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An interactive operation management of a micro-grid with multiple distributed generations using multi-objective uniform water cycle algorithm

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  • Deihimi, Ali
  • Keshavarz Zahed, Babak
  • Iravani, Reza

Abstract

Accommodation of DGs (distributed generations) close to loads has led to the concept of MG (micro-grid) for better reliability and quality of energy supply. MG as a clump of consumers and DGs can operate in stand-alone and grid-connected modes, and often needs ESS (energy storage system) to handle generation surplus/shortage. Variations of renewable sources and consumptions along with economical and environmental issues necessitate an efficient OM (operation management) of MG for short-term scheduling of energy outputs of DGs, ESS and exchange route to upstream macro-grid. This paper presents MOUWCA (multi-objective uniform water cycle algorithm) for optimal OM of MG considering operation cost and emission as objectives. The problem is casted to find 24 POFs (pareto-optimal fronts) corresponding to 24 h of the day (unlike previous studies giving one POF per day) to provide more flexibility for selecting hourly compromise solutions. Through an interactive process, charging/discharging of ESS is balanced over a day based on the desired order of hours for discharging ESS. MOUWCA is examined on some benchmark problems and compared with NSGA-II (non-dominated GA-II), MOPSO (multi-objective particle swarm optimization) and NCA (normal constraint algorithm) to verify its effectiveness. MOUWCA is then applied to a typical MG where its superiority is confirmed in comparison to other previously used algorithms.

Suggested Citation

  • Deihimi, Ali & Keshavarz Zahed, Babak & Iravani, Reza, 2016. "An interactive operation management of a micro-grid with multiple distributed generations using multi-objective uniform water cycle algorithm," Energy, Elsevier, vol. 106(C), pages 482-509.
    • Handle: RePEc:eee:energy:v:106:y:2016:i:c:p:482-509
    DOI: 10.1016/j.energy.2016.03.048
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    References listed on IDEAS

    as
    1. Johansson, Bengt, 2013. "Security aspects of future renewable energy systems–A short overview," Energy, Elsevier, vol. 61(C), pages 598-605.
    2. Baziar, Aliasghar & Kavousi-Fard, Abdollah, 2013. "Considering uncertainty in the optimal energy management of renewable micro-grids including storage devices," Renewable Energy, Elsevier, vol. 59(C), pages 158-166.
    3. Ippolito, M.G. & Di Silvestre, M.L. & Riva Sanseverino, E. & Zizzo, G. & Graditi, G., 2014. "Multi-objective optimized management of electrical energy storage systems in an islanded network with renewable energy sources under different design scenarios," Energy, Elsevier, vol. 64(C), pages 648-662.
    4. Niknam, Taher & Golestaneh, Faranak & Malekpour, Ahmadreza, 2012. "Probabilistic energy and operation management of a microgrid containing wind/photovoltaic/fuel cell generation and energy storage devices based on point estimate method and self-adaptive gravitational," Energy, Elsevier, vol. 43(1), pages 427-437.
    5. Aghaei, Jamshid & Alizadeh, Mohammad-Iman, 2013. "Multi-objective self-scheduling of CHP (combined heat and power)-based microgrids considering demand response programs and ESSs (energy storage systems)," Energy, Elsevier, vol. 55(C), pages 1044-1054.
    6. Hong, Ying-Yi & Lin, Jie-Kai, 2013. "Interactive multi-objective active power scheduling considering uncertain renewable energies using adaptive chaos clonal evolutionary programming," Energy, Elsevier, vol. 53(C), pages 212-220.
    7. Moghaddam, Amjad Anvari & Seifi, Alireza & Niknam, Taher & Alizadeh Pahlavani, Mohammad Reza, 2011. "Multi-objective operation management of a renewable MG (micro-grid) with back-up micro-turbine/fuel cell/battery hybrid power source," Energy, Elsevier, vol. 36(11), pages 6490-6507.
    8. Naraharisetti, Pavan Kumar & Karimi, I.A. & Anand, Abhay & Lee, Dong-Yup, 2011. "A linear diversity constraint – Application to scheduling in microgrids," Energy, Elsevier, vol. 36(7), pages 4235-4243.
    9. Mohammadi, Sirus & Mozafari, Babak & Solimani, Soodabeh & Niknam, Taher, 2013. "An Adaptive Modified Firefly Optimisation Algorithm based on Hong's Point Estimate Method to optimal operation management in a microgrid with consideration of uncertainties," Energy, Elsevier, vol. 51(C), pages 339-348.
    10. 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.
    11. Kuznetsova, Elizaveta & Li, Yan-Fu & Ruiz, Carlos & Zio, Enrico & Ault, Graham & Bell, Keith, 2013. "Reinforcement learning for microgrid energy management," Energy, Elsevier, vol. 59(C), pages 133-146.
    12. Soares, J. & Silva, M. & Sousa, T. & Vale, Z. & Morais, H., 2012. "Distributed energy resource short-term scheduling using Signaled Particle Swarm Optimization," Energy, Elsevier, vol. 42(1), pages 466-476.
    13. Motevasel, Mehdi & Seifi, Ali Reza & Niknam, Taher, 2013. "Multi-objective energy management of CHP (combined heat and power)-based micro-grid," Energy, Elsevier, vol. 51(C), pages 123-136.
    14. Moghaddam, Amjad Anvari & Seifi, Alireza & Niknam, Taher, 2012. "Multi-operation management of a typical micro-grids using Particle Swarm Optimization: A comparative study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1268-1281.
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