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Economic and technical analysis of reactive power provision from distributed energy resources in microgrids

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  • Gandhi, Oktoviano
  • Rodríguez-Gallegos, Carlos D.
  • Zhang, Wenjie
  • Srinivasan, Dipti
  • Reindl, Thomas

Abstract

This work analyses the economic and technical impact of local reactive power provision in grid-connected microgrids with distributed energy resources. Costs of reactive power provision by photovoltaic systems and battery energy storage systems are explicitly formulated and an objective function incorporating the costs is proposed. The advantage of the proposed objective function is validated by comparing it with other objective functions frequently employed in the literature. From various case studies, the extent of economic and technical benefits of local reactive power provision for the microgrid is established. Subsequently, the technical and economic competitiveness of reactive power provision using inverter-based distributed energy resources are compared against those using switched capacitors. Extensive sensitivity analyses are performed to determine the scenarios in which one technology is more competitive than the other. Inverter efficiency has been identified as the most important parameter for reactive power provision from distributed energy resources while electricity price is the most crucial factor for switched capacitors’ competitiveness in producing reactive power.

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  • Gandhi, Oktoviano & Rodríguez-Gallegos, Carlos D. & Zhang, Wenjie & Srinivasan, Dipti & Reindl, Thomas, 2018. "Economic and technical analysis of reactive power provision from distributed energy resources in microgrids," Applied Energy, Elsevier, vol. 210(C), pages 827-841.
    • Handle: RePEc:eee:appene:v:210:y:2018:i:c:p:827-841
    DOI: 10.1016/j.apenergy.2017.08.154
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    1. Quan, Hao & Srinivasan, Dipti & Khosravi, Abbas, 2016. "Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk: A comparative study," Energy, Elsevier, vol. 103(C), pages 735-745.
    2. Jian, Linni & Zheng, Yanchong & Xiao, Xinping & Chan, C.C., 2015. "Optimal scheduling for vehicle-to-grid operation with stochastic connection of plug-in electric vehicles to smart grid," Applied Energy, Elsevier, vol. 146(C), pages 150-161.
    3. Elsied, Moataz & Oukaour, Amrane & Gualous, Hamid & Hassan, Radwan, 2015. "Energy management and optimization in microgrid system based on green energy," Energy, Elsevier, vol. 84(C), pages 139-151.
    4. Cervone, Guido & Clemente-Harding, Laura & Alessandrini, Stefano & Delle Monache, Luca, 2017. "Short-term photovoltaic power forecasting using Artificial Neural Networks and an Analog Ensemble," Renewable Energy, Elsevier, vol. 108(C), pages 274-286.
    5. Kuznetsova, Elizaveta & Li, Yan-Fu & Ruiz, Carlos & Zio, Enrico, 2014. "An integrated framework of agent-based modelling and robust optimization for microgrid energy management," Applied Energy, Elsevier, vol. 129(C), pages 70-88.
    6. Quan, Hao & Srinivasan, Dipti & Khambadkone, Ashwin M. & Khosravi, Abbas, 2015. "A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources," Applied Energy, Elsevier, vol. 152(C), pages 71-82.
    7. Hung, Duong Quoc & Mithulananthan, N. & Bansal, R.C., 2014. "Integration of PV and BES units in commercial distribution systems considering energy loss and voltage stability," Applied Energy, Elsevier, vol. 113(C), pages 1162-1170.
    8. Reddy, S. Surender & Abhyankar, A.R. & Bijwe, P.R., 2011. "Reactive power price clearing using multi-objective optimization," Energy, Elsevier, vol. 36(5), pages 3579-3589.
    9. Sousa, Tiago & Morais, Hugo & Vale, Zita & Castro, Rui, 2015. "A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context," Energy, Elsevier, vol. 85(C), pages 236-250.
    10. Zare, Mohsen & Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Amiri, Babak, 2014. "Multi-objective probabilistic reactive power and voltage control with wind site correlations," Energy, Elsevier, vol. 66(C), pages 810-822.
    11. Kargarian, A. & Raoofat, M. & Mohammadi, M., 2011. "Reactive power market management considering voltage control area reserve and system security," Applied Energy, Elsevier, vol. 88(11), pages 3832-3840.
    12. Antunes, Carlos Henggeler & Pires, Dulce Fernão & Barrico, Carlos & Gomes, Álvaro & Martins, António Gomes, 2009. "A multi-objective evolutionary algorithm for reactive power compensation in distribution networks," Applied Energy, Elsevier, vol. 86(7-8), pages 977-984, July.
    13. Radhakrishnan, Bharat Menon & Srinivasan, Dipti, 2016. "A multi-agent based distributed energy management scheme for smart grid applications," Energy, Elsevier, vol. 103(C), pages 192-204.
    14. Savić, Aleksandar & Đurišić, Željko, 2014. "Optimal sizing and location of SVC devices for improvement of voltage profile in distribution network with dispersed photovoltaic and wind power plants," Applied Energy, Elsevier, vol. 134(C), pages 114-124.
    15. Biswas (Raha), Syamasree & Mandal, Kamal Krishna & Chakraborty, Niladri, 2016. "Pareto-efficient double auction power transactions for economic reactive power dispatch," Applied Energy, Elsevier, vol. 168(C), pages 610-627.
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    2. Xu, Jian & Wang, Jing & Liao, Siyang & Sun, Yuanzhang & Ke, Deping & Li, Xiong & Liu, Ji & Jiang, Yibo & Wei, Congying & Tang, Bowen, 2018. "Stochastic multi-objective optimization of photovoltaics integrated three-phase distribution network based on dynamic scenarios," Applied Energy, Elsevier, vol. 231(C), pages 985-996.
    3. M. A. Graña-López & A. García-Diez & A. Filgueira-Vizoso & J. Chouza-Gestoso & A. Masdías-Bonome, 2019. "Study of the Sustainability of Electrical Power Systems: Analysis of the Causes that Generate Reactive Power," Sustainability, MDPI, vol. 11(24), pages 1-13, December.
    4. Gandhi, Oktoviano & Rodríguez-Gallegos, Carlos D. & Zhang, Wenjie & Reindl, Thomas & Srinivasan, Dipti, 2022. "Levelised cost of PV integration for distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    5. Sayyed Ahmad Ali & Arif Hussain & Waseem Haider & Habib Ur Rehman & Syed Ali Abbas Kazmi, 2023. "Optimal Energy Management System of Isolated Multi-Microgrids with Local Energy Transactive Market with Indigenous PV-, Wind-, and Biomass-Based Resources," Energies, MDPI, vol. 16(4), pages 1-38, February.
    6. Anaya, Karim L. & Pollitt, Michael G., 2020. "Reactive power procurement: A review of current trends," Applied Energy, Elsevier, vol. 270(C).
    7. Anaya, K. & Pollitt, M., 2018. "Reactive Power Procurement: Lessons from Three Leading Countries," Cambridge Working Papers in Economics 1854, Faculty of Economics, University of Cambridge.
    8. Vavilapalli, Sridhar & Umashankar, S. & Sanjeevikumar, P. & Ramachandaramurthy, Vigna K. & Mihet-Popa, Lucian & Fedák, Viliam, 2018. "Three-stage control architecture for cascaded H-Bridge inverters in large-scale PV systems – Real time simulation validation," Applied Energy, Elsevier, vol. 229(C), pages 1111-1127.
    9. Lei Zhang & Yingqi Liu & Beibei Pang & Bingxiang Sun & Ari Kokko, 2020. "Second Use Value of China’s New Energy Vehicle Battery: A View Based on Multi-Scenario Simulation," Sustainability, MDPI, vol. 12(1), pages 1-25, January.
    10. Wang, Licheng & Yan, Ruifeng & Saha, Tapan Kumar, 2019. "Voltage regulation challenges with unbalanced PV integration in low voltage distribution systems and the corresponding solution," Applied Energy, Elsevier, vol. 256(C).
    11. Yin, Linfei & Lu, Yuejiang, 2021. "Expandable deep width learning for voltage control of three-state energy model based smart grids containing flexible energy sources," Energy, Elsevier, vol. 226(C).
    12. Erfan Mohagheghi & Mansour Alramlawi & Aouss Gabash & Frede Blaabjerg & Pu Li, 2020. "Real-Time Active-Reactive Optimal Power Flow with Flexible Operation of Battery Storage Systems," Energies, MDPI, vol. 13(7), pages 1-17, April.
    13. Nevena Srećković & Miran Rošer & Gorazd Štumberger, 2021. "Utilization of Active Distribution Network Elements for Optimization of a Distribution Network Operation," Energies, MDPI, vol. 14(12), pages 1-17, June.
    14. Gandhi, Oktoviano & Zhang, Wenjie & Rodríguez-Gallegos, Carlos D. & Verbois, Hadrien & Sun, Hongbin & Reindl, Thomas & Srinivasan, Dipti, 2020. "Local reactive power dispatch optimisation minimising global objectives," Applied Energy, Elsevier, vol. 262(C).
    15. Silveira, Jose Ronaldo & Brandao, Danilo Iglesias & Fernandes, Nicolas T.D. & Uturbey, Wadaed & Cardoso, Braz, 2021. "Multifunctional dispatchable microgrids," Applied Energy, Elsevier, vol. 282(PA).
    16. Ronaldo Silveira Junior, Jose & Conrado, Bruna R.P. & Matheus dos Santos Alonso, Augusto & Iglesias Brandao, Danilo, 2023. "Interoperability of single-controllable clusters: Aggregate response of low-voltage microgrids," Applied Energy, Elsevier, vol. 340(C).
    17. Rodríguez-Gallegos, Carlos D. & Gandhi, Oktoviano & Bieri, Monika & Reindl, Thomas & Panda, S.K., 2018. "A diesel replacement strategy for off-grid systems based on progressive introduction of PV and batteries: An Indonesian case study," Applied Energy, Elsevier, vol. 229(C), pages 1218-1232.
    18. Singh, Pushpendra & Meena, Nand K. & Yang, Jin & Vega-Fuentes, Eduardo & Bishnoi, Shree Krishna, 2020. "Multi-criteria decision making monarch butterfly optimization for optimal distributed energy resources mix in distribution networks," Applied Energy, Elsevier, vol. 278(C).
    19. Rodríguez-Gallegos, Carlos D. & Yang, Dazhi & Gandhi, Oktoviano & Bieri, Monika & Reindl, Thomas & Panda, S.K., 2018. "A multi-objective and robust optimization approach for sizing and placement of PV and batteries in off-grid systems fully operated by diesel generators: An Indonesian case study," Energy, Elsevier, vol. 160(C), pages 410-429.
    20. Alam, Mollah Rezaul & Alam, M.J.E. & Somani, Abhishek & Melton, Ronald B. & Tushar, Wayes & Bai, Feifei & Yan, Ruifeng & Saha, Tapan K., 2021. "Evaluating the feasibility of transactive approach for voltage management using inverters of a PV plant," Applied Energy, Elsevier, vol. 291(C).
    21. Wu, Raphael & Sansavini, Giovanni, 2020. "Integrating reliability and resilience to support the transition from passive distribution grids to islanding microgrids," Applied Energy, Elsevier, vol. 272(C).

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