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A micro-grid operation analysis for cost-effective battery energy storage and RES plants integration

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  • Barelli, L.
  • Bidini, G.
  • Bonucci, F.

Abstract

Penetration of renewable energy is strongly slowed by its characteristic intermittency and fluctuating trend and by the inadequacy of electricity networks. These issues can be addressed through the development of new or improved storage technologies with higher performance, availability, durability, safety and lower costs. In the present work, micro-grids characterized by the presence of different subsections including renewable plants coupled with batteries storage solution are investigated through the development of a suitable code. Several design conditions and features, related to RES plant, storage system and users, were considered in order to realize a sensitivity analysis aimed to examine, on a yearly base and with one minute time step, interactions among the different micro-grid subsections and to identify the best solutions from both economic and energy point of views.

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  • Barelli, L. & Bidini, G. & Bonucci, F., 2016. "A micro-grid operation analysis for cost-effective battery energy storage and RES plants integration," Energy, Elsevier, vol. 113(C), pages 831-844.
    • Handle: RePEc:eee:energy:v:113:y:2016:i:c:p:831-844
    DOI: 10.1016/j.energy.2016.07.117
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    Cited by:

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    7. Linda Barelli & Gianni Bidini & Paolo Cherubini & Andrea Micangeli & Dario Pelosi & Carlo Tacconelli, 2019. "How Hybridization of Energy Storage Technologies Can Provide Additional Flexibility and Competitiveness to Microgrids in the Context of Developing Countries," Energies, MDPI, vol. 12(16), pages 1-22, August.
    8. Linda Barelli & Gianni Bidini & Fabio Bonucci & Luca Castellini & Simone Castellini & Andrea Ottaviano & Dario Pelosi & Alberto Zuccari, 2018. "Dynamic Analysis of a Hybrid Energy Storage System (H-ESS) Coupled to a Photovoltaic (PV) Plant," Energies, MDPI, vol. 11(2), pages 1-23, February.
    9. Barelli, L. & Bidini, G. & Ottaviano, A., 2017. "Integration of SOFC/GT hybrid systems in Micro-Grids," Energy, Elsevier, vol. 118(C), pages 716-728.
    10. Roy, Kallol & Mandal, Kamal Krishna & Mandal, Atis Chandra, 2019. "Ant-Lion Optimizer algorithm and recurrent neural network for energy management of micro grid connected system," Energy, Elsevier, vol. 167(C), pages 402-416.
    11. Bartolucci, Lorenzo & Cordiner, Stefano & Mulone, Vincenzo & Rocco, Vittorio & Rossi, Joao Luis, 2018. "Hybrid renewable energy systems for renewable integration in microgrids: Influence of sizing on performance," Energy, Elsevier, vol. 152(C), pages 744-758.
    12. Baghaee, H.R. & Mirsalim, M. & Gharehpetian, G.B. & Talebi, H.A., 2016. "Reliability/cost-based multi-objective Pareto optimal design of stand-alone wind/PV/FC generation microgrid system," Energy, Elsevier, vol. 115(P1), pages 1022-1041.
    13. Nojavan, Sayyad & Majidi, Majid & Esfetanaj, Naser Nourani, 2017. "An efficient cost-reliability optimization model for optimal siting and sizing of energy storage system in a microgrid in the presence of responsible load management," Energy, Elsevier, vol. 139(C), pages 89-97.
    14. Yong Long & Yu Wang & Chengrong Pan, 2018. "Incentive Mechanism of Micro-grid Project Development," Sustainability, MDPI, vol. 10(1), pages 1-19, January.
    15. Lingmin, Chen & Jiekang, Wu & Fan, Wu & Huiling, Tang & Changjie, Li & Yan, Xiong, 2020. "Energy flow optimization method for multi-energy system oriented to combined cooling, heating and power," Energy, Elsevier, vol. 211(C).
    16. Wang, Yubo & Shi, Wenbo & Wang, Bin & Chu, Chi-Cheng & Gadh, Rajit, 2017. "Optimal operation of stationary and mobile batteries in distribution grids," Applied Energy, Elsevier, vol. 190(C), pages 1289-1301.
    17. Wang, Luhao & Li, Qiqiang & Ding, Ran & Sun, Mingshun & Wang, Guirong, 2017. "Integrated scheduling of energy supply and demand in microgrids under uncertainty: A robust multi-objective optimization approach," Energy, Elsevier, vol. 130(C), pages 1-14.

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