CN111898796A - Method for optimizing reliability of multi-service converged power distribution network - Google Patents
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Abstract
The embodiment of the application provides a method for optimizing the reliability of a multi-service integrated power distribution network, which comprises the following steps: step 1, acquiring physical information and load flow information of a power distribution network; step 2, calculating the comprehensive vulnerability of each node of the power distribution network according to the physical information and the load flow information; step 3, acquiring the operation index of the power distribution network; step 4, calculating the reconstruction weight of each power distribution network operation index according to the power distribution network operation index; and 5, sorting the comprehensive vulnerability of each node and the transformation weight of the operation indexes of the power distribution network, and sorting the nodes transformed by the power distribution network and the operation index weights of the power distribution network as a transformation sequence of the power distribution network, so that the reliability of the power distribution network is improved. The method aims at helping a power grid company to carry out reliability optimization on the nodes of the power distribution network, selects a proper data type and carries out priority calculation. Therefore, the cost of a power grid company is controlled, and the power supply reliability and the economic benefit are improved.
Description
Technical Field
The invention belongs to the technical reliability field of a power distribution network, and particularly relates to a method for optimizing the reliability of a power distribution network with multi-service fusion.
Background
In order to meet the demands of users, power supply enterprises need to invest a large amount of capital every year for the construction and transformation of power distribution networks. In recent years, computer science and technology are rapidly developed, wherein big data technology is a very important product. The big data technology refers to a technical framework which is used for analyzing a large amount of data with complex sources and extracting the value of the data by a specific mathematical method.
At present, key technologies of benefit optimization analysis of a power distribution network based on big data mainly comprise a data preprocessing technology, a data storage technology, a data mining technology, a visualization technology and the like.
CN201610603366.7 discloses a distribution network transformation project economy evaluation method based on power supply reliability, which comprises the following steps: 1) reading engineering information to be evaluated; 2) loading the equipment reliability parameters of the project and the network structure chart before and after construction; 3) calculating the reliability index lifting amplitude VORI before and after the engineering construction; 4) calculating the average investment benefit index AAIR of the engineering in the introduced year; 5) the engineering was evaluated by AAIR. The method directly estimates the corresponding investment scale by means of the power distribution network planning result, but the method is not suitable for medium and low voltage power distribution network investment decisions with numerous projects and complex situations because the workload is too large. And other methods are mostly based on the power distribution network planning of an evaluation system, and the final result is greatly different due to the difference of the evaluation systems. The existing power distribution network investment optimization strategy is difficult to comprehensively reflect the relationship between cost and benefit reliability, so a new power distribution network asset operation reliability optimization method based on big data analysis needs to be provided.
Disclosure of Invention
In order to solve the technical problems in the prior art, the invention aims to provide a method for optimizing the reliability of a multi-service converged power distribution network. The method aims at helping a power grid company to carry out reliability optimization on the nodes of the power distribution network, selects a proper data type and carries out cost and fund accounting. Therefore, the cost of a power grid company is controlled, and the power supply reliability and the economic benefit are improved.
The invention adopts the following technical scheme. A method for optimizing the reliability of a multi-service converged power distribution network comprises the following steps:
step 1, acquiring physical information and load flow information of a power distribution network;
step 2, calculating the comprehensive vulnerability of each node of the power distribution network according to the physical information and the load flow information;
step 3, acquiring the operation index of the power distribution network;
step 4, calculating the reconstruction weight of each power distribution network operation index according to the power distribution network operation index;
and 5, sorting the comprehensive vulnerability of each node and the transformation weight of the operation indexes of the power distribution network, and sorting the nodes transformed by the power distribution network and the operation index weights of the power distribution network as the transformation sequence of the power distribution network.
Optionally, in step 1, the physical information of the power distribution network includes: number n of nodes of power distribution network and ith node v of power distribution networkiDegree k ofi，viThe ith node viAnd j node viLength d of shortest path betweenij，
Wherein i is 1,2, …, n; j is 1,2, …, n,
ith node v of power distribution networkiDegree k ofiRefers to the sum v in the distribution networkiThe number of directly connected edges;
vithe neighbor node set of (c) is defined byiA set of nodes connected directly by edges;
the trend information includes: ith node viInjection power P ofiReference capacity S of distribution network systemb。
Optionally, step 1 further includes:
calculating the average shortest distance L of the power distribution network according to the following formula,
in the formula: n represents the number of nodes of the power distribution network; g represents a power distribution network node set; dijRepresents the ith node viAnd j node viLength of shortest path between;
the ith node v is calculated by the following formulaiNode degree function Ii，
In the formula: liIndicating the deletion of the ith node v of the distribution networkiThen, the ith node v of the power distribution networkiThe number of the connected node pairs is maintained in a centralized manner by the neighbor nodes; k is a radical ofiRepresenting the ith node v of the distribution networkiDegree of (c).
Optionally, step 1 further includes:
the ith node v is calculated by the following formulaiInjection power ratio of NPi，
In the formula: piRepresents the ith node viThe injection power of (3); sbAnd representing the reference capacity of the power distribution network system.
Optionally, step 2 includes:
the ith node v is calculated by the following formulaiComprehensive vulnerability index N ofi，
Ni＝(a1ki+a2Ii+a3NPi) (4)，
In the formula: k is a radical ofiRepresenting the ith node v of the distribution networkiDegree of (a)1Represents its weight; i isiRepresents the ith node viNode degree function of a2Represents its weight; n is a radical ofPiRepresents the ith node viInjection power ratio of a3Representing its weight.
Optionally, in the step 2, the ith node v of the power distribution network is determined according to a fuzzy analytic hierarchy processiDegree k ofiWeight of a1I-th node viWeight a of the node degree function of2I-th node viWeight a of the injected power ratio of3。
Optionally, the power distribution network operation index in step 3 includes: p benefit-type indicators with ideal values of 1 and q cost-type indicators with ideal values of 0, wherein p and q are positive integers.
Optionally, the step 4 specifically includes:
step 4.1, calculating the index improvement degree of the power distribution network according to the following formula,
in the formula: mbenefitIndicating the improvement degree of the benefit type index; mbenefitIndicating the degree of improvement of the cost-type index; n is a radical ofreRepresenting the modified index value; n is a radical ofoRepresenting a current index value; constructing a power distribution network operation index improvement degree set according to the sequence of p benefit indexes and q cost indexes
Mz＝(M1,…,Mp,Mp+1,…,Mp+q)；，
Step 4.2, constructing a judgment matrix of (p + q) × (p + q) according to the calculation result in the step 3.1, and calculating an element beta in the judgment matrix according to the following formulaxy，
x denotes a row of the decision matrix, x is 1,2, … (p + q), y denotes a column of the decision matrix, y is 1,2, … (p + q);
step 4.3, calculating the weight of the operation index of the power distribution network by using the following formula,
w1,w2,…,w11representing the weights of p benefit-type indicators and q cost-type indicators, respectively.
Optionally, the benefit type indicator includes: the method comprises the following steps of (1) line interconnection rate, line section standardization rate, line standardization structure proportion, line N-1 passage rate, line insulation rate and distribution automation coverage rate;
cost-type indicators include: unreasonable proportion of line segment number, line length overrun proportion, heavy-load line proportion, heavy-load distribution ratio and high-loss distribution ratio.
Optionally, in step 4, the reconstruction weights of the p benefit indicators with ideal values of 1 and the q cost indicators with ideal values of 0 are determined by an analytic hierarchy process.
The method has the advantages that compared with the prior art, the method for optimizing the reliability of the power distribution network with multi-service integration is provided, the method aims at helping a power grid company to carry out power distribution network node reliability optimization, selects a proper data type, carries out transformation priority calculation and helps cost fund accounting, so that the power grid company is helped to control cost, and power supply reliability and economic benefit are improved.
Drawings
Fig. 1 is a flowchart of a method for optimizing reliability of a multi-service converged power distribution network according to the present invention.
Detailed Description
The present application is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present application is not limited thereby.
As shown in fig. 1, the present invention provides a method for optimizing reliability of a power distribution network with multi-service convergence, which is characterized by comprising the following steps:
step 1, acquiring physical information and load flow information of the power distribution network.
The physical information of the power distribution network includes: number n of nodes of power distribution network and ith node v of power distribution networkiDegree k ofi，viThe ith node viAnd j node viLength d of shortest path betweenij，
Wherein the content of the first and second substances,
i＝1,2,…,n；j＝1,2,…,n，
ith node v of power distribution networkiDegree k ofiRefers to the sum v in the distribution networkiThe number of directly connected edges;
vithe neighbor node set of (c) is defined byiA set of nodes connected directly by edges;
the trend information includes: ith node viInjection power P ofiReference capacity S of distribution network systemb。
Calculating the average shortest distance L of the power distribution network according to the following formula,
in the formula:
n represents the number of nodes of the power distribution network;
g represents a power distribution network node set;
dijrepresents the ith node viAnd j node viLength of shortest path between;
the ith node v is calculated by the following formulaiNode degree function Ii，
In the formula:
liindicating the deletion of the ith node v of the distribution networkiThen, the ith node v of the power distribution networkiThe number of the connected node pairs is maintained in a centralized manner by the neighbor nodes;
kirepresenting the ith node v of the distribution networkiDegree of (c).
The ith node v is calculated by the following formulaiInjection power ratio of NPi，
In the formula:
Pirepresents the ith node viThe injection power of (3);
Sband representing the reference capacity of the power distribution network system.
And 2, calculating the comprehensive vulnerability of each node of the power distribution network according to the physical information and the load flow information.
The ith node v is calculated by the following formulaiComprehensive vulnerability index N ofi，
Ni＝(a1ki+a2Ii+a3NPi) (4)，
In the formula:
kirepresenting the ith node v of the distribution networkiDegree of (a)1Represents its weight;
Iirepresents the ith node viNode degree function of a2Represents its weight;
NPirepresents the ith node viInjection power ratio of a3Representing its weight.
It is noted that those skilled in the art can configure the ith node v of the power distribution network at williDegree k ofiWeight of a1I-th node viWeight a of the node degree function of2I-th node viWeight a of the injected power ratio of3. Such as, but not limited to, historical experience, averaging, neural networks, etc., or a combination thereof. As a preferred mode, the method can determine the ith node v of the power distribution network according to a fuzzy analytic hierarchy processiDegree k ofiWeight of a1I-th node viWeight a of the node degree function of2I-th node viWeight a of the injected power ratio of3。
And step 3, acquiring the operation indexes of the power distribution network.
The operation indexes of the power distribution network in the step 3 comprise: p benefit-type indicators with ideal values of 1 and q cost-type indicators with ideal values of 0, wherein p and q are positive integers.
The benefit type indexes include: the method comprises the following steps of (1) line interconnection rate, line section standardization rate, line standardization structure proportion, line N-1 passage rate, line insulation rate and distribution automation coverage rate; i.e. p is 6.
Cost-type indicators include: the line segment number is unreasonable in proportion, the line length is transfinite in proportion, the heavy-load line proportion, the heavy-load distribution ratio and the high-loss distribution ratio, namely q is 5.
It is noted that one skilled in the art may choose more or fewer, or other types of distribution network operation indicators, depending on engineering practices. The above are only non-limiting preferred examples.
And 4, calculating the reconstruction weight of each power distribution network operation index according to the power distribution network operation index. It is noted that those skilled in the art can configure the modification weight of the operation index of the power distribution network at will. Such as, but not limited to, historical experience, averaging, neural networks, etc., or a combination thereof. As a preferable mode, step 4 specifically includes:
step 4.1, calculating the index improvement degree of the power distribution network according to the following formula,
in the formula:
Mbenefitindicating the improvement degree of the benefit type index;
Mbenefitindicating the degree of improvement of the cost-type index;
Nrerepresenting the modified index value;
Norepresenting a current index value;
constructing a power distribution network operation index improvement degree set M according to the sequence of p benefit indexes and q cost indexesz＝(M1,…,Mp,Mp+1,…,Mp+q)
Step 4.2, constructing a judgment matrix of (p + q) × (p + q) according to the calculation result in the step 3.1, and calculating an element beta in the judgment matrix according to the following formulaxy，
x represents a row of the decision matrix, and x is 1,2, … (p + q);
y denotes a column of the determination matrix, and y is 1,2, … (p + q);
step 4.3, the power distribution network operation index weight is obtained by using the following formula,
w1,w2,…,w11representing the weights of p benefit-type indicators and q cost-type indicators, respectively.
In a further preferred embodiment of the present invention, p modification weights of the benefit index with the ideal value of 1 and q modification weights of the cost index with the ideal value of 0 are determined by an analytic hierarchy process in step 4.
And 5, sorting the comprehensive vulnerability of each node and the transformation weight of the operation indexes of the power distribution network, and sorting the nodes transformed by the power distribution network and the operation index weights of the power distribution network as the transformation sequence of the power distribution network.
Calculation example:
take a distribution network in a certain area as an example. The following table shows the partial lines of the distribution network in the area and the weight of the partial lines, and the weight is determined by the length of the lines.
TABLE 1 line and line length
From Table 1, the line lengths and the injection powers of the line nodes, the comprehensive vulnerability of the nodes can be obtained, as shown in Table 2
TABLE 2 node composite vulnerability
| Node name | Comprehensive vulnerability |
| S457569 | 0.420189274 |
| K457571_457577 | 0.143225806 |
| K457579_457585 | 0.363735664 |
| L457571_457577 | 0.170725455 |
| L457579_457585 | 0.149528514 |
| S457568 | 0.147573676 |
And 11 power grid operation indexes of line connection rate, line section standardization rate, line connection mode standardization rate, line section number improvement rate, overrun line length improvement rate, line N-1 passage rate, line heavy load rate, distribution transformer heavy load rate, high loss distribution transformer occupation rate, line insulation aging rate and distribution transformer automation rate are selected to calculate the transformation weight.
TABLE 3 initial data and improvement degree of distribution network operation index
And substituting the initial data of the operation indexes of the power distribution network in the table 3 into the formulas (5) and (6) to reach the data of the last 1 column. Substituting the data of the last 1 column into the formula (7) to construct a judgment matrix. As shown below
And substituting the structural matrix into a formula (8) to obtain the transformation weights of the line interconnection rate, the line section standardization rate, the line connection mode standardization rate, the line section number improvement rate, the overrun line length improvement rate, the line N-1 passage rate, the line overloading rate, the distribution transformer overloading rate, the high-loss distribution transformer occupation rate, the line insulation aging rate and the distribution transformer automation rate. Table 4 shows the initial data of the operation index and the improvement degree of the distribution network.
TABLE 4 initial data and improvement degree of distribution network operation index
The priority of each index transformation requirement can be seen from the calculation result. And combining the calculated importance of the nodes, selecting the nodes with high importance, and preferentially transforming the power grid operation indexes with higher weight, so that the power supply reliability of the power distribution network can be effectively improved.
The method has the advantages that compared with the prior art, the method for optimizing the reliability of the power distribution network with multi-service integration is provided, the method aims at helping a power grid company to carry out power distribution network node reliability optimization, selects a proper data type, carries out transformation priority calculation and helps cost fund accounting, so that the power grid company is helped to control cost, and power supply reliability and economic benefit are improved.
The present applicant has described and illustrated embodiments of the present invention in detail with reference to the accompanying drawings, but it should be understood by those skilled in the art that the above embodiments are merely preferred embodiments of the present invention, and the detailed description is only for the purpose of helping the reader to better understand the spirit of the present invention, and not for limiting the scope of the present invention, and on the contrary, any improvement or modification made based on the spirit of the present invention should fall within the scope of the present invention.
Claims (10)
1. A method for optimizing the reliability of a multi-service converged power distribution network is characterized by comprising the following steps:
step 1, acquiring physical information and load flow information of a power distribution network;
step 2, calculating the comprehensive vulnerability of each node of the power distribution network according to the physical information and the load flow information;
step 3, acquiring the operation index of the power distribution network;
step 4, calculating the reconstruction weight of each power distribution network operation index according to the power distribution network operation index;
and 5, sorting the comprehensive vulnerability of each node and the transformation weight of the operation indexes of the power distribution network, and sorting the nodes transformed by the power distribution network and the operation index weights of the power distribution network as the transformation sequence of the power distribution network.
2. The method for optimizing the reliability of the multi-service converged power distribution network according to claim 1, wherein in the step 1, the physical information of the power distribution network comprises: number n of nodes of power distribution network and ith node v of power distribution networkiDegree k ofi，viThe ith node viAnd j node viLength d of shortest path betweenij，
Wherein, i is 1,2,. and n; j is 1,2, n,
ith node v of power distribution networkiDegree k ofiRefers to power distributionIn a network with viThe number of directly connected edges;
vithe neighbor node set of (c) is defined byiA set of nodes connected directly by edges;
the trend information includes: ith node viInjection power P ofiReference capacity S of distribution network systemb。
3. The method for optimizing the reliability of the multi-service converged power distribution network according to claim 2, wherein the step 1 further comprises:
calculating the average shortest distance L of the power distribution network according to the following formula,
in the formula: n represents the number of nodes of the power distribution network; g represents a power distribution network node set; dijRepresents the ith node viAnd j node viLength of shortest path between;
the ith node v is calculated by the following formulaiNode degree function Ii，
In the formula: liIndicating the deletion of the ith node v of the distribution networkiThen, the ith node v of the power distribution networkiThe number of the connected node pairs is maintained in a centralized manner by the neighbor nodes; k is a radical ofiRepresenting the ith node v of the distribution networkiDegree of (c).
4. The method for optimizing the reliability of the multi-service converged power distribution network according to claim 3, wherein the step 1 further comprises:
the ith node v is calculated by the following formulaiInjection power ratio of NPi，
In the formula: piRepresents the ith node viThe injection power of (3); sbAnd representing the reference capacity of the power distribution network system.
5. The method for optimizing the reliability of the multi-service converged power distribution network according to claim 4, wherein the step 2 comprises:
the ith node v is calculated by the following formulaiComprehensive vulnerability index N ofi，
Ni＝(a1ki+a2Ii+a3NPi) (4)，
In the formula: k is a radical ofiRepresenting the ith node v of the distribution networkiDegree of (a)1Represents its weight; i isiRepresents the ith node viNode degree function of a2Represents its weight; n is a radical ofPiRepresents the ith node viInjection power ratio of a3Representing its weight.
6. The method for optimizing the reliability of the multi-service converged power distribution network according to claim 5, wherein in the step 2, the ith node v of the power distribution network is determined according to a fuzzy analytic hierarchy processiDegree k ofiWeight of a1I-th node viWeight a of the node degree function of2I-th node viWeight a of the injected power ratio of3。
7. The method for optimizing the reliability of the multi-service converged power distribution network according to any one of claims 1 to 6, wherein the operation indexes of the power distribution network in the step 3 comprise: p benefit-type indicators with ideal values of 1 and q cost-type indicators with ideal values of 0, wherein p and q are positive integers.
8. The method for optimizing reliability of a multi-service converged power distribution network according to claim 7, wherein the step 4 specifically comprises:
step 4.1, calculating the index improvement degree of the power distribution network according to the following formula,
in the formula: mbenefitIndicating the improvement degree of the benefit type index; mbenefitIndicating the degree of improvement of the cost-type index; n is a radical ofreRepresenting the modified index value; n is a radical ofoRepresenting a current index value; constructing a power distribution network operation index improvement degree set according to the sequence of p benefit indexes and q cost indexes
Mz＝(M1，...，Mp，Mp+1，...，Mp+q)；
Step 4.2, constructing a judgment matrix of (p + q) × (p + q) according to the calculation result in the step 3.1, and calculating an element beta in the judgment matrix according to the following formulaxy，
x denotes a row of the determination matrix, x is 1, 2. (p + q), y denotes a column of the determination matrix, and y is 1, 2. (p + q);
step 4.3, calculating the weight of the operation index of the power distribution network by using the following formula,
w1，w2，…，w11representing the weights of p benefit-type indicators and q cost-type indicators, respectively.
9. The method of claim 7, wherein the benefit indicators comprise: the method comprises the following steps of (1) line interconnection rate, line section standardization rate, line standardization structure proportion, line N-1 passage rate, line insulation rate and distribution automation coverage rate;
cost-type indicators include: unreasonable proportion of line segment number, line length overrun proportion, heavy-load line proportion, heavy-load distribution ratio and high-loss distribution ratio.
10. The method for optimizing the reliability of the multi-service converged power distribution network according to claim 7, wherein in step 4, p benefit type indicators with ideal values of 1 and q cost type indicators with ideal values of 0 are determined by an analytic hierarchy process.
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| CN112686772A (en) * | 2020-12-11 | 2021-04-20 | 国网湖北省电力有限公司电力科学研究院 | Method for determining flexible and straight transformation time sequence of multi-feed receiving-end power grid |
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