Security constrained unit commitment pricing optimization using linear programming for electricity markets
View Patent ↗The present invention is a method for optimizing security constrained unit commitment in the day ahead wholesale electricity market using mixed integer linear programming techniques. The wholesale electricity market uniquely requires the submission of offers to supply energy and ancillary services at stated prices, as well as bids to purchase energy, and known operating and security constraints. The present invention address the above noted needs by providing a SCUC engine to support and implement the requirements via a computer system implementation.
1. A computer implemented system for optimal energy and energy reserve dispatching in an electricity market of at least one market participant, said system comprising: a database; and
a processor configured for:
inputting constraints of said at least one market participant;
clearing energy and energy reserve bids;
calculating a minimum sum of total market costs using mixed integers to represent variables in the relationship;
min
C
tot
=
∑
T
t
-
1
{
∑
N
l
=
1
[
c
start
(
i
,
t
)
·
Z
(
i
,
t
)
+
c
nold
(
i
,
t
)
·
Y
(
i
,
t
)
+
C
en
(
i
,
t
)
+
c
reg
(
i
,
t
)
+
∑
j
∈
com
c
j
(
i
,
t
)
}
]
wherein minC tot is a minimum sum of total market costs, t is a time step of a time period T, i is an energy bid of N energy bids, c start (i,t) is a start up cost for an energy generating bid i at time step t, Z(i,t) is a start up binary variable for the energy generating bid i at the time step t, c nold (i,t) is a no-load cost segment for the energy generating bid i at time step t, Y(i,t) is a status binary variable for the energy generating bid i at the time t, c en (i,t) is a cost of the commodity energy for the energy generating bid i at time step t, c reg (i,t) is a cost of the commodity regulating reserve energy for the energy generating bid i at time step t,j is a bid curve identifier for a number of bid curves com, and c j (i,t) is a bid curve for the energy generating bid i at time step t; and
pricing the dispatch of energy and energy reserve responsive to the minimum sum of total market costs considering said constraints of said at least one market participant using mixed integer linear programming techniques.
2. The system of claim 1 , wherein said constraint is a market participant energy limit.
3. The system of claim 1 , wherein said constraint is a load energy limit.
4. The system of claim 1 , wherein said constraint is a market participant regulation availability.
5. The system of claim 1 , wherein said constraint is a market participant regulation range.
6. The system of claim 1 , wherein said constraint is a market participant spinning reserve limit.
7. The system of claim 1 , wherein said constraint is a load spinning reserve limit.
8. The system of claim 1 , wherein said constraint is a market participant non-spinning reserve limit.
9. The system of claim 1 , wherein said constraint is a market participant capacity limit.
10. The system of claim 1 , wherein said constraint is a load capacity limit.
11. The system of claim 1 , wherein said pricing the dispatch of energy further comprises modeling linear bid curves corresponding to the energy and the energy reserve bids with a linear term and at least one associated linear equation for use in said mixed integer linear programming techniques.
12. The system of claim 1 , wherein said pricing is further responsive to one or more cost functions associated with generation of energy over a time interval.
13. The system of claim 12 wherein said pricing is further configured for minimizing said one or more cost functions.
14. The system of claim 12 wherein said one or more cost functions comprise at least one of a start up cost, a no load cost, a cost of the commodity energy, and a cost of commodity regulating reserve energy.
15. The system of claim 1 wherein said energy reserve comprises at least one of ten minute spinning reserve, ten-minute non-spinning reserve, and thirty minute operating reserve.
16. The system of claim 1 , wherein said pricing is further responsive to one or more power functions associated with consumption of energy over a time interval.
17. The system of claim 16 wherein said one or more power functions comprise at least one of power of commodity energy, power penalty factor, power of price sensitive load, power penalty factor of the price dependent load, and power of price non-sensitive load.
18. A method for optimal energy and energy reserve dispatching in an electricity market of at least one market participant, said method comprising:
inputting constraints of said at least one market participant;
clearing energy and energy reserve bids;
calculating a minimum sum of total market costs by using mixed integers to represent variables in the relationship:
min
C
tot
=
∑
T
t
-
1
{
∑
N
l
=
1
[
c
start
(
i
,
t
)
·
Z
(
i
,
t
)
+
c
nold
(
i
,
t
)
·
Y
(
i
,
t
)
+
C
en
(
i
,
t
)
+
c
reg
(
i
,
t
)
+
∑
j
∈
com
c
j
(
i
,
t
)
}
]
wherein minC tot is a minimum sum of total market costs, t is a time step of a time period T, i is an energy bid of N energy bids, c start (i,t) is a start up cost for an energy generating bid i at time step t, Z(i,t) is a start up binary variable for the energy generating bid i at the time step t, c nold (i,t) is a no-load cost segment for the energy generating bid i at time step t, Y(i,t) is a status binary variable for the energy generating bid i at the time t, c en (i,t) is a cost of the commodity energy for the energy generating bid i at time step t, c reg (i,t) is a cost of the commodity regulating reserve energy for the energy generating bid i at time step t,j is a bid curve identifier for a number of bid curves com, and c j (i,t) is a bid curve for the energy generating bid i at time step t; wherein the bid curves are modeled by a linear term and at least one associated linear equation; and
pricing the dispatch of energy and energy reserves responsive to the minimum sum of total market costs considering said constraints of said at least one market participant using a mixed integer linear programming technique.
19. A computer readable medium containing program instructions recorded therein, which, when executed by a computer, causing the computer to implement a method for optimal energy and energy reserve dispatching in an electricity market of at least one market participant, said method comprising:
inputting constraints of said at least one market participant;
clearing energy and energy reserve bids;
calculating a minimum sum of total market costs by using mixed integers to represent variables in the relationship:
min
C
tot
=
∑
T
t
-
1
{
∑
N
l
=
1
[
c
start
(
i
,
t
)
·
Z
(
i
,
t
)
+
c
nold
(
i
,
t
)
·
Y
(
i
,
t
)
+
C
en
(
i
,
t
)
+
c
reg
(
i
,
t
)
+
∑
j
∈
com
c
j
(
i
,
t
)
}
]
wherein minC tot is a minimum sum of total market costs, t is a time step of a time period T, i is an energy bid of N energy bids, c start (i,t) is a start up cost for an energy generating bid i at time step t, Z(i,t) is a start up binary variable for the energy generating bid i at the time step t, c nold (i,t) is a no-load cost segment for the energy generating bid i at time step t, Y(i,t) is a status binary variable for the energy generating bid i at the time t, c en (i,t) is a cost of the commodity energy for the energy generating bid i at time step t, c reg (i,t) is a cost of the commodity regulating reserve energy for the energy generating bid i at time step t,j is a bid curve identifier for a number of bid curves com, and c j (i,t) is a bid curve for the energy generating bid i at time step t; wherein the bid curves are modeled by a linear term and at least one associated linear equation; and
pricing the dispatch of energy and energy reserve responsive to the minimum sum of total market costs considering said constraints of said at least one market participant using a mixed integer linear programming technique.