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Stochastic programming and market equilibrium analysis of microgrids energy management systems

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  • Hu, Ming-Che
  • Lu, Su-Ying
  • Chen, Yen-Haw

Abstract

Microgrids facilitate optimum utilization of distributed renewable energy, provides better local energy supply, and reduces transmission loss and greenhouse gas emission. Because the uncertainty in energy demand affects the energy demand and supply system, the aim of this research is to develop a stochastic optimization and its market equilibrium for microgrids in the electricity market. Therefore, a two-stage stochastic programming model for microgrids and the market competition model are derived in this paper. In the stochastic model, energy demand and supply uncertainties are considered. Furthermore, a case study of the stochastic model is conducted to simulate the uncertainties on the INER microgrids in Taiwanese market. The optimal investment of the generators and batteries installation and operating strategies are determined under energy demand and supply uncertainties for the INER microgrids. The results show optimal investment and operating strategies for the current INER microgrids are also determined by the proposed two-stage stochastic model in the market. In addition, trade-off between the battery capacity and microgrids performance is investigated. Battery usage and power trading between the microgrids and main grid systems are the functions of battery capacity.

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  • Hu, Ming-Che & Lu, Su-Ying & Chen, Yen-Haw, 2016. "Stochastic programming and market equilibrium analysis of microgrids energy management systems," Energy, Elsevier, vol. 113(C), pages 662-670.
  • Handle: RePEc:eee:energy:v:113:y:2016:i:c:p:662-670
    DOI: 10.1016/j.energy.2016.07.061
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    1. Lu, D. & Fakham, H. & Zhou, T. & François, B., 2010. "Application of Petri nets for the energy management of a photovoltaic based power station including storage units," Renewable Energy, Elsevier, vol. 35(6), pages 1117-1124.
    2. Abu-Sharkh, S. & Arnold, R.J. & Kohler, J. & Li, R. & Markvart, T. & Ross, J.N. & Steemers, K. & Wilson, P. & Yao, R., 2006. "Can microgrids make a major contribution to UK energy supply?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(2), pages 78-127, April.
    3. Trujillo, C.L. & Velasco, D. & Figueres, E. & Garcerá, G. & Ortega, R., 2011. "Modeling and control of a push-pull converter for photovoltaic microinverters operating in island mode," Applied Energy, Elsevier, vol. 88(8), pages 2824-2834, August.
    4. Neil Strachan, 2007. "Setting greenhouse gas emission targets under baseline uncertainty: the Bush Climate Change Initiative," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 12(4), pages 455-470, May.
    5. Niknam, Taher & Khodaei, Amin & Fallahi, Farhad, 2009. "A new decomposition approach for the thermal unit commitment problem," Applied Energy, Elsevier, vol. 86(9), pages 1667-1674, September.
    6. Ren, Hongbo & Gao, Weijun, 2010. "A MILP model for integrated plan and evaluation of distributed energy systems," Applied Energy, Elsevier, vol. 87(3), pages 1001-1014, March.
    7. Siddiqui, Afzal S. & Marnay, Chris, 2008. "Distributed generation investment by a microgrid under uncertainty," Energy, Elsevier, vol. 33(12), pages 1729-1737.
    8. Morais, Hugo & Kádár, Péter & Faria, Pedro & Vale, Zita A. & Khodr, H.M., 2010. "Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming," Renewable Energy, Elsevier, vol. 35(1), pages 151-156.
    9. Tsikalakis, A.G. & Hatziargyriou, N.D., 2007. "Environmental benefits of distributed generation with and without emissions trading," Energy Policy, Elsevier, vol. 35(6), pages 3395-3409, June.
    10. Moisés Costa, Paulo & Matos, Manuel A., 2010. "Capacity credit of microgeneration and microgrids," Energy Policy, Elsevier, vol. 38(10), pages 6330-6337, October.
    11. Kanudia, Amit & Loulou, Richard, 1998. "Robust responses to climate change via stochastic MARKAL: The case of Quebec," European Journal of Operational Research, Elsevier, vol. 106(1), pages 15-30, April.
    12. Chaurey, A. & Kandpal, T.C., 2010. "A techno-economic comparison of rural electrification based on solar home systems and PV microgrids," Energy Policy, Elsevier, vol. 38(6), pages 3118-3129, June.
    13. Kelleher, J. & Ringwood, J.V., 2009. "A computational tool for evaluating the economics of solar and wind microgeneration of electricity," Energy, Elsevier, vol. 34(4), pages 401-409.
    14. Kamel, Rashad M. & Chaouachi, Aymen & Nagasaka, Ken, 2010. "Wind power smoothing using fuzzy logic pitch controller and energy capacitor system for improvement Micro-Grid performance in islanding mode," Energy, Elsevier, vol. 35(5), pages 2119-2129.
    15. Hu, Ming-Che & Hobbs, Benjamin F., 2010. "Analysis of multi-pollutant policies for the U.S. power sector under technology and policy uncertainty using MARKAL," Energy, Elsevier, vol. 35(12), pages 5430-5442.
    16. Bayod-Rújula, Angel A., 2009. "Future development of the electricity systems with distributed generation," Energy, Elsevier, vol. 34(3), pages 377-383.
    17. 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.
    18. Vachirasricirikul, Sitthidet & Ngamroo, Issarachai, 2011. "Robust controller design of heat pump and plug-in hybrid electric vehicle for frequency control in a smart microgrid based on specified-structure mixed H2/H∞ control technique," Applied Energy, Elsevier, vol. 88(11), pages 3860-3868.
    19. Costa, Paulo Moisés & Matos, Manuel A. & Peças Lopes, J.A., 2008. "Regulation of microgeneration and microgrids," Energy Policy, Elsevier, vol. 36(10), pages 3893-3904, October.
    Full references (including those not matched with items on IDEAS)

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    17. Moradi, Hadis & Esfahanian, Mahdi & Abtahi, Amir & Zilouchian, Ali, 2018. "Optimization and energy management of a standalone hybrid microgrid in the presence of battery storage system," Energy, Elsevier, vol. 147(C), pages 226-238.
    18. Aryani, Morteza & Ahmadian, Mohammad & Sheikh-El-Eslami, Mohammad-Kazem, 2021. "Coordination of risk-based generation investments in conventional and renewable capacities in oligopolistic electricity markets: A robust regulatory tool," Energy, Elsevier, vol. 214(C).
    19. Chen, Tengpeng & Cao, Yuhao & Qing, Xinlin & Zhang, Jingrui & Sun, Yuhao & Amaratunga, Gehan A.J., 2022. "Multi-energy microgrid robust energy management with a novel decision-making strategy," Energy, Elsevier, vol. 239(PA).
    20. Zhu, Junjie & Huang, Shengjun & Liu, Yajie & Lei, Hongtao & Sang, Bo, 2021. "Optimal energy management for grid-connected microgrids via expected-scenario-oriented robust optimization," Energy, Elsevier, vol. 216(C).
    21. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.
    22. Àlex Alonso-Travesset & Helena Martín & Sergio Coronas & Jordi de la Hoz, 2022. "Optimization Models under Uncertainty in Distributed Generation Systems: A Review," Energies, MDPI, vol. 15(5), pages 1-40, March.
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