Publication

An analysis of multi objective energy scheduling in PV-BESS system under prediction uncertainty

Journal Article (2021)

Journal

IEEE Transactions on Energy Conversion

Pages

2276-2286

Volume

36

Number

3

Doc link

https://doi.org/10.1109/TEC.2021.3055453

File

Download the digital copy of the doc pdf document

Abstract

Energy storage systems (ESSs) are being considered to overcome issues in modern grids, caused by increasing penetration of renewable generation. Nevertheless, integration of ESS should also be supplemented with an optimal energy management framework to ensure maximum benefits from ESS. Conventional energy management of battery, used with PV system, maximises self-consumption but does not mitigate grid congestion or address battery degradation. Model predictive control (MPC) can alleviate congestion, degradation while maximizing self-consumption. As such, studies will be carried out, in this work, to highlight the improvement with MPC based energy management over conventional method using simulations of one-year system behaviour. As MPC uses forecast information in decision making, the impact of forecast uncertainties will be assessed and addressing the same through constraint tightening will be presented. It is concluded that MPC provides improvement in system behaviour over multiple performance criteria.

Categories

optimal control, optimisation.

Author keywords

Energy Management, Energy Storage, Batteries

Scientific reference

U. Raveendran Nair, M. Sandelic, A. Sangwongwanich, T. Dragicevic, R. Costa and F. Blaabjerg. An analysis of multi objective energy scheduling in PV-BESS system under prediction uncertainty. IEEE Transactions on Energy Conversion, 36(3): 2276-2286, 2021.