IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 25, NO. 2, MAY 2010 749
Maximizing Firm Wind Connection to Security
Constrained Transmission Networks
Daniel J. Burke, Graduate Student Member, IEEE, and Mark J. O’Malley, Fellow, IEEE
Abstract—Prudent use of existing transmission capacity could be
achieved by an optimal allocation of wind capacity to distinct trans-
mission nodes. The statistical interdependency of geographically
separate wind sites and the partially-dispatchable nature of wind
power require a collective analysis of all potential wind farms over
an extended time-frame in any optimized transmission planning
study. The methodology presented in this paper separates this large
optimization problem into smaller subtasks, including a year-long
sequential time series hourly integer unit commitment, a linear dc
load-flow network model with hourly security constraints, and a
linear programming optimization model to estimate the maximum
firm wind energy penetration for a given network. A novel maximal-
vector based constraint redundancy analysis is employed to signifi-
cantly reduce the linear programming optimization dimensionality.
Firm wind capacity connections are facilitated in this paper—i.e.,
those to which wind curtailment to manage congestion is not appli-
cable within a typical system “planning” timeframe analysis. Each
bus is allocated firm capacity on the basis of maximizing the pos-
sible firm wind energy penetration in the transmission system as a
whole, while preserving traditional network security standards.
Index Terms—Computational geometry, linear programming
redundancy, power transmission, wind energy.
NOMENCLATURE AND
UNITS
A. Indices
Linear constraint coefficient position
index.
Time series hourly position index.
Network bus position index.
Network branch index.
Potential wind farm network location
index.
DC load flow reference bus position index.
Power flow contingency scenario index.
Maximal-vector redundancy stop-criterion
set index.
Manuscript received November 07, 2008; revised September 15, 2009. First
published December 01, 2009; current version published April 21, 2010. This
work was conducted in the Electricity Research Centre, University College
Dublin, Ireland, which is supported by Airtricity, Bord Gais, Bord na Mona,
Cylon Controls, the Commission for Energy Regulation, Eirgrid, ESB Interna-
tional, ESB Networks, ESB Powergen, Siemens, South Western Services, and
Viridian. The work of D. J. Burke was supported by Sustainable Energy Ireland
through a postgraduate research scholarship from the Irish Research Council
for Science Engineering and Technology. Paper no. TPWRS-00914-2008.
The authors are with the School of Electrical, Electronic and Mechan-
ical Engineering, University College Dublin, Dublin 4, Ireland (e-mail:
Digital Object Identifier 10.1109/TPWRS.2009.2033931
B. Constants
DC load flow power transfer distribution
factors for line “
” with respect to bus “ ”
under contingency scenario “
”.
Average system power demand level
(MW).
Thermal capacity for branch “ ” (MW).
Capacity factor of wind farm “ ”.
Capacity factor of system averaged wind
power time series.
Number of generation sites in the power
system.
Number of network branches in the system.
Total number of contingency scenarios
considered.
Length of the wind power time series
(years).
Maximal vector redundancy analysis
stop-criterion.
Discrete wind energy penetration target
increment.
C. Time Series
Nominal 1-MW wind power time series
“
” in hour “ ” (MW).
Average value of all the nominal 1-MW
wind power time series in hour “
” (MW).
Geographically smoothed total system
wind power production value in hour “
”
(MW).
Partial load flow solution of
load/conventional plant in branch
“
”, hour “ ” under contingency scenario
“
” (MW).
D. Variables
“ ” wind capacity optimization variables
(MW).
Approximated system total wind capacity
(MW).
Power flow in branch “ ” (MW).
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