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Model Predictive Control for Photovoltaic Plants with Non-Ideal Energy Storage Using Mixed Integer Linear Programming

Author

Listed:
  • Angel L. Cedeño

    (Departamento Electrónica, Universidad Técnica Federico Santa María (UTFSM), Av. España 1680, Valparaíso 2390123, Chile
    Advanced Center for Electrical and Electronic Engineering (AC3E), Gral. Bari 699, Valparaíso 2390136, Chile)

  • Reinier López Ahuar

    (Departamento Electrónica, Universidad Técnica Federico Santa María (UTFSM), Av. España 1680, Valparaíso 2390123, Chile)

  • José Rojas

    (Departamento Electrónica, Universidad Técnica Federico Santa María (UTFSM), Av. España 1680, Valparaíso 2390123, Chile)

  • Gonzalo Carvajal

    (Departamento Electrónica, Universidad Técnica Federico Santa María (UTFSM), Av. España 1680, Valparaíso 2390123, Chile)

  • César Silva

    (Departamento Electrónica, Universidad Técnica Federico Santa María (UTFSM), Av. España 1680, Valparaíso 2390123, Chile
    Centro Científico Tecnológico de Valparaíso (CCTVal), Gral. Bari 699, Valparaíso 2390136, Chile)

  • Juan C. Agüero

    (Departamento Electrónica, Universidad Técnica Federico Santa María (UTFSM), Av. España 1680, Valparaíso 2390123, Chile
    Advanced Center for Electrical and Electronic Engineering (AC3E), Gral. Bari 699, Valparaíso 2390136, Chile)

Abstract

This paper proposes a model-based predictive control strategy based on mixed-integer linear programming for a photovoltaic power plant with battery energy storage. The control objective is to maximize the revenues from energy delivered from both photovoltaic panels and batteries to the grid in a deregulated electricity market. For each control interval, the proposed algorithm incorporates information on solar radiation, market prices, and the state of charge of the batteries to determine the intervals of energy injection into the grid to maximize the economic benefits. The proposed strategy considers the rate-based variable efficiency in the battery model and time-varying energies prices, thus providing a more general implementation than previous schemes proposed in the literature for the same purpose. Simulations considering the operational procedures of the Spanish market as a case study show that, by integrating the battery efficiency in the model, the proposed control strategy increments the economic benefits in 21% compared to previous results reported in the literature for the same operational conditions. Additionally, the proposed approach reduces the number of charge and discharge cycles, potentially extending the lifespan of batteries.

Suggested Citation

  • Angel L. Cedeño & Reinier López Ahuar & José Rojas & Gonzalo Carvajal & César Silva & Juan C. Agüero, 2022. "Model Predictive Control for Photovoltaic Plants with Non-Ideal Energy Storage Using Mixed Integer Linear Programming," Energies, MDPI, vol. 15(17), pages 1-21, September.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6427-:d:905302
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    References listed on IDEAS

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    1. Zahra Foroozandeh & Sérgio Ramos & João Soares & Fernando Lezama & Zita Vale & António Gomes & Rodrigo L. Joench, 2020. "A Mixed Binary Linear Programming Model for Optimal Energy Management of Smart Buildings," Energies, MDPI, vol. 13(7), pages 1-16, April.
    2. Yu Hu & Miguel Armada & Maria Jesus Sanchez, 2021. "Potential utilization of Battery Energy Storage Systems (BESS) in the major European electricity markets," Papers 2112.09816, arXiv.org, revised Jun 2022.
    3. Eleonora Achiluzzi & Kirushaanth Kobikrishna & Abenayan Sivabalan & Carlos Sabillon & Bala Venkatesh, 2020. "Optimal Asset Planning for Prosumers Considering Energy Storage and Photovoltaic (PV) Units: A Stochastic Approach," Energies, MDPI, vol. 13(7), pages 1-20, April.
    4. Bullich-Massagué, Eduard & Cifuentes-García, Francisco-Javier & Glenny-Crende, Ignacio & Cheah-Mañé, Marc & Aragüés-Peñalba, Mònica & Díaz-González, Francisco & Gomis-Bellmunt, Oriol, 2020. "A review of energy storage technologies for large scale photovoltaic power plants," Applied Energy, Elsevier, vol. 274(C).
    5. Yuqing Yang & Stephen Bremner & Chris Menictas & Merlinde Kay, 2019. "A Mixed Receding Horizon Control Strategy for Battery Energy Storage System Scheduling in a Hybrid PV and Wind Power Plant with Different Forecast Techniques," Energies, MDPI, vol. 12(12), pages 1-25, June.
    6. Tobajas, Javier & Garcia-Torres, Felix & Roncero-Sánchez, Pedro & Vázquez, Javier & Bellatreche, Ladjel & Nieto, Emilio, 2022. "Resilience-oriented schedule of microgrids with hybrid energy storage system using model predictive control," Applied Energy, Elsevier, vol. 306(PB).
    7. Fred Glover, 1975. "Improved Linear Integer Programming Formulations of Nonlinear Integer Problems," Management Science, INFORMS, vol. 22(4), pages 455-460, December.
    8. Sánchez de la Nieta, Agustín A. & Paterakis, Nikolaos G. & Gibescu, Madeleine, 2020. "Participation of photovoltaic power producers in short-term electricity markets based on rescheduling and risk-hedging mapping," Applied Energy, Elsevier, vol. 266(C).
    9. Arsalis, Alexandros & Papanastasiou, Panos & Georghiou, George E., 2022. "A comparative review of lithium-ion battery and regenerative hydrogen fuel cell technologies for integration with photovoltaic applications," Renewable Energy, Elsevier, vol. 191(C), pages 943-960.
    10. Mohammadi, Kasra & Naderi, Mahmoud & Saghafifar, Mohammad, 2018. "Economic feasibility of developing grid-connected photovoltaic plants in the southern coast of Iran," Energy, Elsevier, vol. 156(C), pages 17-31.
    11. Marvin Barivure Sigalo & Ajit C. Pillai & Saptarshi Das & Mohammad Abusara, 2021. "An Energy Management System for the Control of Battery Storage in a Grid-Connected Microgrid Using Mixed Integer Linear Programming," Energies, MDPI, vol. 14(19), pages 1-14, September.
    12. DiOrio, Nicholas & Denholm, Paul & Hobbs, William B., 2020. "A model for evaluating the configuration and dispatch of PV plus battery power plants," Applied Energy, Elsevier, vol. 262(C).
    13. Zahid Ullah & Arshad & Hany Hassanin, 2022. "Modeling, Optimization, and Analysis of a Virtual Power Plant Demand Response Mechanism for the Internal Electricity Market Considering the Uncertainty of Renewable Energy Sources," Energies, MDPI, vol. 15(14), pages 1-16, July.
    14. Rae-Kyun Kim & Mark B. Glick & Keith R. Olson & Yun-Su Kim, 2020. "MILP-PSO Combined Optimization Algorithm for an Islanded Microgrid Scheduling with Detailed Battery ESS Efficiency Model and Policy Considerations," Energies, MDPI, vol. 13(8), pages 1-17, April.
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