Post-disaster power grid restoration time prediction method considering distribution network resilience

Abstract

The present invention relates to a method for predicting the power restoration time of a post-disaster power grid considering the resilience of a distribution network, comprising the following steps: step S1: obtaining power grid data information of a distribution network; step S2: according to the power grid data information, introducing the distribution network resilience index described by the integral of the weighted loss of load and the time axis of the distribution network under natural disasters, and constructing a distribution network function curve model; step S3: obtaining natural disaster-related parameters, and establishing a natural disaster model according to the natural disaster-related parameters; step S4: constructing a basic calculation model for the total power restoration time of a post-disaster power grid considering the resilience of the distribution network; step S5: correcting the basic calculation model for the total power restoration time of a post-disaster power grid considering the resilience of the distribution network, and obtaining an accurate calculation model for the total time of fault processing of the distribution network; step S6: obtaining the power grid data information of the post-disaster distribution network, and obtaining the power restoration time of the post-disaster power grid based on the accurate calculation model for the total time of fault processing of the distribution network. The present invention can quickly obtain the power restoration time of the post-disaster power grid with high accuracy, and can effectively improve the reliability of the distribution network.

Description

Technical Field

[0001] The present invention belongs to the field of electrical automation, and in particular relates to a method for predicting power restoration time of a power grid after a disaster taking into account the resilience of the distribution network. Background Art

[0002] With the development of economy and technology and the improvement of people's living standards, electricity has become an indispensable secondary energy source in people's production and life, bringing endless convenience to people's production and life.

[0003] The distribution terminal unit (DTU) is the basic equipment of distribution automation. It can monitor the operation status of the distribution line, detect line faults in time, diagnose and isolate the faulty section, and restore power supply to the non-faulty section, which can significantly improve the power supply reliability of the distribution network. At present, the research on distribution terminals can be roughly divided into two categories. One is to focus on the optimization configuration of distribution terminals, and the other is to focus on the impact of distribution terminals on the power supply reliability of distribution networks. Both types of research on distribution terminals require the establishment of a reliability model for distribution terminals. At the same time, distribution terminals, like other power equipment, are bound to fail during operation, which will affect the power supply reliability of the entire system.

[0004] The total fault handling time of the distribution network refers to the total time consumed from the occurrence to the completion of the handling of the fault when a distribution network fault occurs. The total fault handling time of the distribution network is one of the important parameters of the distribution network, and directly affects the reliability calculation results of the distribution network. Therefore, the calculation of the total fault handling time of the distribution network is very important. However, the current calculation process of the total fault handling time of the distribution network is relatively simple and rough. In addition, due to the increase in the number of distributed power sources, the resilience of the distribution network is gradually enhanced, and the ability to resist natural disasters is gradually enhanced. Few people have proposed a method for calculating the post-disaster power restoration time of the power grid that considers the resilience of the distribution network. The calculation results of the total fault handling time of the distribution network obtained by the previous distribution network restoration time calculation method are of poor accuracy, which has seriously affected the reliability calculation results of the distribution network. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a method for predicting the power restoration time of a post-disaster power grid taking into account the resilience of the distribution network, which can quickly obtain the power restoration time of the post-disaster power grid with high accuracy and effectively improve the reliability of the distribution network.

[0006] To achieve the above object, the present invention adopts the following technical solution:

[0007] A method for predicting power restoration time of a power grid after a disaster considering the resilience of the distribution network comprises the following steps:

[0008] Step S1: Obtain the power grid data information of the distribution network;

[0009] Step S2: According to the power grid data information, and introducing the distribution network resilience index described by the integral of the weighted load loss of the distribution network under natural disasters with respect to the time axis, construct a distribution network function curve model;

[0010] Step S3: Obtain the natural disaster-related parameters, and establish a natural disaster model based on the natural disaster-related parameters;

[0011] Step S4: Construct a basic calculation model for the total post-disaster power restoration time of the power grid considering the resilience of the distribution network;

[0012] Step S5: Based on the probability prediction theory, correct the basic calculation model for the total post-disaster power restoration time of the power grid considering the resilience of the distribution network to obtain an accurate calculation model for the total power grid fault handling time;

[0013] Step S6: Obtain the power grid data information of the post-disaster distribution network, and based on the accurate calculation model for the total power grid fault handling time, obtain the post-disaster power restoration time of the power grid.

[0014] Furthermore, the power grid data information includes the length of the power supply main line, the length of the power supply branch line, the average repair time corresponding to the failure rate, the operation time of the disconnector, the load of each load point, and the number of power supply users at each load point.

[0015] Furthermore, the distribution network function curve model has the time as the abscissa and the load level as the ordinate.

[0016] Furthermore, the natural disaster is a typhoon, and Step S3 is specifically:

[0017] Construct a typhoon static wind field model:

[0018]

[0019] where K is an empirical parameter; v m is the maximum wind speed; r mv is the maximum wind speed radius; r s is the typhoon influence area radius; β is the typhoon boundary factor, representing the ratio of the maximum gradient wind speed to the boundary wind speed

[0020] Construct a typhoon dynamic wind field model. The typhoon dynamic wind field is used to describe the wind field change after the typhoon makes landfall, and is modeled as a set H of a series of static wind fields;

[0021] H = {h a} a = 0, 1, …, |H| (2)

[0022] h a = Γ(h0丨α, ph , v h , ΔT a ) (3)

[0023] where |·| is the number of elements in the set, and the same applies hereinafter; h0 is the wind field at the time of typhoon landing; h α is the wind field at time a after typhoon landing, and Γ(·) is a time-varying function of h α with respect to h0. The function Γ(·) can be simulated in combination with the following parameters: typhoon landing attenuation factor α, typhoon movement path p h , typhoon movement speed v h , and the time ΔT experienced at time a after typhoon landing.

[0024] Furthermore, the basic calculation model for the total post-disaster power restoration time of the power grid considering the resilience of the distribution network is as follows:

[0025] When the resilience of the distribution network can resist natural disasters, the total post-disaster power restoration time T of the power grid considering the resilience of the distribution network f is determined by the natural disaster model and the distribution network function curve model. The specific basic calculation model T f is:

[0026] T f = t1 - t0 (4)

[0027] where t0 is the time of disaster occurrence, and t1 is the time when the distribution network function returns to normal;

[0028] B. When the resilience of the distribution network cannot resist natural disasters, the total post-disaster power restoration time T of the power grid considering the resilience of the distribution network f is determined by the distribution network resilience failure time, fault location time, fault isolation time, expected fault patrol time, and fault recovery time. The specific basic calculation model T f is:

[0029] T f = T loc-r + T iso-r + T pat-exp + T rec + t2 - t0 (5)

[0030] In the formula, T loc-r is the fault location time; T iso-r is the fault isolation time; T pat-exp is the expected fault patrol time; T rec is the fault recovery time; t0 is the time of disaster occurrence, and t2 is the time when the distribution network function fails.

[0031] Furthermore, the expected fault patrol time is specifically:

[0032]

[0033] Where k is the segment number of the faulty feeder; N is the total number of segments of the faulty feeder; ΔL k is the length of the kth section of the faulty feeder; L is the length of the faulty feeder; t p It is the feeder inspection time per unit length; and it is stipulated that the failure rate per unit length of each feeder is the same.

[0034] Furthermore, the step S5 is based on the probability prediction theory to modify the basic calculation model of the total time for power restoration of the power grid after a disaster based on the resilience of the distribution network, so that the original model is updated in real time according to the probability of possible failure of the distribution network, thereby realizing the prediction of the power restoration time of the power grid after a disaster considering the resilience of the distribution network, specifically:

[0035] a. Use the following formula to calculate the corrected fault location time T loc-exp :

[0036] T loc-exp =(1-P loc-f )*T loc-f +P loc-f *T loc-f (7)

[0037] Where T loc-exp P is the positioning time after automatic positioning fails; loc-f Indicates the probability of failure of positioning function;

[0038] b. Use the following formula to calculate the corrected fault isolation time T iso-exp :

[0039] T iso-exp =(1-P iso-f )*T iso-f +P iso-f *T iso-f (8)

[0040] Where T iso-f P is the isolation time after automatic isolation fails; iso-f Indicates the probability of failure of the isolation function;

[0041] c. Use the following calculation to calculate the corrected fault recovery time T rec-exp :

[0042]

[0043] Where T ter is the recovery time of the power distribution terminal failure, and

[0044] T rec is the uncorrected fault recovery time;

[0045] d. Construct an accurate calculation model for the total time of distribution network fault processing:

[0046] (1) When the resilience of the distribution network can resist natural disasters, the total time for power restoration after a disaster is accurately calculated by considering the resilience of the distribution network:

[0047] T f =t1-t0 (10);

[0048] (2) When the resilience of the distribution network cannot resist natural disasters, a precise calculation model for the total time of power restoration after a disaster considering the resilience of the distribution network is proposed:

[0049] T f =T loc-exp +T iso-exp +T pat-exp +T rec-exp +t2-t0 (11).

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] The present invention can quickly obtain the power restoration time of the power grid after a disaster with high accuracy, and effectively improve the reliability of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 is a flow chart of the method of the present invention;

[0053] Figure 2 Schematic diagram of a differential model of a feeder in one embodiment of the present invention. DETAILED DESCRIPTION

[0054] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0055] Please refer to Figure 1 The present invention provides a method for calculating the power restoration time of a power grid after a disaster taking into account the resilience of the distribution network, comprising the following steps:

[0056] S1. Read the grid data information and historical data of the distribution network;

[0057] S2. Based on the grid data information and historical data of the distribution network and the distribution network resilience concept curve, the distribution network resilience index described by the integral of the weighted loss of load and the time axis of the distribution network under natural disasters is introduced to establish a distribution network function curve model;

[0058] S3. Establish a natural disaster model based on relevant parameters of natural disasters;

[0059] S4. Establish a basic calculation model for the total time of power grid restoration after a disaster considering the resilience of the distribution network;

[0060] S5. Modify the basic calculation model of the total post-disaster power grid restoration time considering the resilience of the distribution network established in step S4 to obtain an accurate calculation model of the total distribution network fault handling time;

[0061] S6. Calculate the final total distribution network fault handling time according to the accurate calculation model of the total distribution network fault handling time obtained in step S5.

[0062] Preferably, in this embodiment, the power grid data information includes the length of the power supply main line, the length of the power supply branch line, the average repair time corresponding to the failure rate, the operation time of the disconnector, the load of each load point, and the number of power supply users at each load point.

[0063] Preferably, in this embodiment, the distribution network function curve model has time as the abscissa and load level as the ordinate.

[0064] Preferably, in this embodiment, a natural disaster model is established, specifically:

[0065] A. Typhoon static wind field modeling: The influence range of a typhoon can be approximated as a circle, and the wind speed (or gradient wind speed) v at each point within its influence range is a piecewise function related to the distance d from this point to the eye of the typhoon. The wind speed outside the typhoon influence range is 0. For the area within the influence range: when d increases from 0 to the maximum wind speed radius, the wind speed increases monotonically; when d increases from the maximum wind speed radius to the typhoon coverage radius, the wind speed decreases monotonically.

[0066]

[0067] where K is an empirical parameter; v m is the maximum wind speed; r mv is the maximum wind speed radius; r s is the typhoon influence area radius; β is the typhoon boundary factor, representing the ratio of the maximum gradient wind speed to the boundary wind speed.

[0068] B. Typhoon dynamic wind field modeling: The typhoon dynamic wind field is used to describe the change of the wind field after the typhoon makes landfall and can be modeled as a set H of a series of static wind fields:

[0069] H = {h a} a = 0, 1, …, |H| (24)

[0070] h a = Γ(h0丨α, p h , v h , ΔT a ) (25)

[0071] where 丨·丨 is the number of elements in the set, and the same applies hereinafter; h0 is the wind field when the typhoon makes landfall; hα is the wind field at time a after the typhoon landed, Γ(·) is h α The function Γ(·) can be simulated by combining the following parameters: typhoon landing attenuation factor α, typhoon movement path p h , typhoon moving speed v h , the time △T that elapses at moment a after the typhoon makes landfall.

[0072] Preferably, in this embodiment, a basic calculation model for the total time of power restoration after a disaster considering the resilience of the distribution network is established, specifically:

[0073] A. When the distribution network resilience can resist natural disasters, the total time T for power restoration after a disaster considering the resilience of the distribution network f The specific basic calculation model T is determined by the natural disaster model and the distribution network function curve model. f for:

[0074] T f =t1-t0(26)

[0075] Among them, t0 is the time when the disaster occurs, and t1 is the time when the distribution network function returns to normal.

[0076] B. When the resilience of the distribution network cannot resist natural disasters, the total time T for power restoration after a disaster considering the resilience of the distribution network f The specific basic calculation model T is determined by the distribution network resilience failure time, fault location time, fault isolation time, expected value of fault line inspection time and fault recovery time. f for:

[0077] T f =T loc-r +T iso-r +T pat-exp +T rec +t2-t0 (27)

[0078] Where, T loc-r is the fault location time; T iso-r is the fault isolation time; T pat-exp is the expected value of fault line inspection time; T rec is the fault recovery time; t2 is the moment when the distribution network function fails.

[0079] The expected value of the fault line inspection time is specifically calculated by the following formula:

[0080]

[0081] Where k is the segment number of the faulty feeder; N is the total number of segments of the faulty feeder; ΔL kis the length of the kth section of the faulty feeder; L is the length of the faulty feeder; t p It is the feeder inspection time per unit length; and it is stipulated that the failure rate per unit length of each feeder is the same.

[0082] Preferably, in this embodiment, the method for calculating the expected value of the fault line inspection time is as follows:

[0083] Assume that after a feeder fault occurs in the distribution system, the fault location process has determined that the fault occurs in a feeder in the system. Let the length of the feeder be L and the line inspection time per unit length be t p , the failure rate per unit length of each feeder is the same. The differential model of the feeder is established using the differential idea, and the feeder is divided into N small sections, such as Figure 2 Shown

[0084]

[0085]

[0086]

[0087] According to the established feeder differential model, the fault patrol time t within the feeder section is proportional to the patrol distance from the head end of the faulty feeder (it can also be the end of the faulty feeder, which does not affect the fault patrol time) to the fault point, that is, n k is the number of sections from the head end of the faulty feeder to section k;

[0088] Therefore, the expected line inspection time in the entire fault feeder section can be expressed as:

[0089]

[0090] Preferably, in this embodiment, step S5 is specifically:

[0091] a. Use the following formula to calculate the corrected fault location time T loc-exp :

[0092] T loc-exp =(1-P loc-f )*T loc-f +P loc-f *T loc-f (33)

[0093] Where T loc-exp P is the positioning time after automatic positioning fails; loc-f Indicates the probability of failure of positioning function;

[0094] b. Use the following formula to calculate the corrected fault isolation time Tiso-exp :

[0095] T iso-exp =(1-P iso-f )*T iso-f +P iso-f *T iso-f (34)

[0096] Where T iso-f P is the isolation time after automatic isolation fails; iso-f Indicates the probability of failure of the isolation function;

[0097] c. Use the following calculation to calculate the corrected fault recovery time T rec-exp :

[0098]

[0099] Where T ter is the recovery time of the power distribution terminal failure, and

[0100] T rec is the uncorrected fault recovery time;

[0101] d. Use the following formula as an accurate calculation model for the total time of distribution network fault processing:

[0102] (1) When the resilience of the distribution network can resist natural disasters, the total time for power restoration after a disaster considering the resilience of the distribution network is precisely calculated as follows: T f =t1-t0(36);

[0103] (2) When the resilience of the distribution network cannot resist natural disasters, a precise calculation model for the total time of power restoration after a disaster considering the resilience of the distribution network is proposed: T f =T loc-exp +T iso-exp +T pat-exp +T rec-exp +t2-t0(37).

[0104] Embodiment 1:

[0105] In this embodiment, the distribution network related data such as feeder failure rate, feeder length, number of load points and number of users are obtained. When the distribution terminal is not installed, the fault handling time is 3 hours. In this example, when the distribution terminal functions normally, the fault location time T loc-r Take 0.017h, fault isolation time T iso-r Take 0h; positioning time after telemetry failure T loc-f Take 0.1h as the isolation time after remote control failure T iso-f Take 0.5h. Fault recovery time T recTake 0.2h. The telemetry function recovery time t3 of the distribution terminal is 0.15h, the telesignaling function recovery time t4 is 0.2h, and the remote control function recovery time t5 is 0.25h. Read the data related to natural disasters. Typhoon disasters are one of the most frequent and most serious natural disasters in the world. It is a major global problem facing human survival and development today. Taking the actual typhoon data as an example, the coordinates of the typhoon landing position are (-150km, -125km), moving at 45° to the horizontal axis, with a speed of 18m / s and a maximum wind speed radius of 47 kilometers. The distribution network function curve model and typhoon model are established based on historical data. According to the post-disaster power grid restoration time calculation method considering the resilience of the distribution network proposed by the present invention, it can be obtained that this typhoon can be resisted by the resilience of the distribution network, and the restoration time T f =t1-t0=2.397h; Taking the actual typhoon data as an example, the typhoon landing position coordinates are (-120km, -100km), moving at 60° to the horizontal axis, with a speed of 49.5m / s, and a maximum wind speed radius of 120 kilometers. The distribution network function curve model and the typhoon model are established based on historical data. According to the post-disaster power grid restoration time calculation method considering the resilience of the distribution network proposed in the present invention, it can be obtained that this typhoon cannot be resisted by the resilience of the distribution network, and the restoration time of the entire distribution network can be calculated by the following formula: T f =T loc-exp +T iso-exp +T pat-exp +T rec-exp +t2-t0=1.667h.

[0106] The above description is only a preferred embodiment of the present invention. All equivalent changes and modifications made according to the scope of the patent application of the present invention should fall within the scope of the present invention.

Claims

1. A method for predicting power restoration time of a power grid after a disaster considering the resilience of the distribution network, characterized in that: The following steps are involved: Step S1: Obtaining grid data information of the distribution network; Step S2: Based on the power grid data information, the distribution network resilience index described by the integral of the weighted loss of load and the time axis of the distribution network under natural disasters is introduced to construct a distribution network function curve model; the distribution network function curve model takes time as the horizontal coordinate and the load level as the vertical coordinate; Step S3: Obtaining natural disaster related parameters, and establishing a natural disaster model based on the natural disaster related parameters; Step S4: Construct a basic calculation model for the total time of power restoration after a disaster considering the resilience of the distribution network; the details are as follows: When the distribution network resilience can resist natural disasters, the total time T for power grid restoration after a disaster considering the resilience of the distribution network is f The specific basic calculation model T is determined by the natural disaster model and the distribution network function curve model. f for: T f =t1-t0 (4) Among them, t0 is the time when the disaster occurs, and t1 is the time when the distribution network function returns to normal; B. When the resilience of the distribution network cannot resist natural disasters, the total time T for power restoration after a disaster considering the resilience of the distribution network f The specific basic calculation model T is determined by the distribution network resilience failure time, fault location time, fault isolation time, expected value of fault line inspection time and fault recovery time. f for: T f =T loc-r +T iso-r +T pat-exp +T rec +t2-t0 (5) Where, T loc-r is the fault location time; T iso-r is the fault isolation time; T pat-exp is the expected value of fault line inspection time; T rec is the fault recovery time; t0 is the time when the disaster occurs, and t2 is the time when the distribution network function fails; Step S5: Based on the probability prediction theory, the basic calculation model of the total time for power restoration of the power grid after a disaster considering the resilience of the distribution network is corrected to obtain an accurate calculation model for the total time for handling distribution network faults; Step S6: Obtain the grid data information of the post-disaster distribution network, and obtain the post-disaster grid restoration time based on an accurate calculation model of the total time for handling distribution network faults.

2. The method for predicting power restoration time of a power grid after a disaster considering the resilience of the distribution network according to claim 1 is characterized in that: The power grid data information includes the length of the power supply trunk line, the length of the power supply branch line, the average repair time corresponding to the failure rate, the operation time of the isolation switch, the load amount of each load point and the number of power supply users at each load point.

3. The method for predicting power restoration time of a power grid after a disaster considering the resilience of the distribution network according to claim 1 is characterized in that: The natural disaster is a typhoon, and step S3 is specifically as follows: Construct a typhoon static wind field model: Among them, K is an empirical parameter; v m is the maximum wind speed; r mv is the maximum wind speed radius; r s is the radius of the typhoon impact area; β is the typhoon boundary factor, which represents the ratio of the maximum gradient wind speed to the boundary wind speed Construct a typhoon dynamic wind field model. The typhoon dynamic wind field is used to describe the wind field changes after the typhoon lands. It is modeled as a set of static wind fields H. H={h a } a=0,1,…,|H| (2) h a = Γ(h0|α, p h , v h , ΔT a ) (3) where, |·| represents the number of elements in the set, and the same applies hereinafter; h0 is the wind field at the time of typhoon landing; h α is the wind field at time a after typhoon landing, and Γ(·) is a time-varying function of h α with respect to h0; the function Γ(·) can be simulated in combination with the following parameters: typhoon landing attenuation factor α, typhoon movement path p h , typhoon movement speed v h , time ΔT experienced at time a after typhoon landing a .

4. The method for predicting power restoration time of a power grid after a disaster considering the resilience of the distribution network according to claim 1 is characterized in that: The expected value of the fault line inspection time is specifically: Where k is the segment number of the faulty feeder; N is the total number of segments of the faulty feeder; ΔL k is the length of the kth section of the faulty feeder; L is the length of the faulty feeder; t p It is the feeder inspection time per unit length; and it is stipulated that the failure rate per unit length of each feeder is the same.

5. A method for predicting power restoration time of a power grid after a disaster considering the resilience of the distribution network according to claim 1, characterized in that: Step S5 is based on the probability prediction theory to modify the basic calculation model of the total time for power restoration of the power grid after a disaster based on the resilience of the distribution network, so that the original model is updated in real time according to the probability of possible failure of the distribution network, thereby realizing the prediction of the power restoration time of the power grid after a disaster considering the resilience of the distribution network, specifically: a. Use the following formula to calculate the corrected fault location time T loc-exp : T loc-exp =(1-P loc-f )*T loc-f +P loc-f *T loc-f (7) Where T loc-exp P is the positioning time after automatic positioning fails; loc-f Indicates the probability of failure of positioning function; b. Use the following formula to calculate the corrected fault isolation time T iso-exp : T iso-exp =(1-P iso-f )*T iso-f +P iso-f *T iso-f (8) Where T iso-f P is the isolation time after automatic isolation fails; iso-f Indicates the probability of failure of the isolation function; c. Use the following calculation to calculate the corrected fault recovery time T rec-exp : Where T ter is the recovery time of the power distribution terminal failure, and T rec is the uncorrected fault recovery time; d. Construct an accurate calculation model for the total time of distribution network fault processing: (1) When the resilience of the distribution network can resist natural disasters, the total time for power restoration after a disaster is accurately calculated by considering the resilience of the distribution network: T f =t1-t0 (10); (2) When the resilience of the distribution network cannot resist natural disasters, a precise calculation model for the total time of power restoration after a disaster considering the resilience of the distribution network is proposed: T f =T loc-exp +T iso-exp +T pat-exp +T rec-exp +t2-t0 (11)。

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