CN104281978A - Available transmission capacity calculation method based on probabilistic power flow - Google Patents

Abstract

The present invention relates to a calculation method of available transmission capacity based on probability flow. The present invention uses the probability ATC of the probability flow calculation system, which greatly reduces the calculation amount compared with the simulation method, thereby improving the calculation speed of the system probability ATC, and further improving AQTC. calculation speed; put forward the concept of transmission component ATC and its influence factor on system ATC, add transmission components to the power system in order of influence factors from large to small, and take the influence of more transmission components into the system probability ATC result Among them, the deviation from the actual probability ATC expectation of the system is gradually reduced, thereby meeting the calculation accuracy of the probability ATC required by the system, and at the same time satisfying the calculation accuracy of AQTC. Therefore, the present invention can be widely used in the fields of calculation of probabilistic available power transmission capacity and calculation of probabilistic available power transmission capacity.

Description

A Calculation Method of Available Transmission Capacity Based on Probabilistic Power Flow

technical field

The invention relates to a calculation method of available transmission power, in particular to a calculation method of available transmission capacity based on probability flow.

Background technique

As a clean renewable energy, wind power has been vigorously developed in today's increasingly severe energy crisis. However, with the continuous expansion of the grid-connected scale of wind power, wind curtailment by wind farms is gradually becoming a common phenomenon in grid operation. Due to the obvious complementary advantages of inter-regional resources in my country, through large-scale coordination, the inter-regional load staggering effect and the complementary effect between power structures can be fully utilized, so as to maximize the consumption of wind power and other renewable energy sources. Regional grid for long-distance transmission. Generally speaking, the production plan of a power generation company is given by the higher-level competent authority in the form of annual electricity consumption; while wind power power is highly uncertain in the short term, but has certain rules in the long run and can be predicted more accurately. Therefore, wind power trading is more suitable for signing contracts on a long-term scale. The number of wind power transactions is not only related to the amount of wind energy that can be provided and received by both parties to the transaction, but also depends on the transmission capacity of the power grid. Therefore, how to determine the amount of wind power available for transmission between the two parties to the transaction, that is, to determine the Available Quantity Transfer Capability (AQTC) between the two parties to the transaction, is one of the key issues to be resolved before the transaction.

The so-called available power transmission capacity (AQTC) refers to the power transmission capacity remaining and available for commercial use in the actual physical transmission network within a specified period of time. The concept of the existing available transmission capacity (Available Transfer Capability, ATC) refers to the remaining transmission capacity available for commercial use in the actual physical transmission network. Compared with the two, although both reflect the available transmission capacity of the grid, ATC reflects power, while AQTC refers to electricity.

There are many factors affecting AQTC, such as generation plan within the period, load forecast, unit combination, maintenance plan, etc., so its calculation method is relatively complicated and difficult to calculate accurately. There is no relatively mature calculation method for AQTC. By referring to the existing ATC algorithm, it can provide an idea for the calculation of AQTC: select a typical mode in a small cycle with little change in the operating mode, and use the probability of ATC to simulate the uncertainty of each time section in this cycle. Once the operation mode changes greatly, the typical mode is reselected, and the probabilistic ATC under the new typical mode is calculated. Finally, the probabilistic ATC and time scale in each typical mode are weighted and calculated to obtain the long-period available power transmission.

Typical selection methods have been well applied in actual projects. Based on experience, the staff have explored more mature and simple selection methods, such as the largest method in summer, the smallest method in summer, the largest method in winter, and the smallest method in winter. However, there are still some deficiencies in the calculation of probabilistic ATC. At present, the calculation methods for probabilistic available transmission capacity (probabilistic ATC) mainly include the following categories:

(1) Algorithm based on stochastic programming: In the process of calculating ATC, first use the SPR (two-stage Stochastic Programming with Recourse) method to make the discrete variables continuous, and then use the CCP (Chance Constrained Programming) method according to the calculation results of SPR Deal with continuous variables to obtain the ATC value in the sense of probability. Since this method uses the processing of discrete variables and continuous variables in the calculation process, the calculation speed is not very ideal.

(2) Enumeration method: The enumeration method proposed later is to combine the enumeration of the system state with the optimization algorithm to calculate ATC. When calculating ATC, if the serious faults of the system are less, the method is more effective, but for the actual power system, the exponential time characteristic of the enumeration method still limits its application, and it cannot really effectively deal with the middle of the large system. Long term ATC calculation.

(3) Algorithm based on Monte Carlo simulation: The Monte Carlo method is used to sample the system state. This method can easily deal with a large number of uncertain factors in the actual power grid, and its calculation time does not increase sharply with the increase of the system scale or the complexity of the network connection. It is a very widely used calculation method. However, in order to ensure the accuracy, the number of sampling times in the simulation is tens of thousands, so this method is very time-consuming and it is difficult to guarantee the calculation efficiency.

(4) Algorithm based on Bootstrap: This method is applied to long-term ATC calculation, which can make full use of recent market information (such as generator output, node load level, etc.) as an estimated sample. However, as a new algorithm, it cannot deal with the uncertainty of some network parameters well (such as random faults of power lines, etc.), and needs further improvement.

(5) ATC calculation method based on probability: Document Lei Dong, Saifeng Li, Yihan Yang, Hai Bao. Asia-Pacific Power and Energy Engineering Conference (APPEEC2010), 2010 "The Calculation of Transfer Reliability Margin Based on the Probabilistic Load Flow" Using the probability power flow, the ATC is calculated after fully considering the two margins of TRM and CBM. Although the speed is significantly improved, only one bottleneck line is considered, and the probabilistic influence of other transmission components is ignored, which makes it difficult to satisfy the calculation accuracy of the algorithm.

To sum up, in the existing probabilistic ATC calculation methods, the models of methods (1)-(4) are too complicated and the calculation is too time-consuming; although the calculation speed of (5) is guaranteed, the bottleneck conditions considered are too few and the accuracy is not enough . If the calculation speed of probabilistic ATC is too slow, it will make it difficult to guarantee the calculation efficiency of AQTC, and it will be difficult to use it in engineering; if the calculation accuracy of probabilistic ATC is not enough, the deviation between the subsequent calculated AQTC and the actual value will be too large, It can not play a guiding role for both parties in the transaction, resulting in waste or shortage of power resources.

Contents of the invention

In view of the above problems, the object of the present invention is to provide a calculation method of available transmission capacity based on probability power flow that takes into account both speed and accuracy.

In order to achieve the above object, the present invention adopts the following technical solutions: a method for calculating the available transmission capacity based on probabilistic power flow, which includes the following steps: 1) for the power system that needs to calculate AQTC, select several typical methods in the cycle, the typical The modes include typical mode 1, typical mode 2, ..., typical mode n, and set the duration of each typical mode in the period; 2) take each typical mode as the operation mode of the power system in turn, and calculate the Probabilistic ATC expectation under each operating mode, which includes the following steps: 2-1) read in the data of the power system to be calculated under a certain operating mode, the power system data includes various parameters of each power transmission element; and set The required accuracy requirement of the power system under this mode of operation; 2-2) calculate the deterministic ATC of the power system according to the parameters of each power transmission element obtained, which is denoted as ATC _c ; 2-3) make the ATC _c of gained as The power injected into the feeding area and the outgoing power in the receiving area are used to calculate the probability flow distribution of the power system at this time, which includes the power distribution of the transmission line and the voltage distribution of the transmission bus; 2-4) According to the probability flow distribution of the power system, Calculate the influence factor of each transmission element on the system ATC, and sort the transmission elements according to the influence factor from large to small; 2-5) Select the transmission element with the largest influence factor as the component set composed of the power transmission element to be added to the power system , calculate the ATC of its power transmission element and use the obtained probability distribution curve of the power transmission element ATC as the initial distribution curve of the power system probability ATC, and take the expectation of the initial distribution curve as the initial expectation of the power system probability ATC; 2- 6) According to the sorting results of the impact factors from large to small, add power transmission components to the component set in turn; 2-7) Determine whether the power transmission components to be added are independent of each other; if independent, go to the next step ; If not independent, then remove, return to step 2-6) add the next power transmission element; 2-8) calculate the probability ATC of the added power transmission element, and compare its distribution curve with the original probability ATC distribution curve of the power system Fitting to obtain the new probability ATC distribution curve of the power system, and calculate the expectation of the new probability ATC distribution curve; 2-9) If the difference between the new expectation obtained by the power system and the original expectation obtained last time satisfies the preset Accuracy requirements, then use the new probability ATC distribution curve as the final distribution curve of the power system; if not satisfied, return to step 2-6) Continue to add new transmission components until the preset accuracy requirements are met; 3 ) Multiply the probability ATC expectation in each typical mode by the duration of each typical mode, and sum the obtained products to obtain the AQTC in the period.

2-4) of said step 2) includes the following content: the impact factor μ of the power transmission element on the system probability ATC is as follows: the influence factor _μ i of the transmission line i on the system probability ATC is: Among them, P _imax is the allowable maximum power of transmission line i; P _i is the probabilistic power of transmission line i; the influence factor μ _j of bus j to system probability ATC is: Among them, V _jmin is the lower limit of the bus voltage; V _jmax is the upper limit of the bus voltage; V _j is the voltage of the bus j; through the value of the influence factor μ, the degree of influence of each transmission element on the power system can be sorted, which represents μ _i and μ _j are collectively referred to as the impact factor μ, the greater the value of μ, the greater the degree of influence, and vice versa.

2-5) of said step 2) includes the following content: the ATC of the transmission element, including the available transmission capacity LATC of the transmission line and the available transmission capacity BATC of the transmission bus; 1. the available transmission capacity LATC of the transmission line: set any one The transmission line i is the bottleneck factor, and the transmission capacity of the power system that can be reused for commercial use is the available transmission capacity LATC _i of the transmission line i; let ΔLATC _i be the definite system state with all parameters known, and the transmission line i When ΔLATC is the bottleneck factor, the power can be increased or decreased in the feeding and receiving areas; if the growth relationship between P _i and ΔLATC _i is positively correlated, then: ${\mathrm{LATC}}_i={\mathrm{ATC}}_c+\mathrm{\&Delta;}{\mathrm{LATC}}_i={\mathrm{ATC}}_c+\frac{P_{i\max }-P_i}{S_{\mathrm{Ai}}-S_{\mathrm{Bi}}};$ Among them, P _imax is the allowable maximum power of transmission line i; P _i is the probabilistic power of transmission line i; S _Ai is the sensitivity of power increase in feeding area to the power of transmission line i; S _Bi is the impact of power increase in receiving area The power sensitivity of transmission line i; if the growth relationship between P _i and ΔLATC _i is negatively correlated, LATC _i is considered to be infinite at this time, regardless of the influence of this transmission line i on the probability result; ②The availability of transmission bus Transmission capacity BATC: Assuming that any bus j is the bottleneck factor, the transmission capacity of the power system that can be reused for commercial use is the available transmission capacity BATC _j of bus j; let ΔBATC _j be the definite system state in which all parameters are known , when the bus j is the bottleneck factor, the power in the feeding and receiving areas can be increased or decreased; if the growth relationship between V _j and ΔBATC _j is positively correlated, then: when V _j <V _jmin : ; When V _j > V _jmin : ${\mathrm{BATC}}_j={\mathrm{ATC}}_c+\mathrm{\&Delta;}{\mathrm{BATC}}_j={\mathrm{ATC}}_c+\frac{V_{j\max }-V_j}{S_{\mathrm{Aj}}-S_{\mathrm{bj}}};$ Among them, V _jmin is the lower limit of the bus voltage; V _jmax is the upper limit of the bus voltage; S _Aj is the voltage sensitivity of the power increase in the feeding area to the bus j; S _Bj is the voltage sensitivity of the power increase in the receiving area to the bus j; positive correlation When S _Aj -S _Bj >0; if the growth relationship between V _j and ΔBATC _j is negatively correlated, then: when V _j >V _jmax : ; When V _j < V _jmax : ${\mathrm{BATC}}_j={\mathrm{ATC}}_c+\mathrm{\&Delta;}{\mathrm{BATC}}_j={\mathrm{ATC}}_c+\frac{V_j-V_{j\min }}{S_{\mathrm{Aj}}-S_{\mathrm{bj}}}.$

The relevant conditions of any two transmission lines in 2-7) of the step 2) are as follows: if the two transmission lines can meet the following three numerical requirements at the same time, then these two transmission lines are related: dominant correlation degree β _D Greater than 75% of the maximum correlation S _max : ;The total correlation β is greater than 75% of the dominant correlation: The same number λ is greater than 75% of the total number of nodes N or less than 25% of the total number of nodes N: or

The present invention has the following advantages due to the adoption of the above technical scheme: 1. The present invention utilizes the probability ATC of the probability power flow calculation system, which greatly reduces the calculation amount compared with the simulation method, thereby improving the calculation speed of the system probability ATC, and then improving AQTC calculation speed. 2. Propose the concept of transmission component ATC and its influence factors on the system ATC, add transmission components to the power system in order of influence factors from large to small, and take the influence of more transmission components into the probability ATC results of the system, The deviation from the actual probability ATC expectation of the system is reduced step by step, thereby meeting the calculation accuracy of the probability ATC required by the system, and at the same time satisfying the calculation accuracy of AQTC. In view of the above reasons, the present invention can be widely used in the fields of probabilistic available power transmission capacity calculation and probabilistic available power transmission capacity calculation.

Description of drawings

Figure 1 is a schematic diagram of a typical method selection

Fig. 2 is a schematic flow chart of probability ATC calculation in the present invention

Figure 3 is a schematic diagram of the probability distribution of transmission line i power

Figure 4 is a schematic diagram of the qualitative relationship between the power P _i of transmission line i and ΔLATC _i

Figure 5 is a schematic diagram of the probability distribution of the voltage of the transmission bus j

Figure 6 is a schematic diagram of the qualitative relationship between the voltage V _j of the transmission bus j and ΔBATC _j

Detailed ways

The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

1) As shown in Figure 1, first of all, for the power system that needs to calculate AQTC (Available Quantity TransferCapability, available power transfer capability), several typical methods are selected in the cycle, namely typical method 1, typical method 2, ..., typical method n . Set the duration of each typical mode in the cycle, and the selection principle is as follows: select a typical mode as a representative in a small cycle with little change in the operating mode, and re-select the typical mode once the operating mode changes greatly. In the actual power system, the staff has explored a relatively mature method of selecting typical modes based on years of operating experience, which can be directly applied.

2) Taking each typical mode as the operating mode of the power system in turn, and calculating the expectation of the probability ATC of the power system under each operating mode, which includes the following steps:

It should be noted that the steps for calculating the probability ATC expectation in different operating modes of the power system are consistent, so the description will not be repeated, and only the calculation process of the probability ATC in this operating mode will be described as a representative.

2-1) As shown in Figure 2, read in the data of the power system to be calculated under this operation mode, the power system data includes the power transmission components such as generators, transmission lines, transformers, and reactive power compensation devices commonly used in this field Various parameters, in order to calculate the deterministic ATC and probabilistic power flow of the power system based on these existing parameters. The probability ATC of the transmission element can be obtained by using the results of the probability flow, that is, the available transmission capacity of the transmission element, which includes the available transmission capacity LATC (Line Available Transfer Capability) of the transmission line and the available transmission capacity BATC (Bus Available Transfer Capability) of the transmission bus. In the present invention, the power transmission elements that affect the probability ATC of the power system are the power transmission line and the generator, and the ATC of the power transmission line is LATC, and the ATC of the generator is BATC.

2-2) According to the parameters of each power transmission element obtained, the deterministic ATC of the power system is calculated by using the ATC algorithm commonly used in the art based on continuous power flow, which is denoted as ATC _c ;

2-3) Let the obtained ATC _c be the injected power in the feeding area and the outflowing power in the receiving area, and use the probabilistic power flow algorithm commonly used in this field combined with semi-invariant and Gram-Charlier series expansion to calculate the power flow of the power system at this time Probabilistic power flow distributions, which include the power distribution of transmission lines and the voltage distribution of transmission buses;

2-4) According to the probability flow distribution of the power system, the influence factors of each transmission element on the system ATC are calculated, and the transmission elements are sorted according to the influence factors from large to small;

The system probability ATC is subject to the power transmission element that crosses the limit first (exceeding the operating limit), so the power transmission element that operates closer to the limit state may have a greater impact on the system probability ATC, so the influence factor μ of the power transmission element is proposed It is used to compare the degree of influence of each transmission element on the system probability ATC.

Let the influence factor μ _i of the transmission line i on the system probability ATC be:

${\mathrm{<span\; class="notranslate">\; \&mu;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; \&Integral;</span>}_{\mathrm{<span\; class="notranslate">\; 0</span>}}^{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; max</span>}}}{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dx</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

Let the influence factor μ _j of the bus j on the system probability ATC be:

${\mathrm{<span\; class="notranslate">\; \&mu;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; \&Integral;</span>}_{{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; min</span>}}}^{{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; max</span>}}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dx</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

According to the value of the influence factor μ (μ _i and μ _j are collectively referred to as the influence factor μ), the degree of influence of each transmission element on the power system can be sorted: the larger the value of μ, the greater the degree of influence, and vice versa. In this way, when adding power transmission elements for probability fitting iterations, the power transmission elements with less influence can be ignored if the accuracy is satisfied. For the actual system with large system scale and concentrated bottleneck power transmission components, the calculation amount is greatly reduced.

2-5) Select the power transmission element with the largest influence factor as the initial power transmission element of the element set formed by adding power transmission elements to the power system, calculate the ATC of its power transmission element, and use its probability distribution curve as the initial distribution curve of the power system probability ATC , taking the expectation of the initial distribution curve as the initial expectation of the power system probability ATC;

① Available transmission capacity LATC of transmission lines

Assuming that any transmission line i is the bottleneck factor, the reusable transmission capacity of the power system for commercial use is the available transmission capacity LATC _i of the transmission line i.

As shown in Figure 3 and Figure 4, let ΔLATC _i be the power that can be increased (or decreased) in the feeding and receiving areas when the transmission line i is taken as the bottleneck factor in a definite system state where all parameters are known , where ΔLATC _i >0 indicates that the transmission line i has not reached its operating limit in this system state; ΔLATC _i =0 indicates that the transmission line i has just reached the operating limit in this system state; ΔLATC _i <0 indicates In this system state, the transmission line i has already exceeded the operating limit. Let P _i be the probabilistic power of transmission line i.

If as ΔLATC _i increases, the power (absolute value) P _i of transmission line i also increases, that is, the growth relationship between ΔLATC _i and P _i is positively correlated, then the relationship between the two is as follows:

$\begin{array}{cc}\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; LATC</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; max</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; Ai</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; Bi</span>}}}& {\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; Ai</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; Bi</span>}}<span\; class="notranslate">\; ></span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>\end{array}$

Among them, P _imax is the maximum transmission power allowed by the transmission line i; S _Ai is the sensitivity of the power increase in the feeding area to the power of the transmission line i; S _Bi is the sensitivity of the power increase in the receiving area to the power of the transmission line i, because the load growth, so it has a negative sign; S _Ai -S _Bi >0 is equivalent to the positive correlation between the growth relationship between ΔLATC _i and _Pi .

If the power (absolute value) of transmission line i decreases with the increase of ΔLATC _i , that is, the growth relationship between ΔLATC _i and _Pi is negatively correlated ( _SAi -S _Bi <0), then it can be considered that ΔLATC _i at this time is positive infinity. Normally, if the power (absolute value) of transmission line i decreases with the increase of ΔLATC _i , then in the process of increasing ΔLATC _i , transmission line i can never reach its limit, because the limit of the line is A maximum value that cannot be reached has no lower limit, so it can be considered that ΔLATC _i is positive and infinite. In other words, the influence of this transmission line i on the probability result is not considered during negative correlation.

Use the formula (4) to calculate the available transmission capacity LATC _i of the transmission line i:

${\mathrm{<span\; class="notranslate">\; LATC</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; ATC</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; LATC</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; ATC</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; +</span>\frac{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; max</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; Ai</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; Bi</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; )</span>$

②Available transmission capacity BATC of transmission bus

Assuming that any bus j is the bottleneck factor, the transmission capacity of the power system that can be reused for commercial use is the available transmission capacity BATC _j of bus j.

As shown in Fig. 5 and Fig. 6, let ΔBATC _j be the power that can be increased (or decreased) in the feeding and receiving areas when all the parameters are known and the definite system state is taken as the bottleneck factor. Among them, ΔBATC _j > 0 means that in this system state, bus j has not reached the operating limit; ΔBATC _j = 0 means that in this system state, bus j has just reached the operating limit; ΔBATC _j < 0 means that in this system state, Bus j has already exceeded the operating limit.

If the growth relationship between V _j and ΔBATC _j is positive, then:

When V _j < V _jmin : BATC _j = 0 (5)

When V _j > V _jmin : ${\mathrm{BATC}}_j={\mathrm{ATC}}_c+\frac{V_{j\max }-V_j}{S_{\mathrm{Aj}}-S_{\mathrm{bj}}}---\left(6\right)$

Among them, V _j is the voltage of bus j; V _jmin is the lower limit of the voltage of bus j; V _jmax is the upper limit of the voltage of bus j; S _Aj is the voltage sensitivity of power increase in the feeding area to bus _j ; The voltage sensitivity of regional power growth to bus j; S _Aj -S _Bj >0 in positive correlation.

If the growth relationship between V _j and ΔBATC _j is negatively correlated, then:

When V _j >V _jmax : BATC _j = 0 (7)

When V _j < V _jmax : ${\mathrm{BATC}}_j={\mathrm{ATC}}_c+\frac{V_j-V_{j\min }}{S_{\mathrm{Aj}}-S_{\mathrm{bj}}}---\left(8\right)$

It should be noted that since the power P _i of transmission line i and the voltage V _j of transmission bus j are probabilistic values, the available transmission capacity LATC _i of transmission line i and the available transmission capacity BATC _{j of transmission bus j} are both probabilistic ATC.

2-6) According to the sorting results of the impact factors from large to small, add power transmission components to the component set in turn. Since multiple power transmission components can be considered in the probability results according to the size of the impact factors, it can be considered that the added power transmission components The more, the closer to the exact value, the higher the accuracy, while satisfying the calculation speed, the accuracy control is achieved;

2-7) Judging whether the power transmission component to be added is independent of each power transmission component that has been added; if independent, proceed to the next step; if related (not independent), then eliminate and return to step 2-6) Add the next power transmission Components, the process of judging independence is as follows:

If the power transmission component to be added is a bus, because the bus and the transmission line are independent, add it directly and proceed to the next step without judging the mutual independence of the added power transmission component; if the added power transmission component is a power transmission Lines are calculated for the correlation with the added transmission lines in the component set, so as to judge mutual independence, and there is no need to perform independence judgments with the added transmission buses in the component set.

The correlation judgment method between transmission lines is as follows:

Let any two transmission lines be m-n, p-q, define the total correlation (Line Relevancy, LR) of these two transmission lines as the sum of the products of their injection sensitivities to each node, then the total correlation between any two transmission lines β:

$\mathrm{<span\; class="notranslate">\; \&beta;</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; p</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; q</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 9</span>}<span\; class="notranslate">\; )</span>$

Among them, β is the total correlation between the transmission lines mn and pq; N is the calculated number of nodes in the power system; S _mn,i is the calculated sensitivity of the power injection of the bus j in the power system to the transmission line mn ; S _pq,i is the calculated sensitivity of power injection of bus j to transmission line pq in the power system.

In general, the power of the transmission line is most affected by the power injected at the two ends of the transmission line, which is reflected in the l-w sensitivity matrix between the power l of the transmission line and the injected power w of the node. The sensitivity of all node powers to it is the largest.

Therefore, the sensitivity of the injected power of the transmission line endpoint is considered separately, and the sum of the sensitivity products of the transmission line endpoint to the two transmission lines is defined as the Dominant Relevance (DR). If the two transmission lines have the same endpoint, then only Calculate once:

${\mathrm{<span\; class="notranslate">\; \&beta;</span>}}_{\mathrm{<span\; class="notranslate">\; D.</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; p</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; q</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; p</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; q</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 10</span>}<span\; class="notranslate">\; )</span>$

Among them, β _D is the dominant correlation between transmission line mn and transmission line pq.

Define the sum of the sensitivity products of the remaining nodes to the two transmission lines as Non-Dominant Relevance (NDR):

${\mathrm{<span\; class="notranslate">\; \&beta;</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; \&NotEqual;</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; p</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; q</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; p</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; q</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 11</span>}<span\; class="notranslate">\; )</span>$

Among them, _βN is the non-dominant correlation between the transmission line mn and the transmission line pq.

Count the same number λ of the sensitivity of the two transmission lines to each node, and calculate the maximum value of the sensitivity product, that is, the maximum correlation S _max :

S _max ＝max{S _mn,j ×S _pq,j } (12)

The dominant correlation reflects the sum of the random fluctuations of the dominant nodes (transmission line endpoints) on the power of the two transmission lines. If the two transmission lines are correlated, the products of the sensitivities of the dominant nodes basically maintain the same sign (or the value of nodes with different signs is very small), and the dominant correlation degree is relatively large.

The total correlation reflects the sum of the random fluctuations of each node on the power of the two transmission lines. If the two transmission lines are correlated, the correlation degree of the dominant node will be larger, and the non-dominant correlation degree should have the same sign as the dominant correlation degree, or a different sign but a small value, and the total correlation degree of the two will be larger.

The number of the same number reflects the influence direction of the random fluctuation of each node on the power of the two transmission lines. If the two transmission lines are positively correlated, the number of nodes with the same number is much greater than the number of nodes with different numbers; if the two transmission lines are negatively correlated, the number of nodes with the same number is much smaller than the number of nodes with different numbers.

If the two transmission lines can meet the following three numerical requirements at the same time, the two transmission lines are related to each other, that is, they are not independent: the dominant correlation degree β _D is greater than 75% of the maximum correlation degree S _max : The total correlation β is greater than 75% of the dominant correlation β _D : The same number λ is greater than 75% of the total number of nodes N or less than 25% of the total number of nodes N: or

2-8) Calculate the probability ATC of the added power transmission element, fit its distribution curve with the original probability ATC distribution curve of the power system, obtain the new probability ATC distribution curve of the power system, and calculate the new probability ATC distribution The expectation of the curve, the fitting process is as follows:

P _AB (x)＝P _A (x)×P _B (B≥x)+P _A (A≥x)×P _B (x)-P _A (x)×P _B (x) (13)

Among them, AB is a system composed of any two transmission elements A and B; P _AB is the distribution of the probability ATC of the AB system; P _A is the probability ATC distribution of the transmission element A; P _B is the probability ATC distribution of the transmission element B; x∈(0,+∞).

Introduce cumulative function $f_A\left(x\right)=\underset{-\&infin;}{\overset{x}{\&Integral;}}{P}_A\left(x\right)\mathrm{dx},f_B\left(x\right)=\underset{-\&infin;}{\overset{x}{\&Integral;}}{P}_B\left(x\right)\mathrm{dx},$ Then there are:

P _AB (x)＝P _A (x)×(1-F _B (x))+(1-F _A (x))×P _B (x)+P _A (x)×P _B (x) ( 14)

2-9) If the difference between the new expectation obtained by the power system and the original expectation obtained last time meets the preset accuracy requirements, the new probability ATC distribution curve is used as the final distribution curve of the power system; if not satisfied, Then return to step 2-6) and continue to add new power transmission elements until the preset accuracy requirements are met.

3) Multiply the expected probability ATC under each typical mode by the duration of each typical mode, and sum the obtained products to obtain the AQTC within the period.

The above is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto, any person familiar with the technical field within the technical scope disclosed in the present invention, according to the technical solution of the present invention Any equivalent replacement or change of the inventive concepts thereof shall fall within the protection scope of the present invention.

Claims (5)

1. A calculation method of available transmission capacity based on probability power flow, which comprises the following steps: 1) For the power system that needs to calculate AQTC, select several typical modes in the period, the typical modes include typical mode 1, typical mode 2, ..., typical mode n, and set the duration of each typical mode in the cycle ; 2) Taking each typical mode as the operating mode of the power system in turn, and calculating the probability ATC expectation of the power system under each operating mode, which includes the following steps: 2-1) Read in the data of the power system to be calculated in a certain operation mode, the power system data includes various parameters of each power transmission element; and set the required accuracy requirements of the power system in this operation mode; 2-2) Calculate the deterministic ATC of the power system according to the parameters of each power transmission element obtained, denoted as ATC _c ; 2-3) Let the obtained ATC _c be the injected power in the feeding area and the outflowing power in the receiving area, and calculate the probability power flow distribution of the power system at this time, which includes the power distribution of the transmission line and the voltage distribution of the transmission bus; 2-4) According to the probability flow distribution of the power system, the influence factors of each transmission element on the system ATC are calculated, and the transmission elements are sorted according to the influence factors from large to small; 2-5) Select the power transmission element with the largest influence factor as the initial power transmission element of the element set composed of power transmission elements to be added to the power system, calculate the ATC of the power transmission element, and use the probability distribution curve of the power transmission element ATC as the probability distribution curve of the power system The initial distribution curve of ATC, taking the expectation of the initial distribution curve as the initial expectation of the power system probability ATC; 2-6) According to the sorting results of the impact factors from large to small, add power transmission components to the component set in sequence; 2-7) Determine whether the power transmission element to be added is independent of each power transmission element that has been added; if independent, proceed to the next step; if not independent, then reject and return to step 2-6) to add the next power transmission element; 2-8) Calculate the probability ATC of the added power transmission element, fit its distribution curve with the original probability ATC distribution curve of the power system, obtain the new probability ATC distribution curve of the power system, and calculate the new probability ATC distribution the expectation of the curve; 2-9) If the difference between the new expectation obtained by the power system and the original expectation obtained last time meets the preset accuracy requirements, the new probability ATC distribution curve is used as the final distribution curve of the power system; if not satisfied, Then return to step 2-6) and continue to add new power transmission elements until the preset accuracy requirements are met; 3) Multiply the expected probability ATC under each typical mode by the duration of each typical mode, and sum the obtained products to obtain the AQTC within the period. 2. A kind of available transmission capacity calculation method based on probability power flow as claimed in claim 1, is characterized in that: the 2-4) of described step 2) comprises the following content: The influence factor μ of the power transmission element affects the system probability ATC as follows: Let the influence factor μ _i of the transmission line i on the system probability ATC be: ${\mathrm{<span\; class="notranslate">\; \&mu;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; \&Integral;</span>}_{\mathrm{<span\; class="notranslate">\; 0</span>}}^{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; max</span>}}}{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dx</span>}$ Among them, P _imax is the allowable maximum power of transmission line i; P _i is the probabilistic power of transmission line i; Let the influence factor μ _j of the bus on the system probability ATC be: ${\mathrm{<span\; class="notranslate">\; \&mu;</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>{<span\; class="notranslate">\; \&Integral;</span>}_{{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; min</span>}}}^{{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; max</span>}}}{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dx</span>}$ Among them, V _jmin is the lower limit of bus voltage; V _jmax is the upper limit of bus voltage; V _j is the voltage of bus j; The degree of influence of each transmission element on the power system can be sorted by the value of the influence factor μ, and its representative μ _i and μ _j are collectively called the influence factor μ, the greater the value of μ, the greater the degree of influence, and vice versa. 3. A kind of available transmission capacity calculation method based on probability power flow as claimed in claim 1, is characterized in that: the 2-5) of described step 2) comprises the following content: The ATC of the transmission components, including the available transmission capacity LATC of the transmission line and the available transmission capacity BATC of the transmission bus; ① Available transmission capacity LATC of transmission lines Assuming that any transmission line i is the bottleneck factor, the transmission capacity of the power system that can be reused for commercial use is the available transmission capacity LATC _i of the transmission line i; let ΔLATC _i be the definite system state where all parameters are known, When the transmission line i is used as the bottleneck factor, the power that can be increased or decreased in the feeding and receiving areas; If the growth relationship between P _i and ΔLATC _i is positively correlated, then: ${\mathrm{<span\; class="notranslate">\; LATC</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; ATC</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; LATC</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; ATC</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; +</span>\frac{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; max</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; Ai</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; Bi</span>}}}$ Among them, P _imax is the allowable maximum power of transmission line i; P _i is the probabilistic power of transmission line i; S _Ai is the sensitivity of power increase in feeding area to the power of transmission line i; S _Bi is the impact of power increase in receiving area Sensitivity of transmission line i power; If the growth relationship between P _i and ΔLATC _i is negatively correlated, it is considered that LATC _i is infinite at this time, and the influence of this transmission line i on the probability result is not considered; ②Available transmission capacity BATC of transmission bus Assuming that any bus j is the bottleneck factor, the transmission capacity of the power system that can be reused for commercial use is the available transmission capacity BATC _j of bus j; let ΔBATC _j be the definite system state with known all parameters, with bus j When it is a bottleneck factor, the power that can be increased or decreased in the two areas of power feeding and power receiving; If the growth relationship between V _j and ΔBATC _j is positive, then: When V _j < V _jmin : BATC _j = 0 When V _j > V _jmin : ${\mathrm{BATC}}_j={\mathrm{ATC}}_c+\mathrm{\&Delta;}{\mathrm{BATC}}_j={\mathrm{ATC}}_c+\frac{V_{j\max }-V_j}{S_{\mathrm{Aj}}-S_{\mathrm{bj}}}$ Among them, V _jmin is the lower limit of the bus voltage; V _jmax is the upper limit of the bus voltage; S _Aj is the voltage sensitivity of the power increase in the feeding area to the bus j; S _Bj is the voltage sensitivity of the power increase in the receiving area to the bus j; positive correlation When S _Aj -S _Bj >0; If the growth relationship between V _j and ΔBATC _j is negatively correlated, then: When V _j >V _jmax : BATC _j = 0 When V _j < V _jmax : ${\mathrm{BATC}}_j={\mathrm{ATC}}_c+\mathrm{\&Delta;}{\mathrm{BATC}}_j={\mathrm{ATC}}_c+\frac{V_j-V_{j\min }}{S_{\mathrm{Aj}}-S_{\mathrm{bj}}}.$ 4. A kind of available transmission capacity calculation method based on probability power flow as claimed in claim 2, is characterized in that: the 2-5) of described step 2) comprises the following content: The ATC of the transmission components, including the available transmission capacity LATC of the transmission line and the available transmission capacity BATC of the transmission bus; ① Available transmission capacity LATC of transmission lines Assuming that any transmission line i is the bottleneck factor, the transmission capacity of the power system that can be reused for commercial use is the available transmission capacity LATC _i of the transmission line i; let ΔLATC _i be the definite system state where all parameters are known, When the transmission line i is used as the bottleneck factor, the power that can be increased or decreased in the feeding and receiving areas; If the growth relationship between P _i and ΔLATC _i is positively correlated, then: ${\mathrm{<span\; class="notranslate">\; LATC</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; ATC</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}{\mathrm{<span\; class="notranslate">\; LATC</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; ATC</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; +</span>\frac{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; max</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; Ai</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; Bi</span>}}}$ Among them, P _imax is the allowable maximum power of transmission line i; P _i is the probabilistic power of transmission line i; S _Ai is the sensitivity of power increase in feeding area to the power of transmission line i; S _Bi is the impact of power increase in receiving area Sensitivity of transmission line i power; If the growth relationship between P _i and ΔLATC _i is negatively correlated, it is considered that LATC _i is infinite at this time, and the influence of this transmission line i on the probability result is not considered; ②Available transmission capacity BATC of transmission bus Assuming that any bus j is the bottleneck factor, the transmission capacity of the power system that can be reused for commercial use is the available transmission capacity BATC _j of bus j; let ΔBATC _j be the definite system state with known all parameters, with bus j When it is a bottleneck factor, the power that can be increased or decreased in the two areas of power feeding and power receiving; If the growth relationship between V _j and ΔBATC _j is positive, then: When V _j < V _jmin : BATC _j = 0 When V _j > V _jmin : ${\mathrm{BATC}}_j={\mathrm{ATC}}_c+\mathrm{\&Delta;}{\mathrm{BATC}}_j={\mathrm{ATC}}_c+\frac{V_{j\max }-V_j}{S_{\mathrm{Aj}}-S_{\mathrm{bj}}}$ Among them, V _jmin is the lower limit of the bus voltage; V _jmax is the upper limit of the bus voltage; S _Aj is the voltage sensitivity of the power increase in the feeding area to the bus j; S _Bj is the voltage sensitivity of the power increase in the receiving area to the bus j; positive correlation When S _Aj -S _Bj >0; If the growth relationship between V _j and ΔBATC _j is negatively correlated, then: When V _j >V _jmax : BATC _j = 0 When V _j < V _jmax : ${\mathrm{BATC}}_j={\mathrm{ATC}}_c+\mathrm{\&Delta;}{\mathrm{BATC}}_j={\mathrm{ATC}}_c+\frac{V_j-V_{j\min }}{S_{\mathrm{Aj}}-S_{\mathrm{bj}}}.$ 5. A method for calculating available transmission capacity based on probability flow as claimed in claim 1 or 2 or 3 or 4, characterized in that: the conditions related to any two transmission lines in 2-7) of said step 2) are as follows : If the two transmission lines can meet the following three numerical requirements at the same time, the two transmission lines are related: the dominant correlation degree β _D is greater than 75% of the maximum correlation degree S _max : The total correlation β is greater than 75% of the dominant correlation: The same number λ is greater than 75% of the total number of nodes N or less than 25% of the total number of nodes N: $\mathrm{\&lambda;}>\frac{3}{4}N$ or $\mathrm{\&lambda;}<\frac{1}{4}N.$