CN105552899A - Method for calculating recovery capability of power grid after blackout - Google Patents

Abstract

The invention discloses a method for calculating the resilience of a power grid after a blackout, which includes: 1) identifying the specific state of the system after the blackout, and obtaining the data used for calculation; 2) screening out the available black-start units in the system, and calculating all 3) Calculate the average shortest distance from each unit to be restored to the black start unit in the system and the average shortest distance from the load node to each unit node in the system, and calculate the average distance between the two ; 4) The quotient of the per unit value of the capacity sum of the black start unit and the average distance in step 3) is taken as the resilience of the power grid after a blackout. Beneficial effects of the present invention: It provides a quantitative means for evaluating and analyzing the resilience of the power grid after a blackout, and can conveniently find weak points in improving the resilience of the power grid, and propose corresponding improvement measures.

Description

A Method of Calculating the Resilience of Power Network After a Major Blackout

technical field

The invention relates to a calculation method of a power grid index, in particular to a calculation method for calculating the recovery force of a power grid after a major blackout.

Background technique

With the rapid development of the economy and society, the scale of the power system is getting larger and larger, and with the construction of UHV AC and DC grids and the connection of large-scale renewable energy bases such as large-scale wind farms and photovoltaic power stations to the grid, the dynamic behavior of the power system It has become increasingly complex, and environmental issues and economic factors must be considered during the operation of the power grid, making the operating point of the power grid closer to its safety limit point, which greatly increases the complexity of power grid operation and maintenance. Therefore, if the local failure of the system is not handled properly, it is very likely to cause a large-scale power outage in the system. For example, on August 14, 2003, the most serious power outage in North American history occurred. The power outage affected many areas in the United States and Canada, with a loss of load of 61.8GW and a population of 50 million. Improper handling of the short-circuit fault of the 345kV transmission line caused a large-scale transfer of the power flow, resulting in chain tripping of multiple transmission lines due to overload, and finally led to a major blackout. France, Italy and other countries lost a total of about 16 million kW of load, and 15 million users were affected; on November 10, 2009, a major blackout occurred in the power grids of Brazil and Paraguay, resulting in tripping of three 750kV lines and blocking of two ±600kV DC lines. The power grid lost about 17 million kW of power, and the power outage spread to 12 states in Brazil and most parts of neighboring Paraguay, affecting 50 to 60 million people; on July 30 and 31, 2012, two consecutive incidents occurred in northern and eastern India. The second large-scale power outage covered more than half of the country and directly affected the lives of more than 600 million people. The operation experience of power systems at home and abroad shows that although a large number of applications of new technologies and new equipment in power systems can improve the stability and reliability of system operation, it still cannot avoid the occurrence of major blackouts.

Modern society is increasingly dependent on reliable power supply. Once a large-scale power outage occurs, it will have a huge impact on social production and life and huge economic losses. The data analysis of many blackout accidents at home and abroad shows that the loss caused by the blackout accident has an exponential relationship with the blackout time. The longer the system is out of power, the more serious the adverse effects will be. After a power outage, under the guidance of the corresponding recovery plan, carry out the corresponding recovery operation as soon as possible, which is conducive to speeding up the recovery process of the system, shortening the power outage time of the system, thereby reducing the impact and loss caused by the system power outage. The duration of the system recovery process is not only related to factors such as the completeness of the recovery plan and the proficiency of dispatchers, but also to the rapid recovery ability of the power grid itself after external disturbances, that is, the resilience of the power grid. Power grid resilience mainly considers the ability of the system to quickly recover by using various resources in the event of extreme accidents such as large-scale power outages, which has not been involved in traditional power system planning. Resilience is an important feature of smart grid, and research on grid resilience is an inevitable trend in the development of smart grid. Power grid resilience is related to various factors such as the grid structure of the system, power supply, and load distribution. Taking the improvement of power grid resilience as the goal can guide the development planning of the power grid, and can also analyze the existing power grid and propose corresponding improvement measures.

At this stage, the research on power grid resilience has just started, and its evaluation theory and method research still needs further systematic results. The analysis of relevant factors is still in the qualitative analysis stage, and there is a lack of quantitative analysis tools.

Contents of the invention

The object of the present invention is to provide a method for calculating the restoration force of the power grid after a blackout in order to solve the above problems. Considering the factors such as the capacity and distribution of the available black-start units and units to be restored in the power grid, the grid structure and the distribution of load stations after a major blackout, a quantitative calculation method for the resilience of the power grid is proposed to guide the power grid Provide a basis for planning and improving grid resilience.

To achieve the above object, the specific scheme of the present invention is as follows:

A method for calculating the power grid resilience after a blackout, comprising the following steps:

(1) Conduct availability diagnosis on all power transmission and transformation equipment in the system, obtain the number of black-start units and units to be restored in the system and their corresponding unit capacities, the connection relationship of available transmission lines in the system and their corresponding line parameters ;

(2) Establish a weighted network connection matrix corresponding to the system according to the acquired data;

(3) Screen out the available black start units in the system, and calculate the sum of the capacities of all available black start units and the corresponding unit value;

(4) Calculate the average shortest distance from each unit to be restored in the system to the black start unit and the average shortest distance from the load node to each unit node, and calculate the average distance of the above two average shortest distances;

(5) According to the per-unit value of the sum of the capacities of all available black start units calculated in step (3) and the average distance calculated in step (4), the resilience of the power grid after a blackout is calculated, which is Development planning provides a reference basis.

In said step (1), the method for carrying out availability diagnosis to all power transmission and transformation equipment in the system is:

Identify and judge the operating status of all power generation, transmission and transformation equipment in the system, and screen out the equipment that is in the fault state or maintenance state, that is, the equipment that is unavailable during the recovery process.

In the step (2), when establishing the corresponding weighted network connection matrix M of the system, M is a square matrix, and the number of rows and columns are equal to the number of available power plants and substation nodes in the system;

When there is an available transmission line l _ij between node i and node j in the system, let the per unit value of the line reactance of line l _ij be x _ij , its corresponding element in the connection matrix M is M _ij , and M _ij =M _ji =x _ij ; otherwise, if there is no available transmission line between node i and node j in the system, M _ij =M _ji =∞.

In the step (3), the average shortest distance from each unit to be restored to the black start unit in the system is determined according to the minimum value of the shortest distance from each unit to be restored to each black start unit.

Further, when calculating the shortest distance Dis _ij from the unit i to be restored to the black-start unit j, the node where the black-start unit j is located is taken as the source point s, the node where the unit i is to be recovered is taken as the target node t, and the weighted network connection matrix M The nodes in are divided into two types, which are respectively recorded as set S and set U: set S is the set of target nodes that have already calculated the shortest path to the source point s, and set U is the set of target nodes that have not yet calculated the shortest path to the source point s A collection of target nodes.

Further, using the shortest path method to calculate the shortest distance Dis _ij from the unit i to be restored to the black start unit j, the specific method is as follows:

1) During the initial calculation, the set S only contains the source point s, and the set U contains all nodes except the source point s. For any point x in the set U, D[x] is the distance from the source point s to the point x , which is the value M _sx of the corresponding element in the connection matrix M of the line between the source point s and the node x;

2) Select the point x with the smallest D[x] from the set U, and then move the point x from the set U to the set S;

3) For any node y in the remaining nodes of the set U, if D[y]>D[x]+M _xy exists, then set the distance D[y] from the source point s to the point y as D[x]+ M _xy , where M _xy is the value of the corresponding element in the connection matrix M of the line between node x and node y;

4) Select the point y with the smallest D[y] from the remaining nodes, and then move the point y from the set U to the set S;

5) Repeat step 3) and step 4), until all nodes in the set U are moved to the set S;

6) The shortest distance from the source point s to the target node t is D[t].

In the step (4), the average shortest distance from the load node to each unit node is determined according to the minimum value of the shortest distances from the unit i to be restored to all unit nodes.

Further, when calculating the average shortest distance from the load node to each unit node, the load nodes are divided into two categories: one is included in the recovery path corresponding to the minimum value of the shortest distance from each unit to be restored to each black start unit load nodes; the other type is load nodes not included in the above path;

The first type of load nodes have been included in the recovery path, so they are not considered, only the second type of load nodes are considered, and the nodes included in the recovery path corresponding to the minimum value of the shortest distance from each unit to be restored to each black start unit for clustering.

Further, the shortest path method is used to calculate the shortest distance from unit i to be restored to all unit nodes.

In the step (5), the resilience of the power grid after the blackout is: the quotient of the per unit value of the sum of the capacities of all available black start units and the average distance calculated in the step (4).

Beneficial effects of the present invention:

First, the method for calculating the power grid resilience after a blackout proposed by the present invention can easily calculate the resilience of different power grids after a blackout accident, and compare them with each other.

Second, the method for calculating the resilience of the power grid after a blackout proposed by the present invention provides a quantitative means for evaluating and analyzing the resilience of the power grid after a blackout, and can facilitate the search for the improvement of the resilience of the power grid. Weakness points and corresponding improvement measures are put forward.

Third, the quantitative calculation method for calculating the resilience of the power grid after a blackout proposed by the present invention makes it more intuitive and effective to guide the planning of the power grid with the goal of maximizing the resilience of the power grid.

Fourth, the present invention comprehensively considers factors such as the capacity and location of the black-start unit in the power grid when calculating the resilience of the power grid after a major blackout, so that the calculation result of the grid resilience is more objective, and can be used to guide the layout optimization and optimization of the black-start unit. Capacity optimization.

Fifth, the present invention considers the positional relationship between the unit to be restored and the black-start unit, which can effectively reflect the start-up process of the unit to be restored during the black-start process, so that the power grid resilience can effectively reflect the actual recovery ability of the power grid after a fault occurs.

Sixth, the present invention classifies the load nodes when calculating the resilience of the power grid after a major power outage, which is more in line with the actual recovery process after a power outage in the power grid.

Description of drawings

Fig. 1 is the flow chart of the method for calculating power grid resilience after a large blackout in the present invention;

FIG. 2 is a structural diagram of an IEEE30 node system according to an embodiment of the present invention.

detailed description

The present invention is described in detail below in conjunction with accompanying drawing:

A method for calculating the resilience of the power grid after a blackout, as shown in Figure 1, includes the following steps:

(1) Conduct availability diagnosis on all power transmission and transformation equipment in the system, obtain the number of black-start units and units to be restored in the system and their corresponding unit capacities, the connection relationship of available transmission lines in the system and their corresponding line parameters ;

(2) Establish a weighted network connection matrix corresponding to the system according to the acquired data;

When establishing the weighted network connection matrix M corresponding to the system, M is a square matrix, and the number of rows and columns is equal to the number of sites available in the system. When there is an available connection line l _ij between node i and node j in the system, and the per unit value of the line reactance of line l _ij is x _ij , then the element M _ij in the connection matrix M = M _ji = x _ij ; Conversely, if there is no available connection line between node i and node j in the system, M _ij =M _ji =∞. For a system containing n sites, the corresponding connection matrix M is as follows.

$\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; =</span>\left[\begin{array}{ccccccc}{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 11</span>}}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 12</span>}}& \mathrm{<span\; class="notranslate">\; ...</span>}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; j</span>}}& \mathrm{<span\; class="notranslate">\; ...</span>}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; no</span>}}\\ {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; twenty\; one</span>}}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; twenty\; two</span>}}& \mathrm{<span\; class="notranslate">\; ...</span>}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; i</span>}}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; j</span>}}& \mathrm{<span\; class="notranslate">\; ...</span>}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; no</span>}}\\ <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& & <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& & <span\; class="notranslate">\; .</span>\\ <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& & <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& & <span\; class="notranslate">\; .</span>\\ <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& \mathrm{<span\; class="notranslate">\; ...</span>}& <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& \mathrm{<span\; class="notranslate">\; ...</span>}& <span\; class="notranslate">\; .</span>\\ {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 1</span>}}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}& \mathrm{<span\; class="notranslate">\; ...</span>}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; i</span>}}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}& \mathrm{<span\; class="notranslate">\; ...</span>}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; no</span>}}\\ {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}\mathrm{<span\; class="notranslate">\; 1</span>}}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}& \mathrm{<span\; class="notranslate">\; ...</span>}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}\mathrm{<span\; class="notranslate">\; i</span>}}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}\mathrm{<span\; class="notranslate">\; j</span>}}& \mathrm{<span\; class="notranslate">\; ...</span>}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}\mathrm{<span\; class="notranslate">\; no</span>}}\\ <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& & <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& & <span\; class="notranslate">\; .</span>\\ <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& & <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& & <span\; class="notranslate">\; .</span>\\ <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& \mathrm{<span\; class="notranslate">\; ...</span>}& <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& \mathrm{<span\; class="notranslate">\; ...</span>}& <span\; class="notranslate">\; .</span>\\ {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; 1</span>}}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}& \mathrm{<span\; class="notranslate">\; ...</span>}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; i</span>}}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; j</span>}}& \mathrm{<span\; class="notranslate">\; ...</span>}& {\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; no</span>}}\end{array}\right]$

In the formula, for any elements M _ij and M _ji , there exists M _ij =M _ji .

(3) Screen out the available black start units in the system, and calculate the sum of the capacities of all available black start units and the corresponding unit value;

The recovery process after a large-scale power outage in the system includes the black start stage, network structure reconstruction and load recovery stage. During the black start phase, the black start group available in the system will be started first. After the black start unit is successfully started, it will provide the required start-up power for the remaining units that do not have self-start capability, so that they can be restarted and connected to the grid. In the stage of network structure reconstruction, it is necessary to gradually restore the important transmission lines and important load sites in the system, establish a strong network frame, and lay the foundation for subsequent load recovery. Large-scale load recovery, restore the power supply to the lost load as soon as possible, and shorten the power outage time of the system. The successful start of the black start unit is the beginning of the whole recovery process. The capacity of the black start unit represents the ability of the system to recover quickly after a large-scale power outage, and can be used as an important indicator to reflect the resilience of the power grid. After filtering out all available black start units in the system, the calculation formula for the sum of the capacities of all black start units P _black is as follows

${\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}$

In the formula, n is the number of black start units available in the system; P _i is the capacity of the i-th black start unit. The formula for calculating the per unit value of P _black is as follows

${\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; k</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; k</span>}}}{{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; B</span>}}}$

In the formula, S _B is the power base value selected in step S1.

(4) Calculate the average shortest distance from each unit to be restored in the system to the black start unit and the average shortest distance from the load node to each unit node, and calculate the average distance of the above two average shortest distances;

The average shortest distance from each unit to be restored to the black start unit Calculated as follows:

$\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; S</span>}}}<span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; S</span>}\mathrm{<span\; class="notranslate">\; i</span>}}}{\mathrm{<span\; class="notranslate">\; m</span>}}$

L _Si =min(Dis _ij ),j=1,2,...,n

In the formula, m is the number of units to be restored, n is the number of black-start units, Dis _ij is the shortest distance from unit i to be restored to black-start unit j, L _Si is the minimum distance of the shortest distance from unit i to be restored to each black-start unit value.

When calculating the shortest distance Dis _ij from the unit i to be restored to the black-start unit j, the node where the black-start unit j is located is taken as the source point s, and the node where the unit i is to be recovered is taken as the target node t, and the shortest path algorithm is used for calculation. For the weighted network connection matrix M, the shortest path algorithm divides the nodes in M into two types, which are recorded as set S and set U respectively. The set S is the set of points whose shortest path to the source point s has been calculated, and the set U is the set of points whose shortest path to the source point s has not been calculated yet. The calculation steps of the shortest path algorithm are:

1. During the initial calculation, the set S only contains the source point s, and the set U contains all nodes except the source point s. For any point x in the set U, D[x] is the distance from the source point s to the point x , which is the value M _sx of the corresponding element in the connection matrix M of the line between the source point s and the node x;

2. Select the point x with the smallest D[x] from the set U, and then move the point x from the set U to the set S;

3. For any node y in the remaining nodes of the set U, if D[y]>D[x]+M _xy exists, then set the distance D[y] from the source point s to the point y as D[x]+ M _xy ;

4. Repeat step 2 and step 3 until all nodes in set U are moved to set S;

5. The shortest distance from the source point s to the target node t is D[t].

When calculating the shortest distance from the load node to all unit nodes, the load nodes are divided into two categories: one is the load node included in the recovery path corresponding to the minimum value of the shortest distance from each unit to be restored to each black start unit ; the other type is the load nodes not included in the above paths. The first type of load node is already included in the recovery path, so it is not considered. Here, only the second type of load node is considered, and the recovery path corresponding to the minimum value of the shortest distance from each unit to be restored to each black start unit is included. nodes are clustered. The average shortest distance from the load node to each unit node The calculation formula is

$\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; d</span>}}}<span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; d</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; i</span>}}}{\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; d</span>}}$

L _ldi =min(Dis _ij ),j=1,2,...,nut

In the formula, nld is the number of load nodes of the second type; nut is the number of all unit nodes; Dis _ij is the shortest distance from load node i to unit node j; L _ldi is the shortest distance from unit i to be restored to all unit nodes min. When calculating Dis _ij , the shortest path algorithm is also used.

and average of for

$\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; =</span>\frac{\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; S</span>}}}<span\; class="notranslate">\; +</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; d</span>}}}}{\mathrm{<span\; class="notranslate">\; 2</span>}}$

(5) According to the per-unit value of the sum of the capacities of all available black-start units calculated in step (3) and the average distance calculated in step (4), the resilience of the power grid after a blackout is calculated, which is Development planning provides a reference basis.

The calculation method of the restoration force R _es of the power grid after a blackout is

${\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; k</span>}}^{<span\; class="notranslate">\; *</span>}}{\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; L</span>}}}$

in, is the per unit value of the sum of the capacities of all available black start units, for and average of.

As an implementation mode, the present invention performs simulation calculations for the IEEE30 node system, and illustrates the method flow for calculating the recovery force of the power grid after a blackout accident. The IEEE30 node system structure diagram is shown in Figure 2. According to the method of calculating the resilience of the power grid after a blackout, the specific steps for calculating the resilience of the power grid after a blackout in the IEEE30 node system are as follows:

S1: Identify the specific state of the system, obtain the data used for calculation, and establish a weighted network connection matrix corresponding to the system.

Identifying the state of the system refers to the availability diagnosis of all power transmission and transformation equipment in the system, that is, identifying and judging the state of the equipment, and screening out the equipment in the fault state or maintenance state (unavailable during the recovery process) equipment); the data required for the calculation include: the number and capacity of the black-start unit and the unit to be restored in the system, the connection relationship of the available transmission lines in the system and the corresponding line parameters.

When calculating the per unit value x _ij of the line reactance of the line l _ij , the reference value S _B is taken as 100MVA, and U _B is taken as the standard voltage of each voltage level.

In the IEEE30 node system, the unit on node 1 is a black start unit with a capacity of 50MW. The units on nodes 2, 13, 22, 23 and 27 are the units to be restored, and the capacity of the units is 60MW, 25MW, 45MW, 50MW and 55MW respectively. The voltage level of the IEEE30 node system is 220kV.

In this step, the availability of various equipment in the power grid is diagnosed after a power outage in the IEEE30 node system, and the conclusion is as follows: all types of equipment in the IEEE30 node system are available during the recovery process. And obtain the number and unit capacity of the black start unit and the unit to be restored in the system, the connection relationship of the transmission line in the system and the corresponding line parameters, and calculate the per unit value of the reactance of each line. According to the system topology of IEEE30 nodes and the per unit value of the calculated reactance of each line, the connection matrix M corresponding to the IEEE30 node system is established.

S2: Select the black start units available in the system, and calculate the sum of the capacities of all black start units and the corresponding unit value;

During the black start phase, the black start group available in the system will be started first. After the black start unit is successfully started, it will provide the required starting power for the remaining units that do not have self-starting capability, so that they can be restarted and connected to the grid. The capacity of the black start unit represents the ability of the system to quickly recover after a large-scale power outage, and can be used as an important indicator to reflect the resilience of the power grid.

In this step, only the units on node 1 in the IEEE30 node system are black-start units, and it is easy to calculate the sum of the capacities of the black-start units in the system P _black to be 50MW, and the corresponding unit value is

${\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; k</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; k</span>}}}{{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; B</span>}}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 50</span>}}{\mathrm{<span\; class="notranslate">\; 100</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0.5</span>}$

S3: Calculate the average shortest distance from each unit to be restored in the system to the black start unit and the average shortest distance from the load node to each unit node, and calculate the average distance between the two.

According to the connection matrix M corresponding to the IEEE30 node system, first calculate the shortest distance from nodes 2, 13, 22, 23, and 27 where the unit to be restored is located to node 1 where the black-start unit is located. The calculation steps of the shortest path algorithm are:

1. In the initial calculation, the set S only contains node 1, and the set U contains all nodes except node 1. For any point x in the set U, D[x] is the distance from node 1 to point x;

2. The point x with the smallest D[x] in the set U is the node 2, and move the node 2 from the set U to the set S;

3. For any node y in the remaining nodes of the set U, if D[y]>D[x]+M _xy exists, then set the distance D[y] from node 1 to point y as D[x]+M _xy ;

4. Repeat steps 2 and 3 until all nodes in the set U are moved to the set S;

5. The shortest distances from nodes 2, 13, 22, 23 and 27 to node 1 where the black start unit is located are D[2], D[13], D[22], D[23] and D[27].

The average shortest distance from the units to be restored on nodes 2, 13, 22, 23 and 27 to the black start units Calculated as follows:

$\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; S</span>}}}<span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; 5</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; S</span>}\mathrm{<span\; class="notranslate">\; i</span>}}}{\mathrm{<span\; class="notranslate">\; 5</span>}}$

L _Si =Dis[i]

The shortest distance path from the unit to be restored on node 2 to the black start unit on node 1 is: 1-2, and the shortest distance is 0.0575.

The shortest distance paths from the unit to be restored on node 13 to the black start unit on node 1 are: 1-3, 3-4, 4-12, 12-13, and the shortest distance is 0.6191.

The shortest distance path from the unit to be restored on node 22 to the black start unit on node 1 is: 1-2, 2-6, 6-9, 9-10, 10-21, 21-22, and the shortest distance is 0.6503 .

The shortest distance paths from the unit to be restored on node 23 to the black start unit on node 1 are: 1-3, 3-4, 4-12, 12-15, 15-23, and the shortest distance is 0.8115.

The shortest distance paths from the unit to be restored on node 27 to the black start unit on node 1 are: 1-2, 2-6, 6-28, 28-27, and the shortest distance is 0.6897.

The average shortest distance from the units to be restored on nodes 2, 13, 22, 23 and 27 to the black start units is 0.5656.

The load nodes can be divided into two categories: the first category is the nodes included in the shortest path from nodes 2, 13, 22, 23 and 27 to node 1, and the nodes included are: 3, 4, 6, 9, 10, 15 , 21, 28.

The second category is the remaining load nodes, including nodes 5, 7, 8, 11, 14, 16, 17, 18, 19, 20, 24, 25, 26, 29, and 30. When calculating the shortest distance from the second type of node to each unit, the lines 1-2, 1-3, 3-4, 4-12, 12-13, 2-6, 6-9, 9-10, 10- 21, 21-22, 12-15, 15-23, 2-6, 6-28, 28-27 and the nodes connected by the lines are clustered into a point 1, the shortest distance from the second type of nodes to each unit node, That is, the shortest distance to point 1 after clustering. Using the shortest path algorithm to calculate the shortest distance from the second type of stage to each unit node is shown in Table 1.

Table 1 The shortest distance from the second type of node to each unit node

node number shortest distance node number shortest distance 5 0.1980 19 0.2770 7 0.0820 20 0.2090 8 0.0420 twenty four 0.1790 11 0.2080 25 0.2087 14 0.1997 26 0.5887 16 0.1987 29 0.4153 17 0.0845 30 0.6027 18 0.2185

The average shortest distance from the load node to each unit node is 0.2475. so and average of for

$\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; =</span>\frac{\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; S</span>}}}<span\; class="notranslate">\; +</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; d</span>}}}}{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0.4065</span>}$

S4: The quotient of the per unit value of the sum of the capacities of the black start units and the average distance in S3 is used as a method for quantitatively calculating the power grid resilience after a blackout.

The calculation method of the restoration force R _es of the power grid after a blackout is

${\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; b</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; k</span>}}^{<span\; class="notranslate">\; *</span>}}{\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; L</span>}}}$

${\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 0.5</span>}}{\mathrm{<span\; class="notranslate">\; 0.4065</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1.23</span>}$

The power grid resilience of the IEEE30 node system after a blackout is 1.23.

Although the specific implementation of the present invention has been described above in conjunction with the accompanying drawings, it does not limit the protection scope of the present invention. Those skilled in the art should understand that on the basis of the technical solution of the present invention, those skilled in the art do not need to pay creative work Various modifications or variations that can be made are still within the protection scope of the present invention.

Claims (10)

1. A method for calculating power grid resilience after a blackout is characterized in that it may further comprise the steps: (1) Conduct availability diagnosis on all power transmission and transformation equipment in the system, obtain the number of black-start units and units to be restored in the system and their corresponding unit capacities, the connection relationship of available transmission lines in the system and their corresponding line parameters ; (2) Establish a weighted network connection matrix corresponding to the system according to the acquired data; (3) Screen out the available black start units in the system, and calculate the sum of the capacities of all available black start units and the corresponding unit value; (4) Calculate the average shortest distance from each unit to be restored in the system to the black start unit and the average shortest distance from the load node to each unit node, and calculate the average distance of the above two average shortest distances; (5) According to the per-unit value of the sum of the capacities of all available black start units calculated in step (3) and the average distance calculated in step (4), the resilience of the power grid after a blackout is calculated, which is Development planning provides a reference basis. 2. a kind of method for calculating power grid resilience after a large blackout as claimed in claim 1 is characterized in that, in the described step (1), the method for carrying out availability diagnosis to all power transmission and transformation equipment in the system is: Identify and judge the operating status of all power generation, transmission and transformation equipment in the system, and screen out the equipment that is in the fault state or maintenance state, that is, the equipment that is unavailable during the recovery process. 3. A kind of method for calculating power grid resilience after a large blackout as claimed in claim 1, is characterized in that, in described step (2), when establishing the corresponding weighted network connection matrix M of the system, M is a square matrix , and the number of rows and columns is equal to the number of power plant and substation nodes available in the system; When there is an available transmission line l _ij between node i and node j in the system, let the per unit value of the line reactance of line l _ij be x _ij , its corresponding element in the connection matrix M is M _ij , and M _ij =M _ji =x _ij ; otherwise, if there is no available transmission line between node i and node j in the system, M _ij =M _ji =∞. 4. A method for calculating the power grid resilience after a major blackout as claimed in claim 1, characterized in that, in the step (3), the average shortest distance from each unit to be restored to the black start unit in the system is based on each The minimum value of the shortest distance from the unit to be restored to each black start unit is determined. 5. A method for calculating the power grid resilience after a major blackout as claimed in claim 4, wherein when calculating the shortest distance Dis _ij from the unit i to be restored to the black start unit j, the node where the black start unit j is located As the source point s, the node where the unit i to be restored is located is used as the target node t, and the nodes in the weighted network connection matrix M are divided into two types, which are recorded as set S and set U respectively: set S is the The set of target nodes of the shortest path, the set U is the set of target nodes that have not yet calculated the shortest path to the source point s. 6. A kind of method for calculating power grid resilience after a large blackout as claimed in claim 5 is characterized in that, adopting the shortest path method to calculate the shortest distance Dis _ij from the unit i to be restored to the black start unit j, the specific method is as follows: 1) During the initial calculation, the set S only contains the source point s, and the set U contains all nodes except the source point s. For any point x in the set U, D[x] is the distance from the source point s to the point x , which is the value M _sx of the corresponding element in the connection matrix M of the line between the source point s and the node x; 2) Select the point x with the smallest D[x] from the set U, and then move the point x from the set U to the set S; 3) For any node y in the remaining nodes of the set U, if D[y]>D[x]+M _xy exists, then set the distance D[y] from the source point s to the point y as D[x]+ M _xy , where M _xy is the value of the corresponding element in the connection matrix M of the line between node x and node y; 4) Select the point y with the smallest D[y] from the remaining nodes, and then move the point y from the set U to the set S; 5) Repeat step 3) and step 4), until all nodes in the set U are moved to the set S; 6) The shortest distance from the source point s to the target node t is D[t]. 7. a kind of method for calculating power grid resilience after a large blackout as claimed in claim 1, is characterized in that, in described step (4), the average shortest distance from load node to each unit node is according to unit i to be restored to all The minimum value of the shortest distance to the unit node is determined. 8. A kind of method for calculating power grid resilience after a large blackout as claimed in claim 7, is characterized in that, when calculating the average shortest distance from load node to each unit node, load node is divided into two classes: one class is already The load nodes included in the restoration path corresponding to the minimum value of the shortest distance from each unit to be restored to each black start unit; the other type is the load node not included in the above path; The first type of load nodes have been included in the recovery path, so they are not considered, only the second type of load nodes are considered, and the nodes included in the recovery path corresponding to the minimum value of the shortest distance from each unit to be restored to each black start unit for clustering. 9. A method for calculating the power grid resilience after a blackout as claimed in claim 7, wherein the shortest path method is used to calculate the shortest distance from unit i to be restored to all unit nodes. 10. A method for calculating the resilience of the power grid after a major blackout as claimed in claim 1, wherein in the step (5), the resilience of the grid after a major blackout is: the capacity of all available black start units The quotient of the per unit value of the sum and the average distance calculated in step (4).