A Method and System for Calculating the Available Transfer Capability of a Power Grid Based on the Mode

Abstract

The present invention belongs to the technical field of power automation, and discloses a method, device, equipment and medium for calculating the available transmission capacity of a power grid based on the mode; the method includes: obtaining the actual active power output values of a wind farm in the previous n time periods; determining the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment according to the actual active power output values of the wind farm in the previous n time periods; substituting the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment into the calculation model of the available transmission capacity of a large power grid considering the wind power prediction error interval to obtain the calculation result of the available transmission capacity; and outputting the calculation result of the available transmission capacity. The present invention accurately quantifies and analyzes the impact of wind power prediction error on the available transmission capacity, and is closest to the actual situation to the greatest extent; obtains the calculation result of the available transmission capacity, improves the accuracy of calculating the available transmission capacity of a new power system, and ensures the safety of the power grid.

Description

Technical Field

[0001] The present invention belongs to the technical field of power automation, and particularly relates to a method and system for calculating the available transmission capacity of a power grid based on the mode. Background Art

[0002] With the increasing installed capacity of new energy wind turbine units, the proportion of wind power in the power system is increasing; the randomness and volatility of wind power output cause inevitable certain errors in prediction, which have a certain impact on the calculation results of the available transmission capacity of the power system, and further affect the safe operation of the power grid. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and system for calculating the available transmission capacity of a power grid based on the mode, which can accurately quantify and analyze the impact of wind power prediction errors on the available transmission capacity, be closest to the actual situation to the greatest extent, improve the accuracy of calculating the available transmission capacity of the power system, and ensure the safety of the power grid.

[0004] To achieve the above purpose, the present invention adopts the following technical solutions:

[0005] In a first aspect, the present invention provides a method for calculating the available transmission capacity of a power grid based on the mode, including:

[0006] Obtaining the actual active power output values of the wind farm in the previous n time periods; determining the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment according to the actual active power output values of the wind farm in the previous n time periods;

[0007] Substituting the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment into the calculation model of the available transmission capacity of the large power grid considering the wind power prediction error range to obtain the calculation result of the available transmission capacity;

[0008] Outputting the calculation result of the available transmission capacity.

[0009] A further improvement of the present invention lies in that: the step of obtaining the actual active power output values of the wind farm in the previous n time periods; determining the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment according to the actual active power output values of the wind farm in the previous n time periods specifically includes:

[0010] Obtaining the actual active power output values of the wind farm in the previous n time periods \(X=\{x_1,x_2,\cdots,x\) n-1 ,x n \}\);

[0011] Calculating the linear correlation between \(X\) and \(Y\):

[0012]

[0013] Among them, Y = {y1, y2,..., y n-1 , y n} is the actual active power output value of the wind farm in n historical periods; according to the linear correlation between X and Y, select the Y related to X; for the Y related to X, if the n + 1th moment of Y is a positive error, record it as e, and if it is a negative error, record it as w;

[0014] E = {e1, e2, e3,..., e h} is the vector composed of the predicted positive errors at the n + 1th moment in the historical Y related to X. The mode of the positive error vector is:

[0015] M o,h = ξ h - 3(ξ h - M d,h ) (2)

[0016] ξ h is the mean value of h elements in E, and M d,h is the median in E = {e1, e2, e3,..., e h};

[0017] The upper limit P G,lmt2 of the wind power prediction error = x n+1 + M o,h

[0018] W = {w1, w2, w3,..., w l} is the vector composed of the predicted negative errors at the n + 1th moment in the historical Y related to X. The mode of the negative error vector is:

[0019] M o,l = ξ l - 3(ξ l - M d,l ) (3)

[0020] ξ l is the mean value of l elements in W, and M d,l is the median in W = {w1, w2, w3,..., w l};

[0021] The lower limit P G,lmt1 of the wind power prediction error = x n+1 - M o,l .

[0022] A further improvement of the present invention is that when ρ XY ≥ 0.8, it is considered that X and Y are linearly correlated.

[0023] A further improvement of the present invention lies in that: the calculation model of the available transfer capability of the large power grid considering the wind power prediction error range is specifically as follows:

[0024] max:-B ij (f i (P G )+S i (P L )-f j (P G )-S j (P L ))

[0025] s.t.

[0026]

[0027] Wherein:

[0028] B ij : The susceptance of branch ij;

[0029] f i : The linear function corresponding to the generator output in the row corresponding to θ in the matrix (B'); -1 corresponding to θ i in the row of the matrix (B');

[0030] S i : The element of the linear function corresponding to the load in the row corresponding to θ in the matrix (B'); -1 corresponding to θ i in the row of the matrix (B');

[0031] B': Composed of the negative value of the reciprocal of the branch impedance, per unit value;

[0032] θ: The radian value of the node phase angle;

[0033] P L : The active power vector of the node load;

[0034] P G : The active power vector of the node generation;

[0035] P ij,lmt : The active power limit of branch ij;

[0036] K ij,max is S i (P G,W,lmt1 )-f j (P G,W,lmt1 )、S i (P G,W,lmt1 )-f j (P G,W,lmt2 )、S i (P G,W,lmt2 )-f j (P G,W,lmt1) and S i (P G,W,lmt2 ) - f j (P G,W,lmt2 ) the maximum value in;

[0037] P G,W,lmt1 : the lower limit vector of the active power prediction of the node wind power generation;

[0038] P G,W,lmt2 : the upper limit vector of the active power prediction of the node wind power generation;

[0039] P S,LMT : the maximum network loss;

[0040] Calculate the available transmission capacity of the target branch ij considering the wind power prediction error according to Equation (5).

[0041] Second, the present invention provides a method for calculating the available transmission capacity of the power grid based on the mode, including the following steps:

[0042] Set all wind power prediction errors to zero, calculate the available transmission capacity of the target end face of the power system, and obtain the first available transmission value of the target end face;

[0043] Set all wind power prediction errors to the preset limit value, calculate the available transmission capacity of the target end face of the power system, and obtain the second available transmission value of the target end face;

[0044] Calculate the difference between the first available transmission value of the target end face and the second available transmission value of the target end face. If the difference is greater than the preset threshold, perform the following steps:

[0045] Obtain the actual active power output values of the wind farm in the previous n time periods; according to the actual active power output values of the wind farm in the previous n time periods, determine the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)th moment;

[0046] Substitute the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)th moment into the calculation model of the available transmission capacity of the large power grid considering the wind power prediction error interval to obtain the calculation result of the available transmission capacity;

[0047] Output the calculation result of the available transmission capacity.

[0048] A further improvement of the present invention lies in: the step of obtaining the actual active power output values of the wind farm in the previous n time periods; according to the actual active power output values of the wind farm in the previous n time periods, determining the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)th moment specifically includes:

[0049] Obtain the actual active power output values of the wind farm in the previous n time periods X = {x1, x2,..., x n-1 , x n};

[0050] Calculate the linear correlation between X and Y:

[0051]

[0052] where Y = {y1, y2,..., y n-1 , y n} is the actual active power output value of the wind farm in n historical periods; screen Y related to X according to the linear correlation between X and Y; for Y related to X, if the error at the (n + 1)-th moment of Y is positive, record it as e, and if it is negative, record it as w;

[0053] E = {e1, e2, e3,..., e h} is the vector composed of the predicted positive errors at the (n + 1)-th moment in the historical Y related to X, and the mode of the positive error vector is:

[0054] M o,h = ξ h - 3(ξ h - M d,h ) (2)

[0055] ξ h is the mean value of h elements in E, and M d,h is the median in E = {e1, e2, e3,..., e h};

[0056] The upper limit of wind power prediction error P G,lmt2 = x n+1 + M o,h

[0057] W = {w1, w2, w3,..., w l} is the vector composed of the predicted negative errors at the (n + 1)-th moment in the historical Y related to X, and the mode of the negative error vector is:

[0058] M o,l = ξ l - 3(ξ l - M d,l ) (3)

[0059] ξ l is the mean value of l elements in W, and M d,l is the median in W = {w1, w2, w3,..., w l};

[0060] The lower limit of wind power prediction error P G,lmt1 = x n+1 - M o,l .

[0061] A further improvement of the present invention lies in that: the calculation model of the available transfer capability of a large power grid considering the wind power prediction error range is specifically as follows:

[0062] max:-B ij (f i (P G )+S i (P L )-f j (P G )-S j (P L ))

[0063] s.t.

[0064]

[0065] Wherein:

[0066] B ij : The susceptance of branch ij;

[0067] f i : The linear function corresponding to the generator output in the row corresponding to θ in the matrix (B'); -1 corresponding to θ i in the row of the matrix (B');

[0068] S i : The linear function element corresponding to the load in the row corresponding to θ in the matrix (B'); -1 corresponding to θ i in the row of the matrix (B');

[0069] B': Composed of the negative values of the reciprocals of the branch impedances, per-unit value;

[0070] θ: The radian value of the node phase angle;

[0071] P L : The active power vector of the node load;

[0072] P G : The active power vector of the node generation;

[0073] P ij,lmt : The active power limit of branch ij;

[0074] K ij,max is S i (P G,W,lmt1 )-f j (P G,W,lmt1 )、S i (P G,W,lmt1 )-f j (P G,W,lmt2 )、S i (P G,W,lmt2 )-f j (P G,W,lmt1) and S i (P G,W,lmt2 ) - f j (P G,W,lmt2 ) the maximum value in;

[0075] P G,W,lmt1 : the lower limit vector of the active power prediction of node wind power generation;

[0076] P G,W,lmt2 : the upper limit vector of the active power prediction of node wind power generation;

[0077] P S,LMT : the maximum value of network loss;

[0078] Calculate the available transfer capacity of the target branch ij considering the wind power prediction error according to Equation (5).

[0079] Thirdly, the present invention provides a device for calculating the available transfer capacity of a power grid based on the mode, including:

[0080] An error calculation module, configured to obtain the actual active power output values of the wind farm in the previous n time periods; determine the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment according to the actual active power output values of the wind farm in the previous n time periods;

[0081] A transfer capacity calculation module, configured to substitute the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment into the calculation model of the available transfer capacity of the large power grid considering the wind power prediction error interval to obtain the calculation result of the available transfer capacity;

[0082] An output module, configured to output the calculation result of the available transfer capacity.

[0083] A further improvement of the present invention lies in: in the error calculation module, the steps of obtaining the actual active power output values of the wind farm in the previous n time periods; determining the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment according to the actual active power output values of the wind farm in the previous n time periods specifically include:

[0084] Obtain the actual active power output values X = {x1, x2,..., x n-1 , x n} of the wind farm in the previous n time periods;

[0085] Calculate the linear correlation between X and Y:

[0086]

[0087] where Y = {y1, y2,..., y n-1 , y n} is the actual active power output value in n time periods of the wind farm history; screen Y related to X according to the linear correlation between X and Y; for Y related to X, if the error at the (n + 1)-th moment of Y is positive, record it as e, and if the error is negative, record it as w;

[0088] E = {e1, e2, e3,..., e h} is the vector composed of the predicted positive errors at the (n + 1)-th moment in the historical Y related to X, and the mode of the positive error vector is:

[0089] M o,h = ξ h - 3(ξ h - M d,h ) (2)

[0090] ξ h is the mean value of h elements in E, and M d,h is the median in E = {e1, e2, e3,..., e h};

[0091] The upper limit P of the wind power prediction error G,lmt2 = x n+1 + M o,h

[0092] W = {w1, w2, w3,..., w l} is the vector composed of the predicted negative errors at the (n + 1)-th moment in the historical Y related to X, and the mode of the negative error vector is:

[0093] M o,l = ξ l - 3(ξ l - M d,l ) (3)

[0094] ξ l is the mean value of l elements in W, and M d,l is the median in W = {w1, w2, w3,..., w l};

[0095] The lower limit P of the wind power prediction error G,lmt1 = x n+1 - M o,l ;

[0096] The calculation model of the available transfer capability of the large power grid considering the wind power prediction error interval is specifically:

[0097] max: - B ij (f i (P G ) + S i (P L ) - f j (PG ) - S j (P L ))

[0098] s.t.

[0099]

[0100] where:

[0101] B ij : susceptance of branch ij;

[0102] f i : linear function corresponding to the generator output in the row of matrix (B') -1 corresponding to θ i in the row;

[0103] S i : elements of the linear function corresponding to the load in the row of matrix (B') -1 corresponding to θ i in the row;

[0104] B': composed of the negative reciprocal of the branch impedance, per-unit value;

[0105] θ: radian value of the node phase angle;

[0106] P L : active power vector of node load;

[0107] P G : active power vector of node generation;

[0108] P ij,lmt : active power limit of branch ij;

[0109] K ij,max is the maximum value among S i (P G,W,lmt1 ) - f j (P G,W,lmt1 ), S i (P G,W,lmt1 ) - f j (P G,W,lmt2 ), S i (P G,W,lmt2 ) - f j (P G,W,lmt1 ) and S i (P G,W,lmt2 ) - f j (P G,W,lmt2 );

[0110] P G,W,lmt1 : lower limit vector of predicted active power of wind power generation at nodes;

[0111] P G,W,lmt2: upper limit vector of active power prediction for node wind power generation;

[0112] P S,LMT : maximum network loss;

[0113] Calculate the available transfer capability of the target branch ij considering the wind power prediction error according to Equation (5).

[0114] Fourthly, the present invention provides an electronic device, including a processor and a memory. The processor is used to execute a computer program stored in the memory to implement the above-mentioned method for calculating the available transfer capability of a power grid based on the mode.

[0115] Fifthly, the present invention provides a computer-readable storage medium. The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, it implements the above-mentioned method for calculating the available transfer capability of a power grid based on the mode.

[0116] Compared with the prior art, the present invention has the following beneficial effects:

[0117] The present invention provides a method and system for calculating the available transfer capability of a power grid based on the mode. Aiming at the problem that the randomness and volatility of the high proportion of wind power output in the new power system cause inevitable certain errors in prediction, which have a certain impact on the calculation result of the available transfer capability of the power system. First, obtain the actual active power output values of the wind farm in the previous n time periods; according to the actual active power output values of the wind farm in the previous n time periods, determine the upper limit and lower limit of the wind power prediction error of the wind farm at the n + 1 moment, accurately quantify and analyze the impact of the wind power prediction error on the available transfer capability, and be closest to the actual situation to the greatest extent; then substitute the upper limit and lower limit of the wind power prediction error of the wind farm at the n + 1 moment into the large power grid transfer capability calculation model considering the wind power prediction error interval to obtain the calculation result of the available transfer capability, improve the accuracy of the available transfer capability calculation of the new power system, ensure the safety of the power grid, and support the operation of the power market.

[0118] The application prospects of the present invention: (1) It can be applied to the provincial and local intelligent power grid dispatching and control systems; (2) It can be applied to the engineering implementation of the regulation cloud platform; (3) It can be applied to the engineering implementation of the new generation dispatching control system; (4) It can provide basic services for the safe operation of power grids rich in new energy resources.

[0119] In summary, the present invention has good promotion and application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0120] The accompanying drawings forming a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0121] Figure 1 It is a schematic flow chart of a method for calculating the available transmission capacity of a power grid based on the mode according to the present invention;

[0122] Figure 2 It is a schematic flow chart of another method for calculating the available transmission capacity of a power grid based on the mode according to the present invention;

[0123] Figure 3 It is a structural block diagram of a device for calculating the available transmission capacity of a power grid based on the mode according to the present invention;

[0124] Figure 4 It is a structural block diagram of an electronic device according to the present invention. Detailed implementation manners

[0125] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments. It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments may be combined with each other.

[0126] The following detailed descriptions are all exemplary descriptions, aiming to provide further detailed descriptions of the present invention. Unless otherwise specified, all technical terms adopted by the present invention have the same meaning as commonly understood by those of ordinary skill in the art to which the present invention pertains. The terms used in the present invention are only for describing specific implementation manners and are not intended to limit the exemplary embodiments according to the present invention.

[0127] Explanation of technical terms:

[0128] (1) Available transfer capability (ATC) refers to the remaining transmission capacity in the actual physical power transmission network that can be used commercially based on the existing transmission contracts. This definition shows that under the market environment, the power transmission capacity problem of the power grid is no longer simply the power exchange capacity between regions in the original sense, but the maximum additional transmission power that may be increased between regions or point-to-points under the condition of ensuring the safe and reliable operation of the system based on the existing transmission contracts.

[0129] (2) Mode: It refers to the value with an obvious central tendency point in the statistical distribution, representing the general level of the data. It is also the value that appears most frequently in a set of data. Sometimes there are several modes in a set of numbers.

[0130] (3) Pearson correlation coefficient: In statistics, also known as Pearson product-moment correlation coefficient (abbreviated as PPMCC or PCCs), it is used to measure the correlation (linear correlation) between two variables X and Y, and its value ranges from -1 to 1.

[0131] (4) Network congestion risk: Congestion means that the requirements for power transmission are greater than the actual physical transmission capacity of the power grid. According to the location where congestion occurs, it can be divided into internal regional transmission congestion and inter-regional transmission congestion.

[0132] According to the error between the predicted value and the actual value of the wind power output in the recent 96 points, the present invention calculates the correlation of the historical error of the wind power output prediction corresponding to the 96-point data by using the Pearson coefficient, selects the historical records with high correlation, statistically calculates the positive error and the negative error according to the error distribution of the historical prediction at the next moment for these historical records, and calculates the mode of the positive error and the negative error as the upper and lower limits of the wind power output prediction error at the next moment, and substitutes them into the calculation model of the available transmission capacity of the large power grid considering the wind power prediction error interval to obtain the available transmission capacity of the large power grid considering the wind power prediction error interval.

[0133] Embodiment 1

[0134] Please refer to Figure 1 as shown, the present invention provides a method for calculating the available transmission capacity of a power grid based on the mode, including:

[0135] S1. Obtain the actual active power output values of the wind farm in the previous n time periods; according to the actual active power output values of the wind farm in the previous n time periods, determine the upper limit and the lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment;

[0136] S2. Substitute the upper limit and the lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment into the calculation model of the available transmission capacity of the large power grid considering the wind power prediction error interval to obtain the calculation result of the available transmission capacity;

[0137] S3. Output the calculation result of the available transmission capacity.

[0138] In a specific embodiment: the step of obtaining the actual active power output values of the wind farm in the previous n time periods; according to the actual active power output values of the wind farm in the previous n time periods, determining the upper limit and the lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment specifically includes:

[0139] Obtain the actual active power output values X = {x1, x2,..., x n-1 , x n} of the wind farm for the first n time periods;

[0140] Calculate the linear correlation between X and Y:

[0141]

[0142] where Y = {y1, y2,..., y n-1 , y n} are the actual active power output values of the wind farm for the historical n time periods; Screen Y related to X according to the linear correlation between X and Y (when ρ XY ≥0.8, it is considered that X and Y are linearly correlated); For Y related to X, if the n + 1th moment of Y is a positive error, record it as e, and if it is a negative error, record it as w;

[0143] E = {e1, e2, e3,..., e h} is the vector composed of the predicted positive errors at the n + 1th moment in the historical Y related to X, and the mode of the positive error vector is:

[0144] M o,h = ξ h - 3(ξ h - M d,h ) (2)

[0145] ξ h is the mean of h elements in E, and M d,h is the median in E = {e1, e2, e3,..., e h};

[0146] The upper limit P G,lmt2 of the wind power prediction error = x n+1 + M o,h

[0147] W = {w1, w2, w3,..., w l} is the vector composed of the predicted negative errors at the n + 1th moment in the historical Y related to X, and the mode of the negative error vector is:

[0148] M o,l = ξ l - 3(ξ l - M d,l ) (3)

[0149] ξ l is the mean of l elements in W, and M d,l is the median in W = {w1, w2, w3,..., w l};

[0150] Lower limit P of wind power prediction error G,lmt1 = x n+1 - M o,l .

[0151] In a specific embodiment: One sampling point is taken every 15 minutes, and n = 96, representing the sampling data of one day.

[0152] In a specific embodiment: The calculation model of the available transfer capability of a large power grid considering the wind power prediction error interval is specifically:[[]]

[0153] max: - B ij (f i (P G ) + S i (P L ) - f j (P G ) - S j (P L ))

[0154] s.t.

[0155]

[0156] Wherein:

[0157] B ij : The susceptance of branch ij;

[0158] f i : The linear function corresponding to the generator output in the row corresponding to θ in the matrix (B'); -1 in i one row corresponding to the generator output;

[0159] S i : The element of the linear function corresponding to the load in the row corresponding to θ in the matrix (B'); -1 in i one row corresponding to the load;

[0160] B': Composed of the negative reciprocal of the branch impedance, per unit value;

[0161] θ: The radian value of the node phase angle;

[0162] P L : The active power vector of the node load;

[0163] P G : The active power vector of the node generation;

[0164] P ij,lmt : The active power limit of branch ij;

[0165] K ij,max is S i (P G,W,lmt1 ) - f j(P G,W,lmt1 ), S i (P G,W,lmt1 )-f j (P G,W,lmt2 ), S i (P G,W,lmt2 )-f j (P G,W,lmt1 ) and S i (P G,W,lmt2 )-f j (P G,W,lmt2 )

[0166] P G,W,lmt1 : node wind power generation active power prediction lower limit vector;

[0167] P G,W,lmt2 : upper limit vector of the node wind power active power prediction;

[0168] P S,LMT : Maximum network loss;

[0169] The available transmission capacity of the target branch ij considering the wind power prediction error is calculated according to formula (5).

[0170] Based on the real-time operation status of the power grid and the prediction results of wind power output, the present invention takes into account a certain prediction error of wind power and obtains a power grid network congestion risk that is close to the actual situation; based on the historical correlation of wind power output, the upper and lower limits of the error of wind farm output are obtained using the mode theory. It has statistical information of a large amount of historical data, is relatively close to the actual situation, and has good practicality.

[0171] Example 2

[0172] See also Figure 2 As shown, the present invention provides a method for calculating the available transmission capacity of a power grid based on a mode, comprising:

[0173] Set all wind power prediction errors to zero, calculate the target end-face available transmission capacity of the power system, and obtain the first target end-face available transmission value;

[0174] Setting all wind power prediction errors to preset limit values, calculating the target end-face available transmission capacity of the power system, and obtaining the target end-face second available transmission value;

[0175] Calculate the difference between the first available power transmission value of the target end face and the second available power transmission value of the target end face. If the difference is greater than a preset threshold, perform the following steps:

[0176] Obtaining the actual active power output values of the wind farm in the previous n time periods; determining the upper limit and lower limit of the wind power prediction error of the wind farm at time n+1 based on the actual active power output values of the wind farm in the previous n time periods;

[0177] Substitute the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment into the calculation model of the available transfer capability of the large power grid considering the wind power prediction error interval to obtain the calculation result of the available transfer capability;

[0178] Output the calculation result of the available transfer capability

[0179] In a specific embodiment, the wind power prediction error interval based on the mode is obtained through the following steps:

[0180] Assume that the current moment is the n-th moment, and let X = {x1, x2,..., x n-1 , x n} be the actual active power output values of a certain wind farm in the previous n periods (in a specific embodiment, n can be 96), x n+1 be the predicted value of the active power output at the next moment (n + 1). It is necessary to determine the upper limit and lower limit of the error of the predicted value of the wind power output at the (n + 1)-th moment. Let Y = {y1, y2,..., y n-1 , y n} be the actual active power output values of the wind farm in the historical n periods (in a specific embodiment, Y is the historical actual active power output values corresponding to X in the n periods). According to the Pearson formula, the linear correlation between X and Y is:

[0181]

[0182] Select Y related to X according to the linear correlation between X and Y (when ρ XY ≥0.8, it is considered that X and Y are linearly correlated); for Y related to X, if the error at the (n + 1)-th moment of Y is positive, it is recorded as e, and if it is negative, it is recorded as w.

[0183] Let E = {e1, e2, e3,..., e h} be the vector composed of the positive prediction errors at the (n + 1)-th moment in the historical Y related to X, and h be the number of positive errors. Then the mode of the positive error vector is:

[0184] M o,h = ξ h - 3(ξ h - M d,h ) (2)

[0185] ξ h is the mean value of the h elements in E, and M d,h is the median in E = {e1, e2, e3,..., e h}.

[0186] P G,lmt2 : Upper limit of wind power prediction error;

[0187] Let \(W = \{w_1, w_2, w_3, \cdots, w\) l \} be the vector composed of the predicted negative errors at the \((n + 1)\)-th moment in the historical \(Y\) related to \(X\). Let \(l\) be the number of positive errors. Then the mode of the negative error vector is:

[0188] \(M\) o,l = \xi l - 3(\xi l - M d,l ) (3)

[0189] \(\xi\) l is the mean of the \(l\) elements in \(W\), and \(M\) d,l is the median of \(W=\{w_1, w_2, w_3, \cdots, w\) l \}\).

[0190] The upper limit \(P\) of the wind power prediction error G,lmt2 = x n+1 + M o,h ;

[0191] The lower limit \(P\) of the wind power prediction error G,lmt1 = x n+1 - M o,l .

[0192] DC power flow mathematical model:

[0193] \(P = B'\theta\)

[0194] \(\theta=(B')\) -1 \(P\)

[0195] \(\theta\) i = f i (P G ) + S i (P L )

[0196] \(P\) ij = - B ij (\(\theta\) i - \(\theta\) j ) = - B ij (f i (P G ) + S i (P L ) - f j (P G ) - S j (P L ))

[0197] Where:

[0198] \(P\): Active power injected at the node, positive for the generator, negative for the load, and 0 for the zero-injection node, in per-unit value;

[0199] B': Composed of the negative values of the reciprocals of the branch impedances, in per-unit value;

[0200] θ: The radian value of the node phase angle, excluding the slack node, which is 0 for the slack node;

[0201] f i : The matrix (B') -1 corresponding to θ i in the row corresponding to the linear function of the generator output;

[0202] S i : The matrix (B') -1 corresponding to θ i in the row corresponding to the linear function element of the load;

[0203] P ij : The power of branch ij;

[0204] B ij : The susceptance of branch ij;

[0205] P L : The active power vector of the node load;

[0206] P G : The active power vector of the node generation.

[0207] Calculation model for the available transfer capability of a large power grid considering the wind power prediction error interval:

[0208] Among them, the calculation model and constraint conditions for the available transfer capability of branch ij considering the wind power prediction error interval are shown in Equation (4):

[0209] max: -B ij (f i (P G )) + S i (P L ) - f j (P G ) - S j (P L ))

[0210] s.t.

[0211]

[0212] Among them:

[0213] P L : The active power vector of the node load;

[0214] P G : The active power vector of the node generation, which is a variable of this model;

[0215] P G,lmt1 : The lower limit of the wind power prediction error;

[0216] P G,lmt2 : Upper limit of wind power prediction error;

[0217] P G,W,lmt1 : Lower limit vector of active power prediction of wind power generation at nodes;

[0218] P G,W,lmt2 : Upper limit vector of active power prediction of wind power generation at nodes;

[0219] P ij,lmt : Active power limit of branch ij;

[0220] P S,LMT : Maximum network loss;

[0221] Formula (5) can be derived from formula (4):

[0222] max:-B ij (f i (P G )+S i (P L )-f j (P G )-S j (P L ))

[0223] s.t.

[0224]

[0225] where K ij,max is the maximum value among S i (P G,W,lmt1 )-f j (P G,W,lmt1 ), S i (P G,W,lmt1 )-f j (P G,W,lmt2 ), S i (P G,W,lmt2 )-f j (P G,W,lmt1 ) and S i (P G,W,lmt2 )-f j (P G,W,lmt2 ). Therefore, given the upper and lower limits of the prediction errors of each wind turbine, the available transfer capacity of the target branch considering the wind power prediction error can be calculated according to formula (5). The advantage of formula (5) is that it can take into account the upper and lower limits of the prediction errors of the wind power values, and without increasing the number of constraint conditions, the calculation amount is the same as when the wind power prediction value of the wind turbine is taken as a fixed value.

[0226] In a specific embodiment, after calculating the available transmission capacity of the target branch, in actual production, if there is a demand, the adjustment amount of the unit of the target branch is adjusted according to the calculated available transmission capacity to meet the demand.

[0227] Embodiment 3

[0228] Please refer to Figure 3 As shown, the present invention provides a calculation device for the available transmission capacity of a power grid based on the mode, including:

[0229] An error calculation module, configured to obtain the actual active power output values of the wind farm in the previous n time periods; according to the actual active power output values of the wind farm in the previous n time periods, determine the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment;

[0230] A transmission capacity calculation module, configured to substitute the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment into the calculation model of the available transmission capacity of the large power grid considering the wind power prediction error interval to obtain the calculation result of the available transmission capacity;

[0231] An output module, configured to output the calculation result of the available transmission capacity.

[0232] In a specific embodiment, in the error calculation module, the steps of obtaining the actual active power output values of the wind farm in the previous n time periods; and according to the actual active power output values of the wind farm in the previous n time periods, determining the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment specifically include:

[0233] Obtain the actual active power output values X = {x1, x2,..., x n-1 , x n} of the wind farm in the previous n time periods;

[0234] Calculate the linear correlation between X and Y:

[0235]

[0236] where Y = {y1, y2,..., y n-1 , y n} is the actual active power output values of the wind farm in the previous n historical time periods; according to the linear correlation between X and Y, screen the Y related to X (when ρ XY ≥0.8, it is considered that X and Y are linearly correlated). For the Y related to X, if the (n + 1)-th moment of Y is a positive error, record it as e, and for a negative error, record it as w;

[0237] E = {e1, e2, e3,..., e h} is the vector composed of the predicted positive errors at the (n + 1)-th moment in the historical Y related to X, and the mode of the positive error vector is:

[0238] M o,h = ξ h - 3(ξ h - M d,h )(2)

[0239] ξ h is the mean of h elements in E, and M d,h is the median in E = {e1, e2, e3,..., e h};

[0240] The upper limit P of wind power prediction error G,lmt2 = x n+1 + M o,h

[0241] W = {w1, w2, w3,..., w l} is the vector composed of the negative prediction errors at the (n + 1)-th moment in the historical Y related to X. The mode of the negative error vector is:

[0242] M o,l = ξ l - 3(ξ l - M d,l )(3)

[0243] ξ l is the mean of l elements in W, and M d,l is the median in W = {w1, w2, w3,..., w l};

[0244] The lower limit P of wind power prediction error G,lmt1 = x n+1 - M o,l ;

[0245] The calculation model of the available transfer capability of large power grids considering the wind power prediction error interval is specifically:

[0246] max: - B ij (f i (P G ) + S i (P L ) - f j (P G ) - S j (P L ))

[0247] s.t.

[0248]

[0249] Where:

[0250] B ij : The susceptance of branch ij;

[0251] f i : the matrix (B') -1 corresponding to θ i a linear function of the unit output corresponding to one row;

[0252] S i : the matrix (B') -1 corresponding to θ i an element of a linear function of the load corresponding to one row;

[0253] B': composed of the negative values of the reciprocals of the branch impedances, in per-unit value;

[0254] θ: the radian value of the node phase angle;

[0255] P L : the active power vector of the node load;

[0256] P G : the active power vector of the node power generation;

[0257] P ij,lmt : the active power limit of branch ij;

[0258] K ij,max is S i (P G,W,lmt1 ) - f j (P G,W,lmt1 )、S i (P G,W,lmt1 ) - f j (P G,W,lmt2 )、S i (P G,W,lmt2 ) - f j (P G,W,lmt1 ) and S i (P G,W,lmt2 ) - f j (P G,W,lmt2 ) the maximum value in;

[0259] P G,W,lmt1 : the lower limit vector of the predicted active power of wind power generation at the node;

[0260] P G,W,lmt2 : the upper limit vector of the predicted active power of wind power generation at the node;

[0261] P S,LMT : the maximum value of network loss;

[0262] Calculate the available transfer capability of the target branch ij considering the wind power prediction error according to Equation (5).

[0263] Example 4

[0264] Please refer to Figure 4As shown, the present invention also provides an electronic device 100 for implementing a method for calculating the available transmission capacity of a power grid based on the mode; the electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on the at least one processor 102, and at least one communication bus 104.

[0265] The memory 101 can be used to store the computer program 103. The processor 102 realizes the method steps of a method for calculating the available transmission capacity of a power grid based on the mode according to any one of Embodiments 1 to 2 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101. The memory 101 mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.); the data storage area can store data created according to the use of the electronic device 100 (such as audio data, etc.). In addition, the memory 101 can include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices.

[0266] The at least one processor 102 can be a Central Processing Unit (CPU), or can also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 102 can be a microprocessor or the processor 102 can also be any conventional processor, etc. The processor 102 is the control center of the electronic device 100, and connects various parts of the entire electronic device 100 through various interfaces and lines.

[0267] The memory 101 in the electronic device 100 stores multiple instructions to implement a method for calculating the available transmission capacity of a power grid based on the mode, and the processor 102 can execute the multiple instructions to thereby implement:

[0268] Obtain the actual active power output values of the wind farm in the previous n time periods; determine the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment according to the actual active power output values of the wind farm in the previous n time periods;

[0269] Substitute the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment into the large power grid available transfer capability calculation model considering the wind power prediction error interval to obtain the available transfer capability calculation result;

[0270] Output the available transfer capability calculation result.

[0271] Embodiment 5

[0272] If the modules / units integrated in the electronic device 100 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above embodiment methods of the present invention, it can also be completed by a computer program instructing relevant hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the above various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, and read-only memory (ROM, Read-Only Memory).

[0273] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0274] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, and the combination of processes and / or blocks in the flowcharts and / or block diagrams can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate for realizing the processesFigure 1 one process or multiple processes and / or blocks Figure 1 means for the functions specified in one block or multiple blocks.

[0275] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including instruction means that implement the functions in the process Figure 1 one process or multiple processes and / or blocks Figure 1 specified in one block or multiple blocks.

[0276] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in the process Figure 1 one process or multiple processes and / or blocks Figure 1 specified in one block or multiple blocks.

[0277] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: the specific implementation manners of the present invention can still be modified or equivalently replaced, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. A method for calculating the available transfer capability of a power grid based on the mode, characterized in that, Including: Obtain the actual active power output values of the wind farm for the previous n time periods; According to the actual active power output values of the wind farm for the previous n time periods, determine the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment; Substitute the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment into the calculation model of the available transmission capacity of the large power grid considering the wind power prediction error interval to obtain the calculation result of the available transmission capacity; Output the calculation result of the available transmission capacity; The step of obtaining the actual active power output values of the wind farm for the previous n time periods; The steps of determining the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment according to the actual active power output values of the wind farm for the previous n time periods specifically include: Obtain the actual active power output values of the wind farm in the first n time periods ; Calculate the linear correlation between X and Y: (1) Among them, is the actual active power output value of the wind farm in n time periods of the historical data; according to the linear correlation between X and Y, the Y related to X is screened; for the Y related to X, if the error at the (n + 1)-th moment of Y is positive, it is recorded as e, and if the error is negative, it is recorded as w. is a vector composed of predicted positive errors at the (n + 1)-th moment in the historical Y related to X. The mode of the positive error vector is: (2) is the mean of h elements in E, and is the median in Upper limit of wind power prediction error = + ; is a vector composed of predicted negative errors at the (n + 1)-th moment in the historical Y related to X, and the mode of the negative error vector is: (3) is the mean of l elements in W, and is the median in Lower limit of wind power prediction error - 。 2. The method for calculating the available transmission capacity of a power grid based on the mode according to claim 1, wherein The calculation model of the available transmission capacity of the large power grid considering the wind power prediction error interval is specifically: （5） Where: : branch ij susceptance; : Matrix corresponding to a linear function of the unit output corresponding to a row : Matrix corresponding to the elements of the linear function of the corresponding load in a row; : Composed of the negative values of the reciprocals of the branch impedances, per-unit value; : The radian value of the node phase angle; : Active power vector of node load; : Active power vector of node power generation; : Active power limit of branch ij; is 、 、 and the maximum value among; : Lower limit vector of active power prediction for node wind power generation; : Upper limit vector of active power prediction for node wind power generation; : Maximum network loss; Calculate the target branch considering the wind power prediction error according to Equation (5). ij Available transfer capability.

3. A method for calculating the available transfer capability of a power grid based on the mode, characterized in that, Including the following steps: Set all wind power prediction errors to zero, calculate the available transmission capacity of the target end face of the power system, and obtain the first available transmission value of the target end face; Set all wind power prediction errors to the preset limit value, calculate the available transmission capacity of the target end face of the power system, and obtain the second available transmission value of the target end face; Calculate the difference between the first available transmission value and the second available transmission value of the target end face. If the difference is greater than the preset threshold, perform the following steps: Obtain the actual active power output values of the wind farm for the previous n time periods; according to the actual active power output values of the wind farm for the previous n time periods, determine the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment; Substitute the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment into the calculation model of the available transmission capacity of the large power grid considering the wind power prediction error interval to obtain the calculation result of the available transmission capacity; Output the calculation result of the available transmission capacity; The step of obtaining the actual active power output values of the wind farm for the previous n time periods; The steps of determining the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment according to the actual active power output values of the wind farm for the previous n time periods specifically include: Obtain the actual active power output values of the wind farm in the first n time periods ; Calculate the linear correlation between X and Y: (1) Among them, is the actual active power output value of the wind farm in n time periods of the historical data; for Y related to X, if the error at the (n + 1)-th moment of Y is positive, it is recorded as e, and if the error is negative, it is recorded as w; It is a vector composed of the predicted positive errors at the (n + 1)-th moment in the historical Y related to X, and the mode of the positive error vector is: (2) is the mean of h elements in E, is the median in Upper limit of wind power prediction error = + It is a vector composed of predicted negative errors at the (n + 1)-th moment in the historical Y related to X. The mode of the negative error vector is: (3) The mean of l the number of elements in W; Lower limit of wind power prediction error - 。 4. A method for calculating the available transmission capacity of a power grid based on the mode according to claim 3, characterized in that, The calculation model of the available transmission capacity of the large power grid considering the wind power prediction error interval is specifically: （5） Where: : branch ij susceptance; : Matrix corresponding to a linear function of the unit output corresponding to one row : Matrix corresponding to the elements of the linear function of the corresponding load in a row; : Composed of the negative values of the reciprocals of the branch impedances, per-unit value; : The radian value of the node phase angle; : Active power vector of node load; : Active power vector of node power generation; : Active power limit of branch ij; is 、 、 and the maximum value among; : Lower limit vector of active power prediction for node wind power generation; : Upper limit vector of active power prediction for node wind power generation; : Maximum network loss; Calculate the available transfer capability of the target branch considering the wind power prediction error according to Equation (5). ij ​ 5. A calculation device for the available transmission capacity of a power grid based on the mode, characterized in that, Including: An error calculation module for obtaining the actual active power output values of the wind farm for the previous n time periods; According to the actual active power output values of the wind farm for the previous n time periods, determine the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment; A transmission capacity calculation module for substituting the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment into the calculation model of the available transmission capacity of the large power grid considering the wind power prediction error interval to obtain the calculation result of the available transmission capacity; An output module for outputting the calculation result of the available transmission capacity; In the error calculation module, obtain the actual active power output values of the wind farm for the previous n time periods; The steps of determining the upper limit and lower limit of the wind power prediction error of the wind farm at the (n + 1)-th moment according to the actual active power output values of the wind farm for the previous n time periods specifically include: Obtain the actual active power output values of the wind farm in the first n time periods ; Calculate the linear correlation between X and Y: (1) Among them, is the actual active power output value of the wind farm in n time periods of the historical data; screen Y related to X according to the linear correlation between X and Y; for Y related to X, if the error at the (n + 1)-th moment of Y is positive, record it as e, and if the error is negative, record it as w; For the vector composed of the predicted positive errors at the (n + 1)-th moment in the historical Y related to X, the mode of the positive error vector is: (2) is the mean of h elements in E, is the median in Upper limit of wind power prediction error = + is a vector composed of predicted negative errors at the (n + 1)-th moment in the historical Y related to X, and the mode of the negative error vector is: (3) is the mean of l elements in W, and is the median in Lower limit of wind power prediction error - ; The calculation model of available transfer capability of large power grid considering the error interval of wind power prediction is specifically as follows: （5） Where: : branch ij susceptance; : Matrix corresponding to a linear function of the unit output corresponding to one row : Matrix corresponding to the linear function elements of the corresponding load in a row : Composed of the negative values of the reciprocals of the branch impedances, per-unit value; : The radian value of the node phase angle; : Active power vector of node load; : Active power vector of node power generation; : Active power limit of branch ij; is 、 、 and the maximum value among; : Lower limit vector of active power prediction for node wind power generation; : Node wind power active power prediction upper limit vector; : Maximum network loss; Calculate the available transmission capacity of the target branch considering the wind power prediction error according to Equation (5). ij ​ 6. An electronic device, characterized in that, It includes a processor and a memory. The processor is used to execute the computer program stored in the memory to implement a method for calculating the available transfer capability of the power grid based on the mode as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by the processor, it implements a method for calculating the available transfer capability of the power grid based on the mode as described in any one of claims 1 to 4.

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