CN102684224B - Unit combination method for resolving and considering wind power volatility - Google Patents

Unit combination method for resolving and considering wind power volatility Download PDF

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CN102684224B
CN102684224B CN201210165681.8A CN201210165681A CN102684224B CN 102684224 B CN102684224 B CN 102684224B CN 201210165681 A CN201210165681 A CN 201210165681A CN 102684224 B CN102684224 B CN 102684224B
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CN102684224A (en
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江全元
周博然
张恺伦
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Zhejiang University ZJU
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Abstract

The invention discloses a unit combination method for resolving and considering wind power volatility. Compared with the existing unit combination method, the method has the benefits that by applying an interval linear programming theory, the system security can stability can be theoretically ensured within a wind power output fluctuation scope, and the economy of the system is improved on the premise of safety; and under the realistic background that wind power and other new energy resources are largely introduced, the ability of the power system to answer the wind power volatility can be effectively improved, and the system safety and the stability are improved.

Description

A kind of Unit Combination method of considering wind-powered electricity generation fluctuation that solves
Technical field
The operation, analysis and the dispatching technique field that the invention belongs to electric power system, relate in particular to a kind of Unit Combination method that contains the fluctuation energy such as wind-powered electricity generation.
Background technology
In the macroeconomic of guaranteeing to improve under the prerequisite of power grid security system, be how the core content of electrical network Short Term Generation Schedules always.Along with the fast development of new energy technology, a large amount of new forms of energy particularly wind power generation are connected to the grid in recent years.Compare with conventional Power Generation Mode, wind power generation has the pollution-free advantage such as renewable.But wind power generation self also exists some shortcomings, for example wind turbine generator is exerted oneself adjustablely hardly, and the pace of change of exerting oneself is fast, scope is large, is difficult to Accurate Prediction etc., and these problems have caused huge threat to the safety and stability of electrical network.Therefore, how to tackle the problem that the access of a large amount of wind-powered electricity generations brings, become the challenge that Optimization of Unit Commitment By Improved is new.
In traditional Unit Combination model, do not consider the new forms of energy such as wind-powered electricity generation that randomness is very strong, therefore the fluctuation of system is not obvious, and Unit Combination method traditional under such prerequisite is dealt with the fluctuation of system loading or power supply by the capacity of reserved system total load certain percentage.But along with a large amount of accesses of the new forms of energy such as wind-powered electricity generation, the fluctuation of electric power system is more and more significant, traditional alternative mean cannot adapt to the requirement of the electrical network of fluctuation enhancing.Therefore the fluctuation of electric power system has been brought unprecedented challenge to the safety of system, is badly in need of a kind of Unit Combination method that can guarantee that electric power system still can safe and stable operation under fluctuation.
Summary of the invention
The object of the invention is to for the deficiencies in the prior art, a kind of Unit Combination method of considering wind-powered electricity generation fluctuation that solves is provided, the present invention guarantees that Unit Commitment result can guarantee the safety and stability of system in the situation that of power supply and load fluctuation, and improves the economy of system.
The object of the invention is to be achieved through the following technical solutions: a kind of Unit Combination method of considering wind-powered electricity generation fluctuation that solves, comprises the steps:
The first step: receive the following 24 hours workload demand data of system that electrical network machine unit scheduling center draws; Receive wind energy turbine set to the wind-powered electricity generation big or small prediction data of exerting oneself, comprise that prediction wind-powered electricity generation is exerted oneself and to go out the bound that wind-powered electricity generation exerts oneself interval; The machine unit characteristic data that report according to each power plant draw the restrain condition of each unit.
Second step: the data that receive according to the first step are carried out modeling to the Optimization of Unit Commitment By Improved of electric power system, according to service requirement select target function and constraints, comprise equality constraint and inequality constraints condition, forms mixed integer nonlinear programming problem.
The 3rd step: according to the mixed integer nonlinear programming problem of previous step generation, draw target function and the constraints of primal problem, solve primal problem.
Target function in primal problem is that entire system expense is minimum, and constraints is: the Benders that power-balance constraint, unit output constraint, unit ramp loss, the minimum start and stop time-constrain of unit and every order 4 the 5th step produce cuts constraint (retraining without this in iteration for the first time).
The 4th step: the result of the 3rd step is carried out to Network Security Constraints check, if result can not meet the demands, produce corresponding Benders and cut, the Benders of generation is cut as new constraints, return to the 3rd step.
In Network Security Constraints check problem, added non-negative slack variable, guaranteed that Network Security Constraints check problem has solution, by check, minimize slack variable and whether be greater than zero, judge that whether Network Security Constraints satisfied.
The 5th step: use interval linear programming theoretical, result of calculation is carried out to full sight constraint test, if institute's Constrained is all satisfied, obtain final result; Otherwise produce corresponding Benders, cut as new constraints, be back to the 3rd step;
In full sight constraint test, need the constraint of check to comprise:
1, system power balance Operations of Interva Constraint:
Figure 373579DEST_PATH_IMAGE001
；
Wherein
Figure 683337DEST_PATH_IMAGE002
for unit is meritorious, exert oneself,
Figure 930560DEST_PATH_IMAGE003
for Unit Commitment state,
Figure 983967DEST_PATH_IMAGE004
be respectively system node burden with power prediction minimum value and maximum;
2, Line Flow Operations of Interva Constraint:
Figure 823747DEST_PATH_IMAGE005
；
Wherein
Figure 242090DEST_PATH_IMAGE002
for unit is meritorious, exert oneself,
Figure 800110DEST_PATH_IMAGE006
for Line Flow binding occurrence,
Figure 329311DEST_PATH_IMAGE004
be respectively system node burden with power prediction minimum value and maximum,
Figure 289177DEST_PATH_IMAGE007
for the transfer breadth coefficient matrix of node active power input to circuit;
3, node voltage Operations of Interva Constraint:
Figure 940738DEST_PATH_IMAGE008
；
Wherein,
Figure 658159DEST_PATH_IMAGE009
unit is idle exerts oneself, be respectively system node reactive load forecasting minimum value and maximum,
Figure 303958DEST_PATH_IMAGE011
for the Jacobian matrix of node reactive power input to node voltage,
Figure 126421DEST_PATH_IMAGE012
with
Figure 393454DEST_PATH_IMAGE013
be respectively the bound of system node voltage change.
The 6th step: gained final result can be used as the scheme of electrical network machine unit scheduling, in order to dispatch start-stop of generator set machine, to improve entire system economy and fail safe.
The invention has the beneficial effects as follows, method of the present invention uses interval linear programming theoretical, can in wind-powered electricity generation is exerted oneself fluctuation range, in safety and stability, improve the economy of result in assurance system.Under the realistic background of a large amount of accesses of the new forms of energy such as wind-powered electricity generation, the method can improve the ability of electric power system reply wind-powered electricity generation fluctuation effectively, improves security and stability and the economy of system.
Accompanying drawing explanation
Fig. 1 is flow chart of the present invention;
Fig. 2 is IEEE-30 node system;
Fig. 3 is system loading predicted value;
Fig. 4 is the wind power generation forecast interval bound of exerting oneself;
Fig. 5 is system reserve machine climbing schematic diagram.
Embodiment
The present invention solves the Unit Combination method of considering wind-powered electricity generation fluctuation, comprises the steps:
The first step: receive system that electrical network machine unit scheduling center draws in the workload demand data of 24 hours next; Receive wind energy turbine set for the wind-powered electricity generation big or small prediction data of exerting oneself, comprise that prediction wind-powered electricity generation is exerted oneself and to go out the bound that wind-powered electricity generation exerts oneself interval; The machine unit characteristic data that report according to each power plant draw the restrain condition of each unit.
Second step: the data that receive according to the first step are carried out modeling to the Optimization of Unit Commitment By Improved of electric power system, according to service requirement select target function and constraints, comprise equality constraint and inequality constraints condition, forms mixed integer nonlinear programming problem.
The 3rd step: according to the mixed integer nonlinear programming problem of previous step generation, draw target function and the constraints of primal problem, solve primal problem.
Target function in primal problem is that entire system expense is minimum, and constraints is: the Benders that power-balance constraint, unit output constraint, unit ramp loss, the minimum start and stop time-constrain of unit and every order 4 the 5th step produce cuts constraint (retraining without this in iteration for the first time).
The 4th step: the result for the 3rd step is carried out Network Security Constraints check, if result can not meet the demands, produces corresponding Benders and cuts, and the Benders of generation is cut as new constraints, returns to the 3rd step.
In Network Security Constraints check problem, added non-negative slack variable, guaranteed that Network Security Constraints check problem has solution, by check, minimize slack variable and whether be greater than zero, judge that whether Network Security Constraints satisfied.
The 5th step: use interval linear programming theoretical, result of calculation is carried out to full sight constraint test, if institute's Constrained is all satisfied, obtain final result; Otherwise produce corresponding Benders, cut as new constraints, be back to the 3rd step;
In full sight constraint test, need the constraint of check to comprise:
1, system power balance Operations of Interva Constraint:
；
Wherein
Figure 198916DEST_PATH_IMAGE002
for unit is meritorious, exert oneself,
Figure 129963DEST_PATH_IMAGE003
for Unit Commitment state,
Figure 884292DEST_PATH_IMAGE004
be respectively system node burden with power prediction minimum value and maximum;
2, Line Flow Operations of Interva Constraint:
Figure 886883DEST_PATH_IMAGE005
；
Wherein for unit is meritorious, exert oneself,
Figure 512217DEST_PATH_IMAGE006
for Line Flow binding occurrence, be respectively system node burden with power prediction minimum value and maximum, for the transfer breadth coefficient matrix of node active power input to circuit;
3, node voltage Operations of Interva Constraint:
Figure 108655DEST_PATH_IMAGE008
；
Wherein, unit is idle exerts oneself,
Figure 110426DEST_PATH_IMAGE010
be respectively system node reactive load forecasting minimum value and maximum,
Figure 392503DEST_PATH_IMAGE011
for the Jacobian matrix of node reactive power input to node voltage,
Figure 624901DEST_PATH_IMAGE012
with
Figure 396548DEST_PATH_IMAGE013
be respectively the bound of system node voltage change.
The 6th step: the final result that the 5th step is obtained is as the scheme of electrical network machine unit scheduling, in order to dispatch start-stop of generator set machine, to improve entire system economy and fail safe.
Below in conjunction with accompanying drawing, embodiments of the invention are elaborated, flow chart of the present invention is as shown in Figure 1.
embodiment:
This example is used IEEE-30 node system, as shown in Figure 2.As shown in Figure 3, each period wind-powered electricity generation of system is exerted oneself big or small forecast interval as shown in Figure 4 to each period payload of system.Target setting function is system total power production cost minimum (1), wherein for unit generation cost,
Figure 167375DEST_PATH_IMAGE015
for unit start cost,
Figure 956077DEST_PATH_IMAGE016
for total time hop count; for generator number of units;
Figure 336560DEST_PATH_IMAGE018
for unit
Figure 960439DEST_PATH_IMAGE019
constantly
Figure 167430DEST_PATH_IMAGE020
meritorious exerting oneself.
Figure 218562DEST_PATH_IMAGE021
（1）
Constraints is: burden with power Constraints of Equilibrium (2), unit output constraint (3), unit ramp loss (4), the maximum start and stop time-constrain (5) of unit, Line Flow constraint (6), node voltage constraint (7).
Figure 143793DEST_PATH_IMAGE022
（2）
In formula:
Figure 368101DEST_PATH_IMAGE023
;
Figure 632860DEST_PATH_IMAGE024
for unit
Figure 651632DEST_PATH_IMAGE025
constantly
Figure 517955DEST_PATH_IMAGE020
start and stop state; for generator number of units; for load bus sum;
Figure 120472DEST_PATH_IMAGE027
for load constantly
Figure 258509DEST_PATH_IMAGE020
meritorious demand.
Figure 560178DEST_PATH_IMAGE029
（3）
In formula:
Figure 186331DEST_PATH_IMAGE030
;
Figure 245554DEST_PATH_IMAGE023
;
Figure 615355DEST_PATH_IMAGE024
for unit
Figure 207748DEST_PATH_IMAGE025
constantly
Figure 4803DEST_PATH_IMAGE020
start and stop state;
Figure 613639DEST_PATH_IMAGE018
for unit constantly
Figure 469917DEST_PATH_IMAGE020
meritorious exerting oneself; for unit
Figure 471688DEST_PATH_IMAGE025
constantly
Figure 183292DEST_PATH_IMAGE020
idle exerting oneself;
Figure 986163DEST_PATH_IMAGE032
with be respectively unit
Figure 144666DEST_PATH_IMAGE025
the meritorious bound of exerting oneself;
Figure 659961DEST_PATH_IMAGE034
with
Figure 379656DEST_PATH_IMAGE035
be respectively unit
Figure 627097DEST_PATH_IMAGE025
the idle bound of exerting oneself.
Figure 697821DEST_PATH_IMAGE036
（4）
In formula:
Figure 688911DEST_PATH_IMAGE030
;
Figure 528691DEST_PATH_IMAGE037
;
Figure 9351DEST_PATH_IMAGE018
for unit
Figure 505055DEST_PATH_IMAGE019
constantly
Figure 96573DEST_PATH_IMAGE020
meritorious exerting oneself;
Figure 227078DEST_PATH_IMAGE038
for unit
Figure 144218DEST_PATH_IMAGE025
meritorious maximum creep speed of exerting oneself.
Figure 861638DEST_PATH_IMAGE039
（5）
In formula:
Figure 256848DEST_PATH_IMAGE024
for unit
Figure 71220DEST_PATH_IMAGE025
constantly
Figure 831365DEST_PATH_IMAGE020
start and stop state; for unit
Figure 234982DEST_PATH_IMAGE025
continuous line duration;
Figure 903861DEST_PATH_IMAGE041
for unit
Figure 897225DEST_PATH_IMAGE025
the continuous off-line time;
Figure 93632DEST_PATH_IMAGE042
for Wei not unit continuous online and off-line time of minimum.
Figure 291712DEST_PATH_IMAGE043
（6）
In formula:
Figure 659239DEST_PATH_IMAGE023
;
Figure 838548DEST_PATH_IMAGE044
;
Figure 113671DEST_PATH_IMAGE018
for unit
Figure 757142DEST_PATH_IMAGE019
constantly
Figure 528527DEST_PATH_IMAGE020
meritorious exerting oneself;
Figure 257448DEST_PATH_IMAGE027
for load constantly
Figure 771923DEST_PATH_IMAGE020
meritorious demand;
Figure 481254DEST_PATH_IMAGE045
for circuit sum;
Figure 431892DEST_PATH_IMAGE007
for the transfer breadth coefficient matrix of node active power input to circuit;
Figure 252080DEST_PATH_IMAGE046
for circuit
Figure 604564DEST_PATH_IMAGE047
the power delivery upper limit.
Figure 547113DEST_PATH_IMAGE048
（7）
In formula: ;
Figure 841882DEST_PATH_IMAGE049
;
Figure 252135DEST_PATH_IMAGE050
for node sum; for unit
Figure 290815DEST_PATH_IMAGE025
constantly
Figure 452806DEST_PATH_IMAGE020
idle exerting oneself;
Figure 514303DEST_PATH_IMAGE051
for load
Figure 736337DEST_PATH_IMAGE028
constantly
Figure 148864DEST_PATH_IMAGE020
reactive requirement; for the Jacobian matrix of node reactive power input to node voltage;
Figure 794664DEST_PATH_IMAGE053
with be respectively the bound of node voltage changing value.
The problems referred to above can be divided into following three problems: Scenario primal problem, network constraint check problem and full sight check problem.
scenario primal problem:
The target function corresponding (1) of Scenario primal problem, constraint is (2)-(5).Itself be to solve an Optimization of Unit Commitment By Improved that does not contain Network Security Constraints.By solving this problem, draw the size of exerting oneself of unit under each sight, and all sights share same set of Unit Commitment scheme.This problem can be used MILP (MILP) method to solve.
network constraint check:
Can Network Security Constraints check problem is actually the unit output of checking Scenario primal problem to obtain meet Network Security Constraints (6), (7) under corresponding situation.Can be summarized as and solve target function:
Figure 821843DEST_PATH_IMAGE055
（8）
Meet constraints:
Figure 387953DEST_PATH_IMAGE056
Figure 689622DEST_PATH_IMAGE057
Wherein:
Figure 987879DEST_PATH_IMAGE058
, , ,
Figure 573078DEST_PATH_IMAGE061
for non-negative slack variable.
If the value of target function (8) is 0, illustrate that unit output meets all Network Security Constraints, otherwise produce corresponding Benders, cut (9), as new constraint, add primal problem.
Figure 370133DEST_PATH_IMAGE062
（9）
Wherein
Figure 409328DEST_PATH_IMAGE063
the unit of obtaining for primal problem
Figure 582820DEST_PATH_IMAGE019
constantly
Figure 531184DEST_PATH_IMAGE064
the meritorious value of exerting oneself,
Figure 499140DEST_PATH_IMAGE065
the unit of obtaining for primal problem constantly the idle value of exerting oneself,
Figure 109747DEST_PATH_IMAGE066
result of calculation for target function (8).
full sight check
After completing above two steps, required result can meet total optimization under considered multiple sight, and meets related constraint, but such start and stop scheme differs and under all sights, meets security constraint surely.
In this method, using wind-powered electricity generation as a kind of " load " that sends power, and merge with general load, think the load that only has of fluctuation.Load may be big or small given with interval form, and the be constrained to load balancing directly related with load retrains (2), network trend constraint (6) and node voltage constraint (7).In order further to use interval linear programming theoretical, write these three constraints as interval form (10)-(12).
Figure 186288DEST_PATH_IMAGE067
（10）
Figure 769716DEST_PATH_IMAGE068
（11）
Figure 19432DEST_PATH_IMAGE069
（12）
Wherein
Figure 440923DEST_PATH_IMAGE070
for node load
Figure 750682DEST_PATH_IMAGE071
constantly
Figure 759089DEST_PATH_IMAGE020
active power is surveyed interval bound,
Figure 812496DEST_PATH_IMAGE072
for node load
Figure 652276DEST_PATH_IMAGE071
constantly
Figure 70619DEST_PATH_IMAGE020
reactive power forecast interval bound.
Can full sight check problem be checked under the Unit Combination scheme of gained above, obtain one group of unit output value, meets the security constraint under worst case.If there is such one group of unit output value, show that the Unit Combination state of gained can meet full sight security constraint.
This problem can be write as target function:
（13）
Meet constraint (3), (4), (14)-(16).
Figure 157841DEST_PATH_IMAGE074
（14）
Figure 852127DEST_PATH_IMAGE075
（15）
Figure 503688DEST_PATH_IMAGE076
（16）
Wherein
Figure 985223DEST_PATH_IMAGE077
for non-negative slack variable.
At these, approximately intrafascicularly only have (14), (15), (16) are directly relevant with prediction load interval variable, and wherein constraint (15) is basically identical with constraint (16) form, therefore only introduce the processing method of constraint (15), constraint (16) can be used identical method to process.First defined variable
Figure 380432DEST_PATH_IMAGE078
, in constraint (33) ta constant matrices, therefore p lD value be also within certain scope, its bound is expressed as
Figure 866908DEST_PATH_IMAGE079
.Constraint (15) can be expressed as (17), does the most strictly check, retrains (17) and then is write as (18).If can find, meet the most strictly feasible solution of constraint, in that reality, necessarily also can find feasible solution.In like manner constraint (16) can be write as (19).
Figure 954950DEST_PATH_IMAGE080
（17）
（18）
Figure 358567DEST_PATH_IMAGE082
（19）
Wherein,
Figure 761866DEST_PATH_IMAGE083
, it is limited to up and down
Figure 958492DEST_PATH_IMAGE084
,
Figure 712822DEST_PATH_IMAGE085
.
Next the equation Operations of Interva Constraint of exerting oneself (14), first definition
Figure 449834DEST_PATH_IMAGE086
.Theoretical according to interval linear programming, equality constraint (14) worst case occurs in:
（20）
Wherein,
Figure 839281DEST_PATH_IMAGE088
,
Figure 753011DEST_PATH_IMAGE089
represent different sights.
From (20), can know that worst case occurs under a certain sight in two kinds of sights, be can not determine but specifically occur under any sight, and therefore two kinds of sights all will be considered.So for total tthe problem of individual time period just has plant the worst possible sight, amount of calculation is obviously unacceptable like this.Observe the feature of this problem self, power-balance constraint and Network Security Constraints are all only relevant with the unit output of current time, not in the same time between independence mutually.Only constraint (20) need be brought into each constantly, then add the climbing constraint (21) between the worst cases of two adjacent periods.Like this
Figure 937185DEST_PATH_IMAGE090
planting the worst sight equality constraint can use
Figure 210034DEST_PATH_IMAGE091
planting worst case equality constraint replaces.
Figure 938956DEST_PATH_IMAGE092
（21）
Therefore, full sight check problem can be expressed as: target function is (13), meets constraint (3), and (4), (18)-(21), wherein
Figure 955453DEST_PATH_IMAGE093
.
Solve problem above, if the target function of gained is 0, represent that this Unit Commitment function meets the security constraint of full sight; If be greater than 0, produce corresponding Benders and cut (22), as new constraint, bring Scenario primal problem into and again solve.
Figure 453431DEST_PATH_IMAGE094
（22）
In the present invention, used the method for interval linear programming theory, Unit Combination result has been carried out to full sight safety verification.Therefore result can guarantee theoretically, and when load (comprising wind-powered electricity generation etc.) fluctuates arbitrarily in forecast interval, system can be by regulating unit output meet security constraint.In table 2, contrasted with standby constraint type and met security constraint Unit Combination (SCUC) method of system loading fluctuation and (the full scenario security constrained unit commitment of the full sight security constraint Unit Combination based on interval linear programming theory that the present invention proposes, FS-SCUC) method meets the ability of system restriction when load fluctuation.In table, SCUC-X refers to that reserve capacity accounts for percent X of system loading size.
table 2: wind-powered electricity generation goes out security of system under fluctuation
Figure 959498DEST_PATH_IMAGE095
note:√ representative system security constraint can all meet, and * representative system security constraint can not all meet.
table 3: system total cost
Figure 617794DEST_PATH_IMAGE096
FS-SCUC method is well positioned to meet system safety constraint when wind-powered electricity generation goes out fluctuation as can be seen from Table 2, improves security of system.Common SCUC model is not considering that wind-powered electricity generation all can meet system safety constraint while processing fluctuation, but when wind-powered electricity generation goes out fluctuation, SCUC cannot meet system safety constraint.Improve system reserve capacity, when reserve capacity is 20%, acquired results can meet wind-powered electricity generation and go out the system safety under fluctuation, but the expense of the SCUC method in this time is higher than FS-SCUC method.When reserve capacity is less than 20%, acquired results can not meet wind-powered electricity generation and go out the system safety under fluctuation.When capacity is greater than 20%, acquired results can not meet wind-powered electricity generation and go out the system safety under fluctuation, and related causes can illustrate in the analysis below.
Simple increase reserve capacity can not meet and when wind-powered electricity generation goes out fluctuation, meet system safety constraint is because the restriction of the climbing capacity of system unit.As can be seen from Figure 5, if the upper limit that wind-powered electricity generation is exerted oneself in forecast interval constantly, and the next lower limit that is constantly positioned at would so just need very large lower climbing capacity.If a lower limit that constantly wind-powered electricity generation is exerted oneself in forecast interval in like manner, and the next upper limit that is constantly positioned at, so just need to very large upper climbing capacity.Traditional Unit Combination method is not considered such constraint, therefore cannot guarantee system safety.
To sum up, solving that we propose considers that the Unit Combination method of wind-powered electricity generation fluctuation is well positioned to meet the security requirement of system when wind-powered electricity generation goes out fluctuation owing to having comprised full sight constraint test, improved greatly the fail safe of system, the fluctuation problem of bringing for the extensive access of wind-powered electricity generation provides effective solution.

Claims (1)

1. solve a Unit Combination method of considering wind-powered electricity generation fluctuation, it is characterized in that comprising the steps:
(1) receive the following 24 hours workload demand data of system that electrical network machine unit scheduling center draws; Receive wind energy turbine set to the wind-powered electricity generation big or small prediction data of exerting oneself, comprise the bound interval of exerting oneself prediction wind-powered electricity generation size and wind-powered electricity generation exerting oneself; The machine unit characteristic data that report according to each power plant draw the restrain condition of each unit;
(2) data that receive according to step (1) are carried out modeling to the Optimization of Unit Commitment By Improved of electric power system, according to service requirement select target function and constraints, comprise equality constraint and inequality constraints condition, form mixed integer nonlinear programming problem;
(3) according to the mixed integer nonlinear programming problem of step (2) generation, draw target function and the constraints of primal problem, solve primal problem;
(4) result of step (3) is carried out to Network Security Constraints check, if result can not meet the demands, produce corresponding Benders and cut, the Benders of generation is cut as new constraints, return to step (3); (5) use interval linear programming theoretical, result of calculation is carried out to full sight constraint test, if institute's Constrained all meets, obtain final result; Otherwise produce corresponding Benders, cut as new constraints, be back to step (3);
(6) scheduling scheme using step (5) gained final result as electrical network unit, in order to dispatch start-stop of generator set machine, to improve entire system economy and fail safe;
In described step (2), described target function is that entire system expense is minimum; Equality constraint is system loading Constraints of Equilibrium; Inequality constraints comprises unit minimax units limits, unit ramp loss, minimum start and stop time-constrain, Line Flow constraint and node voltage constraint;
In described step (3), target function in described primal problem is that entire system expense is minimum, and described constraints is: the Benders that power-balance constraint, unit output constraint, unit ramp loss, the minimum start and stop time-constrain of unit and each step (4) and step (5) produce cuts constraint;
In described step (5), in described full sight constraint test, need the constraint of check to comprise system power balance Operations of Interva Constraint, Line Flow Operations of Interva Constraint and node voltage Operations of Interva Constraint, specific as follows:
(A) system power balance Operations of Interva Constraint:
ΣPu = Σ [ P load min , P load max ] ;
Wherein, to be that unit is meritorious exert oneself P, and u is Unit Commitment state, be respectively system node burden with power prediction minimum value and maximum;
(B) Line Flow Operations of Interva Constraint:
- FL ≤ ΣTP - ΣT [ P load min , P load max ] ≤ FL ;
Wherein, to be that unit is meritorious exert oneself P, and FL is Line Flow binding occurrence,
Figure FDA0000462784650000022
be respectively system node burden with power prediction minimum value and maximum, T is the transfer breadth coefficient matrix of node active power input to circuit;
(C) node voltage Operations of Interva Constraint:
Δ V min ≤ ΣBQ - ΣB [ Q load min , Q load max ] ≤ Δ V max ;
Wherein, to be that unit is idle exert oneself Q, be respectively system node reactive load forecasting minimum value and maximum, B is the Jacobian matrix of node reactive power input to node voltage, Δ V maxwith Δ V minbe respectively the bound of system node voltage change.
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