CN109800906A - Distributing net and power distribution network Joint economics dispatching method towards new energy consumption - Google Patents
Distributing net and power distribution network Joint economics dispatching method towards new energy consumption Download PDFInfo
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Abstract
The invention discloses a kind of distributing net towards new energy consumption and power distribution network Joint economics dispatching methods, comprising: carries out state analysis to distributing net, obtains node head, pipeline flow, and calculate electrical power consumption of water pump using the active power of τ period water pump p；Distributing net is approximately load bus access power distribution network, carries out distribution power flow analysis by the active and reactive power equilibrium based on power distribution network node i, obtains node voltage, line power stream, distributed generation resource power generation consumption rate and higher level's power grid purchase of electricity；The adaptive value that each particle is calculated according to the objective function of economic optimum judges whether each particle meets distributing net and power distribution network operation constrains using multiple constraint conditions；According to itself optimal solution of feasibility rule more new particle and globally optimal solution；Global search is carried out based on simulated annealing, updates globally optimal solution again, if reaching the iteration upper limit, globally optimal solution is exported, generates distributing net power distribution network Joint economics operation plan.The present invention solves that city distributing net operation power charge is excessively high, the difficult problem of power distribution network distributed energy consumption.
Description
Technical field
The present invention relates to power distribution network-distributing net joint optimal operation method, it is suitable for saving city distributing net operation power charge,
And promote the horizontal field of distribution system renewable energy consumption more particularly to a kind of distributing net and distribution towards new energy consumption
Net Joint economics dispatching method.
Background technique
In traditional sense, power distribution network is respectively independently operated with city distributing net.To distributing net, if being usually mounted with
Dry electricity water pump, to overcome topography difference and loss due to duct friction, guarantee urban water supply reliability.In actual operation, water distribution
Net operation power charge is higher, and wherein water pump electricity charge accounting is very big；In addition, in order to guarantee the reliability to supply water, reservoir in distributing net
It is in full water state multi-period greatly, virtually reduces the economy and flexibility of distributing net operation.
It is general that water pump access point is only regarded as load point to power distribution network, distributing net cannot be regarded as to the adjustable money of load side
Source plays its soft readjustment potentiality；As distributed energy largely accesses, power distribution network also faces distribution type renewable energy consumption
Difficult problem.
Foreign countries have some researchs and point out power distribution network and distributing net is close association in actual operation, and proposing can will
Water energy interacted system is combined into city distributing net with (defeated) power grid to be comprehensively considered[1-2], but correlative study is also in starting
Stage；Have some researchs and passes through water pump gearshift adjustment[3]Or control water pump is run in electricity price low ebb period[4]Etc. modes reduce water
The pump operation electricity charge, but distributing net is not regarded as flexible load from power grid angle and is used.
Summary of the invention
The present invention provides a kind of distributing net towards new energy consumption and power distribution network Joint economics dispatching method, the present invention
Solve that city distributing net operation power charge is excessively high, the difficult problem of power distribution network distributed energy consumption can using the frequency conversion of water pump
The storage capacity of tonality and reservoir regards distributing net as power distribution network flexible load resource, described below:
A kind of distributing net and power distribution network Joint economics dispatching method towards new energy consumption, which comprises
1) state analysis is carried out to distributing net, obtains node head, pipeline flow, and utilize the active of τ period water pump p
Power calculation water outlet pump power consumption；
It 2) is approximately load bus access distribution by distributing net based on the active and reactive power equilibrium of power distribution network node i
Net carries out distribution power flow analysis, obtains node voltage, line power stream, distributed generation resource power generation consumption rate and higher level's electricity
Online shopping electricity；
3) adaptive value that each particle is calculated according to the objective function of economic optimum judges each grain using multiple constraint conditions
Whether son meets distributing net and power distribution network operation constrains；According to itself optimal solution of feasibility rule more new particle and global optimum
Solution；
4) global search is carried out based on simulated annealing, updates globally optimal solution again, if reaching the iteration upper limit, exports
Globally optimal solution generates distributing net power distribution network Joint economics operation plan；Otherwise it re-execute the steps 1).
The objective function is that association system operating cost is minimum, specifically:
Wherein, operating cost C includes power distribution network operating costAbandonment rejection penaltyAnd water pump operation expense
The multiple constraint condition includes: distributing net operation constraint；Power distribution network operation constraint；And by τ period water pump p's
The distributing net power distribution network coupling constraint of active power, the active and reactive power equilibrium of power distribution network node i composition.
The active power of the τ period water pump p specifically:
In formula: Ep,τFor the active power of τ period water pump p；ρ, g are respectively the density and normal gravity coefficient of water；h0、rpWith
npFor parameters of pump, can be obtained by the head curve that producer provides；ωp,τFor the relative rotation speed of τ period water pump p, the embodiment of the present invention
Assuming that ω in the periodp,τIt remains unchanged；Qp,τFor the flow of τ period water pump p；ηpFor water pump pump machine efficiency
The active and reactive power equilibrium of the power distribution network node i couples distributing net with power distribution network, specifically:
In formula: Epi,τFor the water pump active power at τ period node i；β is pump power factor；WithRespectively
Active power and reactive power when water pump power consumption are not counted at τ period power distribution network node i；Pri,τAnd Qri,τThe respectively τ period
Active power and the reactive power injection of distributed generation resource at point i；Vi,τAnd Vj,τThe respectively voltage magnitude of node i and node j；
GijAnd BijRespectively node i, the real and imaginary parts of admittance between j；θij,τPhase angle difference for node i, between j.
The beneficial effect of the technical scheme provided by the present invention is that:
1, this method can adjust water pump power output, control reservoir under the premise of meter and power distribution network, distributing net security constraint
Flexible water storage makes the period that water pump operation is big in distributed energy power output and electricity price is low, is saving association system operating cost
Meanwhile the consumption for promoting renewable energy is horizontal；
2, example statistics indicate that, this method can make association system totle drilling cost save 12.76%, wherein distributing net operating cost
41.39% can be reduced, and effectively lifting system renewable energy can dissolve level；
3, this method can promote power distribution network, distributing net dispatching flexibility, alleviate part water pump in the distributing net of city and frequently open
The problem of stopping；Facilitate the quality of voltage of improvement power distribution network；
4, according to this method, reservoir can regard the energy-storage units of distributing net Yu power distribution network association system as, and capacity can shadow
Association system management and running are rung, suitable reservoir capacity can make distributing net power distribution network combined dispatching reach economic optimum.
Detailed description of the invention
Fig. 1 is the schematic diagram of power distribution network and distributing net association system；
Fig. 2 is the topological schematic diagram of distributing net；
Fig. 3 is the flow chart of a kind of distributing net towards new energy consumption and power distribution network Joint economics dispatching method.
Fig. 4 is the IEEE-33 node power distribution net system schematic containing distributed wind-power generator；
Fig. 5 is the improved distributing net Richmond system schematic；
Fig. 6 is power distribution network daily load curve in embodiment 3；
Fig. 7 is blower power prediction curve in embodiment 3；
Fig. 8 is the variation of the Sino-Japan purchase electricity price of embodiment 3；
Fig. 9 is each wind turbine power generation consumption rate under 3 middle part branch scape of embodiment；
Wherein, line is scene I one by one, and --- -- line is scene II.WT1-WT3 is the number of three Fans.
Figure 10 is water pump 24 hours relative rotation speeds in part under different scenes in embodiment 3；
Wherein, (a) is water pump 1A, (b) is water pump 3A, (c) is water pump 4B, (d) is water pump 5C, (e) is water pump 6D.
Figure 11 is each reservoir of scene II moisture storage capacity variation in 24 hours in embodiment 3；
Wherein, (a) is reservoir A, (b) is reservoir B, (c) is reservoir C, (d) is reservoir D, (e) is reservoir
E (f) is reservoir F.
Figure 12 is power distribution network node voltage maximum/minimum value in embodiment 3.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, embodiment of the present invention is made below further
Ground detailed description.
Embodiment 1
The embodiment of the present invention couples power distribution network with distributing net by electric water pump, forms a kind of water energy interacted system, herein
On the basis of propose a kind of power distribution network-distributing net joint optimal operation method.
A kind of distributing net and power distribution network Joint economics dispatching method towards new energy consumption, this method includes following step
It is rapid:
101: state analysis being carried out to distributing net, obtains node head, pipeline flow, and having using τ period water pump p
Function power calculation water outlet pump power consumption；
102: distributing net is approximately that load bus access is matched by the active and reactive power equilibrium based on power distribution network node i
Power grid carries out distribution power flow analysis, obtains node voltage, line power stream, distributed generation resource power generation consumption rate and higher level
Power grid purchase of electricity；
103: calculating the adaptive value of each particle according to the objective function of economic optimum, judged using multiple constraint conditions each
Whether particle meets distributing net and power distribution network operation constrains；According to itself optimal solution of feasibility rule more new particle and global optimum
Solution；
104: global search is carried out based on simulated annealing, updates globally optimal solution again, it is defeated if reaching the iteration upper limit
Globally optimal solution out generates distributing net power distribution network Joint economics operation plan；Otherwise 101 are re-execute the steps.
In conclusion this method makes electric water pump in system that can concentrate on blower/photovoltaic power output larger, electricity price lower period
Operation, helps to solve the problems, such as that the distributing net water pump electricity charge are excessively high, and it is horizontal effectively to promote the consumption of distribution system new energy.
Embodiment 2
The scheme in embodiment 1 is further introduced below with reference to Fig. 1-Fig. 3, described below:
One, power distribution network-distributing net association system
1.1 joint optimal operation physical basis
Fig. 1 provides a power distribution network-distributing net association system schematic diagram.Comprehensive energy service provider from higher level's power grid power purchase,
Reservoir/water factory's water is deployed simultaneously, is combined by water pump with reservoir and intra domain user offer water and electricity supply service in area's is provided.
Power distribution network utilizes the frequency property of water pump, and water pump access point is regarded as flexible load node and is regulated and controled, is being guaranteed
Under the premise of the hydraulic pressure of distributing net, optimization water pump power output, auxiliary improves power distribution network operating condition.If wind-powered electricity generation/photovoltaic power output is big, system
Electricity price is low, then increases water pump power output, and water is transmitted to reservoir storage；Conversely, then by reservoir/water factory and reservoir jointly to pipe
Net water delivery maintains hydraulic pressure, and water pump then even shut down by low-frequency operation, reduces electricity consumption.Reservoir water storage and water distribution are operated with dampening
Potential variation, play the role of energy storage.The coordinated operation of reservoir and water pump is the base of power distribution network Yu distributing net combined dispatching
Plinth.
The modeling of 1.2 distributing nets
1.2.1 waterpower compensating computation model
Water distribution net topology schematic diagram is as shown in Figure 2.Assuming that distributing net shares nwA node (including connecting node, reservoir
Node and reservoir node) and lwBranch (including water pump branch, valve branch and water delivery pipeline section), wherein containing ntA reservoir and
nvA water pump.Waterpower compensating computation is to ask each node head and each branch stream in distributing net under node reservoir storage known conditions
Amount, essence are to solve for distributing net steady-state operation point.Assuming that when a dispatching cycle [0, T] is by N number of continuous and isometric scheduling
Section Δ t composition, when segment number τ=1,2,3...N.Since state change is slower in water distribution network management, this method is approximately considered pipeline section
Middle water velocity remains unchanged in a scheduling slot.The core of waterpower compensating computation is node flow continuity equation and branch
Road head equation, such as formula (1), (2) are shown.
In formula: i, j are node serial number, i, j=1,2 ..., nw；qi,τFor τ period node i water requirement；Qij,τIt is managed for the τ period
The flow of section ij；For the height above sea level of node i；hi,τFor the node pressure head of τ period node i；Δhij,τTo connect i, j
Branch head loss；J ∈ i indicates that j node is the node being connected with i.
The embodiment of the present invention assumes that capacity reservoir is sufficiently large, and head approximate constant, as shown in formula (3).
In formula: hrs,τFor the head of τ period reservoir rs；For the initial head of reservoir rs.
N to any time period τ, in addition to reservoirw- 1 node can be arranged according to formula (1) writes nw- 1 node flow continuity side
Journey；lwBranch can arrange according to formula (2) and write lwA branch head equation.Thus the equation group formed shares nw+lw- 1 equation, nw
+2lw- 1 unknown quantity (n including removing reservoirw- 1 node head, lwA bypass flow and lwA branch head loss).To ask
Solving equations require supplementation with lwA Δ hij,τExpression formula.
1) water pump: the head loss Δ h of τ period water pump pp,τFor the opposite number of its lift, can be calculated according to its head curve,
As shown in formula (4).
In formula: h0、rpAnd npFor parameters of pump, can be obtained by the head curve that producer provides；ωp,τFor the phase of τ period water pump p
To revolving speed, and the ω within the periodp,τIt remains unchanged；Qp,τFor the flow of τ period water pump p.
2) valve: shown in the head loss such as formula (5) of τ period valve jm.
In formula: Δ hjm,τFor the head loss of τ period valve jm；mjmFor the waterhead fall of valve jm；Qjm,τWhen for τ
The flow of section valve jm.
3) water delivery pipeline section: the head loss of τ period pipeline section ij is calculated by Darcy-Weisbach formula[5], such as formula (6) institute
Show.
In formula: Δ hij,τFor the head loss of τ period water delivery pipeline section ij；Qij,τFor the flow of τ period water delivery pipeline section ij；rij
For equation coefficients；fijFor pipeline section ij coefficient of friction, LijAnd DijThe respectively length and diameter of pipeline section ij；G is acceleration of gravity.
Formula (4)-(7) are substituted into formula (2), original equation group can meet solution and require, and can be asked with Todini-Pilati method
Solution[6], EPANET software realization is utilized herein.
1.2.2 component models constrain
1) node: in addition to reservoir, any water requirement is greater than 0 node, and pressure head should be greater than least favorable service head
(technical term of this field)[7], as shown in formula (8).
In formula: hi,τFor the pressure head of τ period node i；For the least favorable service head of node i；If node needs water
Amount is 0, then only needs hi,τ>0。
2) reservoir: in a certain period shown in the change of water level of reservoir c such as formula (9).
In formula: hc,τAnd hc,τ-1Head of the respectively reservoir c in τ and (τ -1) period initial time；AcFor reservoir c's
Average traversal area；Qic,τ-1For the pipeline section ic that is connected with reservoir c (τ -1) period initial time pipeline flow；τ=2,
3,4,...N；The initial head of reservoirIt is known.
The capacity and water-in and water-out flow restriction of reservoir are respectively as shown in formula (10) and (12).The feed water flow of reservoir c
Measure Rc,τWith water flow ZC, τIt is provided by formula (11).
In formula:WithThe respectively upper and lower bound of reservoir c head；For the maximum inlet/outlet of reservoir c
Flow.
Assuming that the power distribution network low power consumption period is the preceding N of a dispatching cycle0A scheduling slot, ckIndicate k-th of water storage
Pond.Reservoir utilizes water pump water storage in the power distribution network low power consumption phase, and during this period, reservoir total moisture storage capacity in distributing net need to be greater than 0,
As shown in formula (13):
In formula:For with reservoir ckConnected pipeline section ickIn the pipeline flow of (τ -1) period initial time；τ=2,
3,...,N0+1。
In addition, being a periodic scheduling under the influence of avoiding, at the end of this dispatching cycle, water storage pool water level is not lower than initial
Water level, as shown in formula (14).
In formula: k=1,2,3 ... nt。
Relative rotation speed is no more than its upper limitAs shown in formula (15)
In formula: ωp,τFor the relative rotation speed of τ period water pump p.
Water pump is unidirectionally to draw water.Its flow and head loss should meet formula (16) in any time period.
Δhp,τ≤0,Qp,τ≥0 (16)
In formula: Δ hp,τFor the head loss of τ period water pump p；Qp,τFor the flow of τ period water pump p.
The electricity consumption E of τ period water pump pp,τIt can be calculated by formula (17).
In formula: ρ, g are respectively the density and acceleration of gravity of water；ηpIt, can by Pump Efficiency Curve for water pump pump machine efficiency
?.
Valve: not allowing to flow backwards under valve opening state, as shown in formula (18).
Wherein, Qjm,τFor the flow of τ period valve jm.
1.3 Modeling of Distribution Network
1.3.1 power flow algorithm
Assuming that power distribution network has leBranch, neA node, node 1 are balance nodes, and node 2 arrives node 1+npvFor PV section
Point, remaining node are PQ node.From power grid absorbing reactive power when fan operation, also regard PQ node as[8], and dispatched at one
In period, the active power of distributed generation resource is invariable.Load flow calculation essence is to determine power distribution network according to node power equation
Operating status[9-10], as shown in formula (19).
In formula: Pri,τAnd Qri,τThe active and reactive power of distributed generation resource respectively at τ period node i；With
The respectively active and reactive power of node i load；Vi,τAnd Vj,τThe respectively voltage magnitude of node i and node j；GijAnd Bij
Respectively node i, the real and imaginary parts of admittance between j；θij,τPhase angle difference (i, j=1,2 ..., n for node i, between je)。
1.3.2 operation constraint
1) quality of voltage: power distribution network node voltage need to be maintained at a certain range, as shown in formula (20).
In formula:WithThe respectively upper and lower bound of node i voltage magnitude；I=1,2,3..., ne。
2) operational safety: line transmission power must not exceed its maximum power, as shown in formula (21).
In formula: Pl,τFor the transimission power of τ period route l；For the maximum power of route l；L=1,2,3..., le。
1.4 power distribution network distributing nets couple link modeling
Distributing net is coupled with power distribution network using water pump.Joint type (4), (17) first obtain being turned by water pump is opposite
Fast ωp,τ, pump capacity QP, τThe water pump active power of expression, as shown in formula (22).
In formula: Ep,τFor the active power of τ period water pump p；ρ, g are respectively the density and normal gravity coefficient of water；h0、rpWith
npFor parameters of pump, can be obtained by the head curve that producer provides；ωp,τFor the relative rotation speed of τ period water pump p, the embodiment of the present invention
Assuming that ω in the periodp,τIt remains unchanged；Qp,τFor the flow of τ period water pump p；ηpFor water pump pump machine efficiency.
Joint type (19), (22) obtain formula (23).Formula (23) indicate power distribution network node i active for being connected with water pump p and
Power distribution network is accessed in distributing net by reactive power equilibrium in the form of water pump power consumption, to make water pump relative rotation speed, pump capacity
And distributed generation resource power output combines, and realizes distributing net and power distribution network in the coupling of mathematics level, distributing net and power distribution network
Thus it is able to carry out Holistic modeling.
In formula: Epi,τFor the water pump active power at τ period node i, calculated by formula (22)；β is pump power factor；WithActive power and reactive power when water pump power consumption are respectively not counted at τ period power distribution network node i；Pri,τWith
Qri,τActive power and the reactive power injection of distributed generation resource respectively at τ period node i；Vi,τAnd Vj,τRespectively node i
With the voltage magnitude of node j；GijAnd BijRespectively node i, the real and imaginary parts of admittance between j；θij,τFor node i, between j
Phase angle difference (i, j=1,2 ..., ne)。
Distributing net and power distribution network are coupled by formula (22)-(23) in the form of water pump power consumption, are to realize that distributing net-is matched
The key of power grid joint Optimized Operation and basis.
2 distributing net power distribution network Joint economics scheduling models
2.1 distributing net power distribution network Joint economics scheduling mathematic models
Based on formula (22), (23) and aforementioned model built, with distributing net-minimum mesh of power distribution network association system operating cost
Mark constructs systematic economy scheduling model, as shown in formula (24)-(26).
Formula (24) is the objective function of Optimized Operation, i.e. association system operating cost is minimum, and operating cost C includes power distribution network
Operating costAbandonment rejection penaltyAnd water pump operation expenseFormula (1)-(18) are distributing net operation constraint；
Formula (19)-(21) are power distribution network operation constraint；Formula (22)-(23) are that distributing net power distribution network couples link；Formula (9)-formula (14) is
The multi-period cooperative scheduling of reservoir, water pump, power distribution network creates condition；Reservoir water storage optimizes by adjusting water storage in formula (11)
The flow of inlet water R in pondc,τWith water flow Zc,τIt realizes.
S.t. (1)-(18), (19)-(21), (22)-(23)
In formula: (1)-(18), (19)-(21), (22)-(23), the constraint condition of (25)-(26) as formula (24).
Wherein, Epi,τFor the water pump active power at τ period node i；Pri,τAnd Qri,τRespectively τ period node i punishes cloth
The active and reactive power of formula power supply；Indicate that distributed electrical source node r is not connected with node i；Indicate distributing net water
Pump p is not connected with node i.
To distributing net power distribution network carry out joint optimal operation, be meet distributing net power distribution network operation constraint under the premise of,
Seek the operation plan for meeting formula (24), optimized variable includes day part water pump relative rotation speed ω in dispatching cyclep,τ, water storage
Pond inlet/outlet flow Rc,τAnd Zc,τ。
In the power distribution network Joint economics scheduling model of distributing net: the operating status of distributing net, which utilizes, is based on Todini-
The tool box the Epanet Embedding function of Pilati method carries out analytical calculation[5]；Distribution Running State passes through distribution power flow point
Analysis, which calculates, to be determined[11]。
1) power distribution network operating cost
Power distribution network operating cost is the sum of system superior power grid power purchase expense and line loss cost, such as formula (27) institute
Show.
In formula:And Cl,τRespectively τ period purchase electricity price and line loss unit cost；WτFor τ period purchase of electricity；ΔSl,τ
For τ period branch l line loss.
2) abandonment is punished
Shown in system abandonment rejection penalty such as formula (29)[12]。
In formula: CpenFor abandonment penalty coefficient；Pr,τFor the practical power output of τ period blower；Wav,τIt is expected for τ period blower
Power.
Formula (30) defines system wind electricity digestion rate η.
η=Pr,τ/Wav,τ (30)
3) water pump operation expense
Distributing net operating cost is mainly the water pump electricity charge, and k-th of water pump is expressed as p in distributing netk, τ period water pump operation
Shown in expense such as formula (31).
In formula: CτFor water pump unit price of power；For the power consumption of k-th of water pump of τ period.
2.2 model solution
Distributing net power distribution network Joint economics scheduling model in the embodiment of the present invention contains that there are many schedulable resources and many
Complex nonlinear constraint, is the non-convex nonlinear problem of typical higher-dimension, and this method uses the improvement particle based on feasibility
Group's method realizes the solution of distributing net power distribution network Joint economics scheduling mathematic model.
Improvement particle swarm optimization based on feasibility combines conventional particle group's method with simulated annealing, and introducing can
Row rule, it may be assumed that feasible solution is always better than infeasible solution；In two feasible solutions, the solution for obtaining more preferable target function value is preferential；Two
In a infeasible solution, the lesser solution of constraint violation value is preferential.The introducing of feasibility rule is so that in processing problem containing constrained optimization
When can separate and consider objective function and constraint violation.Wherein, feasibility rule is known to those skilled in the art, the present invention
Embodiment does not repeat them here this.
Objective function in the embodiment of the present invention is (24), and constraint violation situation is to constraint (1)-(18), (19)-(21)
And constraint (22)-(23) and (25)-(26) violate the sum of absolute value of index and indicate.According to feasibility rule, feasible solution is always
Better than infeasible solution, it is excessive that this is likely to result in the search pressure to feasible solution, leads to algorithm Premature Convergence, falls into part most
It is excellent.In consideration of it, the improvement particle swarm optimization based on feasibility introduces simulated annealing, part is jumped out using its probabilistic jumping property most
It is excellent, avoid Premature Convergence.Concrete principle is detailed in document [13].
Using the improvement particle swarm optimization based on feasibility, the solution procedure of the Optimal Operation Model in the embodiment of the present invention is such as
Under, flow chart is shown in Fig. 3.
Step 1: user demand of the comprehensive energy service provider to distributing net in dispatching cycle and power distribution network, water pump electricity price and point
Cloth energy power output is predicted.Improvement particle swarm algorithm optimized variable (day part in dispatching cycle based on feasibility is set
Water pump relative rotation speed ωp,τ, reservoir inlet/outlet flow Rc,τAnd Zc,τ) initial space, be arranged target function type (24) and its
Corresponding constraint formula (1)-(18), (19)-(21), (22)-(23) and (25)-(26).Initialization improves particle swarm algorithm to generate
Initial population and corresponding particle rapidity.
Step 2: using Todini-Pilati method to distributing net carry out state analysis, obtain distributing net node head,
Pipeline flow and utilization formula (22) calculated electrical power consumption of water pump.
Step 3: using formula (23) by distributing net be approximately load bus access power distribution network, carry out distribution power flow analysis.
Obtain node voltage, line power stream, distributed generation resource power generation consumption rate and higher level's power grid purchase of electricity.
Step 4: the adaptive value (target function value) of each particle is calculated according to formula (24)；Utilize formula (1)-(18), (19)-
(21), (22)-(23) and (25)-(26) calculate violation of each particle to the operation constraint of distributing net power distribution network；It is advised according to feasibility
Then more new particle itself optimal solution pbest and globally optimal solution gbest.
Step 5: the global search based on simulated annealing is carried out, updates gbest again, it is defeated if reaching the iteration upper limit
Gbest out generates distributing net power distribution network Joint economics operation plan；Otherwise 2 are gone to step.
In conclusion this method can adjust water pump power output, control under the premise of meter and power distribution network, distributing net security constraint
The flexible water storage of reservoir processed makes the period that water pump operation is big in distributed energy power output and electricity price is low, is saving association system fortune
While row cost, the consumption for promoting renewable energy is horizontal.
Embodiment 3
Below with reference to specific experimental data, column are calculated to the scheme progress feasibility verifying in Examples 1 and 2, are detailed in down
Text description:
Experimental enviroment: computer one: Inter (R) Core (TM) i5-6300HQ CPU, memory: 8.00GB；Software loop
Border: Windows10 64, matlab version: 9.0.0.341360 (R2016a), EPANET2 version: 2.00.12
(EPANET2)。
3.1 simulation parameter
Construct the IEEE-33 node power distribution net containing blower[14](Fig. 4) and the improved distributing net Richmond[15,16](Fig. 5)
Example is coupled, carries out 24 hours Optimized Operations using context of methods.All water pumps and reservoir both participate in adjusting.0-7 Shi Weiyong
Electric low-valley interval.Distribution network voltage a reference value 12.66kV, it is desirable that power distribution network node voltage fluctuating range is no more than 7%[17].Match
Power grid daily load curve[18], power of fan prediction curve[19-20]Respectively as Figure 6-Figure 7,24 hours purchase electricity price songs of system
Line is as shown in Figure 8[21], other simulation parameters[22-23]Referring to following table.
It is influenced for the scheduling of research distributing net power distribution network Joint economics and its by reservoir capacity in distributing net, is chosen herein
Power distribution network/distributing net independently dispatch with joint optimal operation under four kinds of scenes, formulate 24 hours operation plans a few days ago, each tune
Spending period interval is 1 hour.
Scene I: the respective independent operating in power distribution network/distributing net；
Scene II: power distribution network-power distribution network joint optimal operation, remaining parameter are identical as scene I；
Scene III: scene III is divided into two kinds of scenes of III-A and III-B again.In scene III-A and III-B, distributing net
Interior each reservoir capacity is reduced to the 50% and 25% of former capacity respectively, remaining parameter is identical as scene II；
Scene IV: scene IV is divided into two kinds of situations of IV-C and IV-D again.In scene IV-C and IV-D, respectively stored in distributing net
Pond capacity is increased separately to the 125% of former capacity and 150%, remaining parameter is identical as scene II.
3.2 analysis of simulation result
3.2.1 optimum results compare
System wind electricity digestion rate is respectively such as table 1 under power distribution network/distributing net operating cost and part scene under different scenes
With shown in Fig. 9.
Day operation expenses statement under 1 different scenes of table
Tab.1 Daily operation cost of diffrent scenarios
In conjunction with table 1 and Fig. 9: totle drilling cost is 19275.96 yuan in system one day in scene I, and distributing net operating cost is higher,
Abandonment punishment is higher, and economy is poor.In terms of wind electricity digestion, blower power output is larger when 0-3, and electric load very little, blower at three
All there is wind-abandoning phenomenon, abandonment rate is higher.Up to 100%, system abandonment pressure disappears wind electricity digestion rate after when 3；In scene II
628.98 yuan of distributing net operating cost, 41.39% is reduced than scene I, abandonment punishment completely eliminates, distribution network loss and the electricity charge
It is reduced.One day totle drilling cost of system saves 12.76% than scene I, and economy is obviously improved.In terms of wind electricity digestion, system is each
Period wind electricity digestion rate up to 100%, effectively solves the problems, such as abandonment；One day totle drilling cost of system increases compared with scene II in scene III-A
Add, increases to 17395.61 yuan by 16817.13 yuan, have no wind-abandoning phenomenon；In scene III-B, system synthesis sheet is compared with scene III-
A is further increased, and at this time since reservoir storage capacity is limited, and distributing net can not dissolve wind energy more than needed completely, is occurred
Wind-abandoning phenomenon；In scene IV-C, distributing net and power distribution network operating cost are reduced compared with scene II, this reduction of system synthesis and without abandoning
Wind phenomenon；Scene IV-D is suitable with scene IV-C totle drilling cost.
Figure 10 provides water pump 24 hours relative rotation speeds in part in scene I, scene II and scene III-B.
Big in 16-21 hourly water demand due to system in scene I, the reservoir A of hub location should keep high water level, and not
The case where can exceed that maximum stage, water pump 1A, 3A is made to be frequent start and stop is unfavorable for water pump longtime running.By being compared with Fig. 6
As can be seen that water pump operation state and network load peak-to-valley association of characteristics degree are little in scene I.
Water pump operation concentrates on the low power consumption period in scene II.In 0-3, each water pump operation dissolves wind in higher rotation speed
Electricity and be reservoir water storage.Rear fan power output reduces when 3, electric load increases, and system is without wind electricity digestion pressure, each water pump power output
It is corresponding to reduce.When to 7, all water pumps are completely closed.Hereafter only have water pump 5C in 16-19 to meet formula (14) constraint and transport
Turn.It can be seen that water pump operation state is contributed with blower under scene II and electric load is closely related.
Water pump operation situation is similar with scene III-B in scene III-A, although water pump concentrates on the operation of low power consumption period
To dissolve wind-powered electricity generation more than needed, improve water storage pool water level, but since reservoir capacity is smaller, in the water use peak phase water level decreasing compared with
Fastly, water pump 1A-6D need to be operated in the higher 15-19 of electricity price to meet reservoir restriction of water level (14), led to distributing net and matched
Operation of power networks cost increases.In terms of wind electricity digestion, reservoir capacity is smaller compared with scene III-A in distributing net in scene III-B, right
The digestion capability of wind-powered electricity generation is limited, results in certain wind-abandoning phenomenon；In scene IV-C and scene IV-D water pump operation situation then with
It is similar in scene II.
As the above analysis, when reservoir capacity deficiency in distributing net, it not only will affect the economical operation of distributing net,
Also power distribution network economical operation can be impacted, its operating cost is caused to increase, and when reservoir capacity is too small, in distributing net
Reservoir can not dissolve wind energy more than needed, there is also wind-abandoning phenomenon；When reservoir capacity suitably increases in distributing net, not only
Wind-powered electricity generation can be dissolved completely, moreover it is possible to reduce power distribution network distributing net operating cost；When reservoir capacity increases excessive in distributing net,
Power distribution network distributing net operating cost can not further decrease, but also increase reservoir dilatation and maintenance cost.
3.2.2 water pump-reservoir coordinative role
It chooses 24 hours moisture storage capacitys of each reservoir in scene II and changes water pump-water storage when to distributing net power distribution network combined dispatching
The coordinative role in pond is analyzed.
As shown in figure 11, moisture storage capacity is by reservoir actual water level and most flood for the variation of reservoir moisture storage capacity in scene II mono- day
The ratio of position indicates.In conjunction with Figure 10, in 0-3, to dissolve wind-powered electricity generation, each water pump power output is higher, and reservoir B-F receives water pump water storage
Thus water level obviously goes up, and reservoir A proportioning pump 5C, pump 6D in distributing net maincenter, the operation for pumping 7F, are reservoir C-F
Water distribution, water level are declined；In 3-7, though system without wind electricity digestion pressure, still in the electricity price ebb period, due to storing
Pond C, E, F at 3 before reached the water storage upper limit and supplied water to water distribution network users, reservoir A is with water pressure reduction, and this period
Reservoir A, B, D water level does not reach the upper limit, therefore pumps 1A-4B reduction revolving speed and continue to improve corresponding water storage pool water level to reservoir water storage
To meet the total moisture storage capacity constraint of distributing net reservoir.As it can be seen that water pump and reservoir operation are coordinated with each other.
As the above analysis, water pump concentrates on blower and contributes higher, the electric load lower period as water storage in scene II
Pond water storage keeps scheduling result more excellent.
3.2.3 quality of voltage
Power distribution network node is minimum in scene I and scene II lower day and ceiling voltage variation is as shown in figure 12 (with node electricity
Per unit value is pressed to indicate).Each node voltage fluctuation of power distribution network is no more than the 7% of voltage base value under two kinds of scenes, meets electric energy matter
Amount requires[20]。
Scene I is compared, the minimum node voltage of scene II is generally slightly promoted, and shows better quality of voltage.It is right
Than highest node voltage in scene I and scene II: in 0-4, a large amount of power consumptions of water pump, reduce to a certain extent in scene II
Low power consumption phase raised highest node voltage, power distribution network highest node voltage are slightly reduced compared with scene I；In 5-7, in conjunction with figure
6 and Figure 11 is it is found that power distribution network customer charge increases at this time, and only reservoir A and reservoir D continues water storage, water distribution in scene II
Net water pump power consumption is reduced, and power distribution network highest node voltage is slightly raised compared with scene I；Remaining period scene II and scene I highest
Node voltage is almost the same.
Bibliography
[1]Macknick J.A Review of Operational Water Consumption and
Withdrawal Factors for Electricity Generating Technologies[R].National
Renewable Energy Laboratory, 2011.
[2]Santhosh Apoorva,Farid Amro M.,Youcef-Toumi,Kamal.Optimal network
flow for the supply side of the energy-water nexus[C]//Proceedings-2013IEEE
International Workshop on Intelligent Energy Systems,2013:155-160.
[3] Menke R, Abraham E, Stoianov I.Modeling Variable Speed Pumps for
Optimal Pump Scheduling [C] .World Environmental and Water Resources Congress,
2016.
[4]Bunn S M,Reynolds L.The energy-efficiency benefits of pump-
scheduling optimization for potable water supplies[J].IBM Journal of Research
and Devolopment,2009,53(3).
[5]Lewis A.Rossman.EPANET2USERS MANUAL[EB/OL].U.S.Environmental
Protection Agency.https://www.epa.gov/water-research/epanet
[6]Tanyimboh T T.Robust Algorithm for Head-Dependent Analysis of
Water Distribution Systems [C] .Water Distribution Systems Analysis 2008, Kruger
Nationa-l Park, South Africa, 2008.
[7] Todini E, Pilati S.A Gradient Algorithm for the A-nalysis of Pipe
Networks [J] .Computer applications in water supply, 1988,1:1-20.
[8] FEIJOO AE, CIDRAS J.Modeling of Wind Farms in the Load Flow
Analysis [J] .IEEE Trans on Power System, 2000,15 (1): 110-115.
[9]Milano F.Power System[EB/OL].New York:Springer-Verlag Berlin
Heidelberg,2010.http://www.uclm.es/area/gsee/wed/Federico/psat.htm
Electricity of the such as [10] Luo Baifeng, Mu Yunfei, Zhao Bo based on Unified Power Flow model-gas coupling integrated energy system is static
Sensitivity analysis [J] Automation of Electric Systems, 2018 (13)
LUO Bofeng,MU YUNFEI,ZHAOBO,et al.Static Sensitivity Analysis of
Integrated Electricity and Gas System Based on Unified Power Flow Model[J]
.Automation of Electric Power Systems,2018(13):29-35.
[11]Zimmerman R D,Murillo-Sanchez C E.Matpower Users’Manual[EB/OL]
.Power Systems Engineering Research Center.https://www.pserc.cornell.edu/
matpower/MATPOWER-manual.pdf
[12]Miranda V,Hang P S.Economic dispatch model with fuzzy constraints
and attitudes of dispatchers,IEEE Transactions on Power Systems,2005,20(4):
2143-2145.
[13] Qie He, Ling Wang.A hybrid particle swarm optimization with a
feasibility-based rule for constrained optimization[J].Applied Mathematics
And Computation, 2007,186:1407-1433.
[14] Baran M E, Wu F F.Network reconfiglation in distribution systems
For loss reduction and load balancing [J] .IEEE Trans on Power Delivery, 1989,4
(2): 1401-1407.
[15] Guidoin M, Kapelan Z, Savic D.Using high performance techniques to
Accelerate demand-driven hydraulic solvers [J] .Journal of Hydroinformatics,
2013,15 (1): 38-54.
[16]Richmond Water Distribution Network.(2013).
http://emps.exeter.ac.uk/engineering/research/cws/downloads/
benchmarks/.
[17] Standardization Administration of China .GB/T 12325-2008 power quality-supply voltage deviation [EB/
OL] .2008.http: //c.gb688.cn/bzgk/gb/showGb? type=online&hcno=75EBBCF838AA40D
281EDA854B8F63AD7
[18] Qian K, Zhou C, Allan M.Modeling of Load Demand Due to EV Battery
Charging in Distribution Syst-ems [J] .IEEE Transactions on Power Systems, 2011,
26(2):802-810.
[19] Pazouki S, Haghifam M R, Moser A.Uncertainty modeling in optimal
operation of e-nergy hub in presence of wind,storage an-d demand response[J]
.International Journal of Electrical Power&Energy Systems, 2014,61:335-345.
[20] Gu Wei, Lu Shuai, WangJun multizone integrated energy system heat network modeling and running Optimization [J] China electricity
Machine engineering journal, 2017,37 (5): 1305-1315.
GU Wei,LU Shuai,WANG Jun.Modeling of the Heating Network for Multi-
district Integrated Energy System and Its Operation Optimization[J]
.Proceedings of the CSEE,2017,37(5):1305-1315.
[21]New York Independent System Operator[EB/OL]:New York.http://
Www.nyiso.com, 2018-7.
[22]Tanyimboh T T.Robust Algorithm for Head-Dependent Analysis of
Water Distribution Systems[C].International Conference on Water Distribution
Systems A-nalysis, 2018:1-11.
[23] study of the Song Dynasty east, Wang Zengqi, the Journal of Shandong agri.Univ determination [J] of Lv Yan water supply pump frequency converting speed regulating range,
2010,41 (4): 579-582.
SONG XueDong,WANG ZengQi,LvYan.Determination of the Water Pumps
Varying Frequency Speed Regulation Range[J].Journal og Shandong Agricultural
University,2010,41(4):579-582.
It will be appreciated by those skilled in the art that attached drawing is the schematic diagram of a preferred embodiment, the embodiments of the present invention
Serial number is for illustration only, does not represent the advantages or disadvantages of the embodiments.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all in spirit of the invention and
Within principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (5)
1. a kind of distributing net and power distribution network Joint economics dispatching method towards new energy consumption, which is characterized in that the method
Include:
1) state analysis is carried out to distributing net, obtains node head, pipeline flow, and the active power using τ period water pump p
Calculate electrical power consumption of water pump；
It 2) is approximately load bus access power distribution network by distributing net based on the active and reactive power equilibrium of power distribution network node i, into
The analysis of row distribution power flow obtains node voltage, line power stream, distributed generation resource power generation consumption rate and higher level's power grid power purchase
Amount；
3) adaptive value that each particle is calculated according to the objective function of economic optimum judges that each particle is using multiple constraint conditions
It is no to meet distributing net and power distribution network operation constraint；According to itself optimal solution of feasibility rule more new particle and globally optimal solution；
4) global search is carried out based on simulated annealing, updates globally optimal solution again, if reaching the iteration upper limit, exports the overall situation
Optimal solution generates distributing net power distribution network Joint economics operation plan；Otherwise it re-execute the steps 1).
2. a kind of distributing net and power distribution network Joint economics dispatching method towards new energy consumption according to claim 1,
It is characterized in that, the objective function is that association system operating cost is minimum, specifically:
Wherein, operating cost C includes power distribution network operating costAbandonment rejection penaltyAnd water pump operation expense
3. a kind of distributing net and power distribution network Joint economics dispatching method towards new energy consumption according to claim 1,
It is characterized in that, the multiple constraint condition includes: distributing net operation constraint；Power distribution network operation constraint；And by τ period water pump
The distributing net power distribution network coupling constraint that active power, the active and reactive power equilibrium of power distribution network node i of p forms.
4. a kind of distributing net and power distribution network Joint economics dispatching party towards new energy consumption according to claim 1 or 3
Method, which is characterized in that the active power of the τ period water pump p specifically:
In formula: Ep,τFor the active power of τ period water pump p；ρ, g are respectively the density and normal gravity coefficient of water；h0、rpAnd npFor
Parameters of pump can be obtained by the head curve that producer provides；ωp,τFor the relative rotation speed of τ period water pump p, Qp,τFor τ period water pump p
Flow；ηpFor water pump pump machine efficiency.
5. a kind of distributing net and power distribution network Joint economics dispatching party towards new energy consumption according to claim 1 or 3
Method, which is characterized in that the active and reactive power equilibrium of the power distribution network node i couples distributing net with power distribution network, specifically:
In formula: Epi,τFor the water pump active power at τ period node i；β is pump power factor；WithThe respectively τ period
Active power and reactive power when water pump power consumption are not counted at power distribution network node i；Pri,τAnd Qri,τRespectively at τ period node i
The active power and reactive power of distributed generation resource are injected；Vi,τAnd Vj,τThe respectively voltage magnitude of node i and node j；GijWith
BijRespectively node i, the real and imaginary parts of admittance between j；θij,τPhase angle difference for node i, between j.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110601185A (en) * | 2019-09-17 | 2019-12-20 | 武汉大学 | Unified power flow model and random matrix-based comprehensive energy system weak point identification method |
| CN110837912A (en) * | 2019-09-17 | 2020-02-25 | 万克能源科技有限公司 | Energy storage system capacity planning method based on investment benefits |
| CN111325400A (en) * | 2020-02-20 | 2020-06-23 | 内蒙古自治区水利水电勘测设计院 | High-altitude long-distance water delivery positioning method and positioning system thereof |
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2018
- 2018-12-25 CN CN201811589671.0A patent/CN109800906A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110601185A (en) * | 2019-09-17 | 2019-12-20 | 武汉大学 | Unified power flow model and random matrix-based comprehensive energy system weak point identification method |
| CN110837912A (en) * | 2019-09-17 | 2020-02-25 | 万克能源科技有限公司 | Energy storage system capacity planning method based on investment benefits |
| CN111325400A (en) * | 2020-02-20 | 2020-06-23 | 内蒙古自治区水利水电勘测设计院 | High-altitude long-distance water delivery positioning method and positioning system thereof |
| CN111325400B (en) * | 2020-02-20 | 2023-06-02 | 内蒙古自治区水利水电勘测设计院 | High-altitude long-distance water delivery positioning method and positioning system thereof |
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