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Energy management in microgrid with considering high penetration of renewable resources and surplus power generation problem

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  • Tabar, Vahid Sohrabi
  • Abbasi, Vahid

Abstract

Energy management in electrical networks is an important issue that is considered by many in recent studies. This problem becomes more important due to the proliferation and development of renewable generators and their uncertain behavior. Global warming, environmental and economic issues are the main reasons of using renewable resources in electrical networks. Moreover, by increasing the penetration of renewable resources, the surplus power generation problem is appeared in the electrical networks. In this paper, the effect of renewable resources penetration and surplus power generation issues have been investigated. Therefore, a microgrid with high penetration of renewable resources has been utilized in this study with the aim of achieving efficient energy management. In order to overcome the mentioned problems, this paper investigates the advantages and defects of three main strategies which include storing the surplus power by electrical storage, converting the extra power to the hydrogen as a powerful energy carrier and transferring the surplus power to the main grid. Afterward, a comprehensive solution has been presented to resolve the renewable resources penetration and defects of the mentioned strategies. It is worth mentioning that the energy management is presented for future 24-h in which the cost and pollution objective functions are minimized simultaneously. Furthermore, the effects of load, wind speed and solar radiation uncertainties are investigated in the proposed planning. Finally, a sensitivity analysis is presented to reveal the effect of parameters variations on the objective functions. The final results show that with optimizing the energy storage, the cost and pollution are reduced from 3842.981 $ and 75.88 kg to 2888.33 $ and zero kg. As well, by optimizing the tie line capacity and utilizing the power to gas system a revenue about 1720 $ and 210.735 $ are obtained, respectively. Nevertheless, the pollution problem has still remained. In return, the amount of revenue and pollution in the final presented method are about 472.46 $ and zero kg and the surplus problem is totally solved.

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  • Tabar, Vahid Sohrabi & Abbasi, Vahid, 2019. "Energy management in microgrid with considering high penetration of renewable resources and surplus power generation problem," Energy, Elsevier, vol. 189(C).
  • Handle: RePEc:eee:energy:v:189:y:2019:i:c:s0360544219319590
    DOI: 10.1016/j.energy.2019.116264
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    as
    1. Gu, Chenghong & Tang, Can & Xiang, Yue & Xie, Da, 2019. "Power-to-gas management using robust optimisation in integrated energy systems," Applied Energy, Elsevier, vol. 236(C), pages 681-689.
    2. Tabatabaee, Sajad & Mortazavi, Seyed Saeedallah & Niknam, Taher, 2017. "Stochastic scheduling of local distribution systems considering high penetration of plug-in electric vehicles and renewable energy sources," Energy, Elsevier, vol. 121(C), pages 480-490.
    3. Li, Qiang & Gao, Mengkai & Lin, Houfei & Chen, Ziyu & Chen, Minyou, 2019. "MAS-based distributed control method for multi-microgrids with high-penetration renewable energy," Energy, Elsevier, vol. 171(C), pages 284-295.
    4. Tabar, Vahid Sohrabi & Ghassemzadeh, Saeid & Tohidi, Sajjad, 2019. "Energy management in hybrid microgrid with considering multiple power market and real time demand response," Energy, Elsevier, vol. 174(C), pages 10-23.
    5. Li, Gang & Zheng, Xuefei, 2016. "Thermal energy storage system integration forms for a sustainable future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 736-757.
    6. Hawkes, A.D. & Leach, M.A., 2009. "Modelling high level system design and unit commitment for a microgrid," Applied Energy, Elsevier, vol. 86(7-8), pages 1253-1265, July.
    7. Mahani, Khashayar & Farzan, Farbod & Jafari, Mohsen A., 2017. "Network-aware approach for energy storage planning and control in the network with high penetration of renewables," Applied Energy, Elsevier, vol. 195(C), pages 974-990.
    8. Jo, J.H. & Aldeman, M.R. & Loomis, D.G., 2018. "Optimum penetration of regional utility-scale renewable energy systems," Renewable Energy, Elsevier, vol. 118(C), pages 328-334.
    9. Zhou, Bin & Xu, Da & Chan, Ka Wing & Li, Canbing & Cao, Yijia & Bu, Siqi, 2017. "A two-stage framework for multiobjective energy management in distribution networks with a high penetration of wind energy," Energy, Elsevier, vol. 135(C), pages 754-766.
    10. Nunes, Juliana Barbosa & Mahmoudi, Nadali & Saha, Tapan Kumar & Chattopadhyay, Debabrata, 2018. "A stochastic integrated planning of electricity and natural gas networks for Queensland, Australia considering high renewable penetration," Energy, Elsevier, vol. 153(C), pages 539-553.
    11. You, Wei & Geng, Yong & Dong, Huijuan & Wilson, Jeffrey & Pan, Hengyu & Wu, Rui & Sun, Lu & Zhang, Xi & Liu, Zhiqing, 2018. "Technical and economic assessment of RES penetration by modelling China's existing energy system," Energy, Elsevier, vol. 165(PB), pages 900-910.
    12. Rodrigues, E.M.G. & Godina, R. & Santos, S.F. & Bizuayehu, A.W. & Contreras, J. & Catalão, J.P.S., 2014. "Energy storage systems supporting increased penetration of renewables in islanded systems," Energy, Elsevier, vol. 75(C), pages 265-280.
    13. Gioutsos, Dean Marcus & Blok, Kornelis & van Velzen, Leonore & Moorman, Sjoerd, 2018. "Cost-optimal electricity systems with increasing renewable energy penetration for islands across the globe," Applied Energy, Elsevier, vol. 226(C), pages 437-449.
    14. Hamilton, James & Negnevitsky, Michael & Wang, Xiaolin & Lyden, Sarah, 2019. "High penetration renewable generation within Australian isolated and remote power systems," Energy, Elsevier, vol. 168(C), pages 684-692.
    15. Li, Gang, 2016. "Organic Rankine cycle performance evaluation and thermoeconomic assessment with various applications part I: Energy and exergy performance evaluation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 477-499.
    16. Li, Gang, 2016. "Organic Rankine cycle performance evaluation and thermoeconomic assessment with various applications part II: Economic assessment aspect," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 490-505.
    17. Barelli, L. & Desideri, U. & Ottaviano, A., 2015. "Challenges in load balance due to renewable energy sources penetration: The possible role of energy storage technologies relative to the Italian case," Energy, Elsevier, vol. 93(P1), pages 393-405.
    18. Villanueva, D. & Feijóo, A., 2010. "Wind power distributions: A review of their applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1490-1495, June.
    19. Wang, Dongxiao & Qiu, Jing & Reedman, Luke & Meng, Ke & Lai, Loi Lei, 2018. "Two-stage energy management for networked microgrids with high renewable penetration," Applied Energy, Elsevier, vol. 226(C), pages 39-48.
    20. Tabar, Vahid Sohrabi & Jirdehi, Mehdi Ahmadi & Hemmati, Reza, 2017. "Energy management in microgrid based on the multi objective stochastic programming incorporating portable renewable energy resource as demand response option," Energy, Elsevier, vol. 118(C), pages 827-839.
    21. Bartolucci, Lorenzo & Cordiner, Stefano & Mulone, Vincenzo & Rocco, Vittorio & Rossi, Joao Luis, 2018. "Renewable source penetration and microgrids: Effects of MILP – Based control strategies," Energy, Elsevier, vol. 152(C), pages 416-426.
    22. Reihani, Ehsan & Motalleb, Mahdi & Ghorbani, Reza & Saad Saoud, Lyes, 2016. "Load peak shaving and power smoothing of a distribution grid with high renewable energy penetration," Renewable Energy, Elsevier, vol. 86(C), pages 1372-1379.
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    15. Mahmoud M. Gamil & Soichirou Ueda & Akito Nakadomari & Keifa Vamba Konneh & Tomonobu Senjyu & Ashraf M. Hemeida & Mohammed Elsayed Lotfy, 2022. "Optimal Multi-Objective Power Scheduling of a Residential Microgrid Considering Renewable Sources and Demand Response Technique," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    16. Lu, Xiaoxing & Li, Kangping & Xu, Hanchen & Wang, Fei & Zhou, Zhenyu & Zhang, Yagang, 2020. "Fundamentals and business model for resource aggregator of demand response in electricity markets," Energy, Elsevier, vol. 204(C).
    17. Gerald Jones & Xueping Li & Yulin Sun, 2024. "Robust Energy Management Policies for Solar Microgrids via Reinforcement Learning," Energies, MDPI, vol. 17(12), pages 1-22, June.
    18. Constantino Dário Justo & José Eduardo Tafula & Pedro Moura, 2022. "Planning Sustainable Energy Systems in the Southern African Development Community: A Review of Power Systems Planning Approaches," Energies, MDPI, vol. 15(21), pages 1-28, October.
    19. Mukhopadhyay, Bineeta & Das, Debapriya, 2021. "Optimal multi-objective expansion planning of a droop-regulated islanded microgrid," Energy, Elsevier, vol. 218(C).

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