CN105279578A - Power supply optimization configuration bilevel programming method in active distribution network region - Google Patents

Power supply optimization configuration bilevel programming method in active distribution network region Download PDF

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CN105279578A
CN105279578A CN201510706152.8A CN201510706152A CN105279578A CN 105279578 A CN105279578 A CN 105279578A CN 201510706152 A CN201510706152 A CN 201510706152A CN 105279578 A CN105279578 A CN 105279578A
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power supply
electricity
cost
loss
power
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CN105279578B (en
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罗凤章
竺笠
魏炜
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Tianjin Tiancheng Hengchuang Energy Technology Co ltd
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Tianjin University
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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
    • 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

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Abstract

The present invention provides a power supply optimization configuration bilevel programming method in an active distribution network region. The method comprises the following steps: basic data acquisition, model construction, model transformation, algorithm parameter initialization, initial network loss resolution, power generation cost correction per unit power, upper planning scheme resolution, lower planning scheme resolution, iteration termination condition discrimination and the like. Based on an integrated resource strategy planning theory, the method provided by the present invention considers a generalized power supply represented by a photovoltaic power source and an interruptible load from a whole society angle, and establishes the power supply extended optimization bilevel programming model in the active distribution network region. The method comprises: according to the upper-level planning scheme, for the purpose of the lowest total cost of general power supply construction, power generation and pollution treatment, optimizing each power supply installed capacity; according to the lower-level planning scheme, for the purpose of minimum electrical power loss, locating and sizing the general power supply; and finally performing resolution in combination with a simplex method and an improved PSO algorithm. Compared with the conventional programming method, the bilevel programming method provided by the present invention has a significant effect of energy saving and emission reduction, a high resource utilization rate and an improved whole social benefit.

Description

A kind of active distribution network region electricity optimization configuration bi-level programming method
Technical field
The invention belongs to distribution system planning technology field, particularly relate to a kind of active distribution network region electricity optimization configuration bi-level programming method.
Background technology
Along with the problems such as conventional fossil power outage, environmental pollution highlight day by day, the simple traditional Electric Power Network Planning mode relying on increase power supply and investment of substations construction to meet the electricity needs increased fast is subject to the great challenge of each side.Distributed generation technology (DistributedGeneration is called for short DG) and developing rapidly of demand response technology provide thinking for addressing these problems.The scarce capacity of renewable power supply but conventional electrical distribution net is dissolved, therefore the requirement that novel power supply accesses on a large scale cannot be met, its planing method does not consider that DG introduces the impact on power distribution network yet simultaneously, and programme is too conservative, therefore can not make full use of power grid asset.
Active distribution network (the ActiveDistributionNetwork that discusses warmly of academia and industry member in recent years, be called for short ADN) possess the ability that combination controls various distributed power source (DG, controllable burden, energy storage, dsm etc.), the receiving ability of power distribution network to distributed power source can be strengthened, realize the interaction of supply and demand both sides, the discharge of decreasing pollution thing and the wasting of resources.Meanwhile, ADN contributes to promoting power distribution network asset utilization ratio, delays the upgrading of equipment investment, and improves power quality and the power supply reliability of user.For the compatible renewable power supply of active and Demand-side resource, ADN planning needs to consider the multiple factors such as economy, environmental benefit, resource utilization, again because its investment relates to multiple main market players such as Utilities Electric Co., distributed power generation business and demand cluster resource response supplier, this will impel ADN planning to pursue single main body benefit problem from traditional sense and change to complicated multiagent coordinated planning direction.
Introduce comprehensive resources strategic planning (IntegratedResourceStrategyPlanning, be called for short IRSP) theoretical, electric power supply side resource and various forms of electric power demand side resource are carried out comprehensive unification to optimize, from the height of strategy, by economy, law, administration means, integrate the resource of supply side and Demand-side rationally and effectively, under the electricity needs prerequisite meeting economic development, reduce whole society's input cost, the consumption of power resources and pollutant emission, for power consumer provides cost minimum, the maximized power service of comprehensive benefit, become the inevitable requirement of ADN unified plan.
In conventional electrical distribution network planning is drawn, have abundant achievement in research accumulation both at home and abroad for many years, in active distribution network project study, there has also been certain progress in recent years.But great majority research only builds plan model from Utilities Electric Co.'s return on investment angle, for standing in whole society's angle, active distribution network project study supply side and Demand-side resource being included simultaneously in planning waits deeply.
Summary of the invention
In order to solve the problem, the object of the present invention is to provide a kind of active distribution network region electricity optimization configuration bi-level programming method.
In order to achieve the above object, (after waiting the content of claims to determine herein, I copies again)
The present invention is based on comprehensive resources strategic planning theoretical, from whole society's angle, consider that photo-voltaic power supply and interruptible load are the broad sense power supply of representative, establish the Bi-level Programming Models that active distribution network region power extension is optimized.Upper strata plan model for target, optimizes all kinds of power supply installed capacity with the lowest cost of the construction of broad sense power supply, generating and pollution control; Lower floor's plan model take loss minimization as target, is broad sense site selection of coal fired power plant constant volume.Finally solve in conjunction with simplicial method and improvement PSO algorithm.Planing method of the present invention is compared with traditional planning method, and effects of energy saving and emission reduction is obvious, and resource utilization is higher, and whole society's benefit is more outstanding, can provide guidance for the planning of active distribution network, construction and operation.
The beneficial effect of active distribution network region provided by the invention electricity optimization configuration bi-level programming method:
(1) model describes more comprehensively: IRSP Bi-level Programming Models is when solving active distribution network enlarging and distributed power source access planning problem, the planned capacity that whole society's total cost plans all kinds of power supply can be taken into account, and analog ligand electrical network practical operation situation, solve and obtain the minimum active distribution network allocation plan of system losses.Simultaneously in Optimized Iterative, utilize the relation correction power source planning result between system cloud gray model network loss and cost of electricity-generating, can ensure that the level of comprehensive utilization of overall power resources is the highest, make whole society's cost minimum.
(2) environmental benefit is more outstanding: utilize IRSP theoretical direction Electric Power Network Planning, environmental impact can be considered, take into account the energy-saving and emission-reduction benefit of distributed power source and dsm means, more adapt to the development trend of following built environment friendly society than traditional planning theory.
Accompanying drawing explanation
Fig. 1 is all kinds of power supply institutes delivery planning chart in the present invention's middle age lasting load curve;
Fig. 2 is active distribution network region provided by the invention electricity optimization configuration bi-level programming method process flow diagram;
Fig. 3 is 10kV33 node example grid structure topological diagram and node serial number figure;
Embodiment
Be described in detail below in conjunction with drawings and Examples active distribution network region provided by the invention electricity optimization configuration bi-level programming method.
Below for 33 node examples shown in Fig. 3, the process flow diagram shown in composition graphs 2 is described in detail to active distribution network region provided by the invention electricity optimization configuration bi-level programming method.
As shown in Figure 2, active distribution network region provided by the invention electricity optimization configuration bi-level programming method comprises the following step that order performs:
Step one, basic data obtain: the basic data comprising power supply type, grid structure, load level, electric parameter obtaining distribution system to be studied;
In the present embodiment, the basic datas such as the power supply type of 33 Node power distribution system, grid structure, load level, electric parameter are obtained.Wherein, assuming that system is original 1.7 times at the load level in planning year, wherein basic load is by the original power supply supply of system, exceed part by the original power supply of system and newly-built power supply supply, the power supply type of distribution system selects newly-built thermal power generation, investment photo-voltaic power supply and signing interruptible load contract, represent the source substation of power distribution network respectively, the power supply type that distributed power source is different with Demand-side resource these three kinds, grid structure as shown in Figure 3, node serial number as shown in FIG., load level parameter is as shown in table 1, branch road electric parameter is as shown in table 2, the installation node to be selected of setting photo-voltaic power supply is 7, 11, 15, 18, 29, 32, the installation node to be selected of interruptible load is 8, 14, 21, 24, 30, interruptible load is interrupted by original power factor,
Table 133 node example load level parameter
Table 2 branch road electric parameter
Step 2, model construction: the basic data utilizing step one to obtain builds the Bi-level Programming Models based on the region power extension problem of IRSP, and determines levels objective function and the constraint condition of this Bi-level Programming Models;
In step 2, Bi-level Programming Models based on the region power extension problem of IRSP comprises upper and lower layer plan model, wherein, upper strata plan model is for realizing the power supply allocation optimum of macroscopical total amount aspect, ensure whole society's electric generation investment cost and Environmental costs minimum, its objective function comprises the initial outlay construction cost of all kinds of power supply, cost of electricity-generating and pollutant control cost, and be a minimization problem, its mathematic(al) representation is:
min f = Σ i = 1 I ( F i C i + V i C i H i ) + Σ i = 1 I H i C i β i - - - ( 1 )
In formula, i is power type, i=1, and 2,3 represent thermal power generation, photo-voltaic power supply, interruptible load respectively; F ifor such power supply unit capacity construction cost year value, unit/kW; C ifor such power supply installation total volume, kW; V ifor such power supply unit quantity of electricity cost of electricity-generating, unit/kWh; H ifor such power supply annual utilization hours, hour; β ifor the pollutant control cost of such power supply unit quantity of electricity, unit/kWh.F ican be expressed as further:
F i = a i · r 0 · ( 1 + r 0 ) m ( 1 + r 0 ) m - 1 - - - ( 2 )
In formula, a ifor the unit capacity cost of such power supply, unit/kW; r 0for rate of discount; M is the operation time limit (the phase mathematic(al) expectation time limit) of such power supply, year.
The whole year operation time of photo-voltaic power supply and interruptible load limits by daylight factor and treaty content, is difficult to long-term power supply, and the delivery of its shortcoming is made up by thermal power generation.For avoiding the planned capacity of photo-voltaic power supply and interruptible load excessive, thermal power generation planned capacity is too small, thus cause the shortage of actual power amount, upper strata plan model should meet the constraint condition that the total delivery of all power is more than or equal to the annual electrical demand in planning region and be:
Σ i = 1 I C i H i ≥ ∫ 0 8760 L ( t ) · d t - - - ( 3 )
In formula, L (t) is annual average load power hourly.
Lower floor's plan model really holds optimization and system operation simulation optimization, to ensure system cloud gray model loss minimization for all kinds of plant-grid connection reconnaissances realizing microcosmic operation aspect.The objective function of lower floor's plan model should consider the operating cost of all kinds of power supply and the relation of peak-shaving capability, when calculating year operation total expenses, IRSP upper strata is planned the total volume of distributed power source and the interruptible load provided configures to each access point to be selected, by the analogue simulation of typical case's day 24 hours electrical network actual operating states, minimum for target with Energy loss, optimize the partition capacity of access point to be selected, its mathematic(al) representation is:
minf＝loss(4)
Constraint condition is:
P p v + P I L - P i = U i Σ j = 1 n U j ( G i j cosδ i j + B i j sinδ i j ) - - - ( 5 )
Q p v + Q I L - Q i = U i Σ j = 1 n U j ( G i j sinδ i j - B i j cosδ i j ) - - - ( 6 )
U imin≤U i≤U imax(7)
0≤I w≤I jmax(8)
S j≤S jmax(9)
In formula, loss is Energy loss; N is system node number; P pv, Q pv, P iL, Q iLbe respectively the meritorious and reactive power of distributed photovoltaic and interruptible load injection node i; P i, Q ibe respectively the meritorious of node i and load or burden without work; G ij, B ijbe respectively the corresponding element in bus admittance matrix; U ifor the voltage magnitude of node i, U imin, U imaxbe respectively permission upper voltage limit and the lower limit of node i; I jfor the current amplitude of branch road j, I jmaxfor the electrical current heat of branch road j stablizes the upper limit; S jfor the applied power of branch road j, S jmaxfor the applied power upper limit of branch road j.
In the present embodiment, system node voltage bound is respectively 1.05p.u. and 0.95p.u., and branch road allows the maximum current flow through to be 0.4kA, and the branch power upper limit is 6.93kVA.
Step 3, algorithm parameter initialization: the parameter of initialization dual layer resist algorithm, the maximum iteration time of the PSO algorithm that setting improves is 50 times, particle populations number is n, particle code length is the node total number of accessible photo-voltaic power supply and interruptible load in distribution system, Studying factors C1=2, C2=1.732, and determine stopping criterion for iteration;
In the present embodiment, particle populations number is 30, and particle code length is 11 (photo-voltaic power supply node to be selected is 6, and interruptible load node to be selected is 5), Studying factors C1=2, C2=1.732, determines to reach maximum iteration time 50 times as end condition.
Step 4, initial network loss solve: assuming that higher level's substation capacity is sufficient, do not consider photo-voltaic power supply and interruptible load, Energy loss when utilizing lower floor's plan model calculating active distribution network load all to be powered by higher level transformer station, this Energy loss is born by higher level transformer station and thermal power generation;
Step 5, the correction of unit quantity of electricity cost of electricity-generating: utilize lower floor's plan model to solve the Energy loss obtained to share to all kinds of power supply, to revise the cost of electricity-generating of all kinds of power supply by above-mentioned;
In step 5, electrical energy production and the Energy loss produced in transmitting should count cost of electricity-generating, therefore the i-th class power supply unit quantity of electricity cost of electricity-generating V ishould be:
V i = S p d i × ( load d e m + loss i ) load d e m - - - ( 10 )
In formula, S pdiit is the unit quantity of electricity cost of electricity-generating of the i-th class power supply originally; Load demit is the load power consumption that the i-th class power supply is born; Loss iit is the Energy loss that the i-th class power supply is born.Visible i-th class power supply unit quantity of electricity cost of electricity-generating V iit is the dependent variable of load power consumption and Energy loss.
The Energy loss comprising the active distribution network of distributed power source is shared and is divided into two steps to carry out, and the first step will not shared to original electricity provider containing active distribution network Energy loss during distributed power source; The Energy loss variable quantity that second step causes after being accessed by distributed power source is shared to distributed power source.
Δloss＝loss 1-loss′ 1(11)
loss 2＝Δloss(12)
In formula, Δ loss is loss 1with loss 1' difference, loss 1for the total Energy loss after access distributed power source, loss 1' be not containing Energy loss during distributed power source; Loss 2for the Energy loss that distributed power source is shared.
After access distributed power source, if the Energy loss of active distribution network declines, Δ loss is negative, i.e. the Energy loss loss that shares of distributed power source 2for negative value, by the unit quantity of electricity cost of electricity-generating V of formula (10) known photo-voltaic power supply 2reduce; The Energy loss that thermal power generation is shared is still loss 1', but after access distributed power source, thermal power generation and distributed power source provide electric energy to load jointly, and the load power consumption that thermal power generation is born reduces comparatively before, therefore the unit quantity of electricity cost of electricity-generating V of thermal power generation 1slightly increase.If the Energy loss of active distribution network increases, Δ loss is just, the Energy loss of growth is born by distributed power source, and original Energy loss loss is still born in thermal power generation 1', and the load power consumption born reduces.
By that analogy, here just do not repeated by the correction of the cost of electricity-generating introducing all kinds of power supplys that Demand Side Response causes.
Step 6, upper strata plan model solve: utilize above-mentioned revised cost of electricity-generating correction gas-to electricity hour and unit capacity IRSP integrated cost relation curve, and solve IRSP upper strata plan model, to obtain the installed capacity of all kinds of power source planning;
In step 6, IRSP integrated cost comprises the initial outlay construction cost of power supply, fuel cost, operation expense and pollutant control cost, wherein initial outlay construction cost is fixed part, and fuel cost, operation expense (the two unified definition is cost of electricity-generating by the present invention) and pollutant control cost are variation part.In addition, the cost price that above-mentioned every one-tenth should drop into using reality but not price of market exchange, as calculating parameter, can reflect the bona fide cost of all kinds electric generation investment so more objectively, be conducive to the efficiency utilization of resource angle in the whole society.Above-mentioned three class power supplys are with the unit capacity IRSP integrated cost Z of gas-to electricity hour t change iexpression formula such as formula shown in (13):
Z i＝F i+(V i+ωβ i)×t(13)
In formula, i=1,2,3 represents thermal power generation, photo-voltaic power supply, interruptible load respectively; F iit is the i-th class power supply unit capacity construction cost year value; V iit is the i-th class power supply unit quantity of electricity cost of electricity-generating; β iit is the i-th class power supply unit quantity of electricity pollutant control cost; ω is weight, depending on environmental benefit by attention degree.Wherein photo-voltaic power supply generating is without the need to dropping into fuel cost, its unit quantity of electricity cost of electricity-generating V 2only comprise equipment operation maintenance cost.Interruptible load refers to that user and Utilities Electric Co. sign a contract, and user is at load boom period cut-out load, and cut load compensates user by Utilities Electric Co..Because power consumer loses the economic benefit that originally can be produced by cutting load electricity, so the contract signing expense of interruptible load should as IRSP integrated cost Z ifixed part, reimbursement for expenses during cutting load should as IRSP integrated cost Z ivariation part.
In order to comparison and selection unit capacity IRSP integrated cost Z iminimum power source planning scheme, the invention describes gas-to electricity hourage and the unit capacity IRSP integrated cost Z of three class power supplys ibetween relation, as shown in Figure 1a.Wherein, horizontal ordinate is annual 8760 hours, and ordinate is unit capacity IRSP integrated cost Z i; Curve 1,2,3 represents thermal power generation, photo-voltaic power supply and interruptible load respectively, and intercept is unit capacity IRSP integrated cost Z ifixed part F i; Slope is unit capacity IRSP integrated cost Z ivariation part V i+ ω β i.Fig. 1 b is the year lasting load curve in the prediction somewhere planning year utilizing table 3 Plotting data, and horizontal ordinate is equally also annual 8760 hours, and ordinate is burden with power power.Year lasting load curve, based on year sequential load curve, disregards its time sequencing, and average load power L (t) hourly for the whole year rearranges according to order from big to small and obtains by it.Annual average load power L (t) hourly meets formula (14):
L(t)＝L y×P wk×P d×P h(t)(14)
In formula, L ya year peak load, P wkthat Zhou Fenghe accounts for year peak load number percent, P dthat a day peak load accounts for Zhou Fenghe number percent, P hrun sky peak load per hour to account for day peak load number percent.
Table 3 year lasting load curve parameter
When weights omega=1 of environmental benefit, the construction cost of thermal power generation is the highest, and the cost of variation part is minimum; The construction cost of photo-voltaic power supply is slightly lower than thermal power generation, and variation departmental cost is higher, therefore slope is higher than thermal power generation; The fixed cost of interruptible load is minimum, but variable cost is the highest in all kinds of power supply.If more pay attention to environmental problem, the numerical value of weights omega can be increased to obtain the programme of environmental protection more.
As seen from Figure 1, at t 1before moment, the unit capacity IRSP integrated cost Z of the interruptible load representated by curve 3 ilower than other two classes power supplys, therefore P c, P mAX, C enclose area representative load power consumption Q l3solved by Demand-side resource, contracting by this sub-load transform interruptible load as, and the capacity of contract signing is P mAX-P c.At t 1to t 2between moment, the unit capacity IRSP integrated cost Z of the photo-voltaic power supply representated by curve 2 ilower than other two classes power supplys, therefore P b, P c, C, B enclose area representative load power consumption Q l2born by photo-voltaic power supply, installed capacity is P c-P b.At t 2after moment, the unit capacity IRSP integrated cost Z of thermal power generation iminimum, therefore P a, P b, B, A enclose area representative load power consumption Q l1born by thermal power generation, installed capacity is P b-P a.For simplifying Study on Problems, the present invention supposes that power is less than P aload (P a, A, lasting load curve and abscissa axis enclose area) born by original power supply (before Expansion Planning) of active distribution network.
Step 7, lower floor's plan model solve: according to the parameter set in the installed capacity of above-mentioned all kinds of power source planning and step 3, utilize the PSO algorithm improved to solve lower floor's plan model, obtain and meet the photo-voltaic power supply of loss minimization and the addressing constant volume scheme of interruptible load;
Step 8, stopping criterion for iteration differentiate: whether evaluation algorithm reaches maximum iteration time or search the optimum solution meeting accuracy requirement, if then jump out circulation, export IRSP region Expansion Planning of power plants optimal case; Otherwise go to step five, proceed iteration.
For the present embodiment, active distribution network region provided by the invention electricity optimization configuration dual layer resist result is: thermal power generation newly-built installed capacity 2081.4kW, the newly-built installed capacity 1632.7kW of photo-voltaic power supply, interruptible load sign outage capacity 757.9kW, and the particular capacity data of each Joint Enterprise photo-voltaic power supply to be selected and interruptible load refer to table 4.Compared with traditional planning, unit capacity IRSP integrated cost decreases 50.39 ten thousand yuan, decreases by 11.75%; Power construction cost reduction 73.8 ten thousand yuan, decreases by 52.12%; Cost of electricity-generating adds 36.23 ten thousand yuan, and amplification reaches 16.5%; Pollutant control cost reduction 12.52 ten thousand yuan, decreases by 18.42%, day Energy loss reduce 1297.5kWh, decrease by 30.41%.The concrete data that active distribution network region provided by the invention electricity optimization configuration bi-level programming method and traditional planning contrast are in table 5.
Table 4 photo-voltaic power supply and interruptible load allocation optimum scheme
Table 5 the inventive method and traditional planning methods and results contrast

Claims (7)

1. an active distribution network region electricity optimization configuration bi-level programming method, is characterized in that: it comprises the following step that order performs:
Step one, basic data obtain: the basic data comprising power supply type, grid structure, load level, electric parameter obtaining distribution system to be studied;
Step 2, model construction: the basic data utilizing step one to obtain builds the Bi-level Programming Models based on the region power extension problem of IRSP, and determines levels objective function and the constraint condition of this Bi-level Programming Models;
Step 3, algorithm parameter initialization: the parameter of initialization dual layer resist algorithm, the maximum iteration time of the PSO algorithm that setting improves is 50 times, particle populations number is n, particle code length is the node total number of accessible photo-voltaic power supply and interruptible load in distribution system, Studying factors C1=2, C2=1.732, and determine stopping criterion for iteration;
Step 4, initial network loss solve: assuming that higher level's substation capacity is sufficient, do not consider photo-voltaic power supply and interruptible load, Energy loss when utilizing lower floor's plan model calculating active distribution network load all to be powered by higher level transformer station, this Energy loss is born by higher level transformer station and thermal power generation;
Step 5, the correction of unit quantity of electricity cost of electricity-generating: utilize lower floor's plan model to solve the Energy loss obtained to share to all kinds of power supply, to revise the cost of electricity-generating of all kinds of power supply by above-mentioned;
Step 6, upper strata plan model solve: utilize above-mentioned revised cost of electricity-generating correction gas-to electricity hour and unit capacity IRSP integrated cost relation curve, and solve IRSP upper strata plan model, to obtain the installed capacity of all kinds of power source planning;
Step 7, lower floor's plan model solve: according to the parameter set in the installed capacity of above-mentioned all kinds of power source planning and step 3, utilize the PSO algorithm improved to solve lower floor's plan model, obtain and meet the photo-voltaic power supply of loss minimization and the addressing constant volume scheme of interruptible load;
Step 8, stopping criterion for iteration differentiate: whether evaluation algorithm reaches maximum iteration time or search the optimum solution meeting accuracy requirement, if then jump out circulation, export IRSP region Expansion Planning of power plants optimal case; Otherwise go to step five, proceed iteration.
2. active distribution network region according to claim 1 electricity optimization configuration bi-level programming method, it is characterized in that: in step one, described power supply type is selected newly-built thermal power generation, investment photo-voltaic power supply and is signed interruptible load contract, represents the power supply type that the source substation of power distribution network, distributed power source and Demand-side resource these three kinds is different respectively.
3. active distribution network region according to claim 1 electricity optimization configuration bi-level programming method, it is characterized in that: in step 2, the mathematic(al) representation of the objective function of described upper strata plan model is:
min f = Σ i = 1 I ( F i C i + V i C i H i ) + Σ i = 1 I H i C i β i - - - ( 1 )
In formula, i is power type, i=1, and 2,3 represent thermal power generation, photo-voltaic power supply, interruptible load respectively; F ifor such power supply unit capacity construction cost year value, unit/kW; C ifor such power supply installation total volume, kW; V ifor such power supply unit quantity of electricity cost of electricity-generating, unit/kWh; H ifor such power supply annual utilization hours, hour; β ifor the pollutant control cost of such power supply unit quantity of electricity, unit/kWh; F ican be expressed as further:
F i = a i · r 0 · ( 1 + r 0 ) m ( 1 + r 0 ) m - 1 - - - ( 2 )
In formula, a ifor the unit capacity cost of such power supply, unit/kW; r 0for rate of discount; M is the operation time limit of such power supply, year;
The constraint condition of upper strata plan model is:
Σ i = 1 I C i H i ≥ ∫ 0 8760 L ( t ) · d t - - - ( 3 )
In formula, L (t) is annual average load power hourly.
4. active distribution network region according to claim 1 electricity optimization configuration bi-level programming method, it is characterized in that: in step 2, the mathematic(al) representation of the objective function of described lower floor's plan model is:
minf＝loss(4)
Constraint condition is:
P p v + P I L - P i = U i Σ j = 1 n U j ( G i j cosδ i j + B i j sinδ i j ) - - - ( 5 )
Q p v + Q I L - Q i = U i Σ j = 1 n U j ( G i j sinδ i j - B i j cosδ i j ) - - - ( 6 )
U imin≤U i≤U imax(7)
0≤I j≤I jmax(8)
S j≤S jmax(9)
In formula, loss is Energy loss; N is system node number; P pv, Q pv, P iL, Q iLbe respectively the meritorious and reactive power of distributed photovoltaic and interruptible load injection node i; P i, Q ibe respectively the meritorious of node i and load or burden without work; G ij, B ijbe respectively the corresponding element in bus admittance matrix; U ifor the voltage magnitude of node i, U imin, U imaxbe respectively permission upper voltage limit and the lower limit of node i; I jfor the current amplitude of branch road j, I jmaxfor the electrical current heat of branch road j stablizes the upper limit; S jfor the applied power of branch road j, S jmaxfor the applied power upper limit of branch road j.
5. active distribution network region according to claim 1 electricity optimization configuration bi-level programming method, is characterized in that: in step 5, described every class power supply unit quantity of electricity cost of electricity-generating V ifor:
V i = S p d i × ( load d e m + loss i ) load d e m - - - ( 10 )
In formula, S pdiit is the unit quantity of electricity cost of electricity-generating of this power supply originally; Load demit is the load power consumption that such power supply is born; Loss iit is the Energy loss that such power supply is born.
6. active distribution network region according to claim 1 electricity optimization configuration bi-level programming method, it is characterized in that: in step 5, described to be shared by Energy loss to the method for all kinds of power supply be carry out in two steps, and the first step will not shared to original electricity provider containing active distribution network Energy loss during distributed power source; The Energy loss variable quantity that second step causes after being accessed by distributed power source is shared to distributed power source;
Δloss＝loss 1-loss′ 1(11)
loss 2＝Δloss(12)
In formula, Δ loss is loss 1with loss 1' difference, loss 1for the total Energy loss after access distributed power source, loss 1' be not containing Energy loss during distributed power source; Loss 2for the Energy loss that distributed power source is shared.
7. active distribution network region according to claim 1 electricity optimization configuration bi-level programming method, it is characterized in that: in step 6, described IRSP integrated cost comprises the initial outlay construction cost of power supply, fuel cost, operation expense and pollutant control cost, wherein initial outlay construction cost is fixed part, and fuel cost, operation expense and pollutant control cost are variation part; Above-mentioned three class power supplys are with the unit capacity IRSP integrated cost Z of gas-to electricity hour t change iexpression formula such as formula shown in (13):
Z i＝F i+(V i+ωβ i)×t(13)
In formula, i=1,2,3 represents thermal power generation, photo-voltaic power supply, interruptible load respectively; F iit is the i-th class power supply unit capacity construction cost year value; V iit is the i-th class power supply unit quantity of electricity cost of electricity-generating; β iit is the i-th class power supply unit quantity of electricity pollutant control cost; ω is weight, depending on environmental benefit by attention degree.
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