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Coordinated microgrid investment and planning process considering the system operator

Author

Listed:
  • Armendáriz, M.
  • Heleno, M.
  • Cardoso, G.
  • Mashayekh, S.
  • Stadler, M.
  • Nordström, L.

Abstract

Nowadays, a significant number of distribution systems are facing problems to accommodate more photovoltaic (PV) capacity, namely due to the overvoltages during the daylight periods. This has an impact on the private investments in distributed energy resources (DER), since it occurs exactly when the PV prices are becoming attractive, and the opportunity to an energy transition based on solar technologies is being wasted. In particular, this limitation of the networks is a barrier for larger consumers, such as commercial and public buildings, aiming at investing in PV capacity and start operating as microgrids connected to the MV network. To address this challenge, this paper presents a coordinated approach to the microgrid investment and planning problem, where the system operator and the microgrid owner collaborate to improve the voltage control capabilities of the distribution network, increasing the PV potential. The results prove that this collaboration has the benefit of increasing the value of the microgrid investments while improving the quality of service of the system and it should be considered in the future regulatory framework.

Suggested Citation

  • Armendáriz, M. & Heleno, M. & Cardoso, G. & Mashayekh, S. & Stadler, M. & Nordström, L., 2017. "Coordinated microgrid investment and planning process considering the system operator," Applied Energy, Elsevier, vol. 200(C), pages 132-140.
    • Handle: RePEc:eee:appene:v:200:y:2017:i:c:p:132-140
    DOI: 10.1016/j.apenergy.2017.05.076
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    Citations

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    Cited by:

    1. Yang, Yanhong & Pei, Wei & Huo, Qunhai & Sun, Jianjun & Xu, Feng, 2018. "Coordinated planning method of multiple micro-grids and distribution network with flexible interconnection," Applied Energy, Elsevier, vol. 228(C), pages 2361-2374.
    2. Roldán-Blay, Carlos & Escrivá-Escrivá, Guillermo & Roldán-Porta, Carlos & Dasí-Crespo, Daniel, 2023. "Optimal sizing and design of renewable power plants in rural microgrids using multi-objective particle swarm optimization and branch and bound methods," Energy, Elsevier, vol. 284(C).
    3. Haupt, Leon & Schöpf, Michael & Wederhake, Lars & Weibelzahl, Martin, 2020. "The influence of electric vehicle charging strategies on the sizing of electrical energy storage systems in charging hub microgrids," Applied Energy, Elsevier, vol. 273(C).
    4. Gallego-Castillo, Cristobal & Heleno, Miguel & Victoria, Marta, 2021. "Self-consumption for energy communities in Spain: A regional analysis under the new legal framework," Energy Policy, Elsevier, vol. 150(C).
    5. Lu, Tianguang & Ai, Qian & Wang, Zhaoyu, 2018. "Interactive game vector: A stochastic operation-based pricing mechanism for smart energy systems with coupled-microgrids," Applied Energy, Elsevier, vol. 212(C), pages 1462-1475.
    6. 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.
    7. Burillo, Daniel & Chester, Mikhail V. & Ruddell, Benjamin & Johnson, Nathan, 2017. "Electricity demand planning forecasts should consider climate non-stationarity to maintain reserve margins during heat waves," Applied Energy, Elsevier, vol. 206(C), pages 267-277.
    8. Mohammadhafez Bazrafshan & Likhitha Yalamanchili & Nikolaos Gatsis & Juan Gomez, 2019. "Stochastic Planning of Distributed PV Generation," Energies, MDPI, vol. 12(3), pages 1-20, January.
    9. Martín, Mariano & Grossmann, Ignacio E., 2018. "Optimal integration of renewable based processes for fuels and power production: Spain case study," Applied Energy, Elsevier, vol. 213(C), pages 595-610.
    10. Zhu, Dafeng & Yang, Bo & Liu, Qi & Ma, Kai & Zhu, Shanying & Ma, Chengbin & Guan, Xinping, 2020. "Energy trading in microgrids for synergies among electricity, hydrogen and heat networks," Applied Energy, Elsevier, vol. 272(C).
    11. Saumweber, Andrea & Wederhake, Lars & Cardoso, Gonçalo & Fridgen, Gilbert & Heleno, Miguel, 2021. "Designing Pareto optimal electricity retail rates when utility customers are prosumers," Energy Policy, Elsevier, vol. 156(C).
    12. Iria, José & Heleno, Miguel & Cardoso, Gonçalo, 2019. "Optimal sizing and placement of energy storage systems and on-load tap changer transformers in distribution networks," Applied Energy, Elsevier, vol. 250(C), pages 1147-1157.
    13. Rakkyung Ko & Sung-Kwan Joo, 2019. "Stochastic Mixed-Integer Programming (SMIP)-Based Distributed Energy Resource Allocation Method for Virtual Power Plants," Energies, MDPI, vol. 13(1), pages 1-10, December.
    14. Liu, Youbo & Zuo, Kunyu & Liu, Xueqin (Amy) & Liu, Junyong & Kennedy, Jason M., 2018. "Dynamic pricing for decentralized energy trading in micro-grids," Applied Energy, Elsevier, vol. 228(C), pages 689-699.
    15. Guo, Li & Hou, Ruosong & Liu, Yixin & Wang, Chengshan & Lu, Hai, 2020. "A novel typical day selection method for the robust planning of stand-alone wind-photovoltaic-diesel-battery microgrid," Applied Energy, Elsevier, vol. 263(C).

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