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strategy with fast computing speed. But a large storage capacity is required to com-
plete the computation. Shuffled frog leaping algorithm (SFLA) combines the benefits
of both the genetic-based memetic algorithm and the social behavior-based PSO al-
gorithm. However, most of these methods suffer from the curse of dimension when
applied to a modern large-scale power system with heavy constraints. Moreover, these
methods commonly get stuck at a local optimum rather than reaching the global opti-
mum. Even small percentage reduction in fuel costs typically leads to considerable sav-
ings for electric utilities. In this paper, a new fast approach called two-layer hierarchical
market competition algorithm (THMCA) combined with expert system is proposed to
efficiently solve the constrained UC problem.
2
Formulation of the Unit Commitment (UC) Problem
The UC problem is to determine the start-up and shut-down schedules and outputs of
generation units to meet the dynamic demand load during the scheduling horizon at a
minimal total cost. In general, the fuel cost( FC )ofthe i th generator is described as:
FC i ( P i )= a i + b i P i + c i ( P i ) 2 , i = 1 , 2 ,
···
, N unit
(1)
where a i , b i ,and c i are fuel cost coefficients of the i th unit, N unit represents the number
of units, t is the index for time intervals, P i is the power output of the i th unit.
The total operating cost is expressed as the sum of fuel costs, start-up costs, and
shutdown costs of the generating units:
T
t =1
N unit
i =1 FC i ( P i ) u i + SUC i (1 u t 1
) u i + SDC i u t 1
u i )
TFC =
(1
(2)
i
i
SUC i = SUC ihot
if T i
[ MDT i , MDT i + T icold ]
(3)
T i
SUC icold
if
MDT i + T icold
where SUC i and SDC i are start up and shut down costs respectively. u i is the status of
the i th unit at time t . SUC ihot is the hot start-up cost, SUC icold is the cold start-up cost
and T icold is the cold start time.
u i = 1
or u i = 0
i f
online
if
of fline
(4)
The units and system constraints of UC problem, which must be satisfied during the UC
scheduling period, are as follows:
The i th online unit generation limits:
P i min
P i
P i max
(5)
where P i min and P i max are minimum and maximum output power of i th online unit.
For security requirements and economic reasons, some units are assigned with the
must-run status:
u i = 1
t =[ t run
i , begin , t run
for
i , end ]
(6)
where t run
i , begin and t run
i , end are beginning and ending time of i th online must-run unit.
For maintenance requirements, some units are assigned with the must-off status:
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