Locating and sizing planning method for switch matrix control series-parallel hybrid transformer

Abstract

A locating and sizing planning method for a switch matrix control series-parallel hybrid transformer comprises the following steps: forming a planning scene set, corresponding to each time period power and an SCHT to-be-selected installation position set based on distributed power supply and load historical typical day data; based on the planning scene set, the power corresponding to each time period and the SCHT to-be-selected installation position set, combining a pre-constructed double-layer planning mathematical model, and adopting a hybrid algorithm combining a heuristic optimization algorithm and second-order cone programming for solving to obtain an optimal switch matrix control series-parallel hybrid transformer planning scheme; wherein the pre-constructed double-layer planning mathematical model is a planning layer model constructed by taking the minimum comprehensive cost as the target, an operation layer model constructed by taking the maximum flexibility index as the target, and the pre-constructed double-layer planning mathematical model is constructed by the planning layer model and the operation layer model. According to the method, the SCHT system model suitable for planning is established, and optimal power flow optimization of the power distribution system is considered, so that an optimal configuration scheme considering both economical efficiency and flexibility is obtained.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power distribution network planning, in particular to a method for site selection and capacity determination of a switch matrix controlled series-parallel hybrid transformer. BACKGROUND

[0002] In recent years, with the continuous increase of the penetration rate of distributed photovoltaics in the distribution network, the traditional distribution network is gradually evolving into a new type of local power system with source-load interaction. The uncertainty of new energy and load on the distribution network aggravates the random fluctuation of power flow, and the traditional radial AC distribution network faces challenges such as reduced power supply reliability, difficult power flow interconnection, and insufficient load flexible transfer. Flexible interconnection devices (FID) are the key to improving the safe and flexible operation and flexible regulation capacity of the distribution network, and their importance is increasingly prominent. Under this background, some scholars propose to realize flexible interconnection with power electronic type smart soft switch (SOP), which replaces the traditional circuit breaker tie switch through its accurate and rapid power flow regulation to improve the flexible operation capability of the distribution network. However, the total investment cost of SOP planning is high, and the land occupation area is large, so it can only be planned and configured at a few nodes of the distribution network. Some scholars propose to use electromagnetic rotary power flow controllers as the technical route of FID. Although this device has flexible regulation capability, it has high operation and maintenance complexity and weak fault bearing capacity due to the presence of motor rotating elements, which limits its application.

[0003] In the distribution network, since economy is a key factor in the planning of flexible interconnection equipment, and many application scenarios do not require high dynamic performance of regulation accuracy and response speed, therefore, the electromagnetic FID technical route represented by the switch matrix controlled series-parallel hybrid transformer (SCHT) has emerged as the times require. The main part of the device is composed of parallel and series transformers, and the regulation mechanism is composed of a switch matrix array of thyristor switches or mechanical switches to control the winding mechanism. The compensation voltage coupled by the series-parallel transformer realizes the regulation of line active and reactive power. Some scholars have carried out preliminary research on topology construction and flexible interconnection, but there is still a lack of research on the planning of switch matrix controlled series-parallel hybrid transformers in the distribution network.

[0004] In traditional power distribution network planning, the planning method for flexible interconnection devices mainly adopts a single-objective optimization framework, takes investment economy or operation economy as the core target, and takes device site selection, capacity determination and power characteristics as constraint conditions to obtain the planning configuration scheme of the device. Although the single-objective optimization framework can ensure the optimal economy, it fails to fully consider the effect of FID planning on the safe and flexible operation of the system, which leads to the difficulty in effectively coordinating the relationship between planning economy and system flexibility, and often results in the final planning scheme not being optimal in comprehensive benefits, and unable to achieve the best resource allocation effect. SUMMARY

[0005] In order to solve the problem that the method for considering flexible interconnection devices in traditional power distribution network planning mainly adopts a single-objective optimization framework, takes investment economy or operation economy as the core target, and takes device site selection, capacity determination and power characteristics as constraint conditions, fails to fully consider the effect of FID planning on the safe and flexible operation of the system, and is difficult to effectively coordinate the relationship between planning economy and system flexibility, and cannot obtain a planning scheme with optimal comprehensive benefits, the present application proposes a site selection and capacity determination planning method for switch matrix controlled series-parallel hybrid transformers, comprising: Based on the historical typical day data of distributed power sources and loads, a planning scenario set, corresponding power of each period and a set of selected installation positions of the switch matrix controlled series-parallel hybrid transformers are formed; Based on the planning scenario set, corresponding power of each period and the set of selected installation positions of the switch matrix controlled series-parallel hybrid transformers, a double-layer planning mathematical model is constructed in combination with a heuristic optimization algorithm and a second-order cone programming combined algorithm, and an optimal planning scheme of the switch matrix controlled series-parallel hybrid transformers is obtained; The double-layer planning mathematical model is a planning layer model constructed with the minimum comprehensive cost as the target and a running layer model constructed with the maximum flexibility index as the target.

[0006] Preferably, the construction of the double-layer planning mathematical model comprises: A planning objective function is constructed with the minimum comprehensive cost as the target; Planning constraint conditions are set for the planning objective function; A planning layer model is constructed from the planning objective function and the planning constraint conditions; A running objective function is constructed with the maximum flexibility index as the target; Running constraint conditions are set for the running objective function; A running layer model is constructed from the running objective function and the running constraint conditions; The double-layer planning mathematical model is constructed from the planning layer model and the running layer model; The planning constraint condition comprises an installation position and installation capacity constraint of the SCHT. The operation constraint condition comprises an SCHT operation constraint and a power distribution network operation safety constraint.

[0007] Preferably, the planning objective function is as shown in the following formula:

[0008] In the formula, represents a comprehensive cost, represents an investment planning cost, represents an operation and maintenance cost, represents a power distribution network over-limit penalty cost.

[0009] Preferably, the operation objective function is as shown in the following formula:

[0010] In the formula, represents a flexibility index, represents a feeder load balancing degree index, represents a power distribution main transformer balancing degree index, represents a line capacity adequacy index.

[0011] Preferably, the optimal switch matrix control series-parallel hybrid transformer planning scheme is obtained based on the planning scenario set, the corresponding power of each time period and the switch matrix control series-parallel hybrid transformer candidate installation position set, in combination with a pre-constructed bi-level planning mathematical model, and by using a hybrid algorithm combining a heuristic optimization algorithm and a second-order cone programming. On the basis of the candidate installation position set, the access position and installation capacity of the SCHT are optimized by using the heuristic optimization algorithm to solve the planning layer model, so as to generate an initial configuration scheme of the SCHT site selection and capacity determination; The initial configuration scheme of the SCHT site selection and capacity determination is substituted into the operation layer model, and a second-order cone programming solver is used to calculate the operation indexes in the power distribution network; The initial configuration scheme of the SCHT site selection and capacity determination is optimized based on the fitness of each objective in the planning model revised according to the operation indexes in the power distribution network, so as to obtain the optimal switch matrix control series-parallel hybrid transformer planning scheme; The operation indexes in the power distribution network comprise various operation parameters of each node and branch under different scenarios and at different time periods.

[0012] Preferably, the optimal switch matrix control series-parallel hybrid transformer planning scheme is obtained based on the fitness of each objective in the planning model revised according to the operation indexes in the power distribution network, and the initial configuration scheme of the SCHT site selection and capacity determination is optimized. Step 1: Substitute the operational indicators within the distribution network into the planning model to calculate the new fitness values ​​for each objective; Step 2: Determine whether the number of iterations has been reached. If it has, then the initial configuration scheme for the SCHT's addressing and capacity setting is taken as the optimal planning scheme for the series-parallel hybrid transformer controlled by the switch matrix; otherwise, proceed to Step 3. Step 3: Generate a new location and capacity configuration scheme based on the new fitness values ​​of each target, substitute the new location and capacity configuration scheme into the operation layer model to generate new distribution network operation indicators, assign the new distribution network operation indicators to the distribution network operation indicators, and return to Step 1.

[0013] Furthermore, this invention also provides a site selection and capacity planning system for a switch matrix controlled series-parallel hybrid transformer, comprising: The data processing module is used to generate a set of planning scenarios, corresponding power for each time period, and a set of candidate installation locations for series-parallel hybrid transformers controlled by the switch matrix, based on typical daily historical data of distributed power sources and loads. The scheme planning module is used to obtain the optimal scheme planning for the switch matrix controlled series-parallel hybrid transformer based on the planning scenario set, the power corresponding to each time period, and the set of candidate installation locations for the switch matrix controlled series-parallel hybrid transformer, combined with a pre-constructed two-level planning mathematical model, and using a hybrid algorithm combining heuristic optimization algorithm and second-order cone programming. The pre-constructed two-layer programming mathematical model consists of a planning layer model with the goal of minimizing overall cost and an operation layer model with the goal of maximizing flexibility.

[0014] Preferably, it also includes a model building module for: Construct a planning objective function with the goal of minimizing overall cost; Set planning constraints for the planning objective function; The planning layer model is constructed from the planning objective function and planning constraints; Construct the execution objective function with the goal of maximizing the flexibility index; Set runtime constraints for the objective function; The runtime layer model is constructed from the runtime objective function and runtime constraints; A two-layer programming mathematical model is constructed from the planning layer model and the execution layer model; The planning constraints include: the installation location and installation capacity constraints of the SCHT; The operational constraints include: SCHT operational constraints and distribution network operational safety constraints.

[0015] Preferably, the planning objective function is as follows:

[0016] In the formula, Represents total cost, Represents investment planning costs, Represents operation and maintenance costs, This represents the penalty cost for exceeding the limits in the power distribution network.

[0017] Preferably, the objective function is as follows:

[0018] In the formula, Represents a flexibility indicator. This represents the load balancing index of the feeder. Represents the balance index of main transformers in power distribution. This represents an indicator of the adequacy of line capacity.

[0019] Preferably, the scheme planning module includes: The initial planning submodule is used to solve the planning layer model based on the set of candidate installation locations using a heuristic optimization algorithm, optimize the access location and installation capacity of SCHT, and generate the initial configuration scheme for SCHT location and capacity. The parameter optimization submodule is used to substitute the initial configuration scheme of the SCHT's location and capacity into the operation layer model and use a second-order cone programming solver to calculate the operation indicators within the distribution network. The scheme adjustment submodule is used to revise the fitness of each objective in the planning model based on the operation indicators in the distribution network, optimize the initial configuration scheme of SCHT location and capacity, and obtain the optimal planning scheme of series-parallel hybrid transformer controlled by switch matrix. Among them, the operating indicators within the distribution network include: various operating parameters of each node and branch under different scenarios and at different times.

[0020] Preferably, the scheme adjustment submodule is specifically used for: Step 1: Substitute the operational indicators within the distribution network into the planning model to calculate the new fitness values ​​for each objective; Step 2: Determine whether the number of iterations has been reached. If it has, then the initial configuration scheme for the SCHT's addressing and capacity setting is taken as the optimal planning scheme for the series-parallel hybrid transformer controlled by the switch matrix; otherwise, proceed to Step 3. Step 3: Generate a new location and capacity configuration scheme based on the new fitness values ​​of each target, substitute the new location and capacity configuration scheme into the operation layer model to generate new distribution network operation indicators, assign the new distribution network operation indicators to the distribution network operation indicators, and return to Step 1.

[0021] In another aspect, this application also provides an electronic device, comprising: at least one processor and a memory; the memory and the processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, a method for site selection and capacity planning of a series-parallel hybrid transformer controlled by a switch matrix is ​​implemented as described above.

[0022] In another aspect, this application also provides a computer-readable storage medium having an executable program stored thereon, which, when executed, implements the addressing and sizing planning method for a switch matrix controlled series-parallel hybrid transformer as described above.

[0023] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention provides a site selection and capacity planning method for a switch matrix controlled series-parallel hybrid transformer, comprising: forming a planning scenario set, corresponding power for each time period, and a set of candidate installation locations for the SCHT (Series-Parallel Hybrid Transformer) based on typical historical daily data of distributed power sources and loads; and solving the optimal planning scheme for the switch matrix controlled series-parallel hybrid transformer by combining a pre-constructed two-layer planning mathematical model with a hybrid algorithm combining heuristic optimization and second-order cone programming. The pre-constructed two-layer planning mathematical model consists of a planning layer model with the goal of minimizing overall cost and an operation layer model with the goal of maximizing flexibility. This invention establishes a suitable SCHT system model for planning while considering optimal power flow optimization of the distribution system to obtain an optimized configuration scheme that balances economy and flexibility. Attached Figure Description

[0024] Figure 1 This is a flowchart of a method for site selection and capacity planning of a series-parallel hybrid transformer controlled by a switch matrix according to the present invention; Figure 2 This is a detailed flowchart of a method for site selection and capacity planning of a series-parallel hybrid transformer controlled by a switch matrix, according to an embodiment of the present invention. Figure 3 This is a schematic diagram of the switch matrix controlled series-parallel hybrid transformer of the present invention; Figure 4 This is a diagram of the SCHT equivalent power model of the present invention; Figure 5 This is a flowchart of the solution process for the bi-level programming model of the present invention; Figure 6 This is a schematic diagram of an electronic device structure according to the present invention. Detailed Implementation

[0025] The distribution network planning problem for flexible interconnection of switch matrix controlled series-parallel hybrid transformers (SCHT) is a large-scale multi-objective nonlinear optimization problem. How to construct a scientific and reasonable optimization model and solution method is also a challenge. There is an urgent need for a planning method for switch matrix controlled series-parallel hybrid transformers that aims to improve the economy and flexibility of the distribution network. This method should establish a system model of SCHT devices suitable for planning, while also considering the optimal power flow optimization of the distribution system, so as to obtain an optimal configuration scheme that balances economy and flexibility.

[0026] To address this, this invention proposes a site selection and capacity planning method for a switch matrix controlled series-parallel hybrid transformer (SCHT). This method connects the SCHT as a flexible interconnection device to the distribution network, considers the operating characteristics of the SCHT and its impact on the power of the main transformer and feeders, and fully takes into account the influence of source-load uncertainties at different times and in different scenarios. This invention proposes a site selection and capacity planning method for the SCHT that takes into account both economy and flexibility.

[0027] To better understand the present invention, the following description, in conjunction with the accompanying drawings and embodiments, will further illustrate the content of the present invention.

[0028] Example 1: A method for site selection and capacity planning of a switch matrix controlled series-parallel hybrid transformer, such as... Figure 1 As shown: Step S1: Based on the typical daily historical data of distributed power sources and loads, form a set of planning scenarios, corresponding power for each time period, and a set of candidate installation locations for series-parallel hybrid transformers controlled by switch matrix; Step S2: Based on the planning scenario set, the power of each time period, and the set of candidate installation locations for the series-parallel hybrid transformer controlled by the switch matrix, the optimal planning scheme for the series-parallel hybrid transformer controlled by the switch matrix is ​​obtained by combining the pre-constructed two-layer planning mathematical model with a hybrid algorithm that combines heuristic optimization algorithm and second-order cone programming. The pre-constructed two-layer programming mathematical model consists of a planning layer model with the goal of minimizing overall cost and an operation layer model with the goal of maximizing flexibility.

[0029] The technical solution adopted in this invention is as follows: Before step S1, the construction of the two-level planning data model involved in this invention will be introduced.

[0030] A two-layer optimization model (i.e., a two-layer planning data model) architecture for SCHT is established. The upper-layer model is a planning layer model with economic efficiency as the optimization objective, and the lower-layer model is an operation layer model with maximum flexibility as the optimization objective. Specifically, the planning layer model provides the operation layer model with the SCHT location and capacity configuration scheme that minimizes the overall operating cost; the operation layer model provides the planning layer model with operating parameters such as power flow and voltage distribution, system losses, etc., under the maximum system flexibility, optimizing the overall operating cost and forming the SCHT location and capacity configuration scheme.

[0031] The construction of the bi-level programming mathematical model includes: Construct a planning objective function with the goal of minimizing overall cost; Set planning constraints for the planning objective function; The planning layer model is constructed from the planning objective function and planning constraints; Construct the execution objective function with the goal of maximizing the flexibility index; Set runtime constraints for the objective function; The runtime layer model is constructed from the runtime objective function and runtime constraints; A two-layer programming mathematical model is constructed from the planning layer model and the execution layer model; The planning constraints include: the installation location and installation capacity constraints of the SCHT; The operational constraints include: SCHT operational constraints and distribution network operational safety constraints.

[0032] Furthermore, the planning objective function is shown in the following equation:

[0033] In the formula, Represents total cost, Represents investment planning costs, Represents operation and maintenance costs, This represents the penalty cost for exceeding the limits in the power distribution network.

[0034] The objective function is shown in the following equation:

[0035] In the formula, Represents a flexibility indicator. This represents the load balancing index of the feeder. Represents the balance index of main transformers in power distribution. This represents an indicator of the adequacy of line capacity.

[0036] The specific process of constructing the two-level planning data model is as follows: A model for the upper-level SCHT planning layer is established. The planned installation location and installed capacity of SCHT connected to the distribution network are selected as optimization decision variables in the upper-level model. The specific model is as follows: The upper-level SCHT site selection and capacity planning model uses the minimum annual comprehensive cost of the power distribution system as its objective function, including... , , The three parts represent the comprehensive cost using the basic annual present value, and the objective function expression is as follows:

[0037] In the formula, Represents investment planning costs, Represents operation and maintenance costs, This represents the penalty cost for exceeding the limits in the power distribution network.

[0038] Among them, investment planning cost is an important indicator for measuring the economic efficiency of SCHT plant investment and construction, and its functional expression is:

[0039] In the formula, This represents the discount rate for SCHT equipment. The service life of the equipment. This is a set of potential installation locations for the SCHT device. The unit capacity investment cost of SCHT branch road The installation capacity of the SCHT device , Indicates the node sequence number.

[0040] Operation and maintenance costs measure the comprehensive loss costs in the operation of a distribution network, including the operating loss costs of SCHT devices and the annual loss costs of the distribution network. Its functional expression is:

[0041]

[0042]

[0043] In the formula, This is the annual operation and maintenance cost coefficient for the SCHT unit. The total number of scenes; For the scene The probability of occurrence; The number of time periods involved in the optimization; The length of the time period; Unit electricity price; A collection of distribution network lines; Represents a power distribution network scenario time The line loss power; Representing a scene time The power loss of all installed SCHT devices; branch road The resistance; It is a scene time branch road The current; branch road The active power loss of the SCHT device; s represents the scenario.

[0044] The penalty cost for exceeding limits in a distribution network refers to the losses incurred by the distribution system due to voltage and line current exceeding limits. It is designed to ensure that the voltage and current of the planned distribution network remain within safe operating ranges. Its functional expression is:

[0045]

[0046]

[0047] In the formula, , Representing the scene respectively time The penalty cost caused by exceeding the limits of node voltage and line current is calculated by the cost of unit load failure due to exceeding the limits. Represents the set of nodes in the distribution network. , Representing the scene respectively time Penalty coefficients for node voltage exceeding limits and branch current exceeding limits; , Representing the scene respectively time nodes Load and Branch The active power.

[0048] The calculation methods for the node voltage penalty coefficient and the branch current over-limit penalty coefficient are adjusted according to the degree of exceeding the upper and lower limits, and are expressed as piecewise functions, as shown in the following formulas:

[0049]

[0050] In the formula, It is a scene time node voltage, , These are the upper and lower limits of voltage safety constraints in the distribution network; It is the upper limit of current safety constraints.

[0051] The constraints of the upper-level planning model are the installation location and installation capacity constraints of the SCHT, and the constraint expressions are as follows:

[0052]

[0053]

[0054] In the formula: It is a 0-1 variable, where a value of 0 indicates that the branch does not have SCHT installed, and a value of 1 indicates that the branch has SCHT installed; Unit SCHT installation capacity; It is a side road Configure the maximum capacity of a single SCHT unit.

[0055] Step 3 involves modeling the lower-level SCHT runtime model, specifically including the following steps: Step 3.1: Before modeling the lower-level SCHT operating layer, a steady-state power flow model based on the SCHT flexible interconnection needs to be established. SCHT equipment mainly consists of parallel energy extraction transformers, series coupling transformers, and voltage regulating winding mechanisms, such as... Figure 3 As shown, different phase angles and phase voltages are synthesized by combining adjacent phase sequence voltages to synthesize different amplitudes. Finally, the synthesized vector voltage is coupled to the tie point to achieve flexible interconnection. For the distribution network, the SCHT mainly undertakes the functions of connecting distribution network nodes, regulating interconnected power to improve power flow distribution, and coordinating and optimizing the power of various adjustable resources. The active power and reactive power constraint formulas at both ends of the device are as follows:

[0056]

[0057]

[0058]

[0059]

[0060]

[0061] In the formula: , Indicates the injection node of the SCHT device ,node active power, , Indicates the injection node of the SCHT device ,node reactive power; , This indicates the loss of active and reactive power transferred by the SCHT device; This represents the active power loss coefficient during the power transfer process of the device. This represents the equivalent regulating impedance angle of the SCHT device, reflecting the relationship between the transferred active power and reactive power losses. This indicates the capacity of the SCHT device.

[0062] Step 3.2: Establish an optimization model for the lower-level SCHT operation layer model, using electrical parameters such as power flow, voltage, and current in the distribution network for SCHT operation and regulation as decision variables. The specific model is as follows: The lower-level SCHT operation layer model uses the maximization of distribution network flexibility as its objective function, which includes three indices: feeder load balance, distribution transformer balance, and line capacity adequacy. The objective function expression is as follows:

[0063] In the formula, This represents the load balancing index of the feeder. Represents the balance index of main transformers in power distribution. This represents an indicator of the adequacy of line capacity.

[0064] The feeder load balance index measures the uniformity of load distribution among different feeders in a power distribution network. It is calculated by comparing the load rate of all lines with the average load rate. A higher index reflects a higher system balance, meaning that the system experiences fewer extreme overload or underload situations, and the load rates of each feeder are at reasonable and similar levels. The expression for calculating the index is:

[0065] In the formula: This refers to the number of feeders; For the scene time The The load rate of each branch; For the scene time The average load rate of all feeders For the scene The probability of occurrence For branch road numbering, This represents the number of time periods.

[0066] The distribution transformer balance index measures the regulating margin and flexibility of the upstream main transformer in the distribution network in responding to load surges. It is calculated by the load rate of the main transformer relative to its rated capacity. A higher index reflects sufficient capacity margin in the main transformer, meaning the system has ample reserve capacity and flexible power flow regulation capabilities, and the distribution system has greater flexibility in adjustment. The expression for calculating the index is:

[0067] In the formula: The number of main transformers; For the scene time The The actual apparent power of the main transformer. For the first The rated capacity of each main transformer, This indicates the serial number of the main transformer.

[0068] The line capacity adequacy index measures the flexibility of a power distribution system in terms of power transmission and dynamic response. It is calculated by the difference between the current operating current of a line and the upper limit of the current that the line can safely carry. The higher the index, the greater the redundancy or capacity margin of each line during system operation, meaning that the line has a higher ability to cope with load or new energy growth. The index calculation expression is as follows:

[0069] In the formula: Number of lines; For the scene time The The current value of each branch. For the first The maximum allowable current value for normal operation of the line. This represents the number of time periods.

[0070] The constraints of the lower-level operation layer model include SCHT operation constraints and distribution network operation safety constraints. Among them, distribution network operation safety constraints include system power flow constraints and safe operation constraints.

[0071] The power flow constraints are modeled using the Distflow power flow model. Distflow is a power flow equation established based on branch power, which is more suitable for power flow calculations in radial distribution systems compared to traditional power flow algorithms based on node power. The constraints are as follows:

[0072]

[0073]

[0074]

[0075]

[0076]

[0077] In the formula, , Scenes time branch road By node Flow to Node Active power and reactive power, , Scenes time branch road By node Flow to Node Active power and reactive power, , Scenes time nodes ,node Net active power consumption , Scenes time nodes ,node Net power consumption on top , Scenes time nodes ,node The square of the voltage, For the scene time The square of the branch current, , Scenes time node The active and reactive power of the load, , Scenes time node The active and reactive power of distributed power sources , Scenes time Device SCHT injection node The active and reactive power are represented by i and j, where i and j represent node numbers, t represents time, and s represents the scenario. Indicates a branch The reactance.

[0078] Since the above constraints include non-convex constraints on the squares of branch current, node voltage, and power, the original non-convex nonlinear model can be relaxed and transformed into a rotating second-order cone programming model using convex relaxation techniques, as expressed in:

[0079] In the formula, This represents the L2 norm.

[0080] To ensure the safe operation of the power distribution system, both node voltages and branch currents must satisfy power balance constraints, as shown in the following formula:

[0081]

[0082] In the formula: , These represent the upper and lower limits, respectively, the allowable squares of the node voltages in the system; This represents the upper limit of the square of the allowed branch current.

[0083] For SCHT operational constraints, the corresponding branches are modeled according to the modeling method in step 3.1.

[0084] The completed SCHT equivalent power model (i.e., the operating layer model) is as follows: Figure 4 As shown in the figure, and These represent the SCHT injection nodes of the device. Active power and reactive power, and These represent the SCHT injection nodes of the device. Active power and reactive power, and These represent the losses of active and reactive power transferred by the SCHT device, respectively. Indicates the capacity of the SCHT device. and Representing nodes respectively The active and reactive power of the load. and Representing nodes respectively The active and reactive power of the load. and Representing nodes respectively and nodes The voltage.

[0085] Step S1: Based on historical typical daily data of distributed power sources and loads, form a set of planning scenarios, corresponding power for each time period, and a set of candidate installation locations for series-parallel hybrid transformers controlled by a switch matrix, including: The acquired distributed power sources and typical historical daily data of loads are processed, and combined with the electrical topology of the distribution network, the net load data of each node of the distribution network is calculated to form a set of planning scenarios, the corresponding power for each time period, and a set of SCHT candidate installation locations.

[0086] Step S2: Based on the planning scenario set, the corresponding power for each time period, and the set of candidate installation locations for the series-parallel hybrid transformer controlled by the switch matrix, combined with the pre-constructed two-level planning mathematical model, and using a hybrid algorithm combining heuristic optimization and second-order cone programming, the optimal planning scheme for the series-parallel hybrid transformer controlled by the switch matrix is ​​obtained, including: Based on the set of potential installation locations, a heuristic optimization algorithm is used to solve the planning layer model, optimize the access location and installation capacity of SCHT, and generate an initial configuration scheme for SCHT location and capacity. Substitute the initial configuration scheme of the SCHT location and capacity into the operation layer model, and use a second-order cone programming solver to calculate the operation indicators within the distribution network. Based on the fitness of each objective in the revised planning model of the operation indicators in the distribution network, the initial configuration scheme of the SCHT location and capacity is optimized to obtain the optimal planning scheme of the series-parallel hybrid transformer controlled by the switch matrix. Among them, the operating indicators within the distribution network include: various operating parameters of each node and branch under different scenarios and at different times.

[0087] Furthermore, the optimization of the initial site selection and capacity configuration scheme of the SCHT based on the fitness of each objective in the revised planning model according to the operating indicators within the distribution network, to obtain the optimal planning scheme for the series-parallel hybrid transformer controlled by the switch matrix, includes: Step 1: Substitute the operational indicators within the distribution network into the planning model to calculate the new fitness values ​​for each objective; Step 2: Determine whether the number of iterations has been reached. If it has, then the initial configuration scheme for the SCHT's addressing and capacity setting is taken as the optimal planning scheme for the series-parallel hybrid transformer controlled by the switch matrix; otherwise, proceed to Step 3. Step 3: Generate a new location and capacity configuration scheme based on the new fitness values ​​of each target, substitute the new location and capacity configuration scheme into the operation layer model to generate new distribution network operation indicators, assign the new distribution network operation indicators to the distribution network operation indicators, and return to Step 1.

[0088] Step S2 specifically includes: Step 4.1: The upper-level SCHT planning layer model, based on the set of candidate installation locations, uses a heuristic optimization algorithm to optimize the access location and installation capacity of the SCHT, with the goal of minimizing the annual comprehensive operating cost, to generate an initial configuration scheme for the SCHT's location and capacity, and then distributes this configuration scheme to the lower-level optimization model. Step 4.2: The lower-level SCHT operation layer model imports the SCHT configuration scheme obtained from the upper layer. With the goal of maximizing the flexibility indicators of feeder load balance, distribution transformer balance, and line capacity adequacy, the system power flow is optimized. A second-order cone programming solver is used to calculate the various operating parameters of each node and branch under different scenarios and at different times in the distribution network. Step 4.3: Send the distribution network operation indicators obtained from the lower-level model to the upper-level model, calculate the upper-level objective function value. If the number of iterations is not met, the upper-level model updates the fitness value through a heuristic optimization algorithm, forms a new SCHT configuration scheme, and sends it to the lower-level optimization model again, then proceeds to step 4.2. If the convergence condition is met, proceed to step 4.4. Step 4.4: After multiple alternating iterations and optimizations of the upper and lower SCHT models, and when the convergence condition is met, the optimal SCHT addressing and sizing configuration scheme is output, and the calculation is completed.

[0089] Compared with the prior art, the present invention has the following advantages: This invention proposes a site selection and capacity planning method for a series-parallel hybrid transformer (SCHT) controlled by a switch matrix. It introduces a two-layer planning optimization model for SCHTs. The upper-layer model aims to minimize the system's annual comprehensive cost, while the lower-layer model considers the SCHT's operating characteristics to maximize system flexibility. Compared to existing methods that suffer from a single planning objective, this method balances both economic and flexibility goals. It fully explores the potential for flexible interconnection between distribution networks, resulting in a more rational SCHT configuration scheme and reducing the overall investment cost of system planning.

[0090] The SCHT bi-level programming model of this invention simultaneously establishes optimization models for device planning and device operation. Considering the complexity of the calculation, the complex mixed integer nonlinear model is solved in layers, and a hybrid algorithm combining an improved heuristic optimization algorithm and a second-order cone programming algorithm is adopted to accelerate the solution speed of the model while ensuring accuracy.

[0091] This invention uses SCHT as the core equipment to enhance the flexibility of flexible distribution networks. It can make up for the deficiencies in the planning of flexible interconnection equipment in existing distribution networks, especially solving problems such as poor economic efficiency of interconnection such as SOP. The planning scheme is more scientific and applicable, and adapts to the development trend of flexible distribution networks under new distribution systems.

[0092] It should be noted that the above embodiments are not intended to limit the scope of protection of the present invention. Equivalent transformations or substitutions made based on the above technical solutions all fall within the scope of protection of the claims of the present invention.

[0093] Example 2 To address the aforementioned technical problems, this invention discloses a method for site selection and capacity planning of a series-parallel hybrid transformer controlled by a switch matrix, such as... Figure 2 As shown, it includes the following steps: Step 1: Obtain historical data on the electrical topology, distributed power sources, and loads of the distribution network through a data acquisition system to form typical planning scenarios; Step 2: Construct the upper-level SCHT planning layer model (i.e., the planning layer model). The planning layer model considers the comprehensive economic efficiency of system planning, with the lowest comprehensive operating cost as the optimization objective. In this embodiment, the lowest annual comprehensive operating cost is taken as the optimization objective.

[0094] Step 3: Construct the lower-level SCHT operation layer model. The operation layer model considers the system flexibility index and maximizes the flexibility of system nodes and branches by planning the location, capacity and flexible adjustment operation characteristics of SCHT.

[0095] Step 4: Use a hybrid algorithm that combines heuristic optimization and second-order cone programming (SOCP) to solve the mixed integer nonlinear programming model and obtain the SCHT site selection and capacity planning configuration scheme.

[0096] In step 1, the acquired distributed power sources and typical historical daily data of loads are processed, and the net load data of each node of the distribution network is calculated in combination with the electrical topology of the distribution network to form a set of planning scenarios, corresponding power for each time period, and a set of SCHT candidate installation locations. In step 2, the upper-level SCHT planning layer model is modeled. The upper-level model selects the planned installation location and installation capacity of SCHT connected to the distribution network as optimization decision variables. The specific model is as follows: The upper-level SCHT site selection and capacity planning model uses the minimum annual comprehensive cost of the power distribution system as its objective function, including... , , The three parts represent the comprehensive cost using the basic annual present value, and the objective function expression is as follows:

[0097] In the formula, Represents investment planning costs, Represents operation and maintenance costs, This represents the penalty cost for exceeding the limits in the power distribution network.

[0098] Among them, investment planning cost is an important indicator for measuring the economic efficiency of SCHT plant investment and construction, and its functional expression is:

[0099] In the formula, This represents the discount rate for SCHT equipment. The service life of the equipment. This is a set of potential installation locations for the SCHT device. The unit capacity investment cost of SCHT branch road The installation capacity of the SCHT device.

[0100] Operation and maintenance costs measure the comprehensive loss costs in the operation of a distribution network, including the operating loss costs of SCHT devices and the annual loss costs of the distribution network. Its functional expression is:

[0101]

[0102]

[0103] In the formula, This is the annual operation and maintenance cost coefficient for the SCHT unit. The total number of scenes; For the scene The probability of occurrence; The number of time periods involved in the optimization; The length of the time period; Unit electricity price; A collection of distribution network lines; Represents a power distribution network scenario time The line loss power; Representing a scene time The power loss of all installed SCHT devices; branch road The resistance; It is a scene time branch road The current; branch road Active power loss of the SCHT device.

[0104] The penalty cost for exceeding limits in a distribution network refers to the losses incurred by the distribution system due to voltage and line current exceeding limits. It is designed to ensure that the voltage and current of the planned distribution network remain within safe operating ranges. Its functional expression is:

[0105]

[0106]

[0107] In the formula, , Representing the scene respectively time The penalty cost caused by exceeding the limits of node voltage and line current is calculated by the cost of unit load failure due to exceeding the limits. Represents the set of nodes in the distribution network. , Representing the scene respectively time Penalty coefficients for node voltage exceeding limits and branch current exceeding limits; , Representing the scene respectively time nodes Load and Branch The active power.

[0108] The calculation methods for the node voltage penalty coefficient and the branch current over-limit penalty coefficient are adjusted according to the degree of exceeding the upper and lower limits, and are expressed as piecewise functions, as shown in the following formulas:

[0109]

[0110] In the formula, It is a scene time node voltage, , These are the upper and lower limits of voltage safety constraints in the distribution network; It is the upper limit of current safety constraints.

[0111] The constraints of the upper-level planning model are the installation location and installation capacity constraints of the SCHT, and the constraint expressions are as follows:

[0112]

[0113]

[0114] In the formula: It is a 0-1 variable, where a value of 0 indicates that the branch does not have SCHT installed, and a value of 1 indicates that the branch has SCHT installed; Unit SCHT installation capacity; It is a side road Configure the maximum capacity of a single SCHT unit.

[0115] Step 3 involves modeling the lower-level SCHT runtime model, specifically including the following steps: Step 3.1: Before modeling the lower-level SCHT operating layer, a steady-state power flow model based on SCHT flexible interconnection needs to be established. SCHT equipment mainly consists of parallel energy extraction transformers, series coupling transformers, and voltage regulating winding mechanisms. Different phase angles and phase voltages are synthesized by combining adjacent phase sequence voltages to achieve different amplitudes. Finally, the synthesized vector voltage is coupled to the tie point to realize flexible interconnection. For the distribution network, SCHT mainly undertakes the functions of connecting distribution network nodes, regulating interconnected power to improve power flow distribution, and coordinating and optimizing the power of various adjustable resources. The active and reactive power constraint formulas at both ends of the device are as follows:

[0116]

[0117]

[0118]

[0119]

[0120]

[0121] In the formula: , Indicates the injection node of the SCHT device ,node active power, , Indicates the injection node of the SCHT device ,node reactive power; , This indicates the loss of active and reactive power transferred by the SCHT device; This represents the active power loss coefficient during the power transfer process of the device. This represents the equivalent regulating impedance angle of the SCHT device, reflecting the relationship between the transferred active power and reactive power losses. This indicates the capacity of the SCHT device.

[0122] Step 3.2: Establish an optimization model for the lower-level SCHT operation layer model, using electrical parameters such as power flow, voltage, and current in the distribution network for SCHT operation and regulation as decision variables. The specific model is as follows: The lower-level SCHT operation layer model uses the maximization of distribution network flexibility as its objective function, which includes three indices: feeder load balance, distribution transformer balance, and line capacity adequacy. The objective function expression is as follows:

[0123] In the formula, This represents the load balancing index of the feeder. Represents the balance index of main transformers in power distribution. This represents an indicator of the adequacy of line capacity.

[0124] The feeder load balance index measures the uniformity of load distribution among different feeders in a power distribution network. It is calculated by comparing the load rate of all lines with the average load rate. A higher index reflects a higher system balance, meaning that the system experiences fewer extreme overload or underload situations, and the load rates of each feeder are at reasonable and similar levels. The expression for calculating the index is:

[0125] In the formula: This refers to the number of feeders; For the scene time The The load rate of each branch; For the scene time The average load rate of all feeders.

[0126] The distribution transformer balance index measures the regulating margin and flexibility of the upstream main transformer in the distribution network in responding to load surges. It is calculated by the load rate of the main transformer relative to its rated capacity. A higher index reflects sufficient capacity margin in the main transformer, meaning the system has ample reserve capacity and flexible power flow regulation capabilities, and the distribution system has greater flexibility in adjustment. The expression for calculating the index is:

[0127] In the formula: The number of main transformers; For the scene time The The actual apparent power of the main transformer. For the first The rated capacity of each main transformer.

[0128] The line capacity adequacy index measures the flexibility of a power distribution system in terms of power transmission and dynamic response. It is calculated by the difference between the current operating current of a line and the upper limit of the current that the line can safely carry. The higher the index, the greater the redundancy or capacity margin of each line during system operation, meaning that the line has a higher ability to cope with load or new energy growth. The index calculation expression is as follows:

[0129] In the formula: Number of lines; For the scene time The The current value of each branch. For the first The maximum allowable current value for normal operation of the line.

[0130] The constraints of the lower-level operation layer model include SCHT operation constraints and distribution network operation safety constraints. Among them, distribution network operation safety constraints include system power flow constraints and safe operation constraints.

[0131] The power flow constraints are modeled using the Distflow power flow model. Distflow is a power flow equation established based on branch power, which is more suitable for power flow calculations in radial distribution systems compared to traditional power flow algorithms based on node power. The constraints are as follows:

[0132]

[0133]

[0134]

[0135]

[0136]

[0137] In the formula, , Scenes time branch road By node Flow to Node Active power and reactive power, , Scenes time branch road By node Flow to Node Active power and reactive power, , Scenes time nodes ,node Net active power consumption , Scenes time nodes ,node Net power consumption on top , Scenes time nodes ,node The square of the voltage; For the scene time The square of the branch current, , Scenes time node The active and reactive power of the load, , Scenes time node The active and reactive power of distributed power sources , Scenes time Device SCHT injection node The active power and reactive power.

[0138] Since the above constraints include non-convex constraints on the squares of branch current, node voltage, and power, the original non-convex nonlinear model can be relaxed and transformed into a rotating second-order cone programming model using convex relaxation techniques, as expressed in:

[0139] In the formula, This represents the L2 norm.

[0140] To ensure the safe operation of the power distribution system, both node voltages and branch currents must satisfy power balance constraints, as shown in the following formula:

[0141]

[0142] In the formula: , These represent the upper and lower limits, respectively, the allowable squares of the node voltages in the system; This represents the upper limit of the square of the allowed branch current.

[0143] For SCHT operational constraints, the corresponding branches are modeled according to the modeling method in step 3.1.

[0144] The specific solution method in step 4 is as follows: Step 4.1: The upper-level SCHT planning layer model, based on the set of candidate installation locations, uses a heuristic optimization algorithm to optimize the access location and installation capacity of the SCHT, with the goal of minimizing the annual comprehensive operating cost, to generate an initial configuration scheme for the SCHT's location and capacity, and then distributes this configuration scheme to the lower-level optimization model. Step 4.2: The lower-level SCHT operation layer model imports the SCHT configuration scheme obtained from the upper layer. With the goal of maximizing the flexibility indicators of feeder load balance, distribution transformer balance, and line capacity adequacy, the system power flow is optimized. A second-order cone programming solver is used to calculate the various operating parameters of each node and branch under different scenarios and at different times in the distribution network. Step 4.3: Send the distribution network operation indicators obtained from the lower-level model to the upper-level model, calculate the upper-level objective function value. If the number of iterations is not met, the upper-level model updates the fitness value through a heuristic optimization algorithm, forms a new SCHT configuration scheme, and sends it to the lower-level optimization model again, then proceeds to step 4.2. If the convergence condition is met, proceed to step 4.4. Step 4.4: After multiple alternating iterations and optimizations of the upper and lower SCHT models, and when the convergence condition is met, the optimal SCHT addressing and sizing configuration scheme is output, and the calculation is completed.

[0145] Example 3 To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0146] Embodiments 1 and 2 of the present invention provide a method for SCHT site selection and capacity planning that takes into account both economy and flexibility.

[0147] SCHT is a discrete power flow control electromagnetic flexible device designed to inject compensating voltage into interconnected lines to achieve flexible connections in the distribution network. This embodiment illustrates the principle of a switch matrix controlled series-parallel hybrid transformer device, such as... Figure 3As shown, the SCHT device mainly consists of a parallel energy-harvesting transformer, a series coupling transformer, and a voltage-regulating winding mechanism. The inter-winding adjustment mechanism is controlled by a switch matrix array. During interconnection, energy is harvested from the primary side of the parallel transformer to provide excitation voltage. Multiple voltage regulation levels are formed through the combination of multiple windings on the secondary side. Different phase angles and phase voltages are synthesized by combining adjacent phase sequence voltages to synthesize different amplitudes. Finally, the synthesized vector voltage is coupled to the tie point through the series transformer to achieve flexible interconnection. In the figure, the primary sides of the three-phase parallel transformer are A, B, and C, respectively, and the end phases are connected to form the neutral point o. The power supply ports U, V, and W of the power supply winding can supply power to the load, realizing single-phase or three-phase power supply. With port N, a three-phase four-wire power supply can be realized. N is the neutral point, and a, b, and c represent phases A, B, and C of the system. The nine secondary windings of the parallel transformer are divided into three groups, each taking a different phase primary side and connected in series to the series transformer. One end of the series transformer is a', b', and c', and the other end is the neutral point o'. For distribution networks, the main functions of the SCHT (Series-Parallel Hybrid Transformer) are to connect distribution network nodes, regulate interconnected power to improve power flow distribution, and coordinate and optimize the power of various adjustable resources. This invention proposes to connect the SCHT as a flexible interconnection device into the distribution network, taking into account the operating characteristics of the SCHT and its impact on the power of the main transformer and feeders, and fully considering the impact of source-load uncertainties at different times and in different scenarios.

[0148] The technical solution adopted in this invention is as follows: A two-layer optimization model architecture for SCHT is established. The upper-layer model is a planning layer model with economic efficiency as the optimization objective, and the lower-layer model is an operation layer model with maximum flexibility as the optimization objective. Specifically, the planning layer model provides the operation layer model with the SCHT site selection and capacity allocation scheme that minimizes the annual comprehensive operating cost; the operation layer model provides the planning layer model with operating parameters such as power flow and voltage distribution, system losses, etc., under the maximum system flexibility, to optimize the annual comprehensive operating cost and form the SCHT site selection and capacity allocation scheme.

[0149] To address the aforementioned technical issues, such as Figure 5 As shown, it includes the following steps: Step 1: Obtain historical data on the electrical topology, distributed power sources, and loads of the distribution network through a data acquisition system to form typical planning scenarios; Step 2: Construct the upper-level SCHT planning layer model. The planning layer model considers the comprehensive economic efficiency of system planning, with the goal of minimizing the annual comprehensive operating cost.

[0150] Step 3: Construct the lower-level SCHT operation layer model. The operation layer model considers the system's operational flexibility and maximizes the flexibility of system nodes and branches by planning the location, capacity, and flexible adjustment characteristics of SCHT.

[0151] Step 4: To solve the two-level optimization model of this mixed integer nonlinear programming, this embodiment of the invention proposes to use a heuristic algorithm represented by particle swarm optimization (PSO) combined with a hybrid algorithm of second-order cone programming (SOCP) to solve the model and obtain the SCHT site selection and occupancy scheme.

[0152] In step 1, the acquired distributed power sources and typical historical daily data of loads are processed, and the net load data of each node of the distribution network is calculated in combination with the electrical topology of the distribution network to form a set of planning scenarios, corresponding power for each time period, and a set of SCHT candidate installation locations. The steps of constructing the upper-level SCHT planning layer model in step 2 and constructing the lower-level SCHT operation layer model in step 3 are the same as those in the above embodiments, and will not be repeated here.

[0153] This embodiment establishes a steady-state power flow model (i.e., operation layer model) based on SCHT flexible interconnection. SCHT serves as a flexible interconnection branch of the distribution network. Active and reactive power flows into and out of the SCHT are constructed, with inflows into the distribution network being positive and outflows from the distribution network being negative. This is used to construct the active and reactive power constraints at both ends of the SCHT device, as shown in the following formula:

[0154]

[0155]

[0156]

[0157]

[0158]

[0159] In the formula: , Indicates the injection node of the SCHT device ,node active power, , Indicates the injection node of the SCHT device ,node reactive power; , This indicates the loss of active and reactive power transferred by the SCHT device; This represents the active power loss coefficient during the power transfer process of the device. This represents the equivalent regulating impedance angle of the SCHT device, reflecting the relationship between the transferred active power and reactive power losses. This indicates the capacity of the SCHT device.

[0160] The specific solution method in step 4 is shown in Figure 4 of Example 4, and is as follows: Step 4.1, the upper-level SCHT planning layer model, based on the set of candidate installation locations, encodes the SCHT capacity and location using particle information from the particle swarm optimization algorithm, optimizes the SCHT site selection and capacity planning, and generates an initial SCHT site selection and capacity configuration scheme with the goal of minimizing the annual comprehensive operating cost. This configuration scheme is then distributed to the lower-level optimization model. Step 4.2: The lower-level SCHT operation layer model imports the SCHT configuration scheme obtained from the upper layer. With the goal of maximizing the flexibility indicators of feeder load balance, distribution transformer balance, and line capacity adequacy, the system power flow is optimized. A second-order cone programming solver is used to calculate the various operating parameters of each node and branch under different scenarios and at different times in the distribution network. Step 4.3: Send the distribution network operation indicators obtained from the lower-level model to the upper-level model, calculate the upper-level objective function value. If the number of iterations is not met, the upper-level model updates the fitness value through a heuristic optimization algorithm, forms a new SCHT configuration scheme, and sends it to the lower-level optimization model again, then proceeds to step 4.2. If the convergence condition is met, proceed to step 4.4. Step 4.4: After multiple alternating iterations and optimizations of the upper and lower SCHT models, and when the convergence condition is met, the optimal SCHT addressing and sizing configuration scheme is output, and the calculation is completed.

[0161] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

[0162] Example 4 Based on the same inventive concept, this invention also provides a site selection and capacity planning system for a switch matrix controlled series-parallel hybrid transformer, comprising: The data processing module is used to generate a set of planning scenarios, corresponding power for each time period, and a set of candidate installation locations for series-parallel hybrid transformers controlled by the switch matrix, based on typical daily historical data of distributed power sources and loads. The scheme planning module is used to obtain the optimal scheme planning for the switch matrix controlled series-parallel hybrid transformer based on the planning scenario set, the power corresponding to each time period, and the set of candidate installation locations for the switch matrix controlled series-parallel hybrid transformer, combined with a pre-constructed two-level planning mathematical model, and using a hybrid algorithm combining heuristic optimization algorithm and second-order cone programming. The pre-constructed two-layer programming mathematical model consists of a planning layer model with the goal of minimizing overall cost and an operation layer model with the goal of maximizing flexibility.

[0163] Preferably, it also includes a model building module for: Construct a planning objective function with the goal of minimizing overall cost; Set planning constraints for the planning objective function; The planning layer model is constructed from the planning objective function and planning constraints; Construct the execution objective function with the goal of maximizing the flexibility index; Set runtime constraints for the objective function; The runtime layer model is constructed from the runtime objective function and runtime constraints; A two-layer programming mathematical model is constructed from the planning layer model and the execution layer model; The planning constraints include: the installation location and installation capacity constraints of the SCHT; The operational constraints include: SCHT operational constraints and distribution network operational safety constraints.

[0164] Preferably, the planning objective function is as follows:

[0165] In the formula, Represents total cost, Represents investment planning costs, Represents operation and maintenance costs, This represents the penalty cost for exceeding the limits in the power distribution network.

[0166] Preferably, the objective function is as follows:

[0167] In the formula, Represents a flexibility indicator. This represents the load balancing index of the feeder. Represents the balance index of main transformers in power distribution. This represents an indicator of the adequacy of line capacity.

[0168] Preferably, the scheme planning module includes: The initial planning submodule is used to solve the planning layer model based on the set of candidate installation locations using a heuristic optimization algorithm, optimize the access location and installation capacity of SCHT, and generate the initial configuration scheme for SCHT location and capacity. The parameter optimization submodule is used to substitute the initial configuration scheme of the SCHT's location and capacity into the operation layer model and use a second-order cone programming solver to calculate the operation indicators within the distribution network. The scheme adjustment submodule is used to revise the fitness of each objective in the planning model based on the operation indicators in the distribution network, optimize the initial configuration scheme of SCHT location and capacity, and obtain the optimal planning scheme of series-parallel hybrid transformer controlled by switch matrix. Among them, the operating indicators within the distribution network include: various operating parameters of each node and branch under different scenarios and at different times.

[0169] Preferably, the scheme adjustment submodule is specifically used for: Step 1: Substitute the operational indicators within the distribution network into the planning model to calculate the new fitness values ​​for each objective; Step 2: Determine whether the number of iterations has been reached. If it has, then the initial configuration scheme for the SCHT's addressing and capacity setting is taken as the optimal planning scheme for the series-parallel hybrid transformer controlled by the switch matrix; otherwise, proceed to Step 3. Step 3: Generate a new location and capacity configuration scheme based on the new fitness values ​​of each target, substitute the new location and capacity configuration scheme into the operation layer model to generate new distribution network operation indicators, assign the new distribution network operation indicators to the distribution network operation indicators, and return to Step 1.

[0170] Example 5 like Figure 6 As shown, the present invention also provides an electronic device, which may be a computer device, a microcontroller device, a smart mobile device, etc. The electronic device in this embodiment may include a processor, a memory, a transceiver component, etc. The memory, processor, and transceiver component are connected via a bus; the memory can be used to store executable programs, and an exemplary executable program may include instructions; the processor is used to execute the instructions stored in the memory. The memory can also be used to store data, which can be accessed and / or modified when instructions are executed.

[0171] The processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, and it is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the storage medium to realize the corresponding method flow or corresponding function, so as to realize the steps of the addressing and capacity planning method of a switch matrix controlled series-parallel hybrid transformer in the above embodiment.

[0172] Example 6 Based on the same inventive concept, this invention also provides a readable storage medium, specifically an electronic device readable storage medium (Memory). This readable storage medium is a memory device within an electronic device used to store programs and data. It is understood that the storage medium here can include both built-in storage media within the electronic device and extended storage media supported by the electronic device. The storage medium provides storage space, which stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more executable programs (including program code). It should be noted that the storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. Loading and executing one or more instructions stored in the storage medium by the processor can implement the steps of the addressing and capacity planning method for a switch matrix controlled series-parallel hybrid transformer in the above embodiments.

[0173] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0174] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0175] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0176] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0177] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A method for switch matrix control of sizing and location planning of a series-parallel hybrid transformer, characterized in that, The application comprises the following steps: Based on the distributed power supply and load historical typical day data, a planning scenario set, corresponding power of each period and a switch matrix control series-parallel hybrid transformer candidate installation location set are formed; Based on the planning scenario set, corresponding power of each period and the switch matrix control series-parallel hybrid transformer candidate installation location set, a pre-constructed bi-level planning mathematical model is combined, and a hybrid algorithm combining a heuristic optimization algorithm and a second-order cone programming is used for solving, so that an optimal switch matrix control series-parallel hybrid transformer planning scheme is obtained. The pre-constructed bi-level planning mathematical model is a planning layer model constructed with the minimum comprehensive cost as the target and an operation layer model constructed with the maximum flexibility index as the target.

2. The method of claim 1, wherein, The bi-level planning mathematical model is constructed by the following steps: A planning objective function is constructed with the minimum comprehensive cost as the target; Planning constraint conditions are set for the planning objective function; A planning layer model is constructed from the planning objective function and the planning constraint conditions; An operation objective function is constructed with the maximum flexibility index as the target; Operation constraint conditions are set for the operation objective function; An operation layer model is constructed from the operation objective function and the operation constraint conditions; A bi-level planning mathematical model is constructed from the planning layer model and the operation layer model. The planning constraint conditions include SCHT installation location and installation capacity constraints. The operation constraint conditions include SCHT operation constraints and power distribution network operation safety constraints.

3. The method of claim 2, wherein, The planning objective function is shown in the following formula: In the formula, represents the comprehensive cost, represents the investment planning cost, represents the operation and maintenance cost, represents the power distribution network over-limit penalty cost.

4. The method of claim 2, wherein, The operation objective function is shown in the following formula: In the formula, represents a flexibility index, represents a feeder load balance index, represents a distribution main transformer balance index, represents a line capacity adequacy index.

5. The method of claim 1, wherein, The optimal switch matrix control series-parallel hybrid transformer planning scheme is obtained by combining the pre-constructed bi-level planning mathematical model and the hybrid algorithm combining the heuristic optimization algorithm and the second-order cone programming based on the planning scenario set, corresponding power of each period and the switch matrix control series-parallel hybrid transformer candidate installation location set, and comprises the following steps: On the basis of the candidate installation location set, the heuristic optimization algorithm is used to solve the planning layer model, the access location and installation capacity of the SCHT are optimized, and an SCHT site selection and capacity determination initial configuration scheme is generated; The SCHT site selection and capacity determination initial configuration scheme is substituted into the operation layer model, and a second-order cone programming solver is used to calculate the operation index in the power distribution network; Based on the operation index in the power distribution network, the fitness of each target in the planning model is revised, the SCHT site selection and capacity determination initial configuration scheme is optimized, and the optimal switch matrix control series-parallel hybrid transformer planning scheme is obtained. The operation index in the power distribution network includes various operation parameters of each node and branch under different scenarios and at different time points.

6. The method of claim 5, wherein, The optimal switch matrix control series-parallel hybrid transformer planning scheme is obtained by revising the fitness of each target in the planning model based on the operation index in the power distribution network and optimizing the SCHT site selection and capacity determination initial configuration scheme, and comprises the following steps: Step 1: The operation index in the power distribution network is substituted into the planning model to calculate the new fitness value of each target; Step 2: determining whether the number of iterations is reached, if yes, taking the initial configuration scheme of the location and capacity of the SCHT as the optimal switch matrix controlled series-parallel hybrid transformer planning scheme; otherwise, going to step 3; Step 3: generating a new location and capacity configuration scheme according to the new fitness values of the targets, substituting the new location and capacity configuration scheme into the operation layer model to produce new in-distribution network operation indexes, assigning the new in-distribution network operation indexes to the in-distribution network operation indexes, and returning to step 1.

7. A system for selecting the location and capacity planning of a hybrid transformer controlled by a switching matrix, characterized in that, Comprise: A data processing module is configured to form a planning scenario set, corresponding power of each period and a set of candidate installation positions of the switch matrix controlled series-parallel hybrid transformer based on historical typical day data of the distributed power supply and the load; A scheme planning module is configured to obtain the optimal switch matrix controlled series-parallel hybrid transformer planning scheme by combining a pre-constructed double-layer planning mathematical model and a hybrid algorithm combining a heuristic optimization algorithm and a second-order cone programming based on the planning scenario set, corresponding power of each period and the set of candidate installation positions of the switch matrix controlled series-parallel hybrid transformer. The pre-constructed double-layer planning mathematical model is a planning layer model constructed with the minimum comprehensive cost as the target and an operation layer model constructed with the maximum flexibility index as the target.

8. The system of claim 7, wherein, Further comprise a model construction module configured to: construct a planning objective function with the minimum comprehensive cost as the target; set planning constraints for the planning objective function; construct the planning layer model from the planning objective function and the planning constraints; construct an operation objective function with the maximum flexibility index as the target; set operation constraints for the operation objective function; construct the operation layer model from the operation objective function and the operation constraints; construct the double-layer planning mathematical model from the planning layer model and the operation layer model. The planning constraints comprise SCHT installation position and installation capacity constraints. The operation constraints comprise SCHT operation constraints and distribution network operation safety constraints.

9. The system of claim 8, wherein, The planning objective function is shown in the following formula: In the formula, represents the comprehensive cost, represents the investment planning cost, represents the operation and maintenance cost, represents the power distribution network over-limit penalty cost.

10. The system of claim 8, wherein, The operation objective function is shown in the following formula: In the formula, represents a flexibility index, represents a feeder load balance index, represents a distribution main transformer balance index, represents a line capacity adequacy index.

11. The system of claim 7, wherein, The scheme planning module comprises: An initial planning submodule is configured to optimize the access position and installation capacity of the SCHT by solving the planning layer model with the heuristic optimization algorithm based on the set of candidate installation positions, and generate an initial configuration scheme of the location and capacity of the SCHT; A parameter optimization submodule is configured to substitute the initial configuration scheme of the location and capacity of the SCHT into the operation layer model, and calculate in-distribution network operation indexes by using a second-order cone programming solver; A scheme adjustment submodule is configured to revise the fitness of each target in the planning model based on the in-distribution network operation indexes, optimize the initial configuration scheme of the location and capacity of the SCHT, and obtain the optimal switch matrix controlled series-parallel hybrid transformer planning scheme. The in-distribution network operation indexes comprise various operation parameters of each node and branch under different scenarios and at different time.

12. The system of claim 11, wherein, The scheme adjustment submodule is specifically configured to: Step 1: substitute the in-distribution network operation indexes into the planning model to calculate new fitness values of the targets; Step 2: determining whether the iteration number is reached, if yes, taking the initial configuration scheme of the SCHT's location and capacity as the optimal switch matrix controlled series-parallel hybrid transformer planning scheme; otherwise, entering step 3; Step 3: generating a new location and capacity configuration scheme according to the new fitness value of each target, substituting the new location and capacity configuration scheme into the operation layer model to produce a new distribution network operation index, assigning the new distribution network operation index to the distribution network operation index, and returning to step 1.

13. An electronic device, comprising: Comprise: At least one processor and a memory; The memory and the processor are connected through a bus; The memory is used for storing one or more programs; When the one or more programs are executed by the at least one processor, a switch matrix controlled series-parallel hybrid transformer location and capacity planning method as claimed in any one of claims 1 to 6 is implemented.

14. A readable storage medium, characterized by, An execution program is stored thereon, and the execution program is executed to implement a switch matrix controlled series-parallel hybrid transformer location and capacity planning method as claimed in any one of claims 1 to 6.

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