Fulin Fan, Ivana Kockar, Han Xu, 等. Scheduling framework using dynamic optimal power flow for battery energy storage systems[J]. 中国电机工程学会电力与能源系统学报(英文), 2022,8(1):271-280.
Fulin Fan, Ivana Kockar, Han Xu, et al. Scheduling framework using dynamic optimal power flow for battery energy storage systems[J]. CSEE Journal of Power and Energy Systems, 2022, 8(1): 271-280.
Fulin Fan, Ivana Kockar, Han Xu, 等. Scheduling framework using dynamic optimal power flow for battery energy storage systems[J]. 中国电机工程学会电力与能源系统学报(英文), 2022,8(1):271-280.DOI: 10.17775/CSEEJPES.2020.03710.
Fulin Fan, Ivana Kockar, Han Xu, et al. Scheduling framework using dynamic optimal power flow for battery energy storage systems[J]. CSEE Journal of Power and Energy Systems, 2022, 8(1): 271-280.DOI: 10.17775/CSEEJPES.2020.03710.
Scheduling framework using dynamic optimal power flow for battery energy storage systems
Battery energy storage systems (BESS) are instrumental in the transition to a low carbon electrical network with enhanced flexibility
however
the set objective can be accomplished only through suitable scheduling of their operation. This paper develops a dynamic optimal power flow (DOPF)-based scheduling framework to optimize the day(s)-ahead operation of a grid-scale BESS aiming to mitigate the predicted limits on the renewable energy generation as well as smooth out the network demand to be supplied by conventional generators. In DOPF
all the generating units
including the ones that model the exports and imports of the BESS
across the entire network and the complete time horizon are integrated on to a single network. Subsequently
an AC-OPF is applied to dispatch their power outputs to minimize the total generation cost
while satisfying the power balance equations
and handling the unit and network constraints at each time step coupled with intertemporal constraints associated with the state of charge (SOC). Furthermore
the DOPF developed here entails the frequently applied constant current-constant voltage charging profile
which is represented in the SOC domain. Considering the practical application of a 1 MW BESS on a particular 33 kV network
the scheduling framework is designed to meet the pragmatic requirements of the optimum utilization of the available energy capacity of BESS in each cycle