CN109617135A - Hybrid power system power scheduling Multiobjective Decision Making Method - Google Patents
Hybrid power system power scheduling Multiobjective Decision Making Method Download PDFInfo
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- CN109617135A CN109617135A CN201811600246.7A CN201811600246A CN109617135A CN 109617135 A CN109617135 A CN 109617135A CN 201811600246 A CN201811600246 A CN 201811600246A CN 109617135 A CN109617135 A CN 109617135A
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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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- 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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Abstract
The present invention relates to power scheduling technical fields, the problem of solving blended electric power scheduling complexity, policymaker is caused to be difficult to decision.Technical solution is summarized are as follows: passes through multiobjective decision-making form, the object module for the power generation type that decision model is included is established respectively, the corresponding object module of various power generation types parameter objectives to be achieved are set, and all power generation types that Comprehensive Model is included, establish the aims of systems model of hybrid power system, and system parameter objectives to be achieved are set, according to the object module of the object module of above-mentioned various power generation types and electricity generation system, form the world model of power scheduling, the parameter input model being related in world model is calculated, to meet the scheduling that the scheme of model needs carries out blended electric power.Beneficial effect is: policymaker need to only calculate the parameter input model of needs, so that being more easier when being scheduled to blended electric power.The present invention is especially suitable for hybrid power systems.
Description
Technical field
The present invention relates to power scheduling technical fields, in particular to the power scheduling technology of hybrid power system.
Background technique
Thermoelectricity undertakes most basic load as traditional energy form, high reliablity, but coal burning process releases greatly
Measure air pollutants, cause grave danger to environment, the prior art introduces water power, wind-powered electricity generation etc. in electricity generation system, formation with wind,
The combined generating system that water, ignition source integrate two-by-two or the above three integrates.But water power and wind-powered electricity generation are big by effect of natural conditions, by
In factors such as geographical location, weather conditions, the fluctuation of wind power plant season mean wind speed is larger, due to condition of raining, storage capacity limitation etc.
Factor, water in Various Seasonal is carried out in power station, and there is also differences.Wind-powered electricity generation, water power significantly increase the strong dependency of natural conditions
Energy mix systematic electricity scheduling complexity, policymaker is difficult to decision when blended electric power being caused to be dispatched.
Summary of the invention
The present invention is to solve the problem of that blended electric power scheduling complexity causes policymaker to be difficult to decision, provides a kind of mixing hair
Electric system power scheduling Multiobjective Decision Making Method.
To solve the above problems, the technical solution adopted by the present invention is that: hybrid power system power scheduling multiobjective decision-making
Method, comprising:
Decision model is established, the decision model includes thermal power plant's object module, power station object module and wind power plant mesh
Mark at least two and electricity generation system object module in model；
Thermal power plant's object module are as follows: in current dispatching cycle, thermal power plant's carbon emission amount is less than or equal to preset
With reference to α times of moderate heat power plant carbon emission amount dispatching cycle；
The power station object module are as follows: in current dispatching cycle, hydroelectric station surplus water is less than or equal to preset ginseng
β times for examining hydroelectric station surplus water in dispatching cycle；
The wind power plant object module are as follows: in current dispatching cycle, wind power plant wind power utilization is greater than or equal to λ；
The electricity generation system object module are as follows: in current dispatching cycle, corresponding all hairs that decision model is included
The difference of demand electricity consumption is less than or equal to δ in the gross capability of electric type and the dispatching cycle；
The input of design parameter data needed for decision model decision model is calculated, if all calculated results are all divided
Do not meet corresponding condition in decision model, then this can be inputted the corresponding electric power of design parameter data in decision model
Otherwise this cannot be inputted the design parameter data in decision model by the result of decision of the scheduling scheme as current dispatching cycle
The result of decision of the corresponding power scheduling scheme as current dispatching cycle；
Wherein, 0,0 < λ < 1 of α > 0, β >, δ >=0.
As advanced optimizing, multiple wind speed scenes are arranged according to the difference of wind speed, and/or set according to the difference for carrying out water
Set it is multiple come water scene, divided into each wind speed scene and set corresponding λ and α value, or carried out water scene at each and divide into
Corresponding β and α value is set, or corresponding λ, β are set under the combine scenes that each wind speed scene carrys out water scene with each
With α value.
As advanced optimizing, thermal power plant's object module is used:
Wherein, i is i-th of thermal power plant, and I is thermal power plant's sum, and j is j-th of fired power generating unit of Present Thermal Power factory, and J is to work as
The fired power generating unit sum of preceding thermal power plant, t are t-th of unit time, and T is the unit time sum of current dispatching cycle, SijIt is i-th
The carbon emission coefficient of j-th of fired power generating unit burning coal of a thermal power plant, xijtJ-th of fired power generating unit for i-th of thermal power plant exists
Coal-fired weight in t-th of unit time, IijtFor i-th of thermal power plant j-th of fired power generating unit within t-th of unit time
On-off state, open state and off-mode indicate that CE is with reference to the thermoelectricity in dispatching cycle with number 1 and number 0 respectively
Factory's carbon emission amount, i, j, t, I, J and T are positive integer.
As advanced optimizing, thermal power plant's object module further includes thermal power plant's constraint, and thermal power plant's constraint includes:
The constraint of coal available quantity:
Climing constant:
Fired power generating unit units limits: Pij-min≤Tijxijt≤Pij-max；
The constraint of fired power generating unit on-off state:
Wherein,For the maximum coal amount that i-th of thermal power plant in current dispatching cycle is able to use, TijIt is i-th
The coal electricity conversion coefficient of j-th of fired power generating unit of thermal power plant,For i-th of thermal power plant j-th of fired power generating unit in t
Variable quantity of the climbing rate upper limit and the fired power generating unit of a unit time between the climbing rate upper limit of the t-1 unit time,For i-th of thermal power plant j-th of fired power generating unit t-th of unit time climbing rate lower limit and the fired power generating unit
Variable quantity between the climbing rate lower limit of the t-1 unit time, Pij-minJ-th of fired power generating unit for i-th of thermal power plant exists
Minimum load in unit time, Pij-maxFor maximum output of j-th of fired power generating unit within the unit time of i-th of thermal power plant,
Tijt,onFor line duration of j-th of fired power generating unit within t-th of unit time of i-th of thermal power plant, Tij,upFor i-th of thermoelectricity
Minimum line duration of j-th of the fired power generating unit of factory within the unit time, Tijt,offFor j-th of thermal motor of i-th of thermal power plant
Offline time of the group within t-th of unit time, Tij,downFor i-th of thermal power plant j-th of fired power generating unit within the unit time
Minimum offline time.
As advanced optimizing, the power station object module is used:
Wherein, m is m-th of power station, and M is power station sum, and n is n-th of Hydropower Unit of hydropower station at present, and N is to work as
The Hydropower Unit sum in preceding power station, t are t-th of unit time, and T is the unit time sum of current dispatching cycle, Qmax,mFor
M-th of power station can be used for the maximum amount of water to generate electricity, y in current dispatching cyclemntFor n-th of hydroelectric machine in m-th of power station
Water flow of the group within t-th of unit time, gmntFor m-th of power station n-th of Hydropower Unit within t-th of unit time
On-off state, open state and off-mode indicate that Δ t is the unit time with number 1 and number 0 respectively, and CD is reference
Hydroelectric station surplus water in dispatching cycle, m, n, t, M, N and T are positive integer.
As advanced optimizing, the power station object module further includes power station constraint, and the power station constraint includes:
Water volume that can be utilized constraint:
Hydropower Unit water flow constraint: Qmin-mn≤ymnt≤Qmax-mn；
The constraint of reservoir dynamic water:
Wherein, Qmin,mIt can be used for the least quantity to generate electricity, Q in current dispatching cycle for m-th of power stationmin-mnFor m
The minimum water flow that n-th of Hydropower Unit in a power station allows, Qmax-mnAllow for n-th of Hydropower Unit in m-th of power station
Maximum flow of water amount, AmtFor moisture storage capacity of the corresponding reservoir in m-th of power station at the end of t-th of unit time, qmtFor m
Water intake velocity of the corresponding reservoir in a power station within t-th of unit time, AmcIt is the corresponding reservoir in m-th of power station current
Moisture storage capacity when dispatching cycle originates.
As advanced optimizing, the wind power plant object module is used:
Wherein, k is k-th of wind power plant, and K is wind power plant sum, and t is t-th of unit time, and T is current dispatching cycle
Unit time sum, SkFor the template Wind turbines quantity of k-th of wind power plant, ZktIt is k-th of wind power plant t-th of unit time
The conventional Wind turbines quantity of interior operation, LkFor the conventional Wind turbines quantity of k-th of wind power plant, Ptur,ktFor k-th of wind power plant
Wind turbines power curve, k, K, t and T are positive integer.
As advanced optimizing, the wind power plant object module further includes wind power plant constraint, and the wind power plant constraint includes:
The constraint of Wind turbines power curve:
Wind turbines number constraint: Zkt≤Lk；
Wherein, vktFor wind speed of k-th of wind power plant within t-th of unit time, Vin,kFor the wind turbine of k-th of wind power plant
The incision wind speed of group, Vrated,kFor the rated wind speed of the Wind turbines of k-th of wind power plant, Vout,kFor the wind-powered electricity generation of k-th of wind power plant
The cut-out wind speed of unit, Prated,kFor the rated power of the Wind turbines of k-th of wind power plant.
As advanced optimizing, the electricity generation system object module is used:
When decision model includes thermal power plant's object module and power station object module, the electricity generation system object module is adopted
With:
When decision model includes thermal power plant's object module and wind power plant object module, the electricity generation system object module is adopted
With:
When decision model includes power station object module and wind power plant object module, the electricity generation system object module is adopted
With:
When decision model includes thermal power plant's object module, power station object module and wind power plant object module, the hair
Electric system object module uses:
Wherein, PctThe power output for being thermal power plant within the unit time, PhtThe power output for being power station within the unit time, PwtFor
Power output of the wind power plant within the unit time, PdtFor demand electricity consumption in the unit time, t and T are positive integer.
As advanced optimizing, the electricity generation system object module further includes the constraint of system spinning reserve, the system rotation
Turn Reserve Constraint use:
Wherein,The maximum output for being thermal power plant within the unit time,It is thermal power plant within the unit time
Minimum load,The maximum output for being power station within the unit time,The minimum for being power station within the unit time
Power output, a% are preset system spinning reserve rate.
Beneficial effect is: the present invention establishes the power generation type that decision model is included by multiobjective decision-making form respectively
Object module, the corresponding object module of various power generation types parameter objectives to be achieved, and Comprehensive Model institute are set
All power generation types for including, establish the aims of systems model of hybrid power system, and system parameter mesh to be achieved is arranged
Mark, according to the object module of the object module of above-mentioned various power generation types and electricity generation system, forms the global mould of power scheduling
Type, i.e. decision model, in blended electric power scheduling, by the respective detailed parameters data of current dispatching cycle input decision model into
Row calculates, as long as all calculated results meet corresponding condition in decision model respectively, this time calculates used specific ginseng
The corresponding scheduling scheme of number data can be as the power scheduling scheme of current dispatching cycle, and then can calculate the scheduling
The power output etc. of various power generation types under scheme, realizes the scheduling of blended electric power, and policymaker only need to be by the parameter input model of needs
It is calculated, so that being more easier when being scheduled to blended electric power.
Specific embodiment
Below with reference to embodiment, technical solution of the present invention is further illustrated.
The technical scheme is that
Hybrid power system power scheduling Multiobjective Decision Making Method, comprising:
Decision model is established, the decision model includes thermal power plant's object module, power station object module and wind power plant mesh
Mark at least two and electricity generation system object module in model；
Thermal power plant's object module are as follows: in current dispatching cycle, thermal power plant's carbon emission amount is less than or equal to preset
With reference to α times of moderate heat power plant carbon emission amount dispatching cycle；
The power station object module are as follows: in current dispatching cycle, hydroelectric station surplus water is less than or equal to preset ginseng
β times for examining hydroelectric station surplus water in dispatching cycle；
The wind power plant object module are as follows: in current dispatching cycle, wind power plant wind power utilization is greater than or equal to λ；
The electricity generation system object module are as follows: in current dispatching cycle, corresponding all hairs that decision model is included
The difference of demand electricity consumption is less than or equal to δ in the gross capability of electric type and the dispatching cycle；
The input of design parameter data needed for decision model decision model is calculated, if all calculated results are all divided
Do not meet corresponding condition in decision model, then this can be inputted the corresponding electric power of design parameter data in decision model
Otherwise this cannot be inputted the design parameter data in decision model by the result of decision of the scheduling scheme as current dispatching cycle
The result of decision of the corresponding power scheduling scheme as current dispatching cycle；
Wherein, 0,0 < λ < 1 of α > 0, β >, δ >=0.
The above method establishes the target mould for the power generation type that decision model is included by multiobjective decision-making form respectively
The corresponding object module of various power generation types parameter objectives to be achieved, and the institute that Comprehensive Model is included is arranged in type
There is power generation type, establish the aims of systems model of hybrid power system, and system parameter objectives to be achieved are set, according to upper
The object module of various power generation types and the object module of electricity generation system are stated, the world model of power scheduling, i.e. decision are formd
Model calculates the respective detailed parameters data input decision model of current dispatching cycle, only in blended electric power scheduling
Will all calculated results meet corresponding condition in decision model respectively, then this time calculate used in design parameter data it is corresponding
Scheduling scheme can be as the power scheduling scheme of current dispatching cycle, and then calculate various power generations under the scheduling scheme
The power output etc. of type, realizes the scheduling of blended electric power.
As advanced optimizing, multiple wind speed scenes are arranged according to the difference of wind speed, and/or set according to the difference for carrying out water
Set it is multiple come water scene, divided into each wind speed scene and set corresponding λ and α value, or carried out water scene at each and divide into
Corresponding β and α value is set, or corresponding λ, β are set under the combine scenes that each wind speed scene carrys out water scene with each
With α value.
In above-mentioned decision model, thermal power plant's object module is using carbon emission amount as target, the carbon emission amount of current dispatching cycle
Based on the carbon emission amount with reference to dispatching cycle, need to keep carbon emission amount as small as possible, power station object module is to abandon water
For target, the abandoning water of current dispatching cycle needs to keep abandoning water as small as possible based on the abandoning water with reference to dispatching cycle,
Using wind power utilization as target, the wind power utilization that setting current dispatching cycle need to reach needs to make wind wind power plant object module
Electric utilization rate is as big as possible, and electricity generation system object module is using the difference of the gross capability of various power generation types and demand electricity consumption as mesh
Mark balances supply and demand as far as possible by the way that the threshold value of difference is arranged.Wherein α, β and λ are by policymaker according to the use of current dispatching cycle
The comprehensive determinations such as electricity is planned, carbon arranges limit, water volume that can be utilized, carrys out landscape condition；Selection for reference dispatching cycle is to going through in the recent period
The use of history data, empirical data can then select yesterday for example, policymaker will carry out the schedule of today as with reference to scheduling
Period.
The above method is further optimized, specifically may is that
Thermal power plant's object module can use:
Wherein, i is i-th of thermal power plant, and I is thermal power plant's sum, and j is j-th of fired power generating unit of Present Thermal Power factory, and J is to work as
The fired power generating unit sum of preceding thermal power plant, t are t-th of unit time, and T is the unit time sum of current dispatching cycle, SijIt is i-th
The carbon emission coefficient of j-th of fired power generating unit burning coal of a thermal power plant, xijtJ-th of fired power generating unit for i-th of thermal power plant exists
Coal-fired weight in t-th of unit time, IijtFor i-th of thermal power plant j-th of fired power generating unit within t-th of unit time
On-off state, open state and off-mode indicate that CE is with reference to the thermoelectricity in dispatching cycle with number 1 and number 0 respectively
Factory's carbon emission amount, i, j, t, I, J and T are positive integer.By above-mentioned thermal power plant's object module, current scheduling week can be calculated
The total carbon emissions amount of all fired power generating units of all thermal power plants, then compares with the reference cycle in phase, to meet carbon emission
The sets requirement of amount.
It, may be due to the influence of shortage, the human factor of historical data etc., fired power generating unit in above-mentioned thermal power plant's object module
Carbon emission coefficient be not directly available, at this time by investigating experienced engineer, worker, which can be consolidated
It is scheduled on a relatively small range.The carbon emission coefficient S of j-th of fired power generating unit burning coal of i-th of thermal power plantijCalculating
Mode can use:Wherein,It is i-th
The carbon emission amount coefficient Trapezoid Fuzzy Number of j-th of fired power generating unit of a thermal power plant,
rij1For the carbon emission coefficient minimum value of j-th of fired power generating unit burning coal of i-th of thermal power plant, rij4For i-th thermal power plant
The carbon emission coefficient maximum value of j-th of fired power generating unit burning coal, rij2And rij3For j-th of fired power generating unit of i-th of thermal power plant
The carbon emission coefficient of burning coal is in rij1With rij4Between value, rij1< rij2< rij3< rij4, rij1、rij2、rij3 and rij4
The parameter as investigated,For preset attitude parameter,
Above-mentioned thermal power plant's object module can also include that thermal power plant constrains, and thermal power plant's constraint may include:
The constraint of coal available quantity:
Climing constant:
Fired power generating unit units limits: Pij-min≤Tijxijt≤Pij-max；
The constraint of fired power generating unit on-off state:
Wherein,For the maximum coal amount that i-th of thermal power plant in current dispatching cycle is able to use, TijIt is i-th
The coal electricity conversion coefficient of j-th of fired power generating unit of thermal power plant,For i-th of thermal power plant j-th of fired power generating unit in t
Variable quantity of the climbing rate upper limit and the fired power generating unit of a unit time between the climbing rate upper limit of the t-1 unit time,Exist for j-th of fired power generating unit of i-th of thermal power plant in the climbing rate lower limit of t-th of unit time and the fired power generating unit
Variable quantity between the climbing rate lower limit of the t-1 unit time, Pij-minFor i-th of thermal power plant j-th of fired power generating unit in list
Minimum load in the time of position, Pij-maxFor maximum output of j-th of fired power generating unit within the unit time of i-th of thermal power plant,
Tijt,onFor line duration of j-th of fired power generating unit within t-th of unit time of i-th of thermal power plant, Tij,upFor i-th of thermoelectricity
Minimum line duration of j-th of the fired power generating unit of factory within the unit time, Tijt,offFor j-th of thermal motor of i-th of thermal power plant
Offline time of the group within t-th of unit time, Tij,downFor i-th of thermal power plant j-th of fired power generating unit within the unit time
Minimum offline time.After adding above-mentioned constraint condition in a model, calculated result can be made more to tally with the actual situation, calculate knot
Fruit is more accurate.
It, may be due to the influence of shortage, the human factor of historical data etc., the coal of fired power generating unit in above-mentioned thermal power plant's constraint
Electric conversion coefficient is not directly available, and at this time by investigating experienced engineer, worker, can be fixed the parameter
In a relatively small range.The coal electricity conversion coefficient T of j-th of fired power generating unit burning coal of i-th of thermal power plantijCalculating
Mode can use:Wherein,It is i-th
The coal electricity conversion coefficient Trapezoid Fuzzy Number of j-th of fired power generating unit of a thermal power plant,
nij1For the coal electricity conversion coefficient minimum value of j-th of fired power generating unit burning coal of i-th of thermal power plant, nij4For i-th of thermal power plant
J-th of fired power generating unit burning coal coal electricity conversion coefficient maximum value, nij2And nij3For j-th of thermoelectricity of i-th of thermal power plant
The coal electricity conversion coefficient of unit burning coal is in nij1With nij4Between value, nij1< nij2< nij3< nij4, nij1、nij2、nij3
And nij4The parameter as investigated,For preset attitude parameter,
Power station object module can use:
Wherein, m is m-th of power station, and M is power station sum, and n is n-th of Hydropower Unit of hydropower station at present, and N is to work as
The Hydropower Unit sum in preceding power station, t are t-th of unit time, and T is the unit time sum of current dispatching cycle, Qmax,mFor
M-th of power station can be used for the maximum amount of water to generate electricity, y in current dispatching cyclemntFor n-th of hydroelectric machine in m-th of power station
Water flow of the group within t-th of unit time, gmntFor m-th of power station n-th of Hydropower Unit within t-th of unit time
On-off state, open state and off-mode indicate that Δ t is the unit time with number 1 and number 0 respectively, and CD is reference
Hydroelectric station surplus water in dispatching cycle, m, n, t, M, N and T are positive integer.Pass through above-mentioned power station object module, Neng Gouji
The total abandoning water for calculating all Hydropower Units in all power stations in current dispatching cycle, then compares with the reference cycle,
To meet the sets requirement for abandoning water.
Above-mentioned power station object module can also include that power station constrains, and power station constraint may include:
Water volume that can be utilized constraint:
Hydropower Unit water flow constraint: Qmin-mn≤ymnt≤Qmax-mn；
The constraint of reservoir dynamic water:
Wherein, Qmin,mIt can be used for the least quantity to generate electricity, Q in current dispatching cycle for m-th of power stationmax,mMeter
Calculation method can useQmin-mnAllow most for n-th of Hydropower Unit in m-th of power station
Weep amount, Qmax-mnFor the maximum flow of water amount that n-th of Hydropower Unit in m-th of power station allows, AmtFor m-th of power station pair
Moisture storage capacity of the reservoir answered at the end of t-th of unit time, qmtIt is the corresponding reservoir in m-th of power station in t-th of unit
Interior water intake velocity, AmcFor moisture storage capacity of the corresponding reservoir in m-th of power station when current dispatching cycle originates.In a model
After adding above-mentioned constraint condition, calculated result can be made more to tally with the actual situation, calculated result is more accurate.
Wind power plant object module can use:
Wherein, k is k-th of wind power plant, and K is wind power plant sum, and t is t-th of unit time, and T is current dispatching cycle
Unit time sum, SkFor the template Wind turbines quantity of k-th of wind power plant, ZktIt is k-th of wind power plant t-th of unit time
The conventional Wind turbines quantity of interior operation, LkFor the conventional Wind turbines quantity of k-th of wind power plant, Ptur,ktFor k-th of wind power plant
Wind turbines power curve, k, K, t and T are positive integer.By above-mentioned wind power plant object module, can calculate current
Total wind power utilization of all wind power plants in dispatching cycle, to meet the sets requirement of wind power utilization.
Above-mentioned wind power plant object module can also include that wind power plant constrains, and wind power plant constraint may include:
The constraint of Wind turbines power curve:
Wind turbines number constraint: Zkt≤Lk；
Wherein, vktFor wind speed of k-th of wind power plant within t-th of unit time, Vin,kFor the wind turbine of k-th of wind power plant
The incision wind speed of group, Vrated,kFor the rated wind speed of the Wind turbines of k-th of wind power plant, Vout,kFor the wind-powered electricity generation of k-th of wind power plant
The cut-out wind speed of unit, Prated,kFor the rated power of the Wind turbines of k-th of wind power plant.Above-mentioned constraint item is added in a model
After part, calculated result can be made more to tally with the actual situation, calculated result is more accurate.
Electricity generation system object module can use:
When decision model includes thermal power plant's object module and power station object module, the electricity generation system object module is adopted
With:
When decision model includes thermal power plant's object module and wind power plant object module, the electricity generation system object module is adopted
With:
When decision model includes power station object module and wind power plant object module, the electricity generation system object module is adopted
With:
When decision model includes thermal power plant's object module, power station object module and wind power plant object module, the hair
Electric system object module uses:
Wherein, PctThe power output for being thermal power plant within the unit time, PhtThe power output for being power station within the unit time, PwtFor
Power output of the wind power plant within the unit time, PdtFor demand electricity consumption in the unit time, t and T are positive integer.Above-mentioned electricity generation system
Object module sets 0 for δ, and power supply and electricity needs is made to fit like a glove.Pct、PhtAnd PwtCalculation specifically can be with
Using:
Above-mentioned HmIt is the head in m-th of power station, ηmIt is the overall efficiency coefficient of all Hydropower Units in m-th of power station,
9.81 be the gravity coefficient of water, unit kN/m3。
Above-mentioned electricity generation system object module can also include that system spinning reserve constrains, and the constraint of system spinning reserve can adopt
With:
Wherein,The maximum output for being thermal power plant within the unit time,It is thermal power plant within the unit time
Minimum load,The maximum output for being power station within the unit time,The minimum for being power station within the unit time
Power output, a% are preset system spinning reserve rate.By the way that spare capacity is arranged for system, make electric system in overhaul of the equipments, thing
Therefore the supply of electric power is still ensured that when frequency modulation.WithCalculation specifically may be used
To use:
Embodiment
Concrete example illustrates technical solution of the present invention below.The hybrid power system power scheduling multiobjective decision-making of this example
Method, based on the hybrid power system of thermoelectricity, water power and wind-powered electricity generation, system includes power station one, thermal power plant one, thermal power plant two, wind
Electric field one and wind power plant two.
The decision model that this example is established specifically:
In above-mentioned decision model, i is i-th of thermal power plant, and I is thermal power plant's sum, and j is j-th of thermoelectricity of Present Thermal Power factory
Unit, J are the fired power generating unit sum of Present Thermal Power factory, and t is t-th of unit time, and T is that the unit time of current dispatching cycle is total
Number, SijFor the carbon emission coefficient of j-th of fired power generating unit burning coal of i-th of thermal power plant, xijtIt is j-th of i-th of thermal power plant
Coal-fired weight of the fired power generating unit within t-th of unit time, IijtIt is single at t-th for j-th of fired power generating unit of i-th of thermal power plant
On-off state in the time of position, open state and off-mode indicate that CE is with reference to scheduling week with number 1 and number 0 respectively
Interim thermal power plant's carbon emission amount,For the carbon emission amount coefficient Trapezoid Fuzzy Number of j-th of fired power generating unit of i-th of thermal power plant,
rij1For the carbon emission coefficient minimum value of j-th of fired power generating unit burning coal of i-th of thermal power plant, rij4For i-th thermal power plant
The carbon emission coefficient maximum value of j-th of fired power generating unit burning coal, rij2And rij3For j-th of fired power generating unit of i-th of thermal power plant
The carbon emission coefficient of burning coal is in rij1With rij4Between value, rij1< rij2< rij3< rij4,For preset attitude ginseng
Number, For the maximum coal amount that i-th of thermal power plant in current dispatching cycle is able to use, TijIt is i-th
The coal electricity conversion coefficient of j-th of fired power generating unit of a thermal power plant,J-th of fired power generating unit for i-th of thermal power plant exists
Variation of the climbing rate upper limit and the fired power generating unit of t-th of unit time between the climbing rate upper limit of the t-1 unit time
Amount,For i-th of thermal power plant j-th of fired power generating unit t-th of unit time climbing rate lower limit and the thermal motor
Variable quantity of the group between the climbing rate lower limit of the t-1 unit time, Pij-minFor j-th of fired power generating unit of i-th of thermal power plant
Minimum load within the unit time, Pij-maxGo out for maximum of j-th of fired power generating unit within the unit time of i-th of thermal power plant
Power, Tijt,onFor line duration of j-th of fired power generating unit within t-th of unit time of i-th of thermal power plant, Tij,upFor i-th of fire
Minimum line duration of j-th of the fired power generating unit of power plant within the unit time, Tijt,offFor j-th of thermoelectricity of i-th of thermal power plant
Offline time of the unit within t-th of unit time, Tij,downFor i-th of thermal power plant j-th of fired power generating unit in the unit time
Interior minimum offline time,For the coal electricity conversion coefficient Trapezoid Fuzzy Number of j-th of fired power generating unit of i-th of thermal power plant, nij1
For the coal electricity conversion coefficient minimum value of j-th of fired power generating unit burning coal of i-th of thermal power plant, nij4It is the of i-th of thermal power plant
The coal electricity conversion coefficient maximum value of j fired power generating unit burning coal, nij2And nij3For j-th of fired power generating unit of i-th of thermal power plant
The coal electricity conversion coefficient of burning coal is in nij1With nij4Between value, nij1< nij2< nij3< nIj4, For preset attitude
Parameter,M is m-th of power station, and M is power station sum, and n is n-th of Hydropower Unit of hydropower station at present, N
For the Hydropower Unit sum of hydropower station at present, Qmax,mIt can be used for the maximum to generate electricity in current dispatching cycle for m-th of power station
Water, ymntFor the water flow of n-th of Hydropower Unit within t-th of unit time in m-th of power station, gmntFor m-th of water power
On-off state of n-th of the Hydropower Unit stood within t-th of unit time, open state and off-mode use number 1 respectively
It is indicated with number 0, Δ t is the unit time, and CD is with reference to the hydroelectric station surplus water in dispatching cycle, Qmin,mFor m-th of power station
It can be used for the least quantity to generate electricity, Q in current dispatching cyclemin-mnAllow for n-th of Hydropower Unit in m-th power station
Minimum water flow, Qmax-mnFor the maximum flow of water amount that n-th of Hydropower Unit in m-th of power station allows, AmtFor m-th of power station
Moisture storage capacity of corresponding reservoir at the end of t-th of unit time, qmtIt is the corresponding reservoir in m-th of power station in t-th of unit
Water intake velocity in time, AmcFor moisture storage capacity of the corresponding reservoir in m-th of power station when current dispatching cycle originates, k is kth
A wind power plant, K are wind power plant sum, SkFor the template Wind turbines quantity of k-th of wind power plant, ZktIt is k-th of wind power plant in t
The conventional Wind turbines quantity run in a unit time, LkFor the conventional Wind turbines quantity of k-th of wind power plant, Ptur,ktFor
The power curve of the Wind turbines of k-th of wind power plant, vktFor wind speed of k-th of wind power plant within t-th of unit time, Vin,kFor
The incision wind speed of the Wind turbines of k-th of wind power plant, Vrated,kFor the rated wind speed of the Wind turbines of k-th of wind power plant, Vout,k
For the cut-out wind speed of the Wind turbines of k-th of wind power plant, Prated,kFor the rated power of the Wind turbines of k-th of wind power plant, Pct
The power output for being thermal power plant within the unit time, PhtThe power output for being power station within the unit time, PwtIt is wind power plant in the unit time
Interior power output, PdtFor demand electricity consumption in the unit time, HmIt is the head in m-th of power station, ηmIt is all of m-th of power station
The overall efficiency coefficient of Hydropower Unit, 9.81 be the gravity coefficient of water, unit kN/m3,It is thermal power plant in the unit time
Interior maximum output,The minimum load for being thermal power plant within the unit time,It is power station within the unit time
Maximum output,The minimum load for being power station within the unit time, a% are preset system spinning reserve rate, i, j, t,
M, n, k, I, J, M, N, K and T are positive integer.
This example is arranged rich according to the different setting spring, 4 summer, autumn and winter wind speed scenes of wind speed according to the difference for carrying out water
Water, par and low water 3 carry out water scene, and then collectively form 12 different scheduling scenarios, under each scheduling scenario
Corresponding λ, β and α value is set, this example by taking current dispatching cycle is in period when a river is at its normal level summer scene as an example, be arranged α under the scene=
0.965, β=0.95, λ=0.5；Current dispatching cycle uses 24 hours, and the unit time uses 1 hour.
The design parameter data calculated in this example are referring to table 1- table 11.
1 power station of table, one parameter list
The Hydropower Unit parameter list in 2 power station one of table
3 wind power plant of table, one parameter list
4 wind power plant of table, two parameter list
Two preset parameter table of 5 thermal power plant one of table and thermal power plant
Two fuzzy parameter table of 6 thermal power plant one of table and thermal power plant
Anemometer of the wind power plant one in unit time in 7 current dispatching cycle of table
Anemometer of the wind power plant two in unit time in 8 current dispatching cycle of table
Table 9 is the electricity consumption demand schedule of unit time in current dispatching cycle
Water intake velocity table of the reservoir in power station one in unit time in 10 current dispatching cycle of table
Each fired power generating unit is in the coal-fired weight of unit time, each Hydropower Unit in constituent parts in 11 current dispatching cycle of table
The conventional Wind turbines quantity table that the water flow of time and each wind power plant are run in unit time
Required parameter is calculated in this example also: the carbon emission amount of the reference dispatching cycle of selection is 19987 kilograms, abandons water
Amount is 16 × 105Cubic meter；All fired power generating unit whole process are in open state；The maximum coal amount that all thermal power plants are able to use
Assuming that infinitely great；Using 0.5,Using 0.5；Power station one can be used for the least quantity to generate electricity in current dispatching cycle
It is set as 0；For Hydropower Unit when the water flow of unit time is 0, then the Hydropower Unit is off-mode in the unit time, no
It is then open state；Moisture storage capacity of the corresponding reservoir in power station one when current dispatching cycle is originated is using the normal of power station one
Storage capacity value；The head in power station one uses the rated head of the Hydropower Unit in power station one；System spinning reserve rate uses 5%.
Above-mentioned data input decision model is calculated, obtained result referring to table 12- table 14,.
Power output table of 12 power station of table in unit time
Power output table of 13 wind power plant of table in unit time
Table 14 is power output table of the thermal power plant in unit time, and the unit of power output is MW.
The carbon emission amount that current dispatching cycle is calculated is 17478 kilograms, and abandoning water is 9 × 105Cubic meter, wind-powered electricity generation benefit
It is 0.55 with rate.From the above data, it can be seen that all calculated results all meet corresponding condition in decision model respectively, such as
The carbon emission amount of current dispatching cycle is less than 0.965 times with reference to carbon emission amount dispatching cycle, the abandoning water of current dispatching cycle
Less than 0.95 times that reference dispatching cycle abandons water, the wind power utilization of current dispatching cycle is greater than 0.5 etc., therefore, this
Input decision model in the corresponding power scheduling scheme of design parameter data can as the result of decision of current dispatching cycle,
The power scheduling scheme of current dispatching cycle can be transported according to each generating set of this input in the data of unit time
Row.
Claims (10)
1. hybrid power system power scheduling Multiobjective Decision Making Method characterized by comprising
Decision model is established, the decision model includes thermal power plant's object module, power station object module and wind power plant target mould
At least two in type and electricity generation system object module；
Thermal power plant's object module are as follows: in current dispatching cycle, thermal power plant's carbon emission amount is less than or equal to preset reference
Dispatching cycle α times of moderate heat power plant carbon emission amount；
The power station object module are as follows: in current dispatching cycle, hydroelectric station surplus water is less than or equal to preset with reference to tune
β times for spending hydroelectric station surplus water in the period；
The wind power plant object module are as follows: in current dispatching cycle, wind power plant wind power utilization is greater than or equal to λ；
The electricity generation system object module are as follows: in current dispatching cycle, corresponding all power generation classes that decision model is included
The difference of demand electricity consumption is less than or equal to δ in the gross capability of type and the dispatching cycle；
The input of design parameter data needed for decision model decision model is calculated, if all calculated results are all full respectively
This can then be inputted the corresponding power scheduling of design parameter data in decision model by corresponding condition in sufficient decision model
The result of decision of the scheme as current dispatching cycle, the design parameter data that otherwise cannot be inputted this in decision model are corresponding
The result of decision of the power scheduling scheme as current dispatching cycle；
Wherein, 0,0 < λ < 1 of α > 0, β >, δ >=0.
2. hybrid power system power scheduling Multiobjective Decision Making Method as described in claim 1, which is characterized in that further include:
Multiple wind speed scenes are set according to the difference of wind speed, and/or multiple come water scene according to the difference setting for carrying out water, each
A wind speed scene, which is divided into, sets corresponding λ and α value, or corresponding β and α value is arranged in the case where each carrys out water scene, or each
A wind speed scene comes under the combine scenes of water scene that corresponding λ, β and α value is arranged with each.
3. hybrid power system power scheduling Multiobjective Decision Making Method as described in claim 1, which is characterized in that the thermoelectricity
Factory's object module uses:
Wherein, i is i-th of thermal power plant, and I is thermal power plant's sum, and j is j-th of fired power generating unit of Present Thermal Power factory, and J is current fire
The fired power generating unit sum of power plant, t are t-th of unit time, and T is the unit time sum of current dispatching cycle, SijFor i-th of fire
The carbon emission coefficient of j-th of fired power generating unit burning coal of power plant, xijtFor i-th of thermal power plant j-th of fired power generating unit in t
Coal-fired weight in a unit time, IijtFor switch of j-th of fired power generating unit within t-th of unit time of i-th of thermal power plant
Machine state, open state and off-mode indicate that CE is with reference to thermal power plant's carbon in dispatching cycle with number 1 and number 0 respectively
Discharge amount, i, j, t, I, J and T are positive integer.
4. hybrid power system power scheduling Multiobjective Decision Making Method as claimed in claim 3, which is characterized in that the thermoelectricity
Factory's object module further includes thermal power plant's constraint, and thermal power plant's constraint includes:
The constraint of coal available quantity:
Climing constant:
Unit output constraint: Pij-min≤Tijxijt≤Pij-max；
On-off state constraint:
Wherein,For the maximum coal amount that i-th of thermal power plant in current dispatching cycle is able to use, TijFor i-th of fire
The coal electricity conversion coefficient of j-th of fired power generating unit of power plant,For i-th of thermal power plant j-th of fired power generating unit in t
Variable quantity of the climbing rate upper limit and the fired power generating unit of a unit time between the climbing rate upper limit of the t-1 unit time,Exist for j-th of fired power generating unit of i-th of thermal power plant in the climbing rate lower limit of t-th of unit time and the fired power generating unit
Variable quantity between the climbing rate lower limit of the t-1 unit time, Pij-minFor i-th of thermal power plant j-th of fired power generating unit in list
Minimum load in the time of position, Pij-maxFor maximum output of j-th of fired power generating unit within the unit time of i-th of thermal power plant,
Tijt,onFor line duration of j-th of fired power generating unit within t-th of unit time of i-th of thermal power plant, Tij,upFor i-th of thermoelectricity
Minimum line duration of j-th of the fired power generating unit of factory within the unit time, Tijt,offFor j-th of thermal motor of i-th of thermal power plant
Offline time of the group within t-th of unit time, Tij,downFor i-th of thermal power plant j-th of fired power generating unit within the unit time
Minimum offline time.
5. hybrid power system power scheduling Multiobjective Decision Making Method as described in claim 1, which is characterized in that the water power
Object module of standing uses:
Wherein, m is m-th of power station, and M is power station sum, and n is n-th of Hydropower Unit of hydropower station at present, and N is current water
The Hydropower Unit sum in power station, t are t-th of unit time, and T is the unit time sum of current dispatching cycle, Qmax,mIt is m-th
Power station can be used for the maximum amount of water to generate electricity, y in current dispatching cyclemntN-th of Hydropower Unit for m-th of power station exists
Water flow in t-th of unit time, gmntFor n-th of Hydropower Unit opening within t-th of unit time in m-th of power station
Off-mode, open state and off-mode indicate that Δ t is the unit time with number 1 and number 0 respectively, and CD is with reference to scheduling
Hydroelectric station surplus water in period, m, n, t, M, N and T are positive integer.
6. hybrid power system power scheduling Multiobjective Decision Making Method as claimed in claim 5, which is characterized in that the water power
Object module of standing further includes power station constraint, and the power station constraint includes:
Water volume that can be utilized constraint:
Hydropower Unit water flow constraint: Qmin-mn≤ymnt≤Qmax-mn；
The constraint of reservoir dynamic water:
Wherein, Qmin,mIt can be used for the least quantity to generate electricity, Q in current dispatching cycle for m-th of power stationmin-mnFor m-th of water
The minimum water flow that n-th of Hydropower Unit in power station allows, Qmax-mnAllow most for n-th of Hydropower Unit in m-th of power station
Flood flow, AmtFor moisture storage capacity of the corresponding reservoir in m-th of power station at the end of t-th of unit time, qmtFor m-th of water
Water intake velocity of the corresponding reservoir in power station within t-th of unit time, AmcIt is the corresponding reservoir in m-th of power station in current scheduling
Moisture storage capacity when period originates.
7. hybrid power system power scheduling Multiobjective Decision Making Method as described in claim 1, which is characterized in that the wind-powered electricity generation
Field object module uses:
Wherein, k is k-th of wind power plant, and K is wind power plant sum, and t is t-th of unit time, and T is the unit of current dispatching cycle
Time sum, SkFor the template Wind turbines quantity of k-th of wind power plant, ZktIt is transported within t-th of unit time for k-th of wind power plant
Capable conventional Wind turbines quantity, LkFor the conventional Wind turbines quantity of k-th of wind power plant, Ptur,ktFor the wind of k-th of wind power plant
The power curve of motor group, k, K, t and T are positive integer.
8. hybrid power system power scheduling Multiobjective Decision Making Method as claimed in claim 7, which is characterized in that the wind-powered electricity generation
Field object module further includes wind power plant constraint, and the wind power plant constraint includes:
The constraint of Wind turbines power curve:
Wind turbines number constraint: Zkt≤Lk；
Wherein, vktFor wind speed of k-th of wind power plant within t-th of unit time, Vin,kFor the Wind turbines of k-th wind power plant
Cut wind speed, Vrated,kFor the rated wind speed of the Wind turbines of k-th of wind power plant, Vout,kFor the Wind turbines of k-th of wind power plant
Cut-out wind speed, Prated,kFor the rated power of the Wind turbines of k-th of wind power plant.
9. hybrid power system power scheduling Multiobjective Decision Making Method as described in claim 1, it is characterised in that:
When decision model includes thermal power plant's object module and power station object module, the electricity generation system object module is used:
When decision model includes thermal power plant's object module and wind power plant object module, the electricity generation system object module is used:
When decision model includes power station object module and wind power plant object module, the electricity generation system object module is used:
When decision model includes thermal power plant's object module, power station object module and wind power plant object module, the power generation system
Object module of uniting uses:
Wherein, PctThe power output for being thermal power plant within the unit time, PhtThe power output for being power station within the unit time, PwtFor wind-powered electricity generation
Power output of the field within the unit time, PdtFor demand electricity consumption in the unit time, t and T are positive integer.
10. hybrid power system power scheduling Multiobjective Decision Making Method as claimed in claim 9, which is characterized in that the hair
Electric system object module further includes the constraint of system spinning reserve, and the system spinning reserve constraint uses:
Wherein,The maximum output for being thermal power plant within the unit time,The minimum for being thermal power plant within the unit time
Power output,The maximum output for being power station within the unit time,The minimum for being power station within the unit time goes out
Power, a% are preset system spinning reserve rate.
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