A BESS sizing strategy for primary frequency regulation support of solar photovoltaic plants

ABSTRACT: This paper proposes a strategy for sizing a battery energy storage system (BESS) that supports primary frequency regulation (PFR) service of solar photo-voltaic plants. The strategy is composed of an optimization model and a performance assessment algorithm. The optimization model includes...

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Autores:
Mejía Giraldo, Diego
Velásquez Gómez, Gregorio
Muñoz Galeano, Nicolás
Cano Quintero, Juan Bernardo
Lemos Cano, Santiago
Tipo de recurso:
Article of investigation
Fecha de publicación:
2019
Institución:
Universidad de Antioquia
Repositorio:
Repositorio UdeA
Idioma:
eng
OAI Identifier:
oai:bibliotecadigital.udea.edu.co:10495/22568
Acceso en línea:
http://hdl.handle.net/10495/22568
Palabra clave:
Almacenamiento de energía
Energy storage
Baterias solares
Solar batteries
Sistemas de energía fotovoltaica
Photovoltaic power systems
Sistemas de baterías de reserva
Rights
openAccess
License
https://creativecommons.org/licenses/by/4.0/
Description
Summary:ABSTRACT: This paper proposes a strategy for sizing a battery energy storage system (BESS) that supports primary frequency regulation (PFR) service of solar photo-voltaic plants. The strategy is composed of an optimization model and a performance assessment algorithm. The optimization model includes not only investment costs, but also a novel penalty function depending on the state of charge (SoC). This function avoids the existence of a potential inappropriate SoC trajectory during BESS operation that could impede the supply of PFR service. The performance assessment algorithm, fed by the optimization model sizing results, allows the emulation of BESS operation and determines either the success or failure of a particular BESS design. The quality of a BESS design is measured through number of days in whith BESS failed to satisfactorily provide PFR and its associated penalization cost. Battery lifetime, battery replacements, and SoC are also key performance indexes that finally permit making better decisions in the election of the best BESS size. The inclusion of multiple BESS operational restrictions under PFR is another important advantage of this strategy since it adds a realistic characterization of BESS to the analysis. The optimization model was coded using GAMS/CPLEX, and the performance assessment algorithm was implemented in MATLAB. Results were obtained using actual frequency data obtained from the Colombian power system; and the resulting BESS sizes show that the number of BESS penalties, caused by failure to provide PFR service, can be reduced to zero at minimum investment cost.