TY - GEN
T1 - Adaptive Power Pinch Analysis for Energy management of Hybrid Energy Storage Systems
AU - Etim, Nyong Bassey Bassey
AU - Giaouris, Damian
AU - Papadopoulos, Athanasios I.
AU - Patsios, Haris
AU - Papadopoulou, Simira
AU - Voutetakis, Spyros
AU - Seferlis, Panos
AU - Walker, Sara
AU - Taylor, Philip
AU - Gadoue, Shady
N1 - 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 ; Conference date: 27-05-2018 Through 30-05-2018
PY - 2018/4/26
Y1 - 2018/4/26
N2 - This work proposes a hierarchical control based power management strategy exploiting an adaptive Power Pinch analysis algorithm. The power pinch analysis is aided via the insight-based graphical power grand composite curve (PGCC) of the hybrid energy storage system's (HESS) model. This results in the identification of an optimal power management strategy (PMS), effected at the beginning of a control horizon on the HESS. However, a recent study showed that weather and load uncertainty distorts the desired shaped PGCC and consequently leads to the violation of the energy storage's state of charge operating set points. In this work in order to negate the effect of uncertainty, the current output state is utilized as a feedback control. The PGCC is shaped within a receding horizon model predictive control framework. The PGCC re-computation ensues only if the error variance, due to uncertainty, between the real and the estimated battery's state of charge (SOAccBAT) is greater than 5%. The proposed method is evaluated against the standard or Day-Ahead pinch analysis open loop strategy and shows a reduction in over discharging and overcharging of the battery and fossil fuel emission impact by 15%, 44.97%, and 8.8% respectively.
AB - This work proposes a hierarchical control based power management strategy exploiting an adaptive Power Pinch analysis algorithm. The power pinch analysis is aided via the insight-based graphical power grand composite curve (PGCC) of the hybrid energy storage system's (HESS) model. This results in the identification of an optimal power management strategy (PMS), effected at the beginning of a control horizon on the HESS. However, a recent study showed that weather and load uncertainty distorts the desired shaped PGCC and consequently leads to the violation of the energy storage's state of charge operating set points. In this work in order to negate the effect of uncertainty, the current output state is utilized as a feedback control. The PGCC is shaped within a receding horizon model predictive control framework. The PGCC re-computation ensues only if the error variance, due to uncertainty, between the real and the estimated battery's state of charge (SOAccBAT) is greater than 5%. The proposed method is evaluated against the standard or Day-Ahead pinch analysis open loop strategy and shows a reduction in over discharging and overcharging of the battery and fossil fuel emission impact by 15%, 44.97%, and 8.8% respectively.
KW - Adaptive PMS
KW - Adaptive Power Pinch
KW - MPC
KW - Power Grand composite curve
KW - Smart Grid
U2 - 10.1109/ISCAS.2018.8351732
DO - 10.1109/ISCAS.2018.8351732
M3 - Chapter in a published conference proceeding
T3 - Proceedings - IEEE International Symposium on Circuits and Systems
BT - 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings
PB - IEEE
CY - United States
T2 - 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018
Y2 - 27 May 2018 through 30 May 2018
ER -
