CN106712116A - Completely distributed power system unit input configuration method and system - Google Patents

Completely distributed power system unit input configuration method and system Download PDF

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CN106712116A
CN106712116A CN201710178987.XA CN201710178987A CN106712116A CN 106712116 A CN106712116 A CN 106712116A CN 201710178987 A CN201710178987 A CN 201710178987A CN 106712116 A CN106712116 A CN 106712116A
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unit
iteration
variable
constraint
original variable
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CN106712116B (en
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杨林峰
张婷婷
简金宝
张晨
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Guangxi Xinghongyuan Technology Co.,Ltd.
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Guangxi University
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

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  • Power Engineering (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
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Abstract

The invention provides a completely distributed power system unit input configuration method and system. The method comprises the steps of: constructing a unit commitment model, dividing and arranging constraint conditions thereof, and obtaining an iteration formula of an alternating direction method of multipliers, wherein iteration variables comprise an original variable x, an original variable z and a dual variable u; solving iteration variables of each unit in current iteration, a target function value of the unit commitment model and a coupling constraint violation value; judging whether the target function value and the coupling constraint violation value satisfy a first condition, if satisfying, recording the original variable x and the target function value, otherwise, returning to solve the iteration variables; and judging whether the coupling constraint violation value satisfies a second condition, if satisfying, configuring each unit, otherwise, judging whether the number of iterations exceeds a maximum, if exceeding, configuring each unit, otherwise, returning to solve the iteration variables. The method and the system can realize complete decoupling, distributed calculation and privacy protection of a large-scale unit commitment.

Description

Fully distributed power system unit puts into collocation method and system
Technical field
The present invention relates to field of power, more particularly to a kind of fully distributed power system unit input configuration side Method and system.
Background technology
Increase and the energy crisis increasingly sharpened with power system scale, operation of the people to power system economy It is required that more and more higher.Unit Commitment optimization has material impact to Economical Operation of Power Systems, sacurity dispatching, and it is not Substantial amounts of financial cost can be only saved, and the reliability of power system is improved by certain spinning reserve.Unit group Close optimization problem and be related to two subproblems, one is Unit Combination, for determining there is which unit output；Another is economical Sharing of load, for determining to need these units go out how much power.The decision variable of Unit Commitment Problem is directed not only to represent The discrete variable of operating states of the units (operation, shutdown are represented with 1,0 respectively), and it is related to represent the semicontinuous change of unit output Amount is, it is necessary to consider a large amount of linear, nonlinear equatioies or the inequality constraints such as including power-balance, spinning reserve, minimum start and stop.
Unit Combination (Unit Commitment, abbreviation UC) problem of power system is it needs to be determined that unit is in different behaviour Make each time period, the unit operation plan of different loads under constraint and environment.Complicated operation limitation and nonconvex property, Yi Jiwen The scale of topic so that the solution of large-scale UC problems is challenging.The existing method for solving the problems, such as UC includes artificial intelligence Can (AI) algorithm and numerical optimization technique.These method major parts are approximation methods, can not realize the complete of power system unit Full decoupling and Distributed Calculation, particularly with extensive fully distributed Optimization of Unit Commitment By Improved, the complexity of solution is high, and nothing Privacy between method protection unit.
The content of the invention
The present invention provides a kind of fully distributed power system unit input collocation method and system, existing for solving Power system crew qiting method can not realize the full decoupled and Distributed Calculation of power system unit, the complexity of solution Height, and the problem of privacy between unit cannot be protected.
The first aspect of the invention is to provide a kind of fully distributed power system unit input collocation method, bag Include：
According to the basic data of each unit in Unit Commitment, Unit Combination model, the basic data are built Including：The spinning reserve data of the operation characteristic data, load prediction data and day part of group of motors；
Constraints to the Unit Combination model is divided, and obtains the first constraint set, the second constraint set and the 3rd Constraint set, first constraint set include unit starting expense, exert oneself, creep speed, the minimum start-stop time, original state and shape State logical relation is constrained, and second constraint set includes that power of the assembling unit Constraints of Equilibrium and spinning reserve are constrained, the 3rd constraint Collection includes state and starts unit output and payment for initiation variable nonnegativity restrictions after variable 0-1 constraints and projection；
According to first constraint set, the second constraint set and the 3rd constraint set, the Unit Combination model is arranged, And according to arrangement after the Unit Combination model, using alternating direction multiplier (Alternating Direction Method Of Multipliers, ADMM), the corresponding alternating direction multiplier method of acquisition is iterative, and the alternating direction multiplier method is iterative Iteration variable includes original variable x, original variable z and dual variable u；
According to first constraint set and the 3rd constraint set, the Unit Combination model is decoupled, asked respectively Solve the original variable of each unit in the Unit Commitment under this upper strata iterationWherein k+1 is this The number of times of upper strata iteration, i is machine group #；
The quadratic programming problem built based on second constraint set is converted into lagrange duality problem, according to unit Object function to the lagrange duality problem is decoupled, according to the current original variable of each unitUtilize ADMM methods are cooperateed with, complete distribution solves the original variable of each unit under this upper strata iteration respectively
According to the current original variable of each unitAnd original variableBased on the alternating direction multiplier method It is iterative, obtain the dual variable of each unit under this upper strata iteration
According to the current original variable of each unitSolve the object function of each unit under this upper strata iteration Value and coupling constraint violate angle value, and the target function value current to each unit and coupling constraint violate angle value summation respectively, The target function value and coupling constraint for obtaining the Unit Combination model under this upper strata iteration violate angle value；
Judge that the current target function value of the Unit Combination model and coupling constraint violate whether angle value meets default First condition, if meeting, records the current original variable of each unitThe target current with the Unit Combination model Functional value, otherwise returns to perform and described solves under this upper strata iteration each unit in the Unit Commitment respectively Original variableThe step of；
Judge that the current coupling constraint of the Unit Combination model violates whether angle value meets default second condition, if full Foot, then stop upper strata iteration, according to the current original variable of each unitThe target current with the Unit Combination model Whether functional value, configures to each unit, otherwise, judge the number of times k+1 of this upper strata iteration beyond default iteration Maximum, if exceeding, stops upper strata iteration, according to the current original variable of each unitWith the Unit Combination mould The current target function value of type, configures to each unit, and otherwise return execution is described solves stacking on this respectively For the original variable of each unit in the lower Unit CommitmentThe step of.
The second aspect of the invention is to provide a kind of fully distributed power system unit input configuration system, bag Include：
Module is built, for the basic data according to each unit in Unit Commitment, Unit Combination model is built, The basic data includes：The spinning reserve data of the operation characteristic data, load prediction data and day part of generating set；
Division module, divides for the constraints to the Unit Combination model, obtains the first constraint set, second Constraint set and the 3rd constraint set, first constraint set include unit starting expense, exert oneself, creep speed, the minimum start-stop time, Original state and state logic relation constraint, second constraint set include that power of the assembling unit Constraints of Equilibrium and spinning reserve are constrained, 3rd constraint set includes state and starts after variable 0-1 constraint and projection unit output and payment for initiation variable is non-breaks a promise Beam；
Sorting module, for according to first constraint set, the second constraint set and the 3rd constraint set, to the Unit Combination Model is arranged, and according to arrangement after the Unit Combination model, using alternating direction multiplier, obtain corresponding alternating side Iterative to multiplier method, the iterative iteration variable of alternating direction multiplier method includes original variable x, original variable z and antithesis Variable u；
First decoupling module, for according to first constraint set and the 3rd constraint set, to the Unit Combination mould Type is decoupled, and the original variable of each unit in the Unit Commitment under this upper strata iteration is solved respectivelyWherein k+1 is the number of times of this upper strata iteration, and i is machine group #；
Second decoupling module, for the quadratic programming problem built based on second constraint set to be converted into Lagrange Dual problem, decouples according to unit to the object function of the lagrange duality problem, current according to each unit Original variableUsing ADMM methods are cooperateed with, complete distribution solves the original of each unit under this upper strata iteration respectively Beginning variable
Antithesis module, for according to the current original variable of each unitAnd original variableBased on the friendship It is iterative for direction multiplier method, obtain the dual variable of each unit under this upper strata iteration
Module is solved, for according to the current original variable of each unitSolve each under this upper strata iteration The target function value and coupling constraint of unit violate angle value, respectively the target function value and coupling constraint current to each unit Angle value summation is violated, the target function value and coupling constraint violation degree of the Unit Combination model under this upper strata iteration is obtained Value；
First judge module, for judging the current target function value of the Unit Combination model and coupling constraint violation degree Whether value meets default first condition, if meeting, records the current original variable of each unitWith the unit group The current target function value of matched moulds type, otherwise indicates first decoupling module to perform again and described solves this upper strata respectively Under iteration in the Unit Commitment each unit original variableThe step of；
Second judge module, for judging that the current coupling constraint of the Unit Combination model violates whether angle value meets pre- If second condition, if meet, stop upper strata iteration, according to the current original variable of each unitWith the unit The current target function value of built-up pattern, configures to each unit, otherwise, judges the number of times k+1 of this upper strata iteration Whether exceed default iterations max, if exceeding, stop upper strata iteration, according to the current original variable of each unitThe target function value current with the Unit Combination model, configures to each unit, otherwise indicates described first Decoupling module performs described solve under this upper strata iteration each unit in the Unit Commitment respectively again Original variableThe step of.
Fully distributed power system unit input collocation method and system that the present invention is provided, using power system machine The basic data of each unit in group combination, builds Unit Combination model and its constraint condition set is divided, using alternating side To multiplier method, based on the first constraint set and the 3rd constraint set, Unit Combination model is decoupled；Secondary rule are built based on the second constraint set The problem of drawing, and be converted into lagrange duality problem its object function is decoupled, using cooperative alternative direction multiplier method, ask The target function value and coupling constraint for solving Unit Combination model violate angle value；When the current target function value of Unit Combination model and Coupling constraint violates angle value when meeting default condition, then the mesh of the original variable x according to each unit and Unit Combination model Offer of tender numerical value is configured to each unit.The complete distributed method for solving that such scheme is based on alternating direction multiplier method is realized The full decoupled and Distributed Calculation of power system unit, can protect the privacy between unit.
Brief description of the drawings
Fig. 1 is that the flow of the fully distributed power system unit input collocation method that the embodiment of the present invention one is provided is shown It is intended to；
Fig. 2 is that the flow of the fully distributed power system unit input collocation method that the embodiment of the present invention two is provided is shown It is intended to；
Fig. 3 is that the structure of the fully distributed power system unit input configuration system that the embodiment of the present invention four is provided is shown It is intended to；
Fig. 4 is that the structure of the fully distributed power system unit input configuration system that the embodiment of the present invention five is provided is shown It is intended to.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete Site preparation is described, it is clear that described embodiment is only a part of embodiment of the invention, rather than whole embodiments.It is based on Embodiment in the present invention, the every other reality that those of ordinary skill in the art obtain under the premise of creative work is not made Example is applied, the scope of protection of the invention is belonged to.
Fig. 1 is that the flow of the fully distributed power system unit input collocation method that the embodiment of the present invention one is provided is shown It is intended to, as shown in figure 1, methods described comprises the following steps：
101st, according to the basic data of each unit in Unit Commitment, Unit Combination model, the basis are built Data include：The spinning reserve data of the operation characteristic data, load prediction data and day part of generating set.
For example, the operation characteristic data of generating set may include but be not limited to：The fuel cost of generating set, startup Expense, cold start-up time, minimum start-stop time, the unit creep speed upper bound/lower bound, the unit output upper bound/lower bound, unit are initial Starting state and go out force data.
With actual scene for example：According to the basic data of each unit in Unit Commitment：Generating set The spinning reserve data of operation characteristic data, load prediction data and day part, build the electric power based on two class state variables System unit built-up pattern.
102nd, the constraints to the Unit Combination model is divided, obtain the first constraint set, the second constraint set and 3rd constraint set.
Wherein, first constraint set include unit starting expense, exert oneself, creep speed, the minimum start-stop time, initial shape State and state logic relation constraint, second constraint set include that power of the assembling unit Constraints of Equilibrium and spinning reserve are constrained, described the Three constraint sets include state and start unit output and payment for initiation variable nonnegativity restrictions after variable 0-1 constraints and projection.
103rd, according to first constraint set, the second constraint set and the 3rd constraint set, the Unit Combination model is carried out Arrange, and according to arrangement after the Unit Combination model, using alternating direction multiplier (Alternating Direction Method of Multipliers, abbreviation ADMM), the corresponding alternating direction multiplier method of acquisition is iterative, and the alternating direction multiplies The sub- iterative iteration variable of method includes original variable x, original variable z and dual variable u.
104th, according to first constraint set and the 3rd constraint set, the Unit Combination model is decoupled, point The original variable of each unit in the Unit Commitment under this upper strata iteration is not solved
Wherein k+1 is the number of times of this upper strata iteration, and i is machine group #.
105th, the quadratic programming problem built based on second constraint set is converted into lagrange duality problem, according to Unit is decoupled to the object function of the lagrange duality problem, according to the current original variable of each unit Using ADMM methods are cooperateed with, complete distribution solves the original variable of each unit under this upper strata iteration respectively
106th, according to the original variable that each unit is currentAnd original variableMultiplied based on the alternating direction Sub- method is iterative, obtains the dual variable of each unit under this upper strata iteration
107th, according to the original variable that each unit is currentSolve the target of each unit under this upper strata iteration Functional value and coupling constraint violate angle value, and the target function value current to each unit and coupling constraint are violated angle value and asked respectively With the target function value and coupling constraint for obtaining the Unit Combination model under this upper strata iteration violate angle value.
108th, judge that the current target function value of the Unit Combination model and coupling constraint violate whether angle value meets pre- If first condition, if meet, record the current original variable of each unitIt is current with the Unit Combination model Target function value, otherwise returns described in execution 104 and solves the Unit Commitment under this upper strata iteration respectively In each unit original variableThe step of.
For example, above-mentioned first condition may include：
Wherein, N is unit quantity,It is the target function value of each unit under+1 upper strata iteration of kth,For The target function value of Unit Combination model after the iteration of kth time upper strata,BiIt is the described second constraint concentrator The inequality coefficient matrix of group i, It is the equation coefficients matrix of unit i in second constraint set,It is the equality constraint constant matrices of second constraint set, c is the inequality constraints constant matrices of second constraint set, εc For coupling constraint violates angle value, εfeasibleIt is feasible convergence parameter.
109th, judge that the current coupling constraint of the Unit Combination model violates whether angle value meets default second condition, If meeting, stop upper strata iteration, according to the current original variable of each unitIt is current with the Unit Combination model Whether target function value, configures to each unit, otherwise, judge the number of times k+1 of this upper strata iteration beyond default Iterations max, if exceeding, stops upper strata iteration, according to the current original variable of each unitWith the unit group The current target function value of matched moulds type, configures to each unit, otherwise returns and solves this described in execution 104 respectively Under secondary upper strata iteration in the Unit Commitment each unit original variableThe step of.
For example, above-mentioned second condition may include：
Wherein, N is unit quantity,BiIt is the inequality coefficient of unit i in second constraint set Matrix, It is the equation coefficients matrix of unit i in second constraint set,It is the described second constraint The equality constraint constant matrices of collection, c is the inequality constraints constant matrices of second constraint set, εcIt is coupling constraint violation degree Value, εfeasibleIt is feasible convergence parameter, η is convergence coefficient of the scope between 0~1.
The fully distributed power system unit input collocation method that the present embodiment is provided, using power system unit group The basic data of each unit in conjunction, builds Unit Combination model and its constraint condition set is divided, and is multiplied using alternating direction Sub- method, based on the first constraint set and the 3rd constraint set, decouples Unit Combination model；Quadratic programming is built based on the second constraint set to ask Inscribe, and be converted into lagrange duality problem and its object function is decoupled, using cooperative alternative direction multiplier method, solve machine The target function value and coupling constraint of group built-up pattern violate angle value；When the current target function value of Unit Combination model and coupling When constraint violation angle value meets default condition, then original variable x and the target letter of Unit Combination model according to each unit Numerical value is configured to each unit.The complete distributed method for solving that such scheme is based on alternating direction multiplier method realizes electric power The full decoupled and Distributed Calculation of system unit, can protect the privacy between unit.
Fig. 2 is that the flow of the fully distributed power system unit input collocation method that the embodiment of the present invention two is provided is shown It is intended to, as shown in Fig. 2 on the basis of embodiment one, 105 include：
201st, quadratic programming problem is built based on second constraint set, using Lagrange duality function, by described two Secondary planning problem is converted into the lagrange duality problem；
202nd, the coefficient matrix to the object function of the lagrange duality problem is decoupled by unit, and is carried out whole Reason, according to the current original variable of described each unitUsing the antithesis alternating direction multiplier for cooperateing with ADMM methods to obtain Method is iterative, calculates the original variable obtained under this lower floor's iterationAnd the original variable of each unitWith it is right Mutation amountWhereinIt is the number of times of this lower floor's iteration；
203rd, the original variable under this lower floor's iteration is judgedWith the original variable of each unitWhether meet Default third condition, if meeting, stops lower floor's iteration, by the original variable under this lower floor's iterationBy secondary The optimality condition distribution of planning solves the original variable of each unit under this upper strata iterationOtherwise judge this The number of times of secondary lower floor's iterationWhether exceed default iterations max, if exceeding, stop lower floor's iteration, by this lower floor Original variable under iterationEach machine under this upper strata iteration is solved by the optimality condition distribution of quadratic programming The original variable of groupOtherwise return and perform described in 202 using the antithesis alternating direction multiplier for cooperateing with ADMM methods to obtain Method is iterative, calculates the original variable obtained under this lower floor's iterationAnd the original variable of each unitWith Dual variableThe step of.
For example, the third condition in above-mentioned 203 may include：
‖pr‖2≤εpri, ‖ dr‖2≤εdual；
Wherein,
Wherein, εabs=10-5, εrel=10-4, N is unit quantity, ρ2It is the penalty parameter of lower floor's iteration, T is scheduling total period Number.
Further, by the original variable under this lower floor's iteration in above-mentioned 203By the optimality of quadratic programming Condition distribution solves the original variable of each unit under this upper strata iterationMay include：
Wherein,WithThe inequality coefficient matrix B of unit i in respectively described second constraint setiWith equation coefficients square Battle arrayTransposed matrix.
The fully distributed power system unit input collocation method that the present embodiment is provided, this is solved completely distributed Under secondary upper strata iteration during the original variable z of each unit, this lower floor's iteration is obtained using cooperateing with ADMM methods to calculate Under original variableAnd the original variable of each unitAnd dual variableIf under this lower floor's iterationAnd each Meet third condition, then by under this lower floor's iterationSolved on this by the optimality condition distribution of quadratic programming Original variable z of the stacking for lower each unit.Such scheme can carry out more complete decoupling and be distributed to power system unit Formula is calculated, and is particularly suited for extensive fully distributed Optimization of Unit Commitment By Improved.
The embodiment of the present invention three provides a kind of fully distributed power system unit input collocation method, with following step Suddenly：
301st, collect Unit Commitment basic data and algorithm parameter is set, the Unit Combination basic data bag Include the spinning reserve data of operation characteristic data, load prediction data and the day part of generating set；
Specifically, the operation characteristic data of generating set may include the fuel cost of generating set, payment for initiation use, cold start-up Time, the minimum start-stop time, the unit creep speed upper bound/lower bound, the unit output upper bound/lower bound, unit initial startup state and Go out force data；Load prediction data can be the electric load demand feelings of following several periods obtained according to load prediction software Condition, including following day part power network total load data；
302nd, the power system related data according to collected by step 301, builds the power train based on two class state variables System Unit Combination model；
Specifically, the object function and constraints of the Unit Commitment model of two class state variables are as follows：
Object function：
Wherein,
Unit starting expense restriction：
Unit output is constrained：
Power-balance constraint：
Spinning reserve is constrained：
Ramping rate constraints：Including upward Climing constant and downward Climing constant；Wherein,
Upward Climing constant：
Downward Climing constant：
Wherein,
Unit minimum start-off time constraints：Including available machine time constraint and unused time constraint；Wherein, the available machine time is about Beam：
Unused time constrains：
Wherein：Ui={ min [T, ui,0(T on,i-Ti,0)]}+, Li={ min [T, ui,0(T off,i+Ti,0)]}+；
Unit original state is constrained：
ui,t=ui,0,t∈[1,…,Ui+Li] (11)；
Set state is constrained：
ui,t-ui,t-1≤si,t(12)；
Wherein, FCIt is optimization aim,The cost of exerting oneself of unit i, i.e. unit fuel cost are represented, i represents unit subscript, t Period subscript is represented, N represents unit quantity, hop count, α when T represents that scheduling is totali, βi, γiRepresent the secondary fuel expense of unit i Function coefficients,Represent that unit i carries out the secondary fuel cost function coefficient of projective transformation, Chot,iRepresent unit i's Thermal starting expense, Ccold,iThe cold start-up expense of unit i is represented,T on,iThe minimum available machine time of unit i is represented,T off,iExpression machine The minimum downtime of group i, Tcold,iRepresent and calculate unit i cold start-up times, f 'Init, i, tRepresent unit i in t meter and heat The part that payment for initiation exceeds, { }+Represent max (0), UiRepresent that unit i still needs to available machine time, L in initial timeiRepresent Unit i still needs to the unused time in initial time,The upper bound of exerting oneself of unit i is represented,P iThe lower bound of exerting oneself of unit i is represented,Table Show the exert oneself sizes of the unit i in t of two class state variable unit models, PD,tBorn needed for power system when representing t periods Lotus, RtRepresent spinning reserve value, P needed for t period power systemsup,iThe upward creep speed of unit i is represented,Represent unit I carries out the upward creep speed after projective transformation, Pdown,iThe downward creep speed of unit i is represented,Represent that unit i enters Downward creep speed after row projective transformation, Pstart,iMinimum load value when representing that unit i starts shooting,Represent unit i Carry out the minimum load value in start after projective transformation, Pshut,iEIAJ value when representing that unit i shuts down, Expression unit i carries out the EIAJ value in shutdown after projective transformation, ui,0Represent the original state of unit i, Ti,0Represent The time that unit i has run or shut down when initial, ui,tRepresent running statuses of the unit i in t, si,tRepresent unit i in t Moment starts shooting,The part that unit i exceeds in t thermal starting expense is represented,Represent that unit i existsMoment starts shooting；
The Unit Commitment model of two class state variables is as follows：
303rd, the Unit Commitment model of the two class state variables according to constructed by 302, by the constraint in model Three constraint set are divided into, wherein, the first constraint set includes：Unit starting expense, exert oneself, creep speed, minimum start and stop when Between, original state, state logic relation constraint；Institute's Constrained in first constraint set is separate to each unit, can be according to Machine group # is full decoupled；Second constraint set includes：Power of the assembling unit balance, two groups of constraints of spinning reserve；Institute in second constraint set Constrained can be full decoupled by the period；3rd constraint set includes：State and start after variable 0-1 constraint and projection unit output and Payment for initiation variable nonnegativity restrictions；Unit Combination model is carried out according to the first constraint set, the second constraint set and the 3rd constraint set Arrange；
Specifically, all variables are arranged according to unit numbered packets order, the constraint in three constraint sets is compiled according to unit The arrangement of number order of packets；
If
IfAnd
Definition set：
χ1=x | (1), (3), (7), (8), (9), (10), (11), (12) } (14)；
χ2=x | (5), (6) } (15)；
χ1It is as follows by unit decoupling Final finishing：
The coefficient matrices A and constant matrices b of the first constraint set are sorted out, wherein, the coefficient matrices A of the first constraint set presses machine Component masses form constraint factor AiArranged in diagonal matrix form, the constant matrices b=[b of the first constraint set1；…；bN], biFor The constant matrices of the first constraint set constraint；
χ2It is as follows by cycle decoupling Final finishing：
Sort out the second constraint set coefficient matrix B,And constant matrices c,Wherein, the coefficient square of the second constraint set Battle array B=[B1, B2,…,BN],BiIt is the inequality coefficient matrix of the second constraint set unit i, It is the equation coefficients matrix of the second constraint set unit i, c is the inequality constraints constant matrices of the second constraint set,It is the second constraint The equality constraint constant matrices of collection；
ADMM methods are used to meet, Unit Combination model is arranged as follows：
Wherein IχThe indicator function in set χ is defined as, it is as follows：
304th, according to the Unit Combination model after arranging in 303, corresponding upper strata alternating direction multiplier method iteration is write out Formula, iteration variable includes original variable x, original variable z and dual variable u；
Specifically, upper strata alternating direction multiplier method is iterative being：
uk+1=uk+(xk+1-zk+1) (23)；
Wherein, k+1 is the number of times of this upper strata iteration, ρ1It is the penalty parameter of upper strata iteration, xk+1For under this upper strata iteration Original variable x, zk+1It is original variable z, u under this upper strata iterationk+1It is the original variable u under this upper strata iteration；
305th, the original variable x of this upper strata iteration is updated, including：With reference to the first constraint set and the 3rd constraint set, according to Unit is decoupled, and the MINLP model problem after decoupling is calculated according to unit order；
Specifically, the renewal to original variable x includes：
According to formula (21), orderRandomly generateUpper strata iterations k+1=1~M2, ρ1＞ 0, with reference to the first constraint set, the 3rd constraint set, MINLP model problem is constituted, decoupled according to unit, solve following son Problem：
According to the x for solving acquisitioniOriginal variable x to this upper strata iteration is updated；
306th, the original variable z of this upper strata iteration is updated, is comprised the following steps：
Step one：Quadratic programming problem is constituted with reference to the second constraint set after arranging in 303：
It is subproblem that unit decoupling can be first pressed to it, then carries out decoupling computation by the cycle；
Step 2：It is following form that above-mentioned quadratic programming problem is arranged：
Wherein r=xk+1+uk；
Step 3：The strong duality of function when being updated in view of original variable z, according to the Lagrange duality of above mentioned problem Function finds out the function of original variable z when meeting optimality condition：
Wherein, λ be the second constraint set equality constraint Lagrange multiplier vector, γ be the second constraint set inequality constraints Lagrange multiplier vector, BT、Respectively coefficient matrix B,Transposed matrix；
Step 4：The function of above-mentioned original variable z is converted into the antithesis of the quadratic programming problem unrelated with original variable z Problem：
Order：
Wherein,
The dual problem of quadratic programming problem：
Step 5：The coefficient matrix of object function in dual problem is decoupled by unit, common recognition alternating direction is used Multiplier method, writes out lower floor's common recognition alternating direction multiplier method iterative：
Wherein,
ρ2It is the penalty parameter of lower floor's iteration,It is the number of times of this lower floor's iteration,For under this lower floor's iteration The original variable x of each unit,It is the original variable z under this lower floor's iteration,For under this lower floor's iteration each The original variable u of unit；
Step 6：The function variable related to original variable z is calculated according to iterative renewal of the lower floor in above-mentioned steps five：
OrderM3=50, lower floor's iterations ρ2＞ 0；
ForCan be obtained by optimal conditions, updated as follows：
Wherein, I is unit matrix；
It is updated to：
It is updated to：
Step 7：Judge the original variable under this lower floor's iterationWith the original variable of each unitWhether Meet the end condition of lower floor's iteration；
The end condition of lower floor's iteration is：
‖pr‖2≤εpri, ‖ dr‖2≤εdual；
Wherein,
Wherein, εabs=10-5, εrel=10-4；
If meeting, stop lower floor's iteration, order：
Return to original variableIt is worth in the iteration of upper strata, updates the original variable z of this upper strata iteration；
Otherwise judge the number of times of this lower floor's iterationWhether default iterations max M is exceeded3If exceeding, stop Lower floor's iteration, order：
Return to original variableIt is worth in the iteration of upper strata, updates the original variable z of this upper strata iteration；
Otherwise return and perform step 5；
307th, according to original variable x, the original variable z of this upper strata iteration updated in 305,306, with reference to formula：Update the dual variable u of this upper strata iteration；
308th, Unit Combination model objective function value under this upper strata iteration is calculated：
Wherein,Represent the target function value of each unit i；
And the coupling constraint that Unit Combination model is current under this upper strata iteration violates angle value：
Wherein,
309th, judge that the current target function value of Unit Combination model and coupling constraint violate whether angle value meets following bar Part：
Wherein,It is the target function value of Unit Combination model after the iteration of kth time upper strata, εfeasibleFor can Row convergence parameter；
If meeting, the original variable x under this upper strata iteration is updated to optimal solution xbest=xk+1, and by this The target function value of the Unit Combination model under the iteration of upper strata is updated to optimal solutionOtherwise return and perform 305；
Judge that the current coupling constraint of Unit Combination model violates whether angle value meets following condition：
Wherein, η is convergence coefficient of the scope between 0~1；
If meeting, stop upper strata iteration, according to xbestWithEach unit is configured；
Otherwise, judge the number of times k+1 of this upper strata iteration whether beyond default iterations max M2If exceeding, stop Only upper strata iteration, according to xbestWithEach unit is configured, is otherwise returned and is performed 305.
The fully distributed power system unit input collocation method that the present embodiment is provided, using power system unit group The basic data of each unit in conjunction, builds Unit Combination model and its constraint condition set is divided, and is multiplied using alternating direction Sub- method, based on the first constraint set and the 3rd constraint set, decouples Unit Combination model；Quadratic programming is built based on the second constraint set to ask Inscribe, and be converted into lagrange duality problem and its object function is decoupled, using cooperative alternative direction multiplier method, solve machine The target function value and coupling constraint of group built-up pattern violate angle value；When the current target function value of Unit Combination model and coupling When constraint violation angle value meets default condition, then original variable x and the target letter of Unit Combination model according to each unit Numerical value is configured to each unit.The complete distributed method for solving that such scheme is based on alternating direction multiplier method realizes electric power The full decoupled and Distributed Calculation of system unit, can protect the privacy between unit.
Fig. 3 is that the structure of the fully distributed power system unit input configuration system that the embodiment of the present invention four is provided is shown It is intended to, as shown in figure 3, the system includes：
Module 31 is built, for the basic data according to each unit in Unit Commitment, Unit Combination mould is built Type, the basic data includes：The spinning reserve number of the operation characteristic data, load prediction data and day part of generating set According to；
Division module 32, divides for the constraints to the Unit Combination model, obtains the first constraint set, the Two constraint sets and the 3rd constraint set, first constraint set include unit starting expense, exert oneself, creep speed, minimum start and stop when Between, original state and state logic relation constraint, second constraint set includes power of the assembling unit Constraints of Equilibrium and spinning reserve about Beam, the 3rd constraint set includes state and starts unit output and payment for initiation variable non-negative after variable 0-1 constraints and projection Constraint；
Sorting module 33, for according to first constraint set, the second constraint set and the 3rd constraint set, to the unit group Matched moulds type is arranged, and according to arrangement after the Unit Combination model, using alternating direction multiplier, obtain corresponding alternating Direction multiplier method is iterative, and the iterative iteration variable of alternating direction multiplier method includes original variable x, original variable z and right Mutation amount u；
First decoupling module 34, for according to first constraint set and the 3rd constraint set, to the Unit Combination Model is decoupled, and the original variable of each unit in the Unit Commitment under this upper strata iteration is solved respectivelyWherein k+1 is the number of times of this upper strata iteration, and i is machine group #；
Second decoupling module 35, it is bright for the quadratic programming problem built based on second constraint set to be converted into glug Day dual problem, decouples according to unit to the object function of the lagrange duality problem, current according to each unit Original variableUsing ADMM methods are cooperateed with, complete distribution solves each unit under this upper strata iteration respectively Original variable
Antithesis module 36, for according to the current original variable of each unitAnd original variableBased on described Alternating direction multiplier method is iterative, obtains the dual variable of each unit under this upper strata iteration
Module 37 is solved, for according to the current original variable of each unitSolve every under this upper strata iteration The target function value and coupling constraint of individual unit violate angle value, and the target function value current to each unit and coupling be about respectively Beam violates angle value summation, obtains the target function value and coupling constraint violation degree of the Unit Combination model under this upper strata iteration Value；
First judge module 38, for judging that the current target function value of the Unit Combination model and coupling constraint are violated Whether angle value meets default first condition, if meeting, records the current original variable of each unitWith the unit The current target function value of built-up pattern, otherwise indicates the first decoupling module 34 to perform again and described solves this upper strata respectively Under iteration in the Unit Commitment each unit original variableThe step of；
Second judge module 39, for judging that the current coupling constraint of the Unit Combination model violates whether angle value meets Default second condition, if meeting, stops upper strata iteration, according to the current original variable of each unitWith the machine The current target function value of group built-up pattern, configures to each unit, otherwise, judges the number of times k+ of this upper strata iteration Whether 1 exceed default iterations max, if exceeding, stops upper strata iteration, according to the current original variable of each unitThe target function value current with the Unit Combination model, configures to each unit, otherwise indicates first to decouple Module 34 performs the original for solving each unit in the Unit Commitment under this upper strata iteration respectively again Beginning variableThe step of.
Fig. 4 is that the structure of the fully distributed power system unit input configuration system that the embodiment of the present invention five is provided is shown It is intended to, as shown in figure 4, on the basis of example IV, the second decoupling module 35 includes：
Conversion unit 401, for building quadratic programming problem based on second constraint set, using Lagrange duality letter Number, the lagrange duality problem is converted into by the quadratic programming problem；
Unit 402 is arranged, the coefficient matrix for the object function to the lagrange duality problem is carried out by unit Decoupling, and arranged, according to the current original variable of described each unitIt is right using cooperate with ADMM methods to obtain Even alternating direction multiplier method is iterative, calculates the original variable obtained under this lower floor's iterationAnd the original of each unit Beginning variableAnd dual variableWhereinIt is the number of times of this lower floor's iteration；
Judging unit 403, for judging the original variable under this lower floor's iterationWith the original variable of each unitWhether meet default third condition, if meeting, stop lower floor's iteration, by the original variable under this lower floor's iterationThe original variable of each unit under this upper strata iteration is solved by the optimality condition distribution of quadratic programmingOtherwise judge the number of times of this lower floor's iterationWhether exceed default iterations max, if exceeding, stop lower floor Iteration, by the original variable under this lower floor's iterationThis is solved by the optimality condition distribution of quadratic programming The original variable of each unit under the iteration of upper strataOtherwise indicate arrangement unit 402 to perform described utilization again and cooperate with ADMM The antithesis alternating direction multiplier method that method is obtained is iterative, calculates the original variable obtained under this lower floor's iterationAnd The original variable of each unitAnd dual variableThe step of.
It is apparent to those skilled in the art that, for convenience and simplicity of description, the system of foregoing description Specific work process, may be referred to the corresponding process in preceding method embodiment, will not be repeated here.
Finally it should be noted that：Various embodiments above is merely illustrative of the technical solution of the present invention, rather than its limitations；To the greatest extent Pipe has been described in detail with reference to foregoing embodiments to the present invention, it will be understood by those within the art that：Its according to The technical scheme described in foregoing embodiments can so be modified, or which part or all technical characteristic are entered Row equivalent；And these modifications or replacement, the essence of appropriate technical solution is departed from various embodiments of the present invention technology The scope of scheme.

Claims (9)

1. a kind of fully distributed power system unit puts into collocation method, it is characterised in that with following steps：
According to the basic data of each unit in Unit Commitment, Unit Combination model is built, the basic data includes： The spinning reserve data of the operation characteristic data, load prediction data and day part of generating set；
Constraints to the Unit Combination model is divided, and obtains the first constraint set, the second constraint set and the 3rd constraint Collection, first constraint set include unit starting expense, exert oneself, creep speed, minimum start-stop time, original state and state are patrolled Relation constraint is collected, second constraint set includes that power of the assembling unit Constraints of Equilibrium and spinning reserve are constrained, the 3rd constraint set bag Include state and start unit output and payment for initiation variable nonnegativity restrictions after variable 0-1 constraints and projection；
According to first constraint set, the second constraint set and the 3rd constraint set, the Unit Combination model is arranged, and root According to the Unit Combination model after arrangement, using alternating direction multiplier (Alternating Direction Method of Multipliers, ADMM), the corresponding alternating direction multiplier method of acquisition is iterative, the iterative iteration of alternating direction multiplier method Variable includes original variable x, original variable z and dual variable u；
According to first constraint set and the 3rd constraint set, the Unit Combination model is decoupled, solved respectively Under this upper strata iteration in the Unit Commitment each unit original variableWherein k+1 is this upper strata The number of times of iteration, i is machine group #；
The quadratic programming problem built based on second constraint set is converted into lagrange duality problem, according to unit to institute The object function for stating lagrange duality problem is decoupled, according to the current original variable of each unitUsing collaboration ADMM methods, respectively complete distribution solve the original variable of each unit under this upper strata iteration
According to the current original variable of each unitAnd original variableBased on the alternating direction multiplier method iteration Formula, obtains the dual variable of each unit under this upper strata iteration
According to the current original variable of each unitSolve under this upper strata iteration the target function value of each unit and Coupling constraint violates angle value, and the target function value current to each unit and coupling constraint violate angle value summation respectively, obtain The target function value of the Unit Combination model and coupling constraint violate angle value under this upper strata iteration；
Judge that the current target function value of the Unit Combination model and coupling constraint violate whether angle value meets default first Condition, if meeting, records the current original variable of each unitThe object function current with the Unit Combination model Value, otherwise returns and performs the original for solving each unit in the Unit Commitment under this upper strata iteration respectively Beginning variableThe step of；
Judge that the current coupling constraint of the Unit Combination model violates whether angle value meets default second condition, if meeting, Then stop upper strata iteration, according to the current original variable of each unitThe target letter current with the Unit Combination model Numerical value, configures to each unit, otherwise, judges whether the number of times k+1 of this upper strata iteration exceeds default iteration most Big value, if exceeding, stops upper strata iteration, according to the current original variable of each unitWith the Unit Combination model Current target function value, configures to each unit, and otherwise return execution is described solves this upper strata iteration respectively Under in the Unit Commitment each unit original variableThe step of.
2. method according to claim 1, it is characterised in that the operation characteristic data of the generating set include generator The fuel cost of group, payment for initiation use, cold start-up time, minimum start-stop time, the unit creep speed upper bound/lower bound, unit output The upper bound/lower bound, unit initial startup state and go out force data.
3. method according to claim 1, it is characterised in that described to be based on the secondary rule that second constraint set builds The problem of drawing is converted into lagrange duality problem, and the object function of the lagrange duality problem is solved according to unit Coupling, according to the current original variable of each unitUsing ADMM methods are cooperateed with, complete distribution solves this respectively The original variable of each unit under the iteration of upper strataIncluding：
Quadratic programming problem is built based on second constraint set, using Lagrange duality function, the quadratic programming is asked Topic is converted into the lagrange duality problem；
Coefficient matrix to the object function of the lagrange duality problem is decoupled by unit, and is arranged, according to The current original variable of described each unitUsing the antithesis alternating direction multiplier method iteration for cooperateing with ADMM methods to obtain Formula, calculates the original variable obtained under this lower floor's iterationAnd the original variable of each unitAnd dual variableWhereinIt is the number of times of this lower floor's iteration；
Judge the original variable under this lower floor's iterationWith the original variable of each unitWhether default is met Three conditions, if meeting, stop lower floor's iteration, by the original variable under this lower floor's iterationBy quadratic programming most Dominance condition distribution solves the original variable of each unit under this upper strata iterationOtherwise judge this lower floor's iteration Number of timesWhether exceed default iterations max, if exceeding, stop lower floor's iteration, by the original under this lower floor's iteration Beginning variableThe original change of each unit under this upper strata iteration is solved by the optimality condition distribution of quadratic programming AmountOtherwise return to execution described iterative using the antithesis alternating direction multiplier method for cooperateing with ADMM methods to obtain, calculating is obtained Obtain the original variable under this lower floor's iterationAnd the original variable of each unitAnd dual variableStep Suddenly.
4. method according to claim 3, it is characterised in that the third condition includes：
‖pr‖2≤εpri, ‖ dr‖2≤εdual；
Wherein,
p r = [ ( x ^ 1 k ^ + 1 - z ^ k ^ + 1 ) ; ... ; ( x ^ N k ^ + 1 - z ^ k ^ + 1 ) ] ;
d r = [ ( z ^ k ^ - z ^ k ^ + 1 ) ; ... ; ( z ^ k ^ - z ^ k ^ + 1 ) ] ;
ϵ p r i = 2 N T ϵ a b s + ϵ r e l max { | | ( x ^ 1 k ^ + 1 ; ... ; x ^ N k ^ + 1 ) | | 2 , N | | z ^ k ^ + 1 | | 2 } ;
ϵ d u a l = 2 N T ϵ a b s + ϵ r e l | | ( ρ 2 u ^ 1 k ^ + 1 ; ... ; ρ 2 u ^ N k ^ + 1 ) | | 2 ;
Wherein, εabs=10-5, εrel=10-4, N is unit quantity, ρ2It is the penalty parameter of lower floor's iteration, T is hop count when scheduling is total.
5. method according to claim 3, it is characterised in that the original change by each unit under this lower floor's iteration AmountThe original variable of each unit under this upper strata iteration is solved by the optimality condition distribution of quadratic programmingIncluding：
z i k + 1 = x i k + 1 + u i k - 1 2 [ B i T , B ~ i T ] z ^ k ^ + 1 ;
Wherein,WithThe inequality coefficient matrix B of unit i in respectively described second constraint setiWith equation coefficients matrix Transposed matrix.
6. method according to claim 1, it is characterised in that the first condition includes：
Σ i = 1 N A i k + 1 ≤ f x b e s t ;
ϵ c = | | Σ i = 1 N B ~ i k + 1 - c ~ max ( Σ i = 1 N B i k + 1 - c ) | | 2 | | c ~ c | | 2 ≤ ϵ f e a s i b l e ;
Wherein, N is unit quantity,It is the target function value of each unit under+1 upper strata iteration of kth,It is kth time The target function value of Unit Combination model after the iteration of upper strata,BiIt is unit i in second constraint set Inequality coefficient matrix, It is the equation coefficients matrix of unit i in second constraint set,For institute The equality constraint constant matrices of the second constraint set is stated, c is the inequality constraints constant matrices of second constraint set, εcIt is coupling Constraint violation angle value, εfeasibleIt is feasible convergence parameter.
7. method according to claim 1, it is characterised in that the second condition includes：
ϵ c = | | Σ i = 1 N B ~ i k + 1 - c ~ max ( Σ i = 1 N B i k + 1 - c ) | | 2 | | c ~ c | | 2 ≤ ηϵ f e a s i b l e ;
Wherein, N is unit quantity,BiIt is the inequality coefficient square of unit i in second constraint set Battle array, It is the equation coefficients matrix of unit i in second constraint set,It is second constraint set Equality constraint constant matrices, c is the inequality constraints constant matrices of second constraint set, εcIt is coupling constraint violation degree Value, εfeasibleIt is feasible convergence parameter, η is convergence coefficient of the scope between 0~1.
8. a kind of fully distributed power system unit puts into configuration system, it is characterised in that including：
Module is built, for the basic data according to each unit in Unit Commitment, Unit Combination model is built, it is described Basic data includes：The spinning reserve data of the operation characteristic data, load prediction data and day part of generating set；
Division module, divides for the constraints to the Unit Combination model, obtains the first constraint set, the second constraint Collection and the 3rd constraint set, first constraint set include unit starting expense, exert oneself, it is creep speed, the minimum start-stop time, initial State and state logic relation constraint, second constraint set include that power of the assembling unit Constraints of Equilibrium and spinning reserve are constrained, described 3rd constraint set includes state and starts unit output and payment for initiation variable nonnegativity restrictions after variable 0-1 constraints and projection；
Sorting module, for according to first constraint set, the second constraint set and the 3rd constraint set, to the Unit Combination model Arranged, and according to arrangement after the Unit Combination model, using alternating direction multiplier, obtain corresponding alternating direction and multiply Sub- method is iterative, and the iterative iteration variable of alternating direction multiplier method includes original variable x, original variable z and dual variable u；
First decoupling module, for according to first constraint set and the 3rd constraint set, entering to the Unit Combination model Row decoupling, solves the original variable of each unit in the Unit Commitment under this upper strata iteration respectively Wherein k+1 is the number of times of this upper strata iteration, and i is machine group #；
Second decoupling module, for the quadratic programming problem built based on second constraint set to be converted into Lagrange duality Problem, decouples according to unit to the object function of the lagrange duality problem, according to current original of each unit VariableUsing ADMM methods are cooperateed with, complete distribution solves the original change of each unit under this upper strata iteration respectively Amount
Antithesis module, for according to the current original variable of each unitAnd original variableBased on the alternating side It is iterative to multiplier method, obtain the dual variable of each unit under this upper strata iteration
Module is solved, for according to the current original variable of each unitSolve each unit under this upper strata iteration Target function value and coupling constraint violate angle value, the target function value current to each unit and coupling constraint are violated respectively Angle value is sued for peace, and the target function value and coupling constraint for obtaining the Unit Combination model under this upper strata iteration violate angle value；
First judge module, be for judging that the current target function value of the Unit Combination model and coupling constraint violate angle value It is no to meet default first condition, if meeting, record the current original variable of each unitWith the Unit Combination mould The current target function value of type, otherwise indicates first decoupling module to perform again and described solves this upper strata iteration respectively Under in the Unit Commitment each unit original variableThe step of；
Second judge module, for judging that the current coupling constraint of the Unit Combination model violates whether angle value meets default Second condition, if meeting, stops upper strata iteration, according to the current original variable of each unitWith the Unit Combination The current target function value of model, configures to each unit, otherwise, judge this upper strata iteration number of times k+1 whether Beyond default iterations max, if exceeding, stop upper strata iteration, according to the current original variable of each unitWith The current target function value of the Unit Combination model, configures to each unit, otherwise indicates the first decoupling mould Block performs the original change for solving each unit in the Unit Commitment under this upper strata iteration respectively again AmountThe step of.
9. system according to claim 8, it is characterised in that second decoupling module includes：
Conversion unit, for building quadratic programming problem based on second constraint set, using Lagrange duality function, by institute State quadratic programming problem and be converted into the lagrange duality problem；
Unit is arranged, the coefficient matrix for the object function to the lagrange duality problem is decoupled by unit, and Arranged, according to the current original variable of described each unitUsing the antithesis alternating side for cooperateing with ADMM methods to obtain It is iterative to multiplier method, calculate the original variable obtained under this lower floor's iterationAnd the original variable of each unitAnd dual variableWhereinIt is the number of times of this lower floor's iteration；
Judging unit, for judging the original variable under this lower floor's iterationWith the original variable of each unitIt is It is no to meet default third condition, if meeting, stop lower floor's iteration, by the original variable under this lower floor's iterationIt is logical The optimality condition distribution for crossing quadratic programming solves the original variable of each unit under this upper strata iterationOtherwise sentence The number of times of this lower floor's iteration of breakingWhether exceed default iterations max, if exceeding, stop lower floor's iteration, by this Original variable under lower floor's iterationSolved by the optimality condition distribution of quadratic programming every under this upper strata iteration The original variable of individual unitThe arrangement unit is otherwise indicated to perform again described right using cooperate with ADMM methods to obtain Even alternating direction multiplier method is iterative, calculates the original variable obtained under this lower floor's iterationAnd the original of each unit Beginning variableAnd dual variableThe step of.
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