CN108964140A - Correlation low metric organic unity declines net topology structure construction method - Google Patents

Correlation low metric organic unity declines net topology structure construction method Download PDF

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CN108964140A
CN108964140A CN201810848640.6A CN201810848640A CN108964140A CN 108964140 A CN108964140 A CN 108964140A CN 201810848640 A CN201810848640 A CN 201810848640A CN 108964140 A CN108964140 A CN 108964140A
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route
power
unavailability
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杨强
胡颖泽
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Suzhou Zhen Zhen Intelligent Technology Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • 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
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • 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
    • H02J3/388—Islanding, i.e. disconnection of local power supply from the network

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

Correlation low metric organic unity of the present invention declines net topology structure construction method, step are as follows: the node of a certain power load in setting microgrid；Obtain the real time power loss value in network between any two node；State the degree of unavailability of route and device；Practical engineering experience value is substituted into, in conjunction with the risk factor of the two trade-off evaluation system each route；The two is normalized, under unification a to Measure Indexes；Using after normalization route network loss and route degree of unavailability can obtain route

Description

Correlation low metric organic unity declines net topology structure construction method
Technical field
Invention is related to distributed power generation and the energy storage device field of micro-grid system, specifically, it shows a kind of correlation Low metric organic unity declines net topology structure construction method.
Background technique
Along with the increasingly mature of micro-grid system, it is this can independent operating or the electric power network system that is incorporated into the power networks it is more Use renewable energy technologies.Although however having internal combustion engine generator group, combustion gas wheel hair in currently used distributed generation resource The relatively stable reliable power supply system such as motor, but due to needing to consume traditional energy, scale and power supply when its power supply Amount will receive certain restrictions, can not fully meet in microgrid the power requirement of whole power loads, and solar energy, wind power generation System is because it has the characteristics that clean, renewable also more penetrates into micro-grid system.But the latter is due to by day The influence of the factors such as gas, environment, power supply have the characteristics that therefore intermittent, fluctuation can not provide continual and steady electric power Supply.
This has resulted in that the operational efficiency of autonomous micro-grid system will be reduced in terms of two:
On the one hand, when DG powers abundance, a large amount of electric energy will be unable to obtain effective utilization.Although energy storage is set at this time It is standby to receive a part of extra electricity, but its effect is limited and needs a large amount of energy-storage units, to considerably increase micro- The investment and maintenance cost of net system；
On the other hand, when DG electricity shortage, load is unable to get sufficient power supply and is restricted, especially When CL electricity shortage in system, caused by loss will be more serious.
Meanwhile the number of microgrid topological structure matrix weight factor constraints condition at this stage is more, leads to microgrid topology knot Structure building is cumbersome.
It declines the solution of net topology structure construction method therefore, it is necessary to provide a kind of correlation low metric organic unity The above problem.
Summary of the invention
It declines net topology structure construction method the object of the present invention is to provide a kind of correlation low metric organic unity.
Technical solution is as follows:
A kind of correlation low metric organic unity declines net topology structure construction method, specific steps are as follows:
S1 a certain power load j in microgrid) is set, active power and reactive power are respectively PjAnd Qj, upstream supplies Electrical nodes are i, then from node i to the power supply line of node j on all-in resistance and total reactance be respectively RijAnd Xij；
S2 the voltage for) setting node j remains Uj, then from the line network in the power supply line that node i is transferred to node j Damage may be expressed as:
S3 the real time power loss value in network between any two node can) be obtained using expression formula (1)；
S4) during Model in Reliability Evaluation of Power Systems, the degree of unavailability K of route and device is a common measurement Index, it is determined by year failure-frequency and repair time, i.e.,
Wherein, f is year failure-frequency number；R is fault correction time；
S5) be used alone a kind of method or statistical data be likely difficult to effective assessment system practical risk state or Operating condition；In fact, other than using and calculating its degree of unavailability to the failure-frequency of route and the statistical value of repair time, Practical engineering experience is also an important factor；Therefore, in conjunction with the risk system of the two trade-off evaluation system each route Number:
Wherein, KijThe degree of unavailability of route between node i and node j is acquired by expression formula (2)；
EijExpert's assessed value of route between node i and node j；
η is regulatory factor, and both adjustable actual count data and expertise assessment are in risk assessment processes Specific gravity obtains more reasonable assessed value；
S6) in order to preferably unify the two under a Measure Indexes, we normalize firstly the need of by the two；
If the route between node i and node j is Lij, then its normalized route network loss and degree of unavailability are respectively as follows:
Wherein, N is the number of nodes in entire microgrid；
S7) using after normalization route network loss and route degree of unavailability can obtain route LijSynthesis weight evaluation Index are as follows:
If thering is route to be connected directly between node i and node j, acquired by expression formula (6), weight aij；If otherwise section Point i and node j are not connected directly, then aij=0；Diagonal entry aii=0.
Compared with prior art, the present invention considers multifactor building microgrid topological structure matrix weight, and correlation is low Metric organically unite, thus greatly reduce constraint condition number be algorithm simplification lay a good foundation.
Detailed description of the invention
Fig. 1 microgrid topological structure matrix method；
Fig. 2 energy storage device working region；
Fig. 3 scheduling strategy flow chart；
Fig. 4 IEEE 33-bus system testing topology and initial network divide；
Fig. 5 DG and load characteristic curve；
Fig. 6 (a) 00:00 moment is with DG1The MSTs generated for root node；
Fig. 6 (b) 00:00 moment is with DG2The MSTs generated for root node；
Fig. 6 (c) 00:00 moment is with DG3The MSTs generated for root node；
Fig. 7 (a) 05:00 moment is with DG1The MSTs generated for root node；
Fig. 7 (b) 05:00 moment is with DG2The MSTs generated for root node；
Fig. 7 (c) 05:00 moment is with DG3The MSTs generated for root node；
Fig. 7 (d) 05:00 moment is with S1The MSTs generated for root node；
Fig. 7 (e) 05:00 moment is with S2The MSTs generated for root node；
Fig. 7 (f) 05:00 moment is with S3The MSTs generated for root node；
Fig. 8 (a) 00:00 moment cooperative scheduling result；
Fig. 8 (b) 05:00 moment cooperative scheduling result；
CLs powers comparison for 24 hours under Fig. 9 initial configuration comparison scheduling structure；
Figure 10 DG utilization rate correlation curve；
Figure 11 (a) does not use tactful load to meet condition diagram；
Figure 11 (b) in the strategy but system using not having energy storage device load to meet condition diagram；
Figure 11 (c) meets condition diagram using the strategy load；
24 hours cooperative scheduling results of Figure 12.
Specific embodiment
Embodiment:
Referring to Fig. 3, using 33 node topology of IEEE to divide network, topological structure is as shown in Figure 4.
(1) Δ t is sampled at timed intervals, obtains the status information of current time system DGs, CLs, NLs, Ss.
(2) judge whetherAnd if so, executing (3), (18) otherwise are executed；Under the structural system that a upper sampling period determines, in each autonomous microgrid i (DG-CL)iVariation Than having, repartitioning, only do not increase and decrease NLs then either with or without the division trigger door threshold θ for being more than setting；
(3) the microgrid topological structure matrix A (t) of current t moment is constructed,.Its branch weight is true by expression formula (1)-(6) It is fixed.
A certain power load j in microgrid is set, active power and reactive power are respectively PjAnd Qj, upstream power supply section Point be i, then from node i to the power supply line of node j on all-in resistance and total reactance be respectively RijAnd Xij.Set node j's Voltage remains Uj, then may be expressed as: from the route network loss in the power supply line that node i is transferred to node j
The real time power loss value in network between any two node can be obtained using expression formula (1).
During Model in Reliability Evaluation of Power Systems, the degree of unavailability K of route and device is that common measures refers to Mark, it is determined by year failure-frequency and repair time, i.e.,
Wherein, f is year failure-frequency number；R is fault correction time.
It should be pointed out that a kind of method is used alone or statistical data is likely difficult to the reality of effective assessment system Risk status or operating condition.In fact, calculating it not to the failure-frequency of route and the statistical value of repair time in addition to using Outside availability, the practical engineering experience of expert is also an important factor.Therefore, each in conjunction with the two trade-off evaluation system The risk factor of route:
Wherein, KijThe degree of unavailability of route between node i and node j is acquired by expression formula (2)；EijFor node i and Expert's assessed value of route between node j；η is regulatory factor, both adjustable actual count data and expertise assessment Specific gravity in risk assessment processes obtains more reasonable assessed value.
In order to preferably unify the two under a Measure Indexes, we normalize firstly the need of by the two.
If the route between node i and node j is Lij, then its normalized route network loss and degree of unavailability are respectively as follows:
Wherein, N is the number of nodes in entire microgrid；
Using after normalization route network loss and route degree of unavailability can obtain route LijSynthesis weight evaluation index Are as follows:
If thering is route to be connected directly between node i and node j, acquired by expression formula (6), weight aij；If otherwise section Point i and node j are not connected directly, then aij=0；Diagonal entry aii=0.Then microgrid topological structure matrix construction methods are as schemed Shown in 1.
(4) judge whether the total power generation of DGs in system is greater than the aggregate demand of all power loads: judgementIt is to execute (step 5), otherwise executes (step 6)；
(5)Si∈ x | x is load }, i=1 ..., NsAnd execute (step 9)；All energy storage devices are considered as electricity consumption Load；
(6) whether the total power generation of DGs is greater than the aggregate demand of all CLs in system: judgementIt is then (step 7) is executed, (step 8) is otherwise executed；
(7)Si∈ x | x is load } ∪ y | y is generater }, i=1 ..., NsAnd execute (step 9) and (step It is rapid 10)；Energy storage device is considered as power load or power supply (Generater)；
(8)Si∈ y | y is generater }, i=1 ..., NsAnd execute (step 10)；All energy storage devices are considered as DG；
(9) judge each SiSOCi>=80%, i=1 ..., Ns, it is to execute (step 11), otherwise executes (step 12)；
(10) judge each SiSOCi≤ 20%, i=1 ..., Ns, it is to execute (step 11), otherwise executes (step 13)；
(11)The SOC of energy storage devicei>=80% or SOCi ≤ 20%, then the energy storage device is failure to actuate, both not as power supply or not as electrical equipment；
(12)Execute (step 14)；Energy storage device is considered as power supply；
(13)Execute (step 14)；Energy storage device is considered as load；
(14) calculate fromIt arrivesMinimum weight and: Min [sum (weights)]ij, obtain NG×NCLMinimum tree；
(15) minimum weight the smallest Min [sum (weights)] in is selectedijCorresponding GiAs jth important load CLjSupply node；
(16) whole N is determinedG×NCLA set { Gi,CLj},i∈(1,NG),j∈(1,NCL)；
(17) judge each set { Gi,CLj},i∈(1,NG),j∈(1,NCL) in Gi-CLj> 0 is to execute (step 19) (step 18), is otherwise executed；
(18) selection time small weight and Submin [sum (weights)]ijCorresponding GiAs jth important load CLj Supply node and execution (step 19).
(19) G is determinediAnd CLjBetween Municipal in NLs, the number of Tertiary, Light is simultaneously stored in variable nM, nTAnd nLIn.
(20) LMI: ε=min { xM (t)+yT (t)+zL (t)-(G is constructedi-CLj)}
s.t.:0≤ε
x≤nM；y≤nT；z≤nL
(21) value of x, y and z are determined.
(22) G is selectedi, CLjAnd between themY and z Municipal, Tertiary, Light constitute collection Close k | kth Autonomous MG, k ∈ (1, NG×NCL), i.e., k-th autonomous microgrid.
It can be seen that, there are 3 DG in whole network, wherein setting DG by Fig. 41For photovoltaic (0-624.205MW), DG2With DG3For wind energy (82.01-419.50MW), power characteristic comes from Belgian electricity transmission operator Elias(May 13th, 2014), as shown in Fig. 5 (a).Each energy-storage units setting is held with the maximum of 900MWh Amount, then the maximum total capacity of energy-storage system is 2700MWh in system shown in Figure 4.In addition, including 6 in system shown in Figure 4 Important load and 21 insignificant loads, shown in typical characteristic working curve such as Fig. 5 (b) for 24 hours.Each node connection type is such as Table I.
TABLEI
NODES CONNECTED WITH DGS CLS AND NLS IN 33-BUS TEST SYSTEM
Therefore, DG load curve as shown in Figure 4 is it is found that at the 00:00 moment, system I.e. total output is greater than aggregate demand, and therefore, whole energy storage devices are treated as power load and according to its own in system at this time SOC situation decides whether to carry out it charging operations, and (by step 9), and system only searches for MSTs for DGs as root node with true Determine the power supply of CL.According to the MSTs for slave DG to the CLs that the microgrid topological structure matrix A (00:00) at 00:00 moment obtains As shown in Figure 6.The MSTs according to shown in Fig. 6, calculate weight from each DG to each CL and, as shown in Table II.Wherein It is weight and the smallest, the i.e. power supply root node of the CL in certain CL to 3 root node represented by overstriking font.However, needing It is noted that 00:00 moment DG1Be 0 for electric output power, therefore, according to mentioned strategy, be responsible for 7,8 and of power supply 21CLs (presses step 18), arranges to be responsible for power supply by other two DGs respectively, such as lower stroke in Table II according to secondary small weight and principle Shown in line number value.Accordingly, 00:00 micro-grid system is reconfigured as two microgrid subsystems, and according to DG at this time2And DG3Power supply The burden requirement of ability and other NLs, it is (true by step 20) according to LMI algorithm to make full use of DGs remaining capacity as target Surely the insignificant load bus being added in every sub- microgrid.Shown in 00:00 moment cooperative scheduling result such as Fig. 8 (a).
TABLE II
WEIGHT SUMS FROM DGS TO CLS
It is different from the 00:00 moment, the etching system in 05:00At this point, according to mentioned strategy Energy storage device (S) all decides whether to discharge as power supply and according to itself SOC state (Step 10) in system.According to 05: The microgrid topological structure matrix A (05:00) at 00 moment obtains as shown in Figure 7 as the MSTs of root node using DGs and Ss.At this point, From each root node to the weight of each CL and, as shown in Table III.According to Table III as a result, 05:00 micro-grid system quilt Five subsystems are reconstructed into, and according to DG at this time2、DG3、S1-S3Power supply capacity and other NLs burden requirement, according to LMI Algorithm (Step 20) adds " leaf " insignificant load into each autonomous microgrid, to utilize power supply to greatest extent Extra electric energy is to realize making full use of for electric energy.Shown in 05:00 moment cooperative scheduling result such as Fig. 8 (b).
It is made of altogether 3 autonomous micro-grid systems under setting system initial state, as shown in Figure 4.It is each in each autonomy microgrid There are a DG, an energy-storage units and two CLs.Under the initial configuration and under proposed scheduling, system CLs is whole The comparative situation that body obtains power supply is as shown in Figure 9.Result can be seen that in system CLs in the system of coordination strategy as shown in Figure 9 The lower Service Efficiency for obtaining power supply of one scheduling is apparently higher than the Service Efficiency of CLs under original autonomous micro-grid system structure.Since CLs is negative Lotus has a meaning and value bigger than NLs for system, therefore this is from proving that the strategy has effective economy on one side Value.
It is system DG capacity factor correlation curve shown in Figure 10.This it appears that being mentioned in this paper from Figure 10 The utilization rate that autonomous microgrid cooperative scheduling strategy acts on the power generation of lower DG is higher than the utilization under no cooperative scheduling strategy scenarios Rate (being the gas-to electricity Percent efficiency of DG shown in Figure 10 wicket).By reconstructing the architecture of micro-grid system, simultaneously The charge and discharge of rational management energy storage device act, and the electric energy that DG is issued is utilized or stored by energy storage device by power load, and System lack power supply when release, this in systems in practice can effectively from two dimensions of room and time to electric power into Row optimization uses, thus improves DG efficiency, this has great importance in actual electric network.
It is the curve of all load Service Efficiency comparisons shown in Figure 11.As seen from Figure 11, when including energy storage in system When unit, which can ensure the power demand of system entirety load in the most of the time, as shown in Figure 11 (a).And if Energy storage device has sufficiently large capacity in system, then can guarantee all the period of time in conjunction with reasonable autonomous microgrid cooperative scheduling strategy Interior all load electricity consumptions.Even secondly, in systems without energy storage device in the case where, due to the coordination tune of the strategy Degree effect, the power demand of all loads is also available satisfaction in most of the time section, only in part-time when being When total power output of uniting is less than electric energy aggregate demand, just having part NLs cannot power, as shown in Figure 11 (b).It is formed therewith Sharp contrast, even if there are energy storage devices in system, in the case where no rational management, system is in most of time It is inside still unable to satisfy the power requirement of all loads, as shown in Figure 11 (c).Figure 11 has absolutely proved that autonomous microgrid is rationally adjusted The meaning and value of degree, while illustrating reasonable cooperative scheduling strategy than only increasing energy storage device in systems for electric power The optimization of resource, which uses, has prior meaning.
Figure 12 show the peace of the power supply all to system in one day of proposed cooperative scheduling strategy and load electricity consumption Arrange result.Result as shown in Figure 12 can be seen that is dispatched by the reasonable charge and discharge of energy storage device, 00:00-04:30, and 07: The extra electricity that DGs is generated in 30-08:30 the and 11:00-13:00 period is fully absorbed, and makes 05:00-07: The insufficient electrical energy demands of 00,09:00-10:30 and 18:30-21:00 have obtained effective supplement；Meanwhile in 00:00-22: In 30 periods, whole important load electricity consumptions is all fully used, only important negative within the 22:30-24:00 time Carrying capacity demand is since DG and energy storage are exported without electric power, i.e., total electricity is for should be less than CLs aggregate demand, therefore nothing in system It is all unable to satisfy and the power supply for abandoning part CL of having to by how to dispatch.But in actual operation, this some electrical power notch It can be compensated and buying electricity to public electric wire net.In addition, by the cooperative scheduling of this paper, making system for insignificant load NLs power requirement in middle most of time section can attain full and complete satisfaction, and only be greater than total supply in systematic electricity aggregate demand To when, can not just be met by scheduling, and this some electrical power still can be by buying electric acquisition.
It should be understood that (1), in order to make energy storage device have longer service life, there are one for its usual charge and discharge Determine remaining, this programme chooses the 20%-80% that its charge and discharge range is maximum capacitance of storage.
(2) all energy storage devices are uniformly considered as " electricity consumption " according to power supply situation whole in system or " put by the strategy Electricity " equipment, this is with certain realistic meaning: this strategy can effectively avoid storing up from an energy storage device to another The movement of energy equipment charge, so as to avoid the repeated charge " concussion " between battery.
(3) strategy first guarantees that all CL and NL have obtained sufficient electric power and supplied when charging to energy storage device It answers, i.e., is carried out according to CL > NL > S power supply priority, this can reduce the movement of the charge and discharge to energy storage device to the greatest extent, to prolong The service life of long battery reduces operating cost；The scheduling strategy can be realized effectively under the conditions of output power deficiency Input-output power matching, realizes that more microgrids unify the harmony of electricity consumption.On the basis that ensure that important load is sufficiently powered On, the safety of whole system important load electricity consumption is also improved to a certain extent, while can also be realized well mostly micro- The effective use of electric energy between net.
Compared with prior art, the present embodiment considers for " three-level layer (the tertiary level) " in micro-grid system By the monitoring device at electric system connection switch, such as multiple agent, obtains system status information and utilize its control connection Network switch, and then microgrid topological structure is reconstructed from logic level, the electricity supplying and using system of multiple autonomous micro-grid systems is carried out again The Optimized Operation of electric energy is realized in optimum organization by cooperation；Being somebody's turn to do " cauline leaf generation strategy " mainly includes two parts algorithm, i.e. MST Optimal DG-CL power supply relationship is searched for, determines network primary structure；LMI determines adding or deleting for NL node, guarantees DG electricity The maximum of energy utilizes；Specifically:
(1) consider multifactor building microgrid topological structure matrix weight, and the lower metric of these correlations is organic Unite, thus greatly reduce constraint condition number be algorithm simplification lay a good foundation；
(2) MST searching algorithm and LMI optimization algorithm are used in combination with and are constructed under new microgrid topological structure respectively " trunk " and " leaf ", the respective advantage of algorithm had not only been utilized but also has facilitated combining at any time and splitting that use (can basis for algorithm " leaf " node is repartitioned or only increased and decreased to system mode), so as to avoid after each sampling all to the weight of this algorithm New operation, enormously simplifies calculation amount, improves efficiency of algorithm；
(3) charging and discharging state of reasonable arrangement energy-storage units enables the strategy from two dimensions of room and time to electricity It can be carried out Optimum, so that the utilization rate of electric energy be made greatly to be improved；Meanwhile energy storage device is reduced to the greatest extent Charge and discharge number also avoid S to S charge and discharge movement, to reduce the use cost of energy-storage units, extending it makes Use the service life.
Above-described is only some embodiments of the present invention.For those of ordinary skill in the art, not Under the premise of being detached from the invention design, various modifications and improvements can be made, these belong to protection model of the invention It encloses.

Claims (1)

  1. A kind of net topology structure construction method 1. correlation low metric organic unity declines, it is characterised in that: specific steps are as follows:
    S1 the node j of a certain power load in microgrid) is set, active power and reactive power are respectively PjAnd Qj, upstream supplies Electrical nodes are i, then from node i to the power supply line of node j on all-in resistance and total reactance be respectively RijAnd Xij；
    S2 the voltage for) setting node j remains Uj, then can table from the route network loss in the power supply line that node i is transferred to node j It is shown as:
    S3 the real time power loss value in network between any two node can) be obtained using expression formula (1)；
    S4) during Model in Reliability Evaluation of Power Systems, the degree of unavailability K of route and device is a common measurement index, It is determined by year failure-frequency and repair time, i.e.,
    Wherein, f is year failure-frequency number；R is fault correction time；
    S5 a kind of method) is used alone or statistical data is likely difficult to the practical risk state or work item of effective assessment system Part；In fact, other than using and calculating its degree of unavailability to the failure-frequency of route and the statistical value of repair time, Practical Project Experience is also an important factor；Therefore, in conjunction with the risk factor of the two trade-off evaluation system each route:
    Wherein, KijThe degree of unavailability of route between node i and node j is acquired by expression formula (2)；
    EijExpert's assessed value of route between node i and node j；
    η is regulatory factor, the specific gravity of both adjustable actual count data and expertise assessment in risk assessment processes, Obtain more reasonable assessed value；
    S6) in order to preferably unify the two under a Measure Indexes, we normalize firstly the need of by the two；
    If the route between node i and node j is Lij, then its normalized route network loss and degree of unavailability are respectively as follows:
    Wherein, N is the number of nodes in entire microgrid；
    S7) using after normalization route network loss and route degree of unavailability can obtain route LijSynthesis weight evaluation index Are as follows:
    If thering is route to be connected directly between node i and node j, acquired by expression formula (6), weight aij；If otherwise node i and Node j is not connected directly, then aij=0；Diagonal entry aii=0.
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