CN110739719A - Two-step decision method for optimized access of flexible multi-state switch - Google Patents

Two-step decision method for optimized access of flexible multi-state switch Download PDF

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CN110739719A
CN110739719A CN201910815608.2A CN201910815608A CN110739719A CN 110739719 A CN110739719 A CN 110739719A CN 201910815608 A CN201910815608 A CN 201910815608A CN 110739719 A CN110739719 A CN 110739719A
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index
decision
state switch
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王志强
徐艺铭
方正
刘文霞
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North China Electric Power University
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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
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • 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
    • H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
    • H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks

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Abstract

The invention belongs to the technical field of distribution network flexible multi-state switch access optimization, and particularly relates to a two-step decision method for flexible multi-state switch optimized access, which comprises the steps of 1, establishing flexible multi-state switch access position preliminary screening indexes based on external characteristics, and performing -based processing and sequencing, 2, establishing a multi-index flexible multi-state switch optimized access comprehensive decision calculation model considering system reliability, voltage deviation and distributed power supply acceptance capacity, 3, evaluating the system reliability based on a power flow equation and constraint conditions which are met by flexible multi-state switch operation optimization, 4, establishing a multi-index decision model based on gray correlation analysis, determining weight assignment and finally determining an optimal scheme.

Description

Two-step decision method for optimized access of flexible multi-state switch
Technical Field
The invention belongs to the technical field of distribution network flexible multi-state switch access optimization, and particularly relates to a flexible multi-state switch access optimization two-step decision method.
Background
The network reconstruction based on the interconnection switch is limited by the problems of switch response speed, action life, impact current and the like, the requirement of uninterrupted power supply of sensitive loads cannot be met, -step admission of renewable energy sources is limited, and the contribution to the power distribution network is related to multiple factors such as the position and capacity of the power distribution network, the structure and load of the power distribution network and the like due to the fact that the manufacturing cost of the flexible switch is high at the present stage, the contribution to the power distribution network is related to the access position and capacity of the power distribution network, and the relevance of the structure and load of the power distribution network, therefore, the benefit of configuring the flexible switch is scientifically evaluated, optimized configuration is developed, and important significance is achieved for promoting the development of the alternating current and direct current distribution network.
The flexible switch grid connection method has the advantages that the voltage quality is improved, the consumption capacity of a distributed power supply is improved, the feeder line load is greatly balanced, the system voltage deviation is reduced, the network loss is reduced, uninterrupted power supply is achieved, the system reliability is improved and the like, the flexible switch access has an improvement effect on the benefits of voltage, network loss and reliability, the magnitude of each benefit is closely related to factors such as the type and capacity of a DG (distributed generation) and the line load, the position and the number of the flexible switch and the like, the flexible switch is influenced by multiple factors under the same scene, and the effect is mutually coupled, so the access benefit of the flexible switch can be more scientifically reflected through comprehensive benefit evaluation, in order to ensure the scientificity of multi-index comprehensive decision, a plurality of algorithms are used for determining multi-index weights, and have advantages and defects, the hierarchical method is high in subjectivity and large in calculation amount, the combined weighting method considers the uncertainty of indexes obtained by different weighting methods and the problem of the consistency with the real weights, but the scale system is complex.
Disclosure of Invention
Aiming at the technical problem, the invention provides a two-step decision method for optimizing access of flexible multi-state switches, which comprises the following steps:
step 1, establishing an initial screening index of the access position of the flexible multi-state switch based on external characteristics, and performing -based treatment and sequencing;
step 2: establishing considerations includes: the method comprises the following steps that a multi-index flexible multi-state switch including system reliability, voltage deviation and distributed power supply acceptance capacity is optimally accessed into a comprehensive decision calculation model;
and step 3: evaluating the reliability of the system based on a power flow equation and constraint conditions which are optimally met by the operation of the flexible multi-state switch;
and 4, step 4: and establishing a multi-index decision model based on grey correlation analysis, determining weight assignment and finally determining an optimal scheme.
The preliminary screening indexes comprise: load balancing degree, flexible switch arrangement and connection distance, important user number and distributed power supply number.
The system reliability indicators include: the method comprises the following steps of load point average fault rate index, load point fault power failure time expected value, load point power supply reliability and system average power failure duration.
The weight setting of the voltage deviation indicator takes into account two factors: the electrical distance between the node and the head end of the feeder line, the DG access position and the output.
The distributed power supply acceptance capacity index adopts the distributed power supply permeability under the maximum acceptance capacity as an evaluation index, and considers the probability characteristics of DGs and loads.
The multiple indexes further comprise economic benefit indexes: the network loss income and the flexible switch construction investment cost are reduced, and the upgrading and reconstruction benefits are delayed.
The step 3 comprises the following steps: and realizing power balance of each node and non-out-of-limit of voltage and current on each branch by using a power flow equation and constraint conditions, simultaneously considering the fluctuation of DG output, the time sequence characteristics of different load types and the control time sequence characteristics of the flexible switch, and performing reliability evaluation by adopting a sequential Monte Carlo method.
The step 4 comprises the following steps:
processing the multiple indexes into to obtain a normalized decision matrix;
a decision scheme matrix set composed of decision schemes obtained according to the evaluation object and the evaluation index;
forming an index set according to different index attributes;
obtaining an index average value for measuring the average level;
determining a positive ideal index set, a negative ideal index set and a regional index set, and linearly transforming operators for the index values; and obtaining a normalized decision matrix under an ideal condition.
Calculating the distance from the scheme obtained after the preliminary screening to an ideal index value;
calculating a grey correlation coefficient of the sequence to the reference sequence on a certain index;
calculating gray weighted association degree, and determining an evaluation result by taking the gray weighted association degree as reference;
and calculating the relative closeness of the scheme, and sequencing according to the relative closeness to obtain an evaluation result.
The invention has the beneficial effects that:
the method considers the actual situation of the power distribution network in China, namely the scientificity of decision making is improved through multi-index comprehensive decision making, meanwhile, the calculated amount is reduced through two-stage decomposition, the optimization efficiency is improved, analysis is carried out according to asset performance, the recent development direction of power enterprises is met, and the green, safe and sustainable power distribution network construction is effectively supported.
Drawings
FIG. 1 is a diagram of a comprehensive benefit evaluation index system
FIG. 2 is a schematic diagram of the principle of delayed upgrade and reconstruction of a flexible switch
FIG. 3 is a flow chart of a power distribution system reliability evaluation calculation including a flexible switch
FIG. 4 is a block diagram of a three IEEE33 node system access flexible switch
FIG. 5 is a graph of loss versus voltage for three schemes
Detailed Description
The invention is further described with reference to the drawings.
Step 1: and preliminarily screening the access positions of the flexible multi-state switches based on the external characteristics. Indexes of load balance degree, important users and the number of distributed power supplies are established.
(1) The degree of load balancing. Taking three ports as an example, the loads connected with the flexible switches of the ports are respectively L1, L2 and L3, and the sum of the absolute values of the maximum load differences is Lmax。
Lmax＝|L1-L2|+|L1-L3|+|L2-L3| (1)
(2) The important user where the flexible switch is located is in proportion.
(3) The number of distributed power sources is accommodated.
SDG＝SDG,L1+SDG,L2+SDG,L3(3)
As shown in fig. 1, the index may further include: the land price and the connection distance of the flexible switch. CGroundThe cost of installing the flexible switch is the cost of installing the ground price, d is the cost of installing the unit space price, s is the floor area of the flexible switch device, and p is the probability of possible installation. DGeneral assemblyThe total length of the link distance. And the scheme with high cost and low feasibility should be eliminated during primary screening.
CGround＝∑d×s×p (4)
DGeneral assembly＝∑D1+D2+D3(5)
And (4) classifying the screening index data relative to the maximum value thereof to obtain the purity between [0 and 1], evaluating by adopting a variable-weight objective evaluation method, and screening a plurality of candidate schemes by sequencing.
Step 2: and establishing a multi-index comprehensive decision method for optimized access of the flexible multi-state switch, quantizing the performance index and obtaining a calculation model of the performance index.
(1) Evaluation index of system reliability: and based on the probability multi-scenario calculation, the expression under a single scenario is described as follows, the calculation is carried out by a single load unit, and important users consider the range of the swept fault repair domain, the fault recovery domain and the fault switching domain.
Load point mean failure rate index (SAIFI)
Figure BDA0002186279560000051
Expected value (U) of power failure time of load point faultLP-F)
ULP-F＝∑Xt·Ti(7)
Load point power supply reliability rate (ASAI-LP)
System average power off duration (SAIDI)
Figure BDA0002186279560000053
In the formula: lambda [ alpha ]iIs the average failure rate of load point i; n is a radical ofiThe number of users at the load point i; xtFor facility fault outage rates, TiRestoring the power supply time for the load point after the fault; u shapeiThe average power failure time of the load point i; giNumber of active power hours for load point, YiIs the total hours per unit year.
Figure BDA0002186279560000054
Figure BDA0002186279560000055
In the formula: lambda [ alpha ]i,jThe failure rate of power failure of a load point i caused by the failure of a branch feeder line; u shapei,jThe duration of its power outage.
(2) And (3) integrating voltage deviation indexes: the setting of the weight takes into account twoFactors of electrical distance between node and head end of feeder line, DG access position and output, voltage deviation weight W of single node ik,iComprises the following steps:
Figure BDA0002186279560000057
the impedance from the node i to the initial end of the feeder line;
Figure BDA0002186279560000058
the maximum value of the impedance between the initial end and each tail end of the feeder line;apparent power of kth DG at time t; stIs the sum of the feeder line load apparent power;
Figure BDA00021862795600000510
impedance of the DG access point to the balance node;
Figure BDA00021862795600000511
the impedance of node i to the DG access point. When in use
Figure BDA00021862795600000512
Is greater thanTime, correct
Figure BDA00021862795600000514
Figure BDA00021862795600000515
Is zero. U shapek,iIs the voltage at node i in the kth feeder. After the flexible switch is connected, fBiasThe smaller the contribution of the flexible switch to the power distribution network.
Figure BDA0002186279560000061
(3) And (3) the acceptance capacity of the distributed power supply, namely the permeability β of the distributed power supply under the maximum acceptance capacity is used as a valuation index, and an expression formula is shown as a formula (14).The indication is that there is an active load,
Figure BDA0002186279560000063
for the generation of the DG power,
Figure BDA0002186279560000064
and the DG power generation amount is newly increased after the flexible switch is connected. Equation (15) represents the probability of multiple scenes, taking into account the probability characteristics of DG and load.
Figure BDA0002186279560000066
In addition, a quantitative calculation model of economic benefit can be established
(1) Network loss reduction benefits
Figure BDA0002186279560000067
CLossTo reduce the net loss, c is the electricity purchase price, PLOSSAnd (t) is the network power loss amount of the t hour in years, and can be solved by a power flow calculation equation.
(2) Cost of flexible switch construction investment
Figure BDA0002186279560000068
Wherein C is0Investment cost for flexible switches; cSOPThe annual operation and maintenance cost of the flexible switch is reduced; cLOSSFor distribution networksThe annual cost of active loss, d is the discount rate, m is the life cycle of the flexible switch device, e is the unit capacity cost of the flexible switch, and w is the capacity of the flexible switch.
(3) The benefit of upgrading and reconstruction is delayed, as shown in fig. 2.
And step 3: and establishing a method for evaluating the power distribution network optimization power flow and the reliability of the power distribution network system with the flexible multi-state switch, as shown in figure 3. And establishing a power flow equation and constraint conditions which are optimally met by the operation of the flexible multi-state switch, so as to realize power balance of each node and no out-of-limit of voltage and current on each branch, simultaneously considering the fluctuation of DG output, the time sequence characteristics of different load types and the control time sequence characteristics of the flexible switch, and performing reliability evaluation by adopting a sequential Monte Carlo method.
1. The power distribution network comprising the flexible switch has the following optimization trend:
the operation optimization of the three-port flexible switch needs to meet the constraints of a power flow equation and constraint conditions:
in the formula: omegaFlexible switchIs a collection of flexible switches; pk1(t)，Pk2(t)，Pk3(t)，Qk1(t)，Qk2(t)，Qk3(t)Respectively outputting active power and reactive power of each port of the flexible switch in the t period; sk1max、Sk2maxAnd Sk3maxThe access capacity of the converter at each port of the flexible switch is respectively.
Figure BDA0002186279560000072
Uk,j 2＝Uk,i 2-2(Rk,iPk,i+Xk,iQk,i)+(Rk,i 2+Xk,i 2)Ik,i 2(20)
Figure BDA0002186279560000073
Through the formula, the power balance of each node is realized, and the voltage and the current on each branch circuit are not out of limit, wherein
Figure BDA0002186279560000075
Respectively the maximum value and the minimum value of the voltage of the node i of the kth feeder line;representing the rated current of the ith branch of the feeder k.
2. Reliability evaluation calculation of power distribution system with flexible switch
When the traditional power equipment fails, the differential protection device in the power distribution system acts. In order to ensure the correctness of protection judgment, the flexible switching device adopts a low-voltage ride through technology, and after fault isolation, the flexible switching device supplies power to a fault side in a Vf control mode. By calling an optimized load flow program for calculation, if the flexible switch cannot support all load power supplies of a non-fault section, part of the load is removed by scheduling the traditional switch, and a strategy for removing the load according to an important user level is adopted.
And 4, establishing an optimal scheme decision method based on gray correlation analysis, namely firstly grouping multiple indexes to obtain a linear transformation operator on the range of [ -1,1], then establishing a multiple index decision model based on gray correlation analysis, determining weight assignment and finally determining an optimal planning scheme.
1. Grouping method of multi-index decision:
considering the difference of the dimension and the magnitude of the index, firstly, carrying out non-dimensionalized data processing through initialization processing to obtain a normalized decision matrix. Because the index types comprise positive ideal indexes, negative ideal indexes and regional ideal indexes, the operator is linearly transformed in the range of [ -1,1] on the basis of the index types, and the normalized decision matrix is obtained.
A decision scheme matrix set J consisting of decision schemes obtained according to the evaluation objects and the evaluation indexes; according to different index attributes, an index set A is formed, wherein A is { A ═ A }11,A12,A13,A14,A15,A2,A3,A4,A51,A52,A53,A6}. The index value of the scheme matrix J to the index set A is xijIf there are m schemes and n indexes, the decision matrix X is (X)ij)m×nThe expression is shown in the following formula (23). Wherein i is more than or equal to 1 and less than or equal to m, and j is more than or equal to 1 and less than or equal to n.
Figure BDA0002186279560000081
2. The method comprises the following steps of establishing a multi-index decision model based on grey correlation analysis:
(1) firstly, an index average value Y for measuring average level is obtainedij；
Figure BDA0002186279560000082
(2) Determining a positive ideal index set, a negative ideal index set and a regional index set, and linearly transforming operators to the index values. And obtaining a normalized decision matrix under an ideal condition.
(3) Calculating the distances from the five schemes obtained after the preliminary screening to the ideal index value
Figure BDA0002186279560000083
The distance to the positive ideal-type indicator,
the distance to the negative ideality index,
Figure BDA0002186279560000085
(4) and calculating a grey correlation coefficient.
Figure BDA0002186279560000091
Grey correlation coefficient ξi(i) Is a series xijTo reference number sequence x0Correlation coefficient on i-th index, where ρ is [0,1]]Is the resolution factor. Wherein, it is called min { min | x0-xij|}、max{max|x0-xijAnd | is a two-level minimum difference and a two-level maximum difference respectively. In a general case, the larger the resolution coefficient ρ, the larger the resolution, and the smaller the resolution coefficient ρ, the smaller the resolution.
(5) Calculating the gray weighted association degree, and performing gray association analysis, wherein the calculation formula is as follows:
Figure BDA0002186279560000093
wherein r isiAnd determining the evaluation result for the weighted relevance of the ith index to the ideal object by taking the weighted relevance as a reference.
(6) Calculating a relative closeness C of a solutioni
Figure BDA0002186279560000094
(7) And sorting according to relative closeness size. The scheme with high closeness degree is better, the contribution to improving the power distribution network is higher, and the evaluation result is obtained.
Example analysis
The method comprises the steps of taking three improved IEEE33 nodes as examples, simulating the situation that a flexible switch is connected into a power distribution network, accessing the flexible switch into a feeder terminal containing a plurality of distributed power supply grid-connected devices as shown in figure 4, assuming that each power distribution system is connected with distributed renewable energy sources with a fixed quantity, photovoltaic systems are respectively connected with 1-14 nodes and 1-17 nodes, rated capacities are 200kVA and 300kVA, power factors are 0.9, three wind power generating sets are connected with 1-15 nodes, 2-14 nodes, 2-16 nodes and 2-17 nodes, rated capacities are 200kVA, 300kVA, 200kVA and 400kVA, power factors are 0.9, three-terminal flexible switches are connected with 1-18 nodes, 2-18 nodes and 3-18 nodes, connecting line impedance is half of of a distribution line with the maximum impedance of an IEEE33 node, operation conditions of the three-terminal flexible switch when the power distribution system is connected with different load conditions are simulated, operation conditions of the three terminals are different, operation conditions of the three terminals under different load conditions are determined, results are shown in figure 5, initial consideration is given to a comprehensive planning and a comprehensive evaluation scheme for a preliminary screening of a power distribution network, a comprehensive distribution system, a comprehensive optimization evaluation method is obtained, a comprehensive optimization evaluation scheme is carried out, and a comprehensive evaluation method for a comprehensive optimization evaluation method for a comprehensive decision-based on a comprehensive distribution network, a comprehensive distribution system, a comprehensive switch arrangement cost-based on a comprehensive optimization evaluation scheme, a comprehensive optimization evaluation method is obtained, a comprehensive optimization scheme, a comprehensive optimization method is carried out, a comprehensive.
The present invention is not limited to the above embodiments, and any changes or substitutions that can be easily made by those skilled in the art within the technical scope of the present invention are also within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (8)

1, A two-step decision method for optimizing access of a flexible multi-state switch, which is characterized by comprising the following steps:
step 1, establishing an initial screening index of the access position of the flexible multi-state switch based on external characteristics, and performing -based treatment and sequencing;
step 2: establishing considerations includes: the method comprises the following steps that a multi-index flexible multi-state switch including system reliability, voltage deviation and distributed power supply acceptance capacity is optimally accessed into a comprehensive decision calculation model;
and step 3: evaluating the reliability of the system based on a power flow equation and constraint conditions which are optimally met by the operation of the flexible multi-state switch;
and 4, step 4: and establishing a multi-index decision model based on grey correlation analysis, determining weight assignment and finally determining an optimal scheme.
2. The two-step decision method of claim 1, comprising: the preliminary screening indexes comprise: load balancing degree, flexible switch arrangement and connection distance, important user number and distributed power supply number.
3. The two-step decision method of claim 1, comprising: the system reliability indicators include: the method comprises the following steps of load point average fault rate index, load point fault power failure time expected value, load point power supply reliability and system average power failure duration.
4. The two-step decision method of claim 1, comprising: the weight setting of the voltage deviation indicator takes into account two factors: the electrical distance between the node and the head end of the feeder line, the DG access position and the output.
5. The two-step decision method of claim 1, comprising: the distributed power supply acceptance capacity index adopts the distributed power supply permeability under the maximum acceptance capacity as an evaluation index, and considers the probability characteristics of DGs and loads.
6. The two-step decision method of claim 1, comprising: the multiple indexes further comprise economic benefit indexes: the network loss income and the flexible switch construction investment cost are reduced, and the upgrading and reconstruction benefits are delayed.
7. The two-step decision method of claim 1, comprising: the step 3 comprises the following steps: and realizing power balance of each node and non-out-of-limit of voltage and current on each branch by using a power flow equation and constraint conditions, simultaneously considering the fluctuation of DG output, the time sequence characteristics of different load types and the control time sequence characteristics of the flexible switch, and performing reliability evaluation by adopting a sequential Monte Carlo method.
8. The two-step decision method of claim 1, comprising: the step 4 comprises the following steps:
processing the multiple indexes into to obtain a normalized decision matrix;
a decision scheme matrix set composed of decision schemes obtained according to the evaluation object and the evaluation index;
forming an index set according to different index attributes;
obtaining an index average value for measuring the average level;
determining a positive ideal index set, a negative ideal index set and a regional index set, and linearly transforming operators for the index values; obtaining a normalized decision matrix under an ideal condition;
calculating the distance from the scheme obtained after the preliminary screening to an ideal index value;
calculating a grey correlation coefficient of the sequence to the reference sequence on a certain index;
calculating gray weighted association degree, and determining an evaluation result by taking the gray weighted association degree as reference;
and calculating the relative closeness of the scheme, and sequencing according to the relative closeness to obtain an evaluation result.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112053045A (en) * 2020-08-21 2020-12-08 国网浙江省电力有限公司 Power distribution project popularization index calculation method and system based on flexible switch
CN113013869A (en) * 2020-11-03 2021-06-22 国网浙江省电力有限公司 Active power distribution network four-terminal soft switch planning method based on reliability evaluation
CN113344386A (en) * 2021-06-07 2021-09-03 南京理工大学 Electric vehicle charging station planning scheme quantitative evaluation method

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112053045A (en) * 2020-08-21 2020-12-08 国网浙江省电力有限公司 Power distribution project popularization index calculation method and system based on flexible switch
CN113013869A (en) * 2020-11-03 2021-06-22 国网浙江省电力有限公司 Active power distribution network four-terminal soft switch planning method based on reliability evaluation
CN113013869B (en) * 2020-11-03 2022-02-22 国网浙江省电力有限公司 Active power distribution network four-terminal soft switch planning method based on reliability evaluation
CN113344386A (en) * 2021-06-07 2021-09-03 南京理工大学 Electric vehicle charging station planning scheme quantitative evaluation method
CN113344386B (en) * 2021-06-07 2022-08-19 南京理工大学 Electric vehicle charging station planning scheme quantitative evaluation method

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