info:eu-repo/semantics/article
Reliability of autonomous solar-wind microgrids with battery energy storage system applied in the residential sector
Date
2023Registration in:
.
Energy Reports
Author
Zarate Perez, Eliseo
Santos Mejía, Cesar
Sebastián, Rafael
Institutions
Abstract
Residential electricity generation can benefit from the successful deployment of photovoltaic (PV) and wind renewable energy
sources. However, their intermittent nature poses a significant limitation. To address this, a hybrid system can be employed to
enhance system reliability and efficiency. Reliability analysis plays a crucial role in evaluating the energy production capacity
to meet the demand. This study aims to assess the reliability of a hybrid PV/wind microgrid through simulation. Data from
a residence were collected every 10 s, and average values were computed on an hourly basis and exported for computer
processing. Solar irradiation, wind speed, and temperature data were also utilized. The modeling process involved defining
the PV panel, wind turbines, battery energy storage system (BESS), management strategy, and energy autonomy. The results
indicate that when PV and wind systems operate independently, they are unable to consistently reduce the residential energy
deficit. However, the PV/Wind/BESS configuration significantly improves system operation and proves sufficient to meet the
required load in most hours. Through this configuration, only 42.5% of the total PV/wind energy utilized by the residents needs
to be dispatched through the BESS. Moreover, the BESS capacity is reduced by 50% when the systems are used separately. The
public grid only supplies power when the BESS is insufficient to cover the load. Therefore, the optimal sizing of the BESS
plays a critical role in system viability, reducing initial installation costs, regulating microgrid parameters, and contributing
to the reduction of the energy deficit. Hence, investigating the fundamental design parameters of the microgrid and BESS is
essential for identifying the optimal capacity of the system and ensuring model reliability.