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Optimal sizing and control of energy storage in wind power-rich distribution networks

S.W. Alnaser, L.F. Ochoa

I E E E Transactions on Power Systems. 2015;:1-10.

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Abstract

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.

Bibliographic metadata

Type of resource:
Content type:
Publication status:
Accepted
Publication type:
Publication form:
Published date:
Language:
eng
ISSN:
Start page:
1
End page:
10
Total:
9
Pagination:
1-10
Digital Object Identifier:
10.1109/TPWRS.2015.2465181
Funding awarded to University:
  • EPSRC - RESEPSRC
Attached files Open Access licence:
Publishers licence
Attached files embargo period:
Immediate release
Attached files release date:
4th August, 2015
Access state:
Active

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:269953
Created by:
Ochoa, Luis Nando
Created:
4th August, 2015, 14:45:06
Last modified by:
Ochoa, Luis Nando
Last modified:
18th November, 2015, 08:20:11

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