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Economic analysis and optimal energy management models for microgrid systems: A case study in Taiwan

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  • Chen, Yen-Haw
  • Lu, Su-Ying
  • Chang, Yung-Ruei
  • Lee, Ta-Tung
  • Hu, Ming-Che

Abstract

The purpose of this research is to perform economic analysis, formulate an optimization model, and determine optimal operating strategies for smart microgrid systems. Microgrid systems are electricity supply systems that integrate distributed renewable energy production for local demand. Microgrids are able to reduce transmission losses and improve utilization efficiency of electricity and heat. Further, greenhouse gas emissions are reduced by utilizing an efficient power generation microgrid system. This study presents an energy management model that is used to determine optimal operating strategies with maximum profit for a microgrid system in Taiwan. The smart microgrid system is equipped with energy storage devices, photovoltaic power, and wind power generation systems. Sensitivity analyses of investment in storage capacity and growth in electricity demand are conducted for the smart microgrid model. The results show that appropriate battery capacity should be determined on the basis of both battery efficiency and power supply.

Suggested Citation

  • Chen, Yen-Haw & Lu, Su-Ying & Chang, Yung-Ruei & Lee, Ta-Tung & Hu, Ming-Che, 2013. "Economic analysis and optimal energy management models for microgrid systems: A case study in Taiwan," Applied Energy, Elsevier, vol. 103(C), pages 145-154.
  • Handle: RePEc:eee:appene:v:103:y:2013:i:c:p:145-154
    DOI: 10.1016/j.apenergy.2012.09.023
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    1. Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Narimani, Mohammad Rasoul, 2012. "An efficient scenario-based stochastic programming framework for multi-objective optimal micro-grid operation," Applied Energy, Elsevier, vol. 99(C), pages 455-470.
    2. Moisés Costa, Paulo & Matos, Manuel A., 2010. "Capacity credit of microgeneration and microgrids," Energy Policy, Elsevier, vol. 38(10), pages 6330-6337, October.
    3. Siddiqui, Afzal S. & Maribu, Karl, 2009. "Investment and upgrade in distributed generation under uncertainty," Energy Economics, Elsevier, vol. 31(1), pages 25-37, January.
    4. 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.
    5. Toledo, Olga Moraes & Oliveira Filho, Delly & Diniz, Antônia Sônia Alves Cardoso, 2010. "Distributed photovoltaic generation and energy storage systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(1), pages 506-511, January.
    6. Hogan, William W, 1992. "Contract Networks for Electric Power Transmission," Journal of Regulatory Economics, Springer, vol. 4(3), pages 211-242, September.
    7. 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.
    8. Ren, Hongbo & Zhou, Weisheng & Nakagami, Ken'ichi & Gao, Weijun & Wu, Qiong, 2010. "Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 87(12), pages 3642-3651, December.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Giannoulis, E.D. & Haralambopoulos, D.A., 2011. "Distributed Generation in an isolated grid: Methodology of case study for Lesvos - Greece," Applied Energy, Elsevier, vol. 88(7), pages 2530-2540, July.
    18. Zamora, Ramon & Srivastava, Anurag K., 2010. "Controls for microgrids with storage: Review, challenges, and research needs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(7), pages 2009-2018, September.
    19. Siddiqui, Afzal S. & Marnay, Chris, 2008. "Distributed generation investment by a microgrid under uncertainty," Energy, Elsevier, vol. 33(12), pages 1729-1737.
    20. 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.
    21. 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.
    22. 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.
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