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

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 der...

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Published in:Energies (Basel) Vol. 15; no. 17; p. 6427
Main Authors: Cedeño, Angel L., López Ahuar, Reinier, Rojas, José, Carvajal, Gonzalo, Silva, César, Agüero, Juan C.
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.09.2022
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ISSN:1996-1073, 1996-1073
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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.
AbstractList 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.
Audience Academic
Author Carvajal, Gonzalo
Agüero, Juan C.
Cedeño, Angel L.
Silva, César
Rojas, José
López Ahuar, Reinier
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  fullname: Agüero, Juan C.
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Snippet This paper proposes a model-based predictive control strategy based on mixed-integer linear programming for a photovoltaic power plant with battery energy...
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StartPage 6427
SubjectTerms Alternative energy sources
battery energy storage system
Control
Control algorithms
Costs
Efficiency
Electric power-plants
Electricity
Energy industry
Energy storage
Generators
Linear programming
Market prices
MILP
MPC
Optimization
Photovoltaic power generation
photovoltaic systems
Power plants
Profit maximization
Profits
Tariffs
Variables
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Title Model Predictive Control for Photovoltaic Plants with Non-Ideal Energy Storage Using Mixed Integer Linear Programming
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