Low-voltage transformer area distributed photovoltaic regulation and control resource margin aggregation method and system

Abstract

The invention discloses a low-voltage transformer area distributed photovoltaic regulation and control resource margin aggregation method and system, the transformer area voltage sensitivity index adopted by the method significantly reduces the dependence on the power grid topology information, is closer to the actual application scene of the low-voltage transformer area, only needs to process the electric energy meter data in the transformer area, greatly reduces the calculation amount, and improves the calculation efficiency. The method is more suitable for limited computing power of edge equipment. Moreover, the theoretical aggregation margin of the transformer area is accurately calculated according to the current generated power and the current voltage of all the photovoltaic users, and the overall adjustable margin of the transformer area can be accurately evaluated. Meanwhile, a target function is constructed with maximization of the margin utilization rate and minimization of the voltage deviation as optimization targets, full utilization of the photovoltaic adjustable margin of the transformer area is achieved while the safety of the power grid voltage is guaranteed, it is guaranteed that side equipment can provide enough adjustable resources, margin waste is avoided, and the method is suitable for large-scale popularization and application. The accuracy and reliability of distributed photovoltaic regulation and control are improved, and complex and changeable distributed photovoltaic regulation and control scenes can be effectively dealt with.

Description

Technical Field

[0001] The present invention relates to the field of distributed photovoltaic control technology, and in particular to a method and system for aggregating control resource margins of distributed photovoltaics in low-voltage areas, electronic equipment, and a computer-readable storage medium. Background Art

[0002] Renewable energy output is highly random and intermittent, often connected to the distribution network in a densely distributed, fragmented manner. This network is characterized by numerous points, a wide coverage area, and high penetration rates. The disorderly grid connection of large-scale distributed power sources can cause problems such as backflow and voltage fluctuations, requiring active distribution networks to effectively regulate these distributed power sources. Accurate statistics of controllable resources in low-voltage substations are essential for the operation of distributed photovoltaic systems. Precise resource aggregation ensures reliable responses to control commands from the master station.

[0003] However, existing resource aggregation methods rely too much on centralized models and ignore local real-time security constraints and policy requirements, resulting in the "adjustable margin" calculated by the cloud being higher than the actual situation. The generated control instructions do not match the actual capabilities and compliance of the edge. The actual controllable space of the edge equipment is insufficient to meet the cloud instructions, and thus cannot provide sufficient adjustable resources, which may lead to control failure. For example, the Chinese patent application with application number CN202411909735.6 discloses a distributed resource aggregation management method, which constructs the economic benefits of the aggregation area as the objective function, and then derives the target output curve of each photovoltaic power station. This technical solution does not take into account the voltage safety issues and compliance during actual operation, but only considers the maximization of economic benefits. It cannot alleviate the impact of the current large-scale distributed power access on the power grid. The generated control instructions do not match the actual capabilities and compliance of the edge, which may lead to control failure. Summary of the Invention

[0004] The present invention provides a method and system for aggregating the control resource margin of distributed photovoltaic power generation in a low-voltage substation, an electronic device, and a computer-readable storage medium. This method not only ensures that the side equipment can provide sufficient controllable resources, but also avoids margin waste, improves the accuracy and reliability of distributed photovoltaic control, and can effectively cope with complex and changeable distributed photovoltaic control scenarios.

[0005] According to one aspect of the present invention, a method for aggregating control resource margins for distributed photovoltaic systems in a low-voltage area is provided, comprising the following:

[0006] Obtain historical electrical data for all users in the low-voltage area and calculate the area voltage sensitivity between users in the area. The area voltage sensitivity refers to the relationship between the voltage difference between a user's energy meter and the area's total energy meter and the power of other users' energy meters in the area.

[0007] Obtain the current power generation and voltage of all photovoltaic users in the substation area, and calculate the theoretical aggregation margin of the substation area;

[0008] The objective function is constructed with maximizing margin utilization and minimizing voltage deviation as the optimization goals. The relationship between voltage and power is constructed based on the voltage sensitivity of the substation area, and the power of photovoltaic users is constrained by voltage constraints.

[0009] The particle swarm algorithm is used to optimize the objective function and generate power control instructions for all photovoltaic users based on the optimal solution.

[0010] Furthermore, the voltage sensitivity of the substation is calculated based on the following formula:

[0011]

[0012] Among them, S ij represents the voltage sensitivity between the i-th user node and the j-th user node in the substation, and S ij Equal to S ji , ΔV1, ΔV2...ΔV N Indicates the difference between the voltage of each user in the substation area and the total voltage of the substation area, P i Represents the power of the i-th user node in the station area.

[0013] Furthermore, the process of obtaining the current power generation and current voltage of all photovoltaic users in the substation area and calculating the theoretical aggregation margin of the substation area includes the following:

[0014] Determine the basic margin of each photovoltaic user based on whether they have participated in regulation;

[0015] The basic margin of each photovoltaic user is corrected according to its current voltage to obtain an adjustable margin;

[0016] The theoretical aggregate margin of the substation is obtained by summing up the adjustable margins of all photovoltaic users.

[0017] Furthermore, the basic margin of each photovoltaic user is determined based on the following formula:

[0018]

[0019] Where ΔP i represents the basic margin of the i-th photovoltaic user, P set,i represents the rated power of the inverter connected to the i-th photovoltaic user, P i represents the current power generation of the i-th photovoltaic user, and λ represents the lower limit parameter of the inverter connected to the i-th photovoltaic user.

[0020] Furthermore, the basic margin is corrected based on the following formula:

[0021]

[0022] Where ΔP range,i represents the adjustable margin of the i-th photovoltaic user, ΔP i Represents the basic margin of the i-th photovoltaic user, V max and V min They represent the voltage upper limit and voltage lower limit of the i-th photovoltaic user, V i Represents the current voltage value of the i-th photovoltaic user, V nom Indicates the rated voltage value.

[0023] Furthermore, the objective function is expressed as:

[0024]

[0025] Among them, N represents the number of users in the low-voltage area, n represents the number of photovoltaic users in the low-voltage area, V act,i Represents the voltage value of the i-th user after regulation, V nom Indicates the rated voltage value, P act,i represents the power generation of the i-th photovoltaic user after regulation, P i represents the current power generation of the i-th photovoltaic user, The theoretical aggregation margin of the station area, ΔP range，i represents the adjustable margin of the i-th photovoltaic user, and α represents the preset proportional weight coefficient.

[0026] Furthermore, the power of photovoltaic users is constrained by voltage constraints based on the following formula:

[0027]

[0028] in, and Respectively represent the maximum and minimum values that the user voltage can be regulated, V top Indicates the total meter voltage value of the substation, N indicates the number of users in the low-voltage substation, S ij represents the voltage sensitivity between the i-th user node and the j-th user node in the area, P j Represents the power value of the jth user node in the low-voltage area.

[0029] In addition, the present invention also provides a low-voltage distributed photovoltaic control resource margin aggregation system, comprising:

[0030] The substation voltage sensitivity calculation module is used to obtain the historical electrical data of all users in the low-voltage substation and calculate the substation voltage sensitivity between each user in the substation. The substation voltage sensitivity refers to the relationship between the voltage difference between the power meter of a user in the substation and the substation master meter and the power of the power meters of other users in the substation;

[0031] The theoretical aggregation margin calculation module of the substation area is used to obtain the current power generation and current voltage of all photovoltaic users in the substation area and calculate the theoretical aggregation margin of the substation area;

[0032] The objective function construction module is used to construct the objective function with the optimization goals of maximizing margin utilization and minimizing voltage deviation. It also constructs the relationship between voltage and power based on the voltage sensitivity of the substation area and constrains the power of photovoltaic users through voltage constraints.

[0033] The optimization solution and power control module is used to optimize the objective function using the particle swarm algorithm and generate power control instructions for all photovoltaic users based on the optimal solution.

[0034] In addition, the present invention also provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the processor is configured to execute the steps of the above method by calling the computer program stored in the memory.

[0035] In addition, the present invention also provides a computer-readable storage medium for storing a computer program for performing resource margin aggregation for distributed photovoltaic regulation in low-voltage areas. When the computer program is run on a computer, the steps of the method described above are executed.

[0036] The present invention has the following beneficial effects:

[0037] The method for aggregating the control resource margin of distributed photovoltaics in low-voltage areas of the present invention uses an area voltage sensitivity index to characterize the relationship between the voltage difference between a user's electric energy meter and the area's total meter in the area and the power of other users' electric energy meters in the area. Compared with the voltage sensitivity index commonly used in this field, this index can significantly reduce the dependence on grid topology information, and is closer to the actual application scenario of low-voltage areas. Moreover, it only needs to process the electric energy meter data in the low-voltage area, and the amount of calculation is greatly reduced. It is more suitable for the limited computing power of edge devices, which is conducive to achieving rapid response to photovoltaic output fluctuations and load changes, and improving the real-time performance of control. In addition, the theoretical aggregation margin of the area is accurately calculated based on the current power generation power and current voltage of all photovoltaic users in the area, which can accurately evaluate the overall adjustable margin of the low-voltage area. At the same time, the objective function is constructed with maximizing margin utilization and minimizing voltage deviation as the optimization goals, which ensures the voltage safety of the power grid while fully utilizing the adjustable margin of photovoltaic power generation in the substation. This not only ensures that the side equipment can provide sufficient adjustable resources, but also avoids margin waste, improves the accuracy and reliability of distributed photovoltaic control, and can effectively cope with complex and changeable distributed photovoltaic control scenarios.

[0038] In addition, the low-voltage distributed photovoltaic resource margin aggregation system of the present invention also has the above advantages.

[0039] In addition to the above-described objects, features and advantages, the present invention has other objects, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0041] Figure 1 This is a flow chart of a method for aggregating resource margins for distributed photovoltaics in a low-voltage area according to a preferred embodiment of the present application;

[0042] Figure 2 yes Figure 1 Schematic diagram of the sub-process of step S2;

[0043] Figure 3 It is a schematic diagram of the module structure of a low-voltage distributed photovoltaic control resource margin aggregation system according to another embodiment of the present application. DETAILED DESCRIPTION

[0044] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0045] Reference Figure 1 The preferred embodiment of the present application provides a method for aggregating the control resource margin of distributed photovoltaic power generation in a low-voltage area, including the following contents:

[0046] Step S1: Obtain historical electrical data of all users in the low-voltage area and calculate the area voltage sensitivity between each user in the area. The area voltage sensitivity refers to the relationship between the voltage difference between a user's energy meter and the area's total energy meter in the area and the power of the energy meters of other users in the area.

[0047] Step S2: Obtain the current power generation and current voltage of all photovoltaic users in the substation area, and calculate the theoretical aggregation margin of the substation area;

[0048] Step S3: Construct an objective function with maximizing margin utilization and minimizing voltage deviation as optimization goals, and construct a relationship between voltage and power based on the voltage sensitivity of the substation area, and constrain the power of photovoltaic users through voltage constraints;

[0049] Step S4: The particle swarm algorithm is used to optimize and solve the objective function, and power control instructions for all photovoltaic users are generated according to the optimal solution.

[0050] It can be understood that the resource margin aggregation method for distributed photovoltaic control in low-voltage areas of this embodiment uses the area voltage sensitivity index to characterize the relationship between the voltage difference between the electric energy meter of a certain user in the area and the total meter of the area and the power of the electric energy meters of other users in the area. Compared with the voltage sensitivity index commonly used in this field, this index can significantly reduce the dependence on the topology information of the power grid, and is closer to the actual application scenario of the low-voltage area. Moreover, it only needs to process the electric energy meter data in the low-voltage area, and the amount of calculation is greatly reduced. It is more suitable for the limited computing power of edge devices, which is conducive to achieving rapid response to photovoltaic output fluctuations and load changes, and improving the real-time performance of control. In addition, the theoretical aggregation margin of the area is accurately calculated based on the current power generation power and current voltage of all photovoltaic users in the area, which can accurately evaluate the overall adjustable margin of the low-voltage area. At the same time, the objective function is constructed with maximizing margin utilization and minimizing voltage deviation as the optimization goals, which ensures the voltage safety of the power grid while fully utilizing the adjustable margin of photovoltaic power generation in the substation. This not only ensures that the side equipment can provide sufficient adjustable resources, but also avoids margin waste, improves the accuracy and reliability of distributed photovoltaic control, and can effectively cope with complex and changeable distributed photovoltaic control scenarios.

[0051] Among them, the existing voltage sensitivity refers to the response degree of the voltage of a node in the power grid to the power change in the power grid. The calculation of the voltage sensitivity index depends on the complete power grid topology data, such as line impedance, transformer parameters, etc. However, in the actual low-voltage substation, the accuracy of these data cannot be guaranteed. For example, line aging will cause impedance changes, new loads are added but the topology information is not updated in time, etc., and it requires a complex calculation model and a large amount of computing resources, which is difficult to meet the needs of real-time regulation. Therefore, in the step S1, the present invention only focuses on the internal relationship of the substation, that is, only considers the line conditions in the substation, does not consider the line conditions on the high-voltage side of the substation transformer, and the resistance of the line in the substation is much greater than the reactance, constructing a new indicator: substation voltage sensitivity, which specifically refers to the relationship between the voltage difference between the electric energy meter of a certain user in the substation and the substation total meter and the power of the electric energy meters of other users in the substation, that is, the response degree of the voltage difference between the voltage of a certain user in the substation and the voltage of the substation total meter to the power changes of other users in the substation.

[0052] Specifically, the historical voltage data and historical power data of all users in the low-voltage area are obtained, and the voltage sensitivity of the area is calculated based on the following formula:

[0053]

[0054] Among them, S ij represents the voltage sensitivity between the i-th user node and the j-th user node in the substation, and S ij Equal to S ji , ΔV1, ΔV2...ΔV N Indicates the difference between the voltage of each user in the substation area and the total voltage of the substation area, P i Represents the power of the i-th user node in the station area.

[0055] It can be understood that the substation voltage sensitivity index of the present invention can significantly reduce the dependence on grid topology information compared to the voltage sensitivity index commonly used in this field, and is closer to the actual application scenarios of low-voltage substations. Moreover, it only needs to process the electricity meter data in the low-voltage substation, and the amount of calculation is greatly reduced. It is more suitable for the limited computing power of edge devices, which is conducive to achieving rapid response to photovoltaic output fluctuations and load changes, and improving the real-time performance of regulation.

[0056] In addition, if Figure 2 As shown, in step S2, the process of obtaining the current power generation and current voltage of all photovoltaic users in the substation area and calculating the theoretical aggregation margin of the substation area includes the following:

[0057] Step S21: determining the basic margin of each photovoltaic user based on whether the user has participated in the regulation;

[0058] Step S22: Correcting the basic margin of each photovoltaic user according to its current voltage to obtain an adjustable margin;

[0059] Step S23: performing sum calculation based on the adjustable margins of all photovoltaic users to obtain the theoretical aggregate margin of the substation.

[0060] Specifically, there are two states for photovoltaic users in the substation area: controlled and uncontrolled. Controlled means that the photovoltaic users have participated in the regulation, and uncontrolled means that the photovoltaic users have not participated in the regulation. For photovoltaic users that are not participating in the regulation (i.e., currently generating electricity at maximum capacity), there is only a downward adjustment margin, which can be expressed as: ΔP i =P i -P min,i , P min,i =λP set,i For PV users that have participated in the regulation (i.e., not generating electricity at maximum capacity), there is an upward adjustment margin and a downward adjustment margin. The upward adjustment margin is the difference between the rated power of the inverter connected to the PV user and the current power generation power, which can be expressed as: P set,i -P i , the downward adjustment margin is the difference between the current power generation of the photovoltaic user and the minimum power generation, which can be expressed as: P i -P min,i , where, , then the adjustable margin is the sum of the upward margin and the downward margin: P set,i -λP set,i =P set,i (1-λ). Therefore, the present invention determines the basic margin of each photovoltaic user based on the following formula:

[0061]

[0062] Where ΔP i represents the basic margin of the i-th photovoltaic user, P set,i represents the rated power of the inverter connected to the i-th photovoltaic user, P i represents the current power generation of the i-th PV user, and λ represents the lower limit parameter of the inverter connected to the i-th PV user. It is determined by the brand of the inverter. For example, if the active power percentage supported by a certain brand of inverter is 10% to 100%, then λ is set to 10%.

[0063] It can be understood that the theoretical aggregate margin of the substation refers to the sum of the adjustable margins of all distributed photovoltaics in the entire substation. In this field, the adjustable margin of each photovoltaic user is generally defined as the difference between the upper and lower limits of its adjustable power. The present invention calculates the basic margin of each photovoltaic user based on whether each photovoltaic user has participated in regulation, which better combines the actual situation and improves the accuracy of the calculation of the theoretical aggregate margin of the substation.

[0064] The basic margin obtained by the above calculation is the theoretical maximum adjustable margin for each photovoltaic user. However, after the photovoltaic user's power generation is regulated, its voltage will change, and voltage safety problems may occur. The actual adjustable margin cannot reach the theoretical maximum adjustable margin. Therefore, the present invention also takes into account the voltage safety factor to reduce the basic margin. If the current voltage value of the photovoltaic user deviates from the rated voltage value less, that is, the probability of voltage safety problems is greater, then the degree of reduction of the basic margin is greater, that is, the photovoltaic user is not allowed to perform large-scale power regulation. If the current voltage value of the photovoltaic user deviates from the rated voltage value more, the probability of voltage safety problems is lower at this time, then the degree of reduction of the basic margin is smaller, that is, the photovoltaic user is allowed to perform large-scale power regulation. Specifically, the basic margin is corrected based on the following formula:

[0065]

[0066] Where ΔP range,i represents the adjustable margin of the i-th photovoltaic user, ΔP i Represents the basic margin of the i-th photovoltaic user, V max and V min They represent the voltage upper limit and voltage lower limit of the i-th photovoltaic user, V i Represents the current voltage value of the i-th photovoltaic user, V nom Indicates the rated voltage. The rated voltage for non-PV users within a low-voltage area is generally 220V. The rated voltage for PV users is typically higher than that for non-PV users, and is typically multiplied by a factor of 1.05. Furthermore, if a PV user is a designated user, its adjustable margin is set to 0, meaning it is not regulated.

[0067] Finally, the adjustable margin ΔP of all photovoltaic users is calculated range,i Finally, the theoretical aggregate margin of the area can be obtained by summing up the adjustable margins of all photovoltaic users. n represents the number of photovoltaic users in the low-voltage area.

[0068] It can be understood that the present invention first calculates the basic margin of each photovoltaic user based on whether he or she has participated in the regulation, and then reduces the basic margin taking into account the voltage safety factor. Moreover, the less the current voltage value of the photovoltaic user deviates from the rated voltage value, the greater the reduction, and the more it deviates from the rated voltage value, the smaller the reduction. This can effectively prevent voltage safety problems caused by power regulation of photovoltaic users, and improve the accuracy of the calculation of the theoretical aggregation margin of the substation.

[0069] In addition, in step S3, an objective function is constructed with maximizing margin utilization and minimizing voltage deviation as optimization goals. The purpose of minimizing voltage deviation is to ensure grid voltage safety, and the purpose of maximizing margin utilization is to maximize the utilization of the photovoltaic adjustable margin in the substation area, avoid margin waste, meet the basic principle of "maximum generation when possible", and improve the photovoltaic absorption rate. Specifically, the expression of the objective function is:

[0070]

[0071] Among them, N represents the number of users in the low-voltage area, n represents the number of photovoltaic users in the low-voltage area, V act,i Represents the voltage value of the i-th user after regulation, V nom Indicates the rated voltage value, P act,i represents the power generation of the i-th photovoltaic user after regulation, P i represents the current power generation of the i-th photovoltaic user, The theoretical aggregation margin of the station area, ΔP range，i represents the adjustable margin of the i-th photovoltaic user, and α represents the preset proportional weight coefficient, which ranges from (10,100).

[0072] It can be understood that the present invention constructs the objective function with maximizing margin utilization and minimizing voltage deviation as the optimization goals, and realizes the full utilization of the photovoltaic adjustable margin in the substation while ensuring the voltage safety of the power grid. It not only ensures that the side equipment can provide sufficient adjustable resources, but also avoids margin waste, improves the accuracy and reliability of distributed photovoltaic control, and can effectively cope with complex and changeable distributed photovoltaic control scenarios.

[0073] In addition, due to the small coverage area of the low-voltage substation, the changes in the internal flow are mainly affected by the load and distributed photovoltaics within the substation. The influence of users outside the substation on the flow within the substation is relatively weak. Therefore, the influence of users outside the substation on the flow within the substation can be ignored, and the control of distributed photovoltaics can be solved directly based on the relationship between the flow and voltage. Specifically, in the line of the low-voltage substation, the voltage drop ΔV is mainly determined by the line resistance and current, that is, ΔV=I×R. According to the relationship between current and power: I=P / V, the voltage drop can be expressed as: ΔV=P×R / V, that is, the voltage drop is proportional to the power. Therefore, the calculation matrix of the substation voltage sensitivity is transformed to obtain:

[0074]

[0075] The voltage sensitivity of the station area S ij Describes the linear relationship between the voltage of the i-th user node and the power of the j-th user node, so we can get: Then the voltage value V of the i-th user node can be calculated i , V i =V top -ΔV i In the voltage safety constraint, the voltage of low-voltage users has a maximum threshold value. and minimum threshold Therefore, the power of photovoltaic users is constrained by voltage constraints based on the following formula:

[0076]

[0077] in, and Respectively represent the maximum and minimum values that the user voltage can be regulated, V top Indicates the total meter voltage value of the substation, N indicates the number of users in the low-voltage substation, S ij represents the voltage sensitivity between the i-th user node and the j-th user node in the area, P j Indicates the power value of the jth user node in the low-voltage area. In addition, for different users in the low-voltage area, such as photovoltaic users and non-photovoltaic users, and The values can be the same or different and can be set according to actual needs.

[0078] It can be understood that the present invention first calculates the substation voltage sensitivity between each user node based on historical data, and then calculates the impact of the power adjustment of the photovoltaic user at the current moment on the user's own voltage and the voltage of other users. Based on the substation voltage sensitivity, a voltage-power safety constraint is constructed to constrain the power of the photovoltaic user. The existing technology usually ignores that changes in photovoltaic output will cause changes in its own voltage and the voltage of other users, thereby ignoring the substation voltage safety.

[0079] In addition, the constraints also include the total power constraint of the low-voltage area. Specifically, the total power constraint of the low-voltage area must take into account the rated capacity setting of the transformer, which can be expressed as:

[0080]

[0081] Among them, P k and Q K denote the active power and reactive power of the kth user respectively, and Respectively represent the minimum active power and maximum active power of the low-voltage transformer. and They represent the minimum reactive power and maximum reactive power of the low-voltage transformer, and They respectively represent the minimum apparent power and maximum apparent power of the low-voltage transformer.

[0082] In addition, the constraints also include power factor constraints, which can be expressed as: That is, the vector sum of the active power and reactive power of the low-voltage station is equal to its apparent power.

[0083] In addition, the constraints also include meteorological constraints. Since the output of distributed photovoltaics is affected by meteorological conditions, the distributed photovoltaic output prediction technology can predict its theoretical maximum power generation. The control of distributed photovoltaic power generation cannot exceed this power, which can be expressed as: Among them, S i represents the apparent power of the i-th photovoltaic user, In addition, the specific photovoltaic output prediction principle belongs to the existing technology and will not be described here.

[0084] In addition, the constraints also include policy constraints. The types of photovoltaic users in the low-voltage area are roughly divided into non-natural person users, natural person users, and specific users. Following policy factors, the priority of photovoltaic user regulation is generally non-natural person users > natural person users > specific users. Therefore, specific users will not be regulated unless necessary. Therefore, if the photovoltaic user is a specific user, it will not be regulated, which can be expressed as: That is, the current power generated by a specific user is equal to the predicted maximum power generation.

[0085] In addition, in step S4, the particle swarm optimization algorithm is used to solve the objective function. The optimal solution obtained includes the output of each photovoltaic user. The control center can send control instructions to the distributed photovoltaic side equipment according to the optimal solution to control the distributed photovoltaic to adjust its own output according to the control instructions. Among them, the specific process of solving the objective function with the particle swarm optimization algorithm belongs to the existing technology and will not be repeated here. For example, the algorithm solution process includes: (1) the initial population size is set to 50, and the position and speed of each example are randomly generated; (2) a penalty function is constructed, the objective function and the constraint conditions are brought into the penalty function, and the fitness value of each particle is calculated; (3) the optimal value of each particle among all particles is found and saved in P id In the example, the optimal values of all particles are stored in P gd (4) Whether the optimal values obtained all meet the iteration requirements, if so, the calculation is terminated and the result is output; wherein, the maximum number of iterations T = 50, the learning factor c1 = c2 = 1.2, and the number of particle swarms is 50.

[0086] In addition, if Figure 3As shown, another embodiment of the present invention further provides a low-voltage distributed photovoltaic control resource margin aggregation system, preferably using the low-voltage distributed photovoltaic control resource margin aggregation method described above, including:

[0087] The substation voltage sensitivity calculation module is used to obtain the historical electrical data of all users in the low-voltage substation and calculate the substation voltage sensitivity between each user in the substation. The substation voltage sensitivity refers to the relationship between the voltage difference between the power meter of a user in the substation and the substation master meter and the power of the power meters of other users in the substation;

[0088] The theoretical aggregation margin calculation module of the substation area is used to obtain the current power generation and current voltage of all photovoltaic users in the substation area and calculate the theoretical aggregation margin of the substation area;

[0089] The objective function construction module is used to construct the objective function with the optimization goals of maximizing margin utilization and minimizing voltage deviation. It also constructs the relationship between voltage and power based on the voltage sensitivity of the substation area and constrains the power of photovoltaic users through voltage constraints.

[0090] The optimization solution and power control module is used to optimize the objective function using the particle swarm algorithm and generate power control instructions for all photovoltaic users based on the optimal solution.

[0091] It can be understood that the resource margin aggregation system for distributed photovoltaic regulation in low-voltage areas of this embodiment uses the area voltage sensitivity index to characterize the relationship between the voltage difference between the electric energy meter of a certain user in the area and the total meter of the area and the power of the electric energy meters of other users in the area. Compared with the voltage sensitivity index commonly used in this field, this index can significantly reduce the dependence on the topology information of the power grid, and is closer to the actual application scenario of the low-voltage area. Moreover, it only needs to process the electric energy meter data in the low-voltage area, and the amount of calculation is greatly reduced. It is more suitable for the limited computing power of edge devices, which is conducive to achieving rapid response to photovoltaic output fluctuations and load changes, and improving the real-time performance of regulation. In addition, the theoretical aggregation margin of the area is accurately calculated based on the current power generation power and current voltage of all photovoltaic users in the area, which can accurately evaluate the overall adjustable margin of the low-voltage area. At the same time, the objective function is constructed with maximizing margin utilization and minimizing voltage deviation as the optimization goals, which ensures the voltage safety of the power grid while fully utilizing the adjustable margin of photovoltaic power generation in the substation. This not only ensures that the side equipment can provide sufficient adjustable resources, but also avoids margin waste, improves the accuracy and reliability of distributed photovoltaic control, and can effectively cope with complex and changeable distributed photovoltaic control scenarios.

[0092] In addition, another embodiment of the present invention further provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the processor is configured to execute the steps of the above method by calling the computer program stored in the memory.

[0093] In addition, another embodiment of the present invention further provides a computer-readable storage medium for storing a computer program for performing resource margin aggregation for distributed photovoltaic regulation in low-voltage areas, wherein the computer program executes the steps of the method described above when running on a computer.

[0094] Common computer-readable storage media include: floppy disks, flexible disks, hard disks, magnetic tape, any other magnetic media, CD-ROMs, any other optical media, punch cards, paper tape, any other physical medium with a pattern of holes, random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), flash-erasable programmable read-only memory (FLASH-EPROM), any other memory chip or cartridge, or any other medium that can be read by a computer. Instructions can further be transmitted or received via a transmission medium. The term transmission medium may include any tangible or intangible medium that can be used to store, encode, or carry instructions for execution by a machine, and includes digital or analog communication signals or other intangible media that facilitate communication of such instructions. Transmission media include coaxial cables, copper wire, and fiber optics, including the wires of a bus used to transmit a computer data signal.

[0095] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiment of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal translation scripting language JavaScript, etc.

[0096] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0097] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0098] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0099] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0100] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

[0101] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A method for aggregating control resource margins for distributed photovoltaics in low-voltage areas, characterized in that: Includes the following: Obtain historical electrical data for all users in the low-voltage area and calculate the area voltage sensitivity between users in the area. The area voltage sensitivity refers to the relationship between the voltage difference between a user's energy meter and the area's total energy meter and the power of other users' energy meters in the area. Obtain the current power generation and voltage of all photovoltaic users in the substation area, and calculate the theoretical aggregation margin of the substation area; The objective function is constructed with maximizing margin utilization and minimizing voltage deviation as the optimization goals. The relationship between voltage and power is constructed based on the voltage sensitivity of the substation area, and the power of photovoltaic users is constrained by voltage constraints. The particle swarm algorithm is used to optimize the objective function and generate power control instructions for all photovoltaic users based on the optimal solution.

2. The method for regulating resource margin aggregation of distributed photovoltaic in low-voltage areas according to claim 1, characterized in that: The voltage sensitivity of the substation is calculated based on the following formula: Among them, S ij represents the voltage sensitivity between the i-th user node and the j-th user node in the substation, and S ij Equal to S ji , ΔV1, ΔV2...ΔV N Indicates the difference between the voltage of each user in the substation area and the total voltage of the substation area, P i Represents the power of the i-th user node in the station area.

3. The method for regulating resource margin aggregation of distributed photovoltaic in low-voltage areas according to claim 1, characterized in that: The process of obtaining the current power generation and current voltage of all photovoltaic users in the substation area and calculating the theoretical aggregation margin of the substation area includes the following: Determine the basic margin of each photovoltaic user based on whether they have participated in regulation; The basic margin of each photovoltaic user is corrected according to its current voltage to obtain an adjustable margin; The theoretical aggregate margin of the substation is obtained by summing up the adjustable margins of all photovoltaic users.

4. The method for regulating resource margin aggregation of distributed photovoltaic in low-voltage areas according to claim 3, characterized in that: The basic margin for each photovoltaic user is determined based on the following formula: Where ΔP i represents the basic margin of the i-th photovoltaic user, P set,i represents the rated power of the inverter connected to the i-th photovoltaic user, P i represents the current power generation of the i-th photovoltaic user, and λ represents the lower limit parameter of the inverter connected to the i-th photovoltaic user.

5. The method for regulating resource margin aggregation of distributed photovoltaic in low-voltage area according to claim 3, characterized in that: The basic margin is corrected based on the following formula: Where ΔP range,i represents the adjustable margin of the i-th photovoltaic user, ΔP i Represents the basic margin of the i-th photovoltaic user, V max and V min They represent the voltage upper limit and voltage lower limit of the i-th photovoltaic user, V i Represents the current voltage value of the i-th photovoltaic user, V nom Indicates the rated voltage value.

6. The method for regulating resource margin aggregation of distributed photovoltaic in low-voltage areas according to claim 1, characterized in that: The expression of the objective function is: Among them, N represents the number of users in the low-voltage area, n represents the number of photovoltaic users in the low-voltage area, V act,i Represents the voltage value of the i-th user after regulation, V nom Indicates the rated voltage value, P act,i represents the power generation of the i-th photovoltaic user after regulation, P i represents the current power generation of the i-th photovoltaic user, The theoretical aggregation margin of the station area, ΔP range，i represents the adjustable margin of the i-th photovoltaic user, and α represents the preset proportional weight coefficient.

7. The method for regulating resource margin aggregation of distributed photovoltaic in low-voltage area according to claim 1, characterized in that: The power of photovoltaic users is constrained by voltage constraints based on the following formula: in, and Respectively represent the maximum and minimum values that the user voltage can be regulated, V top Indicates the total meter voltage value of the substation, N indicates the number of users in the low-voltage substation, S ij represents the voltage sensitivity between the i-th user node and the j-th user node in the substation, P j Represents the power value of the jth user node in the low-voltage area.

8. A low-voltage distributed photovoltaic control resource margin aggregation system, characterized in that: include: The substation voltage sensitivity calculation module is used to obtain the historical electrical data of all users in the low-voltage substation and calculate the substation voltage sensitivity between each user in the substation. The substation voltage sensitivity refers to the relationship between the voltage difference between the power meter of a user in the substation and the substation master meter and the power of the power meters of other users in the substation; The theoretical aggregation margin calculation module of the substation area is used to obtain the current power generation and current voltage of all photovoltaic users in the substation area and calculate the theoretical aggregation margin of the substation area; The objective function construction module is used to construct the objective function with the optimization goals of maximizing margin utilization and minimizing voltage deviation. It also constructs the relationship between voltage and power based on the voltage sensitivity of the substation area and constrains the power of photovoltaic users through voltage constraints. The optimization solution and power control module is used to optimize the objective function using the particle swarm algorithm and generate power control instructions for all photovoltaic users based on the optimal solution.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a computer program, and the processor is configured to execute the steps of the method according to any one of claims 1 to 7 by calling the computer program stored in the memory.

10. A computer-readable storage medium for storing a computer program for performing resource margin aggregation for distributed photovoltaic control in a low-voltage area, characterized in that: When the computer program is run on a computer, the steps of the method according to any one of claims 1 to 7 are executed.

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