Power distribution network transformation method and device, electronic equipment and computer readable storage medium

Abstract

The invention discloses a transformation method and device of a power distribution network, electronic equipment and a computer readable storage medium. The method comprises the steps that network topology structure parameters of the power distribution network and electric power parameters of the power distribution network are acquired, the network topology structure parameters are used for representing equipment connection relations in the power distribution network, and the electric power parameters are used for representing electric power system characteristics and operation states of the power distribution network; the network topology parameters and the electric power parameters are analyzed based on a pre-established power distribution network flexible transformation model, a transformation strategy of the power distribution network is obtained, and the power distribution network flexible transformation model takes the power supply reliability and the minimum annual comprehensive cost of the power distribution network as transformation targets; and based on the transformation strategy, transforming the power distribution network to obtain a transformed power distribution network. The technical problem that the power supply reliability and the investment cost of the power distribution network cannot be effectively balanced when the power distribution network is transformed is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a method, device, electronic equipment and computer-readable storage medium for transforming a distribution network. Background Art

[0002] At present, with the rapid development of social economy, the demand for electricity continues to rise, especially in high-load density areas, and the traditional AC distribution network has gradually shown problems of insufficient power supply capacity, such as line congestion, increased network loss, and voltage over-limit, etc. In addition, with the promotion of low-carbonization and green energy transformation trends, the penetration rate of renewable energy such as solar energy and wind energy has gradually increased, bringing challenges of volatility and intermittency to the distribution network.

[0003] In the related technologies, when implementing flexible transformation of distribution networks, most of them only focus on the planning of a single type of equipment, but fail to fully consider the balance between the reliability of the entire distribution network system and the economic efficiency of investment while improving the power supply capacity.

[0004] With respect to the above-mentioned technical problem of being unable to effectively balance the power supply reliability and investment cost of the distribution network when transforming the distribution network, no effective solution has been proposed so far. Summary of the invention

[0005] Embodiments of the present invention provide a method, device, electronic device and computer-readable storage medium for transforming a distribution network, so as to at least solve the technical problem that the power supply reliability and investment cost of the distribution network cannot be effectively balanced when transforming the distribution network.

[0006] According to one aspect of an embodiment of the present invention, a method for transforming a distribution network is provided. The method may include: obtaining network topology parameters of the distribution network and power parameters of the distribution network, wherein the network topology parameters are used to characterize the equipment connection relationship in the distribution network, and the power parameters are used to characterize the power system characteristics and operating status of the distribution network; analyzing the network topology parameters and power parameters based on a pre-established distribution network flexible transformation model to obtain a transformation strategy for the distribution network, wherein the distribution network flexible transformation model takes the power supply reliability of the distribution network and the minimization of the annual comprehensive cost as the transformation goals; based on the transformation strategy, transforming the distribution network to obtain a transformed distribution network.

[0007] Optionally, the power parameters of the distribution network include at least: AC and DC line parameters of the distribution network, converter parameters of the distribution network, distributed power supply parameters of the distribution network, load parameters of the distribution network, energy storage device parameters of the distribution network, and reliability-related parameters of the distribution network.

[0008] Optionally, the distribution network flexible transformation model includes at least an objective function aiming at minimizing the annual comprehensive cost of the distribution network, and constraints corresponding to the power grid flow sub-model, key equipment sub-model and reliability assessment sub-model respectively.

[0009] Optionally, network topology parameters and power parameters are analyzed based on a pre-established distribution network flexible transformation model to obtain a transformation strategy for the distribution network, including: calculating equipment investment costs, equipment maintenance costs, electricity purchase costs and load shedding costs in the distribution network based on an objective function; calculating the minimized annual comprehensive cost of the distribution network based on the equipment investment cost, equipment maintenance cost, electricity purchase cost and load shedding cost; and guiding the generation of a distribution network transformation strategy based on the annual comprehensive cost.

[0010] Optionally, the constraints corresponding to the power grid flow sub-model include at least: power balance constraints, node voltage constraints and line capacity constraints, wherein the power balance constraints are used to ensure that the active power and reactive power input and output of all nodes in the distribution network remain balanced, the node voltage constraints are used to ensure that the voltage level of each node in the distribution network remains within a threshold range within a specified time range, and the line capacity constraints are used to ensure that the current of each transmission line in the distribution network does not exceed the rated current. Based on the pre-established distribution network flexible transformation model, the network topology parameters and power parameters are analyzed to obtain the transformation strategy of the distribution network, which also includes: based on the power balance constraints, node voltage constraints, and line capacity constraints in the power grid flow sub-model, guiding the generation of the distribution network transformation strategy.

[0011] Optionally, the constraints corresponding to the key equipment sub-model include at least photovoltaic power supply constraints, converter constraints, DC line constraints and energy storage equipment constraints, wherein the photovoltaic power supply constraints are used to characterize the power output characteristics of the photovoltaic system in the distribution network, the converter constraints are used to control the converter connecting the AC power grid and the DC power grid in the distribution network to provide sufficient power conversion capability under various operating conditions, the DC line constraints are used to ensure that the current and voltage of each transmission line in the DC distribution system in the distribution network operate within a safe range, and the energy storage equipment constraints are used to ensure that the power and energy of the energy storage equipment in the distribution network during the charging and discharging process are within the operating boundary of the energy storage equipment. Based on the pre-established distribution network flexible transformation model, the network topology parameters and power parameters are analyzed to obtain the transformation strategy of the distribution network, which also includes: based on the photovoltaic power supply constraints, converter constraints, DC line constraints and energy storage equipment constraints in the key equipment sub-model, guiding the generation of the transformation strategy of the distribution network.

[0012] Optionally, the constraints of the reliability assessment sub-model are used to evaluate the operating characteristics of the distribution network under different fault scenarios, and the network topology parameters and power parameters are analyzed based on a pre-established distribution network flexible transformation model to obtain a transformation strategy for the distribution network. It also includes: based on the constraints of the reliability sub-model in the reliability assessment sub-model, guiding the generation of a transformation strategy for the distribution network.

[0013] According to another aspect of an embodiment of the present invention, a device for generating a transformation model of a distribution network is also provided. The device may include: an acquisition unit, used to acquire network topology parameters of the distribution network and power parameters of the distribution network, wherein the network topology parameters are used to characterize the connection relationship of the equipment in the distribution network, and the power parameters are used to characterize the power system characteristics and operating status of the distribution network; an analysis unit, used to analyze the network topology parameters and power parameters based on a pre-established flexible transformation model of the distribution network to obtain a transformation strategy of the distribution network, wherein the flexible transformation model of the distribution network takes the power supply reliability of the distribution network and the minimization of the annual comprehensive cost as the transformation goals; a transformation unit, used to transform the distribution network based on the transformation strategy to obtain a transformed distribution network.

[0014] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including 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 distribution network transformation method in an embodiment of the present invention.

[0015] According to another aspect of an embodiment of the present invention, a processor is further provided. The processor is used to run a program, wherein when the program is run, the method for transforming a power distribution network in an embodiment of the present invention is executed.

[0016] According to another aspect of the embodiments of the present invention, a computer program product is provided, which includes computer instructions, and when the computer instructions are executed by a processor, the method for transforming the power distribution network in the embodiments of the present invention is implemented.

[0017] In an embodiment of the present invention, the network topology parameters of the distribution network and the power parameters of the distribution network are obtained, wherein the network topology parameters are used to characterize the equipment connection relationship in the distribution network, and the power parameters are used to characterize the power system characteristics and operating status of the distribution network; the network topology parameters and the power parameters are analyzed based on the pre-established flexible transformation model of the distribution network to obtain the transformation strategy of the distribution network, wherein the flexible transformation model of the distribution network takes the power supply reliability of the distribution network and the minimization of the annual comprehensive cost as the transformation target; based on the transformation strategy, the distribution network is transformed to obtain the transformed distribution network. That is to say, in an embodiment of the present invention, based on the topology and power parameters of the distribution network, the transformation strategy of the distribution network is obtained through the flexible transformation model of the distribution network. Since the flexible transformation model of the distribution network takes the power supply reliability of the distribution network as the core consideration factor and takes the minimization of the annual comprehensive cost as the transformation target, therefore, the distribution network is transformed through the transformation strategy determined by the flexible transformation model of the distribution network, so that the transformed distribution network can balance the economy and system reliability, realize the efficient, stable and flexible operation of the distribution network, and thus solve the technical problem that the power supply reliability and investment cost of the distribution network cannot be effectively balanced when the distribution network is transformed. 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 this application. 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 transforming a distribution network according to an embodiment of the present invention;

[0020] Figure 2 is a schematic diagram of an equivalent circuit model of a two-terminal DC line implemented according to the present invention;

[0021] Figure 3 is a schematic diagram of a power distribution system according to an embodiment of the present invention;

[0022] Figure 4 is a schematic diagram of a modified power distribution system according to an embodiment of the present invention;

[0023] Figure 5 is a schematic diagram of a power supply situation in a high load density area according to an embodiment of the present invention;

[0024] Figure 6 is a schematic diagram of a power supply situation of a distribution network 2 according to an embodiment of the present invention;

[0025] Figure 7 is a schematic diagram of a distribution network transformation device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] 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.

[0027] 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, functional component or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, functional components or devices.

[0028] Example 1

[0029] According to an embodiment of the present invention, an embodiment of a method for transforming a distribution network is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings 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 can be executed in an order different from that shown here.

[0030] Figure 1 is a flow chart of a method for transforming a distribution network according to an embodiment of the present invention. Figure 1 As shown, the method may include the following steps:

[0031] Step S101, obtaining network topology parameters and power parameters of the distribution network.

[0032] In the technical solution provided in the above step S101 of the present invention, the network topology parameters are used to characterize the equipment connection relationship in the distribution network, and the power parameters are used to characterize the power system characteristics and operating status of the distribution network.

[0033] In this embodiment, network topology parameters, AC and DC line parameters, converter parameters, distributed power supply parameters, load parameters, energy storage device parameters, and reliability-related parameters of the distribution network are obtained.

[0034] Optionally, the network topology parameters of the distribution network include a voltage range, a voltage level and a grid structure in the distribution network, wherein the voltage range refers to an allowable interval of voltage fluctuation in the distribution network. During the operation of the distribution network, the voltage will fluctuate within a certain range due to factors such as load changes, power output fluctuations and grid structure. The voltage level is used to indicate the standard voltage level in the distribution network. According to different application scenarios and equipment requirements, the distribution network may include multiple voltage levels.

[0035] Optionally, the AC and DC line parameters include line capacity, line impedance and line length of the transmission lines in the distribution network, wherein the line capacity is used to indicate the maximum power value that the transmission line can transmit under safe operating conditions, the line impedance is a parameter that measures the degree of obstruction of the transmission line to the flow of current, and is composed of resistance and reactance, and the line length (in meters or kilometers) is a direct measurement of the physical length of the transmission line.

[0036] Optionally, the converter parameters include at least the cost and equivalent impedance of the converter between the DC system and the AC system in the distribution network, wherein the converter cost refers to the one-time investment cost of the converter equipment when building or upgrading the distribution network, as well as the subsequent operation and maintenance costs. The equivalent impedance is used to indicate the impedance characteristics presented by the converter from the perspective of the power grid when performing AC-DC or DC-AC conversion.

[0037] Optionally, the distributed power supply parameters include at least power factor and power output forecast value, wherein the power factor is a measure of the ratio of actual power (active power) to apparent power (i.e., the vector sum of active power and reactive power) in the power system. In an AC power system, the power factor reflects the degree of effective utilization of the power output of the power supply. The power output forecast value is a prediction of the output power of the distributed power supply in the future. Since the output of distributed power sources (especially solar and wind power) is greatly affected by weather and time factors, its power output is intermittent and uncertain.

[0038] Optionally, the load parameters include at least a typical daily load curve and peak loads at each node of the system, wherein the typical daily load curve is used to show a graph of load changes over time within a day, which reflects the user's power demand pattern in different time periods. The curve is usually based on historical data statistics and represents the average or typical behavior of the load on a certain type of day (such as weekdays, weekends, holidays). The peak load of each node of the system is used to indicate the maximum power consumption value of each node in the distribution network at a specific time point or within a period of time, usually in kilowatts (kW). The peak load reflects the power supply pressure and demand of the power grid when it is at its highest load state.

[0039] Optionally, the energy storage device parameters include at least upper and lower limits of the charge level, the initial charge level, the charge and discharge efficiency, and the unit capacity cost, wherein the upper and lower limits of the charge level define the range of the state of charge of the energy storage device during operation, that is, the minimum and maximum allowable state of charge. The initial charge level indicates the state of charge of the energy storage device when it starts running, that is, the amount of electrical energy stored when the energy storage device is started. The charge and discharge efficiency describes the energy conversion efficiency of the energy storage device during the charging and discharging process, usually expressed as a percentage. For example, if the charge and discharge efficiency is 85%, then when the energy storage device is charging, only 85% of the input electrical energy can be actually stored, and when discharging, only 85% of the stored electrical energy can be output for use. The unit capacity cost refers to the cost of the energy storage device per unit storage capacity (usually in kW·h or MWh), including equipment purchase cost, installation cost, operation and maintenance cost, etc.

[0040] Optionally, the reliability-related parameters include at least component failure rate, mean failure duration, and unit load shedding cost, wherein the component failure rate refers to the probability of failure of each component (such as transformer, line, circuit breaker, etc.) in the power system within a unit time, usually expressed in "times / year" or "times / hour". Components with high failure rates may cause more frequent power outages, thereby affecting the reliability of the system. Mean Time To Repair (MTTR) refers to the average time required for a component to recover from a failure to a normal operating state, usually in hours. This parameter reflects the response speed and maintenance efficiency after a failure, and affects the length of the power outage. Unit load shedding cost (CCL) refers to the unit cost paid by the power system to cut off part of the load in a fault or emergency in order to ensure the stable operation of the power grid, and the unit is usually "yuan / kilowatt-hour" (￥ / kWh). When the power system encounters a fault or insufficient power generation capacity, in order to protect the key parts and important users of the power grid, load shedding measures may be taken, that is, temporarily disconnecting the power supply of non-critical loads. CCL reflects the losses caused by load shedding to power companies and users, including power sales losses, reduced user satisfaction, and possible compensation costs. In distribution network planning and operation, CCL is used to evaluate the economic and non-economic impacts of different load shedding strategies and help decision makers develop optimal fault management and load dispatch strategies.

[0041] Step S102: Analyze network topology parameters and power parameters based on a pre-established distribution network flexible transformation model to obtain a transformation strategy for the distribution network.

[0042] In the technical solution provided in the above step S102 of the present invention, the distribution network flexible transformation model takes the power supply reliability of the distribution network and minimization of the annual comprehensive cost as the transformation goals.

[0043] In this embodiment, a distribution network flexible transformation model considering reliability and economy is pre-established, wherein the distribution network flexible transformation model can also be called a high load density distribution network flexible transformation planning model considering reliability. The distribution network flexible transformation model generally includes the following components: an objective function with the goal of minimizing the comprehensive cost of the distribution network, constraints corresponding to the power grid flow model, constraints corresponding to the key equipment model, and constraints corresponding to the reliability assessment model.

[0044] Optionally, the objective function is usually aimed at minimizing the annual comprehensive cost of the system, including equipment investment cost, maintenance cost, power purchase cost and load shedding cost.

[0045] Optionally, the constraints corresponding to the power grid flow model include at least power balance constraints, node voltage constraints and line capacity constraints.

[0046] Optionally, the constraints corresponding to the key power resource model include at least photovoltaic power supply constraints, converter constraints, DC line constraints and energy storage device constraints.

[0047] Optionally, the acquired network topology parameters and power parameters are input into the distribution network flexible transformation model for solution to obtain the transformation strategy of the distribution network, wherein the distribution network flexible transformation model can generate the transformation strategy of the distribution network under the guidance of the objective function, the constraints corresponding to the power grid flow model, the constraints corresponding to the key equipment model and the constraints corresponding to the reliability assessment model.

[0048] Optionally, transformation strategies may include: adding or transforming AC and DC lines to increase line capacity and transmission efficiency of the grid; introducing or optimizing converter configuration to achieve flexible conversion of AC and DC power; deploying or adjusting energy storage equipment to balance load fluctuations and improve power supply reliability; considering the optimal configuration of distributed power sources, especially in areas with high load density, to increase local power supply capacity.

[0049] Step S103, based on the transformation strategy, transform the distribution network to obtain a transformed distribution network.

[0050] In the technical solution provided in the above step S103 of the present invention, after obtaining the transformation strategy for transforming the distribution network through the above step S102, the distribution network can be transformed according to the transformation strategy to obtain the transformed distribution network.

[0051] Optionally, the distribution network is transformed according to the transformation strategy, which may involve physical transformation, such as installing new equipment, upgrading lines, or building a new DC distribution network. System software upgrades may also be required to support new operating modes and control strategies.

[0052] Optionally, the transformed distribution network has higher power supply capacity and reliability. The application of DC distribution technology and the reasonable configuration of energy storage equipment can effectively improve the stability and adaptability of the system, especially in high load density areas. The transformed distribution network can better meet power demand, reduce line congestion, network loss and voltage over-limit problems, and improve the access and management capabilities of renewable energy.

[0053] Optionally, after the transformation of the distribution network is completed, the performance of the distribution network can be further optimized and verified. Through simulation tests and field tests, the effect of the transformation plan in actual operation is evaluated to ensure that the transformed distribution network can achieve the expected performance indicators, including but not limited to power supply capacity, power supply quality and economy.

[0054] In the above steps S101 to S103, based on the topological structure and power parameters of the distribution network, a transformation strategy for the distribution network is obtained through the distribution network flexible transformation model. Since the distribution network flexible transformation model takes the power supply reliability of the distribution network as the core consideration factor and minimizes the annual comprehensive cost as the transformation goal, therefore, the distribution network is transformed by the transformation strategy determined by the distribution network flexible transformation model, so that the transformed distribution network can balance the economy and system reliability, realize the efficient, stable and flexible operation of the distribution network, and thus solve the technical problem of not being able to effectively balance the power supply reliability and investment cost of the distribution network when transforming the distribution network.

[0055] The above method of this embodiment is further introduced below.

[0056] As an optional implementation method, step S102 analyzes the network topology parameters and power parameters based on a pre-established distribution network flexible transformation model to obtain a transformation strategy for the distribution network, including: calculating the equipment investment cost, equipment maintenance cost, electricity purchase cost and load shedding cost in the distribution network based on the objective function; calculating the minimized annual comprehensive cost of the distribution network based on the equipment investment cost, equipment maintenance cost, electricity purchase cost and load shedding cost; and guiding the generation of the distribution network transformation strategy based on the annual comprehensive cost.

[0057] In this embodiment, the objective function is the quantity that needs to be minimized or maximized in the planning problem, is a function of the decision variables, and reflects the degree of achievement of the planning goal. The objective function can be expressed by the following formula.

[0058] minC I +C M +C P +C S (1)

[0059] Among them, C I , CM , C P , C S They are equipment investment cost, equipment maintenance cost, power purchase cost and load shedding cost. The objective function aims to minimize the annual comprehensive cost of the distribution system.

[0060] Optionally, the equipment investment cost mainly includes the primary investment cost and construction cost of the equipment. The primary investment cost includes the cost of investing in energy storage, DC lines, and converters at both ends of the DC lines. The construction cost is generally selected as a percentage of the primary investment cost of the project α (5% ˉ 10%), so the equivalent annual investment cost is:

[0061]

[0062] In the above formula, C IESS and C IDC are the annual investment costs of energy storage equipment and DC distribution system respectively; They are the investment cost per unit energy capacity of energy storage, the investment cost per unit power capacity of energy storage, the investment cost per unit length of DC line, and the investment cost per unit capacity of converter; l ij , are the rated energy capacity of energy storage, the rated power of energy storage, the length of DC line ij and the rated capacity of converter at node i; S B is the system power reference value; Indicates whether the DC line is built to the predetermined location. Its value is 1, indicating that the DC line ij is built to the predetermined location. Otherwise, its value is 0, indicating that it is not built. E is the set of nodes where the energy storage device is located. S is the set of DC distribution lines. RR ESS , RR l , RR T are the annual cost conversion factors of energy storage, DC lines and converters, expressed in RR ESS For example:

[0063]

[0064] In the above formula, r is the discount rate; yESS It is the service life of the energy storage equipment.

[0065] Optionally, the equipment maintenance cost includes the material cost and labor cost in equipment operation and maintenance. Based on actual engineering operation experience, the maintenance cost can be simplified to a certain proportion of the system's one-time investment cost:

[0066]

[0067] In the above formula, β e is the proportion of energy storage maintenance cost to its primary investment cost; βl is the ratio of the maintenance cost of the DC line to its primary investment cost; The ratio of the inverter maintenance cost to its primary investment cost.

[0068] Optionally, taking one day as the minimum unit for superimposed calculation in a typical scenario, the cost of purchasing electricity from the public grid can be expressed by the following formula:

[0069]

[0070] In the above formula, is the electricity price at time t in a typical scenario; is the power injected into the substation at time t; Δt is the time step; N Sub is the substation node set; T is the planning time set.

[0071] Optionally, the load shedding cost is calculated based on the expected power shortage value, which is used to measure the load demand that the power system cannot meet when the power supply capacity is insufficient:

[0072]

[0073] In the above formula, is the power outage cost per unit load; EENS is the expected value of energy shortage.

[0074] Optionally, after determining the equipment investment cost, equipment maintenance cost, power purchase cost, and load shedding cost, these costs can be quantified through the objective function, and then the optimization algorithm, such as linear programming, second-order cone programming, or other mathematical optimization methods, can be used to solve the equipment configuration and operation strategy that minimizes the annual comprehensive cost of the distribution network. This process also needs to consider constraints such as the power grid flow model, key equipment model, and reliability assessment model.

[0075] Optionally, after solving the problem of minimizing the annual comprehensive cost, a specific transformation strategy can be generated. This includes determining which equipment needs to be upgraded or newly built (such as DC lines, converters, energy storage equipment), as well as the specific location, capacity and operation strategy of these equipment. The transformation strategy should also consider reliability improvement to ensure that the transformed distribution network is not only economical and efficient, but also can maintain stable operation in the event of a fault.

[0076] As an optional implementation method, the constraints corresponding to the power grid flow sub-model include at least: power balance constraints, node voltage constraints and line capacity constraints, wherein the power balance constraints are used to ensure that the active power and reactive power input and output of all nodes in the distribution network remain balanced, the node voltage constraints are used to ensure that the voltage level of each node in the distribution network remains within a threshold range within a specified time range, and the line capacity constraints are used to ensure that the current of each transmission line in the distribution network does not exceed the rated current. Step S102, based on a pre-established distribution network flexible transformation model, the network topology parameters and power parameters are analyzed to obtain a transformation strategy for the distribution network, and also includes: based on the power balance constraints, node voltage constraints, and line capacity constraints in the power grid flow sub-model, guiding the generation of the distribution network transformation strategy.

[0077] In this embodiment, the constraints of the power grid power flow model include power balance constraints, node voltage constraints and line capacity constraints.

[0078] Optionally, the power balance constraint ensures that the active power and reactive power input and output of all nodes in the distribution network are balanced. This means that at any time, the total power received by a node (from the power source or adjacent nodes) should be equal to the total power consumed by the node (load consumption and transmission loss) plus or minus the power stored (energy storage charging and discharging). This constraint is the basis of the physical operation of the distribution network, which ensures the stability of the power system and the efficient use of energy. In the distribution network flexible transformation model, the power balance constraint is expressed by the following formula (7) and formula (8) to ensure that the distribution network can meet the law of conservation of energy at any time and avoid local overload or power shortage.

[0079]

[0080] In the above formula, δ(j) and π(j) are the child nodes and parent nodes of node j respectively; are the active power and reactive power of branch ij at time t respectively; and are the active power and reactive power demands of the load at node j at time t respectively; and are respectively the active power and reactive power of energy storage discharge at node j at time t; and are the active power and reactive power of energy storage charging at node j at time t respectively; and are the active power and reactive power injected by the power supply at node j at time t respectively; and are the active power and reactive power injected into the converter station at node j at time t respectively; is the square of the current amplitude on the AC line ij at time t; R ij and X ij is the resistance and reactance of the AC line ij; N is the set of distribution network nodes.

[0081] Optionally, the node voltage constraint ensures that the voltage level of each node in the distribution network remains within a threshold range within a specified time range, that is, not lower than the voltage lower limit and not higher than the voltage upper limit. The voltage level is crucial to the safe operation of the power system. Too low a voltage may cause the equipment to malfunction, and too high a voltage may cause equipment damage. In the flexible transformation model of the distribution network, the node voltage constraint is embodied in the form of the following formulas (9) and (10), which are used to limit the range of node voltage changes, ensure the power quality of the power system, and avoid voltage fluctuations from causing adverse effects on users and equipment.

[0082]

[0083] In the above formula, U i,t is the square of the voltage amplitude at node i at time t; V AC_min and V AC_max are the lower and upper limits of the node voltage of the AC distribution network respectively; B is the collection of distribution network lines.

[0084] Optionally, the line capacity constraint ensures that the current carried by each transmission line in the distribution network does not exceed its rated current, avoiding failures and safety problems caused by line overload. The resistance and reactance of the line will produce a voltage drop according to the magnitude of the current flowing through it. When the line current approaches or exceeds its rated value, the voltage drop may become significant, affecting the power transmission efficiency and power quality. In addition, overload may also accelerate line aging and increase the risk of failure. In the flexible transformation model of the distribution network, the line capacity constraint can be expressed by the following formulas (11) and (12), which are used to limit the power and current transmitted by the line to ensure the safety and reliability of power transmission.

[0085]

[0086] In the above formula, is the capacity of the AC line ij.

[0087] Optionally, the above line capacity constraint is a nonlinear constraint, and a second-order cone relaxation method is used to convert the above formulas (11) and (12) into a standard second-order cone form as shown in the following formulas (13) and (14).

[0088]

[0089] Optionally, by analyzing the network topology parameters and power parameters based on a pre-established distribution network flexible transformation model, the above constraints can be comprehensively considered to guide the generation of distribution network transformation strategies.

[0090] Optionally, after the transformation strategy is generated, the transformation strategy can be evaluated to ensure that the transformed distribution network can not only meet the requirements of power balance, voltage quality and line capacity, but also achieve the optimal level in terms of economy, reliability and flexibility.

[0091] Optionally, through this step, the distribution network flexible transformation model can guide power companies or distribution network operators to develop transformation strategies that not only meet the physical characteristics of the power system constraints, but also maximize the reliability and economy of the system. This will not only help solve the problems of insufficient power supply capacity and voltage stability faced by high-load density distribution networks, but also promote the effective access and utilization of new energy and improve the overall operating efficiency and adaptability of the distribution network.

[0092] As an optional implementation, the constraints corresponding to the key equipment sub-model include at least photovoltaic power supply constraints, converter constraints, DC line constraints and energy storage equipment constraints, wherein the photovoltaic power supply constraints are used to characterize the power output characteristics of the photovoltaic system in the distribution network, the converter constraints are used to control the converter connecting the AC power grid and the DC power grid in the distribution network to provide sufficient power conversion capacity under various operating conditions, the DC line constraints are used to ensure that the current and voltage of each transmission line in the DC distribution system in the distribution network operate within a safe range, and the energy storage equipment constraints are used to ensure that the power and energy of the energy storage equipment in the distribution network during the charging and discharging process are within the operating boundary of the energy storage equipment. Step S102, based on the pre-established distribution network flexible transformation model, the network topology parameters and power parameters are analyzed to obtain the transformation strategy of the distribution network, and also includes: based on the photovoltaic power supply constraints, converter constraints, DC line constraints and energy storage equipment constraints in the key equipment sub-model, guiding the generation of the transformation strategy of the distribution network.

[0093] In this embodiment, the constraints corresponding to the key equipment sub-model include at least photovoltaic power supply constraints, converter constraints, DC line constraints and energy storage equipment constraints. In the planning process of flexible transformation of the distribution network, the constraints of the key equipment sub-model are an important basis for ensuring that the distribution network can operate stably and efficiently after the transformation. These constraints are respectively for photovoltaic power supply, converter, DC line and energy storage equipment.

[0094] Optionally, photovoltaic power constraints are considered. As a type of distributed energy, the output power of photovoltaic power is affected by light intensity and weather conditions. Therefore, the power output characteristics of photovoltaic power, such as power factor, maximum output power limit and predicted power output curve, need to be considered in the model. This helps to evaluate and predict the impact of photovoltaic power on the distribution network, ensuring that photovoltaic power can provide stable power output in high load density areas while avoiding grid power imbalance caused by excessive output. The photovoltaic power constraint can be expressed as the following formula (15) and formula (16).

[0095]

[0096] In the above formula, and is the predicted active and reactive power output of the photovoltaic power source at node i at time t; pf gpv is the power factor of the photovoltaic power source; NPV is the set of nodes where the photovoltaic power source is located.

[0097] Optionally, for the constraints of the converter. The converter is a key device connecting the AC distribution network and the DC distribution network, and is responsible for the bidirectional conversion of power. The constraints of the converter include its maximum power conversion capability, conversion efficiency, and the control range of voltage and current. In the flexible transformation of the distribution network, the configuration of the converter is crucial. It is necessary to ensure that sufficient power conversion capacity can be provided under various operating conditions to achieve flexible conversion between AC and DC, meet the dynamic needs of the distribution network, and maintain the stability of the grid. Among them, the constraints of the converter can be expressed by the following formulas (17) to (23).

[0098]

[0099] In the above formula, and They represent the active and reactive power flowing from AC node i to the converter at time t respectively; represents the square of the current amplitude flowing from AC node i to the converter at time t; and represent the equivalent resistance and reactance of the converter at node i respectively; and They represent the active and reactive power flowing from the AC side into the node i for processing at time t respectively; is the capacity of the ideal converter; It represents the square of the voltage amplitude at the AC side of the converter station processed by node i at time t; represents the power injected into the DC side by the converter station at node i at time t; D is the collection of DC lines.

[0100] Optionally, for DC line constraints. The introduction of DC lines can improve the efficiency and reliability of power transmission, but its operation is also limited by current and voltage. DC line constraints include the safe operating range of current and voltage, as well as the limitation of line capacity. Through these constraints, it can be ensured that the DC line can operate safely and stably in the transformed distribution network, avoid exceeding its capacity limit, and ensure the continuity and reliability of power transmission. Among them, the DC line constraints can be expressed by the following formulas (24) to (28).

[0101]

[0102] In the above formula, is the square of the current amplitude on the DC line ij at time t; is the resistance of the DC line ij; V is the square of the voltage amplitude at the DC side of the converter station at node i at time t; DC_min and V DC_max are the lower and upper limits of the DC voltage respectively.

[0103] Optionally, constraints on energy storage devices. Reasonable configuration of energy storage devices plays an important role in solving power fluctuations in the distribution network, improving power supply reliability and peak shaving. Energy storage device constraints mainly include energy balance constraints, reserve range constraints, charge and discharge power range constraints, charge and discharge state constraints, etc. These constraints ensure that the power and energy of the energy storage device during the charging and discharging process are within a safe range, avoiding damage to the equipment due to overcharging or over-discharging, while ensuring that the energy storage device can effectively respond to the dynamic needs of the power grid and improve the flexibility and reliability of the entire distribution network. Among them, the energy storage device constraints can be expressed by the following formulas (29) to (35).

[0104]

[0105] In the above formula, is the discharge state indicator of the energy storage e at time t, and its value of 1 indicates that the energy storage e is in the discharge state at time t, otherwise, its value of 0 indicates that it is not in the discharge state; is the charging state indicator of the energy storage e at time t, a value of 1 indicates that the energy storage e is in a charging state at time t, and a value of 0 indicates that it is not in a charging state; Indicates whether the energy storage e has been built. Its value is 1, indicating that it has been built to the scheduled time, and its value is 0, indicating that it has not been built. are the charging and discharging active powers of energy storage e respectively; are the charging and discharging reactive powers of energy storage e respectively; is the power capacity of energy storage; M is a sufficiently large positive number; represents the stored energy of energy storage e at time t; is the energy capacity of the energy storage device; and They are the lower and upper limits of the charge level of the energy storage respectively; and are the energy storage charging and discharging efficiencies respectively; E is the set of nodes where the energy storage device is located.

[0106] In this step, the distribution network is comprehensively optimized mainly by considering the constraints of the above-mentioned key equipment sub-models. This includes determining the optimal installation location and capacity of photovoltaic power sources, rationally configuring converters to improve power conversion efficiency and reliability, optimizing the path and capacity of DC lines, and determining the layout and capacity of energy storage devices to ensure that the distribution network can operate stably and efficiently under various operating conditions while meeting the requirements of economy and reliability. By solving the model, the optimal transformation strategy can be obtained, including which equipment needs to be built or upgraded, as well as its specific technical parameters and location, so as to guide the transformation and implementation of the distribution network and achieve flexible optimization and reliable operation of high-load density distribution networks.

[0107] As an optional implementation method, the constraints of the reliability assessment sub-model are used to evaluate the operating characteristics of the distribution network under different fault scenarios. Step S102 analyzes the network topology parameters and power parameters based on a pre-established distribution network flexible transformation model to obtain a transformation strategy for the distribution network. It also includes: based on the constraints of the reliability sub-model in the reliability assessment sub-model, guiding the generation of a transformation strategy for the distribution network.

[0108] In this embodiment, the constraints of the reliability assessment sub-model are key indicators used to quantify the system stability and power supply capacity of the distribution network under different fault scenarios. This process ensures that the transformed distribution network can not only meet the current load demand, but also withstand possible equipment failures or other uncertain events in the future, thereby maintaining the continuity and stability of power supply.

[0109] Optionally, the distribution network flexible transformation model and the reliability assessment sub-model are integrated. The distribution network flexible transformation model takes into account the economic and technical characteristics of power equipment, such as cost, efficiency, capacity limitation, etc. The reliability assessment sub-model focuses on the performance of the system under fault conditions, including reliability indicators such as failure rate, fault duration, and system load shedding cost.

[0110] Optionally, based on the N-1 principle, the operating state of the distribution network in the event of a single component failure is simulated. Each fault scenario takes into account the failure rate and fault duration of the faulty component, as well as the impact of the fault on the power supply capacity of the entire system. Among them, the N-1 principle is often used in the study of power supply capacity and reliability evaluation of distribution networks. The core idea is that the power system can maintain stable operation in the event of any single component failure. Based on the N-1 criterion, a linear explicit reliability constraint is proposed. These constraints may include: the continuity and stability of power supply in the event of a single component failure to ensure that critical loads are not affected; the system can be restored to normal operation within the duration of the fault to avoid long-term power supply interruptions; the maximum load shedding limit is used to minimize the impact of the fault on the system power supply capacity and user satisfaction. Among them, these constraints can be shown by the following formulas (36) to (39):

[0111]

[0112] Among them, σ i,k is the power-on status flag of node i under fault scenario k. Its value of 1 indicates that node i has a path to the substation node under scenario k; its value of 0 indicates that there is no path to the substation node; is the load shedding amount of the system at time t under scenario k; is the available capacity of the converter station at node i in scenario k; γ k is a binary auxiliary variable, ensuring λ k is the failure rate of component k; τ k is the average duration of fault scenario k; S is the set of single component failure scenarios of the system.

[0113] Optionally, these constraints will guide the generation of distribution network transformation strategies by solving the integrated model of the flexible transformation model and the reliability assessment sub-model. The transformation strategy should be able to minimize the grid investment and operating costs while ensuring system reliability. The strategy may include equipment upgrades, line expansion, deployment of energy storage equipment, and optimal configuration of distributed power sources to improve the power supply capacity and stability of the distribution network.

[0114] In the above steps, according to the aforementioned objective function, the constraints corresponding to the power flow sub-model, the constraints corresponding to the key equipment sub-model, and the constraints of the reliability assessment sub-model, the flexible transformation model of the distribution network will output a distribution network transformation strategy that meets all economic and reliability constraints. The transformation strategy lists in detail which equipment needs to be upgraded, which lines need to be expanded, the configuration location and capacity of energy storage and distributed power sources, etc., providing specific implementation guidelines for power companies or power grid operators to improve the power supply capacity in high-load density areas and the operating efficiency of the entire system.

[0115] The technical solution of the embodiment of the present invention is illustrated below in conjunction with preferred implementation modes.

[0116] In the related technologies, when implementing flexible transformation of distribution networks, most of them only focus on the planning scheme of a single type of equipment, but fail to fully consider the balance between system reliability and investment economy while improving power supply capacity. How to achieve the optimal planning of flexible transformation based on the existing AC distribution network while ensuring the reliability and economy of the system is a key issue that needs to be solved urgently.

[0117] However, the present invention proposes a method for transforming a distribution network, by obtaining the distribution network topology, AC and DC line parameters, converter parameters, distributed power supply parameters, load parameters, energy storage device parameters, and reliability-related parameters; then, the obtained parameters are input into a pre-established high-load density distribution network flexible transformation planning model that takes reliability into consideration to solve the optimal transformation plan; and the optimal flexible transformation planning result of the high-load density distribution network is output. The present invention can flexibly transform the existing AC distribution network while ensuring the optimal investment economy, improve the power supply capacity and reliability of the distribution network, and thus solve the technical problem that the power supply reliability and investment cost of the distribution network cannot be effectively balanced when transforming the distribution network.

[0118] Figure 2 is a schematic diagram of an equivalent circuit model of a two-terminal DC line implemented according to the present invention, such as Figure 2 As shown in the figure, a double-terminal DC line is usually used to connect two nodes in a distribution network. It can be a connection between DC distribution networks or an interface between an AC distribution network and a DC distribution network. In the flexible transformation planning of the distribution network, the equivalent circuit model of the double-terminal DC line is used to evaluate the impact of the DC line on the overall cost, efficiency and reliability of the system. Through the model, the power transmission capacity, line loss and control strategy of the DC line under different currents and voltages can be calculated.

[0119] Figure 3 is a schematic diagram of a power distribution system according to an embodiment of the present invention. Figure 3 As shown in the figure, the power distribution system consists of two independent distribution networks (distribution network 1 and distribution network 2), each of which includes 33 nodes (e.g., nodes 1-33 in distribution network 1 and nodes 34-66 in distribution network 2). These nodes represent various elements in the power system, such as power sources, loads, switches, and lines. The nodes are connected by lines to form a complex power network. Figure 3 As shown in the figure, high load density areas are marked, that is, the collection of nodes with high load demand. These areas are the key transformation targets and require more electricity to support high load demand. At the same time, they may also face problems such as voltage instability and insufficient power supply capacity.

[0120] Optionally, Figure 3 The load distribution of each node in the power distribution network is shown in Table 1, that is, Table 1 is a table of load distribution of each node in a power distribution system according to an embodiment of the present invention, wherein nodes 12-18 are high load density areas, and the total load peak is 1946kW, accounting for 27.4% of the entire system.

[0121] Table 1 Load distribution of each node in the power distribution system

[0122]

[0123]

[0124] Optionally, Table 2 is a cost parameter table solved by a flexible transformation model according to an embodiment of the present invention. As shown in Table 2, the unit cost of the converter and the unit cost of the DC line affect the selection and location optimization of the equipment in the transformation, while the unit energy capacity cost of the energy storage and the unit load shedding cost guide the configuration and optimization of the energy storage equipment.

[0125] Table 2 Cost related parameters

[0126]

[0127] Optionally, Figure 4 is a schematic diagram of a modified power distribution system according to an embodiment of the present invention. Figure 4 As shown, it shows the Figure 3 The results of the flexible transformation of the distribution network system in the example show the planned locations of key equipment (such as DC lines and energy storage equipment). Figure 4 As shown, the transformed distribution network system has two DC lines built between nodes 16-61 and 18-49; in addition, energy storage equipment is planned and built at nodes 12, 28, 45, and 62 to smooth out load and photovoltaic fluctuations.

[0128] Optionally, Figure 5 is a schematic diagram of a power supply situation in a high load density area according to an embodiment of the present invention, that is, Figure 5 The power supply situation in high load density areas under this planning scheme is shown.

[0129] Optionally, Figure 6It is a schematic diagram of the power supply situation of a distribution network 2 according to an embodiment of the present invention. The energy storage is charged during the low electricity consumption and photovoltaic overflow, and the electric energy is released during the peak electricity consumption, which helps to smooth the peak and fill the valley and reduce the power supply pressure of the system. At 11-15 o'clock on a typical day, the photovoltaic energy of the distribution network 2 overflows, and the electric energy is transferred from the distribution network 2 to the high load density area of ​​the distribution network 1 through the DC line, which effectively alleviates the power supply pressure in the high load density area; at other times, the electric energy is still mainly transmitted by AC lines. The application of DC lines and energy storage helps to alleviate the imbalance of the source and load of the distribution system in time and space, thereby improving its operating efficiency. Table 3 is a comparison table of operating costs before and after the flexible transformation of a distribution network according to an embodiment of the present invention, in which Scheme 1 is a scheme without transformation, and Scheme 2 is the transformation scheme proposed by the present invention.

[0130] Table 3 Comparison of operating costs before and after flexible transformation of distribution network

[0131]

[0132] Optionally, it can be seen from Table 3 that the cost of purchasing electricity accounts for the largest proportion of the total cost. By coordinating the planning of energy storage and DC lines, it is possible to achieve valley shaving and peak filling, and transfer local overflow photovoltaic energy through DC lines to supply power to high load density areas, thereby achieving economic optimization. The annual total cost of Scheme 2 is 15.6% lower than that of Scheme 1; the equivalent annual energy consumption (Equivalent Full Load Heating Hours, referred to as EENS) of Scheme 2 and Scheme 1 are 731.3kWh and 3485.4kWh respectively, a decrease of 79.1%. By comparing the operating costs of the distribution network before and after the transformation, it can be concluded that the operating cost of the distribution network after the transformation is significantly lower than the operating cost of the distribution network before the transformation, that is, the transformation method of the distribution network proposed by the present invention can improve the power supply capacity and reliability of the distribution system while ensuring the optimal investment economy.

[0133] According to an embodiment of the present invention, a device for transforming a distribution network is also provided. It should be noted that the device for transforming a distribution network can be used to execute the method for transforming a distribution network in the embodiment.

[0134] Figure 7 Schematic diagram of a power distribution network transformation device according to an embodiment of the present invention. Figure 7 As shown, the transformation device 700 of the distribution network may include: an acquisition unit 701 , an analysis unit 702 and a transformation unit 703 .

[0135] The acquisition unit 701 is used to acquire network topology parameters and power parameters of the distribution network, wherein the network topology parameters are used to characterize the connection relationship of devices in the distribution network, and the power parameters are used to characterize the power system characteristics and operating status of the distribution network.

[0136] The analysis unit 702 is used to analyze the network topology parameters and power parameters based on the pre-established distribution network flexible transformation model to obtain a transformation strategy for the distribution network, wherein the distribution network flexible transformation model takes the power supply reliability of the distribution network and the minimization of the annual comprehensive cost as the transformation goals.

[0137] The transformation unit 703 is used to transform the distribution network based on the transformation strategy to obtain a transformed distribution network.

[0138] Optionally, the analysis unit 702 is also used to: calculate the equipment investment cost, equipment maintenance cost, electricity purchase cost and load shedding cost in the distribution network based on the objective function; calculate the minimized annual comprehensive cost of the distribution network based on the equipment investment cost, equipment maintenance cost, electricity purchase cost and load shedding cost; and guide the generation of distribution network transformation strategies based on the annual comprehensive cost.

[0139] Optionally, the power grid flow sub-model includes at least: power balance constraints, node voltage constraints and line capacity constraints, wherein the power balance constraints are used to ensure that the active power and reactive power input and output of all nodes in the distribution network remain balanced, the node voltage constraints are used to ensure that the voltage level of each node in the distribution network remains within a threshold range within a specified time range, and the line capacity constraints are used to ensure that the current of each transmission line in the distribution network does not exceed the rated current. The molecular unit 701 is also used to: guide the generation of distribution network transformation strategies based on the power balance constraints, node voltage constraints and line capacity constraints in the power grid flow sub-model.

[0140] Optionally, the key equipment sub-model includes at least photovoltaic power supply constraints, converter constraints, DC line constraints and energy storage equipment constraints, wherein the photovoltaic power supply constraints are used to characterize the power output characteristics of the photovoltaic system in the distribution network, the converter constraints are used to control the converter connecting the AC power grid and the DC power grid in the distribution network to provide sufficient power conversion capability under various operating conditions, the DC line constraints are used to ensure that the current and voltage of each transmission line in the DC distribution system in the distribution network operate within a safe range, and the energy storage equipment constraints are used to ensure that the power and energy of the energy storage equipment in the distribution network during the charging and discharging process are within the operating boundary of the energy storage equipment. The analysis unit 702 is also used to: based on the photovoltaic power supply constraints, converter constraints, DC line constraints and energy storage equipment constraints in the key equipment sub-model, guide the generation of a transformation strategy for the distribution network.

[0141] Optionally, the constraints of the reliability assessment submodel are used to evaluate the operating characteristics of the distribution network under different fault scenarios, and the analysis unit 702 is also used to guide the generation of a transformation strategy for the distribution network based on the constraints of the reliability submodel in the reliability assessment submodel.

[0142] In this embodiment, based on the topological structure and power parameters of the distribution network, a transformation strategy for the distribution network is obtained through a distribution network flexible transformation model. Since the distribution network flexible transformation model takes the power supply reliability of the distribution network as the core consideration factor and minimizes the annual comprehensive cost as the transformation goal, the distribution network is transformed by the transformation strategy determined by the distribution network flexible transformation model. This can enable the transformed distribution network to balance the economy and system reliability, achieve efficient, stable and flexible operation of the distribution network, and thus solve the technical problem of being unable to effectively balance the power supply reliability and investment cost of the distribution network when transforming the distribution network.

[0143] According to an embodiment of the present invention, a computer-readable storage medium is further provided, the storage medium including a stored program, wherein the program executes the method for transforming a distribution network in the embodiment.

[0144] According to an embodiment of the present invention, a processor is further provided, and the processor is used to run a program, wherein the method for transforming the distribution network in the embodiment is executed when the program is run.

[0145] According to another aspect of the embodiments of the present invention, a computer program product is provided, which includes computer instructions, and when the computer instructions are executed by a processor, the method for transforming a power distribution network in the embodiments is implemented.

[0146] 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.

[0147] 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.

[0148] In the several embodiments provided in this application, 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. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that 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.

[0149] 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.

[0150] 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.

[0151] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent functional component, 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 functional component, which is stored in a storage medium and includes several 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), Random Access Memory (RAM), mobile hard disk, magnetic disk or optical disk, etc., various media that can store program codes.

[0152] 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 transforming a distribution network, characterized in that: include: Acquire network topology parameters of a distribution network and power parameters of the distribution network, wherein the network topology parameters are used to characterize the connection relationship of devices in the distribution network, and the power parameters are used to characterize the power system characteristics and operating status of the distribution network; The network topology parameters and the power parameters are analyzed based on a pre-established distribution network flexible transformation model to obtain a transformation strategy for the distribution network, wherein the distribution network flexible transformation model takes the power supply reliability of the distribution network and minimization of the annual comprehensive cost as the transformation goals; Based on the transformation strategy, the distribution network is transformed to obtain the transformed distribution network.

2. The method according to claim 1, characterized in that: The power parameters of the distribution network include at least: AC and DC line parameters of the distribution network, converter parameters of the distribution network, distributed power supply parameters of the distribution network, load parameters of the distribution network, energy storage device parameters of the distribution network, and reliability-related parameters of the distribution network.

3. The method according to claim 1, characterized in that The distribution network flexible transformation model at least includes an objective function with the goal of minimizing the annual comprehensive cost of the distribution network, and constraint conditions corresponding to the power grid flow sub-model, the key equipment sub-model and the reliability assessment sub-model respectively.

4. The method according to claim 3, characterized in that The network topology parameters and the power parameters are analyzed based on a pre-established distribution network flexible transformation model to obtain a transformation strategy for the distribution network, including: Calculate the equipment investment cost, equipment maintenance cost, electricity purchase cost and load shedding cost in the distribution network based on the objective function; Calculating the minimized annual comprehensive cost of the distribution network based on the equipment investment cost, the equipment maintenance cost, the electricity purchase cost and the load shedding cost; Based on the annual comprehensive cost, the generation of the distribution network transformation strategy is guided.

5. The method according to claim 3, characterized in that: The constraints corresponding to the power grid flow sub-model at least include: power balance constraints, node voltage constraints and line capacity constraints, wherein the power balance constraints are used to ensure that the active power and reactive power input and output of all nodes in the distribution network are balanced, the node voltage constraints are used to ensure that the voltage level of each node in the distribution network is maintained within a threshold range within a specified time range, and the line capacity constraints are used to ensure that the current of each transmission line in the distribution network does not exceed the rated current. The network topology parameters and the power parameters are analyzed based on the pre-established distribution network flexible transformation model to obtain the transformation strategy of the distribution network, and further include: Based on the power balance constraint condition, node voltage constraint condition and line capacity constraint condition in the power grid power flow sub-model, the generation of the distribution network transformation strategy is guided.

6. The method according to claim 3, characterized in that The constraints corresponding to the key equipment sub-model at least include photovoltaic power supply constraints, converter constraints, DC line constraints and energy storage equipment constraints, wherein the photovoltaic power supply constraints are used to characterize the power output characteristics of the photovoltaic system in the distribution network, the converter constraints are used to control the converter connecting the AC power grid and the DC power grid in the distribution network to provide sufficient power conversion capacity under various operating conditions, the DC line constraints are used to ensure that the current and voltage of each transmission line in the DC distribution system in the distribution network operate within a safe range, and the energy storage equipment constraints are used to ensure that the power and energy of the energy storage equipment in the distribution network during the charging and discharging process are within the operating boundary of the energy storage equipment. The network topology parameters and the power parameters are analyzed based on the pre-established distribution network flexible transformation model to obtain the transformation strategy of the distribution network, and further include: Based on the photovoltaic power source constraints, converter constraints, DC line constraints and energy storage device constraints in the key equipment sub-model, the generation of the transformation strategy of the distribution network is guided.

7. The method according to claim 3, characterized in that The constraint conditions of the reliability assessment sub-model are used to evaluate the operating characteristics of the distribution network under different fault scenarios, and the network topology parameters and the power parameters are analyzed based on a pre-established distribution network flexible transformation model to obtain a transformation strategy for the distribution network, and further include: Based on the constraint conditions of the reliability sub-model in the reliability assessment sub-model, the generation of the transformation strategy of the distribution network is guided.

8. A method for generating a transformation model of a distribution network, characterized in that: include: An acquisition unit, used to acquire network topology parameters of a distribution network and power parameters of the distribution network, wherein the network topology parameters are used to characterize the connection relationship of devices in the distribution network, and the power parameters are used to characterize the power system characteristics and operating status of the distribution network; An analysis unit, configured to analyze the network topology parameters and the power parameters based on a pre-established distribution network flexible transformation model to obtain a transformation strategy for the distribution network, wherein the distribution network flexible transformation model takes the power supply reliability of the distribution network and minimization of the annual comprehensive cost as transformation goals; A transformation unit is used to transform the distribution network based on the transformation strategy to obtain the transformed distribution network.

9. 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.

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

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