing of distributed energy resources for planning 100% renewable electric power systems," Energy, Elsevier, vol. 239(PE).

    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:13:y:2020:i:16:p:4214-:d:399234. 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.