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Priority load control algorithm for optimal energy management in stand-alone photovoltaic systems

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  • Faxas-Guzmán, J.
  • García-Valverde, R.
  • Serrano-Luján, L.
  • Urbina, A.

Abstract

In stand-alone PV System facilities no grid connection exists, therefore the solar generator and battery bank have to be carefully sized in order to supply the energy demand for a given period of time. Batteries are considered as a weak component of the system, comprising an important part of the total cost and are usually replaced one or two times during PV system lifetime. A priority load control algorithm has been developed in order to gain an optimal energy management over system loads and the battery storage, and therefore provides a better energy management efficiency and guarantee the energy supply for critical loads. This will increase the reliability of the system and the end-user satisfaction. This article describes a stand-alone PV system model used for the development of a priority load control algorithm and explains and implements the algorithm. The results of several test scenario simulations are shown and discussed.

Suggested Citation

  • Faxas-Guzmán, J. & García-Valverde, R. & Serrano-Luján, L. & Urbina, A., 2014. "Priority load control algorithm for optimal energy management in stand-alone photovoltaic systems," Renewable Energy, Elsevier, vol. 68(C), pages 156-162.
    • Handle: RePEc:eee:renene:v:68:y:2014:i:c:p:156-162
    DOI: 10.1016/j.renene.2014.01.040
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    References listed on IDEAS

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    1. Lujano-Rojas, Juan M. & Monteiro, Cláudio & Dufo-López, Rodolfo & Bernal-Agustín, José L., 2012. "Optimum load management strategy for wind/diesel/battery hybrid power systems," Renewable Energy, Elsevier, vol. 44(C), pages 288-295.
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    Cited by:

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    2. Thiaux, Yaël & Dang, Thu Thuy & Schmerber, Louis & Multon, Bernard & Ben Ahmed, Hamid & Bacha, Seddik & Tran, Quoc Tuan, 2019. "Demand-side management strategy in stand-alone hybrid photovoltaic systems with real-time simulation of stochastic electricity consumption behavior," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    3. Bhowmik, Chiranjib & Bhowmik, Sumit & Ray, Amitava & Pandey, Krishna Murari, 2017. "Optimal green energy planning for sustainable development: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 796-813.
    4. Robert Antonio Salas-Puente & Silvia Marzal & Raúl González-Medina & Emilio Figueres & Gabriel Garcera, 2018. "Power Management of the DC Bus Connected Converters in a Hybrid AC/DC Microgrid Tied to the Main Grid," Energies, MDPI, vol. 11(4), pages 1-22, March.
    5. Wu, Zhou & Tazvinga, Henerica & Xia, Xiaohua, 2015. "Demand side management of photovoltaic-battery hybrid system," Applied Energy, Elsevier, vol. 148(C), pages 294-304.
    6. Park, Alex & Lappas, Petros, 2017. "Evaluating demand charge reduction for commercial-scale solar PV coupled with battery storage," Renewable Energy, Elsevier, vol. 108(C), pages 523-532.
    7. Danny Espín-Sarzosa & Rodrigo Palma-Behnke & Oscar Núñez-Mata, 2020. "Energy Management Systems for Microgrids: Main Existing Trends in Centralized Control Architectures," Energies, MDPI, vol. 13(3), pages 1-32, January.
    8. Tang, Ruoli & Wu, Zhou & Li, Xin, 2018. "Optimal operation of photovoltaic/battery/diesel/cold-ironing hybrid energy system for maritime application," Energy, Elsevier, vol. 162(C), pages 697-714.
    9. Mazzola, Simone & Astolfi, Marco & Macchi, Ennio, 2015. "A detailed model for the optimal management of a multigood microgrid," Applied Energy, Elsevier, vol. 154(C), pages 862-873.

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