TY - JOUR
T1 - Optimal sizing and control of energy storage in wind power-rich distribution networks
AU - Alnaser, S.W.
AU - Ochoa, L.F.
N1 - This work was supported in part by the EPSRC project WISE PV (Grant EP/K022229/1).
PY - 2015
Y1 - 2015
N2 - This paper presents a planning framework to find the minimum storage sizes (power and energy) at multiple locations in distribution networks to reduce curtailment from renewable distributed generation (DG), specifically wind farms, whilst managing congestion and voltages. A two-stage iterative process is adopted in this framework. The first stage uses a multi-period AC Optimal Power Flow (OPF) across the studied horizon to obtain initial storage sizes considering hourly wind and load profiles. The second stage adopts a high granularity minute-by-minute control driven by a mono-period bi-level AC OPF to tune the first-stage storage sizes according to the actual curtailment. Congestion and voltages are managed through the optimal control of storage (active and reactive power), on-load tap changers (OLTCs), DG power factor, and DG curtailment as last resort. The proposed storage planning framework is applied to a real 33kV network from the North West of England over one week. Results highlight that by embedding high granularity control aspects into planning it is possible to more accurately size storage facilities. Moreover, intelligent management of further flexibility (i.e., OLTCs, storage and DG power factor control) can lead to much smaller storage capacities. This, however, depends on the required level of curtailment.
AB - This paper presents a planning framework to find the minimum storage sizes (power and energy) at multiple locations in distribution networks to reduce curtailment from renewable distributed generation (DG), specifically wind farms, whilst managing congestion and voltages. A two-stage iterative process is adopted in this framework. The first stage uses a multi-period AC Optimal Power Flow (OPF) across the studied horizon to obtain initial storage sizes considering hourly wind and load profiles. The second stage adopts a high granularity minute-by-minute control driven by a mono-period bi-level AC OPF to tune the first-stage storage sizes according to the actual curtailment. Congestion and voltages are managed through the optimal control of storage (active and reactive power), on-load tap changers (OLTCs), DG power factor, and DG curtailment as last resort. The proposed storage planning framework is applied to a real 33kV network from the North West of England over one week. Results highlight that by embedding high granularity control aspects into planning it is possible to more accurately size storage facilities. Moreover, intelligent management of further flexibility (i.e., OLTCs, storage and DG power factor control) can lead to much smaller storage capacities. This, however, depends on the required level of curtailment.
U2 - 10.1109/TPWRS.2015.2465181
DO - 10.1109/TPWRS.2015.2465181
M3 - Article
SN - 0885-8950
SP - 1
EP - 10
JO - I E E E Transactions on Power Systems
JF - I E E E Transactions on Power Systems
ER -
