Method and apparatus for optimizing maximum active power of grid-forming-type soft open point, and medium

Abstract

Disclosed in the present invention are a method and apparatus for optimizing the maximum active power of a grid-forming-type soft open point, and a medium. The method comprises: acquiring data information of several transformer areas; by means of performing sensitivity parameter extraction on the data information, constructing node voltages of the several transformer areas; performing calculation on the basis of the node voltages and voltage ranges of the node voltages, so as to obtain a maximum active power proportionality coefficient set of each energy supply port in a soft open point; and on the basis of the maximum active power proportionality coefficient set, respectively controlling the energy supply ports in the soft open point to output active powers, and summarizing same, so as to obtain an optimized maximum active power. Provided in the present invention are a method and apparatus for optimizing the maximum active power of a grid-forming-type soft open point, and a medium. By means of extracting data information of several transformer areas and performing calculation, a maximum active power proportionality coefficient set is constructed to control output active powers of a soft open point, so as to obtain an optimized maximum active power, and thus the problem of it being difficult to make, during the control of transformer areas, a grid-forming-type soft open point output the maximum active power can be solved.

Description

A method, apparatus, and dielectric for optimizing the maximum active power of a grid-type soft switch. Technical Field

[0001] This invention relates to the field of power optimization technology, and in particular to a method, apparatus and medium for optimizing the maximum active power of a grid-type soft switch. Background Technology

[0002] Intelligent soft switches possess multiple functions, including multi-port access, power flow control, renewable energy access, distribution area load forecasting, feeder power flow control, multi-point renewable energy balancing, rapid fault isolation, and voltage support reactive power compensation. They serve as channels for power exchange between different low-voltage distribution areas and are an effective solution for optimizing the physical path of power flow. Intelligent soft switches employing network-based technology can quickly respond to rapid changes in distribution area load and support voltage in areas with weak network structures. However, as the active power of the power supply area increases, the voltage at each load node in that area may decrease, posing a risk of the load voltage falling below the lower limit. Therefore, it is necessary to optimize the maximum active power transmitted by the network-based soft switches to achieve voltage quality balance across distribution areas. Currently, the main approach is to optimize the access location of intelligent soft switches to improve the load transfer capacity of the distribution network, maximizing its load transfer capability and ensuring the flexibility of the distribution network.

[0003] However, existing technologies have not studied the changes in distribution network voltage quality after load transfer. They also require a large amount of data and involve complex parameter update operations and maintenance requirements when the network changes, making it difficult to enable network-type soft switches to effectively output maximum active power.

[0004] Summary of the Invention

[0005] This invention provides a method, apparatus, and medium for optimizing the maximum active power of a network-type soft switch, in order to solve the problem that it is difficult to maximize the output active power of a network-type soft switch in transformer area control.

[0006] To address the above problems, this invention provides a method for optimizing the maximum active power of a network-type soft switch, comprising:

[0007] Obtain data information from several distribution areas of the power grid system;

[0008] By extracting sensitivity parameters from the data information, the node voltages of the several transformer areas are constructed.

[0009] The maximum active power ratio coefficient set of each power supply port in the soft switch is calculated based on the node voltage and the voltage range of the node voltage; wherein, the soft switch is an active power control device constructed by a DC bus and several converters using network-type control technology;

[0010] Based on the maximum active power ratio coefficient set, the active power output of each power supply port in the soft switch is controlled and summed to obtain the optimized maximum active power.

[0011] This invention constructs a maximum active power proportional coefficient set by extracting and calculating parameters from acquired data. Based on this set, the active power at each port of the soft switch is controlled to obtain an optimized maximum output active power. This control method is simple, fast, and highly practical. Specifically, by extracting sensitivity parameters, the influence of voltage variations at any node can be taken into account, improving data utilization and eliminating the need for detailed grid parameters, thus enhancing operational convenience. Furthermore, by calculating the maximum active power proportional coefficient set considering the voltage range of nodes, the active power output can be maximized while maintaining the balance and reliable operation of the distribution area using soft switches, achieving a good optimization effect.

[0012] Compared to existing technologies, this invention extracts and calculates data from several distribution areas to construct a set of maximum active power ratio coefficients, which is then used to control the output active power of soft switches and obtain an optimized maximum active power. This method improves the convenience of operation and maintenance while using a small amount of data, and can ensure the safe and stable operation of the power supply area. It can solve the problem of difficulty in maximizing the output active power of grid-type soft switches in distribution area control.

[0013] As a preferred embodiment, the node voltages of the several transformer areas are constructed by extracting sensitivity parameters from the data information, specifically as follows:

[0014] Based on the voltage and power values ​​of different nodes in the data information, a sensitivity matrix between the load node voltage and the load node active power is constructed.

[0015] The sensitivity matrix is ​​subjected to parameter extraction to obtain the sensitivity parameters;

[0016] Using the aforementioned sensitivity parameters, and combining them with the active power output by the soft switches of the aforementioned distribution areas, the node voltages of the aforementioned distribution areas are obtained.

[0017] In this preferred scheme, due to defects such as inaccurate component parameters, untimely information updates, and difficulty in tracking the operating point of the power grid system and related topology changes, there are usually large measurement errors. Therefore, the sensitivity matrix constructed based on the voltage and power values ​​of different nodes can accurately reflect the relationship between voltage and power changes in the distribution area. Thus, the node voltage calculated on this basis can overcome the defect of inaccurate parameters.

[0018] As a preferred embodiment, based on the voltage and power values ​​of different nodes in the data information, a sensitivity matrix between the load node voltage and the load node active power is constructed, specifically as follows:

[0019] By defining the disturbance of the several transformer areas as the active power of each node, and based on the voltage change and active power change of different nodes in the data information, as well as the preset sensitivity parameter of the load node voltage to the active power of the load node, an expression for the node voltage change based on sensitivity is established.

[0020] The sensitivity matrix between the load node voltage and the active power is obtained by solving the preset node voltage-active power sensitivity matrix and the expression for the node voltage change.

[0021] This preferred scheme is the specific process of constructing a sensitivity matrix. Since the voltage of a medium- and low-voltage distribution network is stable and the network topology is determined, the voltage change of any node is mainly affected by the change of active power injected into each node in the network. Therefore, by defining the disturbance of several transformer areas as the active power of each node, this uncertainty can be directly taken into account, so that the sensitivity matrix built on this basis has a good and complete data foundation. This avoids the disadvantages of difficult data acquisition and complex calculation caused by the need to consider the distribution network parameter information such as input network topology and line parameters, load parameters, system fault parameters, reference voltage and reference power parameters.

[0022] As a preferred embodiment, the maximum active power proportional coefficient set for each power supply port in the soft switch is calculated based on the node voltage and the voltage range of the node voltage, specifically as follows:

[0023] Establish a voltage range constraint formula for the node voltage based on the upper and lower limits of the node voltage;

[0024] The node voltage and the voltage range constraint are combined for calculation to obtain the maximum active power output of the i-th node in the k-th power supply zone when the voltage exceeds the limit; wherein the k-th power supply zone belongs to the plurality of zones, and the i-th node is a plurality of zone nodes connected by the soft switch.

[0025] The maximum active power ratio coefficient set of each power supply port in the soft switch is constructed based on the maximum active power output of the k-th power supply zone.

[0026] In this preferred scheme, if the voltage is too high or too low and exceeds the set limit, the voltage will exceed the limit. Therefore, by calculating the maximum active power output of the kth power supply substation among several substations when the voltage exceeds the limit, the maximum active power output limit of several substation nodes connected to the soft switch can be known. Based on the maximum active power ratio coefficient set calculated on this basis, the active power output can be maximized while using the soft switch to adjust and control the active power to maintain the balance and reliable operation of the substation, thus achieving a good optimization effect.

[0027] As a preferred embodiment, a set of maximum active power proportional coefficients for each power supply port in the soft switch is constructed based on the maximum active power output of the k-th power supply zone, specifically as follows:

[0028] By using an integrated method, the maximum active power set that the several power supply areas can output is constructed based on the maximum active power output of the kth power supply area.

[0029] Based on the sum of the maximum active power corresponding to the nodes of the several distribution areas in the maximum active power set and the maximum active power of each distribution area, the maximum active power ratio coefficient set of each power supply port in the soft switch is calculated.

[0030] As a preferred embodiment, the soft switch employs a network-based control technology, consisting of a DC bus and several converters forming an active power controller, specifically:

[0031] The soft switching is established using a DC bus and several converters corresponding to the aforementioned several transformer areas, employing a network-based control technique.

[0032] The plurality of converters include bidirectional AC / DC converters and bidirectional DC / AC converters.

[0033] The soft switch constructed in this preferred embodiment utilizes a bidirectional AC / DC converter and a bidirectional DC / AC converter, which can convert the power of the battery pack into a DC power supply with stable output voltage and frequency and converge it into the DC bus to ensure the normal output of maximum active power.

[0034] The present invention also provides a maximum active power optimization device for a network-type soft switch, comprising a data module, an extraction module, a coefficient module and an output module;

[0035] The data module is used to obtain data information from several distribution areas of the power grid system.

[0036] The extraction module is used to extract sensitivity parameters from the data information to construct the node voltage of the several transformer areas;

[0037] The coefficient module is used to calculate the maximum active power ratio coefficient set of each power supply port in the soft switch based on the node voltage and the voltage range of the node voltage; wherein, the soft switch is an active power control device constructed by a DC bus and several converters using network-type control technology;

[0038] The output module is used to control the output active power of each power supply port in the soft switch according to the maximum active power ratio coefficient set, and then summarize the output active power to obtain the optimized maximum active power.

[0039] As a preferred embodiment, the extraction module includes a matrix unit, a parameter unit, and a voltage unit;

[0040] The matrix unit is used to construct a sensitivity matrix between the load node voltage and the load node active power based on the voltage and power values ​​of different nodes in the data information.

[0041] The parameter unit is used to extract parameters from the sensitivity matrix to obtain sensitivity parameters;

[0042] The voltage unit is used to obtain the node voltage of the plurality of transformer areas by using the sensitivity parameter and combining it with the active power output by the soft switch of the plurality of transformer areas.

[0043] As a preferred embodiment, the matrix unit includes a first sub-unit and a second sub-unit;

[0044] The first subunit is used to define the disturbance amount of the several transformer areas as the active power of each node, and to establish a sensitivity-based expression for the node voltage change amount based on the voltage change amount and active power change amount of different nodes in the data information, as well as the preset sensitivity parameter of the load node voltage to the active power of the load node.

[0045] The second sub-unit is used to solve the preset node voltage-active power sensitivity matrix and the expression for the node voltage change simultaneously to obtain the sensitivity matrix between the load node voltage and the load node active power.

[0046] As a preferred embodiment, the coefficient module includes a constraint unit, a power unit, and a coefficient unit;

[0047] The constraint unit is used to establish a voltage range constraint formula for the node voltage based on the upper and lower limits of the node voltage.

[0048] The power unit is used to perform simultaneous calculations on the node voltage and the voltage range constraint to obtain the maximum active power output of the i-th node in the k-th power supply zone when the voltage exceeds the limit; wherein, the k-th power supply zone belongs to the plurality of zones, and the i-th node is a plurality of zone nodes connected by the soft switch.

[0049] The coefficient unit is used to construct a set of maximum active power ratio coefficients for each power supply port in the soft switch based on the maximum active power output of the kth power supply zone.

[0050] As a preferred embodiment, the coefficient unit includes a third sub-unit and a fourth sub-unit;

[0051] The third subunit is used to construct the maximum active power set that can be output by the plurality of power supply areas based on the maximum active power output of the kth power supply area through an integration method.

[0052] The fourth subunit is used to calculate the maximum active power ratio coefficient set of each power supply port in the soft switch based on the sum of the maximum active power corresponding to the nodes of the several distribution areas in the maximum active power set and the maximum active power of each distribution area.

[0053] As a preferred embodiment, the coefficient module includes a switching unit;

[0054] The switching unit is used to establish the soft switch using a DC bus and several converters corresponding to the several transformer areas, employing a network-type control technology.

[0055] The plurality of converters include bidirectional AC / DC converters and bidirectional DC / AC converters.

[0056] The present invention also provides a storage medium storing a computer program, which is called and executed by a computer to implement the maximum active power optimization method for a network-type soft switch as described above. Attached Figure Description

[0057] Figure 1 is a flowchart illustrating a method for optimizing the maximum active power of a network-type soft switch according to an embodiment of the present invention.

[0058] Figure 2 is a schematic diagram of a low-voltage distribution area based on intelligent soft-switching interconnection provided in an embodiment of the present invention;

[0059] Figure 3 is a schematic diagram of the maximum active power optimization device for a grid-type soft switch provided in an embodiment of the present invention. Detailed Implementation

[0060] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0061] In the description of this application, it should be understood that the terms "first," "second," "third," and "fourth" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first," "second," "third," and "fourth" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "several" means two or more.

[0062] The maximum active power optimization method for network-type soft switches described in this invention is mainly applied to situations where it is necessary to optimize the maximum active power transmitted by network-type intelligent soft switches in order to achieve voltage quality balance in each distribution area.

[0063] Example 1:

[0064] Please refer to Figure 1. An embodiment of the present invention provides a method for optimizing the maximum active power of a network-type soft switch, including S1 to S4. The specific implementation steps are as follows:

[0065] S1. Obtain data information from several transformer substations from the power grid system.

[0066] Step S1 in this embodiment of the invention specifically includes:

[0067] Data information of several low-voltage distribution areas is obtained from the power grid system; where a distribution area refers to the power supply range or region of a transformer.

[0068] S2. By extracting sensitivity parameters from the data information, the node voltages of several transformer areas are constructed.

[0069] In step S2 of this embodiment of the invention, S2 includes S2.1 to S2.2, specifically as follows:

[0070] S2.1. By defining the disturbance of several low-voltage distribution areas as the active power of each node, and based on the voltage change and active power change of different nodes in the data information, as well as the preset sensitivity parameters of the load node voltage to the active power of the load node, a sensitivity-based expression for the node voltage change is established; wherein, the voltage change and active power change are measured at preset time intervals, preferably 15 minutes.

[0071] By combining the definition of the node voltage-active power sensitivity matrix and the expression for node voltage change, a simultaneous solution is performed to obtain the sensitivity matrix S between the active power of the load nodes. P Specifically, when a load node is equivalent to a power-type load, S P It can be considered that the voltage change is mainly determined by the network architecture of the distribution network and related parameters such as line parameters and transformer parameters, and remains unchanged over a relatively long time scale. Therefore, combined with the expression for the change in node voltage, we can know that: S P Total n 2 One variable, which can be monitored online using U i and P i The data is obtained by solving the node voltage-active power sensitivity matrix n. 2 A linear equation in one variable can be used to obtain the sensitivity matrix S. P ;

[0072] The expression for the node voltage change is as follows:

[0073] Define the node voltage-active power sensitivity matrix as follows:

[0074] Sensitivity Matrix S P The calculation formula is:

[0075] Where n is the total number of nodes on the feeder line (cable) in the low-voltage distribution area, ΔU i Let ΔP be the voltage change at the i-th node on the feeder. i S represents the change in active power at the i-th node; Pji Let U be the voltage U of the i-th load node on the feeder to be solved. i The active power P of the j-th load node j Sensitivity,

[0076] This embodiment describes the specific process of constructing a sensitivity matrix. Since the voltage of a medium- and low-voltage distribution network is stable and the network topology is determined, the voltage change of any node is mainly affected by the change of active power of each node injected into the network. Therefore, by defining the disturbance of several distribution areas as the active power of each node, this uncertainty can be directly taken into account, so that the sensitivity matrix built on this basis has a good and complete data foundation. This avoids the disadvantages of difficult data acquisition and complex calculation caused by the need to consider the distribution network parameter information such as input network topology and line parameters, load parameters, system fault parameters, reference voltage and reference power parameters.

[0077] Furthermore, the sensitivity matrix can be updated in real time based on the data from online detection, which helps to automatically allocate the active power of each power supply port of the soft switch when supporting the voltage of the transformer substation, thus improving the convenience of operation and maintenance.

[0078] S2.2. Based on the access node of the soft switch, adjust the sensitivity matrix S. P Parameter extraction is performed to obtain the sensitivity parameter {S}. Pj1 ,...,S Pjn};

[0079] Using the sensitivity parameter {S} Pj1 ,...,S Pjn By combining the active power output of several low-voltage distribution areas through soft switching, the node voltages of several low-voltage distribution areas can be obtained.

[0080] The node voltages are:

[0081] U i (t+1)=U i (t)+S Pji ·ΔP i

[0082] Among them, U i (t) and U i (t+1) represents the active power ΔP output by the transformer area through soft switching. i The active power ΔP before and after output i The voltage at the i-th node.

[0083] Among them, soft switching is an active power control device constructed from a DC bus and several converters using network-based control technology. Soft switching is also called intelligent soft switching, specifically:

[0084] Using a DC bus and several converters corresponding to several low-voltage substations, soft switching is established based on network technology;

[0085] Among them, several converters include bidirectional AC / DC converters and bidirectional DC / AC converters.

[0086] To apply the embodiments of the present invention, please refer to Figure 2. Figure 2 is a schematic diagram of a low-voltage distribution area based on intelligent soft switch interconnection provided by the embodiments of the present invention, showing the structure of the intelligent soft switch (soft switch);

[0087] As shown in Figure 2, the intelligent soft switch mainly consists of three converters and a DC bus, as shown in the dashed box. #1 to #3 are the converter numbers, which are essentially bidirectional AC / DC converters (i.e., power can flow in both directions). The first two converters are connected to AC low-voltage zone 1 and low-voltage zone 2, respectively, and the symbol "AC / DC" is used to indicate the interface nature of the first two converters. The third converter is connected to AC low-voltage zone 3, and the symbol "DC / AC" is used to indicate the interface nature of the third converter. Furthermore, the DC interfaces of all three converters are connected to the DC bus.

[0088] From an overall perspective, step S2 of this embodiment is usually subject to large measurement errors due to defects such as inaccurate component parameters, untimely information updates, and difficulty in tracking the operating point of the power grid system and related topology changes. Therefore, the sensitivity matrix constructed based on the voltage and power values ​​of different nodes can accurately reflect the relationship between voltage and power changes in the distribution area. Thus, the node voltage calculated on this basis can overcome the defect of inaccurate parameters.

[0089] S3. Calculate the maximum active power ratio coefficient set of each power supply port in the soft switch based on the node voltage and the voltage range of the node voltage; whereby the soft switch is an active power control device constructed by a DC bus and several converters using network-type control technology.

[0090] In step S3 of this embodiment of the invention, S3 includes S3.1 to S3.3, specifically as follows:

[0091] S3.1 Establish the voltage range constraint formula for the node voltage based on the upper and lower limits of the node voltage;

[0092] The voltage range constraint formula is as follows:

[0093] U min ≤U i (t+1)≤U max

[0094] Among them, U max and U min These represent the upper and lower limits of the node voltage, respectively. It should be noted that in the low-voltage distribution area, the upper limit of the voltage at the i-th node is U. imax =1.07U NOM The lower voltage limit of the i-th node is U. imin =0.9U NOM U NOM This is the nominal voltage.

[0095] S3.2. Perform simultaneous calculations on the node voltage and voltage range constraints to obtain the maximum active power ΔP emitted by the i-th node in the k-th power supply zone when the voltage exceeds the limit. ki_maxAnd obtain the maximum active power that the power supply area can output; where the kth power supply area belongs to several power supply areas, and the i-th node is the node of the power supply area connected by the soft switch.

[0096] The maximum active power that the kth low-voltage power supply zone can output is:

[0097] ΔP k_max =min{ΔP k1_max ,...,ΔP ki_max ,...,ΔP kn_max ,P sop_max}

[0098] Among them, P sop_max This refers to the rated usable power of the soft-switching port.

[0099] S3.3, Using an integrated method, based on the maximum active power ΔP emitted by the kth power supply zone. k_max Construct a set of maximum active power outputs for several transformer substations;

[0100] Based on the sum of the maximum active power corresponding to several transformer area nodes in the maximum active power concentration and the maximum active power of each transformer area, the set of maximum active power ratio coefficients for each power supply port in the soft switch is calculated.

[0101] Among them, the maximum active power ΔP that each transformer area can output is max for:

[0102] Among them, the maximum active power proportion coefficient K in the maximum active power proportion coefficient set ΔPl for:

[0103] K ΔPl =ΔP l_max / ΔP max

[0104] Wherein, ΔP l_max The maximum active power that the l-th low-voltage distribution area can output is denoted as l; l belongs to 1 to N-1, where N is the number of distribution areas connected by the soft switch, of which 1 distribution area receives active power and the other N-1 are power supply distribution areas.

[0105] In this embodiment, if the voltage is too high or too low and exceeds the set limit, the voltage will exceed the limit. Therefore, by calculating the maximum active power output of the kth power supply substation among several substations when the voltage exceeds the limit, the maximum active power output limit of several substation nodes connected to the soft switch can be known. Based on the maximum active power ratio coefficient set calculated on this basis, the active power output can be maximized while using the soft switch to adjust and control the active power to maintain the balance and reliable operation of the substation, thus achieving a good optimization effect.

[0106] Furthermore, the soft switch constructed in this embodiment utilizes a bidirectional AC / DC converter and a bidirectional DC / AC converter, which can convert the power of the battery pack into a DC power supply with stable output voltage and frequency and converge it into the DC bus, ensuring the normal output of maximum active power.

[0107] S4. Based on the maximum active power proportional coefficient set, control the output active power of each power supply port in the soft switch and summarize them to obtain the optimized maximum active power.

[0108] Step S4 in this embodiment of the invention is specifically as follows:

[0109] Using the maximum active power ratio coefficients from the maximum active power ratio coefficient set as weights, based on the original active power output of each power supply port in the soft switch, the output active power of each corresponding power supply port in the soft switch is controlled by superimposing the change in active power, and the active power output of each power supply port is summarized to the DC bus to obtain the optimized maximum active power.

[0110] Overall, the embodiments of the present invention have the following beneficial effects:

[0111] This embodiment extracts and calculates parameters from the acquired data to construct a maximum active power ratio coefficient set. Based on this, the output of the soft switch is controlled to obtain the optimized maximum active power. This control method is simple, fast, and highly practical. Specifically, by extracting sensitivity parameters, the influencing factors of voltage changes at any node can be taken into account, improving data utilization and eliminating the need for detailed grid parameter information, thus enhancing the convenience of operation and maintenance. Furthermore, by calculating the maximum active power ratio coefficient set considering the voltage range of nodes, the active power output can be maximized while using soft switches to regulate and control active power to maintain the balance and reliable operation of the distribution area, achieving a good optimization effect.

[0112] Compared with the load transfer capacity maximization calculation method, this embodiment estimates and sets the limit and weight coefficient of the active power provided by each power supply area when supporting the voltage of other power supply areas, which can ensure the safe and stable operation of the power supply areas. At the same time, the use of online detection data can update the sensitivity matrix in real time without the need to input data information of distribution network parameters, which improves the convenience of operation and maintenance.

[0113] Example 2:

[0114] Please refer to Figure 3. An embodiment of the present invention provides a maximum active power optimization device for a network-type soft switch, including a data module 10, an extraction module 20, a coefficient module 30, and an output module 40.

[0115] Among them, data module 10 is used to obtain data information of several distribution areas from the power grid system;

[0116] Extraction module 20 is used to extract sensitivity parameters from data information to construct the node voltage of several transformer areas;

[0117] The coefficient module 30 is used to calculate the maximum active power proportional coefficient set of each power supply port in the soft switch based on the node voltage and the voltage range of the node voltage; wherein, the soft switch is an active power control device constructed by a DC bus and several converters using network-type control technology.

[0118] The output module 40 is used to control the output active power of each power supply port in the soft switch according to the maximum active power ratio coefficient set and to summarize the output active power to obtain the optimized maximum active power.

[0119] In one embodiment, data module 10 specifically comprises:

[0120] Data information of several low-voltage distribution areas is obtained from the power grid system; where a distribution area refers to the power supply range or region of a transformer.

[0121] In one embodiment, the extraction module 20 includes a first sub-unit, a second sub-unit, a parameter unit, a voltage unit, and a switching unit;

[0122] The first subunit is used to define the disturbance of several low-voltage distribution areas as the active power of each node, and to establish a sensitivity-based expression for the node voltage change based on the voltage change and active power change of different nodes in the data information, as well as the preset sensitivity parameters of the load node voltage to the load node active power; wherein the voltage change and active power change are measured at preset time intervals, preferably 15 minutes.

[0123] The second sub-unit is used to combine the definition of the node voltage-active power sensitivity matrix and the expression for node voltage change to perform a simultaneous solution, thereby obtaining the sensitivity matrix S between the active power of the load nodes. P Specifically, when a load node is equivalent to a power-type load, S P It can be considered that the voltage change is mainly determined by the network architecture of the distribution network and related parameters such as line parameters and transformer parameters, and remains unchanged over a relatively long time scale. Therefore, combined with the expression for the change in node voltage, we can know that: S P Total n 2 One variable, which can be monitored online using U i and P i The data is obtained by solving the node voltage-active power sensitivity matrix n. 2 A linear equation in one variable can be used to obtain the sensitivity matrix S.P ;

[0124] The expression for the node voltage change is as follows:

[0125] Define the node voltage-active power sensitivity matrix as follows:

[0126] Sensitivity Matrix S P The calculation formula is:

[0127] Where n is the total number of nodes on the feeder line (cable) in the low-voltage distribution area, ΔU i Let ΔP be the voltage change at the i-th node on the feeder. i S represents the change in active power at the i-th node; Pji Let U be the voltage U of the i-th load node on the feeder to be solved. i The active power P of the j-th load node j Sensitivity,

[0128] This embodiment describes the specific process of constructing a sensitivity matrix. Since the voltage of a medium- and low-voltage distribution network is stable and the network topology is determined, the voltage change of any node is mainly affected by the change of active power of each node injected into the network. Therefore, by defining the disturbance of several distribution areas as the active power of each node, this uncertainty can be directly taken into account, so that the sensitivity matrix built on this basis has a good and complete data foundation. This avoids the disadvantages of difficult data acquisition and complex calculation caused by the need to consider the distribution network parameter information such as input network topology and line parameters, load parameters, system fault parameters, reference voltage and reference power parameters.

[0129] Furthermore, the sensitivity matrix can be updated in real time based on the data from online detection, which helps to automatically allocate the active power of each power supply port of the soft switch when supporting the voltage of the transformer substation, thus improving the convenience of operation and maintenance.

[0130] The parameter unit is used to adjust the sensitivity matrix S according to the access node of the soft switch. P Parameter extraction is performed to obtain the sensitivity parameter {S}. Pj1 ,...,S Pjn};

[0131] Voltage unit, used to apply sensitivity parameter {S} Pj1 ,...,S Pjn By combining the active power output of several low-voltage distribution areas through soft switching, the node voltages of several low-voltage distribution areas can be obtained.

[0132] The node voltages are:

[0133] Ui (t+1)=U i (t)+S Pji ·ΔP i

[0134] Among them, U i (t) and U i (t+1) represents the active power ΔP output by the transformer area through soft switching. i The active power ΔP before and after output i The voltage at the i-th node.

[0135] Among them, soft switching is an active power control device constructed from a DC bus and several converters using network-type control technology, and soft switching is also called intelligent soft switching.

[0136] The architecture of soft switching is a switching unit, which specifically consists of:

[0137] Using a DC bus and several converters corresponding to several low-voltage substations, soft switching is established based on network technology;

[0138] Among them, several converters include bidirectional AC / DC converters and bidirectional DC / AC converters.

[0139] To apply the embodiments of the present invention, please refer to Figure 2. Figure 2 is a schematic diagram of a low-voltage distribution area based on intelligent soft switch interconnection provided by the embodiments of the present invention, showing the structure of the intelligent soft switch (soft switch);

[0140] As shown in Figure 2, the intelligent soft switch mainly consists of three converters and a DC bus within the dashed box.

[0141] #1 to #3 are the converter numbers, and they are all essentially bidirectional AC / DC converters (i.e., power can flow in both directions). The first two converters are connected to AC low-voltage section 1 and low-voltage section 2 respectively, and the symbol "AC / DC" is used to indicate the interface nature of the first two converters. The third converter is connected to AC low-voltage section 3, and the symbol "DC / AC" is used to indicate the interface nature of the third converter. Furthermore, the DC interfaces of all three converters are connected to the DC bus.

[0142] From an overall perspective, step S2 of this embodiment is usually subject to large measurement errors due to defects such as inaccurate component parameters, untimely information updates, and difficulty in tracking the operating point of the power grid system and related topology changes. Therefore, the sensitivity matrix constructed based on the voltage and power values ​​of different nodes can accurately reflect the relationship between voltage and power changes in the distribution area. Thus, the node voltage calculated on this basis can overcome the defect of inaccurate parameters.

[0143] In one embodiment, the coefficient module 30 includes a constraint unit, a power unit, a third sub-unit, and a fourth sub-unit;

[0144] Among them, the constraint unit is used to establish the voltage range constraint formula of the node voltage based on the upper limit and lower limit of the node voltage;

[0145] The voltage range constraint formula is as follows:

[0146] U min ≤U i (t+1)≤U max

[0147] Among them, U max and U min These represent the upper and lower limits of the node voltage, respectively. It should be noted that in the low-voltage distribution area, the upper limit of the voltage at the i-th node is U. imax =1.07U NOM The lower voltage limit of the i-th node is U. imin =0.9U NOM U NOM This is the nominal voltage.

[0148] The power unit is used to perform simultaneous calculations on node voltage and voltage range constraints to obtain the maximum active power ΔP emitted by the i-th node in the k-th power supply zone when the voltage exceeds the limit. ki_max And obtain the maximum active power that the power supply area can output; where the kth power supply area belongs to several power supply areas, and the i-th node is the node of the power supply area connected by the soft switch.

[0149] The maximum active power that the kth low-voltage power supply zone can output is:

[0150] ΔP k_max =min{ΔP k1_max ,...,ΔP ki_max ,...,ΔP kn_max ,P sop_max}

[0151] Among them, P sop_max This refers to the rated usable power of the soft-switching port.

[0152] The third subunit is used to integrate the active power output of the k-th power supply zone, based on the maximum value ΔP. ki_max Construct a set of maximum active power outputs for several transformer substations;

[0153] The fourth subunit is used to calculate the maximum active power ratio coefficient set of each power supply port in the soft switch based on the sum of the maximum active power corresponding to several transformer nodes in the maximum active power set and the maximum active power of each transformer.

[0154] Among them, the maximum active power ΔP that each transformer area can output is max for:

[0155] Among them, the maximum active power proportion coefficient K in the maximum active power proportion coefficient set ΔPl for:

[0156] K ΔPl =ΔP l_max / ΔP max

[0157] Wherein, ΔP l_max The maximum active power that the l-th low-voltage distribution area can output is denoted as l; l belongs to 1 to N-1, where N is the number of distribution areas connected by the soft switch, of which 1 distribution area receives active power and the other N-1 are power supply distribution areas.

[0158] In this embodiment, if the voltage is too high or too low and exceeds the set limit, the voltage will exceed the limit. Therefore, by calculating the maximum active power output of the kth power supply substation among several substations when the voltage exceeds the limit, the maximum active power output limit of several substation nodes connected to the soft switch can be known. Based on the maximum active power ratio coefficient set calculated on this basis, the active power output can be maximized while using the soft switch to adjust and control the active power to maintain the balance and reliable operation of the substation, thus achieving a good optimization effect.

[0159] Furthermore, the soft switch constructed in this embodiment utilizes a bidirectional AC / DC converter and a bidirectional DC / AC converter, which can convert the power of the battery pack into a DC power supply with stable output voltage and frequency and converge it into the DC bus, ensuring the normal output of maximum active power.

[0160] In one embodiment, the output module 40 is specifically:

[0161] Using the maximum active power ratio coefficients from the maximum active power ratio coefficient set as weights, based on the original active power output of each power supply port in the soft switch, the output active power of each corresponding power supply port in the soft switch is controlled by superimposing the change in active power, and the active power output of each power supply port is summarized to the DC bus to obtain the optimized maximum active power.

[0162] Overall, the embodiments of the present invention have the following beneficial effects:

[0163] This embodiment extracts and calculates parameters from the acquired data to construct a maximum active power ratio coefficient set. Based on this, the output of the soft switch is controlled to obtain the optimized maximum active power. This control method is simple, fast, and highly practical. Specifically, by extracting sensitivity parameters, the influencing factors of voltage changes at any node can be taken into account, improving data utilization and eliminating the need for detailed grid parameter information, thus enhancing the convenience of operation and maintenance. Furthermore, by calculating the maximum active power ratio coefficient set considering the voltage range of nodes, the active power output can be maximized while using soft switches to regulate and control active power to maintain the balance and reliable operation of the distribution area, achieving a good optimization effect.

[0164] Compared with the load transfer capacity maximization calculation method, this embodiment estimates and sets the limit and weight coefficient of the active power provided by each power supply area when supporting the voltage of other power supply areas, which can ensure the safe and stable operation of the power supply areas. At the same time, the use of online detection data can update the sensitivity matrix in real time without the need to input data information of distribution network parameters, which improves the convenience of operation and maintenance.

[0165] Example 3:

[0166] This invention also provides a computer-readable storage medium, which includes a stored computer program, wherein the computer program controls the device where the computer-readable storage medium is located to execute the aforementioned method for optimizing the maximum active power of a network-type soft switch when it is running.

[0167] One method for optimizing the maximum active power of a network-type soft switch, if implemented as a software functional unit and used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0168] The above are preferred embodiments of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for optimizing the maximum active power of a network-type soft switch, characterized in that, include: Obtain data information from several distribution areas of the power grid system; By extracting sensitivity parameters from the data information, the node voltages of the several transformer areas are constructed. The maximum active power ratio coefficient set of each power supply port in the soft switch is calculated based on the node voltage and the voltage range of the node voltage; wherein, the soft switch is an active power control device constructed by a DC bus and several converters using network-type control technology; Based on the maximum active power ratio coefficient set, the active power output of each power supply port in the soft switch is controlled and summed to obtain the optimized maximum active power.

2. The method for optimizing the maximum active power of a network-type soft switch as described in claim 1, characterized in that, By extracting sensitivity parameters from the data information, the node voltages of the several transformer areas are constructed, specifically as follows: Based on the voltage and power values ​​of different nodes in the data information, a sensitivity matrix between the load node voltage and the load node active power is constructed. The sensitivity matrix is ​​subjected to parameter extraction to obtain the sensitivity parameters; Using the aforementioned sensitivity parameters, and combining them with the active power output by the soft switches of the aforementioned distribution areas, the node voltages of the aforementioned distribution areas are obtained.

3. The method for optimizing the maximum active power of a network-type soft switch as described in claim 2, characterized in that, Based on the voltage and power values ​​of different nodes in the data information, a sensitivity matrix between the load node voltage and the load node active power is constructed, specifically as follows: By defining the disturbance of the several transformer areas as the active power of each node, and based on the voltage change and active power change of different nodes in the data information, as well as the preset sensitivity parameter of the load node voltage to the active power of the load node, an expression for the node voltage change based on sensitivity is established. Combine the preset node voltage-active power sensitivity matrix with the expression for the node voltage change. Solving for the sensitivity matrix between the load node voltage and the load node active power yields the result.

4. The method for optimizing the maximum active power of a network-type soft switch as described in claim 1, characterized in that, The maximum active power proportional coefficient set for each power supply port in the soft switch is calculated based on the node voltage and the voltage range of the node voltage, specifically as follows: Establish a voltage range constraint formula for the node voltage based on the upper and lower limits of the node voltage; The node voltage and the voltage range constraint are combined for calculation to obtain the maximum active power output of the i-th node in the k-th power supply zone when the voltage exceeds the limit; wherein the k-th power supply zone belongs to the plurality of zones, and the i-th node is a plurality of zone nodes connected by the soft switch. The maximum active power ratio coefficient set of each power supply port in the soft switch is constructed based on the maximum active power output of the k-th power supply zone.

5. The method for optimizing the maximum active power of a grid-type soft switch as described in claim 4, characterized in that, Based on the maximum active power output of the k-th power supply zone, a set of maximum active power proportional coefficients for each power supply port in the soft switch is constructed, specifically as follows: By using an integrated method, the maximum active power set that the several power supply areas can output is constructed based on the maximum active power output of the kth power supply area. Based on the sum of the maximum active power corresponding to the nodes of the several distribution areas in the maximum active power set and the maximum active power of each distribution area, the maximum active power ratio coefficient set of each power supply port in the soft switch is calculated.

6. The method for optimizing the maximum active power of a network-type soft switch as described in claim 1, characterized in that, The soft switch is an active power control device constructed using grid-based control technology, consisting of a DC bus and several converters, specifically: The soft switching is established using a DC bus and several converters corresponding to the aforementioned several transformer areas, employing a network-based control technique. The plurality of converters include bidirectional AC / DC converters and bidirectional DC / AC converters.

7. A maximum active power optimization device for a grid-type soft switch, characterized in that, It includes a data module, an extraction module, a coefficient module, and an output module; The data module is used to obtain data information from several distribution areas of the power grid system. The extraction module is used to extract sensitivity parameters from the data information to construct the node voltage of the several transformer areas; The coefficient module is used to calculate the maximum active power ratio coefficient set of each power supply port in the soft switch based on the node voltage and the voltage range of the node voltage; wherein, the soft switch is an active power control device constructed by a DC bus and several converters using network-type control technology; The output module is used to control the output active power of each power supply port in the soft switch according to the maximum active power ratio coefficient set, and then summarize the output active power to obtain the optimized maximum active power.

8. The maximum active power optimization device for a grid-type soft switch as described in claim 7, characterized in that, The extraction module includes a matrix unit, a parameter unit, and a voltage unit; The matrix unit is used to construct a sensitivity matrix between the load node voltage and the load node active power based on the voltage and power values ​​of different nodes in the data information. The parameter unit is used to extract parameters from the sensitivity matrix to obtain sensitivity parameters; The voltage unit is used to obtain the node voltage of the plurality of transformer areas by using the sensitivity parameter and combining it with the active power output by the soft switch of the plurality of transformer areas.

9. The maximum active power optimization device for a grid-type soft switch as described in claim 8, characterized in that, The matrix unit includes a first sub-unit and a second sub-unit; The first subunit is used to define the disturbance amount of the several transformer areas as the active power of each node, and to establish a sensitivity-based expression for the node voltage change amount based on the voltage change amount and active power change amount of different nodes in the data information, as well as the preset sensitivity parameter of the load node voltage to the active power of the load node. The second subunit is used to combine the preset node voltage-active power sensitivity matrix with the node voltage. The simultaneous solution of the expressions for the changes yields the sensitivity matrix between the load node voltage and the load node active power.

10. The maximum active power optimization device for a grid-type soft switch as described in claim 7, characterized in that, The coefficient module includes a constraint unit, a power unit, and a coefficient unit; The constraint unit is used to establish a voltage range constraint formula for the node voltage based on the upper and lower limits of the node voltage. The power unit is used to perform simultaneous calculations on the node voltage and the voltage range constraint to obtain the maximum active power output of the i-th node in the k-th power supply zone when the voltage exceeds the limit; wherein, the k-th power supply zone belongs to the plurality of zones, and the i-th node is a plurality of zone nodes connected by the soft switch. The coefficient unit is used to construct a set of maximum active power ratio coefficients for each power supply port in the soft switch based on the maximum active power output of the kth power supply zone.

11. The maximum active power optimization device for a grid-type soft switch as described in claim 10, characterized in that, The coefficient unit includes a third sub-unit and a fourth sub-unit; The third subunit is used to construct the maximum active power set that can be output by the plurality of power supply areas based on the maximum active power output of the kth power supply area through an integration method. The fourth subunit is used to calculate the maximum active power ratio coefficient set of each power supply port in the soft switch based on the sum of the maximum active power corresponding to the nodes of the several distribution areas in the maximum active power set and the maximum active power of each distribution area.

12. The maximum active power optimization device for a grid-type soft switch as described in claim 7, characterized in that, The coefficient module includes a switching unit; The switching unit is used to establish the soft switch using a DC bus and several converters corresponding to the several transformer areas, employing a network-type control technology. The plurality of converters include bidirectional AC / DC converters and bidirectional DC / AC converters.

13. A storage medium, characterized in that, The storage medium stores a computer program, which is called and executed by a computer to implement the maximum active power optimization method for any of the network-type soft switches as described in claims 1 to 6.

Images