Method and device for locating and sizing reactive power compensation device in cable area

Abstract

The invention discloses a method and a device for locating and sizing a reactive power compensation device in a cable area. The method comprises the steps of obtaining photovoltaic data of a distribution network; determining a reactive power output value of a reactive power compensation device in a cable area in the distribution network based on the photovoltaic data; inputting the reactive power output value, the installation number of the reactive power compensation devices, the import cost parameters of the reactive power compensation devices and the load parameters of the power system corresponding to the cable area into a locating and sizing model of the distribution network for analysis to obtain the initial configuration positions and the initial capacities of the reactive power compensation devices; and determining a target configuration position and a target capacity of the reactive power compensation device based on the initial configuration position, the initial capacity and the demand information of the target node in the cabled area. According to the invention, the technical problem that overvoltage occurs when a power system is in a low load in a high cable area is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of reactive power compensation devices, and in particular to a method and device for site selection and capacity determination of reactive power compensation devices in a cabled area. Background Art

[0002] At present, with the development of urbanization, new urban power grids with high cable rates have been built in many places. Since the cable's capacitance to the ground is relatively large and some new urban areas were built without taking into account the low-load effect caused by the small population in the early stage of urban development, technical problems such as overvoltage may occur in areas with high cable rates when the power system is under low load.

[0003] With respect to the above-mentioned technical problem of overvoltage occurring when the power system is under low load in the area with high cabling rate, no effective solution has been proposed so far. Summary of the invention

[0004] The embodiment of the present invention provides a method and device for site selection and capacity determination of reactive power compensation devices in a cabled area, so as to at least solve the technical problem of overvoltage occurring when the power system is under low load in a highly cabled area.

[0005] According to one aspect of the embodiments of the invention, a method for site selection and capacity determination of reactive compensation devices in a cabled area is provided. The method includes: obtaining photovoltaic data of the distribution network; determining the reactive output value of the reactive compensation device in the cabled area of ​​the distribution network based on the photovoltaic data; inputting the reactive output value, the number of installed reactive compensation devices, the import cost parameters of the reactive compensation device, and the load parameters of the power system corresponding to the cabled area into the site selection and capacity determination model of the distribution network for analysis, and obtaining the initial configuration position and initial capacity of the reactive compensation device, wherein the site selection and capacity determination model is used to be constructed through target constraints and objective functions, the target constraints are used to restrict the parameter data of the power system so that the power system can operate normally, and the objective function is used to be established by taking the total cost after installing the reactive compensation device as the target; based on the initial configuration position, initial capacity and demand information of the target node in the cabled area, the target configuration position and target capacity of the reactive compensation device are determined.

[0006] Optionally, based on photovoltaic data, the reactive output value of the reactive compensation device in the cabled area of ​​the distribution network is determined, including: obtaining multiple probability values ​​of the photovoltaic data; clustering the photovoltaic data to obtain a variety of initial photovoltaic data; selecting target photovoltaic data corresponding to the target probability value from a plurality of probability values ​​corresponding to the various initial photovoltaic data; and determining the reactive output value of the reactive compensation device based on the target photovoltaic data.

[0007] Optionally, based on the initial configuration position, initial capacity and demand information of the target node in the cabled area, the target configuration position and target capacity of the reactive compensation device are determined, including: obtaining the number of nodes in the cabled area; determining an index function of the target node based on the number of nodes and the demand information; and determining the target configuration position and target capacity based on the index function, the initial configuration position and the initial capacity.

[0008] Optionally, based on the number of nodes and demand information, an indicator function of the target node is determined, including: in response to the number of nodes being a first value, based on the demand information, determining the indicator function to be a first indicator function, wherein the first indicator function is used to characterize the offset value between the voltage of the target node and a voltage threshold corresponding to the voltage; in response to the number of nodes being a second value, based on the demand information, determining the indicator function to be a second indicator function, wherein the second indicator function is used to characterize the annual cost of establishing the target node; in response to the number of nodes being a third value, based on the demand information, determining the indicator function to be a third indicator function, wherein the third indicator function is used to establish through the offset value and the annual cost.

[0009] Optionally, the target constraint conditions include: a first constraint condition, a second constraint condition, a third constraint condition, a fourth constraint condition and a fifth constraint condition, wherein the first constraint condition is used to characterize the constraints on the power flow data of the power system, the second constraint condition is used to characterize the constraints on the voltage flowing into the cable area, the third constraint condition is used to characterize the constraints on the number of groups and reactive output values ​​of switched capacitors and reactors in the cable area, the fourth constraint condition is used to constrain the reactive output value and active output value of the photovoltaic device in the reactive compensation device, and the fifth constraint condition is used to constrain the reactive output value of the static reactive generator device in the reactive compensation device.

[0010] Optionally, the objective function includes: a first objective function, a second objective function and a third objective function, wherein the first objective function is used to establish the target by taking the installation cost of the reactive compensation device as the target, the second objective function is used to characterize the network loss in the cabled area, and the third objective function is used to characterize the voltage deviation in the cabled area.

[0011] Optionally, the site selection and capacity determination model includes an upper-level planning model and a lower-level planning model, wherein the upper-level planning model is used to be constructed through target constraints and the first objective function in the objective function, and the lower-level planning model is used to be constructed through target constraints and the second objective function and the third objective function in the objective function.

[0012] According to one aspect of an embodiment of the present invention, a device for site selection and capacity determination of reactive compensation devices in a cabled area is provided, the device also including: an acquisition unit for acquiring photovoltaic data of a distribution network; a first determination unit for determining the reactive output value of reactive compensation devices in the cabled area of ​​the distribution network based on the photovoltaic data; an input unit for inputting the reactive output value, the number of installed reactive compensation devices, the import cost parameters of reactive compensation devices, and the load parameters of the power system corresponding to the cabled area into a site selection and capacity determination model of the distribution network for analysis, so as to obtain the initial configuration position and initial capacity of the reactive compensation device, wherein the site selection and capacity determination model is used to be constructed through target constraints and target functions, the target constraints are used to restrict the parameter data of the power system so that the power system can operate normally, and the target function is used to be established by taking the total cost after installing the reactive compensation device as the target; a second determination unit is used to determine the target configuration position and target capacity of the reactive compensation device based on the initial configuration position, initial capacity and demand information of the target node in the cabled area.

[0013] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored program, wherein when the program is executed by a processor, the device where the storage medium is located is controlled to execute the method in the embodiment of the present invention.

[0014] According to another aspect of an embodiment of the present invention, a processor is provided. The processor is used to run a program, wherein the method in the embodiment of the present invention is executed when the program is run.

[0015] According to another aspect of the embodiments of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the method in the embodiments of the present invention is implemented.

[0016] According to another aspect of an embodiment of the present invention, an electronic device is provided, the electronic device comprising a processor and a memory for storing instructions executable by the processor, wherein the processor is configured to execute the instructions to implement the method in the embodiment of the present invention.

[0017] In an embodiment of the present invention, photovoltaic data of a distribution network is obtained; based on the photovoltaic data, the reactive output value of a reactive compensation device in a cabled area of ​​the distribution network is determined; the reactive output value, the number of installed reactive compensation devices, the import cost parameters of the reactive compensation devices, and the load parameters of the power system corresponding to the cabled area are input into a site selection and sizing model of the distribution network for analysis to obtain an initial configuration position and initial capacity of the reactive compensation device, wherein the site selection and sizing model is used to be constructed through target constraints and an objective function, the target constraints are used to restrict the parameter data of the power system so that the power system can operate normally, and the objective function is used to be established by taking the total cost after installing the reactive compensation device as a target; based on the initial configuration position, the initial capacity, and the demand information of the target node in the cabled area, the target configuration position and target capacity of the reactive compensation device are determined. That is to say, the embodiment of the present invention can first obtain the photovoltaic data of the distribution network, and then according to the photovoltaic data, the reactive output value of the reactive compensation device in the cabled area of ​​the distribution network can be determined, and then the reactive output value, the installation quantity of the reactive compensation device, the import cost parameter of the reactive compensation device, and the load parameter of the power system corresponding to the cabled area obtained above can be input into the site selection and capacity determination model of the distribution network for analysis, so as to obtain the initial configuration position and initial capacity of the reactive compensation device. Finally, according to the initial configuration position and initial capacity obtained above, and the demand information of the target node in the cabled area, the target configuration position and target capacity of the reactive compensation device can be determined. According to the target configuration position and target capacity that have been obtained, the reactive compensation device is installed in the highly cabled area, thereby solving the technical problem of overvoltage in the highly cabled area when the power system is under low load, and achieving the technical effect of maintaining the voltage at a stable voltage in the highly cabled area when the power system is under low load. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0019] Figure 1 is a flow chart of a method for site selection and capacity determination of reactive power compensation devices in a cabled area according to an embodiment of the present invention;

[0020] Figure 2 is a schematic diagram of a topological structure of a node system according to an embodiment of the present invention;

[0021] Figure 3 is a schematic diagram of a bus voltage after processing data in a node system according to an embodiment of the present invention;

[0022] Figure 4is a schematic diagram of the output of a photovoltaic device on four typical days throughout the year according to an embodiment of the present invention;

[0023] Figure 5 is a flow chart of a planning method adopted according to an embodiment of the present invention;

[0024] Figure 6 is a schematic diagram of a planning procedure employed according to an embodiment of the present invention;

[0025] Figure 7 is a schematic diagram of the convergence of an upper layer model according to an embodiment of the present invention;

[0026] Figure 8 is a schematic diagram of site selection results of a photovoltaic device and an SVG device according to an embodiment of the present invention;

[0027] Fig. 9 is a schematic diagram of voltage changes of each node within one day according to an embodiment of the present invention;

[0028] Fig.10 is another schematic diagram of voltage changes of each node within one day according to an embodiment of the present invention;

[0029] Fig.11 It is a schematic diagram of a site selection and capacity determination device for a reactive power compensation device in a cable area according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0032] According to an embodiment of the present invention, a method for site selection and sizing of reactive compensation devices in a cabled area is provided. It should be noted that in the flowchart of the accompanying drawings, the steps shown therein can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that shown here.

[0033] The following is an introduction to the site selection and capacity determination method for reactive power compensation devices in a cabled area according to an embodiment of the present invention.

[0034] Figure 1 is a flow chart of a method for selecting a location and determining the capacity of a reactive power compensation device in a cabled area according to an embodiment of the present invention. Figure 1 As shown, the method for selecting the site and determining the capacity of the reactive power compensation device in the cable area may include the following steps:

[0035] Step S101, obtaining photovoltaic data of the distribution network.

[0036] In the technical solution provided in the above step S101 of the present invention, photovoltaic data of the distribution network can be obtained, wherein the photovoltaic data is used to characterize the access and operating status of the photovoltaic power generation system in the distribution network, such as the power generation, voltage, frequency and other information data of the photovoltaic power generation system. It should be noted that only photovoltaic data is illustrated here, and the data type contained in the photovoltaic data is not specifically limited.

[0037] Step S102: determining the reactive output value of the reactive power compensation device in the cabled area of ​​the distribution network based on the photovoltaic data.

[0038] In the technical solution provided in the above step S102 of the present invention, after obtaining the photovoltaic data, a clustering algorithm (k-means) can be used to determine the reactive output value of the reactive compensation device in the cabled area in the distribution network. The cabled area can be a high cabled area. The clustering algorithm is used to classify the data. The reactive output value is used to characterize the size of the reactive power of the reactive compensation device.

[0039] Optionally, reactive power compensation devices are used to improve the power factor in the power system, reduce losses, and improve efficiency and stability, thereby ensuring the normal operation of the power system. For example, common reactive power compensation devices include capacitors, reactors, static var compensators (SVC), static var generators (SVG), etc. At the same time, photovoltaic, wind power, energy storage and other inverter power sources also have the ability to provide reactive power support.

[0040] It should be noted that this is only a preferred implementation method for determining the reactive output value of the reactive compensation device, and does not specifically limit the process and method for determining the reactive output value of the reactive compensation device. As long as the process and method for determining the reactive output value of the reactive compensation device are based on photovoltaic data, they are within the protection scope of the present invention and are not listed here.

[0041] Step S103, the reactive output value, the number of installed reactive compensation devices, the import cost parameters of the reactive compensation devices, and the load parameters of the power system corresponding to the cabled area are input into the site selection and sizing model of the distribution network for analysis to obtain the initial configuration position and initial capacity of the reactive compensation device.

[0042] In the technical solution provided in step S103 of the present invention, the obtained reactive power output value, the number of installed reactive compensation devices, the introduction cost parameters of the reactive compensation devices, and the load parameters of the power system corresponding to the cable area are input into the site selection and capacity determination model of the distribution network for analysis, so as to obtain the initial configuration position and initial capacity of the reactive compensation device. The initial capacity can be called the initial installation capacity.

[0043] Optionally, the site selection and sizing model is constructed through target constraints and objective functions. The target constraints are used to limit the parameter data of the power system so that the power system can operate normally. The objective function is used to establish the model by taking the total cost after installing the reactive power compensation device as the target.

[0044] Optionally, the number of installed reactive compensation devices, the import cost parameters of the reactive compensation devices and the load parameters of the power system corresponding to the cabled area are obtained, wherein the reactive compensation devices include: SVG devices and photovoltaic devices. For example, the number of installed SVG devices and photovoltaic devices, import cost parameters, load parameters and other pre-parameters are determined.

[0045] Optionally, the reactive power output value, installation quantity, import cost parameters and load parameters are input into the upper planning model in the site selection and sizing model to obtain various types of data, and the various types of data are input into the lower planning model in the site selection and sizing model for analysis to obtain the original configuration position and original capacity of the reactive compensation device. The above process is repeated to obtain multiple original configuration positions and original capacities. When the number of cycles in the site selection and sizing model reaches the number of iterations, the optimal result is selected from the multiple original configuration positions and original capacities as the initial configuration position and initial capacity.

[0046] It should be noted that this is only a preferred implementation method for obtaining the initial configuration position and initial capacity of the reactive power compensation device, and does not specifically limit the process and method for obtaining the initial configuration position and initial capacity of the reactive power compensation device.

[0047] Step S104, determining a target configuration position and a target capacity of the reactive power compensation device based on the initial configuration position, the initial capacity and the demand information of the target node in the cable area.

[0048] In the technical solution provided in the above step S104 of the present invention, the exponential function of the target node is used to determine the target configuration position and target capacity of the reactive compensation device based on the obtained initial configuration position, initial capacity and demand information of the target node in the cabled area.

[0049] Optionally, the target node may be a node set in the cabled area. The exponential function may be a preset function of different types. The target configuration position may be referred to as an optimal configuration position. The target capacity may be referred to as an optimal capacity.

[0050] It should be noted that this is only a preferred implementation method for determining the target configuration position and target capacity of the reactive power compensation device, and does not specifically limit the process and method for determining the target configuration position and target capacity of the reactive power compensation device.

[0051] In the above steps S101 to S104 of the present invention, the photovoltaic data of the distribution network can be first obtained, and then the reactive output value of the reactive compensation device in the cabled area of ​​the distribution network can be determined based on the photovoltaic data. Then, the reactive output value, the number of installed reactive compensation devices, the import cost parameters of the reactive compensation device, and the load parameters of the power system corresponding to the cabled area obtained above can be input into the site selection and capacity determination model of the distribution network for analysis, so as to obtain the initial configuration position and initial capacity of the reactive compensation device. Finally, the target configuration position and target capacity of the reactive compensation device can be determined based on the above-mentioned initial configuration position and initial capacity, as well as the demand information of the target node in the cabled area. According to the obtained target configuration position and target capacity, the reactive compensation device is installed in the highly cabled area, thereby solving the technical problem of overvoltage in the highly cabled area when the power system is under low load, and achieving the technical effect of maintaining the voltage at a stable voltage in the highly cabled area when the power system is under low load.

[0052] The above method of this embodiment is further introduced below.

[0053] As an optional implementation method, based on photovoltaic data, the reactive output value of the reactive compensation device in the cabled area of ​​the distribution network is determined, including: obtaining multiple probability values ​​of the photovoltaic data; clustering the photovoltaic data to obtain a variety of initial photovoltaic data; selecting target photovoltaic data corresponding to the target probability value from the multiple probability values ​​corresponding to the various initial photovoltaic data; and determining the reactive output value of the reactive compensation device based on the target photovoltaic data.

[0054] In this embodiment, multiple probability values ​​of photovoltaic data can be obtained first, and then the photovoltaic data can be clustered using the clustering algorithm k-means to obtain multiple initial photovoltaic data, and then from the multiple probability values ​​corresponding to the multiple initial photovoltaic data, the target photovoltaic data corresponding to the target probability value can be selected, and finally the reactive output value of the reactive compensation device can be determined according to the target photovoltaic data. Among them, the target probability value is the maximum value among the multiple probability values.

[0055] Optionally, based on the photovoltaic data, a clustering algorithm can be used to obtain a typical daily photovoltaic output curve. Based on the daily output curve, a group of photovoltaic daily output data with the largest probability value is selected, and this daily output data is determined as the reactive output value of the photovoltaic device in the reactive compensation device, thereby obtaining the upper and lower limit values ​​corresponding to the reactive output value.

[0056] For example, photovoltaic data is imported, and the k-means clustering algorithm is used to obtain several typical photovoltaic daily output curves, and the group of photovoltaic daily output data with the highest probability is selected, and the upper and lower limits of photovoltaic reactive power output are calculated.

[0057] As an optional implementation method, the target configuration position and target capacity of the reactive compensation device are determined based on the initial configuration position, initial capacity and demand information of the target node in the cabled area, including: obtaining the number of nodes in the cabled area; determining the index function of the target node based on the number of nodes and the demand information; and determining the target configuration position and target capacity based on the index function, the initial configuration position and the initial capacity.

[0058] In this embodiment, the number of nodes in the cabled area is obtained, and then the indicator function of the target node can be determined based on the number of nodes and demand information. Based on the indicator function, initial configuration position and initial capacity obtained above, the purpose of determining the target configuration position and target capacity can be achieved.

[0059] Optionally, the number of nodes may be a preset value, represented by a mode number. The index function may be a function with different index values ​​as targets. For example, a function with the best power quality as an index, a function with the lowest equivalent annual cost as an index, etc. It should be noted that only examples are given here to illustrate the index function, and the index function is not specifically limited.

[0060] Optionally, the initial configuration position and initial capacity are further optimized using an indicator function, and when the number of cycles at this time reaches a maximum number of iterations, the target configuration position and target capacity can be obtained. The maximum number of iterations can be a preset value.

[0061] As an optional implementation method, based on the number of nodes and demand information, an indicator function of the target node is determined, including: in response to the number of nodes being a first value, based on the demand information, determining the indicator function to be a first indicator function, wherein the first indicator function is used to characterize the offset value between the voltage of the target node and the voltage corresponding to the voltage threshold; in response to the number of nodes being a second value, based on the demand information, determining the indicator function to be a second indicator function, wherein the second indicator function is used to characterize the annual cost of establishing the target node; in response to the number of nodes being a third value, based on the demand information, determining the indicator function to be a third indicator function, wherein the third indicator function is used to be established through the offset value and the annual cost.

[0062] In this embodiment, when the number of nodes is a first value, the indicator function can be determined as a first indicator function according to the demand information; when the number of nodes is a second value, the indicator function at this time can be determined as a second indicator function according to the demand information; when the number of nodes is a third value, the indicator function can be determined as a third indicator function according to the demand information.

[0063] Optionally, the first value may be a preset value, such as 1. The second value may be a preset value, such as 2. The third value may be a preset value, such as 3. The voltage of the target node may be the bus voltage of the target node in a standardized case. The annual cost may be referred to as an equivalent annual cost. The equivalent annual cost is normalized to obtain a processed equivalent annual cost, and the processed equivalent annual cost and the offset value are weighted and summed to obtain a weighted value, and the weighted value may be used to construct a third indicator function.

[0064] For example, the objective function in the optimization is selected according to the needs: when the mode number is set to 1, the optimization is based on the best power quality as the indicator, and the measurement indicator is the offset value between the bus voltage and the voltage threshold under the normalization; when the mode number is set to 2, the optimization is still based on the lowest equivalent annual cost as the indicator, and the measurement indicator is still the equivalent annual cost. At this time, it is actually to prevent the optimization in the double-layer optimization from being insufficient; when the mode number is set to 3, the optimization is based on the weighted sum of the normalized values ​​of power quality and cost as the indicator, and the weight can be set by yourself, which can be determined according to the decision on the importance of the two. According to the objective function, the initial configuration position is used as the installation position of the device, and the installation capacity of the initial capacity is used as the maximum value of the reactive output to optimize the 24-hour (h) output of the reactive compensation device, and the cycle is repeated until the maximum number of iterations is reached, so as to obtain the optimal configuration position and capacity of the photovoltaic device and the SVG device.

[0065] As an optional implementation method, the target constraint conditions include: a first constraint condition, a second constraint condition, a third constraint condition, a fourth constraint condition and a fifth constraint condition, wherein the first constraint condition is used to characterize the constraints on the power flow data of the power system, the second constraint condition is used to characterize the constraints on the voltage flowing into the cable area, the third constraint condition is used to characterize the constraints on the number of groups and reactive output values ​​of switched capacitors and reactors in the cable area, the fourth constraint condition is used to constrain the reactive output value and active output value of the photovoltaic device in the reactive compensation device, and the fifth constraint condition is used to constrain the reactive output value of the static reactive generator device in the reactive compensation device.

[0066] In this embodiment, the target constraint condition includes: a first constraint condition, a second constraint condition, a third constraint condition, a fourth constraint condition and a fifth constraint condition, wherein the first constraint condition may be referred to as a power flow constraint condition of the power system, and may be expressed by the following formula:

[0067]

[0068] In the above formula, P i , Q i They are used to represent the active power and reactive power of the node respectively; U i Used to represent the voltage at node i, U j Used to represent the voltage at node j; G ij , B ij They are used to represent the equivalent conductance and equivalent susceptance of the line respectively; δ ij Used to indicate voltage phase angle.

[0069] Optionally, the second constraint condition may be referred to as a voltage upper and lower limit constraint condition of the node, which may be expressed by the following formula:

[0070] U imin <U i <U imax

[0071] In the above formula, U imin Used to indicate the lower limit voltage of the node, U imax Used to indicate the upper voltage limit of a node.

[0072] Optionally, the third constraint condition may be referred to as the number of switched capacitor reactor groups and reactive power constraint condition, which may be expressed by the following formula:

[0073]

[0074] In the above formula, N C 、N LThey are respectively used to represent the number of switched capacitor groups and the number of switched reactor groups, both of which are natural numbers, and N is used to represent a natural number. The number of capacitor banks used to represent the node configuration. The lower limit for the number of capacitor banks used to represent a node configuration. An upper limit on the number of capacitor banks used to represent a node configuration. Used to indicate the number of reactor groups configured in the node. Used to indicate the lower limit of the number of reactor groups in the node configuration. It is used to indicate the upper limit of the number of reactor groups in the node configuration. .Cmax It is used to indicate the upper limit of the total reactive power compensation of capacitor. L.max Used to indicate the upper limit of the total amount of reactive power compensation for inductance.

[0075] Optionally, the fourth constraint condition may be referred to as an active and reactive power constraint condition of the photovoltaic device, which may be expressed by the following formula:

[0076]

[0077] In the above formula, S P Used to indicate photovoltaic capacity, P P Used to indicate the photovoltaic active output value, Q P It is used to indicate the photovoltaic reactive output value, and φ is used to indicate the photovoltaic maximum power factor angle.

[0078] Optionally, the fifth constraint condition may be referred to as a reactive power constraint condition of the SVG device, which may be expressed by the following formula:

[0079] Q Smin <Q S <Q Smax

[0080] In the above formula, Q S Used to indicate the reactive power output value of the SVG device. Smin Used to indicate the lower limit of reactive power output. Smax Used to indicate the upper limit of reactive power output.

[0081] As an optional implementation method, the objective function includes: a first objective function, a second objective function and a third objective function, wherein the first objective function is used to establish the target by taking the installation cost of the reactive power compensation device as the target, the second objective function is used to characterize the network loss in the cabled area, and the third objective function is used to characterize the voltage deviation in the cabled area.

[0082] In this embodiment, the objective function may include a first objective function, a second objective function, and a third objective function, wherein the installation cost may be referred to as a fixed installation cost.

[0083] Optionally, the first objective function is used to establish the equivalent annual investment cost, the fixed installation cost and the voltage over-limit penalty cost as the target, which can be called the equivalent annual total cost objective function, and is represented by the following formula:

[0084]

[0085] In the above formula, F is used to represent the first objective function. a Used to express the annual maintenance cost rate. k crf Used to express the conversion factor of equal annual value. c Used to indicate the price of capacitors per unit capacity. L It is used to indicate the price of reactor per unit capacity. r is used to indicate the discount rate. T is used to indicate the service life of the equipment. Q C Used to indicate the reactive capacity of a single group of capacitors. L Used to indicate the reactive capacity of a single group of reactors. The number of capacitor banks used to represent the node configuration. It is used to indicate the number of reactor groups configured in the node. β is used to indicate the grid loss price. C m It is used to represent the fixed installation cost. λ is used to represent the voltage over-limit penalty coefficient.

[0086] Optionally, the second objective function may be called a network loss objective function, which is used to describe the energy loss of the network and may be expressed by the following formula:

[0087]

[0088] In the above formula, F1 is used to represent the network loss objective function, Used to represent the network loss of node i.

[0089] Optionally, the third objective function may be called a voltage deviation objective function, which is used to describe the voltage deviation of the network and may be expressed by the following formula:

[0090]

[0091] In the above formula, U i Used to represent the voltage value of node i, U base Used to indicate the voltage threshold of node i.

[0092] As an optional implementation method, the site selection and capacity determination model includes an upper-level planning model and a lower-level planning model, wherein the upper-level planning model is used to construct the model through target constraints and the first objective function in the objective function, and the lower-level planning model is used to construct the model through target constraints and the second and third objective functions in the objective function.

[0093] In this embodiment, the site selection and capacity determination model may include two models, namely an upper-level planning model and a lower-level planning model, and the upper-level planning model may be constructed by target constraints and a first objective function, and the lower-level planning model may be constructed by target constraints, a second objective function, and a third objective function. Among them, the upper-level planning model may be referred to as the upper-level model. The lower-level planning model may be referred to as the lower-level model. It should be noted that this is only a preferred implementation method for determining the site selection and capacity determination model, and does not specifically limit the content contained in the site selection and capacity determination model.

[0094] For example, after obtaining the reactive output value of the reactive compensation device in the above text, the optimization algorithm for the reactive output value can be initialized and optimized. First, the upper-level planning model in the site selection and capacity determination model randomly determines a set of configuration locations of photovoltaic devices and SVG devices and the corresponding installation capacity constraints, and transmits them to the lower-level model in the site selection and capacity determination model; the lower-level model, based on the determined locations of photovoltaic devices and SVG, takes the minimum network loss and voltage deviation of the power system as the optimization goal, and optimizes the 24-hour reactive output of photovoltaic devices and SVG devices under the constraints of the installation capacity given by the upper layer, and returns the network loss and node voltage under the optimal situation to the upper-level model; the upper-level planning model takes the equivalent annual total cost as the optimization goal, calculates according to the data returned by the lower-level model, optimizes and updates the configuration location of photovoltaic devices and SVG devices, and then transmits it to the lower-level model; the above process is repeated until the number of iterations is reached, and a set of better results are obtained; enter the post-optimization process, based on the results obtained in the previous step, it is considered that the site selection is more accurate, and it is retained, and the installation capacity in this result is still retained, so as to achieve the purpose of obtaining the initial configuration location and initial capacity.

[0095] In this embodiment, the photovoltaic data of the distribution network can be obtained first, and then the reactive output value of the reactive compensation device in the cabled area of ​​the distribution network can be determined based on the photovoltaic data. Then, the reactive output value, the number of installed reactive compensation devices, the import cost parameters of the reactive compensation device, and the load parameters of the power system corresponding to the cabled area obtained above can be input into the site selection and capacity determination model of the distribution network for analysis, so as to obtain the initial configuration position and initial capacity of the reactive compensation device. Finally, the target configuration position and target capacity of the reactive compensation device can be determined based on the initial configuration position and initial capacity obtained above, as well as the demand information of the target node in the cabled area. According to the obtained target configuration position and target capacity, the reactive compensation device is installed in the highly cabled area, thereby solving the technical problem of overvoltage in the highly cabled area when the power system is under low load, and achieving the technical effect of maintaining the voltage at a stable voltage in the highly cabled area when the power system is under low load.

[0096] The technical solution of the embodiment of the present invention is illustrated below in conjunction with preferred implementation modes.

[0097] In recent years, with the development of urbanization, many places have built new urban power grids with high cable rates. Due to the uncertainty of new energy output, large-scale grid connection has a significant impact on the power flow of the distribution network. When the output is too large, it will cause the power flow to flow in reverse, which will cause node voltage to exceed the limit and fluctuate, bringing challenges to maintaining the voltage stability of the distribution network.

[0098] Furthermore, because the cable's capacitance to the ground is relatively large and some new urban areas were built without taking into account the low-load effect caused by the small population in the early stages of urban development, technical problems such as overvoltage may occur when the power system is under low load in areas with high cabling rates.

[0099] Therefore, in order to solve the above problems, the present invention proposes a reactive power planning and configuration method for areas with high cabling rates. The method first considers the sunshine factor and the uncertainty of the photovoltaic output curve simulation, and constructs multi-dimensional constraints based on the actual operating status of the power grid. Then, the investment cost, operating voltage deviation and operating network loss are modeled, and a multi-objective optimization loss function is constructed. The constructed model is optimized and solved based on a multi-objective genetic optimization algorithm to obtain the optimal reactive power planning and configuration scheme. Finally, based on the above-obtained optimization results, further optimization is performed with the power quality or the equivalent annual cost as the objective function to obtain the optimal configuration position and capacity of the reactive power compensation device, thereby solving the technical problem of overvoltage in high cabling areas when the power system is under low load, and achieving the technical effect of maintaining the voltage at a stable voltage in high cabling areas when the power system is under low load.

[0100] Figure 2 is a schematic diagram of a topological structure of a node system according to an embodiment of the present invention, such as Figure 2 As shown, reference numerals 1 to 33 are used to represent nodes in the node system.

[0101] The embodiment of the present invention selects the topological structure of the node system (IEEE33) to simulate the overvoltage situation of the high-cable urban distribution network during light-load operation. On the basis of the original parameters of the IEEE33 node, the line parameters are modified to the corresponding cable parameters, and the unit length resistance, reactance, and susceptance of the power frequency are 0.233 ohms per kilometer (Ω / km), 0.125Ω / km, and 4.026e-5 Siemens per kilometer (S / km), respectively; in addition, the value of each node load is set to fluctuate between 0.5 and 0.7 times the original value within a day to simulate the light-load operation and load volatility.

[0102] Optionally, the IEEE 33-node distribution network is a typical low-voltage distribution network structure and is the most common network form in the power system. The network includes 33 nodes, including three transformer nodes, 30 load nodes and 6 power generation nodes. The dots in the figure represent nodes, the dotted lines represent tie lines, and the solid lines represent cable lines.

[0103] In an embodiment of the present invention, Figure 3 is a schematic diagram of a bus voltage after processing data in a node system according to an embodiment of the present invention, such as Figure 3 As shown in the figure, the power flow calculation is performed on the node example in the modified node system IEEE33, and the voltage changes of each node at different times of the day are obtained. It can be seen that obvious overvoltages appear at multiple nodes, and the use of SVG devices and the reactive power output of photovoltaic devices for voltage regulation is considered.

[0104] In this embodiment, Figure 4 is a schematic diagram of the output of a photovoltaic device according to an embodiment of the present invention on four typical days throughout the year, such as Figure 4 As shown, the photovoltaic power generation power of the photovoltaic device in different time periods and under different scenarios can be determined.

[0105] Optionally, considering the uncertainty of photovoltaic output, a k-means clustering algorithm is used to perform cluster analysis on the photovoltaic data throughout the year to obtain the output of the photovoltaic device on four typical days throughout the year.

[0106] Figure 5 is a flow chart of a planning method adopted according to an embodiment of the present invention, such as Figure 5 As shown, the planning method may include the following steps:

[0107] Step S501, determining the installation quantity, import cost parameters, load parameters, etc. of SVG devices and photovoltaic devices.

[0108] Step S502, obtaining a typical daily photovoltaic load curve according to photovoltaic data.

[0109] In this embodiment, photovoltaic data is imported, and the k-means clustering algorithm is used to obtain several typical photovoltaic daily output curves, such as Figure 4 As shown, a group of photovoltaic daily output data with the highest probability is selected, and the upper and lower limits of photovoltaic reactive output are calculated.

[0110] Step S503: determine the initial installation position and initial installation capacity.

[0111] In this embodiment, the initial installation location and initial installation capacity can be determined based on the obtained daily power data using a site selection and capacity determination model, wherein the site selection and capacity determination model is established through target constraints and an objective function.

[0112] Specifically, the target constraint condition includes: a first constraint condition, a second constraint condition, a third constraint condition, a fourth constraint condition and a fifth constraint condition, wherein the first constraint condition can be called a power flow constraint condition of the power system, which can be expressed by the following formula:

[0113]

[0114] In the above formula, P i , Q i They are used to represent the active power and reactive power of the node respectively; U i Used to represent the voltage at node i, U j Used to represent the voltage at node j; G ij , B ij They are used to represent the equivalent conductance and equivalent susceptance of the line respectively; δ ij Used to indicate voltage phase angle.

[0115] Optionally, the second constraint condition may be referred to as a voltage upper and lower limit constraint condition of the node, which may be expressed by the following formula:

[0116] U imin <U i <U imax

[0117] In the above formula, U imin Used to indicate the lower limit voltage of the node, U imax Used to indicate the upper voltage limit of a node.

[0118] Optionally, the third constraint condition may be referred to as the number of switched capacitor reactor groups and reactive power constraint condition, which may be expressed by the following formula:

[0119]

[0120] In the above formula, N C 、N L They are respectively used to represent the number of switched capacitor groups and the number of switched reactor groups, both of which are natural numbers, and N is used to represent a natural number. The number of capacitor banks used to represent the node configuration. The lower limit for the number of capacitor banks used to represent a node configuration. An upper limit on the number of capacitor banks used to represent a node configuration. Used to indicate the number of reactor groups configured in the node. Used to indicate the lower limit of the number of reactor groups in the node configuration. It is used to indicate the upper limit of the number of reactor groups in the node configuration. .Cmax It is used to indicate the upper limit of the total reactive power compensation of capacitor. L.max Used to indicate the upper limit of the total amount of reactive power compensation for inductance.

[0121] Optionally, the fourth constraint condition may be referred to as an active and reactive power constraint condition of the photovoltaic device, which may be expressed by the following formula:

[0122]

[0123] In the above formula, S P Used to indicate photovoltaic capacity, P P Used to indicate the photovoltaic active output value, Q P It is used to indicate the photovoltaic reactive output value, and φ is used to indicate the photovoltaic maximum power factor angle.

[0124] Optionally, the fifth constraint condition may be referred to as a reactive power constraint condition of the SVG device, which may be expressed by the following formula:

[0125] Q Smin <Q S <Q Smax

[0126] In the above formula, Q S Used to indicate the reactive power output value of the SVG device. Smin Used to indicate the lower limit of reactive power output. Smax Used to indicate the upper limit of reactive power output.

[0127] In this embodiment, the objective function may include a first objective function, a second objective function and a third objective function. The first objective function is used to establish the equivalent annual investment cost, the fixed installation cost and the voltage over-limit penalty cost as the target, which can be called the equivalent annual total cost objective function, and is represented by the following formula:

[0128]

[0129] In the above formula, F is used to represent the first objective function. a Used to express the annual maintenance cost rate. k crf Used to express the conversion factor of equal annual value. c Used to indicate the price of capacitors per unit capacity. L It is used to indicate the price of reactor per unit capacity. r is used to indicate the discount rate. T is used to indicate the service life of the equipment. Q C Used to indicate the reactive capacity of a single group of capacitors. L Used to indicate the reactive capacity of a single group of reactors. The number of capacitor banks used to represent the node configuration. It is used to indicate the number of reactor groups configured in the node. β is used to indicate the grid loss price. C m It is used to represent the fixed installation cost. λ is used to represent the voltage over-limit penalty coefficient.

[0130] Optionally, the second objective function may be called a network loss objective function, which is used to describe the energy loss of the network and may be expressed by the following formula:

[0131]

[0132] In the above formula, F1 is used to represent the network loss objective function, Used to represent the network loss of node i.

[0133] Optionally, the third objective function may be called a voltage deviation objective function, which is used to describe the voltage deviation of the network and may be expressed by the following formula:

[0134]

[0135] In the above formula, U i Used to represent the voltage value of node i, U base Used to indicate the voltage threshold of node i.

[0136] Optionally, after obtaining the daily power data, the optimization algorithm for the reactive power output value can be initialized and optimization can be started. First, the upper-level planning model in the site selection and capacity determination model randomly determines a set of configuration locations of photovoltaic devices and SVG devices and corresponding installation capacity constraints, and transmits them to the lower-level model in the site selection and capacity determination model.

[0137] Optionally, based on the determined locations of the PV devices and SVG, the lower model takes minimizing the network loss and voltage deviation of the power system as the optimization goal, optimizes the 24-hour reactive output of the PV devices and SVG devices under the constraints of the installation capacity given by the upper layer, and returns the network loss and node voltage in the optimal case to the upper model.

[0138] Optionally, the upper-level planning model takes the equivalent annual total cost as the optimization target, performs calculations based on the data returned by the lower-level model, optimizes and updates the configuration positions of the photovoltaic devices and the SVG devices, and then passes them to the lower-level model; the above process is repeated until the number of iterations is reached to obtain a set of good results; the post-optimization process is entered, and based on the results obtained in the previous step, the site selection is considered to be more accurate and is retained, and the installation capacity in this result is still retained, thereby achieving the purpose of obtaining the initial configuration position and the initial installation capacity.

[0139] Step S504, initializing or updating the population and determining the optimal value of the population.

[0140] In this embodiment, the population is initialized or updated based on the obtained data to determine the optimal value of the population.

[0141] Optionally, a multi-objective optimization problem needs to be solved and analyzed, which can be accomplished using non-dominated sorting and particle swarm optimization algorithms, where the particle swarm optimization algorithm is a heuristic algorithm for finding the global optimal point of the transformed problem.

[0142] Step S505: Check whether the number of iterations has reached the maximum.

[0143] In this embodiment, it can be determined whether the number of iterations reaches the maximum, if yes, step S506 is executed, if no, step S511 is executed.

[0144] Step S506, selecting the objective function for post-optimization according to the mode number.

[0145] In this embodiment, the objective function during post-optimization, that is, the index function, may be selected according to the mode number.

[0146] Optionally, the objective function in the post-optimization is selected according to the requirements: when the mode number is set to 1, the optimization is based on the best power quality as an indicator, and the measurement indicator is the offset value between the bus voltage and the voltage threshold under normalization.

[0147] Optionally, when the mode number is set to 2, the optimization still takes the lowest equivalent annual cost as the indicator, and the measurement indicator is still the equivalent annual cost. This is actually to prevent insufficient optimization in the two-layer optimization.

[0148] Optionally, when the mode number is set to 3, the optimization takes the weighted sum of the normalized values ​​of power quality and cost as the indicator, where the weight can be set by yourself and can be determined based on the decision of the importance of the two. According to the objective function, the initial configuration position is taken as the installation position of the device, and the installation capacity of the initial capacity is taken as the maximum value of the reactive output to optimize the 24-hour output of the reactive compensation device, and the cycle is repeated until the maximum number of iterations is reached, so as to obtain the optimal configuration position and capacity of the photovoltaic device and the SVG device.

[0149] Step S507, initializing or updating the population and determining the optimal value of the population.

[0150] Step S508: Check whether the number of iterations has reached the maximum.

[0151] In this embodiment, it is determined whether the number of iterations reaches the maximum. If not, step S509 is executed. If yes, the process ends directly.

[0152] Step S509, performing power flow calculation according to the output.

[0153] Step S510, calculating the selected index according to the power flow calculation.

[0154] Step S511: The lower model determines the 24-hour reactive power output according to the installed capacity.

[0155] Step S512, performing power flow calculation according to the output.

[0156] Step S513, performing multi-objective optimization according to the network loss and voltage offset values ​​in the power flow calculation results to obtain the optimal output planning.

[0157] Step S514, the reading result is returned to the upper model for equivalent annual cost calculation.

[0158] In this embodiment, after the read result is returned to the upper model for equivalent annual cost calculation, step S504 may be executed.

[0159] In this embodiment, Figure 6 is a schematic diagram of a planning procedure adopted according to an embodiment of the present invention, such as Figure 6 As shown in the figure, the main.m() function is used to configure the initial parameters. After configuring the initial parameters, the PSOFUN.m() function can be used to generate / update the constraints of the upper model, and then the Objective_fun.m() function can be used to calculate the fixed costs such as the installation fee, so as to achieve the purpose of configuring the decision space using the Lower_strategy.m() function.

[0160] Optionally, after using the particle swarm algorithm to update the global optimum and individual optimum for the relevant data in the distribution network, the speed and position can be updated, and then the over-limit processing can be performed, so that the constraint conditions of the upper model can be generated / updated.

[0161] Optionally, after calculating fixed costs such as installation costs, as well as network losses and voltage over-limit penalty fees, the equivalent annual total cost (the objective function value of the upper model) can be obtained. Using the objective function value of the upper model, the global optimum and individual optimum can be updated.

[0162] Optionally, after configuring the decision space, the algorithm in the lower model can be used to implement initialization, and then calculate the objective function value in the lower model. At this time, non-dominated sorting is used to implement external archiving of particles, and then the investment strategy is updated. The above process is repeated with the number of investment groups within 24 hours to obtain the optimal distance value.

[0163] Optionally, the end of loop() function can be used to read the best result so as to calculate the final voltage compensation value and draw a graph based on the voltage compensation value.

[0164] Optionally, after reading the better result, the installation location and maximum capacity can be determined, the power quality and equivalent annual cost can be weighted, and the installation location and maximum capacity can be optimized to update the global optimum and individual optimum, and read the optimal result, calculate the optimal voltage compensation value, and draw a graph based on the voltage compensation value.

[0165] In this embodiment, Figure 7 is a schematic diagram of the convergence of an upper layer model according to an embodiment of the present invention, such as Figure 7 As shown, the equivalent annual total cost can be continuously changed according to the number of iterations, and the equivalent annual total cost is also constantly changing, where the unit of the equivalent annual total cost is cost / yuan.

[0166] In this embodiment, Figure 8 is a schematic diagram of the site selection results of a photovoltaic device and an SVG device according to an embodiment of the present invention, such as Figure 8 As shown, the location of the triangle is the site selection location of the SVG device, and the location of the large circle is the site selection location of the photovoltaic device (PV device).

[0167] In this embodiment, Fig. 9 is a schematic diagram of voltage changes of each node within one day according to an embodiment of the present invention. Fig. 9 As shown, the voltage changes of each node at different times can be determined, and the dotted line and solid line correspond to the voltage results before reactive power optimization and after preliminary reactive power optimization, respectively.

[0168] In this embodiment, Fig.10 FIG. 4 is another schematic diagram of voltage variation of each node within one day according to an embodiment of the present invention. Fig.10 As shown, the dotted line and the solid line correspond to the voltage results before reactive power optimization and after optimization with power quality as the optimization target, respectively.

[0169] Optionally, from Fig. 9 and Fig.10 It can be seen that after reactive power optimization, the voltage limit and overall stability have been greatly improved. Fig. 9 and Fig.10 The horizontal comparison shows that the stability of the optimized voltage has been further improved after the power quality is optimized.

[0170] In this embodiment, the photovoltaic data of the distribution network can be obtained first, and then the reactive output value of the reactive compensation device in the cabled area of ​​the distribution network can be determined based on the photovoltaic data. Then, the reactive output value, the number of installed reactive compensation devices, the import cost parameters of the reactive compensation device, and the load parameters of the power system corresponding to the cabled area obtained above can be input into the site selection and capacity determination model of the distribution network for analysis, so as to obtain the initial configuration position and initial capacity of the reactive compensation device. Finally, the target configuration position and target capacity of the reactive compensation device can be determined based on the initial configuration position and initial capacity obtained above, as well as the demand information of the target node in the cabled area. According to the obtained target configuration position and target capacity, the reactive compensation device is installed in the highly cabled area, thereby solving the technical problem of overvoltage in the highly cabled area when the power system is under low load, and achieving the technical effect of maintaining the voltage at a stable voltage in the highly cabled area when the power system is under low load.

[0171] According to an embodiment of the present invention, a device for selecting and sizing a reactive compensation device in a cabled area is provided. It should be noted that the device for selecting and sizing a reactive compensation device in a cabled area can be used to execute a method for selecting and sizing a reactive compensation device in a cabled area in an embodiment.

[0172] Fig.11 is a schematic diagram of a site selection and capacity determination device for a reactive power compensation device in a cabled area according to an embodiment of the present invention. Fig.11 As shown, a device 1100 for selecting a location and determining the capacity of a reactive power compensation device in a cabled area may include: an acquisition unit 1101 , a first determination unit 1102 , an input unit 1103 , and a second determination unit 1104 .

[0173] The acquisition unit 1101 is used to acquire photovoltaic data of the distribution network.

[0174] The first determining unit 1102 is used to determine the reactive power output value of the reactive power compensation device in the cable area of ​​the distribution network based on the photovoltaic data.

[0175] Input unit 1103 is used to input the reactive output value, the number of installed reactive compensation devices, the import cost parameters of the reactive compensation devices, and the load parameters of the power system corresponding to the cabled area into the site selection and sizing model of the distribution network for analysis, so as to obtain the initial configuration position and initial capacity of the reactive compensation device, wherein the site selection and sizing model is used to be constructed through target constraints and objective functions, the target constraints are used to restrict the parameter data of the power system so that the power system can operate normally, and the objective function is used to be established by taking the total cost after installing the reactive compensation device as the target.

[0176] The second determining unit 1104 is used to determine the target configuration position and target capacity of the reactive power compensation device based on the initial configuration position, the initial capacity and the demand information of the target node in the cable area.

[0177] Optionally, the first determination unit 1102 may include: a first acquisition module, used to acquire multiple probability values ​​of photovoltaic data; a second acquisition module, used to cluster the photovoltaic data to obtain a plurality of initial photovoltaic data; a selection module, used to select target photovoltaic data corresponding to the target probability value from a plurality of probability values ​​corresponding to the plurality of initial photovoltaic data; and a first determination module, used to determine the reactive output value of the reactive compensation device based on the target photovoltaic data.

[0178] Optionally, the second determination unit 1104 may include: a third acquisition module, used to obtain the number of nodes in the cabled area; a second determination module, used to determine the indicator function of the target node based on the number of nodes and demand information; a third determination module, used to determine the target configuration position and target capacity based on the indicator function, the initial configuration position and the initial capacity.

[0179] Optionally, the second determination module may include: a first determination submodule, used to determine, in response to the number of nodes being a first value, based on demand information, that the indicator function is a first indicator function, wherein the first indicator function is used to characterize the offset value between the voltage of the target node and a voltage threshold corresponding to the voltage; a second determination submodule, used to determine, in response to the number of nodes being a second value, based on demand information, that the indicator function is a second indicator function, wherein the second indicator function is used to characterize the annual cost of establishing the target node; and a third determination submodule, used to determine, in response to the number of nodes being a third value, based on demand information, that the indicator function is a third indicator function, wherein the third indicator function is used to be established through the offset value and the annual cost.

[0180] Optionally, the target constraint conditions include: a first constraint condition, a second constraint condition, a third constraint condition, a fourth constraint condition and a fifth constraint condition, wherein the first constraint condition is used to characterize the constraints on the power flow data of the power system, the second constraint condition is used to characterize the constraints on the voltage flowing into the cable area, the third constraint condition is used to characterize the constraints on the number of groups and reactive output values ​​of switched capacitors and reactors in the cable area, the fourth constraint condition is used to constrain the reactive output value and active output value of the photovoltaic device in the reactive compensation device, and the fifth constraint condition is used to constrain the reactive output value of the static reactive generator device in the reactive compensation device.

[0181] Optionally, the objective function includes: a first objective function, a second objective function and a third objective function, wherein the first objective function is used to establish the target by taking the installation cost of the reactive compensation device as the target, the second objective function is used to characterize the network loss in the cabled area, and the third objective function is used to characterize the voltage deviation in the cabled area.

[0182] Optionally, the site selection and capacity determination model includes an upper-level planning model and a lower-level planning model, wherein the upper-level planning model is used to be constructed through target constraints and the first objective function in the objective function, and the lower-level planning model is used to be constructed through target constraints and the second objective function and the third objective function in the objective function.

[0183] In this embodiment, the photovoltaic data of the distribution network is acquired by an acquisition unit; the reactive output value of the reactive compensation device in the cabled area of ​​the distribution network is determined by a first determination unit based on the photovoltaic data; the reactive output value, the number of installed reactive compensation devices, the import cost parameters of the reactive compensation device, and the load parameters of the power system corresponding to the cabled area are input into the site selection and capacity determination model of the distribution network for analysis by an input unit to obtain the initial configuration position and initial capacity of the reactive compensation device, wherein the site selection and capacity determination model is used to be constructed through target constraints and target functions, the target constraints are used to restrict the parameter data of the power system so that the power system can operate normally, and the target function is used to be established by taking the total cost after installing the reactive compensation device as the target; the target configuration position and target capacity of the reactive compensation device are determined by a second determination unit based on the initial configuration position, initial capacity and demand information of the target node in the cabled area, so as to solve the technical problem of overvoltage in a highly cabled area when the power system is under low load, and to achieve the technical effect of maintaining a stable voltage in a highly cabled area when the power system is under low load.

[0184] According to an embodiment of the present invention, a computer-readable storage medium is also provided, which includes a stored program, wherein when the program is executed by a processor, the device where the readable storage medium is located is controlled to execute the method for site selection and capacity determination of reactive compensation devices in a cabled area in the embodiment.

[0185] According to an embodiment of the present invention, a processor is further provided, the processor being used to run a program, wherein when the program is run, the method for selecting a site and determining the capacity of a reactive compensation device in a cabled area in the embodiment is executed.

[0186] According to an embodiment of the present invention, a computer program product is also provided, including a computer program. When the computer program is executed by a processor, the method for site selection and capacity determination of reactive power compensation devices in a cabled area in an embodiment of the present invention is implemented.

[0187] According to an embodiment of the present invention, an electronic device is also provided, the electronic device comprising a processor and a memory for storing instructions executable by the processor, wherein the processor is configured to execute the instructions to implement the method for selecting a location and determining the capacity of a reactive power compensation device in a cabled area in an embodiment of the present invention.

[0188] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0189] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0190] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic, for example, the division of units can be a logical function division, and there can be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0191] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0192] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0193] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0194] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for site selection and capacity determination of reactive power compensation devices in a cabled area, characterized in that: include: Obtain photovoltaic data of the distribution network; Based on the photovoltaic data, determining the reactive output value of the reactive power compensation device in the cabled area of ​​the distribution network; The reactive power value, the number of installed reactive compensation devices, the import cost parameters of the reactive compensation devices, and the load parameters of the power system corresponding to the cabled area are input into the site selection and capacity determination model of the distribution network for analysis to obtain the initial configuration position and initial capacity of the reactive compensation device, wherein the site selection and capacity determination model is used to be constructed through target constraints and objective functions, the target constraints are used to restrict the parameter data of the power system so that the power system can operate normally, and the objective function is used to be established by taking the total cost after installing the reactive compensation device as the target; Based on the initial configuration position, the initial capacity and demand information of the target node in the cable area, a target configuration position and a target capacity of the reactive power compensation device are determined.

2. The method according to claim 1, characterized in that Determining the reactive output value of the reactive power compensation device in the cable area of ​​the distribution network based on the photovoltaic data includes: Acquire multiple probability values ​​of the photovoltaic data; Performing clustering processing on the photovoltaic data to obtain a plurality of initial photovoltaic data; Selecting target photovoltaic data corresponding to a target probability value from a plurality of probability values ​​corresponding to the plurality of initial photovoltaic data; Based on the target photovoltaic data, a reactive output value of the reactive compensation device is determined.

3. The method according to claim 1, characterized in that Determining a target configuration position and a target capacity of the reactive power compensation device based on the initial configuration position, the initial capacity, and demand information of a target node in the cabled area includes: Obtaining the number of nodes in the cabled area; Determining an indicator function of the target node based on the number of nodes and the demand information; Based on the indicator function, the initial configuration position and the initial capacity, the target configuration position and the target capacity are determined.

4. The method according to claim 3, characterized in that Determining an indicator function of the target node based on the number of nodes and the demand information includes: In response to the number of nodes being a first value, based on the demand information, determining that the indicator function is a first indicator function, wherein the first indicator function is used to characterize an offset value between a voltage of the target node and a voltage threshold corresponding to the voltage; In response to the number of nodes being a second value, based on the demand information, determining the index function to be a second index function, wherein the second index function is used to characterize an annual cost of establishing the target node; In response to the number of nodes being a third value, based on the demand information, determining that the index function is a third index function, wherein the third index function is used to be established by using the offset value and the annual cost.

5. The method according to claim 1, characterized in that The target constraint conditions include: a first constraint condition, a second constraint condition, a third constraint condition, a fourth constraint condition and a fifth constraint condition, wherein the first constraint condition is used to characterize the constraints on the power flow data of the power system, the second constraint condition is used to characterize the constraints on the voltage flowing into the cable area, the third constraint condition is used to characterize the constraints on the number of groups and reactive output values ​​of switched capacitors and reactors in the cable area, the fourth constraint condition is used to constrain the reactive output value and active output value of the photovoltaic device in the reactive compensation device, and the fifth constraint condition is used to constrain the reactive output value of the static reactive generator device in the reactive compensation device.

6. The method according to claim 1, characterized in that The objective function includes: a first objective function, a second objective function and a third objective function, wherein the first objective function is used to establish by taking the installation cost of the reactive compensation device as a target, the second objective function is used to characterize the network loss in the cabled area, and the third objective function is used to characterize the voltage deviation in the cabled area.

7. The method according to claim 1, characterized in that The site selection and capacity determination model includes an upper-level planning model and a lower-level planning model, wherein the upper-level planning model is used to be constructed through the target constraints and the first objective function in the objective function, and the lower-level planning model is used to be constructed through the target constraints and the second and third objective functions in the objective function.

8. A device for selecting and determining the location and capacity of a reactive power compensation device in a cabled area, characterized in that: include: An acquisition unit, used to acquire photovoltaic data of the distribution network; A first determining unit is used to determine a reactive power output value of a reactive power compensation device in a cabled area in the distribution network based on the photovoltaic data; An input unit is used to input the reactive power value, the number of installed reactive compensation devices, the introduction cost parameters of the reactive compensation devices, and the load parameters of the power system corresponding to the cabled area into the site selection and capacity determination model of the distribution network for analysis, so as to obtain the initial configuration position and initial capacity of the reactive compensation device, wherein the site selection and capacity determination model is used to be constructed through target constraints and objective functions, the target constraints are used to restrict the parameter data of the power system so that the power system can operate normally, and the objective function is used to be established by taking the total cost after installing the reactive compensation device as the target; The second determining unit is used to determine the target configuration position and target capacity of the reactive power compensation device based on the initial configuration position, the initial capacity and demand information of the target node in the cable area.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed by a processor, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: A memory storing an executable program; A processor, configured to run the program, wherein the program executes the method according to any one of claims 1 to 7 when running.

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