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Optimizing Capacities of Distributed Generation and Energy Storage in a Small Autonomous Power System Considering Uncertainty in Renewables

Author

Listed:
  • Ying-Yi Hong

    (Department of Electrical Engineering, Chung Yuan Christian University, 200 Chung Pei Road, Taoyuan 32023, Taiwan)

  • Yuan-Ming Lai

    (Department of Electrical Engineering, Chung Yuan Christian University, 200 Chung Pei Road, Taoyuan 32023, Taiwan)

  • Yung-Ruei Chang

    (Division of Smart Grid, Institute of Nuclear Energy Research, Longtan 32546, Taiwan)

  • Yih-Der Lee

    (Division of Smart Grid, Institute of Nuclear Energy Research, Longtan 32546, Taiwan)

  • Pang-Wei Liu

    (Division of Smart Grid, Institute of Nuclear Energy Research, Longtan 32546, Taiwan)

Abstract

This paper explores real power generation planning, considering distributed generation resources and energy storage in a small standalone power system. On account of the Kyoto Protocol and Copenhagen Accord, wind and photovoltaic (PV) powers are considered as clean and renewable energies. In this study, a genetic algorithm (GA) was used to determine the optimal capacities of wind-turbine-generators, PV, diesel generators and energy storage in a small standalone power system. The investment costs (installation, unit and maintenance costs) of the distributed generation resources and energy storage and the cost of fuel for the diesel generators were minimized while the reliability requirement and CO 2 emission limit were fulfilled. The renewable sources and loads were modeled by random variables because of their uncertainties. The equality and inequality constraints in the genetic algorithms were treated by cumulant effects and cumulative probability of random variables, respectively. The IEEE reliability data for an 8760 h load profile with a 150 kW peak load were used to demonstrate the applicability of the proposed method.

Suggested Citation

  • Ying-Yi Hong & Yuan-Ming Lai & Yung-Ruei Chang & Yih-Der Lee & Pang-Wei Liu, 2015. "Optimizing Capacities of Distributed Generation and Energy Storage in a Small Autonomous Power System Considering Uncertainty in Renewables," Energies, MDPI, vol. 8(4), pages 1-20, March.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:4:p:2473-2492:d:47504
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    References listed on IDEAS

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    1. Kashefi Kaviani, A. & Riahy, G.H. & Kouhsari, SH.M., 2009. "Optimal design of a reliable hydrogen-based stand-alone wind/PV generating system, considering component outages," Renewable Energy, Elsevier, vol. 34(11), pages 2380-2390.
    2. Lujano-Rojas, Juan M. & Dufo-López, Rodolfo & Bernal-Agustín, José L., 2013. "Probabilistic modelling and analysis of stand-alone hybrid power systems," Energy, Elsevier, vol. 63(C), pages 19-27.
    3. Lujano-Rojas, Juan M. & Dufo-López, Rodolfo & Bernal-Agustín, José L., 2012. "Optimal sizing of small wind/battery systems considering the DC bus voltage stability effect on energy capture, wind speed variability, and load uncertainty," Applied Energy, Elsevier, vol. 93(C), pages 404-412.
    4. Diaf, S. & Notton, G. & Belhamel, M. & Haddadi, M. & Louche, A., 2008. "Design and techno-economical optimization for hybrid PV/wind system under various meteorological conditions," Applied Energy, Elsevier, vol. 85(10), pages 968-987, October.
    5. Chen, Shin-Guang, 2013. "Bayesian approach for optimal PV system sizing under climate change," Omega, Elsevier, vol. 41(2), pages 176-185.
    6. Nelson, D.B. & Nehrir, M.H. & Wang, C., 2006. "Unit sizing and cost analysis of stand-alone hybrid wind/PV/fuel cell power generation systems," Renewable Energy, Elsevier, vol. 31(10), pages 1641-1656.
    7. Kaldellis, J. K., 2002. "Optimum autonomous wind-power system sizing for remote consumers, using long-term wind speed data," Applied Energy, Elsevier, vol. 71(3), pages 215-233, March.
    8. Borhanazad, Hanieh & Mekhilef, Saad & Gounder Ganapathy, Velappa & Modiri-Delshad, Mostafa & Mirtaheri, Ali, 2014. "Optimization of micro-grid system using MOPSO," Renewable Energy, Elsevier, vol. 71(C), pages 295-306.
    9. Sharafi, Masoud & ELMekkawy, Tarek Y., 2014. "Multi-objective optimal design of hybrid renewable energy systems using PSO-simulation based approach," Renewable Energy, Elsevier, vol. 68(C), pages 67-79.
    10. Diaf, S. & Diaf, D. & Belhamel, M. & Haddadi, M. & Louche, A., 2007. "A methodology for optimal sizing of autonomous hybrid PV/wind system," Energy Policy, Elsevier, vol. 35(11), pages 5708-5718, November.
    11. Ai, B. & Yang, H. & Shen, H. & Liao, X., 2003. "Computer-aided design of PV/wind hybrid system," Renewable Energy, Elsevier, vol. 28(10), pages 1491-1512.
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