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Optimization Models for Islanded Micro-Grids: A Comparative Analysis between Linear Programming and Mixed Integer Programming

Author

Listed:
  • Alberto Dolara

    (Department of Energy, Politecnico di Milano, Via La Masa 34, 20156 Milan, Italy)

  • Francesco Grimaccia

    (Department of Energy, Politecnico di Milano, Via La Masa 34, 20156 Milan, Italy)

  • Giulia Magistrati

    (Department of Energy, Politecnico di Milano, Via La Masa 34, 20156 Milan, Italy)

  • Gabriele Marchegiani

    (Elvi Energy S.r.l., Piazza del Tricolore 4, 20129 Milan, Italy)

Abstract

This paper presents a comparison of optimization methods applied to islanded micro-grids including renewable energy sources, diesel generators and battery energy storage systems. In particular, a comparative analysis between an optimization model based on linear programming and a model based on mixed integer programming has been carried out. The general formulation of these models has been presented and applied to a real case study micro-grid installed in Somalia. The case study is an islanded micro-grid supplying the city of Garowe by means of a hybrid power plant, consisting of diesel generators, photovoltaic systems and batteries. In both models the optimization is based on load demand and renewable energy production forecast. The optimized control of the battery state of charge, of the spinning reserve and diesel generators allows harvesting as much renewable power as possible or to minimize the use of fossil fuels in energy production.

Suggested Citation

  • Alberto Dolara & Francesco Grimaccia & Giulia Magistrati & Gabriele Marchegiani, 2017. "Optimization Models for Islanded Micro-Grids: A Comparative Analysis between Linear Programming and Mixed Integer Programming," Energies, MDPI, vol. 10(2), pages 1-20, February.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:2:p:241-:d:90589
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    References listed on IDEAS

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    1. Partovi, Farzad & Nikzad, Mehdi & Mozafari, Babak & Ranjbar, Ali Mohamad, 2011. "A stochastic security approach to energy and spinning reserve scheduling considering demand response program," Energy, Elsevier, vol. 36(5), pages 3130-3137.
    2. Kyriakarakos, George & Dounis, Anastasios I. & Rozakis, Stelios & Arvanitis, Konstantinos G. & Papadakis, George, 2011. "Polygeneration microgrids: A viable solution in remote areas for supplying power, potable water and hydrogen as transportation fuel," Applied Energy, Elsevier, vol. 88(12), pages 4517-4526.
    3. Wierzbowski, Michal & Lyzwa, Wojciech & Musial, Izabela, 2016. "MILP model for long-term energy mix planning with consideration of power system reserves," Applied Energy, Elsevier, vol. 169(C), pages 93-111.
    4. Bischi, Aldo & Taccari, Leonardo & Martelli, Emanuele & Amaldi, Edoardo & Manzolini, Giampaolo & Silva, Paolo & Campanari, Stefano & Macchi, Ennio, 2014. "A detailed MILP optimization model for combined cooling, heat and power system operation planning," Energy, Elsevier, vol. 74(C), pages 12-26.
    5. Emanuele Ogliari & Francesco Grimaccia & Sonia Leva & Marco Mussetta, 2013. "Hybrid Predictive Models for Accurate Forecasting in PV Systems," Energies, MDPI, vol. 6(4), pages 1-12, April.
    6. Changbin Hu & Shanna Luo & Zhengxi Li & Xin Wang & Li Sun, 2015. "Energy Coordinative Optimization of Wind-Storage-Load Microgrids Based on Short-Term Prediction," Energies, MDPI, vol. 8(2), pages 1-24, February.
    7. Tolis, Athanasios I. & Rentizelas, Athanasios A., 2011. "An impact assessment of electricity and emission allowances pricing in optimised expansion planning of power sector portfolios," Applied Energy, Elsevier, vol. 88(11), pages 3791-3806.
    8. Lidula, N.W.A. & Rajapakse, A.D., 2011. "Microgrids research: A review of experimental microgrids and test systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 186-202, January.
    9. Leva, S. & Dolara, A. & Grimaccia, F. & Mussetta, M. & Ogliari, E., 2017. "Analysis and validation of 24 hours ahead neural network forecasting of photovoltaic output power," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 131(C), pages 88-100.
    10. Alberto Dolara & Francesco Grimaccia & Sonia Leva & Marco Mussetta & Emanuele Ogliari, 2015. "A Physical Hybrid Artificial Neural Network for Short Term Forecasting of PV Plant Power Output," Energies, MDPI, vol. 8(2), pages 1-16, February.
    11. Karami, Nabil & Moubayed, Nazih & Outbib, Rachid, 2017. "General review and classification of different MPPT Techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 1-18.
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