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Optimal Economic Dispatch in Microgrids with Renewable Energy Sources

Author

Listed:
  • F. Daniel Santillán-Lemus

    (Postgraduate Department, Polytechnic University of Tulancingo (UPT), Tulancingo 43629, Mexico)

  • Hertwin Minor-Popocatl

    (School Engineering and Business (Postgraduate), Popular Autonomous University of the State of Puebla (UPAEP), Puebla 72410, Mexico)

  • Omar Aguilar-Mejía

    (School Engineering and Business (Postgraduate), Popular Autonomous University of the State of Puebla (UPAEP), Puebla 72410, Mexico)

  • Ruben Tapia-Olvera

    (Department of Electric Power, National Autonomous University of Mexico (UNAM), CDMX 04510, Mexico)

Abstract

Due to the opening of the energy market and agreements for the reduction of pollution emissions, the use of microgrids attracts more attention in the scientific community, but the management of the distribution of electricity has new challenges. This paper considers different distributed generation systems as a main part to design a microgrid and the resources management is defined in a period through proposed dynamic economic dispatch approach. The inputs are obtained by the model predictive control algorithm considering variations of both pattern of consumption and generation systems capacity, including conventional and renewable energy sources. Furthermore, the proposed approach considers a benefits program to customers involving a demand restriction and the costs of regeneration of the pollutants produced by conventional generation systems. The dispatch strategy through a mathematical programming approach seeks to reduce to the minimum the fuel cost of conventional generators, the energy transactions, the regeneration of polluted emissions and, finally, includes the benefit in electricity demand reduction satisfying all restrictions through mathematical programming strategy. The model is implemented in LINGO 17.0 software (Lindo Systems, 1415 North Dayton Street, Chicago, IL, USA). The results exhibit the proposed approach effectiveness through a study case under different considerations.

Suggested Citation

  • F. Daniel Santillán-Lemus & Hertwin Minor-Popocatl & Omar Aguilar-Mejía & Ruben Tapia-Olvera, 2019. "Optimal Economic Dispatch in Microgrids with Renewable Energy Sources," Energies, MDPI, vol. 12(1), pages 1-14, January.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:1:p:181-:d:195428
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    References listed on IDEAS

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    1. Xiuyun Wang & Shaoxin Chen & Yibing Zhou & Jian Wang & Yang Cui, 2018. "Optimal Dispatch of Microgrid with Combined Heat and Power System Considering Environmental Cost," Energies, MDPI, vol. 11(10), pages 1-23, September.
    2. Soshinskaya, Mariya & Crijns-Graus, Wina H.J. & Guerrero, Josep M. & Vasquez, Juan C., 2014. "Microgrids: Experiences, barriers and success factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 659-672.
    3. McLarty, Dustin & Panossian, Nadia & Jabbari, Faryar & Traverso, Alberto, 2019. "Dynamic economic dispatch using complementary quadratic programming," Energy, Elsevier, vol. 166(C), pages 755-764.
    4. Nwulu, Nnamdi I. & Xia, Xiaohua, 2017. "Optimal dispatch for a microgrid incorporating renewables and demand response," Renewable Energy, Elsevier, vol. 101(C), pages 16-28.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Lingling Li & Jiarui Pei & Qiang Shen, 2023. "A Review of Research on Dynamic and Static Economic Dispatching of Hybrid Wind–Thermal Power Microgrids," Energies, MDPI, vol. 16(10), pages 1-23, May.
    2. Hyung-Joon Kim & Mun-Kyeom Kim, 2019. "Multi-Objective Based Optimal Energy Management of Grid-Connected Microgrid Considering Advanced Demand Response," Energies, MDPI, vol. 12(21), pages 1-28, October.
    3. Ismail Marouani & Tawfik Guesmi & Hsan Hadj Abdallah & Badr M. Alshammari & Khalid Alqunun & Ahmed S. Alshammari & Salem Rahmani, 2022. "Combined Economic Emission Dispatch with and without Consideration of PV and Wind Energy by Using Various Optimization Techniques: A Review," Energies, MDPI, vol. 15(12), pages 1-35, June.
    4. Bhatti, Bilal Ahmad & Broadwater, Robert, 2019. "Energy trading in the distribution system using a non-model based game theoretic approach," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    5. Lorenzo Bartolucci & Stefano Cordiner & Vincenzo Mulone & Marina Santarelli, 2019. "Ancillary Services Provided by Hybrid Residential Renewable Energy Systems through Thermal and Electrochemical Storage Systems," Energies, MDPI, vol. 12(12), pages 1-18, June.

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