CN117081141B - Micro-grid island division method based on entropy method-set pair analysis - Google Patents

Micro-grid island division method based on entropy method-set pair analysis Download PDF

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CN117081141B
CN117081141B CN202310853631.7A CN202310853631A CN117081141B CN 117081141 B CN117081141 B CN 117081141B CN 202310853631 A CN202310853631 A CN 202310853631A CN 117081141 B CN117081141 B CN 117081141B
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island
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王灿
王振
褚四虎
马辉
张晓佳
张佳恒
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China Three Gorges University CTGU
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Abstract

The micro-grid island division method based on entropy method-set pair analysis comprises the following steps: step 1: constructing a load index comprehensive relation model based on entropy method-set pair analysis; step 2: constructing a micro-grid island division model; step 3: and solving the micro-grid island division model by adopting a dynamic programming algorithm. The method fully evaluates the priority of the load and the economic loss of power failure, reduces the economic loss caused by power failure of the load in the island division process and ensures the power supply reliability of important loads.

Description

Micro-grid island division method based on entropy method-set pair analysis
Technical Field
The invention relates to the technical field of micro-grid island division, in particular to a micro-grid island division method based on entropy method-set pair analysis
Background
Along with the higher permeability of the distributed power supply, the traditional power supply protection measures cannot adapt to the influence caused by the structural change of the micro-grid, and island operation is widely applied to the micro-grid as a novel protection measure. The switching of the grid connection and island operation modes of the micro-grid can enable the distributed power supply to be used as a supplementary power supply and a standby power supply, and island operation is an important operation mode for guaranteeing important load power supply in the micro-grid after a fault. Therefore, the method has important practical significance in ensuring safe switching of the island operation of the micro-grid, improving the power supply reliability of the micro-grid, reducing the load power failure loss caused by the power system fault and the like.
In the prior art, a literature [1]:"A Risk Management Procedure for Island Partitioning of Automated Radial Distribution Networks With Distributed Generators"(Zeljko N.Popovic,Stanko D.Knezevic,Branislav S.Brbaklic,"A Risk Management Procedure for Island Partitioning of Automated Radial Distribution Networks With Distributed Generators,"IEEE trans.power syst.,vol.35,no.5,pp.3895-3905,Sept.2020.) proposes an automatic radial island division method aiming at the problems of power generation and load uncertainty in island division, and the method makes different island division scenes according to the correlation between loads and distributed power supplies. However, this document focuses on the economy of system operation after islanding, and does not consider the priority of the load.
Document [2]:"Bi-level service restoration strategy for active distribution system considering different types of energy supply sources"(Li Z,Khrebtova T,Zhao N,et al.Bi-level service restoration strategy for active distribution system considering different types of energy supply sources.IET Generation,Transmission&Distribution.2020,14(9):4186-4194.) constructs a double-layer optimization method to solve the optimal island to minimize the economic cost in the fault recovery process and re-activate the most electricity load. The planned island is characterized in that island dividing areas are planned in advance according to the output and load capacity of the distributed power supply in the micro-grid, but the actual island occurrence time is unpredictable, and the actual situation can lead the island dividing areas planned in advance to have certain deviation, so that the utilization efficiency of the distributed power supply can not be fully exerted or the continuous power supply of important loads in the micro-grid can not be met.
Aiming at the problem of island division of a distributed power supply under the condition of unplanned island fault of a micro-grid, literature [3]:"Optimization strategy for island partitioning and reconfiguration of faulted distribution network containing distributed generation"(Y.Xiang,J.Liu,L.Yao,et al.,"Optimization strategy for island partitioning and reconfiguration of faulted distribution network containing distributed generation,"Power System Technology,vol.37,no.4,pp.1025-1032,Apr.2013.) provides a two-stage structure optimization method of the micro-grid, an initial island solution set is searched by adopting a hidden enumeration method, and then an interruption magnitude value is checked and reactive compensation is calculated so as to determine a final island. According to the running characteristics of the distributed power supply, the literature [4]:"A Method to Ensure Power Supply Reliability for Key Load in Distribution Network Containing Distributed Generation"(X.Xie,F.Wang,Q.Chen,et al.,"A Method to Ensure Power Supply Reliability for Key Load in Distribution Network Containing Distributed Generation,"Power System Technology,vol.37,no.5,pp.1447-1453,May 2013.) utilizes a binary combination variation particle swarm algorithm to conduct global optimal search on the power distribution system, and the isolated island obtained by dividing has certain frequency modulation and voltage regulation capability. From the above-mentioned literature study, it is known that when a system fails, a micro-grid can form an island by a distributed power source to continuously supply power to a load, and island division is one of important means for recovering power supply of the system after the failure. But selecting which load resumes its power supply is also a research topic, and various properties of the load affect the reliability and economy of the system after island division.
Disclosure of Invention
In order to scientifically and reasonably divide the micro-grid island, ensure safe switching of the operation of the micro-grid island, improve the power supply reliability of the micro-grid and reduce the loss of load power failure caused by power system faults. The invention provides a micro-grid island dividing method based on entropy method-set pair analysis, which fully evaluates the priority of a load and economic loss of power failure, reduces the economic loss caused by power failure of the load in the island dividing process and ensures the power supply reliability of important loads.
The technical scheme adopted by the invention is as follows:
the micro-grid island division method based on entropy method-set pair analysis comprises the following steps:
step 1: constructing a load index comprehensive relation model based on entropy method-set pair analysis;
Step 2: constructing a micro-grid island division model;
step 3: and solving the micro-grid island division model by adopting a dynamic programming algorithm.
The step 1 comprises the following steps:
Step 1.1: two sets A, B with degrees of association are described by the degree of association, which is expressed as:
μA-B＝a+bI+cJ；
a+b+c＝1；
Wherein mu A-B is the degree of association of the set pair formed by the two sets; a. b and c are the same degree, the difference degree and the opposite degree respectively; I. j is a difference coefficient and a contrast coefficient respectively; the range of values of I is between [ -1,1], when I takes-1 and 1, the representation is deterministic, and as I approaches 0, the uncertainty of b is stronger; j is usually-1. N is the total number of features contained in the set pair; s, F, P are two sets of common feature numbers, opposite feature numbers, and neither common nor opposite feature numbers, respectively.
Step 1.2: calculating the degree of association mu ijk of the load evaluation index j of each load i with the evaluation standard grade, and then calculating the comprehensive degree of association of the load i by using the degree of association mu ijk
The step 1.2 comprises the following steps:
Step 1.2.1: dividing the class of the load evaluation index j of the load i into five classes of I, II, III, IV and V, wherein: the level I is optimal and the level V is worst. s k is a limit value corresponding to each level, k=1, 2,3,4,5, and each level corresponds to one limit region;
Step 1.2.2: for evaluation indexes of different pointing types, the relevance function μ k of each level represents different, and the formula μ A-B =a+bi+ cJ can be further expanded to:
μk＝μA-B＝aij+bij_1I1+bij_2I2+…+bij_mIm+cijJ
Wherein a ij、cij is the same degree and opposite degree corresponding to the load evaluation index j of the load i, and b ij_1、bij_2、bij_m is the difference degree corresponding to the evaluation index j of the load i after expansion;
Step 1.2.3: when calculating the single-index association degree mu ijk, taking a load i and an evaluation standard grade k which are associated with a load evaluation index j as two sets, and forming a set pair;
for smaller and better indices, the single index association degree μ ijk of the evaluation index of the load i is calculated as follows:
For the larger and better index, the single-index association degree μ ijk of the evaluation index of the load i is calculated as follows:
Wherein x ij is a sampling value of the load i evaluation index j; if the sampling value x ij is in the range of the value required by the evaluation standard level k, the index association degree mu ijk =1; if x ij is at a level of separation, μ ijk = -1; if x ij is in the adjacent rank, then the closer μ ijk∈[-1,1];xij is to rank k, the closer μ ijk is to 1, and the closer x ij is to the rank spaced from rank k, the closer μ ijk is to-1.
In the step1, the load importance level and the unit power change coefficient are positive indexes in the three selected load evaluation indexes, and the larger the value is, the better the value is; the load outage economic loss is a negative index, and the smaller the value is, the better the value is;
Calculating the association degree of each index according to the corresponding association degree function, coupling the entropy weight of the index into the set pair association, and calculating the comprehensive association degree between the load i and the evaluation standard grade k The method comprises the following steps:
Wherein ω j is the weight of the evaluation index j calculated based on the entropy method; Comprehensive association degree for evaluation index of load i, and/> If the degree of identity between the load i and the evaluation criterion class k is greater,/>The closer to 1, the more prone the load i is to membership grade k; conversely, if the load i is closer to the evaluation criterion class k, the degree of difference between the load i and the evaluation criterion class k is greaterThe closer to-1, the more prone the load i is to be not affiliated to the evaluation criterion class k; m is the total number of loads.
In the step 2, the micro-grid island division model comprises an objective function and constraint conditions;
the maximum load comprehensive recovery amount after the micro-grid faults is used as an objective function:
In the method, in the process of the invention, The index comprehensive relation degree of the node load i calculated for the second part; p Li is the active power of the load node P; x i is an integer variable, when x i =1, indicating that the load i is divided in an island, and when x i =0, indicating that the load i is not divided in an island; n is the total number of indexes involved in the evaluation.
The island division problem is to find the optimal solution of the objective function on the premise of meeting the constraint, and the objective function solution should meet the following constraint conditions:
(1) Island internal power balance constraint:
When dividing an island, the maximum active power which can be supplied by a distributed power supply in the island is not lower than the load power, and the reactive power is used for compensating on site, and is specifically expressed as follows:
In the method, in the process of the invention, Active power and reactive power capacity for all distributed power sources output in the island; Active power and reactive power capacity for all loads in the island; k is the number of distributed power supplies in the island; m is the total number of loads; p Gi is the active power output by the distributed power supply i in the island; p Li is the active power of load i in island; q Gi is reactive power output by the distributed power supply i in the island; q Li is the reactive power of the load i in the island.
(2) Node voltage constraint:
The voltage on the bus cannot be out of limit, and excessive voltage can cause overheating of long-term electrified equipment or damage to the equipment. The low voltage of the node bus can cause switching and protection actions, so that the actions of the system are unreliable, and the network stability is influenced. The node voltage constraint is expressed as:
Uimin≤Ui≤Uimax
Wherein U i is the voltage of node i; u imin and U imax are the minimum and maximum values of the voltage at node i, respectively.
(3) Line current constraint:
In order to ensure that the protection action does not malfunction when the island is operated, the current flowing through the transformer and the current flowing through the line should not exceed rated currents, otherwise the protection action causes the line to be out of operation, thus causing unbalanced power in the island.
Imaxij<INij
Wherein, I maxij is the maximum current flowing through the transformer and the line; i Nij is the rated current on the transformer and line.
(4) Island radiation operation constraints:
g∈G
Wherein g is the network topology structure after fault recovery; g is the set of network radial structures.
Step 3: the island division objective function is solved by adopting a dynamic programming algorithm, and the specific steps of solving are as follows:
Step1, reading the whole network structure information, the fault occurrence position, the output power of the distributed power supply and the load capacity, and initializing the state variables of the dynamic programming algorithm.
Step2, calculating index weights of the load evaluation indexes of all nodes by adopting an entropy method, analyzing and calculating the degree of association between the load indexes and the I-level evaluation grade by a set, and coupling the load evaluation index entropy weights and the index association degree into a load evaluation index comprehensive association degree.
Step3, searching and dividing the primary island range by adopting a dynamic programming algorithm, judging whether the important loads are in the island after the division is finished, if not, entering Step4, and if so, entering Step5.
Step4, traversing all nodes again by using a dynamic programming algorithm, ensuring that the I-level important load completely enters the island area to restore power supply, and then updating the island range.
Step5, judging whether the power balance constraint is met, if not, cutting off the part II and III, adjusting the power supply area by the load, and updating the island range again until the power balance constraint is met and entering the next Step.
Step6, outputting a final island division result.
The invention discloses a micro-grid island division method based on entropy method-set pair analysis, which has the following technical effects:
1) In the step 1 of the invention, the fitting degree among various indexes of different loads is described by adopting a set analysis principle, the quantitative analysis of the same, different and opposite is carried out by utilizing the relation degree, and the uncertainty factors and the deterministic factors of the load indexes are included into the comprehensive relation degree to carry out dialectical analysis and mathematical treatment:
① The set of impacts on the analysis may comprehensively consider the impact of multiple load metrics, thereby providing a more comprehensive and comprehensive load analysis result.
② Set pair analysis may help identify correlations and interrelationships between different load indicators. By analyzing the correlation among different indexes, hidden rules and correlations can be found, and a reference basis is provided for the subsequent island division.
2) In the step 2 of the invention, the maximum load comprehensive recovery amount after the micro-grid fault is used as an objective function of island division, and the power balance constraint, the node voltage constraint, the line current constraint and the island radiation operation constraint in each island are fully considered. The following principles are followed:
① Important load priority principle. The interruption of the power supply of the load can cause certain economic loss and can cause personal safety influence when serious. According to the important order of the loads, the I and II-level loads should be powered preferentially, and when the DG capacity is sufficient, the III-level loads are powered as much as possible.
② Maximum load principle. In order to improve the utilization rate of DG in the micro-grid system and reduce energy waste, the island division should ensure as much load power supply as possible in the system and reduce the load power loss.
③ The radial operation principle of the power grid. According to the open-loop operation requirement of the micro-grid, the network is ensured to be in a radial structure when the island is divided, so that the stability and the reliability of the operation of the micro-grid are improved.
④ The principle of less switching times. The island division should select a division scheme with the least switching operation times, so as to reduce the action loss of the switching element and improve the action timeliness of the system.
The guidelines aim at ensuring the safe, reliable and stable operation of the system, not only ensuring the stable operation of the island, but also minimizing the loss of power failure as much as possible, thereby improving the power supply quality and the satisfaction degree of users.
3) In step 3 of the present invention, the objective is to restore the power supply to the important load as much as possible when island division is performed, so as to avoid overload of the system due to overload. However, island partitioning involves a number of factors, including factors in terms of load demand, DG output, stability, system capacity, etc., which affect each other and are mutually constrained, and it is difficult to build a suitable model solution for island partitioning. Therefore, the method solves the island division model of the micro-grid by adopting a dynamic programming algorithm, and the algorithm can obtain a more reasonable result in a shorter time, thereby being beneficial to improving the efficiency and the precision of island division of the micro-grid. By solving the island division objective function, the invention can obtain a more scientific and efficient island division scheme and provide effective technical support and guarantee for the recovery work of the micro-grid.
4) According to the method, the three indexes of the importance level of the load, the economic loss of the power failure of the load and the unit power change coefficient are subjected to objective weight assignment by using an entropy method, and the weights of different indexes are assigned by using the attribute of the data, so that the interference of subjective factors is avoided.
5) The method constructs a load index comprehensive relation degree determining method based on a set analysis principle. And optimizing different load indexes by utilizing a set analysis principle, and describing the relation between different loads and evaluation grades through the comprehensive association degree of the load indexes. The advantages are that: the relation degree can express the relation between the load index and the load evaluation standard, and can reflect the influence of the load on the reliable power supply of the important load and the economic operation of the system in island division.
6) The method combines the load weight and the set analysis principle to construct the micro-grid island division model. The micro-grid island division model can carry out differential division on load nodes and determine the optimal island area.
Drawings
Fig. 1 is a microgrid island division flow diagram.
FIG. 2 (a) is an island division diagram of method A when tie lines are considered;
FIG. 2 (B) is an island division diagram of method B when tie lines are considered;
Fig. 2 (C) is an island division diagram of method C when the tie line is considered.
FIG. 3 is a graph of the load distribution in each method division island.
Detailed Description
The micro-grid island division method based on entropy method-set pair analysis comprises the following steps:
Step one, constructing a load index comprehensive association degree model based on entropy method-set pair analysis:
The collection pair is formed by combining two collections with certain connection, the relationship degree is used for quantitatively describing the object information, and the relationship and conversion relationship between the two collection pairs are reflected through the 'same degree, different degree and opposite degree'.
(1) Set analysis principle:
Two sets A, B with a degree of association are characterized by their "same, different, opposite" characteristics, expressed as:
μA-B＝a+bI+cJ
a+b+c＝1
wherein mu A-B is the degree of association of the set pair formed by the two sets; a. b and c are the same degree, the difference degree and the opposite degree respectively; I. j is a difference coefficient and a contrast coefficient respectively, the value range of I is between [ -1,1], when I takes-1 and 1, the representation is deterministic, and as I approaches 0, the uncertainty of b is stronger; j is usually-1. N is the total number of features contained in the set pair; s, F, P are two sets of common feature numbers, opposite feature numbers, and neither common nor opposite feature numbers, respectively.
(2) And (3) comprehensive contact degree determination:
Because the load evaluation involves a plurality of evaluation indexes, and the influence effect of each index has a difference on the operation influence of the micro-grid after island, the same-opposite correlation degree mu ijk of the evaluation index j of each load i and the evaluation index standard corresponding to each evaluation grade is needed, and then the comprehensive correlation degree of the load i is further calculated by utilizing mu ijk The invention divides the evaluation standard class of the load into five classes of I, II, III, IV and V, wherein the class I is optimal and the class V is worst. s k (k=1, 2,3,4, 5) is a limit value corresponding to each level, and each level corresponds to one limit region.
The degree of association is a key link for researching load stability evaluation in island division, and the degree of association function mu k of each level is different for indexes of different pointing types according to the data characteristics of each index of the load. The formula μ A-B =a+bi+ cJ can be further extended as:
μk＝μA-B＝aij+bij_1I1+bij_2I2+…+bij_mIm+cijJ
Where a ij、cij is the degree of identity and the degree of opposition corresponding to the evaluation index j of the load i, and b ij_1、bij_2、bij_m is the degree of difference corresponding to the evaluation index j of the load i after expansion.
When calculating the single index association degree mu ijk, the load i and the evaluation standard grade k which are related to the load evaluation index j are taken as two sets, and form a set pair, so that quantitative analysis of 'same, different and opposite' is performed on the attribute of the proximity of the load i and the evaluation standard grade k.
For smaller and better indices, the single index association degree μ ijk of the evaluation index of the load i is calculated as follows:
For the larger and better index, the single-index association degree μ ijk of the evaluation index of the load i is calculated as follows:
Wherein x ij is a sampling value of the load i evaluation index j; if the sampling value x ij is in the range of the value required by the evaluation standard level k, the index association degree mu ijk =1; if x ij is at a level of separation, μ ijk = -1; if x ij is in the adjacent rank, then the closer μ ijk∈[-1,1];xij is to rank k, the closer μ ijk is to 1, and the closer x ij is to the rank spaced from rank k, the closer μ ijk is to-1.
Among the three load evaluation indexes selected by the invention, the load importance level and the unit power change coefficient are forward indexes, and the larger the value is, the better the value is. The load outage economic loss is a negative index, and the smaller the value is, the better the value is. Calculating the association degree of each index according to the corresponding association degree function, coupling the entropy weight of the index into the set pair association, and calculating the comprehensive association degree between the load i and the evaluation standard gradeThe method comprises the following steps:
Wherein ω j is the weight of the evaluation index j calculated based on the entropy method; Comprehensive association degree for evaluation index of load i, and/> If the degree of identity between the load i and the evaluation criterion class k is greater,/>The closer to 1, the more prone the load i is to membership grade k; conversely, if the load i is closer to the level k, the degree of difference is greater,/>The closer to-1, the more prone the load i is to not be affiliated with the rating k.
The part establishes a corresponding load evaluation method by combining the set analysis theory and the load evaluation system, and forms a set pair by the load index and the divided load evaluation grade. In order to more accurately distinguish the difference between the load index and the load evaluation grade, the triangular fuzzy number is converted into the relation degree according to each divided threshold interval. The relation between the load index and the load evaluation standard is expressed by the relation, and the influence of the important load power supply stability and the economic operation of the system in the island division of the load is reflected by the relation. In the island division load evaluation standard, the optimal comprehensive evaluation grade I of the load is prioritized, so that the comprehensive association degree of the load on the grade I is given priorityIs the reference basis.
Step two, constructing island division optimization objective functions and constraint conditions:
the invention takes the maximum load comprehensive recovery amount after micro-grid faults as the objective function of island division:
In the method, in the process of the invention, The index comprehensive relation degree of the node load i calculated for the second part; p Li is the active power of the load node P; x i is an integer variable. When x i =1, it means that the load i is divided in the island, and when x i =0, it means that the load i is not divided in the island.
The island division problem is to find the optimal solution of the objective function on the premise of meeting the constraint, and the island division objective function solution should meet the following constraint condition.
(1) Island internal power balance constraint:
When dividing an island, the maximum active power which can be supplied by a distributed power supply in the island is not lower than the load power, and the reactive power is used for compensating on site, and is specifically expressed as follows:
In the method, in the process of the invention, Active power and reactive power capacity for all distributed power sources output in the island; Active power and reactive power capacity for all loads in an island.
(2) Node voltage constraint:
The voltage on the bus cannot be out of limit, and excessive voltage can cause overheating of long-term electrified equipment or damage to the equipment. The low voltage of the node bus can cause switching and protection actions, so that the actions of the system are unreliable, and the network stability is influenced. The node voltage constraint is expressed as:
Uimin≤Ui≤Uimax
Wherein U i is the voltage of node i; u imin and U imax are the minimum and maximum values of the voltage at node i, respectively.
(3) Line current constraint:
In order to ensure that the protection action does not malfunction when the island is operated, the current flowing through the transformer and the current flowing through the line should not exceed rated currents, otherwise the protection action causes the line to be out of operation, thus causing unbalanced power in the island.
Imaxij<INij
Wherein, I maxij is the maximum current flowing through the transformer and the line; i Nij is the rated current on the transformer and line.
(4) Island radiation operation constraints:
g∈G
Wherein g is the network topology structure after fault recovery; g is the set of network radial structures.
Executing a micro-grid island division method:
According to the method, the dynamic programming algorithm is adopted to solve the micro-grid island division model, and the algorithm can obtain a reasonable result in a short time, so that the efficiency and the precision of micro-grid island division are improved. By solving the island division objective function, the island division method is more scientific and efficient, and effective technical support and guarantee are provided for the recovery work of the micro-grid. The island division objective function is solved by the method. Fig. 1 is a micro-grid island division flow chart. The micro-grid island division method comprises the following specific steps of:
Step1, reading the whole network structure information, the fault occurrence position, the output power of the distributed power supply and the load capacity, and initializing the state variables of the dynamic programming algorithm.
Step2, calculating index weights of the load evaluation indexes of all nodes by adopting an entropy method, analyzing and calculating the degree of association between the load indexes and the I-level evaluation grade by a set, and coupling the load evaluation index entropy weights and the index association degree into a load evaluation index comprehensive association degree.
Step3, searching and dividing the primary island range by adopting a dynamic programming algorithm, judging whether the important loads are in the island after the division is finished, if not, entering Step4, and if so, entering Step5.
Step4, traversing all nodes again by using a dynamic programming algorithm, ensuring that the I-level important load completely enters the island area to restore power supply, and then updating the island range.
Step5, judging whether the power balance constraint is met, if not, cutting off the part II and III, adjusting the power supply area by the load, and updating the island range again until the power balance constraint is met and entering the next Step.
Step6, outputting a final island division result.
Fig. 2 (a) to 2 (c) are isolated island division diagrams of the respective methods when the tie lines are considered. The micro-grid island division method based on entropy method-set pair analysis is compared with a double-layer service recovery method of an active power distribution system taking different types of energy sources into consideration in method B, and an active power distribution network fault recovery method based on second-order cone planning in method C.
Fig. 2 (a) shows the island division result of method a, which forms 4 island regions, island 1 comprising distributed power supply 4 and distributed power supply 6, and which is formed for disconnected branches 1-2, 36-37. Island 2 contains distributed power supply 2 and distributed power supply 5, which opens branches 40-41, 47-48, 61-62, 67-68, 10-11 while closing tie switch S1. Island 3 contains distributed power supply 3, which opens branches 11-12, 11-55, 57-58, 15-16, closing tie switch S3. Island 4 contains distributed power supply 1, which opens branches 17-18, 50-51, 52-53, closing tie switch S4.
Fig. 2 (B) shows the island division result of method B, which divides the micro-grid into 5 island regions, the island 1 comprising the distributed power source 4 and the distributed power source 6, the island being formed by the disconnection branches 6-7, 29-30, 37-38. Island 2 comprises a distributed power supply 2, which island is formed for breaking branches 43-44, 47-48. Island 3 contains distributed power supply 5, which opens branches 61-62, 67-68, 9-42, 10-11 while closing tie switch S1. Island 4 contains distributed power supply 3, which opens branches 11-12, 11-55, closing tie switch S3. Island 5 contains distributed power supply 1, which opens branches 17-18, 50-51, 52-53, closing tie switch S4.
Fig. 2 (C) shows the island division result of method C, wherein the micro-grid is divided into 4 island regions, and island 1 comprises distributed power source 4 and distributed power source 6, and the island is formed by disconnecting branches 2-3, 4-5, 30-31, and 37-38. Island 2 contains distributed power supply 2 and distributed power supply 5, which in island division disconnects branches 62-63, 68-69, 8-9, 10-11, 47-48. While closing tie switch S1. Island 3 contains distributed power supply 3, which opens branches 11-12, 11-55, 15-16, 57-58, closing tie switch S3. Island 4 contains distributed power supply 1, which opens branches 17-18, 50-51, 52-53, closing tie switch S4. The three methods respectively act on the switch 17 times, 17 times and 19 times in the island dividing process.
FIG. 3 is a graph of the load distribution in islands of each method division. The micro-grid island division method based on entropy method-set pair analysis is compared with a double-layer service recovery method of an active power distribution system taking different types of energy sources into consideration in method B, and an active power distribution network fault recovery method based on second-order cone planning in method C. From the graph of fig. 3, which shows the load distribution pattern included in each island of method a, the i-level load ratios in islands 1-4 were 9.44%, 19.54%, 77.52%, and 16.65%, respectively. In fig. 3, subplot B shows a load profile included in each island of method B, with the i-level load ratios in the islands 1-5 divided under the method being 1.68%, 0%, 25.73%, 60.81%, 16.65%, respectively. In fig. 3, subplot C shows a load profile included in each island of method C, with the i-level load ratios in the islands 1-5 divided under the method being 0%, 12.69%, 77.52%, 16.65%, respectively. In consideration of the tie switch closure, the island region still exists within the island region divided by methods B and C and does not contain a class i important load. Under the scene, the method A still ensures that the power supply of the I-level important load exists in each island area, and ensures the reliability of island operation.
Table 1 comparison of island division method results
Table 1 is a comparison table of island division method results, and compares a micro-grid island division method based on entropy method-set pair analysis provided by the method a with a double-layer service recovery method of an active power distribution system taking different types of energy sources into consideration by the method B, and a fault recovery method of the active power distribution network based on active management of second-order cone planning by the method C. As can be seen from the comparison result,
The I-stage load recovery power of method A was 322.25kW, the I-stage load recovery rate was 100%, and the I-stage load recovery power of methods B and C was 277.9kW and 283.65kW, respectively, and the I-stage load recovery rates were 86.24% and 88.02%, respectively.
Since method B does not take into account the importance level of the load during the division, method B cannot guarantee that all the important loads of level i are powered back. The method C is limited by the influence of the fixed load weight to cause misjudgment of the important load, so that the recovery of the I-level important load under the method C is incomplete. The method A optimizes the defect of fixed weight in solving, so that the method A divides the I-level load in the system into islands to continuously supply power when the islands are divided. Meanwhile, in the method A, B and the method C, the I-level important load recovery rate is improved when the contact line switch is closed in a less consideration manner.
The economic loss of power outage per unit time caused by the three methods after island division is 39.94$/kWh, 45.31$/kWh and 47.86$/kWh respectively. The method A fully considers the economic loss of load outage during island division, so that the selection of the load during island formation can fully consider the load with higher priority recovery outage loss, and the load outage loss during island operation is minimized. The method B considers the total economic cost in the recovery process after island division, the method C does not consider the economic loss of island operation, so that the method B and the method C ignore the economic loss caused by load outage in the load selection process, and meanwhile, the method B does not consider the importance level of the load, and the important load is cut off to cause the economic loss of the whole system. In addition, method a closes the tie switches S1, S3, S4, discards the more powerful load nodes such as 68, 69, 17, and switches in more small load nodes, restoring more load power and increasing the power supply area at limited distributed power source output power. The island divided by the method A fully utilizes the output power of the distributed power supply, the utilization rate of the distributed power supply of the island in the method A is 97.432%, the utilization rates of the distributed power supplies of the island in the method B, C are 96.559% and 97.144%, and under the condition that the connection line switch is considered to be closed, the utilization rate of the distributed power supply in the island is effectively improved by the methods, and load power supply in the island is recovered as much as possible. The method A has more load power supply recovered in island division, and reduces the loss caused by the load in outage.

Claims (5)

1. The micro-grid island division method based on entropy method-set pair analysis is characterized by comprising the following steps of:
step 1: constructing a load index comprehensive relation model based on entropy method-set pair analysis;
Step 2: constructing a micro-grid island division model;
Step 3: solving the island division model of the micro-grid by adopting a dynamic programming algorithm;
The step 1 comprises the following steps:
Step 1.1: two sets A, B with degrees of association are described by the degree of association, which is expressed as:
μA-B＝a+bI+cJ；
a+b+c＝1；
Wherein mu A-B is the degree of association of the set pair formed by the two sets; a. b and c are the same degree, the difference degree and the opposite degree respectively; I. j is a difference coefficient and a contrast coefficient respectively; n is the total number of features contained in the set pair; s, F, P are two sets of common feature numbers, opposite feature numbers, and neither common nor opposite feature numbers, respectively;
step 1.2: calculating the degree of association mu ijk of the load evaluation index j of each load i with the evaluation standard grade, and then calculating the comprehensive degree of association of the load i by using the degree of association mu ijk
The step 1.2 comprises the following steps:
Step 1.2.1: dividing the class of the load evaluation index j of the load i into five classes of I, II, III, IV and V, wherein: the I level is optimal, and the V level is worst; s k is a limit value corresponding to each level, k=1, 2,3,4,5, and each level corresponds to one limit region;
Step 1.2.2: for the type of evaluation index, the relevance function μ k of each rank represents a difference, and the formula μ A-B =a+bi+ cJ can be further extended to:
μk＝μA-B＝aij+bij_1I1+bij_2I2+…+bij_mIm+cijJ
Wherein a ij、cij is the same degree and opposite degree corresponding to the load evaluation index j of the load i, and b ij_1、bij_2、bij_m is the difference degree corresponding to the evaluation index j of the load i after expansion;
Step 1.2.3: when calculating the single-index association degree mu ijk, taking a load i and an evaluation standard grade k which are associated with a load evaluation index j as two sets, and forming a set pair;
for smaller and better indices, the single index association degree μ ijk of the evaluation index of the load i is calculated as follows:
For the larger and better index, the single-index association degree μ ijk of the evaluation index of the load i is calculated as follows:
Wherein x ij is a sampling value of the load i evaluation index j; if the sampling value x ij is in the range of the value required by the evaluation standard level k, the index association degree mu ijk =1; if x ij is at a level of separation, μ ijk = -1; if x ij is in the adjacent rank, then the closer μ ijk∈[-1,1];xij is to rank k, the closer μ ijk is to 1, and the closer x ij is to the rank spaced from rank k, the closer μ ijk is to-1.
2. The micro-grid island division method based on entropy method-set pair analysis according to claim 1, wherein: in the step 1, the load importance level and the unit power change coefficient are positive indexes in the three selected load evaluation indexes, and the larger the value is, the better the value is; the load outage economic loss is a negative index, and the smaller the value is, the better the value is;
Calculating the association degree of each index according to the corresponding association degree function, coupling the entropy weight of the index into the set pair association, and calculating the comprehensive association degree between the load i and the evaluation standard grade k The method comprises the following steps:
Wherein ω j is the weight of the evaluation index j calculated based on the entropy method; comprehensive association degree for evaluation index of load i and If the degree of identity between the load i and the evaluation criterion class k is greater,/>The closer to 1, the more prone the load i is to membership grade k; conversely, if the load i is closer to the evaluation criterion class k, the degree of difference between the load i and the evaluation criterion class k is greaterThe closer to-1, the more prone the load i is to be not affiliated to the evaluation criterion class k; m is the total number of loads.
3. The micro-grid island division method based on entropy method-set pair analysis according to claim 1, wherein: in the step 2, the maximum load comprehensive recovery amount after the micro-grid fault is taken as an objective function:
In the method, in the process of the invention, The index comprehensive relation degree of the node load i calculated for the second part; p Li is the active power of load i in island; x i is an integer variable, when x i =1, indicating that the load i is divided in an island, and when x i =0, indicating that the load i is not divided in an island; n is the total number of indexes involved in the evaluation.
4. The micro-grid island division method based on entropy method-set pair analysis according to claim 3, wherein: the island division problem is to find the optimal solution of the objective function on the premise of meeting the constraint, and the objective function solution should meet the following constraint conditions:
(1) Island internal power balance constraint:
When dividing an island, the maximum active power which can be supplied by a distributed power supply in the island is not lower than the load power, and the reactive power is used for compensating on site, and is specifically expressed as follows:
In the method, in the process of the invention, Active power and reactive power capacity for all distributed power sources output in the island; active power and reactive power capacity for all loads in the island; l is the number of distributed power supplies in the island; m is the total number of loads; p Ge is the active power output by the distributed power supply e in the island; p Li is the active power of load i in island; q Ge is the reactive power output by the distributed power supply e in the island; q Li is the reactive power of the load i in the island;
(2) Node voltage constraint:
The voltage on the bus cannot be out of limit, and the voltage is too high, so that long-term electrified equipment is overheated or damaged; the low voltage of the node bus can cause switching and protection actions, so that the actions of the system are unreliable, and the network stability is influenced; the node voltage constraint is expressed as:
Uymin≤Uy≤Uymax
Wherein U y is the voltage of the node y; u ymin and U ymax are the minimum and maximum values of the voltage at node y, respectively;
(3) Line current constraint:
In order to ensure that the protection action does not malfunction when the island is operated, the current flowing through the transformer and the current flowing through the line should not exceed rated current, otherwise, the protection action causes the line to be out of operation to cause unbalanced power in the island;
Imaxij<INij
Wherein, I maxij is the maximum current flowing through the transformer and the line; i Nij is the rated current on the transformer and the line;
(4) Island radiation operation constraints:
g∈G
Wherein g is the network topology structure after fault recovery; g is the set of network radial structures.
5. The micro-grid island division method based on entropy method-set pair analysis according to claim 1, wherein: in step 3, the specific steps of solving are as follows:
step1, reading the whole network structure information, fault occurrence positions, distributed power supply output power and load capacity, and initializing a dynamic programming algorithm state variable;
Step2, calculating index weights of the load evaluation indexes of all nodes by adopting an entropy method, analyzing and calculating the degree of association between the load indexes and the I-level evaluation grade by a set, and coupling the load evaluation index entropy weights and the index association degree into a load evaluation index comprehensive association degree;
Step3, searching and dividing a primary island range by adopting a dynamic programming algorithm, judging whether important loads are in the island after division is finished, if not, entering Step4, and if so, entering Step5;
step4, traversing all nodes again by using a dynamic programming algorithm, ensuring that the I-level important load fully enters an island area to restore power supply, and then updating the island range;
step5, judging whether the power balance constraint is met, if not, cutting off the part II and III, adjusting the power supply area by the load, and updating the island range again until the power balance constraint is met and entering the next Step;
step6, outputting a final island division result.
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