Voltage fast correction method and device for wide-area new energy fluctuation

Abstract

The application discloses a voltage fast correction method and device for wide-area new energy fluctuation, relates to the field of power system optimization control, and comprises the following steps: S1, centralized reactive power optimization is carried out by using an opportunity constraint programming reactive power optimization model, and an optimal operation point of a power system in a time period is solved; S2, at the optimal operation point, analytical expressions of voltage sensitivity coefficients and network loss micro-increment rates are derived; S3, when power fluctuation of a new energy node occurs, the amplitude and phase angle states of the node voltage are corrected according to a power fluctuation interval, and the corrected voltage sensitivity coefficients and network loss micro-increment rates are obtained by substituting the analytical expressions; and S4, at each time of the time period, the optimal reactive power regulation amount of each new energy node is solved by using a segmented calculation mode, and voltage fast correction is completed. The application can effectively suppress system voltage disturbance caused by active power fluctuation of new energy, reduce system active power loss, and simultaneously improve voltage safety level and system operation economy under wide-area new energy fluctuation.

Description

Technical Field

[0001] This invention relates to the field of power system optimization control technology, and in particular to a method and apparatus for rapid voltage correction of fluctuations in wide-area renewable energy sources. Background Technology

[0002] In recent years, the new energy industry has entered a new stage of rapid development. The large-scale development and efficient utilization of new energy sources, while effectively optimizing the energy structure and alleviating environmental pressures, also pose new challenges to the optimized operation and precise control of the power system. Since most new energy power plants are connected to the main grid via long-distance transmission lines, the grid-connected system exhibits significant weak grid characteristics. Furthermore, the randomness and volatility of new energy output can easily cause system voltage fluctuations or even exceed limits, directly threatening the voltage safety and stability of the power system. Facing the dynamic fluctuations in new energy output over a wide area, the difficulty of coordinated optimization control of the power system has increased significantly. Currently, while centralized reactive power optimization methods have the advantage of converging to the global optimum, they place extremely high demands on the system's computing and communication capabilities, making it difficult to efficiently adapt to the real-time requirements of reactive power and voltage optimization control under scenarios of rapid fluctuations in new energy output over a wide area. Traditional sensitivity analysis methods achieve rapid regulation of new energy reactive power through linear voltage sensitivity, but their core drawback is that the system sensitivity coefficient must be fixed at a specific operating point and cannot be dynamically adjusted according to the operating state. However, in practical engineering scenarios, the continuous fluctuations in renewable energy output lead to constant changes in system operating status, resulting in dynamic shifts in the sensitivity coefficient. This directly affects the accuracy and effectiveness of voltage regulation, and the regulation effect decreases significantly as the amplitude of renewable energy fluctuations increases. Therefore, it is urgent to explore an effective method to correct the voltage sensitivity coefficient and the incremental rate of grid losses in real time according to renewable energy fluctuations, and to establish a rapid voltage correction model for wide-area renewable energy fluctuations. This will improve the voltage security level and economic efficiency of the power system, providing technical support for the stable operation of the power system after large-scale renewable energy grid integration. Summary of the Invention

[0003] To address the above problems, this invention proposes a method and device for rapid voltage correction of wide-area renewable energy fluctuations. It employs a reactive power optimization model based on chance-constrained programming to perform centralized reactive power optimization of the power system. By reasonably setting confidence levels and voltage safety margins, it effectively reduces the risk of voltage exceeding limits. Analytical expressions for the power system voltage sensitivity coefficient and the incremental rate of network losses are derived. By dynamically correcting the voltage sensitivity coefficient and the incremental rate of network losses according to renewable energy fluctuations, the calculation accuracy of these two parameters under renewable energy fluctuation scenarios is significantly improved. Furthermore, based on the dynamically corrected voltage sensitivity coefficient and the incremental rate of network losses, each renewable energy node uses a piecewise calculation method to solve for the optimal reactive power regulation and dynamically adjusts the reactive power output of renewable energy for real-time voltage correction, effectively suppressing voltage exceeding-limit problems caused by short-term fluctuations in renewable energy.

[0004] On the one hand, the method for rapid voltage correction of wide-area renewable energy fluctuations has the following specific steps:

[0005] S1, with a preset time period as the cycle, constructs a reactive power optimization model based on voltage safety margin to realize opportunity constraint planning for the power system connected to the new energy node, performs centralized reactive power optimization calculation, obtains the optimal operating point of the power system within the time period, and controls the power system to operate at the optimal operating point.

[0006] S2, at the optimal operating point, derive analytical expressions for the voltage sensitivity coefficient and the incremental rate of network loss in response to voltage amplitude and phase angle.

[0007] S3, when power fluctuations occur at new energy nodes during the time period, the power fluctuation interval is divided, and the node voltage amplitude and phase angle state are corrected according to the power fluctuation interval. The corrected voltage amplitude and phase angle state are substituted into the analytical expression of voltage sensitivity coefficient and the analytical expression of network loss incremental rate to obtain the corrected voltage sensitivity coefficient and network loss incremental rate.

[0008] S4. At each moment within the time period, each new energy node uses a segmented calculation method to solve for the optimal reactive power regulation based on the corrected voltage sensitivity coefficient and the incremental rate of network loss, and dynamically adjusts the reactive power output to complete the rapid voltage correction.

[0009] Preferably, the reactive power optimization model based on voltage safety margin for opportunity-constrained planning takes minimizing the total active power loss of the power system as the objective function, satisfies conventional constraints including power balance equations, equipment capacity and reactive power output limits, and satisfies opportunity constraints constructed based on voltage safety margin.

[0010] The process of constructing the opportunity constraints is as follows:

[0011] Based on the probability distribution of active power fluctuations in new energy sources and the system voltage sensitivity matrix, the probability distribution of voltage amplitude fluctuations is obtained; based on the probability distribution of voltage amplitude fluctuations, the voltage safety margin that ensures the node voltage does not exceed the limit under a preset confidence level is calculated.

[0012] Embedding the voltage safety margin into the constraint condition of the node voltage amplitude, we obtain the opportunity constraint condition, expressed as: ;in, Indicates the lower limit of voltage amplitude; Indicates voltage safety margin; Indicates the first Voltage amplitude at each node; Indicates the upper limit of voltage amplitude; Represents a set of nodes.

[0013] Preferably, the probability distribution of the voltage amplitude fluctuation is a normal distribution; the voltage safety margin calculated based on the probability distribution of the voltage amplitude fluctuation to ensure that the node voltage does not exceed the limit at a preset confidence level is expressed as:

[0014] ;

[0015] Where Φ(x) represents the standard normal integral function; Represents a node The average value of the voltage amplitude fluctuation; β represents the confidence level; This indicates the allowable voltage fluctuation, i.e., the voltage safety margin; Represents a node Standard deviation of voltage fluctuation.

[0016] Preferably, the probability distribution of the voltage amplitude fluctuation follows a normal distribution; its standard deviation is expressed as:

[0017] ;

[0018] ;

[0019] ;

[0020] in, This represents the average value of voltage amplitude fluctuations; This represents the sensitivity matrix of voltage amplitude to active power. All are The elements in Indicates the number of nodes; This represents the average value of active power fluctuations; T represents the covariance matrix; T represents the transpose. Represents a node Standard deviation of active power fluctuation; Represents a node Standard deviation of voltage fluctuation; Represents the correlation coefficient matrix; Represents a set of nodes.

[0021] Preferably, the process of dividing the power fluctuation range and correcting the node voltage amplitude and phase angle state based on the power fluctuation range is as follows:

[0022] Based on the standard deviation of the active power fluctuation of new energy sources as the basic interval width, the active power fluctuation of new energy sources is divided into several fluctuation intervals.

[0023] For each increase in the active power fluctuation amplitude by one interval, the voltage amplitude and phase angle are corrected once using a correction formula; the correction formula is expressed as:

[0024] ;

[0025] in, Represents the magnitude vector of node voltages; The phase angle vector representing the node voltage; This represents the sensitivity matrix of voltage amplitude to active power. This represents the sensitivity matrix of voltage phase angle to active power. Indicates the interval width; Indicates the first A fluctuation range; Indicates the first A range of fluctuations.

[0026] Preferably, the optimal reactive power regulation of each new energy node is solved using a piecewise calculation method based on the corrected voltage sensitivity coefficient and the incremental rate of network loss, as follows:

[0027] Determining new energy node based on the corrected voltage sensitivity coefficient When active power fluctuates, does the power system experience voltage over-limit?

[0028] If no voltage exceedance occurs in the power system, then the node... The reactive power is adjusted along the direction of the negative network loss incremental rate, and the optimal reactive power adjustment of the new energy node is solved by a segmented calculation method.

[0029] If the power system experiences a voltage over-limit, the reactive power is first adjusted in the direction of eliminating the voltage over-limit, and then the reactive power is adjusted in the direction of the negative network loss incremental rate. The optimal reactive power adjustment amount of the new energy node is solved by a segmented calculation method.

[0030] Preferably, the step of determining the new energy node using the corrected voltage sensitivity coefficient is... To determine whether a voltage exceedance occurs in the power system during active power fluctuations, the following steps are taken: The voltage amplitude at a node after an active power fluctuation is calculated using a corrected voltage sensitivity coefficient, and the result is used to determine whether a voltage exceedance has occurred. The voltage amplitude at the node after an active power fluctuation is expressed as follows:

[0031] ;

[0032] in, Represents a node After the fluctuation of active power of new energy, the node The total fluctuation of voltage amplitude; Represents a node Voltage to node Merit corresponds to the first Sensitivity coefficient for each fluctuation range; Represents a node Standard deviation of active power fluctuations in new energy sources; Represents a node Voltage to node Merit corresponds to the first Sensitivity coefficient for each fluctuation range; Represents a node Total fluctuation of active power from new energy sources; Indicates the total number of fluctuation intervals; Represents a set of nodes.

[0033] Preferably, when no voltage exceedance occurs in the power system, the optimal reactive power regulation of the new energy node is expressed as:

[0034] ;

[0035] ;

[0036] ;

[0037] in, To avoid causing node Permissible nodes under voltage over-limit conditions Reactive power regulation; Indicates the fluctuation range corresponding nodes Reactive power regulation; Represents a node The upper limit of voltage amplitude; Represents a node Voltage amplitude at the optimal operating point; Represents a node Voltage to node Merit corresponds to the first Sensitivity coefficient for each fluctuation range; Represents a node Standard deviation of active power fluctuations in new energy sources; Represents a node Voltage to node The sensitivity coefficient for reactive power corresponding to the τth fluctuation interval; Indicates the total number of fluctuation intervals; Represents a node Total fluctuation of active power from new energy sources; Represents a set of nodes; Represents a node The final reactive power that needs to be adjusted; min indicates taking the minimum value.

[0038] Preferably, when a voltage over-limit occurs in the power system, the reactive power is adjusted in the direction of eliminating the voltage over-limit, as follows:

[0039] For the node Fluctuation range of active power of new energy Time node No voltage limit was exceeded, but the voltage fluctuated within the specified range. Time-occurring node Operating conditions exceeding voltage limits, within the fluctuation range. The required reactive power regulation is expressed as follows:

[0040] ;

[0041] in, Indicates the fluctuation range corresponding nodes Reactive power regulation; Represents a node The upper limit of voltage amplitude; Represents a node Voltage amplitude at the optimal operating point; Represents a node Voltage to node Merit corresponds to the first Sensitivity coefficient for each fluctuation range; node Standard deviation of active power fluctuations in new energy sources; Represents a node Voltage to node i corresponds to the reactive power of the first Sensitivity coefficient for each fluctuation range; Indicates the total number of fluctuation intervals; Represents a node After the fluctuation of active power of new energy, the node The total fluctuation of voltage amplitude; Represents a set of nodes; Indicates the range of fluctuations The set of nodes where the voltage exceeds the limit; Indicates the range of fluctuations The set of nodes where the voltage exceeds the limit;

[0042] For the node New energy power fluctuation range and Time node All operating conditions resulted in voltage exceeding limits, within the fluctuation range. The required reactive power regulation is expressed as follows:

[0043] ;

[0044] in, Represents a node Fluctuations in the active power of new energy sources;

[0045] For the node Power fluctuation range Time node Under operating conditions where no voltage exceedance occurs, within the fluctuation range The required reactive power regulation is expressed as follows:

[0046] ;

[0047] in, Indicates from 1 to 1 The set of any nodes that exceed the limit within the fluctuation range;

[0048] node The final required reactive power regulation is expressed as follows:

[0049] ;

[0050] ;

[0051] in, To eliminate nodes Node required for voltage over-limit Reactive power regulation; This indicates the elimination of all nodes with voltage exceeding the limit. The final reactive power that needs to be adjusted; max indicates taking the maximum value.

[0052] On the other hand, a voltage fast correction device for wide-area new energy fluctuations includes the following:

[0053] The centralized reactive power optimization module is used to perform centralized reactive power optimization calculations on the power system connected to new energy nodes for a preset time period. It adopts a reactive power optimization model based on voltage safety margin to realize opportunity constraint programming, solves the optimal operating point of the power system within the time period, and controls the power system to operate at the optimal operating point.

[0054] The analytical expression acquisition module is used to derive analytical expressions for the voltage sensitivity coefficient and the incremental rate of network loss in response to voltage amplitude and phase angle at the optimal operating point.

[0055] The voltage sensitivity coefficient and network loss incremental rate correction module is used to divide the power fluctuation range when the power fluctuation of the new energy node occurs within the time period, correct the node voltage amplitude and phase angle state according to the power fluctuation range, and substitute the corrected voltage amplitude and phase angle state into the analytical expression of voltage sensitivity coefficient and analytical expression of network loss incremental rate to obtain the corrected voltage sensitivity coefficient and network loss incremental rate.

[0056] The new energy node correction module is used to calculate the optimal reactive power regulation of each new energy node at each moment within the time period based on the corrected voltage sensitivity coefficient and the incremental rate of network loss, and dynamically adjust the reactive power output of the new energy node to complete the rapid voltage correction.

[0057] Compared with the prior art, the present invention has the following beneficial effects:

[0058] (1) This invention, through centralized optimization based on opportunity-constrained programming, takes minimizing the active power loss of the system as the core optimization objective, and effectively reduces the risk of voltage exceeding the limit by reasonably setting the confidence level and voltage safety margin, thereby achieving a synergistic balance between the voltage safety level and the operational efficiency of the new energy power system.

[0059] (2) This invention derives analytical expressions for the voltage sensitivity coefficient and the incremental rate of network loss in the power system. Given the voltage amplitude and phase angle of the system, the two types of parameters can be calculated quickly based on these analytical expressions. At the same time, by dynamically correcting the voltage sensitivity coefficient and the incremental rate of network loss with the fluctuation of new energy sources, the calculation accuracy of the two types of parameters under the scenario of new energy fluctuation is significantly improved, so that they can adapt to the nonlinear operating characteristics of the system.

[0060] (3) The present invention uses a segmented calculation method to solve the optimal reactive power regulation for each new energy node and dynamically adjusts the reactive power output of new energy to perform real-time voltage correction. This can effectively suppress the voltage over-limit problem caused by short-term fluctuations of new energy, while reducing the active power loss of the system and further improving the voltage safety level and operation economy of the high-proportion new energy power system. In addition, the voltage sensitivity coefficient and the micro-increase rate of network loss are dynamically corrected in combination with the fluctuation characteristics of new energy, which further strengthens the optimization control effect of the real-time voltage correction method and improves the adaptability and accuracy of the control strategy. Attached Figure Description

[0061] The present invention will now be described in further detail with reference to the accompanying drawings;

[0062] Figure 1 This is a flowchart of a method for rapid voltage correction of wide-area renewable energy fluctuations according to an embodiment of the present invention;

[0063] Figure 2This is a topology diagram of an IEEE-39 system containing new energy access, illustrating the fast voltage correction method for wide-area new energy fluctuations according to an embodiment of the present invention.

[0064] Figure 3 This is a voltage distribution diagram after reactive power optimization for the voltage fast correction method for wide-area new energy fluctuations according to an embodiment of the present invention.

[0065] Figure 4 The system voltage sensitivity of the fast voltage correction method for wide-area renewable energy fluctuations in this embodiment of the invention to the power of nodes 36 and 38 is shown.

[0066] Figure 5 The incremental rates of active and reactive power network losses in the system of the voltage fast correction method for wide-area new energy fluctuations according to an embodiment of the present invention;

[0067] Figure 6 This is a schematic diagram illustrating the correction process of voltage sensitivity coefficient and network loss incremental rate in the voltage fast correction method for wide-area new energy fluctuations according to an embodiment of the present invention.

[0068] Figure 7 This is a schematic diagram illustrating the calculation of reactive power regulation in a fast voltage correction method for wide-area new energy fluctuations according to an embodiment of the present invention.

[0069] Figure 8 The reactive power curve at node 36 of the voltage fast correction method for wide-area new energy fluctuations in this embodiment of the invention;

[0070] Figure 9 The reactive power curve at node 38 of the voltage fast correction method for wide-area new energy fluctuations in this embodiment of the invention;

[0071] Figure 10 The active power time-series curves of new energy sources at nodes 36 and 38 are shown in the embodiment of the present invention for the fast voltage correction method for wide-area new energy fluctuations.

[0072] Figure 11 The reactive power curve at node 36 of the voltage fast correction method for wide-area new energy fluctuations in this embodiment of the invention;

[0073] Figure 12 The reactive power curve at node 38 of the voltage fast correction method for wide-area new energy fluctuations in this embodiment of the invention;

[0074] Figure 13 Network loss curves for different optimization methods of the voltage fast correction method for wide-area renewable energy fluctuations according to embodiments of the present invention;

[0075] Figure 14This diagram illustrates the maximum system voltage values ​​of different optimization methods for the fast voltage correction method for wide-area renewable energy fluctuations according to an embodiment of the present invention.

[0076] Figure 15 This is a structural block diagram of a voltage fast correction device for wide-area new energy fluctuations according to an embodiment of the present invention. Detailed Implementation

[0077] The present invention will be further described below through specific embodiments.

[0078] This embodiment constructs a reactive power optimization model based on chance-constrained programming, proposes a method for calculating voltage safety margin, derives analytical expressions for voltage sensitivity coefficient and network loss incremental rate, establishes a method for dynamically correcting the above two types of parameters according to renewable energy fluctuations, and proposes a real-time voltage correction method for wide-area renewable energy fluctuations, thereby improving the system voltage safety level and operational economy.

[0079] First, based on the system monitoring status at the initial moment of a time period, the power system control center employs a chance-constrained programming method to perform centralized reactive power optimization, solving for the optimal operating point of the system during that time period. Simultaneously, control commands are issued to each reactive power device, providing a foundation for renewable energy reactive power optimization control at each moment within that time period. Second, at the optimal operating point of the system during that time period, analytical expressions for the voltage sensitivity coefficient and the incremental rate of network loss are derived. A method for dynamically correcting these parameters based on fluctuations in renewable energy output is proposed. By real-time correction of node voltage amplitude and phase angle, and updating the analytical formulas for these two types of parameters, the calculation accuracy of the voltage sensitivity coefficient and the incremental rate of network loss under wide-area renewable energy fluctuation scenarios can be significantly improved, providing theoretical support and computational basis for subsequent real-time and accurate voltage correction. Finally, a real-time voltage correction method for wide-area renewable energy power fluctuations is proposed. Based on the dynamically corrected voltage sensitivity coefficient and the incremental rate of network loss, the optimal reactive power regulation is solved by a piecewise calculation method for each renewable energy node, and the reactive power output of the renewable energy node is dynamically adjusted. This method can effectively suppress system voltage disturbances caused by renewable energy active power fluctuations, reduce system active power network losses, and simultaneously improve the voltage safety level and system operation economy under wide-area renewable energy fluctuations.

[0080] like Figure 1 As shown, the method for rapid voltage correction of wide-area renewable energy fluctuations includes the following specific steps:

[0081] S1, with a preset time period as the cycle, for the power system connected to the new energy node, adopts a reactive power optimization model based on voltage safety margin to realize opportunity constraint programming, performs centralized reactive power optimization calculation on the power system, solves the optimal operating point of the power system within the time period, and controls the power system to operate at the optimal operating point.

[0082] A time period can be divided into several moments. At the beginning of each time period, the control center periodically collects the operating status of each device in the system. Taking the minimization of network loss as the objective function and considering the uncertainty of new energy sources, a reactive power optimization model of the power system based on chance-constrained programming is established. The model uses the voltage amplitude and voltage phase angle of each node as state variables, and the reactive power output of generators and new energy sources as control variables. The node power and voltage amplitude and phase angle satisfy the power balance equation. An improved interior-point method is used to solve the optimization model, thereby realizing centralized reactive power optimization at the time period scale. Assuming that the power fluctuation of each node with new energy access follows a normal distribution within the time period, the established model prevents the system voltage from exceeding the limit by reserving a voltage safety margin controlled by confidence in the voltage constraint conditions.

[0083] S11, Construct the objective function.

[0084] The objective function of the reactive power optimization model of the power system based on chance-constrained programming consists of two parts, as shown in Equation (1). The first term represents series losses, such as branch losses and transformer copper losses, and the second term represents parallel losses, such as transformer iron losses and grounding conduction losses at nodes.

[0085] (1);

[0086] In the formula: P loss This represents the active power loss. i, j, and k are nodes, and l is a branch, with its starting and ending points being nodes i and j, respectively. V i and θ i Let k be the voltage magnitude and voltage phase angle at node i, respectively. l and θ shift,l Let k be the transformer turns ratio and phase shift angle on branch l, respectively. For branches without transformers, k is... l Equal to 1, θ shift,l Equals 0. G l Let G0 be the conductance of branch l. Let G0 be the ground conductance of node k. l Let n and y be the total number of branches and nodes in the system, respectively. Let L be the set of all branches. Let B be the set of all nodes.

[0087] S12, construct the constraints.

[0088] The equality constraints of the reactive power optimization model of the power system based on chance-constrained programming are the power balance equations, as shown in equation (2). The inequality constraints include branch transmission power constraints and variable boundary constraints, as shown in equations (3)-(7), respectively.

[0089] (2);

[0090] (3);

[0091] (4);

[0092] (5);

[0093] (6);

[0094] (7);

[0095] In the formula: P gen,i and Q gen,i These are the active and reactive power of the generator injected into node i, respectively. res,i and Q res,i These are the active and reactive power of the new energy source injected into node i, respectively. load,i and Q load,i G represents the active and reactive power of the load at node i, respectively. ij and B ij θ represents the conductance and susceptance between nodes i and j in the nodal admittance matrix. ij S represents the phase angle difference between node i and node j. l The transmission power of branch l is S, and its maximum transmission capacity is S. l,max Q gen,i Let Q be the reactive power at generator node i, with upper and lower limits Qmax gen,i and Qmin gen,i, respectively. res,i Let be the reactive power of node i including new energy sources, with upper and lower limits Qmax res,i and Qmin res,i, respectively. i,max and V i,min ΔV represents the upper and lower limits of the voltage amplitude at node i. i θ represents the voltage safety margin at node i. i,max and θ i,min represents the upper and lower limits of the voltage phase angle at node i.

[0096] S13, calculate voltage safety margin.

[0097] According to relevant theorems in probability theory, any linear combination of multivariate normal distributions follows a one-dimensional normal distribution. In this embodiment, it is assumed that the power fluctuations of the new energy nodes follow a normal distribution with a mean of 0. After the linear affine transformation of the sensitivity matrix, the voltage amplitude and phase angle of each node will also follow a normal distribution. The linear affine process is shown in Equation (8). The sensitivity matrix in Equation (8) is obtained by inverting the Jacobian matrix, as shown in Equation (9). The Jacobian matrix is ​​obtained from Equations (10)-(12).

[0098] (8);

[0099] (9);

[0100] (10);

[0101] (11);

[0102] (12);

[0103] In the formula: ΔP and ΔQ represent the active and reactive power increments of new energy sources. ΔV and Δθ represent the voltage amplitude and phase angle increments. i and Q i Let V be the total active and reactive power injected into node i, and let V be the elements of ΔP and ΔQ, respectively. i and θ i Let S be the voltage magnitude and phase angle at node i, and ΔV and Δθ be the elements, respectively. VP and S VQ This is the sensitivity matrix of voltage amplitude to active and reactive power. Similarly, S can be obtained. θP and S θQ Matrices N, H, L, and J constitute the Jacobian matrix.

[0104] Assuming the mean of active power fluctuation at nodes containing new energy sources is 0, after the linear affine transformation in equation (13), the mean of voltage amplitude fluctuation at each node is also 0. The probability distribution of voltage amplitude fluctuation considering the influence of correlation can be obtained from equations (14)-(16). Furthermore, the allowable voltage fluctuation ΔV at node i without exceeding the limit under confidence level β is obtained through equation (17). i This is incorporated into the voltage constraint as a voltage safety margin to control the risk of voltage exceeding limits.

[0105] (13);

[0106] (14);

[0107] (15);

[0108] (16);

[0109] (17);

[0110] In the formula: and These are the average values ​​of voltage amplitude fluctuation and active power fluctuation, respectively. A ρ Let R be the correlation coefficient matrix. Let R be the covariance matrix. ΔP δ,i and S represents the standard deviation of active power fluctuation and voltage fluctuation at node i.VP,i,j It is matrix S VP The elements. ΔV i Let be the voltage fluctuation at node i, and its average value is . N(x) is the standard normal distribution function. Φ(x) is the standard normal integral function. β is the confidence level.

[0111] As can be seen from the above analysis, formulas (1)-(17) constitute a reactive power optimization model based on chance-constrained programming. In this embodiment, an improved interior-point method is used to solve this nonlinear programming problem. The obtained time-period optimization results will be used to guide the optimization control of renewable energy reactive power and system voltage correction at each moment within that time period.

[0112] This embodiment is performed in a modified IEEE-39 node system. For example... Figure 2 As shown, the renewable energy power stations are connected to nodes 36 and 38 respectively. Assume that the active power fluctuations of the renewable energy power stations follow a normal distribution within the time period, with a standard deviation of ΔP. δ,i =25 MW, the time-period optimization based on opportunity-constrained programming uses a confidence level β = 0.95. The correlation coefficient between the two renewable energy power stations is ρ = 0.5, and the upper and lower limits of the voltage at all nodes in the system are V. i,max = 1.1 pu and V i,min = 0.9pu. Assume the measured active power of nodes 36 and 38 during the time period is 560MW and 830MW respectively, and each is equipped with a 100MVar static var compensator. According to S1, at the initial moment of each time period, with the objective function of minimizing network loss and considering the uncertainty of renewable energy power fluctuations, a reactive power optimization model of the power system based on chance-constrained programming is established to obtain the optimal operating point for each time period. The model uses the voltage amplitude and voltage phase angle of each node as state variables, and the reactive power output of generators and renewable energy sources as control variables. An improved interior-point method is used to solve the optimization model.

[0113] like Figure 3 As shown, the solid black line represents the voltage after reactive power optimization of the power system based on chance-constrained programming, which is slightly lower than the voltage limit (1.1 pu). This is because a voltage safety margin is reserved in the voltage constraint conditions to prevent voltage exceedances that may be caused by fluctuations in new energy sources. The optimal state obtained by power flow optimization without reserving a voltage safety margin is shown as the dashed black line. In this case, nodes 25 and 36 reach the voltage limit, and the optimal state is closer to the voltage limit. This indicates that in high-voltage transmission systems, optimal power flow calculation aimed at minimizing network losses will maximize the overall voltage level, thereby reducing network losses.

[0114] S2, at the optimal operating point, derive analytical expressions for the voltage sensitivity coefficient and the incremental rate of network loss in response to voltage amplitude and phase angle.

[0115] At the optimal operating point of the system period, the analytical expressions for voltage sensitivity coefficient and network loss incremental rate are derived. Based on the division of the new energy fluctuation range, the voltage amplitude and phase angle of the nodes are dynamically corrected. Substituting these into the analytical formulas of the above two types of parameters can significantly improve the calculation accuracy of voltage sensitivity coefficient and network loss incremental rate.

[0116] The analytical expression of the voltage sensitivity matrix is ​​shown in equations (9)-(12). When the voltage amplitude and phase angle of the system nodes at a certain operating point are known, the voltage sensitivity matrix can be directly calculated using equations (9)-(12). The active power loss is not only a function of the node voltage amplitude and phase angle, but also a function of active power and reactive power. The gradient formula (18) can be obtained by differentiation. By combining equations (8) and (18), the incremental rate of network loss can be obtained, as shown in equation (19). When the system state (V, θ) is given, the gradient of network loss with respect to voltage amplitude and phase angle can be obtained through equations (20)-(21), and then the incremental rate of network loss can be obtained.

[0117] (18);

[0118] (19);

[0119] (20);

[0120] (twenty one);

[0121] In the formula: P loss For active power losses, P and Q represent active and reactive power from new energy sources, and V and θ represent voltage amplitude and phase angle, respectively. ΔP and ΔQ represent the increments of active and reactive power from new energy sources, and ΔV and Δθ represent the increments of voltage amplitude and phase angle, respectively. G LP and G LQ These represent the incremental rates of active power loss and reactive power loss, respectively. Matrices N, H, L, and J constitute the Jacobian matrix. and V represents the gradient of active power loss with respect to the voltage magnitude and phase angle at node i. i and V j This represents the voltage amplitude. θ i and θ j k is the voltage phase angle. l and θ shift,l These represent the transformer turns ratio and phase shift angle on branch l, respectively. l Let G0 be the conductance of branch l. Let G0k be the ground conductance of node k.

[0122] At the optimal operating point obtained by reactive power optimization of a power system based on chance-constrained programming, the voltage sensitivity and incremental rate of network loss obtained using the analytical expression are as follows: Figure 4 and Figure 5As shown, an increase in reactive power injected into a node leads to an increase in voltage amplitude, while an increase in active power injected into a node leads to a decrease in voltage amplitude. Reactive power is more sensitive to voltage amplitude than active power, indicating that reactive power has a greater impact on voltage amplitude. Combined with... Figure 2 and Figure 4 It can be seen that the voltage amplitude is more sensitive to the injected power at its adjacent nodes than at other nodes. For example, the active and reactive power at node 36 has the greatest impact on its own voltage amplitude, followed by the voltage amplitudes of nodes {23, 22, 21, 24, 16} that are electrically close to node 36. The same pattern can be observed at node 38. Figure 5 It can be seen that increasing the active power at nodes 36 and 38 increases power loss, while increasing the reactive power decreases power loss. Therefore, the sensitivity coefficient and the incremental rate of network loss can indicate the direction of reactive power adjustment for the real-time voltage correction method, in order to prevent voltage exceedance and reduce network loss.

[0123] S3, when power fluctuations occur at new energy nodes during the time period, the power fluctuation interval is divided, and the node voltage amplitude and phase angle state are corrected according to the power fluctuation interval. The corrected voltage amplitude and phase angle state are substituted into the analytical expression of voltage sensitivity coefficient and the analytical expression of network loss incremental rate to obtain the corrected voltage sensitivity coefficient and network loss incremental rate.

[0124] When renewable energy access nodes experience significant power fluctuations during a given period, such as sudden power changes caused by gusts at wind farms or moving clouds at photovoltaic power plants, the actual operating state of the power system may differ significantly from the optimal operating point obtained in S1. In this case, the sensitivity coefficient and network loss increment rate calculated in S2 are not accurate enough, and renewable energy fluctuations can cause dynamic shifts in the sensitivity coefficient, directly affecting the accuracy and effectiveness of voltage regulation. Therefore, this embodiment proposes a method to correct the voltage sensitivity coefficient and network loss increment rate according to renewable energy fluctuations, thereby improving their calculation accuracy.

[0125] First, based on the standard deviation of the active power fluctuation of new energy sources as the base interval width, the active power fluctuation of new energy sources is divided into several fluctuation intervals, such as... Figure 6 As shown, the fluctuation range is -3ΔP δ,i To 3ΔP δ,i The initial voltage state (V,θ) is obtained by reactive power optimization based on chance-constrained programming in S1. τ=0 Secondly, based on the magnitude of the power fluctuation, equation (22) is used to define the system voltage state (V,θ). τ Perform dynamic corrections, such as Figure 6 As shown by the green arrow, the system voltage state is corrected once for each increase in the active power fluctuation amplitude within a certain interval. Then, the corrected state (V,θ) obtained in (22) is...τ±1 Substituting into the analytical expressions of equations (9) and (18), we obtain the voltage sensitivity coefficient and network loss increment rate after correction for different fluctuation amplitudes, such as... Figure 6 As shown by the blue arrow in the middle. For each renewable energy access node, it is only necessary to correct the voltage sensitivity coefficient and the incremental rate of network loss once at the beginning of the time period according to the above process, so that the voltage fast correction method can be used at every moment of the entire time period.

[0126] (twenty two);

[0127] In the formula: This represents the magnitude vector of the node voltage. This represents the phase angle vector of the node voltage. τ is the index of the fluctuation range. This represents the sensitivity matrix of voltage amplitude to active power. This represents the sensitivity matrix of voltage phase angle to active power. ΔP δ,i The standard deviation of active power fluctuations in new energy sources. The interval width is equal to the standard deviation of active power fluctuations in new energy sources.

[0128] exist Figure 6 In the diagram, the red dashed line represents the corrected voltage state, and the black solid line represents the optimal voltage state of the system after considering the fluctuations in renewable energy. As the amplitude of the active power fluctuations from renewable energy increases, the corrected voltage state can follow the optimal voltage state, demonstrating the characteristics of nonlinear sensitivity. A smaller fluctuation range width will result in the two lines being closer, but this increases the computational burden on voltage sensitivity and the correction of the incremental rate of network loss. Therefore, the standard deviation of the active power fluctuations from renewable energy is chosen as the power fluctuation range width.

[0129] This embodiment derives analytical expressions for the voltage sensitivity coefficient and the incremental rate of network loss at the optimal operating point of the system time period, and proposes a method for dynamically correcting the above parameters according to the fluctuation of renewable energy output. By correcting the node voltage amplitude and phase angle in real time and updating by substituting into the analytical formulas of the two types of parameters, the calculation accuracy of the voltage sensitivity coefficient and the incremental rate of network loss under the scenario of wide-area renewable energy fluctuation can be significantly improved, providing a foundation for the subsequent realization of real-time and accurate voltage correction.

[0130] S4. At each moment within the time period, each new energy node uses a segmented calculation method to solve for the optimal reactive power regulation based on the corrected voltage sensitivity coefficient and the incremental rate of network loss, and dynamically adjusts the reactive power output of the new energy node to complete the rapid voltage correction.

[0131] A real-time voltage correction method for wide-area renewable energy power fluctuations is proposed. Based on dynamically corrected voltage sensitivity coefficients and incremental network loss rates, each renewable energy node uses a piecewise calculation method to solve for the optimal reactive power regulation and dynamically adjusts its own reactive power output, thereby improving voltage safety and system operational economy. This method can effectively suppress system voltage disturbances caused by renewable energy active power fluctuations and reduce system active power losses.

[0132] S41, voltage segmentation calculation after new energy fluctuations.

[0133] When performing real-time voltage correction at each moment within a time period, each renewable energy node reaches a consensus that it assumes no power fluctuations occur at other nodes. During time period T... k At each time t within n The sub-control unit, including the new energy access node, measures the local new energy active power fluctuation ΔP online. i The number of new energy power fluctuation ranges at node i is calculated using equation (23). The sub-control unit uses sensitivity S VP,i,j To determine the active power fluctuation ΔP at node i i When the voltage exceeds the limit, it is shown in equation (24).

[0134] (twenty three);

[0135] (twenty four);

[0136] In the formula: T i ΔP represents the number of renewable energy power fluctuation ranges at node i. i Let i be the total fluctuation of the active power of new energy sources at node i. Represents a node Standard deviation of active power fluctuation in new energy sources. |x|、 Let x be the absolute value and the integer value. This represents the voltage amplitude at node j after the fluctuation of the active power of new energy at node i. It represents the sensitivity coefficient of the voltage at node j to the active power at node i corresponding to the τth fluctuation interval. Represents a set of nodes.

[0137] Figure 7 The solid black line in the middle represents the optimal voltage state obtained by reactive power optimization over a time period. When the active power fluctuation at node i is ΔP i At this time, the blue solid line represents the system voltage state without voltage over-limit, the green solid line represents the system voltage state with voltage over-limit, the red dashed line represents the upper limit of voltage at each node, and the dashed curve represents the system voltage state when the active power fluctuation at node i is an integer multiple of the standard deviation.

[0138] S42 is a voltage segmentation correction designed to reduce active power losses.

[0139] If the active power fluctuation of the new energy source at node i is ΔP i If the voltage of the power system does not exceed the limit, the reactive power of node i should be adjusted along the direction of the negative network loss incremental rate so that the voltage is within the allowable range and the network loss can be further reduced. For node j, where the voltage is within the feasible range, the allowable reactive power adjustment amount of node i can be obtained by adding the reactive power adjustment amounts of all fluctuation ranges, as shown in equation (25).

[0140] (25);

[0141] (26);

[0142] In the formula: This refers to the amount of reactive power regulation allowed at node i without causing the voltage at node j to exceed its limit. This represents the reactive power adjustment at node i corresponding to the fluctuation range τ. Represents a node The upper limit of voltage amplitude. Represents a node Voltage amplitude at the optimal operating point. It represents the sensitivity coefficient of the voltage at node j to the active power at node i corresponding to the τth fluctuation interval. Represents a node Standard deviation of active power fluctuation in new energy sources. This represents the sensitivity coefficient of the voltage at node j to the reactive power at node i corresponding to the τth fluctuation interval. This represents the total number of fluctuation intervals. Represents a node Total fluctuation of active power of new energy sources. Represents a set of nodes.

[0143] The reactive power regulation of node i under different fluctuation ranges is calculated using equation (26), such as Figure 7 ΔQ i,j1,1 and ΔQ i,j1,2 As shown. The reactive power that needs to be adjusted at node i is determined by equation (27), that is, the reactive power of node i is adjusted along the direction of the negative network loss incremental rate, so that only one node voltage amplitude reaches its upper limit, while the voltage amplitudes of other nodes are still within the feasible voltage range.

[0144] (27);

[0145] Where: ΔQ i Let represent the reactive power that node i ultimately needs to adjust. `min` represents the minimum value.

[0146] S43 is a segmented voltage correction designed to eliminate voltage over-limits.

[0147] If the active power fluctuation of the new energy source at node i is ΔP i When the voltage exceeds the limit in the power system, the reactive power is first adjusted in the direction of eliminating the voltage exceedance, and then adjusted in the direction of the negative network loss incremental rate to further reduce network losses within the allowable voltage range. The reactive power adjustment amount of node i can still be obtained by adding the adjustment amounts of all fluctuation intervals, as shown in equation (25). The reactive power adjustment amount required for node i power in different fluctuation intervals when the voltage of node j is within the allowable range is calculated by (28)-(30).

[0148] For the operating condition where node j does not experience voltage over-limit during the renewable energy power fluctuation range τ-1 at node i, but experiences voltage over-limit during the fluctuation range τ, the reactive power regulation required during the fluctuation range τ is determined by equation (28), such as... Figure 7 ΔQ i,j2,-1 and ΔQ i,j3,-2 As shown. For the operating condition where the voltage exceeds the limit at node j in both the new energy power fluctuation ranges τ-1 and τ at node i, the reactive power regulation required in the fluctuation range τ is determined by equation (29), as follows. Figure 2 ΔQ i,j2,-2 As shown. For node j not experiencing voltage overshoot during the power fluctuation range τ at node i, the required reactive power regulation during the fluctuation range τ is determined by equation (30), as follows: Figure 7 ΔQ i,j3,-1 As shown. In order to eliminate voltage overruns at all nodes in the power system, that is, to bring the voltage of all nodes that have experienced voltage overruns back to the feasible voltage range, the reactive power regulation amount required for node i is determined by equation (31). The process after eliminating the system voltage overruns is the same as in S42 when the system has no voltage overruns, that is, to adjust the reactive power along the direction of the negative network loss incremental rate.

[0149] (28);

[0150] (29);

[0151] (30);

[0152] (31);

[0153] In the formula: This represents the reactive power adjustment at node i corresponding to the fluctuation range τ. Represents a node The upper limit of voltage amplitude. Represents a node Voltage amplitude at the optimal operating point. It represents the sensitivity coefficient of the voltage at node j to the active power at node i corresponding to the τth fluctuation interval. Represents new energy nodes The standard deviation of active power fluctuation. This represents the sensitivity coefficient of the voltage at node j to the reactive power at node i corresponding to the τth fluctuation interval. This represents the total number of fluctuation intervals. This represents the total fluctuation in the voltage amplitude at node j after the fluctuation in the active power of new energy at node i. Represents a node Fluctuations in the active power of new energy sources. The reactive power regulation required at node i to eliminate the voltage over-limit at node j. This represents the reactive power that needs to be adjusted to eliminate all node voltage over-limit nodes i. `max` indicates taking the maximum value. Represents a set of nodes. This represents the set of nodes where the voltage exceeds the limit at the fluctuation range τ. This represents the set of nodes where the voltage exceeds the limit at the fluctuation range τ-1. Indicates from 1 to 1 The set of any nodes that exceed the limit within the fluctuation range.

[0154] When calculating reactive power regulation using the voltage fast correction method, it is only necessary to perform linear calculations based on the sensitivity coefficient and the incremental rate of network loss, without the need for iterative solutions like optimization programs, thus its calculation speed is very fast.

[0155] The effectiveness of the rapid voltage correction method is demonstrated by comparing the reactive power and voltage regulation effects of different methods. The reactive power curves of different methods are shown below. Figure 8 and Figure 9 As shown, Figure 8 The red curve in the figure represents the optimal reactive power when the active power of node 36 fluctuates alone, which is obtained through optimal power flow. Figure 9 The black dashed line in the figure represents the reactive power curve obtained using the traditional method, which optimizes reactive power over time periods to enable rapid voltage correction. Figure 8 The blue line in the image represents the different fluctuation range widths ΔP. interval The reactive power of new energy sources was obtained using the fast voltage correction method after correcting for the voltage sensitivity coefficient and the incremental rate of grid loss. Clearly, compared to traditional methods, the reactive power obtained by the fast voltage correction method is closer to the optimal reactive power. The smaller the fluctuation range of the corrected sensitivity and the incremental rate of grid loss, the more pronounced its nonlinear characteristics, and the better the reactive power tracking performance of the fast voltage correction method towards the optimal reactive power. Figure 9 Similar phenomena can be tested in node 38.

[0156] Based on the above model, a 25MW interval was set for the sensitivity coefficient and the incremental rate of network loss correction, and a 240s simulation test was conducted on the IEEE-39 node system. It was assumed that the central controller performed reactive power optimization every 30s, and the voltage fast correction method optimized the reactive power of renewable energy sources every 2 seconds. The active power of renewable energy sources at nodes 36 and 38 was as follows: Figure 10 The solid line is shown. It is assumed that by controlling the static reactive power compensators at nodes 36 and 38, the reactive power from new energy sources can be adjusted quickly enough.

[0157] like Figure 11 and 12 As shown, the optimal reactive power is obtained by repeatedly running the optimal power flow at various times. However, with the increase in the scale of power systems, this method places extremely high demands on the computing and communication capabilities of centralized systems, making it difficult to apply in practice. Traditional methods, based on time-period reactive power optimization, do not perform fast voltage correction. In contrast, the reactive power obtained by the fast voltage correction method is closer to the optimal reactive power curve, which verifies that the fast voltage correction method can effectively track the optimal reactive power. From... Figure 13 As can be seen, the network loss of the fast voltage correction method is much lower than that of the traditional method. According to the statistics in Table 1, the average network loss of the fast voltage correction method is reduced by 0.476% compared to the traditional method, thus improving operational economy.

[0158] Table 1: Average network loss for different optimization methods.

[0159]

[0160] An optimal power flow calculation is performed at every 2 seconds, and the resulting maximum system voltage is consistently 1.1 pu. Figure 14 As shown by the dashed line, the traditional method, based on time-period reactive power optimization, does not perform rapid voltage correction. Although the maximum system voltage is below 1.1 pu, it exceeds the limit at {168s, 170s, 172s} because the renewable energy sources at nodes 36 and 38 experience significant power fluctuations at these times. The rapid voltage correction method, on the other hand, achieves a maximum system voltage very close to 1.1 pu, but it does not exceed the voltage limit throughout the simulation. Furthermore, the voltage change trend of the rapid voltage correction method is essentially the opposite of that of the time-period optimization method. Therefore, the rapid voltage correction method can effectively prevent voltage exceedances caused by renewable energy fluctuations.

[0161] This embodiment demonstrates the feasibility of the proposed fast voltage correction method for wide-area renewable energy fluctuations based on dynamic correction of voltage sensitivity coefficient and network loss increment rate. The proposed strategy constructs a reactive power optimization model based on chance-constrained programming, derives analytical expressions for voltage sensitivity and network loss increment rate, proposes a method to correct voltage sensitivity and network loss increment rate according to renewable energy fluctuations, and establishes a fast voltage correction method for wide-area renewable energy fluctuations. This effectively eliminates voltage over-limit caused by renewable energy fluctuations, reduces active power losses, and provides reactive power and voltage optimization control effects.

[0162] like Figure 15 As shown, the present invention also discloses a fast voltage correction device for wide-area new energy fluctuations, comprising:

[0163] The centralized reactive power optimization module 1501 is used to perform centralized reactive power optimization calculations on the power system connected to new energy nodes for a preset time period. It adopts a reactive power optimization model based on voltage safety margin to realize opportunity constraint programming, solves the optimal operating point of the power system within the time period, and controls the power system to operate at the optimal operating point.

[0164] The analytical expression acquisition module 1502 is used to derive analytical expressions for the voltage sensitivity coefficient and the network loss incremental rate in response to voltage amplitude and phase angle at the optimal operating point.

[0165] The voltage sensitivity coefficient and network loss incremental rate correction module 1503 is used to divide the power fluctuation range when the power fluctuation of the new energy node occurs within the time period, correct the node voltage amplitude and phase angle state according to the power fluctuation range, and substitute the corrected voltage amplitude and phase angle state into the analytical expression of voltage sensitivity coefficient and analytical expression of network loss incremental rate to obtain the corrected voltage sensitivity coefficient and network loss incremental rate.

[0166] The new energy node correction module 1504 is used to calculate the optimal reactive power regulation of each new energy node at each moment within the time period based on the corrected voltage sensitivity coefficient and the incremental rate of network loss, and dynamically adjust the reactive power output of the new energy node to complete the rapid voltage correction.

[0167] The specific implementation of the voltage fast correction device for wide-area new energy fluctuations is the same as the voltage fast correction method for wide-area new energy fluctuations, and will not be described again in this embodiment.

[0168] The above are merely specific embodiments of the present invention, but the design concept of the present invention is not limited thereto. Any non-substantial modifications made to the present invention using this concept shall be considered as infringing upon the protection scope of the present invention.

Claims

1. A method for rapid voltage correction of wide-area renewable energy fluctuations, characterized in that, Includes the following steps: S1, with a preset time period as the cycle, constructs a reactive power optimization model based on voltage safety margin to realize opportunity constraint planning for the power system connected to the new energy node, performs centralized reactive power optimization calculation, obtains the optimal operating point of the power system within the time period, and controls the power system to operate at the optimal operating point. S2, at the optimal operating point, derive analytical expressions for the voltage sensitivity coefficient and the incremental rate of network loss in response to voltage amplitude and phase angle. S3, when power fluctuations occur at new energy nodes during the time period, the power fluctuation interval is divided, and the node voltage amplitude and phase angle state are corrected according to the power fluctuation interval. The corrected voltage amplitude and phase angle state are substituted into the analytical expression of voltage sensitivity coefficient and the analytical expression of network loss incremental rate to obtain the corrected voltage sensitivity coefficient and network loss incremental rate. S4. At each moment within the time period, each new energy node uses a segmented calculation method to solve for the optimal reactive power regulation based on the corrected voltage sensitivity coefficient and the incremental rate of network loss, and dynamically adjusts the reactive power output to complete the rapid voltage correction.

2. The method for rapid voltage correction of wide-area new energy fluctuations according to claim 1, characterized in that, The reactive power optimization model based on voltage safety margin and opportunity-constrained planning takes minimizing the total active power loss of the power system as the objective function, satisfies conventional constraints including power balance equations, equipment capacity and reactive power output limits, and also satisfies opportunity constraints constructed based on voltage safety margin. The process of constructing the opportunity constraints is as follows: Based on the probability distribution of active power fluctuations in new energy sources and the system voltage sensitivity matrix, the probability distribution of voltage amplitude fluctuations is obtained; based on the probability distribution of voltage amplitude fluctuations, the voltage safety margin that ensures the node voltage does not exceed the limit under a preset confidence level is calculated. Embedding the voltage safety margin into the constraint condition of the node voltage amplitude, we obtain the opportunity constraint condition, expressed as: ;in, Indicates the lower limit of voltage amplitude; Indicates voltage safety margin; Indicates the first Voltage amplitude at each node; Indicates the upper limit of voltage amplitude; Represents a set of nodes.

3. The method for rapid voltage correction of wide-area new energy fluctuations according to claim 2, characterized in that, The probability distribution of the voltage amplitude fluctuation is a normal distribution; the voltage safety margin calculated based on the probability distribution of voltage amplitude fluctuation to ensure that the node voltage does not exceed the limit at a preset confidence level is expressed as: ； Where Φ(x) represents the standard normal integral function; Represents a node The average value of the voltage amplitude fluctuation; β represents the confidence level; This indicates the allowable voltage fluctuation, i.e., the voltage safety margin; Represents a node Standard deviation of voltage fluctuation.

4. The method for rapid voltage correction of wide-area new energy fluctuations according to claim 2, characterized in that, The probability distribution of the voltage amplitude fluctuation follows a normal distribution; its standard deviation is expressed as: ； ； ； in, This represents the average value of voltage amplitude fluctuations; This represents the sensitivity matrix of voltage amplitude to active power. All are The elements in Indicates the number of nodes; This represents the average value of active power fluctuations; T represents the covariance matrix; T represents the transpose. Represents a node Standard deviation of active power fluctuation; Represents a node Standard deviation of voltage fluctuation; Represents the correlation coefficient matrix; Represents a set of nodes.

5. The method for rapid voltage correction of wide-area new energy fluctuations according to claim 1, characterized in that, The process of dividing the power fluctuation range and correcting the node voltage amplitude and phase angle state based on the power fluctuation range is as follows: Based on the standard deviation of the active power fluctuation of new energy sources as the basic interval width, the active power fluctuation of new energy sources is divided into several fluctuation intervals. For each increase in the active power fluctuation amplitude by one interval, the voltage amplitude and phase angle are corrected once using a correction formula; the correction formula is expressed as: ； in, Represents the magnitude vector of node voltages; The phase angle vector representing the node voltage; This represents the sensitivity matrix of voltage amplitude to active power. This represents the sensitivity matrix of voltage phase angle to active power. Indicates the interval width; Indicates the first A fluctuation range; Indicates the first A range of fluctuations.

6. The method for rapid voltage correction of wide-area new energy fluctuations according to claim 1, characterized in that, The optimal reactive power regulation of each new energy node is calculated using a piecewise calculation method based on the corrected voltage sensitivity coefficient and the incremental rate of network loss, as follows: Determining new energy node based on the corrected voltage sensitivity coefficient When active power fluctuates, does the power system experience voltage over-limit? If no voltage exceedance occurs in the power system, then the node... The reactive power is adjusted along the direction of the negative network loss incremental rate, and the optimal reactive power adjustment of the new energy node is solved by a segmented calculation method. If the power system experiences a voltage over-limit, the reactive power is first adjusted in the direction of eliminating the voltage over-limit, and then the reactive power is adjusted in the direction of the negative network loss incremental rate. The optimal reactive power adjustment amount of the new energy node is solved by a segmented calculation method.

7. The method for rapid voltage correction of wide-area new energy fluctuations according to claim 6, characterized in that, The method of determining new energy nodes using the corrected voltage sensitivity coefficient To determine whether a voltage exceedance occurs in the power system during active power fluctuations, the following steps are taken: The voltage amplitude at a node after an active power fluctuation is calculated using a corrected voltage sensitivity coefficient, and the result is used to determine whether a voltage exceedance has occurred. The voltage amplitude at the node after an active power fluctuation is expressed as follows: ； in, Represents a node After the fluctuation of active power of new energy, the node The total fluctuation of voltage amplitude; Represents a node Voltage to node Merit corresponds to the first Sensitivity coefficient for each fluctuation range; Represents a node Standard deviation of active power fluctuations in new energy sources; Represents a node Voltage to node Merit corresponds to the first Sensitivity coefficient for each fluctuation range; Represents a node Total fluctuation of active power from new energy sources; Indicates the total number of fluctuation intervals; Represents a set of nodes.

8. The method for rapid voltage correction of wide-area new energy fluctuations according to claim 6, characterized in that, When no voltage exceedance occurs in the power system, the optimal reactive power regulation at the renewable energy node is expressed as: ； ； ； in, To avoid causing node Permissible nodes under voltage over-limit conditions Reactive power regulation; Indicates the fluctuation range corresponding nodes Reactive power regulation; Represents a node The upper limit of voltage amplitude; Represents a node Voltage amplitude at the optimal operating point; Represents a node Voltage to node Merit corresponds to the first Sensitivity coefficient for each fluctuation range; Represents a node Standard deviation of active power fluctuations in new energy sources; Represents a node Voltage to node The sensitivity coefficient for reactive power corresponding to the τth fluctuation interval; Indicates the total number of fluctuation intervals; Represents a node Total fluctuation of active power from new energy sources; Represents a set of nodes; Represents a node The final reactive power that needs to be adjusted; min indicates taking the minimum value.

9. The method for rapid voltage correction of wide-area new energy fluctuations according to claim 6, characterized in that, When a voltage over-limit occurs in the power system, the reactive power is adjusted in the direction of eliminating the voltage over-limit, as follows: For the node Fluctuation range of active power of new energy Time node No voltage limit was exceeded, but the voltage fluctuated within the specified range. Time-occurring node Operating conditions exceeding voltage limits, within the fluctuation range. The required reactive power regulation is expressed as follows: ； in, Indicates the fluctuation range corresponding nodes Reactive power regulation; Represents a node The upper limit of voltage amplitude; Represents a node Voltage amplitude at the optimal operating point; Represents a node Voltage to node Merit corresponds to the first Sensitivity coefficient for each fluctuation range; node Standard deviation of active power fluctuations in new energy sources; Represents a node Voltage to node i corresponds to the reactive power of the first Sensitivity coefficient for each fluctuation range; Indicates the total number of fluctuation intervals; Represents a node After the fluctuation of active power of new energy, the node The total fluctuation of voltage amplitude; Represents a set of nodes; Indicates the range of fluctuations The set of nodes where the voltage exceeds the limit; Indicates the range of fluctuations The set of nodes where the voltage exceeds the limit; For the node New energy power fluctuation range and Time node All operating conditions resulted in voltage exceeding limits, within the fluctuation range. The required reactive power regulation is expressed as follows: ； in, Represents a node Fluctuations in the active power of new energy sources; For the node Power fluctuation range Time node Under operating conditions where no voltage exceedance occurs, within the fluctuation range The required reactive power regulation is expressed as follows: ； in, Indicates from 1 to 1 The set of any nodes that exceed the limit within the fluctuation range; node The final required reactive power regulation is expressed as follows: ； ； in, To eliminate nodes Node required for voltage over-limit Reactive power regulation; This indicates the elimination of all nodes with voltage exceeding the limit. The final reactive power that needs to be adjusted; max indicates taking the maximum value.

10. A voltage fast correction device for wide-area new energy fluctuations, characterized in that, Including the following: The centralized reactive power optimization module is used to perform centralized reactive power optimization calculations on the power system connected to new energy nodes for a preset time period. It adopts a reactive power optimization model based on voltage safety margin to realize opportunity constraint programming, solves the optimal operating point of the power system within the time period, and controls the power system to operate at the optimal operating point. The analytical expression acquisition module is used to derive analytical expressions for the voltage sensitivity coefficient and the incremental rate of network loss in response to voltage amplitude and phase angle at the optimal operating point. The voltage sensitivity coefficient and network loss incremental rate correction module is used to divide the power fluctuation range when the power fluctuation of the new energy node occurs within the time period, correct the node voltage amplitude and phase angle state according to the power fluctuation range, and substitute the corrected voltage amplitude and phase angle state into the analytical expression of voltage sensitivity coefficient and analytical expression of network loss incremental rate to obtain the corrected voltage sensitivity coefficient and network loss incremental rate. The new energy node correction module is used to calculate the optimal reactive power regulation of each new energy node at each moment within the time period based on the corrected voltage sensitivity coefficient and the incremental rate of network loss, and dynamically adjust the reactive power output of the new energy node to complete the rapid voltage correction.

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