CN110535120A - Consider the interconnection system distributed Optimization Scheduling of electric-gas of air pollution diffusion - Google Patents
Consider the interconnection system distributed Optimization Scheduling of electric-gas of air pollution diffusion Download PDFInfo
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- 238000009792 diffusion process Methods 0.000 title claims abstract description 44
- 238000005457 optimization Methods 0.000 title claims abstract description 25
- 238000003915 air pollution Methods 0.000 title claims abstract description 14
- 239000007789 gas Substances 0.000 claims abstract description 68
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- 238000003462 Bender reaction Methods 0.000 claims abstract description 13
- 239000003345 natural gas Substances 0.000 claims abstract description 12
- 238000000354 decomposition reaction Methods 0.000 claims abstract description 10
- 230000008569 process Effects 0.000 claims abstract description 9
- 235000019504 cigarettes Nutrition 0.000 claims description 36
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- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 5
- 229910052799 carbon Inorganic materials 0.000 description 5
- 230000000875 corresponding effect Effects 0.000 description 5
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
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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
-
- 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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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The invention discloses a kind of interconnection system distributed Optimization Schedulings of electric-gas for considering air pollution diffusion.Increase environmental correclation constraint in economic load dispatching model, by penalizing convex-concave process by model convexification, optimal electric-gas energy flow problem is decomposed into the electric power networks primal problem that can independently solve and natural gas grid string bag problem based on generalized benders decomposition, the two, which need to only exchange a small amount of boundary information, can achieve the purpose that collaboration optimization.Distributed dispatching method protects power grid gas net respectively internal privacy, and it is excessive to avoid central dispatching mechanism pressure.Compared with traditional total amount control of pollution method, dispatching method of the invention treats different regions with a certain discrimination according to environment tolerance, and electric-gas interacted system is enabled to significantly reduce contribution of the electrical activity to low environment tolerance power area pollutant with lower cost sacrifice.
Description
Technical field
The present invention relates to integrated energy system scheduling fields, more particularly to a kind of electric-gas for considering air pollution diffusion
Interconnection system distributed dispatching method.
Background technique
Atmosphere pollution is to influence the important environmental problem of human lives.As a main energy consumption industry, electric power
Industry discharges a large amount of pollutant in power generation process and causes damages to atmospheric environment and people's health.It in recent years, is raising
The pollution of efficiency of energy utilization and reduction to environment, the energy internet that electric system is gradually coupled to various energy resources network turn
Type.And have benefited from the electric-gas that heating value of natural gas is high, discharges the advantages that low and reserves are big, and electric power networks and natural gas network couple
Interacted system (Integrated Power and Gas System, IPGS) transition becomes a kind of base under energy internet
Plinth form, and (Optimal Power-Gas Flow, OPGF) can be flowed and also be expected to by considering economy, the optimal electric-gas of environmental factor
As it is a kind of realize that the energy is reliably supplied while reduce atmosphere pollution new way.
Although energy carrier is transitioned into electric-gas energy stream from the direction of energy, to the control mode of atmosphere pollution according to
So maintain original prediction emission mode.Since the density of population and vegetative coverage situation of different regions are not quite similar,
It is also different to the tolerance and self-purification capacity of atmosphere pollution, and prediction emission mode ignores these factors,
It tends not to minimize the harm of atmosphere pollution.In fact, the groundlevel concentration of atmosphere pollution is to endanger health of people
Direct factor, and consider pollutant and different regions and the control model of atmosphere pollution tolerance be only
A kind of more direct effective mode.Pollutant mainly due to caused by the diffusion of discharge of pollutant sources pollutant,
And the factor for influencing atmosphere pollution diffusion mainly includes the pollution sources factors such as pollution source position, height and discharge amount, and
The Natural environment factors such as wind speed, wind direction, atmospheric stability.Therefore, atmosphere pollution is constructed according to pollution sources condition and atmospheric conditions
The space-time diffusion model of object is the basis for reducing the harm of IPGS atmosphere pollution.
On the other hand, many researchs about IPGS operation at present are still by the way of centralized and unified Optimized Operation.It should
Mode requires control centre to fully understand the gentle net operating mechanism of power grid, this requires very the professional ability of control centre
It is high；On the other hand it also implies that oneself internal information will be fully exposed by the gentle net of power grid, is supplied as the independent energy
Network is answered, electric power networks and natural gas network are often unwilling all to upload to the information of oneself into a control centre；Meanwhile day
Right gas network and electric power networks load condition and internal networking structure change frequent occurrence, and the data of control centre update difficulty
It is bigger.For this purpose, domestic and foreign scholars propose the method for many electric-gas interacted system dispersion collaboration optimizations, wherein dispersing
The core algorithm of collaboration with alternating direction multipliers method (Alternating Direction Method of Multipliers,
ADMM based on).Generalized benders decomposition (Generalized Benders Decomposition, GBD) is also that dispersion solves
A kind of feasible method, it is cut by a series of linear restrictions of grey iterative generation and is constantly approached feasible zone and codomain, solve
Speed is fast.GBD disperses in collaboration optimization in IPGS with less at present.
Summary of the invention
For traditional Control of total air pollutant emission to reducing the inefficient defect of electrical activity contamination hazard,
It is proposed the interconnection system distributed Optimization Scheduling of electric-gas of consideration air pollution diffusion.
The interconnection system distributed Optimization Scheduling process of electric-gas for considering air pollution diffusion is as shown in Figure 1, chat
It states as follows:
Step 1: establishing power network model, natural gas network model and atmosphere pollution space-time diffusion model；It is required that
The form of the non-convex difference for being constrained to convex function in model built.
Step 2: being optimized by PCCP-GBD bilayer alternative manner with energizing the minimum target of cost, obtain each monitoring
The benchmark pollution concentration of point.
Step 3: the pollution concentration that mark is changed being constructed as base value using the benchmark pollution concentration in step 2 and contributes total amountIndex.
Step 4: increasing atmosphere pollution constraint for the model in step 1.Different constraints can be used as needed, such as is wanted
The pollution concentration contribution total amount for asking mark to changeIndex down ratio is greater than given value.
Step 5: the model for being added to atmosphere pollution constraint passes through PCCP-GBD bilayer alternative manner to energize cost
Minimum target optimizes.
The space of description pollutant is described using Gauss cigarette group model as the atmosphere pollution space-time diffusion model
Continuous plume is regarded as and is made of a series of cigarette group of Driftdiffusions in an atmosphere by diffusion process, the model；
Scheduling model is established, in scheduling model, the time step Δ t of the variables such as unit output, gas source power output is referred to as
Scheduling slot；It is Δ τ=Δ t/M discharge period that scheduling slot, which is further subdivided into M step-length,；Each discharge period discharges one
Cigarette group represents the pollutant discharged in the period, and the cigarette group quality of all discharge periods is equal scheduling in each scheduling slot
When segment index indicate that segment index is indicated with τ when discharge with t, τ ∈ t indicates that discharge period τ is the segmentation in scheduling slot t；If hair
Motor i discharges the cigarette group that a quality is Q (τ ') in τ ' the period, then its contribution of concentration C to the period monitoring point τ (x, y, z)i
Are as follows:
Ci(τ ', τ, x, y, z)=Qi(τ′)×Gi(τ′,τ,x,y,z)(6)
Distribution function GiCalculating such as formula (2) shown in, wherein ψ is to indicate intermediate variable convenient and being arranged, and e is nature
Constant 2.71828..；
σx(τ',τ)、σy(τ',τ)、σz(τ ', τ) is that the cigarette group of τ ' period is joined in the diffusion of τ period x, y, z axis direction respectively
Number；xi(τ',τ)、yi(τ',τ)、zi(τ ', τ) is centre coordinate of the cigarette group in the τ period；Diffusion parameter calculating formula are as follows:
In formula, subscript α represents x, y, z axis, aα(τ),bα(τ) is constant related with atmospheric stability grade；Cigarette cluster centre coordinate
The wind friction velocity calculating that can be rolled into a ball by cigarette in motion process is as follows:
(x in formulai,0,yi,0) be generator i position coordinates, zi,0The high, [v for its effective emission sourcex(n),vy(n),vz
(n)]TFor wind velocity vector
Since atmospheric stability grade constantly changes, diffusion parameter σαAlso do not stopping to switch with the relation curve of diffusion time, then
It needs to be modified formula (4), (5)；
With the diffusion of cigarette group, its concentration constantly reduces until can be ignored；Assuming that the cigarette group W discharge period of release
No longer have an impact to the concentration of monitoring point afterwards, if there is N in IPGSGA generator, then IPGS is to monitoring point j in the dense of period τ
Degree contribution C (τ, j) be before this contribution of concentration of W discharge period all generators discharge with that is,
The pollutant concentration contribution margin of one scheduling slot is the average value that it is respectively segmented, monitoring point j in scheduling slot t
Mean concentration are as follows:
The pollution concentration contributes total amountCalculation formula it is as follows:
Cj,tIt is monitoring point j obtained in step 2 in the benchmark pollution concentration of period t, T is that all scheduling slots (please supplement
Illustrate how " scheduling slot " obtains) set, CbaseFor the weighting concentration and ω of each monitoring pointjFor monitoring point j's
Weight depends on its environment tolerance, Cj,t,0It is IPGS to the integrated concentration contribution margin of all monitoring points.
The electrical network model is using simplified DC power flow description:
θSlack, t=0 (10)
rd≤PG,t-PG,t-1≤ru(14)
AGPG,t-Bθt-PD,t=0 (15)
Wherein, scheduling slot index indicates that segment index is indicated with τ when discharge with t, and τ ∈ t indicates that discharge period τ is scheduling
Segmentation in period t, θslack,tFor balance nodes voltage phase angle, θtFor node voltage phase angle vector, xijFor the electricity of route i-j
It is anti-,For route active power limit value, "-" and " _ " and the bound for representing relevant variable, ΩPBFor electric power networks node set,
ΩGCFor coal unit set, ΩGTFor Gas Generator Set set, PG,tFor generator power phasor, rdAnd ruRespectively unit is downward
With ratio of slope vector of valae of climbing；Formula (15) is the constraint of node active balance, wherein AGIt is that electric power networks node-unit closes with B
Join matrix and node admittance matrix imaginary part, PD,tFor node load vector；Formula (16) and formula (17) are respectively coal unit and combustion
The consumption equation of mechanism of qi group, PGC,i,tAnd PGT,i,tThe respectively active power output of coal unit i and Gas Generator Set i in the t period,
DGC,i,tAnd fGT,i,tRespectively corresponding unit time coal consumption and air consumption, ai,bi,ciAnd αi,βi,γiFor consumption characteristic
Coefficient；Cost in formula (18)coalFor coal totle drilling cost, PC,iFor the purchase coal price lattice of unit i；The power generation of unit in electric power networks
Discharge amount is expressed as
Total emission volumn in emission ξ mono- day indicates are as follows:
Wherein subscript ξ represents different emissions, hi,ξ、gi,ξTo discharge constant accordingly.
The natural gas network model is as follows:
Asfs,t-APfP,t-fD,t=0 (22)
pc,ij,t≤R×pi,t,ij∈Ωact(24)
Ω in formulapassAnd ΩactRespectively compressor-free and there is Compressor Pipes set；Formula (21) is Weymouth stable state
Gas flow equation, wherein fij,tFlow for pipeline ij in the t period, pi,tAnd pj,tFor the air pressure of node i and node j, Kij> 0 is pipe
Road transmission；Formula (22) describes node air balance, ASFor node gas source incidence matrix, fS,tGo out force vector, A for gas sourcePFor
Node pipeline incidence matrix, fP,tFor chimneying vector, (its element is equal to corresponding fij,t), fD,tFor node load vector；Formula
(23) node air pressure range is indicated；Formula (24) is the constraint of air pressure containing compressor, pc,ij,tFor compressor outlet air pressure, R is compressor
Maximum step-up ratio, formula (25) are the gas flow equation containing Compressor Pipes；Cost in formula (26)gasTo purchase gas totle drilling cost, PS,iGas source i
Gas Prices.
The PCCP-GBD bilayer alternative manner is as follows:
Step 2.1: seeking initial point for step 3.Temporarily ignore the non-convex constraint for the difference that form in model is two convex functions,
Problem is split by gas host problem using generalized benders decomposition and power grid subproblem carries out distributed optimization.
Step 2.2: form in model of rewriting is the non-convex constraint of the difference of two convex functions.For equality constraint, first by it
One is converted to be more than or equal to one less than or equal to two inequality constraints of equal value.It is the difference of two convex functions by form
Inequality is rewritten into the form less than or equal to 0.
Step 2.3: by step 2.2 be formed by convex function that symbol in inequality constraints is negative using Taylor's formula to
Fixed initial point carries out first order Taylor expansion, to increase non-negative slack variable less than or equal to a number the right, by all slack variables
The sum of be added with original objective function as new objective function multiplied by a penalty coefficient.The given initial point is first
Step 2.1 is derived from when secondary iteration, and step 2.5 is derived from successive iterations.
Step 2.4: splitting into gas host problem and electricity using the optimization problem that generalized benders decomposition forms step 3
Net problem carries out distributed optimization, and feasible cut for generating step 1 before generalized benders decomposition iteration starts is added to this
In the model of step.
Step 2.5: the convergence for carrying out PCCP to the result of step 2.4 is examined.Stop calculating and exporting if having restrained excellent
Change result.With the calculated result of step 2.4 for new initial point return step 2.3 if not converged.
Accepted standard is examined in PCCP convergence in the step 2.5 are as follows:
|objk-objk-1|≤ε1|objk-1| and max δ≤ε2
Wherein ε1And ε2For previously given condition of convergence constant, objkFor the target value of current iteration acquired, objk-1
For the target value that last iteration acquires, δ be in claim 6 step 2.4 on the right side of inequality increased slack variable set,
Max δ indicates the maximum value in all slack variables.
Compared with prior art, the beneficial effects of the present invention are: making the gentle net of power grid can by generalized benders decomposition
Collaboration optimization can be realized only to exchange a small amount of information, protected respectively internal privacy, avoided central dispatching mechanism pressure mistake
Greatly.As shown in embodiment simulation result, compared with traditional total amount control of pollution method, consideration atmosphere pollution proposed by the present invention
The dispatching method of object spatial and temporal distributions treats different regions with a certain discrimination according to environment tolerance, enables electrical interconnection system with lower
Cost sacrifice, significantly reduce electrical activity to low environment tolerance power area pollutant contribution, reduce to resident
The influence of life.
Detailed description of the invention
Fig. 1 is to roll into a ball model schematic to describe the Gauss cigarette of atmosphere pollution diffusion process in embodiment；
Fig. 2 is the diffusion coefficient processing method schematic diagram that this cigarette rolls into a ball model time-varying；
Fig. 3 is PCCP-GBD distributed optimization algorithm flow schematic diagram；
Fig. 4 is simcity schematic layout pattern used in embodiment；
Fig. 5 is the effect of optimization comparison diagram of algorithms of different in embodiment.
Specific embodiment
Specific implementation of the invention is described further below in conjunction with drawings and examples, but implementation and guarantor of the invention
Protect it is without being limited thereto, if it is noted that below have not especially detailed description process or parameter, be that those skilled in the art can
Referring to the prior art understand or realize.
The present embodiment describes the spatial diffusion process of pollutant using Gauss cigarette group model, which sees continuous plume
It is formed at a series of cigarette group by Driftdiffusions in an atmosphere, as shown in Figure 1.In the gentle net scheduling of power grid, unit output, gas
The time step Δ t of the variables such as source power output is referred to as scheduling slot.In general, scheduling slot takes longer to reduce decision change
Amount.But to emission due to rolling into a ball the continuous plume of approximate representation with discrete cigarette, consequently only that the approximation journey when discrete segment is sufficiently small
Degree is just sufficiently high.For this purpose, it is Δ τ=Δ t/M discharge period that scheduling slot is further subdivided into M step-length by the present embodiment.Each
The discharge period discharges a cigarette group and represents the pollutant discharged in the period, and all cigarettes for discharging the periods in each scheduling slot
Group's quality is equal.In the present embodiment, scheduling slot index indicates that segment index is indicated with τ when discharge with t, and τ ∈ t indicates discharge
Period τ is the segmentation in scheduling slot t.If generator i discharges the cigarette group that a quality is Q (τ ') in τ ' the period, when it is to τ
The contribution of concentration C of section monitoring point (x, y, z)iFor
Ci(τ ', τ, x, y, z)=Qi(τ′)×Gi(τ′,τ,x,y,z)(11)
Distribution function GiCalculating such as formula (2) shown in, wherein ψ is to indicate intermediate variable convenient and being arranged, and e is nature
Constant 2.71828...
σx(τ',τ)、σy(τ',τ)、σz(τ ', τ) is that the cigarette group of τ ' period is joined in the diffusion of τ period x, y, z axis direction respectively
Number.xi(τ',τ)、yi(τ',τ)、zi(τ ', τ) is centre coordinate of the cigarette group in the τ period.Diffusion parameter calculating formula is
In formula, subscript α represents x, y, z axis, aα(τ),bα(τ) is constant related with atmospheric stability grade.Cigarette cluster centre coordinate
The wind friction velocity calculating that can be rolled into a ball by cigarette in motion process is as follows:
(x in formulai,0,yi,0) be generator i position coordinates, zi,0The high, [v for its effective emission sourcex(n),vy(n),vz
(n)]TFor wind velocity vector.
Since atmospheric stability grade constantly changes, diffusion parameter σαAlso do not stopping to switch with the relation curve of diffusion time, this
When need to be modified formula (4) (5).As shown in Fig. 2 ,+1 period of τ and τ atmospheric stability is different, corresponding diffusion parameter σ
It is respectively curve 1 and curve 2 with diffusion time change procedure.For guarantee σ τ at continuously, by curve 2 to left μ and curve 1
Intersect at the diffusion profile after the curve 2 ' that point [τ, σ (τ ', τ)] obtains changes as atmospheric environment.Have
Eliminate the diffusion coefficient that translational movement μ obtains+1 period of τ are as follows:
With the diffusion of cigarette group, its concentration constantly reduces until can be ignored.Present embodiment assumes that cigarette group release W
No longer have an impact to the concentration of monitoring point after the discharge period.If there is N in IPGSGA generator, then IPGS to monitoring point j when
The contribution of concentration C (τ, j) of section τ be before this contribution of concentration of W discharge period all generators discharge with that is,
The present embodiment pays close attention to the pollutant concentration contribution margin of each scheduling slot in a dispatching cycle, if when a scheduling
The pollutant concentration contribution margin of section is the average value that it is respectively segmented, and the mean concentration of monitoring point j is in scheduling slot t
It is obtained to evaluate influence size of the various dispatching methods to environment first to energize the minimum optimization aim of cost
IPGS is C to the integrated concentration contribution margin of all monitoring pointsj,t,0, and define the IPGS pollution concentration contribution total amount of mark change
T is the set of all scheduling slots, C in formulabaseFor the weighting concentration and ω in each areajFor the weight of regional j,
Depending on its environment tolerance.The present invention replaces ω with the density of population specific gravity approximation of this areaj.The present embodiment only considers
Electric-gas coupled system is to the contribution margin of pollution concentration, other pollution sources are not in discussion scope.
The present embodiment describes electric power networks using simplified DC power flow.
θslack,t=0 (22)
rd≤PG,t-PG,t-1≤ru(26)
AGPG,t-Bθt-PD,t=0 (27)
Wherein, θslack,tFor balance nodes voltage phase angle, θtFor node voltage phase angle vector, xijFor the reactance of route i-j,For route active power limit value, "-" and " _ " and the bound for representing relevant variable, ΩPBFor electric power networks node set,
ΩGCFor coal unit set, ΩGTFor Gas Generator Set set, PG,tFor generator power phasor, rdAnd ruRespectively unit is downward
With ratio of slope vector of valae of climbing；Formula (17) is the constraint of node active balance, wherein AGIt is that electric power networks node-unit closes with B
Join matrix and node admittance matrix imaginary part, PD,tFor node load vector；Formula (18) and formula (19) are respectively coal unit and combustion
The consumption equation of mechanism of qi group, PGC,i,tAnd PGT,i,tThe respectively active power output of coal unit i and Gas Generator Set i in the t period,
DGC,i,tAnd fGT,i,tRespectively corresponding unit time coal consumption and air consumption, ai,bi,ciAnd αi,βi,γiFor consumption characteristic
Coefficient.Cost in formula (20)coalFor coal totle drilling cost, PC,iFor the purchase coal price lattice of unit i.The power generation discharge amount of unit is expressed as
Wherein subscript ξ represents different emissions, hi,ξ、gi,ξTo discharge constant accordingly.Discharge in emission ξ mono- day
Total amount is expressed as
The present embodiment uses following natural gas network model.
Asfs,t-APfP,t-fD,t=0 (34)
pc,ij,t≤R×pi,t,ij∈Ωact(36)
Ω in formulapassAnd ΩactRespectively compressor-free and there is Compressor Pipes set.Formula (23) is Weymouth stable state
Gas flow equation, wherein fij,tFlow for pipeline ij in the t period, pi,tAnd pj,tFor the air pressure of node i and node j, Kij> 0 is pipe
Road transmission.Formula (24) describes node air balance, ASFor node gas source incidence matrix, fS,tGo out force vector, A for gas sourcePFor
Node pipeline incidence matrix, fP,tFor chimneying vector, (its element is equal to corresponding fij,t), fD,tFor node load vector.Formula
(25) node air pressure range is indicated.Formula (26) is the constraint of air pressure containing compressor, pc,ij,tFor compressor outlet air pressure, R is compressor
Maximum step-up ratio, formula (27) are the gas flow equation containing Compressor Pipes.Cost in formula (28)gasTo purchase gas totle drilling cost, PS,iGas source i
Gas Prices.
The present embodiment Optimized model is with geographical location information, next day data of weather forecast and power grid, gas net load prediction number
According to for input, to energize the minimum target of cost, at the same limit electrical activity to atmosphere pollution depth contribution and carbon emission amount, it is right
Each generator output and gas source power output make a policy.
(1) energy supply cost objective is minimized
Energizing cost includes purchase coal cost and purchase gas cost.
min obj(xp,xg)=costcoal+costgas(39)
In formula: xpAnd xgThe respectively decision variable set of the gentle net of power grid mainly includes the gentle net gas source of generator output
Power output and network node branch correlated variables.
(2) air pollution concentration contribution limitation additional constraint
The present embodiment limits IPGS to including SO2、NOxAnd the contribution of tri- kinds of pollutants of TSP.Regulation mark is changed
Pollution concentration contributes total amountLower than certain threshold value, it may be assumed that
Cj,t-Cj,t,0≤0,j∈Ωlow(42)
In formula,When to disregard costMinimum value, γAPAnd cmax,jFor constant, ΩlowAnd ΩhighRespectively
Low environment tolerates the monitoring point set of power and high environment tolerance power.Formula (37) (38) indicates considering the excellent of Air Pollutant Emission
After changing scheduling, the contribution of concentration value in area IPGS low to environment tolerance power should be reduced；For sparse population, environment tolerance
The high area of power allows the rising of certain amplitude.C is taken in the present embodimentmax,jIt is 0.5.
(3) carbon emission amount limits additional constraint
The present embodiment regulation carbon emission amount must not exceed certain threshold value.
Qco2,0-Qco2≥γC(Qco2,0-Qco2,min)(44)
In formula, Qco2,0Only to consider CO when energizing cost objective2Discharge amount, Qco2,minIt is attainable most to disregard cost
Small CO2Discharge amount, fC,0For carbon emission, γCFor the proportionality coefficient for limiting IPGS carbon emission.
The present embodiment realizes that the dispersion collaboration of the gentle net of power grid is excellent using the method for generalized benders decomposition of the present invention
Change, in PCCP-GBD bilayer alternative manner as described in the present invention in the present embodiment to the treatment process of constraint non-convex in model
It operates as follows.
Non-convex in power grid is constrained to formula (18) and (19) two unit consumption equations, it directly can relax as inequality
Constraint.
Since unnecessary consumption will increase cost, so the constraint above when using cost as target is tight.Work as mesh
Target can be added to tighten constraint (40) as penalty term multiplied by a smaller coefficient in consumption summation when being free of cost in mark.
The nonconvex property of natural gas network derives from formula (23) and (27).Enable πi=pi 2, formula (23) can be rewritten as
Convex function will be subtracted according to Taylor's formula and be unfolded and add slack variable, the variable of subscripting k is that kth time changes in formula
For the initial point of Taylor expansion in the process, all slack variable δ >=0 are required in this section.
Similarly, π is enabledc,ij=pc,ij 2, formula (27) can expand into
fij 2-Kij(πc,ij-πj)≤0(49)
Penalty term Δ such as formula (40) is defined, and is multiplied by coefficient ρ and is added in objective function, new objective function such as formula (43)
It is shown.
minobj(xp,xg)=costcoal+costgas+ρΔ(51)
After above-mentioned processing, continue to be iterated solution using the PCCP-GBD bilayer distributed algorithm.The present embodiment
The PCCP condition of convergence of setting is | objk-objk-1|≤ε1|objk-1| and max δ≤ε2, wherein ε1And ε2For previously given receipts
Hold back conditional constant.
Table 1
With 39 node power network of standard IEEE and the natural network establishment of Belgian 20 nodes simulation city as shown in Fig. 4
The SO of monitoring point M1 to M5 under different scheduling modes is drawn in city by simulation result2Concentration is as shown in Fig. 5.Wherein scene 1: no
Count atmosphere pollution and CO2Discharge only considers energy supply cost.Overall goal is min costcoal+costgas.Scene 2: do not consider
The diffusion of atmosphere pollution space-time and CO2Discharge minimizes Air Pollutant Emission total amount.Overall goal is minQSO2/QSO2,0+
QNOx/QNOx,0+QTSP/QTSP,0.Scene 3: considering the diffusion of atmosphere pollution space-time, minimizes pollutant and contributes total amount.
Overall goal isAs shown in Fig. 5,2 prediction emission of scene and scene 3 consider the concentration tribute of pollutant spatial and temporal distributions
The case where offering relative scene 1 consideration energy supply cost of control all makes air quality obtain certain improvement, but scene 3 is due to needle
Densely inhabited district is optimized, urban pollutants contribution of concentration fall is more significantly larger than scene 2.In combination with table
1 as can be seen that consider that the contribution of concentration control of 3 pollutant spatial and temporal distributions of scene can be with lower than 2 prediction emission of scene
Cost preferably improve the air quality of objective area.
Claims (7)
1. considering the interconnection system distributed Optimization Scheduling of electric-gas of air pollution diffusion, which is characterized in that including following step
It is rapid:
Step 1: establishing includes power network model, the entirety of natural gas network model and atmosphere pollution space-time diffusion model
Optimized model, it is desirable that the form of the non-convex difference for being constrained to convex function in model built；
Step 2: for all models in step 1 by penalizing convex-concave (PCCP)-broad sense Benders (GBD) to decompose double-layer lap generation
Method is optimized with energizing the minimum target of cost, obtains the pollutant concentration at each air monitoring point as its pollution
Concentration；
Step 3: the pollution concentration that mark is changed being constructed as base value using the benchmark pollution concentration in step 2 and contributes total amountIndex；
Step 4: increasing atmosphere pollution constraint for the global optimization model in step 1.
Step 5: for be added to atmosphere pollution constraint model by penalize convex-concave-broad sense Benders bilayer alternative manner for
The energy minimum target of cost optimizes.The management and running of electrical interconnection system are instructed with optimum results.
2. the interconnection system distributed Optimization Scheduling of electric-gas of air pollution diffusion is considered according to claim 1, it is special
Sign is, in step 1, description pollution is described as the atmosphere pollution space-time diffusion model using Gauss cigarette group model
Continuous plume is regarded as and is made of a series of cigarette group of Driftdiffusions in an atmosphere by the spatial diffusion process of object, the model；
In scheduling model, the time step Δ t of the variables such as unit output, gas source power output is referred to as scheduling slot；When will dispatch
It is Δ τ=Δ t/M discharge period that section, which is further subdivided into M step-length,；Each discharge period discharges a cigarette group and represents in the period
The pollutant of discharge, and in each scheduling slot it is all discharge the periods cigarettes group quality be equal scheduling slot index indicated with t,
Segment index is indicated with τ when discharge, and τ ∈ t indicates that discharge period τ is the segmentation in scheduling slot t；If generator i is arranged in τ ' the period
The cigarette group that a quality is Q (τ ') is put, then its contribution of concentration C to the period monitoring point τ (x, y, z)iAre as follows:
Ci(τ ', τ, x, y, z)=Qi(τ′)×Gi(τ′,τ,x,y,z) (1)
Distribution function GiCalculating such as formula (2) shown in, wherein ψ is to indicate intermediate variable convenient and being arranged, and e is natural constant
2.71828..；
σx(τ',τ)、σy(τ',τ)、σz(τ ', τ) is diffusion parameter of the cigarette group in τ period x, y, z axis direction of τ ' period respectively；xi
(τ',τ)、yi(τ',τ)、zi(τ ', τ) is centre coordinate of the cigarette group in the τ period；Diffusion parameter calculating formula are as follows:
In formula, subscript α represents x, y, z axis, aα(τ),bα(τ) is constant related with atmospheric stability grade；Cigarette cluster centre coordinate can be by
Wind friction velocity in cigarette group's motion process calculates as follows:
(x in formulai,0,yi,0) be generator i position coordinates, zi,0The high, [v for its effective emission sourcex(n),vy(n),vz(n)]TFor
Wind velocity vector；
With the diffusion of cigarette group, its concentration constantly reduces until can be ignored；Assuming that after the cigarette group W discharge period of release i.e.
No longer have an impact to the concentration of monitoring point, if electric-gas interacted system (Integrated Power and Gas System,
IPGS there is N in)GA generator, then IPGS is W before this discharge period institute in the contribution of concentration C (τ, j) of period τ to monitoring point j
Have generator discharge contribution of concentration and, i.e.,
The pollutant concentration contribution margin of one scheduling slot is the average value that it is respectively segmented, and monitoring point j's is averaged in scheduling slot t
Concentration are as follows:
。
3. the interconnection system distributed Optimization Scheduling of electric-gas of air pollution diffusion is considered according to claim 1, it is special
Sign is that in step 3, the pollution concentration contributes total amountCalculation formula it is as follows:
Cj,tIt is monitoring point j obtained in step 2 in the benchmark pollution concentration of period t, T is the set of all scheduling slots, Cbase
For the weighting concentration and ω of each monitoring pointjFor the weight of monitoring point j, its environment tolerance, C are depended onj,t,0It is IPGS pairs
The integrated concentration contribution margin of all monitoring points.
4. the interconnection system distributed Optimization Scheduling of electric-gas of air pollution diffusion is considered according to claim 1, it is special
Sign is that in step 1, the electrical network model is using simplified DC power flow description:
θslack,t=0 (10)
rd≤PG,t-PG,t-1≤ru(14)
AGPG,t-Bθt-PD,t=0 (15)
Wherein, scheduling slot index indicates that segment index is indicated with τ when discharge with t, and τ ∈ t indicates that discharge period τ is scheduling slot t
In segmentation, θslack,tFor balance nodes voltage phase angle, θtFor node voltage phase angle vector, xijFor the reactance of route i-j,For
Route active power limit value, "-" and " _ " and the bound for representing relevant variable, ΩPBFor electric power networks node set, ΩGCFor
Coal unit set, ΩGTFor Gas Generator Set set, PG,tFor generator power phasor, rdAnd ruRespectively unit is downwardly and upwardly
Climbing rate vector of valae；Formula (15) is the constraint of node active balance, wherein AGIt is electric power networks node-unit incidence matrix with B
And node admittance matrix imaginary part, PD,tFor node load vector；Formula (16) and formula (17) are respectively coal unit and Gas Generator Set
Consumption equation, PGC,i,tAnd PGT,i,tThe respectively active power output of coal unit i and Gas Generator Set i in the t period, DGC,i,tWith
fGT,i,tRespectively corresponding unit time coal consumption and air consumption, ai,bi,ciAnd αi,βi,γiFor consumption characteristic coefficient；Formula
(18) cost incoalFor coal totle drilling cost, PC,iFor the purchase coal price lattice of unit i；
The power generation discharge amount of unit in electric power networks is expressed as
Total emission volumn in emission ξ mono- day indicates are as follows:
Wherein subscript ξ represents different emissions, such as SO2, CO2, hi,ξ、gi,ξTo discharge constant accordingly.
5. the interconnection system distributed Optimization Scheduling of electric-gas of air pollution diffusion is considered according to claim 1, it is special
Sign is that in step 1, the natural gas network model is as follows:
Asfs,t-APfP,t-fD,t=0 (22)
pc,ij,t≤R×pi,t,ij∈Ωact(24)
Ω in formulapassAnd ΩactRespectively compressor-free and there is Compressor Pipes set；Formula (21) is the steady-state gas flow side Weymouth
Journey, wherein fij,tFlow for pipeline ij in the t period, pi,tAnd pj,tFor the air pressure of node i and node j, Kij> 0 transmits for pipeline
Constant；Formula (22) describes node air balance, ASFor node gas source incidence matrix, fS,tGo out force vector, A for gas sourcePFor node pipe
Road incidence matrix, fP,tFor chimneying vector, (its element is equal to corresponding fij,t), fD,tFor node load vector；Formula (23) table
Show node air pressure range；Formula (24) is the constraint of air pressure containing compressor, pc,ij,tFor compressor outlet air pressure, R is that compressor most rises higher
Pressure ratio, formula (25) are the gas flow equation containing Compressor Pipes；Cost in formula (26)gasTo purchase gas totle drilling cost, PS,iGas source i's is natural
Gas price lattice.
6. the interconnection system distributed Optimization Scheduling of electric-gas of air pollution diffusion is considered according to claim 1, it is special
Sign is, in step 2, the PCCP-GBD bilayer alternative manner the following steps are included:
The archetype for remembering step 1 is model 1.
Step 2.1: ignore the non-convex constraint for the difference that form in model 1 is two convex functions, it will most using generalized benders decomposition
Excellent electric-gas energy flow problem splits into power grid primal problem and natural gas grid subproblem carries out distributed optimization；Benders is recorded to decompose
It solves the feasible of formation and cuts constraint；
Step 2.2: form in model 2 of rewriting is the non-convex constraint of the difference of two convex functions: for equality constraint, being first converted to one
A form is more than or equal to 0 and a form is two inequality constraints less than or equal to 0, is the difference of two convex functions by form
Inequality be rewritten into the form less than or equal to 0；Such as A-B=0 is converted toWherein A and B respectively represents one
Convex function.Remember that revised model is model 2；
Step 2.3 by step 2.1 generate it is feasible cut constraint and be added in model 2, be denoted as model 3；
Step 2.4: the convex function that symbol is negative in the inequality constraints for the difference that the form in model 3 is two convex functions is used
Taylor's formula carries out first order Taylor expansion in given initial point, increases non-negative slack variable being less than or equal to a number the right, will
The sum of all slack variables are added with original objective function as new objective function multiplied by a penalty coefficient；It is described given
Initial point is the value of relevant variable in step 2.1 result in first time iteration, in step 2.5 result in successive iterations
The value of relevant variable；It is denoted as model 4；
Step 2.5: model 4 being split into the gentle net problem of power grid primal problem using generalized benders decomposition and carries out distribution
Optimization；
Step 2.6: PCCP convergence being carried out to the result of step 2.5 and is examined, stops calculating if having restrained and exports optimum results；
With the calculated result of step 2.5 for new initial point return step 2.4 if not converged.
7. the interconnection system distributed Optimization Scheduling of electric-gas of air pollution diffusion is considered according to claim 6, it is special
Sign is that accepted standard is examined in the PCCP convergence in the step 2.6 are as follows:
|objk-objk-1|≤ε1|objk-1| and max δ≤ε2
Wherein ε1And ε2For previously given condition of convergence constant, objkFor the target value of current iteration acquired, objk-1It is upper
The target value that secondary iteration acquires, δ be claim 6 step 2.4 on the right side of inequality increased slack variable set, max δ table
Show the maximum value in all slack variables.
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