.png){kind=icon}
.png){kind=icon}
Return
Optimal Battery Dispatch Using Finite-Input Set Non-Linear Model Predictive Control: Algorithm Development and Case Study
.png){kind=icon}
OA
AI
DOI：10.3390/electronics11010101.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The advancement in battery manufacturing has played a significant role in the use of batteries as a cost-effective energy storage system. This paper proposes an optimal charging and discharging strategy for the battery energy storage system deployed for economic dispatch and supply/demand balancing services in the presence of intermittent renewables such as solar photovoltaic systems. A decision-making strategy for battery charge/discharge operations in a discrete-time rolling horizon framework is developed as a finite-input set non-linear model predictive control instances and a dynamic programming procedure is proposed for its real-time implementation. The proposed scheme is tested on controllable loads and a photovoltaic generation scenario in the premises of a sports centre, as a part of a pilot demonstration of the inteGRIDy EU-funded project. The test results confirm that the implemented stacking of the battery and optimal decision-making algorithm can enhance net saving in the electricity bill of the sports centre, and lead to corresponding CO2 reductions.
Keywords:
battery management systems
smart energy solution
PV generation
non-linear optimization
optimal charging and discharging
dynamic programming