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

Angel L. Cedeño (), Reinier López Ahuar, José Rojas, Gonzalo Carvajal, César Silva and Juan C. Agüero
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Angel L. Cedeño: Departamento Electrónica, Universidad Técnica Federico Santa María (UTFSM), Av. España 1680, Valparaíso 2390123, 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
Juan C. Agüero: Departamento Electrónica, Universidad Técnica Federico Santa María (UTFSM), Av. España 1680, Valparaíso 2390123, Chile

Energies, 2022, vol. 15, issue 17, 1-21

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.

Keywords: battery energy storage system; photovoltaic systems; MPC; MILP (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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