CN108599268A - A kind of Optimization Scheduling a few days ago considering the constraint of wind power plant space time correlation - Google Patents
A kind of Optimization Scheduling a few days ago considering the constraint of wind power plant space time correlation Download PDFInfo
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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
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- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
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- 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
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/76—Power conversion electric or electronic aspects
Abstract
The present invention relates to a kind of Optimization Schedulings a few days ago of consideration wind power plant space time correlation constraint, include the following steps：1) the robust Unit Combination mathematical model for considering cost of electricity-generating and abandoning eolian is established；2) for the steric crowding of wind-powered electricity generation and time smoothing effect, structure considers the uncertain collection of wind-powered electricity generation room and time constraint；3) mathematical model is decomposed into Unit Combination primal problem, Security and feasibility examines subproblem and maximally utilizes wind-powered electricity generation subproblem, the coupled relation for establishing boss's problem using arranging and constraining generating algorithm, and it is solved to obtain Optimized Operation scheme, compared with prior art, the present invention has many advantages, such as that fast and reliable, applicability is high, consideration is comprehensive, effect of optimization is good.
Description
Technical field
The present invention relates to wind power plant scheduling fields, more particularly, to a kind of a few days ago excellent of consideration wind power plant space time correlation constraint
Change dispatching method.
Background technology
It reduces the dependence to fossil energy and greatly develops the clean energy resource that wind-powered electricity generation is representative and have become international community's reply
The widespread consensus of Global climate change.Energy Development in China relevant policies propose, to the year two thousand thirty, the power generation of the renewable resources such as wind-powered electricity generation
Amount is up to 20%, and high proportion wind-electricity integration has become the inexorable trend of China's electric power development.However, as wind-powered electricity generation is in power grid
Middle ratio is constantly soaring, and randomness and intermittence bring severe challenge to Optimization of Unit Commitment By Improved, and it is uncertain to exacerbate it
Property.Under high proportion wind power integration, traditional certainty Unit Combination model]It has been difficult to be applicable in.For this purpose, wind power output is not true
Qualitative modeling has become the critical issue studied needed for Unit Combination under high proportion wind-powered electricity generation.
For the uncertainty of wind-powered electricity generation, the processing method of mainstream is roughly divided into 3 classes at present：Spare Criterion Method, random optimization
Method and robust optimization.Spare Criterion Method is to cope with the uncertainty of wind-powered electricity generation, this method by configuring the spare of certain capacity
It is simple and practicable, but the spare capacity for taking into account economy and reliability is difficult to determine.Random optimization method be by wind-power electricity generation with
Airport scape and dependent probability are modeled to portray the uncertainty of wind-powered electricity generation, but Stochastic Programming Model is because with computationally intensive, meter
The problems such as precision can not ensure is calculated, popularization and application are restricted.Robust optimizes rule using uncertain collection to describe wind-powered electricity generation not
Certainty can provide the robust solution met under most harsh conditions, obtained in Unit Commitment in recent years preliminary
Application.
However, existing robust Unit Combination is mostly with Unit Commitment expense and the minimum object function of operating cost, and
It is assumed that wind power output can all be dissolved by system.Wind-powered electricity generation possibly can not all be disappeared completely when in view of high proportion wind-electricity integration
Receive, but at present robust Unit Combination to abandon wind research relatively fewer, it is therefore desirable to wind is abandoned in consideration in robust Unit Combination, is promoted
The digestion capability of wind-powered electricity generation.
Further, since robust optimization is attempt to obtain the robust solution for meeting any scene, this makes its scheduling scheme excessively
It is conservative.Therefore, uncertain collection should be shunk as possible under the premise of not influencing decision making reliability to improve the economy of model.Some
Document has refined the form that the uncertainty description of wind power is bounded-but-unknown uncertainty in wind power each period
Value range, but the time smoothing effect of wind power is not accounted for, keep model still overly conservative.Although some documents consider
The time smoothing effect of wind-powered electricity generation is studied, but has ignored the steric crowding of wind-powered electricity generation.Therefore consider wind power plant
Steric crowding and time smoothing effect uncertain collection need further research.
Consider that the Optimal Operation Model a few days ago of wind power plant space time correlation constraint is one while including from the point of view of mathematics essence
The higher-dimension of continuous variable and discrete variable, nonlinear mixed integer programming problem, direct solution difficulty are big.For the ease of meter
It calculates, is generally converted into the optimization problem of a multilayer nest, innermost layer optimization problem is eliminated with dualistic transformation.Usually adopt
Robust Unit Combination is solved with Benders algorithms, but its convergence efficiency depends on the quality of dual solution, is easy to meet with calculating speed
Slow problem.It is calculated for large-scale alternating iteration, row and constraint generating algorithm can recognize that uncertain factor influenced
Key variables, are the new variable and constraint of primal problem dynamic creation, but application study of the algorithm in robust Unit Combination
It is relatively fewer.
Therefore, it is badly in need of a kind of Optimization Scheduling a few days ago considering the constraint of wind power plant space time correlation, can either fully considers
The steric crowding and time smoothing effect of wind, and can rapidly and accurately obtain and obtain Optimized Operation result.
Invention content
It is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide when a kind of consideration wind power plant
The Optimization Scheduling a few days ago of null Context constraint.
The purpose of the present invention can be achieved through the following technical solutions：
A kind of Optimization Scheduling a few days ago considering the constraint of wind power plant space time correlation, includes the following steps：
1) the robust Unit Combination mathematical model for considering cost of electricity-generating and abandoning eolian is established；
2) for the steric crowding of wind-powered electricity generation and time smoothing effect, structure considers the constraint of wind-powered electricity generation room and time not
Determine collection；
3) mathematical model is decomposed into Unit Combination primal problem, Security and feasibility examines subproblem and maximally utilizes wind
Electrical issues establish the coupled relation of boss's problem using arranging and constraining generating algorithm, and are solved to obtain Optimized Operation
Scheme.
In the step 1), the object function of cost of electricity-generating and the robust Unit Combination mathematical model for abandoning eolian is considered
For：
Wherein, F is cost of electricity-generating and abandons the sum of wind punishment cost, suiFor the startup expense of system unit, sdiFor System Computer
The idleness expense of group, zi,tAnd ui,tIt is 0/1 variable of first stage, to indicate the start and stop state transformation of unit i, if unit
I becomes starting then z in period t from shutting downi,t=1, otherwise zi,t=0, if unit i period t from run become shut down if ui,t=
1, otherwise zi,t=0, fi,t(pi,t) be unit operating cost quadratic function, T be scheduling slot sum, N be unit sum, NW
It is total for wind power plant,For j-th of wind power plant t moment wind power output power,It is j-th of wind power plant in t moment
Optimal scheduling is contributed, λjPenalty coefficient when wind is abandoned for j-th of wind power plant, subscript w indicates that wind-powered electricity generation, subscript b indicate normal condition；
Constraints includes：
A) minimum available machine time constraint：
Wherein,For the minimum available machine time of unit i,On the basis of operation shapes of the unit i in the t-1 periods under state
State variable,On the basis of under state unit i in the operating status variable of t periods, yi,hIt is unit i when having run/having stopped transport
Interior operating status variable, h are to have run/idle time；
B) minimum downtime constraint：
Wherein,For the minimum downtime of unit i；
C) the logical constraint of set state and state conversion：
D) system reserve constrains：
Wherein, pb,tFor the load at t period nodes b, r is spinning reserve rate, pi,maxFor the maximum output of unit i, ND is
Node total number；
E) unit output constrains：
Wherein, pi,maxAnd pi,minThe respectively minimum and maximum power generating value of unit i.
F) power-balance constraint：
Wherein,On the basis of outputs of the unit i in the t periods under state,On the basis of under state j-th of wind power plant exist
The optimal scheduling of t moment is contributed；
G) unit ramp loss：
Wherein, RUiAnd RDiThe upper and lower climbing rate of respectively unit i.
H) transmission line of electricity capacity-constrained：
Wherein,Respectively node i, the power transfer factor of j, b to circuit l,For circuit
Maximum transmission capacity；
I) the units limits of wind power plant：
Wherein,It is wind power output power of j-th of wind power plant in t moment, W is constrained not for wind-powered electricity generation room and time
Determine collection.
In the step 2), the uncertain collection W of wind-powered electricity generation room and time constraint is expressed as：
Wherein, wj,tExpectation for j-th of wind power plant in t moment is contributed, Δ wj,tFor wind power output power and desired value
Maximum deviation amount,For 0/1 variable,For the space constraint parameter of wind power output power,For wind power output power
Time-constrain parameter, the one or two row illustrates the prediction power of wind-powered electricity generation, the uncertain constraint of third time of the act, fourth line in formula
For the uncertain constraint in space.
The detailed process that its parameter calculates includes the following steps：
21) the conservative degree control parameter Δ w of setj,tCalculating：The given conservative degree control parameter α ∈ (0,1) of a set are come
The conservative degree of set is controlled, i.e.,：
Wherein, φ-1() is the inverse function of standardized normal distribution cumulative probability density function, σj,tExist for j-th of wind power plant
The standard deviation of t moment；.
22) parameterWithCalculating：
It enables
Wherein, ej,tFor the prediction error of wind power output power, YjFor the e at j-th of wind power plant all momentj,tSummation；YtFor
The e of all wind power plants of t momentj,tSummation.
Wherein, M is wind power plant number；T is scheduling slot number.
In addition, for the ease of solving, absolute value is concentrated to carry out linearization process to uncertain.It enablesThen not
Determine that collection can be converted to：
Wherein,
aj,t=-aj,t,1+aj,t,2
-Ndj,t,1≤aj,t≤Ndj,t,2
0≤aj,t,1≤Ndj,t,1
0≤aj,t,2≤Ndj,t,2
dj,t,1+dj,t,2=1
Wherein, aj,t, aj,t,1, aj,t,2It is the auxiliary variable of introducing；dj,t,1,dj,t,2It is 0/1 variable (if aj,t＞ 0, then
dj,t,1=0, dj,t,2=1；If aj,t＜ 0, then dj,t,1=1, dj,t,2=0)；N is a sufficiently large positive number.
In the step 3), Unit Combination primal problem is expressed as：
Wherein, constraints is minimum available machine time constraint, minimum downtime constraint, set state and state conversion
Logical constraint, system reserve constraint, unit output constraint, power-balance constraint, unit ramp loss, transmission line of electricity capacity are about
The target function value that the C＆CG of beam, the units limits of wind power plant and all generations is cut and η >=0, η are subproblem.
In the step 3), it is to examine that Security and feasibility, which examines subproblem Security and feasibility to examine the target of subproblem,
Whether the solution for testing primal problem can adapt to all wind-powered electricity generation random fluctuations.If accordingly, it is considered to all not have to constraining under most harsh conditions
Have out-of-limit, no matter then how uncertain factor changes, can ensure the safe operation of system, structure is expressed as max-min
Problem, i.e.,：
υ1,lt≥0
υ2t≥0
υ3t≥0
Wherein, ZCThe target function value of subproblem, υ are examined for Security and feasibility1,lt,υ2,lt,υ3,ltThe pine respectively introduced
Relaxation variable,To consider the wind power output of wind-powered electricity generation uncertainty optimization,To consider the unit of wind-powered electricity generation uncertainty optimization
It contributes, subscript u indicates to consider the uncertain state of wind-powered electricity generation.
In the step 3), if primal problem is by safety examination, then needs further to solve wind-powered electricity generation and maximally utilize son
Problem, the object function of the subproblem are to abandon wind punishment cost minimum under most harsh conditions, maximally utilize wind-powered electricity generation subproblem
It is expressed as：
Wherein, ZSThe object function of subproblem, constraints and Security and feasibility syndrome are maximally utilized for wind-powered electricity generation
The constraints of problem is identical, but does not include slack variable.
In the step 3), is solved using C＆CG algorithms, specifically include following steps：
31) primal problem：Unit Combination primal problem is solved using mixed integer programming, obtains operating status, the machine at each moment
Group is contributed and the object function lower bound of second stage, and passes to next stage；
32) subproblem：The operating states of the units variable transmitted to Unit Combination primal problem optimizes and generates cut set, produces
Giving birth to cut set includes：
321) operating states of the units solved in Unit Combination primal problem is substituted into feasibility test subproblem, judged
Whether operating states of the units meets the requirements under most severe scene, if the sum of slack variable is not 0, the operating states of the units is not
It meets the requirements, generates C＆CG and cut and return primal problem, operating states of the units is adjusted, if in Security and feasibility check problem
The sum of slack variable of introducing is 0, then proves that problem is feasible, carries out the solution that wind-powered electricity generation maximally utilizes subproblem；
322) solution obtained in step 31) substitution wind-powered electricity generation is maximally utilized in subproblem, calculates its dual problem, obtains
The upper bound of second stage object function obtains optimal solution when iteration convergence, otherwise generates C＆CG and cuts and return primal problem, right
Operating states of the units is adjusted.
Compared with prior art, the present invention has the following advantages：
One, fast and reliable：Compared with the conventional method, method for solving disclosed by the invention can obtain decision fast and reliablely
The Optimized Operation of variable is as a result, effectively improve computational efficiency.
Two, increase the applicability of model：Consider on the basis of considering the Optimized Operation a few days ago of wind power plant space time correlation constraint
Abandoning wind punishment cost can ensure that wind-powered electricity generation maximally utilizes wind-powered electricity generation when cannot all be dissolved, and increase the applicability of model.
Three, consider the steric crowding and time smoothing effect of wind-powered electricity generation：Consider wind-powered electricity generation time and space constraint not really
Fixed collection can more meticulously describe the uncertainty of wind-powered electricity generation, and then obtain that effect of optimization is more preferable, more meets actual motion feelings
The scheduling scheme of condition.
Description of the drawings
Fig. 1 is the IEEE39 node system figures that wind power plant is added.
Fig. 2 is the schematic diagram of the optimum results variation under different wind-powered electricity generation ratios.
Fig. 3 is change curve schematic diagram of the error with iterations.
Fig. 4 is the schematic diagram of the uncertain collection of two kinds of models.
Fig. 5 is the schematic diagram that wind power plant steric crowding influences result of calculation.
Fig. 6 is flow chart of the method for the present invention.
Specific implementation mode
The present invention is described in detail with specific embodiment below in conjunction with the accompanying drawings.
Embodiment
The present invention proposes a kind of Optimization Scheduling a few days ago of consideration wind power plant space time correlation constraint, as shown in fig. 6, this
Invention has initially set up the mathematical model of the robust Unit Combination of high proportion wind-powered electricity generation, which is generated electricity with minimizing in dispatching cycle
Wind punishment cost of abandoning under cost and most severe scene is target, while meeting a variety of fired power generating units and the pact of Wind turbines
Beam.
Secondly, its uncertain collection is established for the wind power output with steric crowding and time smoothing effect.
Then, former problem is decoupled by the Unit Combination primal problem of ground state based on the robust principle of optimality and two sons is asked
Topic is safety verification subproblem and maximally utilizes wind-powered electricity generation subproblem.
Then in view of the solution difficulty of high proportion wind-powered electricity generation model, integrated use duality theory, mixed integer programming and C＆
CG algorithms, which are iterated model, to be solved until obtaining the scheduling scheme with robustness and economy.
Embodiment 1：
Lower mask body combines an IEEE39 node system comprising 1 wind power plant to carry out detailed analysis, as shown in Figure 1.
In order to analyze the robustness of set, the conservative degree control parameter α of different set is taken, its influence to dispatching cost, tool are analyzed
The results are shown in Table 1 for body.As can be seen from Table 1, the scheduling knot that robust Unit Combination Optimized model obtains under different control parameter α
Fruit is all different, and the change for not knowing collection thus will have a direct impact on the scheduling decision of robust Unit Combination；In addition as control is joined
The reduction of number α, indeterminacy section constantly shrinks, and the cost of electricity-generating that robust Unit Combination model optimization obtains and abandons wind punishment cost
Also downward trend is presented.
Scheduling result under the different control parameter α of table 1
| α | Cost of electricity-generating/($) | Abandon wind punishment cost/($) | Totle drilling cost/($) |
| 0.9 | 72640 | 7977 | 80617 |
| 0.7 | 71424 | 7808 | 79232 |
| 0.5 | 70216 | 7684 | 77900 |
| 0.3 | 69100 | 7540 | 76640 |
| 0.1 | 67735 | 7437 | 75172 |
In order to analyze the influence for abandoning wind model to scheduling decision, it is divided into four kinds of schemes and compares and analyzes.
Scheme 1：It (can be optimized by the 60% of wind power plant capacity, i.e. wind power integration ratio by consumption completely in wind power
Example is under the premise of 15%), does not consider to abandon wind in robust Unit Combination model；
Scheme 2：It (can be optimized by the 60% of wind power plant capacity, i.e. wind power integration ratio by consumption completely in wind power
Example is considers to abandon wind under the premise of 15%), in robust Unit Combination model；
Scheme 3：It (cannot be optimized by the capacity of wind power plant, i.e. wind power integration ratio by consumption completely in wind power
Under the premise of 23%), do not consider to abandon wind in robust Unit Combination model；
Scheme 4：It (cannot be optimized by the capacity of wind power plant, i.e. wind power integration ratio by consumption completely in wind power
Consider to abandon wind under the premise of 23%), in robust Unit Combination model.
The scheduling result of 2 four kinds of schemes of table
By table 2 ("-" is indicated without solution in table 2) it is found that considering to abandon wind when wind power can be dissolved all, in model
With do not consider that the scheduling result for abandoning wind is the same；And when wind power cannot be dissolved all, if not considering to abandon wind
Model may be without feasible solution.Accordingly, it is considered to which the scheduling model for abandoning wind is more suitable for the electric power system dispatching of the wind-powered electricity generation containing high proportion.
In order to study the Optimized Operation results change under different wind-powered electricity generation ratios, keeping generating set total installation of generating capacity constant
The case where, it is continuously increased wind power integration capacity, optimum results are as shown in Figure 2.It can be seen from the figure that in wind power integration ratio
When less than 19%, since wind power can be dissolved all, so it is 0 to abandon wind punishment cost, while with wind electricity digestion quantitative change
Greatly, cost of electricity-generating tapers into.But when wind power integration ratio is 19%~33%, since wind power cannot be dissolved all,
Gradually increase so abandoning wind punishment cost；Increase afterwards in addition, cost of electricity-generating is first reduced, because wind power integration is forced and stopped after reaching saturation
The unit of better economy, causes cost of electricity-generating to increase.It can be seen that considering a few days ago excellent of wind power plant space time correlation constraint
Increase abandons wind punishment cost and promotes wind electricity digestion in change scheduling model, improves the wind electricity digestion capability of model.
In order to analyze row and constrain the validity of generating algorithm, generating algorithm and Benders will be arranged and constrained in conjunction with scene 1
Decomposition method is compared.Control parameter α values are 0.9 in calculating process, and the calculated performance of two kinds of algorithms is counted such as 3 institute of table
Show.As can be seen from the table, the scheduling totle drilling cost that two methods obtain is very close, but the calculating time of C＆CG algorithms is only
/ 6th of Benders decomposition algorithms, iterations decrease 192%.In addition, the further convergence of two kinds of algorithms of comparison
Curve, as shown in Figure 3, it can be seen that influenced by dual solution quality, the convergence process of Benders decomposition algorithms is relatively slowly simultaneously
It will appear some small oscillations, and the iterative convergent process for arranging and constraining generating algorithm is more rapid reliable.For this purpose, identical
In the case of solving precision, compared with Benders algorithms, generating algorithm is arranged and constrained due to can effectively feed back to examination in chief
Crucial constraint is inscribed to accelerate to restrain, therefore its computational efficiency higher.
The comparison of 3 three kinds of solutions of table
| Computational methods | Calculate time/(s) | Totle drilling cost/($) | Iterations |
| Benders decomposition methods | 420205 | 336000 | 1126201 |
| Row and constraint generating algorithm | 407000 | 320500 | 927505 |
For the influence of further analysis time smoothing effect and steric crowding.Assuming that control parameter α=0.9 is present
Two kinds of models are respectively adopted and carry out simulation analysis, model 1 considers time uncertain constraint, and model 2 does not consider that the time uncertain
Constraint (), other constraints all sames.The uncertain collection built under two kinds of models is as shown in Figure 4.It can be with from Fig. 4
Find out, it is contemplated that the uncertain collection interval width of time uncertain constraint does not know the width of constraint more than not accounting for the time
Narrow, uncertain section has obtained certain contraction.In addition, not accounting for the operation assembly of the model 2 of time uncertain constraint
This is 82070 $, and the operation totle drilling cost for considering the model 1 of time uncertain constraint is then 80671 $, is subtracted compared with model 2
1399 $ are lacked, therefore have considered that the model of time smoothing effect can efficiently reduce the conservative of the uncertain collection of robust, optimization effect
Fruit is more preferable.
Influence (set time constrained parameters for further analysis space constellation effect to model), it will be former
The wind power plant for carrying out access node 29 is divided into multiple small wind power plants, and the space cluster of wind power plant can be simulated by accessing different nodes
Effect (wind-powered electricity generation total capacity is constant).Specially：1. be divided into 2 wind power plants, then space constraint parameter2. being divided into 4
When wind power plant, then space constraint parameter3. be divided into 6 wind power plants, then space constraint parameter4. being divided into
When 8 wind power plants, then space constraint parameter5. be divided into 10 wind power plants, then space constraint parameter
From figure 5 it can be seen that with the increase of wind-powered electricity generation number, i.e. wind-powered electricity generation field distribution is wider, and space is uncertain to constrain stronger, robust
The totle drilling cost of Unit Combination also tapers into.For this purpose, considering that the model of steric crowding can more meticulously describe wind-powered electricity generation not
Certainty is more met the scheduling scheme of actual motion.
Claims (7)
1. a kind of Optimization Scheduling a few days ago considering the constraint of wind power plant space time correlation, which is characterized in that include the following steps：
1) the robust Unit Combination mathematical model for considering cost of electricity-generating and abandoning eolian is established；
2) for the steric crowding of wind-powered electricity generation and time smoothing effect, structure considers the uncertain of wind-powered electricity generation room and time constraint
Collection；
3) mathematical model is decomposed into Unit Combination primal problem, Security and feasibility examines subproblem and maximally utilizes wind-powered electricity generation
Problem establishes the coupled relation of boss's problem using arranging and constraining generating algorithm, and is solved to obtain Optimized Operation scheme.
2. a kind of Optimization Scheduling a few days ago considering the constraint of wind power plant space time correlation according to claim 1, feature
It is, in the step 1), considers that the object function of cost of electricity-generating and the robust Unit Combination mathematical model for abandoning eolian is：
Wherein, F is cost of electricity-generating and abandons the sum of wind punishment cost, suiFor the startup expense of system unit, sdiFor system unit
Idleness expense, zi,tAnd ui,tIt is 0/1 variable of first stage, to indicate the start and stop state transformation of unit i, if unit i exists
Period t becomes starting then z from shutting downi,t=1, otherwise zi,t=0, if unit i period t from run become shut down if ui,t=1,
Otherwise zi,t=0, fi,t(pi,t) be unit operating cost quadratic function, T is scheduling slot sum, and N is unit sum, and NW is
Wind power plant sum,For j-th of wind power plant t moment wind power output power,For j-th of wind power plant t moment most
Excellent scheduling is contributed, λjPenalty coefficient when wind is abandoned for j-th of wind power plant, subscript w indicates that wind-powered electricity generation, subscript b indicate normal condition；
Constraints includes：
A) minimum available machine time constraint：
Wherein,For the minimum available machine time of unit i,On the basis of under state operating statuses of the unit i in the t-1 periods become
Amount,On the basis of under state unit i in the operating status variable of t periods, yi,hFor unit i run/in idle time
Operating status variable, h be run/idle time；
B) minimum downtime constraint：
Wherein,For the minimum downtime of unit i；
C) the logical constraint of set state and state conversion：
D) system reserve constrains：
Wherein, pb,tFor the load at t period nodes b, r is spinning reserve rate, pi,maxFor the maximum output of unit i, ND is node
Sum；
E) unit output constrains：
Wherein, pi,maxAnd pi,minThe respectively minimum and maximum power generating value of unit i.
F) power-balance constraint：
Wherein,On the basis of outputs of the unit i in the t periods under state,On the basis of under state j-th of wind power plant in t moment
Optimal scheduling contribute；
G) unit ramp loss：
Wherein, RUiAnd RDiThe upper and lower climbing rate of respectively unit i.
H) transmission line of electricity capacity-constrained：
Wherein,Respectively node i, the power transfer factor of j, b to circuit l,For circuit maximum
Transmission capacity；
I) the units limits of wind power plant：
Wherein,It is wind power output power of j-th of wind power plant in t moment, W is not knowing for wind-powered electricity generation room and time constraint
Collection.
3. a kind of Optimization Scheduling a few days ago considering the constraint of wind power plant space time correlation according to claim 2, feature
It is, in the step 2), the uncertain collection W of wind-powered electricity generation room and time constraint is expressed as：
Wherein, wj,tExpectation for j-th of wind power plant in t moment is contributed, Δ wj,tFor the maximum of wind power output power and desired value
Departure,For 0/1 variable,For the space constraint parameter of wind power output power,For wind power output power when
Between constrained parameters.
4. a kind of Optimization Scheduling a few days ago considering the constraint of wind power plant space time correlation according to claim 2, feature
It is, in the step 3), Unit Combination primal problem is expressed as：
Wherein, η is the target function value of subproblem.
5. a kind of Optimization Scheduling a few days ago considering the constraint of wind power plant space time correlation according to claim 2, feature
It is, in the step 3), Security and feasibility examines subproblem to be expressed as max-min problems, i.e.,：
υ1,lt≥0
υ2t≥0
υ3t≥0
Wherein, ZCThe target function value of subproblem, υ are examined for Security and feasibility1,lt,υ2,lt,υ3,ltThe relaxation respectively introduced becomes
Amount,To consider the wind power output of wind-powered electricity generation uncertainty optimization,To consider the unit output of wind-powered electricity generation uncertainty optimization,
Subscript u indicates to consider the uncertain state of wind-powered electricity generation.
6. a kind of Optimization Scheduling a few days ago considering the constraint of wind power plant space time correlation according to claim 5, feature
It is, in the step 3), maximally utilizes wind-powered electricity generation subproblem and be expressed as：
Wherein, ZSThe object function of subproblem is maximally utilized for wind-powered electricity generation, constraints examines subproblem with Security and feasibility
Constraints is identical, but does not include slack variable.
7. a kind of Optimization Scheduling a few days ago considering the constraint of wind power plant space time correlation according to claim 1, feature
It is, in the step 3), is solved using C＆CG algorithms, specifically include following steps：
31) primal problem：Unit Combination primal problem is solved using mixed integer programming, obtains the operating status at each moment, unit goes out
The object function lower bound of power and second stage, and pass to next stage；
32) subproblem：The operating states of the units variable transmitted to Unit Combination primal problem optimizes and generates cut set, and generation is cut
Collection includes：
321) operating states of the units solved in Unit Combination primal problem is substituted into feasibility test subproblem, judges unit
Whether operating status meets the requirements under most severe scene, if the sum of slack variable is not 0, which is unsatisfactory for
It is required that generating C＆CG cuts and return primal problem, operating states of the units is adjusted, if being introduced in Security and feasibility check problem
The sum of slack variable be 0, then prove that problem is feasible, carry out the solution that wind-powered electricity generation maximally utilizes subproblem；
322) solution obtained in step 31) substitution wind-powered electricity generation is maximally utilized in subproblem, calculates its dual problem, obtains second
The upper bound of phase targets function obtains optimal solution when iteration convergence, otherwise generates C＆CG and cuts and return primal problem, to unit
Operating status is adjusted.
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