Power electronic transformer virtual power plant source load cooperative control method and system

Abstract

The invention discloses a power electronic transformer virtual power plant source load cooperative control method and system, and the method comprises the steps: building a load compensation cost model, and building an economic dispatching model with the maximization of the total income of a virtual power plant as a target; iteratively solving a local sub-problem and a global coordination problem based on an economic dispatching model to obtain optimized PET port interactive active power and photovoltaic output power, and updating the state of charge of the energy storage battery to enable the state of charge of the energy storage battery to meet a limited range; according to the method, photovoltaic, energy storage and PET loads are aggregated into a virtual unit capable of being dispatched in a unified mode, the state of charge of the virtual unit is obtained, and dynamic cooperative control over energy storage, photovoltaic and loads is carried out, so that system power balance is achieved. According to the invention, cooperative control and quick response of source-load resources can be realized, and the stability, safety and economical efficiency of a power grid in a high-permeability renewable energy source scene are improved.

Description

Technical Field

[0001] The present invention belongs to the field of coordinated control of power sources and loads in distribution networks, and relates to a method and system for coordinated control of power source and load virtual power plants of a Power Electronic Transformer (PET). Background Art

[0002] With the transformation of the energy structure towards a high proportion of renewable energy, the large-scale access of distributed energy, energy storage systems, and flexible loads has put forward higher requirements for the flexibility and stability of the power grid. However, the characteristics of small capacity, large scale, and diverse types of distributed energy itself make it necessary for flexible resources to match the random fluctuations of power sources and loads through a demand response mechanism. Therefore, the concept of a virtual power plant is proposed: aggregating various distributed resources in the power grid into a whole and uniformly controlling and managing them by the virtual power plant. As a new type of resource aggregation technology, by coordinating dispersed power source, load, and storage resources to participate in the power market and power grid regulation, the virtual power plant has gradually become an important means to improve the system regulation ability, but the existing virtual power plant technology still has limitations.

[0003] Traditional virtual power plants focus on the simple aggregation and scheduling of resources, but insufficiently explore the dynamic control potential of key power electronic devices (such as PETs), and fail to deeply integrate the coordinated optimization of virtual power plants with the flexible power regulation ability of PETs. In addition, the increasing proportion of intermittent power sources has exacerbated the volatility and uncertainty of the power grid, posing higher requirements for the coordination ability of virtual power plants. Summary of the Invention

[0004] To solve the deficiencies in the existing technology, the present invention provides a method for coordinated control of power source and load virtual power plants of a power electronic transformer. Through the deep integration of the multi-port control characteristics of PETs and the coordinated optimization technology of virtual power plants, the coordinated control and rapid response of power source and load resources of PET virtual power plants are realized, thereby improving the stability, reliability, and economy of the power grid system under high-penetration renewable energy scenarios.

[0005] The present invention adopts the following technical solutions.

[0006] In the first aspect of the present invention, a method for coordinated control of power source and load virtual power plants of a power electronic transformer is proposed. The method includes: Step 1: Construct a load compensation cost model based on PET operation parameters, and establish an economic dispatch model with the maximization of the total revenue of the virtual power plant as the goal on the basis of the load compensation cost model; Step 2: Iteratively solve the local sub-problem and the global coordination problem based on the economic dispatch model to obtain the optimized active power of PET port interaction and the photovoltaic output power, and update the state of charge of the energy storage battery in combination with the characteristic parameters of the distributed power source to make the state of charge of the energy storage battery meet the specified range; Step 3: Aggregate the photovoltaic, energy storage, and PET loads into a virtual unit that can be uniformly dispatched. Obtain the state of charge of the virtual unit based on the optimized active power of the PET port interaction, the photovoltaic output power, and the updated state of charge of the energy storage battery. Coordinate the control of the photovoltaic, energy storage, and PET loads according to the state of charge of the virtual unit to achieve system power balance.

[0007] Preferably, in Step 1, according to the PET operation parameters Construct the following load compensation cost model:

[0008] The constraint conditions are:

[0009]

[0010] In the formula, is the load compensation cost, R L is the equivalent resistance of the line, is the reactive power provided by the PET reactive power compensation device, is the loss factor of the PET reactive power compensation device, is the active power of the PET port interaction, is the reactive power of the PET port interaction, is the active power of the interaction between the i th port of the PET and the bus, is the i th port of the PET, V i is the i th port voltage effective value of the PET.

[0011] Preferably, in Step 1, based on the load compensation cost model, establish the following economic dispatch model with the maximization of the total revenue of the virtual power plant as the goal:

[0012]

[0013] In the formula, is the objective function, B is the total revenue of the virtual power plant, is the electricity selling price, z is the global power planned value, C is the marginal cost of power generation, is the charge and discharge power of the energy storage; is the photovoltaic output power; is the load compensation cost.

[0014] Preferably, in step 2, based on the economic dispatch model, the local sub-problem and the global coordination problem are iteratively solved to obtain the optimized active power of the PET port interaction and the photovoltaic output power, including: (1) The objective function expression of the local sub-problem is as follows: , which is used to obtain the k -th optimized photovoltaic output power k and the charge and discharge power of the energy storage during the -th iteration process, and then calculate the ideal active power of the PET port interaction and the coupling variable of the PET AC port:

[0015]

[0016] In the formula, is the penalty coefficient, is the global power plan value of the k -th iteration, is the objective function of the economic dispatch model; (2) The global coordination problem is used to iterate the global power plan value according to the ideal active power of the PET port interaction and the coupling variable of the PET AC port, and feed it back to the local sub-problem until , and output the current , , as the optimized active power of the PET port interaction and the photovoltaic output power ; among them, the formula for iterating the global power plan value is:

[0017] In the formula, is the global power plan value at the k + 1-th iteration, is the global power plan error threshold, is the penalty coefficient.

[0018] Preferably, in step 2, the optimized active power of the PET port interaction and the photovoltaic output power are combined with the characteristic parameters of the distributed power source to update the state of charge of the energy storage battery, so that the updated state of charge of the energy storage battery satisfies , to avoid overcharging or over-discharging, and the update formula is as follows:

[0019] Wherein, is the updated state of charge of the energy storage battery, is the time interval for each update; is the charge-discharge efficiency, is the capacity of the energy storage battery, is the charge-discharge power of the energy storage.

[0020] Preferably, the calculation formula of the charge-discharge power of the energy storage is as follows:

[0021] Wherein, is the charge-discharge power of the energy storage battery when the state of charge of the energy storage battery is 20%, is the charge-discharge power of the energy storage battery when the state of charge of the energy storage battery is 80%.

[0022] Preferably, in step 3, the photovoltaic, energy storage and PET loads are aggregated into a virtual unit that can be uniformly dispatched, and according to the optimized active power exchanged at the PET port , the photovoltaic output power P PV and the updated state of charge of the energy storage battery the state of charge of the virtual unit is obtained as follows:

[0023] Wherein, is the state of charge of the virtual unit, is the updated state of charge of the energy storage battery, is the energy storage charging efficiency, is the photovoltaic efficiency coefficient, is the energy storage discharge efficiency, is the capacity of the energy storage battery.

[0024] Preferably, in step 3, according to the state of charge of the virtual unit, the actions taken by the energy storage, photovoltaic and load in the case of power deficit or power surplus are determined, including: (1) When the system power condition is , and the state of charge of the virtual unit is not close to the upper limit, control the energy storage to charge so that ; (2) When the system power condition is , and the state of charge of the virtual unit is close to the upper limit, if the PET is not operating at full load, increase the PET load, and if the PET is operating at full load, reduce the photovoltaic output so that ; (3) When the system power condition is , and the state of charge of the virtual unit When it is not approaching the lower limit, control the energy storage to discharge, so that ; (4) When the system power condition is , and the state of charge of the virtual unit is approaching the lower limit, if the PET is not in no-load operation, reduce the PET load, if the PET is in no-load operation, increase the photovoltaic output, so that ; Among them, when , it is considered that is approaching the upper limit, otherwise it is not approaching the upper limit; When , it is considered that is approaching the lower limit, otherwise it is not approaching the lower limit, is the judgment threshold.

[0025] The second aspect of the present invention proposes a power electronic transformer virtual power plant source-load collaborative control system, including: A model construction module for constructing a load compensation cost model according to the PET operation parameters, and establishing an economic dispatch model with the goal of maximizing the total revenue of the virtual power plant based on the load compensation cost model; An iterative optimization module for iteratively solving the local sub-problem and the global coordination problem based on the economic dispatch model, obtaining the optimized PET port interactive active power and photovoltaic output power, and updating the state of charge of the energy storage battery in combination with the characteristic parameters of the distributed power source, so that the state of charge of the energy storage battery meets the specified range; A collaborative control module for aggregating photovoltaic, energy storage and PET loads into a virtual unit that can be uniformly dispatched, obtaining the state of charge of the virtual unit based on the optimized PET port interactive active power, photovoltaic output power and the updated state of charge of the energy storage battery, and performing collaborative control on photovoltaic, energy storage and PET loads according to the state of charge of the virtual unit to achieve system power balance.

[0026] The third aspect of the present invention proposes a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method.

[0027] The fourth aspect of the present invention proposes a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the method are implemented.

[0028] The beneficial effects of the present invention are at least as follows compared with the prior art: The present invention constructs a load compensation cost model based on the operating parameters of the PET, and establishes an economic dispatch model with the goal of maximizing the total revenue of the virtual power plant on the basis of the load compensation cost model. It fully considers the port parameters and regulation capabilities of the PET, combines the characteristic parameters of distributed power sources and the regulation capabilities of photovoltaic and energy storage, realizes the optimization of the interactive active power at the PET port and the photovoltaic output power, and considers the SOC limit problem to update the state of charge of the energy storage battery, avoiding overcharging or over-discharging of the energy storage battery, and improving the practicability and safety.

[0029] The present invention decomposes the complex global optimization problem of maximizing the total revenue of the virtual power plant into local sub-problems and global coordination problems and performs iterative solutions, improving the optimization efficiency. By introducing coupling variables, the deviation between the local solution and the global objective is corrected, which can improve the solution accuracy and convergence.

[0030] The present invention aggregates photovoltaic, energy storage, and PET loads into a virtual unit that can be uniformly dispatched. Considering the optimized interactive active power at the PET port, the photovoltaic output power, and the updated state of charge of the energy storage battery, the state of charge of the virtual unit is obtained to determine the actions taken by the energy storage, photovoltaic, and load in the case of power deficit or power surplus, and the optimized coordinated control of the source-load of the PET virtual power plant can be realized. Description of the Drawings

[0031] Figure 1 It is a flow chart of a method for coordinated control of source-load of a virtual power plant of a power electronic transformer proposed by the present invention. Detailed Embodiments

[0032] 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 in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only a part of the embodiments of the present invention, not all of the embodiments. Based on the spirit of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the protection scope of the present invention.

[0033] Embodiment 1 of the present invention provides a method for coordinated control of source-load of a virtual power plant of a power electronic transformer, as Figure 1 shown, including: Step 1: Construct a load compensation cost model based on the operating parameters of the PET, and establish an economic dispatch model with the goal of maximizing the total revenue of the virtual power plant on the basis of the load compensation cost model; Step 101: Construct a load compensation cost model based on the operating parameters of the PET, specifically including: (1) The port parameters of the PET, including the interactive power between the AC / DC ports and the bus, are shown as follows.

[0034]

[0035] In the formula, is the collected PET port parameter, is the i th port of PET and the active power of the interaction with the bus. The positive direction is defined as flowing from the AC side to the DC side, is the i th port of PET and the reactive power of the interaction with the bus.

[0036] (2) Construction of the load compensation cost model:

[0037] The constraint condition is the bus power balance equation:

[0038]

[0039] In the formula, is the load compensation cost.

[0040] R L is the equivalent resistance of the line, is the reactive power provided by the PET reactive power compensation device, is the loss factor of the PET reactive power compensation device.

[0041] is the i th port of PET and the active power of the interaction with the bus. The positive direction is defined as flowing from the AC side to the DC side, is the i th port of PET and the reactive power of the interaction with the bus.

[0042] is the active power of the PET port interaction, is the reactive power of the PET port interaction.

[0043] V i is the effective value of the voltage of the i th port of PET.

[0044] Step 102: Based on the load compensation cost model, establish an economic dispatch model with the goal of maximizing the total revenue of the virtual power plant. Further preferably, establish an economic dispatch model based on the load compensation cost model. Set the objective function of the economic dispatch model to maximize the revenue of the virtual power plant, and calculate according to the following formula:

[0045]

[0046] In the formula, is the objective function, B is the total revenue of the virtual power plant, is the electricity selling price, z is the global objective variable, C is the marginal cost of power generation, is the charge and discharge power of the energy storage; is the output power of the photovoltaic; is the load compensation cost.

[0047] Step 2: Based on the economic dispatch model, perform iterative solutions for the local sub-problem and the global coordination problem to obtain the optimized active power of the PET port interaction and the output power of the photovoltaic. Update the state of charge of the energy storage battery in combination with the characteristic parameters of the distributed power source to make the state of charge of the energy storage battery meet the specified range, including: Step 201: Based on the economic dispatch model in Step 1, perform iterative solutions for the local sub-problem and the global coordination problem to obtain the optimized active power of the PET port interaction and the output power of the photovoltaic . Specifically, use the ADMM optimization algorithm to decompose the global problem into a local sub-problem and a global coordination problem, and solve them alternately to coordinate the local decisions of multiple PETs: (1) The optimization objective of the local sub-problem is the minimization of the negative revenue, and the expression of the objective function is as follows:

[0048] The physical meaning of solving the local sub-problem is to minimize its own cost while approaching the global objective variable under the satisfaction of local constraints, is defined as the global power plan value k at the th iteration. Before the iteration starts, z the initial value is given artificially.

[0049] After the k th iteration of the local sub-problem, the output power of the photovoltaic and the charge and discharge power of the energy storage are obtained, and then the active power of the PET port interaction and the coupling variable of the PET AC port are calculated under ideal conditions.

[0050]

[0051]

[0052] In the formula, is the penalty coefficient.

[0053] (2) The purpose of global coordination is to iterate the global target variables, and the iteration formula is as follows.

[0054]

[0055] In the formula, is the global power plan value at the k +1-th iteration.

[0056] The obtained by solving the global coordination problem is substituted into the solution of the local sub-problem, and and can be solved. Then, substitute them into the global coordination problem again. Stop when , and output the current , as the finally optimized active power of the PET port interaction , photovoltaic output power , where is the global power plan error threshold.

[0057] Step 202: Update the state of charge of the energy storage battery by combining the optimized active power of the PET port interaction and the photovoltaic output power with the characteristic parameters of the distributed power source, so that the state of charge of the energy storage battery meets the specified range; (1) Obtain the characteristic parameters of the distributed power source in the system, as shown in the following formula.

[0058]

[0059] In the formula, is the characteristic parameter of the distributed power source in the system obtained, is the charge and discharge efficiency, is the capacity of the energy storage battery.

[0060] (2) Dynamically update the SOC of the energy storage battery so that the SOC meets the constraint conditions (the battery SOC boundary ), to avoid overcharging or over-discharging of the battery. The SOC update formula is as follows:

[0061] In the formula, is the updated SOC of the energy storage battery within , is the interval time for each update, is the charge and discharge efficiency, is the capacity of the energy storage battery.

[0062] Since the flexible load regulation amount of the system changes, the total load L of the system also changes. Usually, the system reference load is set in advance to beL base , in the above formula The calculation formula is as follows.

[0063]

[0064] In the formula,[[]] is the charge and discharge power of the energy storage battery when the SOC is equal to 20%, is the charge and discharge power of the energy storage battery when the SOC is equal to 80%.

[0065] Step 3: Aggregate the PV, energy storage, and PET loads into a virtual unit that can be uniformly dispatched. Based on the interactive active power at the PET port, the PV output power, and the state of charge of the energy storage battery in Step 2, obtain the state of charge of the virtual unit, and perform coordinated control on the PV, energy storage, and PET loads according to the state of charge of the virtual unit to achieve system power balance, specifically including: Step 301: Aggregate the optimization results of Step 2, including P PV , and the SOC' of the equipped energy storage battery, and dynamically combine the three to form a "virtual unit" that can be uniformly dispatched. The state of charge of the virtual unit is shown in the following formula:

[0066] In the formula,[[]] is the state of charge of the virtual unit, is the energy storage charging efficiency (80% - 85%), is the PV efficiency coefficient (0 - 1), which is related to the real-time illumination and temperature, is the energy storage discharge efficiency (80% - 85%).

[0067] Step 302: According to the in Step 301, determine the actions taken by the energy storage, PV, and load in the case of power deficit or power surplus, and perform coordinated control of the source and load of the virtual power plant.

[0068] Further preferably, the virtual power plant needs to flexibly control the behaviors of each component in the system according to different scenarios, as shown in Table 1.

[0069] Table 1

[0070] Among them, when , it is considered that is close to the upper limit, otherwise it is not close to the upper limit; When , it is considered that is close to the lower limit, otherwise it is not close to the lower limit, is the judgment threshold.

[0071] Embodiment 2 of the present invention provides a virtual power plant source-load coordinated control system for a power electronic transformer, including: A model construction module, configured to construct a load compensation cost model according to the PET operation parameters, and establish an economic dispatch model with the maximization of the total revenue of the virtual power plant as the goal based on the load compensation cost model; An iterative optimization module, configured to iteratively solve the local sub-problem and the global coordination problem based on the economic dispatch model, obtain the optimized PET port interactive active power and photovoltaic output power, and update the state of charge of the energy storage battery in combination with the characteristic parameters of the distributed power source, so that the state of charge of the energy storage battery meets the specified range; A coordinated control module, configured to aggregate the photovoltaic, energy storage, and PET loads into a virtual unit that can be uniformly dispatched, obtain the state of charge of the virtual unit based on the optimized PET port interactive active power, photovoltaic output power, and the updated state of charge of the energy storage battery, and perform coordinated control on the photovoltaic, energy storage, and PET loads according to the state of charge of the virtual unit to achieve system power balance.

[0072] Embodiment 3 of the present invention provides a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method.

[0073] Embodiment 4 of the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the method are implemented.

[0074] The present invention constructs a load compensation cost model according to the PET operation parameters, and establishes an economic dispatch model with the maximization of the total revenue of the virtual power plant as the goal based on the load compensation cost model. It fully considers the port parameters and regulation capabilities of the PET, combines the characteristic parameters of the distributed power source and the regulation capabilities of the photovoltaic and energy storage, realizes the optimization of the PET port interactive active power and photovoltaic output power, and considers the SOC limit problem, updates the state of charge of the energy storage battery, avoids overcharging or over-discharging of the energy storage battery, and improves the practicability and safety.

[0075] The present invention decomposes the complex global optimization problem of maximizing the total revenue of the virtual power plant into local sub-problems and global coordination problems and performs iterative solution, improves the optimization efficiency, and corrects the deviation between the local solution and the global goal by introducing coupling variables, which can improve the solution accuracy and convergence.

[0076] The present invention aggregates photovoltaic, energy storage, and PET loads into a virtual unit that can be uniformly dispatched. By comprehensively considering the optimized interactive active power at the PET port, the photovoltaic output power, and the updated state of charge of the energy storage battery, the state of charge of the virtual unit is obtained to determine the actions taken by the energy storage, photovoltaic, and load in the case of power deficit or power surplus, enabling the optimized coordinated control of the source and load of the PET virtual power plant, and having scalability to support the distributed expansion of devices, which is more conducive to the active aggregation and coordinated control of the source and load.

[0077] The present disclosure can be a system, method, and / or computer program product. The computer program product can include a computer-readable storage medium having thereon computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0078] The computer-readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. The computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (non-exhaustive list) of the computer-readable storage medium include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disc (DVD), a memory stick, a floppy disk, a mechanically encoded device, such as a punched card or raised structures in grooves having instructions stored thereon, and any suitable combination of the foregoing. The computer-readable storage medium used herein is not construed as an instantaneous signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagated through a waveguide or other transmission medium (e.g., an optical pulse through an optical fiber cable), or an electrical signal transmitted through a wire.

[0079] The computer-readable program instructions described herein can be downloaded from the computer-readable storage medium to various computing / processing devices, or downloaded to an external computer or external storage device through a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include a copper transmission cable, an optical fiber transmission, a wireless transmission, a router, a firewall, a switch, a gateway computer, and / or an edge server. The network adapter or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0080] Computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state-setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk, C++, etc., and conventional procedural programming languages such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it may be connected to an external computer (e.g., through the Internet using an Internet service provider). In some embodiments, by using the state information of the computer-readable program instructions to customize an electronic circuit, such as a programmable logic circuit, a field-programmable gate array (FPGA), or a programmable logic array (PLA), the electronic circuit can execute the computer-readable program instructions to implement various aspects of the present disclosure.

[0081] 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 them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: it is still possible to modify the specific embodiments of the present invention or make equivalent replacements, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. A virtual power plant-based source-load collaborative control method for a power electronic transformer, characterized in that The method includes: Step 1: Construct a load compensation cost model based on the PET operation parameters, and establish an economic dispatch model with the goal of maximizing the total revenue of the virtual power plant on the basis of the load compensation cost model; Step 2: Iteratively solve the local sub-problem and the global coordination problem based on the economic dispatch model to obtain the optimized active power of the PET port interaction and the photovoltaic output power, and update the state of charge of the energy storage battery in combination with the characteristic parameters of the distributed power source to make the state of charge of the energy storage battery meet the specified range; Step 3: Aggregate the photovoltaic, energy storage, and PET loads into a virtual unit that can be uniformly dispatched, obtain the state of charge of the virtual unit based on the optimized active power of the PET port interaction, the photovoltaic output power, and the updated state of charge of the energy storage battery, and perform coordinated control on the photovoltaic, energy storage, and PET loads according to the state of charge of the virtual unit to achieve system power balance.

2. A method for coordinated control of source-load virtual power plant of a power electronic transformer according to claim 1, characterized in that: In Step 1, according to the PET operating parameters construct the following load compensation cost model: The constraint conditions are: Wherein, is the load compensation cost, R L is the line equivalent resistance, is the reactive power provided by the PET reactive power compensation device, is the loss factor of the PET reactive power compensation device, is the interactive active power at the PET port, is the interactive reactive power at the PET port, is the active power of the i th port of the PET interacting with the bus, is the active power of the i th port of the PET interacting with the bus, V i is the effective value of the voltage at the i th port of the PET.

3. A method for coordinated control of source-load virtual power plant of a power electronic transformer according to claim 1, characterized in that: In step 1, an economic dispatch model is established with the goal of maximizing the total revenue of the virtual power plant on the basis of the load compensation cost model as follows: In the formula, is the objective function, B is the total revenue of the virtual power plant, is the electricity selling price, z is the global power plan value, C is the marginal cost of power generation, is the charge and discharge power of the energy storage; is the photovoltaic output power; is the load compensation cost.

4. A method for coordinated control of source-load virtual power plant of a power electronic transformer according to claim 1, characterized in that: In step 2, iteratively solve the local sub-problem and the global coordination problem based on the economic dispatch model to obtain the optimized active power of the PET port interaction and the photovoltaic output power, including: (1) The objective function expression of the local sub-problem is as follows: , which is used to obtain the photovoltaic output power k at the k -th optimization during the -th iteration, and the charge and discharge power of the energy storage . Furthermore, the active power of the PET port interaction under ideal conditions and the coupling variable of the PET AC port are calculated: In the formula, is the penalty coefficient, is the global power plan value for the k -th iteration, is the objective function of the economic dispatch model; (2) The global coordination problem is used to iteratively calculate the global power plan value based on the active power of the PET port interaction under ideal conditions and the coupling variables of the PET AC port and feed it back to the local sub-problem until , and output the current 、 , which is used as the optimized active power of the PET port interaction and the PV output power ; among them, the formula for iteratively calculating the global power plan value is: In the formula, is the global power plan value at the k +(1)th iteration, is the global power plan error threshold, is the penalty coefficient.

5. A method for coordinated control of source-load virtual power plant of a power electronic transformer according to claim 1, characterized in that: In Step 2, the optimized active power of the PET port interaction and the photovoltaic output power Combine with the characteristic parameters of the distributed power source Update the state of charge of the energy storage battery so that the updated state of charge of the energy storage battery satisfies , to avoid overcharging or over-discharging of the battery. The update formula is as follows: Wherein, is the updated state of charge of the energy storage battery, is the interval time for each update; is the charge-discharge efficiency, is the capacity of the energy storage battery, is the charge-discharge power of the energy storage, is the state of charge of the energy storage battery.

6. A method for coordinated control of source-load virtual power plant of a power electronic transformer according to claim 5, characterized in that: The calculation formula for the charge and discharge power of the energy storage is as follows: Wherein, is the charge and discharge power of the energy storage battery when the state of charge of the energy storage battery is equal to 20%, is the charge and discharge power of the energy storage battery when the state of charge of the energy storage battery is equal to 80%, L is the total system load, L base is the preset system reference load.

7. A method for coordinated control of source-load virtual power plant of a power electronic transformer according to claim 1, characterized in that: In step 3, the photovoltaic, energy storage, and PET loads are aggregated into a virtual unit that can be uniformly dispatched. According to the optimized active power of the PET port interaction , the photovoltaic output power P PV and the updated state of charge of the energy storage battery , the state of charge of the virtual unit is obtained as follows: Wherein, is the state of charge of the virtual unit group, is the updated state of charge of the energy storage battery, is the energy storage charging efficiency, is the photovoltaic efficiency coefficient, is the energy storage discharging efficiency, is the energy storage battery capacity.

8. A method for coordinated control of source-load virtual power plant of a power electronic transformer according to claim 1, characterized in that: In step 3, perform coordinated control on the photovoltaic, energy storage, and PET loads according to the state of charge of the virtual unit to achieve system power balance, including: When the system power condition is , and the state of charge of the virtual unit is not close to the upper limit, control the energy storage charging to make , where is the photovoltaic efficiency coefficient, , P PV are the optimized active power of PET port interaction and the photovoltaic output power; (2)When the system power condition is , and the state of charge of the virtual unit is close to the upper limit, if the PET is not operating at full load, increase the PET load; if the PET is operating at full load, reduce the PV output to make ; (3) When the system power condition is , and the state of charge of the virtual unit is not approaching the lower limit, control the energy storage to discharge, so that ; (4)The system power condition is , and when the state of charge of the virtual unit is close to the lower limit, if the PET is not in no-load operation, reduce the PET load; if the PET is in no-load operation, increase the PV output to make ; Among them, when is the case, it is considered that is close to the upper limit; otherwise, it is not close to the upper limit. When it is considered that is close to the lower limit, otherwise it is not close to the lower limit, is the judgment threshold.

9. A virtual power plant-based source-load collaborative control system for a power electronic transformer, which operates the method according to any one of claims 1-8, characterized in that, The system includes: A model construction module for constructing a load compensation cost model based on the PET operation parameters and establishing an economic dispatch model with the goal of maximizing the total revenue of the virtual power plant on the basis of the load compensation cost model; An iterative optimization module for iteratively solving the local sub-problem and the global coordination problem based on the economic dispatch model to obtain the optimized active power of the PET port interaction and the photovoltaic output power, and updating the state of charge of the energy storage battery in combination with the characteristic parameters of the distributed power source to make the state of charge of the energy storage battery meet the specified range; A coordinated control module, which is used to aggregate photovoltaic, energy storage, and PET loads into a virtual unit that can be uniformly dispatched, obtain the state of charge of the virtual unit based on the optimized active power of the PET port interaction, the photovoltaic output power, and the updated state of charge of the energy storage battery, and perform coordinated control on the photovoltaic, energy storage, and PET loads according to the state of charge of the virtual unit to achieve system power balance.

10. A terminal, comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is used to operate according to the instructions to execute the steps of the method according to any one of claims 1-8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, the steps of the method according to any one of claims 1-8 are implemented.

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