Bus voltage situation assessment method and system considering new energy grid connection

Abstract

The invention discloses a bus voltage situation assessment method and system considering new energy grid connection, and the method comprises the steps: considering the randomness and prediction precision of new energy according to the current development situation of the new energy, and mining the influence of the new energy on the deterioration of the voltage of a power grid based on the historical operation data of the new energy and a prediction precision analysis method; and evaluating a bus voltage deviation severity factor, comprehensively considering information such as a direct current plan and load prediction, and evaluating the voltage situation change of the power grid. Technical support is provided for automatic voltage control and reactive compensation equipment configuration planning, scheduling personnel are assisted to comprehensively master the power grid voltage change situation under new energy grid connection, and the power grid voltage scheduling level is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system operation and control, and in particular relates to a bus voltage situation assessment method and system considering new energy grid connection. Background Art

[0002] With the large-scale grid connection of new energy on the distribution network side, the voltage operation status of the power grid has deteriorated sharply, the difficulty of voltage regulation has increased, and the risk of safe operation of the power grid has increased, especially on the low-voltage distribution network side, where the voltage operation quality has dropped sharply. In addition, the voltage disturbance in the high-voltage DC area caused by the active power plan adjustment has further aggravated the voltage operation risk of the power grid, and the risk of new energy being disconnected from the grid has increased sharply. Summary of the invention

[0003] Purpose of the invention: In view of the problems disclosed in the background technology, the present invention provides a bus voltage situation assessment method and system considering the connection of new energy to the grid, so as to evaluate the voltage situation of the new energy power grid. The bus voltage situation assessment can comprehensively consider the impact of various factors on the voltage, assess the severity of voltage changes, and thus grasp the overall safe operation of the power grid voltage, provide a calculation basis for the weak degree of local power grid voltage, and provide technical support for modules such as automatic voltage control safety decision-making and reactive resource allocation planning.

[0004] Technical solution: First, a bus voltage situation assessment method considering the connection of new energy to the grid:

[0005] Obtain ultra-short-term load forecast information and new energy station forecast data; extract historical forecast data from the historical operation database to evaluate the bus voltage deviation severity factor;

[0006] The bus voltage variation trend is evaluated by combining the bus voltage deviation severity factor, ultra-short-term load forecast information, new energy station forecast data, and active power data in the DC plan formulated on demand.

[0007] Furthermore, historical forecast data is extracted from the historical operation database to evaluate the severity factors of bus voltage deviation, including:

[0008] Evaluate the random bus voltage deviation severity factor based on historical data samples of historical forecast data;

[0009] Evaluate the severity factor of bus voltage deviation based on the historical accuracy of historical forecast data;

[0010] The random bus voltage deviation severity factor and the predicted bus voltage deviation severity factor are combined to evaluate the bus voltage deviation severity factor.

[0011] Furthermore, the bus voltage deviation severity factor is expressed as:

[0012] λ=μh λ h +(1-μ h ) p μ h ∈[0,1]

[0013] where λ h is the random bus voltage deviation severity factor, λ p To predict the bus voltage deviation severity factor, μ h Calculate the weight for the random bus voltage deviation severity factor.

[0014] Furthermore, the random bus voltage deviation severity factor evaluated by historical data samples based on historical forecast data is expressed as:

[0015] λ h =w1(V(P DG,1 ,P DG,2 …,P DG,n ))+w2(N(P DG,1 ,P DG,2 …,P DG,n ))

[0016] +w3(D(P DG,1 ,P DG,2 …,P DG,n ))w1,w2,w3∈(0,1)

[0017] Where n is the maximum number of historical sampling data points for a new energy active power measurement point at a certain moment, P DG,1 ,P DG,2 …,P DG,n is the active power value of the new energy at the 1st, 2nd…, nth historical sampling points of the same sample at a certain moment, V is the variance of the new energy active power sampling data, N is the normal distribution of the new energy active power sampling data, D is the divergence of the new energy active power sampling data, w1, w2, w3 are the weight values ​​of the variance, normal distribution and divergence of the historical data.

[0018] Furthermore, the bus voltage deviation severity factor is estimated based on the historical accuracy of historical prediction data and is expressed as:

[0019]

[0020] Where k is the serial number of a new energy active power measurement point, m is the maximum number of sampling points of a new energy active power measurement point at a certain moment, P DG,k is the kth actual active power collection value of a new energy source, is the kth predicted active power value of a new energy source, g k is the exact weight of the kth active power prediction value.

[0021] Furthermore, the bus voltage variation trend is evaluated by combining the bus voltage deviation severity factor, ultra-short-term load forecast information, new energy station forecast data, and active data in the DC plan formulated on demand; the ultra-short-term load forecast information includes node load, the new energy station forecast data includes new energy output, and the active data in the DC plan includes DC output. The voltage forecast value at the jth moment in the future is expressed as:

[0022]

[0023] Among them, i is the number of the prediction node, j is the number of the predicted future time series, and t i,0 is the current time of the i-th prediction node, t i,j is the jth moment in the future of the ith prediction node, V L (t i,0 ) is the current voltage value of the i-th node, P L (t i,0 ), P D (t i,0 ), P DG (t i,0 ) are the node load, DC output and new energy output of the section at the current moment, are the node load, DC output and new energy output of the section at the jth moment in the future, λ is the bus voltage deviation severity factor, They are the active-voltage sensitivity of node load, DC output and renewable energy output to node voltage respectively.

[0024] In a second aspect, a bus voltage situation assessment system considering new energy grid connection is provided, the system comprising a bus voltage deviation severity factor calculation module and a bus voltage situation assessment module;

[0025] The bus voltage deviation severity factor calculation module extracts historical prediction data from the historical operation database to evaluate the bus voltage deviation severity factor;

[0026] The bus voltage situation assessment module obtains ultra-short-term load forecast information and new energy station forecast data; combines the bus voltage deviation severity factor, ultra-short-term load forecast information and new energy station forecast data and the active power data in the DC plan formulated on demand to assess the bus voltage change situation.

[0027] Furthermore, the bus voltage deviation severity factor calculation module evaluates the random bus voltage deviation severity factor based on the historical data samples of the historical prediction data; evaluates the predicted bus voltage deviation severity factor based on the historical accuracy of the historical prediction data; and evaluates the bus voltage deviation severity factor by comprehensively evaluating the random bus voltage deviation severity factor and the predicted bus voltage deviation severity factor.

[0028] Furthermore, the bus voltage deviation severity factor is expressed as:

[0029] λ=μ h λ h +(1-μ h ) p μ h ∈[0,1]

[0030] where λ h is the random bus voltage deviation severity factor, λ p To predict the bus voltage deviation severity factor, μ h Calculate the weight for the random bus voltage deviation severity factor.

[0031] Furthermore, the random bus voltage deviation severity factor is expressed as:

[0032] λ h =w1(V(P DG,1 ,P DG,2 …,P DG,n ))+w2(N(P DG,1 ,P DG,2 …,P DG,n ))

[0033] +w3(D(P DG,1 ,P DG,2 …,P DG,n ))w1,w2,w3∈(0,1)

[0034] Where n is the maximum number of historical sampling data points for a new energy active power measurement point at a certain moment, P DG,1 ,P DG,2 …,P DG,n is the active power value of the new energy at the 1st, 2nd…, nth historical sampling points of the same sample at a certain moment, V is the variance of the new energy active power sampling data, N is the normal distribution of the new energy active power sampling data, D is the divergence of the new energy active power sampling data, w1, w2, w3 are the weight values ​​of the variance, normal distribution and divergence of the historical data.

[0035] Furthermore, the predicted bus voltage deviation severity factor is expressed as:

[0036]

[0037] Where k is the serial number of a new energy active power measurement point, m is the maximum number of sampling points of a new energy active power measurement point at a certain moment, P DG,k is the kth actual active power collection value of a new energy source, is the kth predicted active power value of a new energy source, g k is the exact weight of the kth active power prediction value.

[0038] Furthermore, the bus voltage variation trend is evaluated by combining the bus voltage deviation severity factor, ultra-short-term load forecast information, new energy station forecast data, and active power data in the DC plan formulated on demand; the ultra-short-term load forecast information includes node load, the new energy station forecast data includes new energy output, and the active power data in the DC plan includes DC output;

[0039] The voltage prediction value at the jth moment in the future is expressed as:

[0040]

[0041] Among them, i is the number of the prediction node, j is the number of the predicted future time series, and t i,0 is the current time of the i-th prediction node, t i,j is the jth moment in the future of the ith prediction node, V L (t i,0 ) is the current voltage value of the i-th node, P L (t i,0 ), P D (t i,0 ), P DG (t i,0 ) are the node load, DC output and new energy output of the section at the current moment, are the node load, DC output and new energy output of the section at the jth moment in the future, λ is the bus voltage deviation severity factor, They are the active-voltage sensitivity of node load, DC output and renewable energy output to node voltage respectively.

[0042] Beneficial effects: The present invention comprehensively evaluates the degree of deterioration of grid voltage operation, grasps the overall grid voltage safety level, understands the weak points of local grid voltage operation, and provides technical support for automatic voltage control, reactive power support capacity assessment, reactive power resource allocation planning, network reconstruction, and maximum absorption of new energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 is a flow chart of the method of the present invention;

[0044] Figure 2 It is a structural diagram of the system of the present invention. DETAILED DESCRIPTION

[0045] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0046] Embodiment 1:

[0047] like Figure 1As shown, the present invention provides a technical solution: a bus voltage situation assessment method considering the connection of new energy to the grid:

[0048] Obtain ultra-short-term load forecast information and new energy station forecast data; extract historical forecast data from the historical operation database to evaluate the bus voltage deviation severity factor;

[0049] The bus voltage variation trend is evaluated by combining the bus voltage deviation severity factor, ultra-short-term load forecast information, new energy station forecast data, and active power data in the DC plan formulated on demand.

[0050] Preferably, historical forecast data is extracted from the historical operation database to evaluate the bus voltage deviation severity factor, including:

[0051] Evaluate the random bus voltage deviation severity factor based on historical data samples of historical forecast data;

[0052] Evaluate the severity factor of bus voltage deviation based on the historical accuracy of historical forecast data;

[0053] The random bus voltage deviation severity factor and the predicted bus voltage deviation severity factor are combined to evaluate the bus voltage deviation severity factor.

[0054] Preferably, the bus voltage deviation severity factor is expressed as:

[0055] λ=μ h λ h +(1-μ h ) p μ h ∈[0,1]

[0056] where λ h is the random bus voltage deviation severity factor, λ p To predict the bus voltage deviation severity factor, μ h Calculate the weight for the random bus voltage deviation severity factor.

[0057] Preferably, the random bus voltage deviation severity factor evaluated based on historical data samples of historical forecast data is expressed as:

[0058] λ h =w1(V(P DG,1 ,P DG,2 …,P DG,n ))+w2(N(P DG,1 ,P DG,2 …,P DG,n ))

[0059] +w3(D(P DG,1 ,P DG,2…,P DG,n ))w1,w2,w3∈(0,1)

[0060] Where n is the maximum number of historical sampling data points for a new energy active power measurement point at a certain moment, P DG,1 ,P DG,2 …,P DG,n is the active power value of the new energy at the 1st, 2nd…, nth historical sampling points of the same sample at a certain moment, V is the variance of the new energy active power sampling data, N is the normal distribution of the new energy active power sampling data, D is the divergence of the new energy active power sampling data, w1, w2, w3 are the weight values ​​of the variance, normal distribution and divergence of the historical data.

[0061] Preferably, the bus voltage deviation severity factor is predicted based on the historical accuracy evaluation of the historical prediction data, expressed as:

[0062]

[0063] Where k is the serial number of a new energy active power measurement point, m is the maximum number of sampling points of a new energy active power measurement point at a certain moment, P DG,k is the kth actual active power collection value of a new energy source, is the kth predicted active power value of a new energy source, g k is the exact weight of the kth active power prediction value.

[0064] Preferably, the bus voltage variation trend is evaluated by combining the bus voltage deviation severity factor, the ultra-short-term load forecast information, the new energy station forecast data, and the active data in the DC plan formulated on demand; wherein the ultra-short-term load forecast information includes the node load, the new energy station forecast data includes the new energy output, and the active data in the DC plan includes the DC output. The voltage forecast value at the jth moment in the future is expressed as:

[0065]

[0066] Among them, i is the number of the prediction node, j is the number of the predicted future time series, and t i,0 is the current time of the i-th prediction node, t i,j is the jth moment in the future of the ith prediction node, V L (t i,0 ) is the current voltage value of the i-th node, P L (t i,0 ), P D (t i,0 ), P DG (t i,0 ) are the node load, DC output and new energy output of the section at the current moment, are the node load, DC output and new energy output of the section at the jth moment in the future, λ is the bus voltage deviation severity factor, They are the active-voltage sensitivity of node load, DC output and renewable energy output to node voltage respectively.

[0067] Embodiment 2:

[0068] like Figure 2 As shown, a bus voltage situation assessment system considering the connection of new energy to the grid, the system includes a bus voltage deviation severity factor calculation module and a bus voltage situation assessment module;

[0069] The bus voltage deviation severity factor calculation module extracts historical prediction data from the historical operation database to evaluate the bus voltage deviation severity factor;

[0070] The bus voltage situation assessment module obtains ultra-short-term load forecast information and new energy station forecast data; combines the bus voltage deviation severity factor, ultra-short-term load forecast information and new energy station forecast data and the active power data in the DC plan formulated on demand to assess the bus voltage change situation.

[0071] Preferably, the bus voltage deviation severity factor calculation module evaluates the random bus voltage deviation severity factor based on historical data samples of historical prediction data; evaluates the predicted bus voltage deviation severity factor based on the historical accuracy of historical prediction data; and evaluates the bus voltage deviation severity factor by comprehensively evaluating the random bus voltage deviation severity factor and the predicted bus voltage deviation severity factor.

[0072] Preferably, the bus voltage deviation severity factor is expressed as:

[0073] λ=μ h λ h +(1-μ h ) p μ h ∈[0,1]

[0074] where λ h is the random bus voltage deviation severity factor, λ p To predict the bus voltage deviation severity factor, μ h Calculate the weight for the random bus voltage deviation severity factor.

[0075] Preferably, the random bus voltage deviation severity factor is expressed as:

[0076] λ h =w1(V(P DG,1 ,P DG,2 …,P DG,n ))+w2(N(PDG,1 ,P DG,2 …,P DG,n ))

[0077] +w3(D(P DG,1 ,P DG,2 …,P DG,n ))w1,w2,w3∈(0,1)

[0078] Where n is the maximum number of historical sampling data points for a new energy active power measurement point at a certain moment, P DG,1 ,P DG,2 …,P DG,n is the active power value of the new energy at the 1st, 2nd…, nth historical sampling points of the same sample at a certain moment, V is the variance of the new energy active power sampling data, N is the normal distribution of the new energy active power sampling data, D is the divergence of the new energy active power sampling data, w1, w2, w3 are the weight values ​​of the variance, normal distribution and divergence of the historical data.

[0079] Preferably, the predicted bus voltage deviation severity factor is expressed as:

[0080]

[0081] Where k is the serial number of a new energy active power measurement point, m is the maximum number of sampling points of a new energy active power measurement point at a certain moment, P DG,k is the kth actual active power collection value of a new energy source, is the kth predicted active power value of a new energy source, g k is the exact weight of the kth active power prediction value.

[0082] Preferably, the bus voltage variation trend is evaluated by combining the bus voltage deviation severity factor, ultra-short-term load forecast information, new energy station forecast data, and active data in the DC plan prepared on demand; wherein the ultra-short-term load forecast information includes node load, the new energy station forecast data includes new energy output, and the active data in the DC plan includes DC output;

[0083] The voltage prediction value at the jth moment in the future is expressed as:

[0084]

[0085] Among them, i is the number of the prediction node, j is the number of the predicted future time series, and t i,0 is the current time of the i-th prediction node, t i,j is the jth moment in the future of the ith prediction node, V L (t i,0 ) is the current voltage value of the i-th node, P L (t i,0 ), PD (t i,0 ), P DG (t i,0 ) are the node load, DC output and new energy output of the section at the current moment, are the node load, DC output and new energy output of the section at the jth moment in the future, λ is the bus voltage deviation severity factor, They are the active-voltage sensitivity of node load, DC output and renewable energy output to node voltage respectively.

[0086] The present invention discloses a bus voltage situation assessment method and system considering the grid connection of new energy. The present invention is based on the current status of new power system construction with large-scale grid connection of new energy in the current power grid, based on the historical operation data and prediction information of new energy, assesses the deteriorating influence of the randomness and prediction accuracy of new energy on the voltage change of the power grid, and then assesses the bus voltage change situation in the future based on the information of ultra-short-term load, DC plan, new energy prediction, etc., so that the dispatching and operating personnel can fully grasp the voltage change trend of the power grid, provide technical support for automatic voltage control, reactive power support capacity assessment, reactive power resource allocation planning, network reconstruction, maximum absorption of new energy, etc., and effectively improve the voltage dispatching level of the power grid.

[0087] A bus voltage status assessment method considering the connection of new energy to the grid mainly considers the impact of changes in the active power of the power grid on the bus voltage status. In the actual operation of the power grid, the reactive load of the power grid has a huge impact on the grid voltage. After large-scale reactive power consumption occurs in the power grid (such as the air conditioning load absorbing a large amount of reactive power in summer), the reactive support capacity of the power grid becomes more strained. This method needs to superimpose the impact of reactive load on voltage.

[0088] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

[0089] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0090] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the lightweight power load forecasting method as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0091] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0092] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present application difficult to understand, the known power supply / ground connection with the integrated circuit (IC) chip and other components may or may not be shown in the provided drawings. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented in the embodiments of the present application (that is, these details should be fully within the scope of understanding of those skilled in the art). In the case of elaborating specific details (e.g., circuits) to describe exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0093] Although the present application has been described in conjunction with specific embodiments of the present application, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

Claims

1. A bus voltage situation assessment method considering new energy grid connection, characterized in that: include: Obtain ultra-short-term load forecast information and new energy station forecast data; extract historical forecast data from the historical operation database to evaluate the bus voltage deviation severity factor; The bus voltage variation trend is evaluated by combining the bus voltage deviation severity factor, ultra-short-term load forecast information, new energy station forecast data, and active power data in the DC plan formulated on demand.

2. A bus voltage situation assessment method considering new energy grid connection according to claim 1, characterized in that: Extract historical forecast data from the historical operation database to evaluate the severity factors of bus voltage deviation, including: Evaluate the random bus voltage deviation severity factor based on historical data samples of historical forecast data; Evaluate the severity factor of bus voltage deviation based on the historical accuracy of historical forecast data; The random bus voltage deviation severity factor and the predicted bus voltage deviation severity factor are combined to evaluate the bus voltage deviation severity factor.

3. A bus voltage situation assessment method considering new energy grid connection according to claim 2, characterized in that: The bus voltage deviation severity factor is expressed as: λ=μ h l h +(1-m h )l p m h ∈[0,1] where λ h is the random bus voltage deviation severity factor, λ p To predict the bus voltage deviation severity factor, μ h Calculate the weight for the random bus voltage deviation severity factor.

4. A bus voltage situation assessment method considering new energy grid connection according to claim 3, characterized in that: The random bus voltage deviation severity factor is evaluated based on the historical data samples of new energy forecast based on historical forecast data, expressed as: λ h =w1(V(P DG,1 ,P DG,2 …,P DG,n ))+w2(N(P DG,1 ,P DG,2 …,P DG,n ))+w3(D(P DG,1 ,P DG,2 …,P DG,n ))w1,w2,w3∈(0,1) Where n is the maximum number of historical sampling data points for a new energy active power measurement point at a certain moment, P DG,1 ,P DG,2 …,P DG,n is the active power value of the new energy at the 1st, 2nd…, nth historical sampling points of the same sample at a certain moment, V is the variance of the new energy active power sampling data, N is the normal distribution of the new energy active power sampling data, D is the divergence of the new energy active power sampling data, w1, w2, w3 are the weight values ​​of the variance, normal distribution and divergence of the historical data.

5. A bus voltage situation assessment method considering new energy grid connection according to claim 3, characterized in that: The historical accuracy of historical prediction data is used to evaluate the severity factor of the predicted bus voltage deviation, which is expressed as: Where k is the serial number of a new energy active power measurement point, m is the maximum number of sampling points of a new energy active power measurement point at a certain moment, P DG,k is the kth actual active power collection value of a new energy source, is the kth predicted active power value of a new energy source, g k is the exact weight of the kth active power prediction value.

6. A bus voltage situation assessment method considering new energy grid connection according to claim 1, characterized in that: Combine the bus voltage deviation severity factor, ultra-short-term load forecast information, new energy station forecast data, and active data in the DC plan formulated on demand to evaluate the bus voltage change trend; the ultra-short-term load forecast information includes node load, the new energy station forecast data includes new energy output, and the active data in the DC plan includes DC output; The voltage prediction value at the jth moment in the future is expressed as: Among them, i is the number of the prediction node, j is the number of the predicted future time series, and t i,0 is the current time of the i-th prediction node, t i,j is the jth moment in the future of the ith prediction node, V L (t i,0 ) is the current voltage value of the i-th node, P L (t i,0 ), P D (t i,0 ), P DG (t i,0 ) are the node load, DC output and new energy output of the section at the current moment, are the node load, DC output and new energy output of the section at the future jth moment, λ is the bus voltage deviation severity factor, They are the active-voltage sensitivity of node load, DC output and renewable energy output to node voltage respectively.

7. A bus voltage situation assessment system considering new energy grid connection, characterized in that: The system includes a bus voltage deviation severity factor calculation module and a bus voltage situation assessment module; The bus voltage deviation severity factor calculation module extracts historical prediction data from the historical operation database to evaluate the bus voltage deviation severity factor; The bus voltage situation assessment module obtains ultra-short-term load forecast information and new energy station forecast data; combines the bus voltage deviation severity factor, ultra-short-term load forecast information and new energy station forecast data and the active power data in the DC plan formulated on demand to assess the bus voltage change situation.

8. A bus voltage situation assessment system considering new energy grid connection according to claim 7, characterized in that: The bus voltage deviation severity factor calculation module evaluates the random bus voltage deviation severity factor based on historical data samples of historical prediction data; evaluates the predicted bus voltage deviation severity factor based on the historical accuracy of historical prediction data; and evaluates the bus voltage deviation severity factor by comprehensively considering the random bus voltage deviation severity factor and the predicted bus voltage deviation severity factor.

9. A bus voltage situation assessment system considering new energy grid connection according to claim 8, characterized in that: The bus voltage deviation severity factor is expressed as: λ=μ h l h +(1-m h )l p m h ∈[0,1] where λ h is the random bus voltage deviation severity factor, λ p To predict the bus voltage deviation severity factor, μ h Calculate the weight for the random bus voltage deviation severity factor.

10. A bus voltage situation assessment system considering new energy grid connection according to claim 9, characterized in that: The random bus voltage deviation severity factor is expressed as: λ h =w1(V(P DG,1 ,P DG,2 …,P DG,n ))+w2(N(P DG,1 ,P DG,2 …,P DG,n ))+w3(D(P DG,1 ,P DG,2 …,P DG,n ))w1,w2,w3∈(0,1) Where n is the maximum number of historical sampling data points for a new energy active power measurement point at a certain moment, P DG,1 ,P DG,2 …,P DG,n is the active power value of the new energy at the 1st, 2nd…, nth historical sampling points of the same sample at a certain moment, V is the variance of the new energy active power sampling data, N is the normal distribution of the new energy active power sampling data, D is the divergence of the new energy active power sampling data, w1, w2, w3 are the weight values ​​of the variance, normal distribution and divergence of the historical data.

11. A bus voltage situation assessment system considering new energy grid connection according to claim 9, characterized in that: The predicted bus voltage deviation severity factor is expressed as: Where k is the serial number of a new energy active power measurement point, m is the maximum number of sampling points of a new energy active power measurement point at a certain moment, P DG,k is the kth actual active power collection value of a new energy source, is the kth predicted active power value of a new energy source, g k is the exact weight of the kth active power prediction value.

12. A bus voltage situation assessment system considering new energy grid connection according to claim 7, characterized in that: Combine the bus voltage deviation severity factor, ultra-short-term load forecast information, new energy station forecast data, and active data in the DC plan formulated on demand to evaluate the bus voltage change trend; the ultra-short-term load forecast information includes node load, the new energy station forecast data includes new energy output, and the active data in the DC plan includes DC output; The voltage prediction value at the jth moment in the future is expressed as: Among them, i is the number of the prediction node, j is the number of the predicted future time series, and t i,0 is the current time of the i-th prediction node, t i,j is the jth moment in the future of the ith prediction node, V L (t i,0 ) is the current voltage value of the i-th node, P L (t i,0 ), P D (t i,0 ), P DG (t i,0 ) are the node load, DC output and new energy output of the section at the current moment, are the node load, DC output and new energy output of the section at the future jth moment, λ is the bus voltage deviation severity factor, They are the active-voltage sensitivity of node load, DC output and renewable energy output to node voltage respectively.

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