CN109584099A - The short-term multiple target generation schedule preparation method in the power station of peak load regulation network and system - Google Patents
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Abstract
The invention discloses a kind of short-term multiple target generation schedule preparation method in the power station of peak load regulation network and systems, firstly, the building short-term multiple target generation schedule compiling model of step power station；Power station way of economic operation is determined according to input condition；If dried particle is randomly generated in feas ible space, and the individual extreme value of each particle is determined based on the target function value of each particle, will be stored in external archive collection by ruleless some particles each other；The position and speed of each particle is updated to repair infeasible solution after random selection some particles carry out multinomial variation, calculate the target function value of each particle again；The individual extreme value of each particle is updated by the target function value of each particle calculated again；External archive set is updated according to the dominance relation of particle and crowding distance, if meeting preset termination condition, exports external archive collection, and then obtain global extremum.The present invention can effectively mitigate peak-load regulating pressure, improve power supply quality.Power grid being capable of safety and stability economical operation.
Description
Technical field
The invention belongs to water project operation field, more particularly, to a kind of power station more mesh in short term of responsive electricity grid peak regulation
Mark generation schedule preparation method and system.
Background technique
With the high speed development of China's power grid construction and the continuous expansion of power grid scale, electricity net safety stable economical operation
Demand is higher and higher, and the problem of electric system peak modulation capacity deficiency is increasingly prominent.Step power station Short Term Generation Schedules are worked out
The important component of basin step centralized control center water tune department belongs to the mode " with the fixed electricity of water ".It is usually total with step
Generated energy, power benefit are optimal or benefit of peak regulation is up to target, comprehensively consider short-term Runoff Forecast, power system load becomes
Change and power station unit maintenance plan, vibrating area etc. of contributing constrain, so that effective use and refinement medium-term schedule are distributed in a few days
Water volume that can be utilized.
Traditional general simple target for only considering generated energy or power benefit of generation schedule establishment, when needing responsive electricity grid
It also often has ignored generated energy only with remaining load maximum value minimum or the minimum objective function of variance when peak regulation demand and adjusts
Peak amount it is between the two make overall plans and coordinate relationship, lead to the generation for abandoning water peak regulation, be unfavorable for water resource and hydraulic power potentials
Effective use.And original multi-objective particle swarm algorithm easily falls into local optimum.
Summary of the invention
Aiming at the above defects or improvement requirements of the prior art, the present invention provides a kind of power station of peak load regulation network is short-term
Thus multiple target generation schedule preparation method and system solve existing power generation preparation method and have ignored both generated energy and peak regulation amount
Between make overall plans and coordinate relationship, lead to the technical problem for abandoning water peak regulation etc..
To achieve the above object, according to one aspect of the present invention, the power station for providing a kind of peak load regulation network is more in short term
Target generation schedule preparation method, comprising:
(1) lotus variance minimum and the short-term multiple target power generation meter of the maximum step power station of step total power generation more than power grid are established
Draw compiling model；
(2) way of economic operation for determining the step power station acquires the step on the basis of unit NHQ curve
The optimum dynamic characteristics in power station, and then obtain the power output of each unit, wherein the step power station way of economic operation packet
It includes with electric Ding Shui and with the fixed electric both of which of water；
(3) several particles are randomly generated in feas ible space, and each grain is determined based on the target function value of each particle
The individual extreme value of son will be stored in external archive collection by ruleless some particles each other then according to the dominance relation of particle
In；
(4) position and speed that each particle is updated by the individual extreme value of each particle, is then selected from all particles at random
After the particle progress multinomial variation for selecting preset ratio, the reparation of infeasible solution is carried out to particle after variation, calculates institute again
There is the target function value of particle；
(5) the individual extreme value that each particle is updated by the target function value of each particle recalculated, if new objective function
Value dominates updated individual extreme value, then with the new updated individual extreme value of target function value replacement；If new objective function
Value and updated individual extreme value insubjection each other, then individual extreme value is as new after randomly choosing fresh target functional value or updating
Individual extreme value；
(6) the external archive collection is updated according to the dominance relation of particle and crowding distance, is judged whether full
Sufficient preset termination condition exports the external archive collection if meeting the preset termination condition, concentrates from the external archive
Two solutions are randomly choosed, global extremum are obtained by comparing the crowding distance of two solutions of selection, using as optimal generation scheme
Drawing up a plan returns to step (4) if being unsatisfactory for the preset termination condition.
Preferably, lotus variance is minimum more than the power grid are as follows: byDetermine lotus more than the smallest power grid
Variance, wherein t is period serial number, number of segment when T is total, DtIndicate lotus more than t period power grid, D indicates being averaged for lotus more than power grid
It is worth, the variance of lotus more than F expression power grid.
Preferably, the step total power generation is maximum are as follows: byDetermine that maximum step always generates electricity
Amount, wherein i is power station serial number, and I is main switching station number, and E indicates step total power generation, Nt iIndicate the power output of the period power station t i, when
Segment length is Δ t, number of segment when T indicates total.
Preferably, the constraint condition of the short-term multiple target generation schedule compiling model of the step power station are as follows: last water level control
Restrict beam, restriction of water level, units limits, letdown flow constraint, water balance constraint, power output Climing constant and unit vibration area about
Beam.
It preferably, is when electricity is determined in a manner of water in the step power station way of economic operation, which comprises
According to plant load, unit dynamic characteristics, byIt is right
Optimum load dispatch scheme under all heads and power output combination successively solves, and obtains power station optimum load dispatch table, wherein K is unit serial number, and K indicates total unit number of units, and H indicates power generation net water head,AndThe total load under the conditions of k-1 platform and k platform unit is respectively indicated,Indicate that total load isNet water head is H situation
Under the optimal total consumption flow of each unit, Qk(Nk, H) and it be kth platform unit output is Nk, net water head be H when consumption flow,For boundary condition,Indicate that -1 unit of kth is in total loadIn the case of net water head is H
Consumption flow, NkFor the power output of kth platform unit.
Preferably, when the step power station way of economic operation is in a manner of the fixed electricity of water, which comprises
Power station net water head is calculated, anticipation power curve in power station is then looked into according to the net water head being calculated, obtains power station most
Big power output NmaxWith minimum load Nmin, and obtain power station maximum output and the corresponding generating flow Q of minimum loadmaxAnd Qmin；
Judge known letdown flow Q whether in QminWith QmaxBetween, if Q < Qmin, then final power output N=0 is set；If Q >
Qmax, then final power output N=N is setmax；
If known letdown flow Q is in QminWith QmaxBetween, then it sets current power output toAnd benefit
Total consumption flow Q' that water acquires the power station when contributing N' is determined to electricity；
If | final power output N=N' is arranged in Q-Q'|≤δ；If Q-Q'> δ, is arranged Nmin=N', and by newest determination
Minimum load determine current power output；If Q'-Q > δ, is arranged Nmax=N', and determined currently by the maximum output of newest determination
Power output, δ is preset threshold.
Preferably, in step (4), byUpdate grain
The speed of son, byThe position of more new particle, wherein w is inertia weight, C1And C2The acceleration being positive
Constant, r1And r2The equally distributed random number between [0,1],Indicate the individual extreme value of i-th of particle,For global pole
Value,Indicate the updated speed of particle,Indicate the speed before particle updates,WithIt respectively indicates
Particle updates forward and backward position.
It is another aspect of this invention to provide that a kind of short-term multiple target generation schedule establishment in the power station for providing peak load regulation network
System, comprising:
Model construction module, it is short for establishing lotus variance minimum and the maximum step power station of step total power generation more than power grid
Phase multiple target generation schedule compiling model；
First computing module, the optimal power for acquiring the step power station on the basis of unit NHQ curve are special
Property, and then the power output of each unit is obtained, and the step power station way of economic operation is determined according to input condition, wherein
The step power station way of economic operation includes with electric Ding Shui and with the fixed electric both of which of water；
Second computing module, for several particles, and the target letter based on each particle to be randomly generated in feas ible space
Numerical value determines the individual extreme value of each particle, then according to the dominance relation of particle, will protect ruleless some particles each other
There are external archive concentrations；
Third computing module updates the position and speed of each particle for the individual extreme value by each particle, then from institute
After thering is the particle for randomly choosing preset ratio in particle to carry out multinomial variation, infeasible solution is carried out to particle after variation and is repaired
It is multiple, the target function value of all particles is calculated again；
4th computing module, for updating the individual pole of each particle by the target function value by each particle recalculated
Value, if new target function value dominates updated individual extreme value, with the new updated individual pole of target function value replacement
Value；If new target function value and updated individual extreme value insubjection each other, fresh target functional value or more is randomly choosed
Individual extreme value is as new individual extreme value after new；
Execution module is judged, for carrying out more according to the dominance relation and crowding distance of particle to the external archive collection
Newly, judge whether to meet preset termination condition, if meeting the preset termination condition, the external archive collection is exported, from institute
It states external archive and concentrates two solutions of random selection, global extremum is obtained by comparing the crowding distance of two solutions of selection, to make
It returns if being unsatisfactory for the preset termination condition for optimal generation scheme drawing up a plan and executes the third computing module
Operation.
In general, through the invention it is contemplated above technical scheme is compared with the prior art, the present invention realizes stream
The Efficient Solution of the short-term multiple target generation schedule compiling model of domain step power station, can achieve the following beneficial effects:
(1) with traditional multi-objective Evolutionary Algorithm (Multi-objection evolutionary algorithm,
MOEA) different, the present invention does not need the process of fitness assignment, and corresponding simplification can be obtained in algorithm design.But due to existing simultaneously
Both multiple globally optimal solutions ruleless each other, the present invention concentrate two solutions of random selection from external archive, by comparing
Crowding distance obtain global extremum.In addition, algorithm falls into local optimum in order to prevent, the present invention is made a variation using multinomial to one
The particle of certainty ratio carries out mutation operation, realizes efficiently asking for the short-term multiple target generation schedule compiling model of basin step power station
Solution.
(2) present invention solves short-term multiple target generation schedule and works out problem, equally selects reservoir level for decision variable pair
Particle is encoded, and initial solution and correction of infeasible solution strategy is generated at random using " gallery " method, according to space optimal flux
Distribution method carries out single period the output calculation " with the fixed electricity of water ", and corrects the power output process for being unsatisfactory for Climing constant, has to engineering
Practical directive significance.
Detailed description of the invention
Fig. 1 is a kind of method flow schematic diagram provided in an embodiment of the present invention；
Qingjiang river cascade power output process and province net Yu Hejie when Fig. 2 is a kind of total power generation maximum provided in an embodiment of the present invention
Fruit figure；
The water level in Qingjiang river cascade power station and power output process when Fig. 3 is a kind of total power generation maximum provided in an embodiment of the present invention
Figure, wherein (a) is the water level and power output procedure chart in water cloth a strip of land between hills power station in Fig. 3, and (b) is the water level of rolling development and goes out in Fig. 3
Power procedure chart, (c) is the water level and power output procedure chart in Gaobazhou power station in Fig. 3.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.As long as in addition, technical characteristic involved in the various embodiments of the present invention described below
Not constituting a conflict with each other can be combined with each other.
The present invention is applied to consider as a whole the model of lotus variance minimum and maximum two targets of step total power generation more than power grid,
Peak-load regulating pressure can effectively be mitigated, improve power supply quality.Power grid being capable of safety and stability economical operation.Also, the present invention is effective
The deficiency that original multi-objective particle swarm algorithm easily falls into local optimum is improved, is improved while meeting peaking demand of power grid whole
The power benefit of a step hydropower station obtains the Pareto optimal solution set being evenly distributed, to formulate the ladder for taking into account peaking demand of power grid
Grade power station Short Term Generation Schedules establishment is offered reference and is referred to.
It is a kind of method flow schematic diagram provided in an embodiment of the present invention as shown in Figure 1, provided in an embodiment of the present invention one
The short-term multiple target generation schedule preparation method in power station of kind of peak load regulation network the following steps are included:
S1: determining model, plans as a whole to establish the step of lotus variance minimum and maximum two targets of step total power generation more than power grid
The short-term multiple target generation schedule compiling model in power station, specifically:
S1.1: model objective function；
S1.1.1: lotus variance is minimum more than power grid, and calculation formula is as follows:
Wherein, i is power station serial number, and i ∈ [1, I], I are main switching station number；T is period serial number, and t ∈ [1, T], T are main switching station
Number；CtAnd DtRespectively indicate t period network load and remaining lotus；Indicate the power output of power station i t period；And F is statistics
Value respectively indicates the average value and its variance of lotus more than power grid；
S1.1.2: step total power generation is maximum, and objective function may be expressed as:
Wherein, E indicates step total power generation；M indicates the unit number of units in i-th of power station；Indicate the period power station t i's
The power output of m platform unit, it is the unit generation flowWith productive headFunction；
S1.2: constraint condition
S1.2.1: last water level control constraint
Wherein,AndIt respectively indicates the actual water level of scheduling end of term power station i and controls last water level；
S1.2.2: restriction of water level
Wherein,WithThe water level and its bound of respectively i-th power station t moment, flood season level
The upper limit is flood season limit level；
S1.2.3: units limits
Wherein,Maximum, the minimum value that respectively i-th of power station t period contributes,Indicate power station i
The power output of t period；
S1.2.4: letdown flow constraint
Wherein,WithRespectively indicate the letdown flow and its bound of power station i t period；
S1.2.5: water balance constraint
Wherein,WithAt the beginning of respectively indicating the power station i t period, last storage capacity value；WithWhen respectively indicating power station i t
Section storage and under let out；Δ t is Period Length；
S1.2.6: power output Climing constant
Wherein, RiClimb power limit out for power station i mono- period,Indicate the power output of i-th of power station t-1 period,Indicate the power output of power station i t period；
S1.2.7: unit vibration area constraint
Wherein,WithThe respectively vibrating area bound of power station i m platform unit,Indicate t period electricity
Stand i m platform unit power output,Indicate the power output of power station i t period；
S2: space flow optimum distribution
The full factory's optimum dynamic characteristics in power station are acquired on the basis of unit NHQ curve and carry out output calculation, are subtracted as much as possible
Small error improves the precision of generation schedule establishment.According to the difference of input condition, Economic Operation in Hydropower Station mode has " fixed with electricity
Water " and " with the fixed electricity of water " both of which；
S2.1: " water is determined with electricity " mode
Known water plant load and unit dynamic characteristics are advised using the constraint of penalty function method processing unit vibrating area, dynamic
The method of drawing solves, and corresponding recurrence formula is as follows:
Wherein, k is unit serial number, k ∈ [1, K]；H indicates power generation net water head；Respectively indicate k-1 and k platform
Total load under the conditions of unit；Indicate that total load isThe optimal total consumption stream of each unit in the case of net water head is H
Amount；Qk(Nk, H) and it be kth platform unit output is Nk, net water head be H when consumption flow；For boundary condition,Indicate that -1 unit of kth is in total loadNet water head is the consumption flow in the case of H, NkFor kth platform machine
The power output of group, K indicate total unit number of units；
The optimum load dispatch scheme under all head H and power output N combination is successively solved according to step S2.1, obtains electricity
It stands optimum load dispatch table, carries out table look-at when " determine water with electricity " calculating；
S2.2: " with the fixed electricity of water " mode
When " with the fixed electricity of water " calculates, lookup need to be iterated to known consumption flow in conjunction with binary search, specific steps are such as
Under:
S2.2.1: calculating power station net water head, and anticipation power curve in power station is looked under given head, obtains power station maximum output
NmaxWith minimum load Nmin, and by checking in its corresponding generating flow QmaxAnd Qmin；
S2.2.2: judge known letdown flow Q whether in QminWith QmaxBetween, if Q < Qmin, then final power output N=is set
0, go to step S2.2.5；If Q > Qmax, then final power output N=N is setmax, go to step S2.2.5；Otherwise step is gone to
S2.2.3 carries out binary search；
S2.2.3: it enables" determining water with electricity " module is utilized to acquire total consumption in power station in the case of the power output
Flow Q'；
S2.2.4: if | Q-Q'|≤δ is arranged final power output N=N', goes to step S2.2.5；If Q-Q'> δ, explanation
N' is less than normal, and N is arrangedmin=N' goes to step S2.2.3 and continues iteration；If Q'-Q > δ, illustrates that N' is bigger than normal, N is setmax=N' turns
Continue iteration to step S2.2.3；
S2.2.5: iteration terminates, and exports final power output N；
Wherein, δ is preset threshold, can be determine according to actual needs.
S3: initialization population
A particle is randomly generated in feas ible space, initializes its speed；Calculate the target function value of each particle；
In embodiments of the present invention, the feasible solution of each optimization problem is known as " particle ", all by optimization problem can
The set of row solution is used as " feas ible space ".
S4: the determination of extreme value
Determine the initial individuals extreme value of each particle, i.e., the initial position of each particle itself；
S5: it is obtained dominating particle according to relationship
According to the dominance relation of particle, ruleless some particles each other are obtained, and are stored in external archive collection NP；
S6: particle position and speed are updated
ByAndIt updates every
A particle position and speed；
Wherein, w is inertia weight；C1、C2The aceleration pulse being positive；r1、r2The equally distributed random number between [0,1],Indicate the individual extreme value of i-th of particle；For global extremum；Indicate the updated speed of particle,Indicate grain
Speed before son update,WithIt respectively indicates particle and updates forward and backward position；
S7: it makes a variation
The particle of preset ratio is randomly choosed, multinomial variation is carried out；
In embodiments of the present invention, preset ratio can determine according to actual needs, and the embodiment of the present invention is preferably 15%.
S8: calculating target function value
Infeasible solution is repaired using correcting strategy, calculates the target function value of all particles again；
S9: it is obtained dominating particle according to relationship
Itself desired positions p of more new particlebestIf new explanation dominates pbest, then it is replaced；If new explanation and pbestEach other
Insubjection then randomly chooses a solution as new pbest；
S10: updating and maintenance
NP is updated and is safeguarded according to the dominance relation of particle and crowding distance；
S11: judge whether to terminate
Judge whether to meet termination condition, if satisfied, output external archive collection NP；Otherwise, it goes to step S6 and continues iteration.
(Qingjiang river cascade power station) with reference to the accompanying drawings and embodiments, it is winged to a kind of limitation particle provided in an embodiment of the present invention
The improvement multi-objective particle swarm algorithm SMPSO of scanning frequency degree is described in detail.
The actual operating mode for choosing one day in 2014 Hubei Province's net and Qingjiang river cascade, using SMPSO algorithm to short-term more
Target generation schedule compiling model is solved.This day 242.18 ten thousand kW of Hubei Province's net load peak-valley difference, variance 5506.10；Clearly
The whole story water level in river step water cloth a strip of land between hills power station is respectively 381.23m and 381.17m, and the whole story water level of rolling development is respectively
The whole story water level of 193.62m and 193.56m, Gaobazhou power station are respectively 78.75m and 78.67m.The power output of each power station unit is shaken
Dynamic area is shown in Table 3, in addition, the single period power output Climing constant in setting power station is the maximum output of single unit.
SMPSO algorithm parameter is provided that aceleration pulse C1, C2∈[1.5,2.5]；Inertia weight ω=0.1；Multinomial
Mutation parameter pm=1/K, wherein K is variable number, η=20；Population and the scale of external archive collection are all 100；Iteration time
2000 generation of number.As a comparison, simultaneous selection OMOPSO algorithm is calculated, corresponding parameter setting are as follows: aceleration pulse C1, C2
∈[1.5,2.0]；Inertia weight ω ∈ [0.1,0.5]；Uniformly variation and non-uniform mutation Probability pm=1/K, wherein K is to become
Measure number；Population scale and the number of iterations are identical as SMPSO algorithm.Using day as dispatching cycle (24 periods), the Qingjian River is carried out
The non-abandoning water phase multiple target generation schedule in step hydropower station works out simulation calculation, obtains the forward position Pareto and optimal solution set distribution such as
Shown in table 4, in embodiments of the present invention, 50 equally distributed non-domination solutions are listed.
Using day as dispatching cycle (24 periods), it is imitative to carry out the non-abandoning water phase multiple target generation schedule establishment in Qingjiang river cascade power station
True simulation calculates, and obtains the forward position Pareto and optimal solution set distribution is as shown in table 1.
The Pareto optimal solution set distribution of 1 Qingjiang river cascade multiple target Short Term Generation Schedules of table establishment
2 Qingjiang river cascade multiple target generation schedule of table works out the comparison of result index
3 Qingjiang river cascade power station characteristic parameter table of table
The Pareto optimal solution set distribution of 4 Qingjiang river cascade multiple target Short Term Generation Schedules of table establishment
The index that province nets under remaining lotus variance minimum and the maximum two kinds of extreme versions of step total power generation is listed in table 2 to compare
As a result.Thus table is reduced to 990.12 from original 5506.10 as it can be seen that remaining lotus variance is netted by 1 province of scheme, decreases by 82.0%；Peak
242.18 ten thousand kWs of the paddy difference by are reduced to 130.97 ten thousand kW, accordingly reduce by 45.9%, benefit of peak regulation is significant.Pass through Qingjian River ladder
The adjusting in grade power station saves lotus more than netting and tends to be steady, and the Peak Load Adjustment of water power is given full play to.And Yu Hefang nets in 50 province of scheme
Difference is 2450.63, the range of decrease 55.5%；Peak-valley difference is 174.07 ten thousand kW, accordingly reduces by 28.1%, and Fig. 2 is shown in corresponding amplitude variation, has
Certain peak regulation effect, but there are still Yu He fluctuation the case where.The step total power generation of scheme 1 is 2315.584 ten thousand kWh, scheme
50 be 2395.551 ten thousand kWh, improve 3.5% than scheme 1, this be lose benefit of peak regulation bring as a result, further proof
The relationship that power benefit and benefit of peak regulation mutually restrict.
By each power station water level of 50 Qingjiang river cascade of Fig. 3 scheme and power output process it is found that the water level in each power station scheduling end of term all reaches
Given last water level is arrived, water level process variation is steady, meets day and the constraint of hour luffing.Each power station of network load low ebb is by minimum
Under let out corresponding power output power generation, when load peak, increases power output operation to meet peak regulation demand, and calculated result is rationally effective.Practical hair
In electric planning procedure, two targets of choosing comprehensively benefit of peak regulation and power benefit are also needed, are concentrated from Pareto non-domination solution
Select last solution.
As it will be easily appreciated by one skilled in the art that the foregoing is merely illustrative of the preferred embodiments of the present invention, not to
The limitation present invention, any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should all include
Within protection scope of the present invention.
Claims (8)
1. a kind of short-term multiple target generation schedule preparation method in the power station of peak load regulation network characterized by comprising
(1) lotus variance minimum and the short-term multiple target generation schedule of the maximum step power station of step total power generation more than power grid is established to compile
Simulation；
(2) way of economic operation for determining the step power station acquires the cascade hydropower on the basis of unit NHQ curve
Optimum dynamic characteristics stood, and then obtain the power output of each unit, wherein the step power station way of economic operation include with
Electric Ding Shui and with the fixed electric both of which of water；
(3) several particles are randomly generated in feas ible space, and each particle is determined based on the target function value of each particle
Individual extreme value will be stored in external archive concentration by ruleless some particles each other then according to the dominance relation of particle；
(4) position and speed of each particle is updated by the individual extreme value of each particle, is then randomly choosed from all particles pre-
If after the particle of ratio carries out multinomial variation, the reparation of infeasible solution being carried out to particle after variation, calculates all grains again
The target function value of son；
(5) the individual extreme value of each particle is updated by the target function value of each particle recalculated, if new target function value branch
With updated individual extreme value, then with the new updated individual extreme value of target function value replacement；If new target function value with
Updated individual extreme value insubjection each other, then individual extreme value is as new after randomly choosing fresh target functional value or updating
Body extreme value；
(6) the external archive collection is updated according to the dominance relation of particle and crowding distance, judges whether to meet pre-
If termination condition, if meeting the preset termination condition, the external archive collection is exported, is concentrated from the external archive random
Two solutions are selected, global extremum are obtained by comparing the crowding distance of two solutions of selection, to work out as optimal generation scheme
Scheme returns to step (4) if being unsatisfactory for the preset termination condition.
2. the method according to claim 1, wherein lotus variance is minimum more than the power grid are as follows: byDetermine lotus variance more than the smallest power grid, wherein t is period serial number, number of segment when T is total, DtIt indicates
Lotus more than t period power grid,Indicate power grid more than lotus average value, F indicate power grid more than lotus variance.
3. method according to claim 1 or 2, which is characterized in that the step total power generation is maximum are as follows: byDetermine maximum step total power generation, wherein i is power station serial number, and I is main switching station number, and E indicates ladder
Grade total power generation,Indicate the power output of the period power station t i, Period Length is Δ t, number of segment when T indicates total.
4. according to the method described in claim 3, it is characterized in that, the short-term multiple target generation schedule establishment of the step power station
The constraint condition of model are as follows: last water level control constraint, restriction of water level, units limits, letdown flow constraint, water balance constraint,
Power output Climing constant and the constraint of unit vibration area.
5. according to the method described in claim 4, it is characterized in that, being fixed with electricity in the step power station way of economic operation
When water mode, which comprises
According to plant load, unit dynamic characteristics, byTo all water
Optimum load dispatch scheme under head and power output combination successively solves, and obtains power station optimum load dispatch table, whereinK is unit serial number, and K indicates total unit number of units, and H indicates power generation net water head,
AndThe total load under the conditions of k-1 platform and k platform unit is respectively indicated,Indicate that total load isNet water head is H
In the case of the optimal total consumption flow of each unit, Qk(Nk, H) and it be kth platform unit output is Nk, net water head be H when consumption flow,For boundary condition,Indicate that -1 unit of kth is in total loadIn the case of net water head is H
Consumption flow, NkFor the power output of kth platform unit.
6. according to the method described in claim 4, it is characterized in that, being fixed with water in the step power station way of economic operation
When electric mode, which comprises
Power station net water head is calculated, anticipation power curve in power station is then looked into according to the net water head being calculated, power station maximum is obtained and goes out
Power NmaxWith minimum load Nmin, and obtain power station maximum output and the corresponding generating flow Q of minimum loadmaxAnd Qmin；
Judge known letdown flow Q whether in QminWith QmaxBetween, if Q < Qmin, then final power output N=0 is set；If Q > Qmax,
The then final power output N=N of settingmax；
If known letdown flow Q is in QminWith QmaxBetween, then it sets current power output toAnd utilize with
Electricity determines total consumption flow Q' that water acquires the power station when contributing N'；
If | final power output N=N' is arranged in Q-Q'|≤δ；If Q-Q'> δ, is arranged Nmin=N', and most by newest determination
Small power output determines current power output；If Q'-Q > δ, is arranged Nmax=N', and determine currently to go out by the maximum output of newest determination
Power, δ are preset threshold.
7. method according to claim 5 or 6, which is characterized in that in step (4), byThe speed of more new particle, byMore
The position of new particle, wherein w is inertia weight, C1And C2The aceleration pulse being positive, r1And r2It is equally distributed between [0,1]
Random number,Indicate the individual extreme value of i-th of particle,
For global extremum,Indicate the updated speed of particle,Indicate the speed before particle updates,WithIt respectively indicates particle and updates forward and backward position.
8. a kind of short-term multiple target generation schedule workout system in the power station of peak load regulation network characterized by comprising
Model construction module is more in short term for establishing lotus variance minimum and the maximum step power station of step total power generation more than power grid
Target generation schedule compiling model；
First computing module, for acquiring the optimum dynamic characteristics of the step power station on the basis of unit NHQ curve, into
And the power output of each unit is obtained, and the step power station way of economic operation is determined according to input condition, wherein the ladder
Grade Economic Operation in Hydropower Station mode includes with electric Ding Shui and with the fixed electric both of which of water；
Second computing module, for several particles, and the target function value based on each particle to be randomly generated in feas ible space
It determines the individual extreme value of each particle, then according to the dominance relation of particle, ruleless some particles will be stored in each other
External archive is concentrated；
Third computing module updates the position and speed of each particle for the individual extreme value by each particle, then from all grains
After the particle progress multinomial variation for randomly choosing preset ratio in son, the reparation of infeasible solution is carried out to particle after variation,
The target function value of all particles is calculated again；
4th computing module, for updating the individual extreme value of each particle by the target function value by each particle recalculated, if
New target function value dominates updated individual extreme value, then with the new updated individual extreme value of target function value replacement；If
New target function value and updated individual extreme value insubjection each other, then it is a after randomly choosing fresh target functional value or updating
Body extreme value is as new individual extreme value；
Judge execution module, for being updated according to the dominance relation and crowding distance of particle to the external archive collection,
Judge whether to meet preset termination condition, if meeting the preset termination condition, export the external archive collection, outside described
Two solutions are randomly choosed in portion's archive set, global extremum are obtained by comparing the crowding distance of two solutions of selection, as most
Excellent generation schedule drawing up a plan returns to the operation for executing the third computing module if being unsatisfactory for the preset termination condition.
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