Superconducting energy storage system applied to optical storage direct flexible system and capacity configuration method thereof

Abstract

The invention belongs to the technical field of micro-grids, and particularly discloses a superconducting energy storage system applied to an optical storage direct-flexible system and a capacity configuration method of the superconducting energy storage system. The system comprises a capacitor, a chopper circuit connected to two ends of the capacitor in parallel, and a first bidirectional DC converter and a second bidirectional DC converter which are respectively connected to two ends of the capacitor in parallel through output ends, the first bidirectional direct-current converter is connected with the high-voltage direct-current bus; the second bidirectional direct-current converter is connected with the low-voltage direct-current bus; the first bidirectional direct-current converter controls the charging and discharging states of the capacitor so as to compensate power fluctuation generated at the high-voltage direct-current bus side; the second bidirectional direct-current converter controls the charging and discharging states of the capacitor so as to compensate power fluctuation generated at the low-voltage direct-current bus side; the chopper circuit absorbs electric energy from the capacitor or releases the electric energy through the superconducting magnet so as to eliminate voltage fluctuation generated at the two ends of the capacitor. According to the invention, the response speed and transmission efficiency of the superconducting energy storage system in the multi-voltage-level optical storage direct-flexible system can be improved.

Description

Technical Field

[0001] The present application relates to the field of microgrid technology, and in particular to a superconducting energy storage system and a capacity configuration method thereof applied to a photovoltaic storage direct-flexible system. Background Art

[0002] As a form of DC microgrid, the PV-storage DC-flexible system can achieve flexible and efficient coordination between source, grid, load and energy storage, and improve the utilization rate of renewable energy. Therefore, the PV-storage DC-flexible system has been widely studied in the field of microgrid technology.

[0003] At present, regarding the hybrid energy storage technology used in DC microgrids, in the application research of superconducting energy storage systems in photovoltaic storage, direct current and flexible systems, superconducting energy storage coils are mostly directly connected to the high-voltage DC bus through a chopper. However, in a multi-voltage photovoltaic storage, direct current and flexible system, this structure will make the response speed and transmission efficiency of the superconducting energy storage system easily restricted by the multiple DC converters set between the buses of each level, making it difficult to give full play to its transient high-power compensation benefits for the photovoltaic storage, direct current and flexible system.

[0004] Therefore, how to better realize the application of superconducting energy storage systems in multi-voltage level photovoltaic direct-flexible systems has become a technical problem that needs to be urgently solved in the industry. Summary of the invention

[0005] Based on this, it is necessary to provide a superconducting energy storage system and its capacity configuration method for use in photovoltaic direct-flexible systems, which can better realize the application of superconducting energy storage systems in multi-voltage level photovoltaic direct-flexible systems, in response to the above-mentioned technical problems.

[0006] In a first aspect, the present application provides a superconducting energy storage system applied to a photovoltaic-storage-direct-flexible system, the photovoltaic-storage-direct-flexible system comprising a high-voltage DC bus and a low-voltage DC bus, including:

[0007] A capacitor, a chopper circuit connected in parallel at both ends of the capacitor, and a first bidirectional DC converter and a second bidirectional DC converter connected in parallel at both ends of the capacitor through output ends; the input end of the first bidirectional DC converter is connected to the high-voltage DC bus; the input end of the second bidirectional DC converter is connected to the low-voltage DC bus; the chopper circuit is built based on a superconducting magnet, a bipolar transistor and a diode;

[0008] The first bidirectional DC converter is used to control the charging and discharging state of the capacitor to compensate for the power fluctuation generated on the high-voltage DC bus side; the second bidirectional DC converter is used to control the charging and discharging state of the capacitor to compensate for the power fluctuation generated on the low-voltage DC bus side; the chopper circuit is used to utilize the superconducting magnet to absorb or release electrical energy to the capacitor to eliminate the voltage fluctuation generated at both ends of the capacitor.

[0009] Optionally, the first bidirectional DC converter includes a first bipolar transistor, a second bipolar transistor, a first inductor, a first diode connected in parallel between the emitter and the collector of the first bipolar transistor, and a second diode connected in parallel between the emitter and the collector of the second bipolar transistor;

[0010] One end of the first inductor is connected to the high-voltage DC bus, and the other end is connected to the emitter of the first bipolar transistor and the collector of the second bipolar transistor; the collector of the first bipolar transistor is connected to the positive electrode of the capacitor, and the emitter of the second bipolar transistor and the negative electrode of the capacitor are connected to the ground;

[0011] The second bidirectional DC converter includes a third bipolar transistor, a fourth bipolar transistor, a second inductor, a third diode connected in parallel between the emitter and the collector of the third bipolar transistor, and a fourth diode connected in parallel between the emitter and the collector of the fourth bipolar transistor;

[0012] One end of the second inductor is connected to the low voltage DC bus, and the other end is connected to the emitter of the third bipolar transistor and the collector of the fourth bipolar transistor; the collector of the third bipolar transistor is connected to the positive electrode of the capacitor, and the emitter of the fourth bipolar transistor is connected to the negative electrode of the capacitor.

[0013] Optionally, the chopper circuit includes a fifth bipolar transistor, a sixth bipolar transistor, a fifth diode, a sixth diode and a superconducting magnet;

[0014] One end of the superconducting magnet is connected to the collector of the fifth bipolar transistor and the anode of the fifth diode, the other end of the superconducting magnet is connected to the emitter of the sixth bipolar transistor and the cathode of the sixth diode, the anode of the sixth diode, the emitter of the fifth bipolar transistor and the cathode of the capacitor are connected, and the collector of the sixth bipolar transistor, the cathode of the fifth diode and the cathode of the capacitor are connected;

[0015] When the fifth bipolar transistor and the sixth bipolar transistor are turned on at the same time, the superconducting magnet absorbs electrical energy from the capacitor; when the fifth bipolar transistor and the sixth bipolar transistor are turned off at the same time, the superconducting magnet releases electrical energy to the capacitor.

[0016] In a second aspect, the present application provides a capacity configuration method applied to any of the above-mentioned superconducting energy storage systems, comprising:

[0017] Based on the inductance parameter information, rated current parameter information and electric energy parameter information of the superconducting magnet in the superconducting energy storage system, the capacity configuration model of the superconducting energy storage system is determined; the electric energy parameter information is determined based on the power fluctuation information of the photovoltaic storage direct and flexible system on the high and low voltage DC bus and the output power of the superconducting energy storage system;

[0018] Based on the objective function of the capacity configuration model, the objective fitness function is obtained; the objective function is constructed with the goal of minimizing the investment cost and operation cost of the superconducting energy storage system;

[0019] Taking minimizing the fitness value of the target fitness function as the optimization goal, the target fitness function is iteratively solved to determine the rated capacity of the superconducting magnet in the superconducting energy storage system.

[0020] Optionally, taking the fitness value of minimizing the target fitness function as the optimization target, iteratively solving the target fitness function to determine the rated capacity of the superconducting magnet in the superconducting energy storage system includes:

[0021] Step S101, initializing each particle of the particle swarm optimization algorithm, the local optimal position of each particle, and the current global optimal particle based on the preset value range of the inductance parameter and the rated current parameter of the superconducting magnet in the superconducting energy storage system;

[0022] Step S102, substituting the inductance parameter information and rated current parameter information corresponding to each particle, and the electric energy parameter information required to be purchased by the superconducting energy storage system into the target fitness function to determine the fitness value of each particle;

[0023] Step S103, with the goal of minimizing the fitness value, updating the local best position of each particle and the global best particle in the current iteration process;

[0024] Step S104, determine whether the current number of iterations reaches the maximum number of iterations or whether the fitness value of the current global optimal particle converges; if not, update the position and speed of each particle and jump to step S103; if yes, execute step S105;

[0025] Step S105, obtaining a global optimal particle of the particle swarm optimization algorithm, and determining the rated capacity of the superconducting magnet in the superconducting energy storage system based on the inductance parameter information and the rated current parameter information corresponding to the global optimal particle.

[0026] Optionally, before determining the capacity configuration model of the superconducting energy storage system based on the inductance parameter information, the rated current parameter information of the superconducting magnet in the superconducting energy storage system and the electric energy parameter information required to be purchased by the superconducting energy storage system, the method further includes:

[0027] Obtain the power fluctuation information of the high and low voltage DC bus of the PV-storage-direct-flexible system at each sampling time within the target period;

[0028] Based on the power fluctuation information at each sampling moment and the maximum output power of the superconducting energy storage system at each sampling moment, the electric energy parameter information required to be purchased by the superconducting energy storage system is determined.

[0029] Optionally, based on inductance parameter information, rated current parameter information of a superconducting magnet in the superconducting energy storage system, and electric energy parameter information required to be purchased by the superconducting energy storage system, a capacity configuration model of the superconducting energy storage system is determined, including:

[0030] Based on the inductance parameter information and the rated current parameter information of the superconducting energy storage system, the investment cost function of the superconducting energy storage system is determined, and based on the rated current parameter information of the superconducting energy storage system and the parameter information of the electric energy required to be purchased by the superconducting energy storage system, the operation cost function of the superconducting energy storage system is determined;

[0031] With the goal of minimizing the investment cost function and the operating cost function of the superconducting energy storage system, the objective function of the capacity configuration model is constructed, and the target constraint conditions are determined based on the value ranges corresponding to the inductance parameter information and the rated current parameter information of the superconducting energy storage system;

[0032] Based on the objective function and objective constraints, a capacity configuration model of the superconducting energy storage system is established.

[0033] In a third aspect, the present application provides a capacity configuration device for a superconducting energy storage system applied to any of the above-mentioned systems, comprising:

[0034] The first processing module is used to determine the capacity configuration model of the superconducting energy storage system based on the inductance parameter information, rated current parameter information and electric energy parameter information required to be purchased by the superconducting energy storage system of the superconducting magnet in the superconducting energy storage system; the electric energy parameter information is determined based on the power fluctuation information of the photovoltaic storage direct and flexible system on the high and low voltage DC bus and the output power of the superconducting energy storage system;

[0035] The second processing module is used to obtain a target fitness function based on the objective function of the capacity configuration model; the objective function is constructed with the goal of minimizing the investment cost and operation cost of the superconducting energy storage system;

[0036] The capacity configuration module is used to iteratively solve the target fitness function by minimizing the fitness value of the target fitness function as the optimization target, and determine the rated capacity of the superconducting magnet in the superconducting energy storage system.

[0037] In a fourth aspect, the present application provides an electronic device comprising: at least one memory for storing programs; and at least one processor for executing the programs stored in the memory. When the programs stored in the memory are executed, the processor is used to execute the method described in the first aspect or any possible implementation of the first aspect.

[0038] In a fifth aspect, the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method described in the first aspect or any possible implementation of the first aspect.

[0039] In a sixth aspect, the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the method described in the first aspect or any possible implementation of the first aspect.

[0040] The superconducting energy storage system and its capacity configuration method applied to the photovoltaic storage direct and flexible system are as follows: the superconducting energy storage system includes a capacitor and a chopper circuit respectively connected in parallel at both ends of the capacitor, a first bidirectional DC converter and a second bidirectional DC converter, wherein the input end of the first bidirectional DC converter is connected to the high-voltage DC bus, and the input end of the second bidirectional DC converter is connected to the low-voltage DC bus, so as to realize the connection of the superconducting energy storage system between the high-voltage DC bus and the low-voltage DC bus of the photovoltaic storage direct and flexible system. In this way, on the one hand, a single bidirectional DC converter can be used as a direct bridge for power compensation of buses of various levels, so that the superconducting energy storage system only needs to pass through one converter when performing power compensation for high and low voltage DC bus systems, and the power transmission efficiency is high; on the other hand, the voltage difference between the high and low voltage DC bus systems can be used to effectively improve the power response speed of the two bidirectional DC converters, reduce the Joule loss caused by the current, further improve the response speed and transmission efficiency of the superconducting energy storage system in the multi-voltage level photovoltaic storage direct and flexible system, and effectively improve the transient high-power compensation efficiency of the superconducting energy storage system for the photovoltaic storage direct and flexible system. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 It is one of the structural schematic diagrams of the superconducting energy storage system applied to the optical storage direct-flexible system provided in the embodiment of the present application;

[0043] Figure 2 This is the second structural schematic diagram of the superconducting energy storage system applied to the optical storage direct-flexible system provided in the embodiment of the present application;

[0044] Figure 3 It is a flow chart of a method for configuring the capacity of a superconducting energy storage system provided in an embodiment of the present application;

[0045] Figure 4 It is a flow chart of a method for purchasing electric energy required by the system in the capacity configuration method provided in an embodiment of the present application;

[0046] Figure 5It is a flow chart of a method for configuring the capacity of a superconducting energy storage system based on a PSO algorithm provided in an embodiment of the present application;

[0047] Figure 6 It is a structural schematic diagram of the superconducting energy storage system provided in the embodiment of the present application applied in a double-busbar structure optical storage direct-flexible system;

[0048] Figure 7 is a structural schematic diagram of a capacity configuration device for a superconducting energy storage system provided in an embodiment of the present application;

[0049] Figure 8 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0051] The terms "first" and "second" in the specification and claims herein are used to distinguish different objects rather than to describe a specific order of the objects. For example, a first bidirectional DC converter and a second bidirectional DC converter are used to distinguish different bidirectional DC converters rather than to describe a specific order of the bidirectional DC converters.

[0052] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0053] First, the technical terms involved in the embodiments of the present application are introduced.

[0054] (1) DC microgrid

[0055] DC microgrids are composed of direct current and are an important part of the future intelligent power distribution system. They are of great significance to promoting energy conservation and emission reduction and achieving sustainable energy development. Compared with AC microgrids, DC microgrids can more efficiently and reliably accommodate distributed renewable energy generation systems such as wind and light, energy storage units, electric vehicles and other DC power loads.

[0056] (2) PV-storage direct-flexible system

[0057] As a form of DC microgrid, the PEDF system is the abbreviation of the application of four technologies: solar photovoltaic (Photovoltaic), energy storage (Energy storage), direct current (Direct current) and flexible interaction (Flexibility) in the construction field. It is an important pillar for the development of zero-carbon energy and is conducive to the direct consumption of wind power and photovoltaic power.

[0058] Among them, "light" refers to solar photovoltaic technology. Solar photovoltaic power generation is one of the main renewable power sources in the future, and the huge exterior surface of buildings is a space resource for the development of distributed photovoltaics.

[0059] "Storage" refers to energy storage technology. In the future power system, energy storage is an indispensable component.

[0060] "Direct" refers to direct current technology. Compared with alternating current, direct current has the characteristics of simple form, easy control, and high transmission efficiency. DC power supply systems are widely used in special systems such as aviation, communications, and ships.

[0061] "Flexible" refers to flexible electricity technology. Flexibility refers to the ability to actively change the power a building draws from the municipal power grid.

[0062] (3) Superconducting energy storage system

[0063] Superconducting Magnetic Energy Storage (SMES) is a power system that uses superconducting coil magnets to directly store electromagnetic energy and return it to the power grid (including DC microgrid) or other loads when needed. It has the advantages of fast response speed and high conversion efficiency. It can not only be used to reduce or even eliminate low-frequency power oscillations in the power grid, but also regulate reactive power and active power, which plays a huge role in improving power supply quality and dynamic stability of the power grid.

[0064] It should be noted that, unlike AC power grids, there is no fluctuation in reactive power in DC microgrids, and the only indicator that determines its power quality is the DC bus voltage. Therefore, the key technology in the photovoltaic storage direct-flexible system is to maintain the stability of the DC bus voltage, that is, to maintain the dynamic balance between the power supply power and the load absorption power. However, the energy supply in the microgrid is random in time, and the energy storage system is often required to smooth the peak and fill the valley.

[0065] Battery energy storage has the advantages of high energy density, easy expansion and maintenance, and is one of the most widely used energy storage methods in microgrids. However, there are two main problems with using batteries in photovoltaic storage direct-flexible systems. The first is that its power response speed is difficult to meet the needs of rapid load changes in photovoltaic storage direct-flexible systems. If the power response speed is increased only by increasing the battery capacity, although the impact of the load on the bus voltage can be reduced, the increased capacity is idle for a long time, which seriously increases the construction cost of the system and causes a waste of resources. The second is that the power deficit of the photovoltaic storage direct-flexible system during operation repeatedly changes between positive and negative, resulting in a high number of battery charge and discharge times, which will greatly reduce its service life. In response to the above problems, some studies have proposed solutions using hybrid energy storage technology in DC microgrids.

[0066] Existing hybrid energy storage technologies, such as battery-supercapacitor, battery-superconducting energy storage, etc., utilize the high energy density of batteries and the high power density of other energy storage methods. Through reasonable power control strategies, they simultaneously compensate for the low-frequency and high-frequency power shortages in DC microgrids, which can solve the problem of voltage fluctuations and reduce the defects of life loss caused by frequent charging and discharging of batteries. Compared with other energy storage methods, superconducting energy storage has the advantages of high conversion efficiency, fast power response speed, and long life. Among them, superconducting magnets are the core of superconducting energy storage systems. The current density of superconducting coils is very large, and there is no Joule loss when DC is passed.

[0067] However, in the application research of existing superconducting energy storage systems in photovoltaic storage, direct current and flexible systems, most superconducting energy storage coils are directly connected to the high-voltage DC bus through a chopper. In photovoltaic storage, direct current and flexible systems with multiple voltage levels, this structure is difficult to fully exert the transient high-power compensation benefits of photovoltaic storage, direct current and flexible systems. In order to solve the above-mentioned defects of the prior art, the present application provides a superconducting energy storage system applied to photovoltaic storage, direct current and flexible systems.

[0068] The embodiments of the present application are described below in conjunction with the drawings in the embodiments of the present application.

[0069] Figure 1 is one of the structural schematic diagrams of a superconducting energy storage system applied to a photovoltaic storage direct-flexible system provided in an embodiment of the present application, wherein the photovoltaic storage direct-flexible system includes a high-voltage DC bus and a low-voltage DC bus, such as Figure 1 As shown, the superconducting energy storage system includes:

[0070] A capacitor C, a chopper circuit 1 connected in parallel at both ends of the capacitor, and a first bidirectional DC converter 2 and a second bidirectional DC converter 3 connected in parallel at both ends of the capacitor C through output ends; the input end of the first bidirectional DC converter 2 is connected to a high-voltage DC bus; the input end of the second bidirectional DC converter 3 is connected to a low-voltage DC bus; the chopper circuit 1 is constructed based on a superconducting magnet, a bipolar transistor and a diode;

[0071] The first bidirectional DC converter 2 is used to control the charging and discharging state of the capacitor to compensate for the power fluctuation generated on the high-voltage DC bus side; the second bidirectional DC converter 3 is used to control the charging and discharging state of the capacitor to compensate for the power fluctuation generated on the low-voltage DC bus side; the chopper circuit 1 is used to utilize a superconducting magnet to absorb or release electrical energy to the capacitor C to eliminate the voltage fluctuation generated at both ends of the capacitor C.

[0072] Specifically, in an embodiment of the present application, the superconducting energy storage system is composed of a capacitor C, a chopper circuit 1 connected in parallel at both ends of the capacitor, and a first bidirectional direct current (DC / DC) converter 2 and a second bidirectional direct current (DC / DC) converter 3 connected in parallel at both ends of the capacitor C through the output ends. The first bidirectional DC converter 2 is connected to the high-voltage DC bus of the photovoltaic storage direct-flexible system, and the second bidirectional DC converter 3 is connected to the low-voltage DC bus of the photovoltaic storage direct-flexible system. In this way, a single bidirectional DC converter is used as a direct bridge for power compensation of buses of various levels, and the superconducting energy storage system is connected between the buses of two voltage levels of the photovoltaic storage direct-flexible system. In this way, when the power compensation of the high and low voltage systems is performed, only one bidirectional DC converter is needed, which avoids the problem that the response speed and transmission efficiency of the traditional superconducting energy storage system in the photovoltaic storage direct-flexible system with multiple voltage levels are easily limited by multiple DC converters connected between buses of various levels.

[0073] In an embodiment of the present application, the state of the first bidirectional DC converter 2 is controlled to control the charging and discharging state of the capacitor C to compensate for the power fluctuations generated on the high-voltage DC bus side; or the operating state of the second bidirectional DC converter 3 is controlled to control the charging and discharging state of the capacitor C to compensate for the power fluctuations generated on the low-voltage DC bus side.

[0074] Meanwhile, the chopper circuit 1 is constructed based on a superconducting magnet, a bipolar transistor and a diode. SC The chopper circuit 1 utilizes the superconducting magnet to absorb or release electric energy to the capacitor C, so as to eliminate the voltage fluctuation across the capacitor C caused by the power fluctuation on the bus side, so as to maintain the voltage U across the capacitor C constant.

[0075] It should be noted that the bipolar transistor described in the embodiments of the present application generally refers to a bipolar junction transistor (BJT).

[0076] It can be understood that the power instructions of the controllers of the two bidirectional DC converters are obtained according to the voltage of the DC buses to which they are connected, while the control signal of the chopper circuit 1 is obtained according to the voltage across the capacitor C.

[0077] For example, taking the high-voltage DC bus side as an example, when the source and load are unbalanced in the high-voltage DC system, the voltage of the high-voltage DC bus will rise or fall, resulting in power fluctuations. By controlling the duty cycle of the first bidirectional DC converter 2, the charge and discharge state of the capacitor C is controlled to compensate for the power shortage caused by the power fluctuation on the high-voltage DC bus side. At the same time, the chopper circuit 1 uses a superconducting magnet to absorb or release electrical energy to the capacitor C to eliminate the voltage fluctuations generated at both ends of the capacitor C at this time.

[0078] The superconducting energy storage system applied to the photovoltaic storage, direct and flexible system in the embodiment of the present application comprises a capacitor and a chopper circuit respectively connected in parallel at both ends of the capacitor, a first bidirectional DC converter and a second bidirectional DC converter, wherein the input end of the first bidirectional DC converter is connected to the high-voltage DC bus, and the input end of the second bidirectional DC converter is connected to the low-voltage DC bus, so as to realize the connection of the superconducting energy storage system between the high-voltage DC bus and the low-voltage DC bus of the photovoltaic storage, direct and flexible system. In this way, on the one hand, a single bidirectional DC converter can be used as a direct bridge for power compensation of buses of various levels, so that the superconducting energy storage system only needs to pass through one converter when performing power compensation for the high-voltage and low-voltage DC bus systems, and the power transmission efficiency is high; on the other hand, the voltage difference between the high-voltage and low-voltage DC bus systems can be used to effectively improve the power response speed of the two bidirectional DC converters, reduce the Joule loss caused by the current, further improve the response speed and transmission efficiency of the superconducting energy storage system in the multi-voltage level photovoltaic storage, direct and flexible system, and effectively improve the transient high-power compensation efficiency of the superconducting energy storage system for the photovoltaic storage, direct and flexible system.

[0079] Figure 2 This is the second structural schematic diagram of the superconducting energy storage system applied to the optical storage direct flexible system provided in the embodiment of the present application, such as Figure 2 As shown, in the embodiment of the present application, the first bidirectional DC converter 2 includes a first bipolar transistor T 1 , the second bipolar transistor T 2 , the first inductor L 1 , connected in parallel with the first bipolar transistor T 1 The first diode D between the emitter and collector 1 and connected in parallel with the second bipolar transistor T 2 The second diode D between the emitter and collector 2 ;

[0080] The first inductor L 1 One end is connected to the high voltage DC bus, and the other end is connected to the first bipolar transistor T 1 The emitter of the second bipolar transistor T 2 The collectors of the first bipolar transistor T 1 The collector of the second bipolar transistor T is connected to the positive electrode of the capacitor C.2 The emitter of and the negative electrode of capacitor C are connected to ground;

[0081] The second bidirectional DC converter 3 includes a third bipolar transistor T 3 , the fourth bipolar transistor T 4 , the second inductor L 2 , connected in parallel with the third bipolar transistor T 3 The third diode D between the emitter and collector 3 and connected in parallel with the fourth bipolar transistor T 4 The fourth diode D between the emitter and collector 4 ;

[0082] The second inductor L 2 One end is connected to the low voltage DC bus, and the other end is connected to the third bipolar transistor T 3 The emitter of the fourth bipolar transistor T 4 The collectors of the third bipolar transistor T 3 The collector of the fourth bipolar transistor T is connected to the positive electrode of the capacitor C. 4 The emitter of is connected to the negative electrode of capacitor C.

[0083] Specifically, in the embodiment of the present application, the first inductor L on the first bidirectional DC converter 2 side 1 and the second inductor L on the second bidirectional DC converter 3 side. 2 They are the freewheeling inductors of two bidirectional DC converters, which can not only limit the rate of current change and smooth the current waveform, but also store and release energy, protect other equipment from sudden changes in voltage and current, and ensure the stability and efficiency of the system circuit.

[0084] In addition, the capacitor C is connected to the two busbars through two bidirectional DC converters, thereby realizing the power flow between the superconducting magnet-capacitor-busbar.

[0085] For example, when the source and load are unbalanced in the high-voltage side DC system, the high-voltage bus voltage will rise or fall. In order to reduce the voltage fluctuation, the fully controlled device of the first bidirectional DC converter 2, i.e., the first bipolar transistor T 1 or the second bipolar transistor T 2 The duty cycle is used to control the charge and discharge state of capacitor C to compensate for this power shortage.

[0086] Similarly, when the source and load are unbalanced in the low-voltage DC system, the low-voltage bus voltage will rise or fall. In order to reduce the voltage fluctuation, the fully controlled device of the second bidirectional DC converter 3, that is, the third bipolar transistor T 3 or the fourth bipolar transistor T 4The duty cycle is used to control the charge and discharge state of capacitor C to compensate for this power shortage.

[0087] The system of the embodiment of the present application constructs a bidirectional DC converter by utilizing two bipolar transistors, an inductor, and two diodes respectively connected in parallel between the emitters and collectors of the corresponding bipolar transistors, thereby realizing bidirectional transmission of DC power, improving circuit flexibility and adaptability, and being beneficial to improving the response speed and transmission efficiency of the superconducting energy storage system; at the same time, its cost is relatively low, so that the cost of the entire converter can be effectively controlled.

[0088] Continue to refer to Figure 2 In the embodiment of the present application, the chopper circuit 1 includes a fifth bipolar transistor T 5 , the sixth bipolar transistor T 6 , the fifth diode D 5 , the sixth diode D 6 and superconducting magnet L SC ;

[0089] Superconducting magnet L SC One end of the fifth bipolar transistor T 5 The collector of the fifth diode D 5 The positive poles of the superconducting magnet L SC The other end of the sixth bipolar transistor T 6 The emitter of the sixth diode D 6 The cathode of the sixth diode D 6 The positive electrode of the fifth bipolar transistor T 5 The emitter of the sixth bipolar transistor T is connected to the negative electrode of the capacitor C. 6 The collector of the fifth diode D 5 The negative electrode of is connected with the positive electrode of capacitor C;

[0090] Among them, the fifth bipolar transistor T 5 and the sixth bipolar transistor T 6 When both are turned on, the superconducting magnet L SC Absorb electrical energy from capacitor C; in the fifth bipolar transistor T 5 and the sixth bipolar transistor T 6 When both are turned off, the superconducting magnet L SC The electrical energy is released to capacitor C.

[0091] Specifically, in the embodiment of the present application, the chopper circuit 1 can be composed of a fifth bipolar transistor T 5 , the sixth bipolar transistor T 6 , the fifth diode D 5 , the sixth diode D 6 and superconducting magnet L SC composition.

[0092] like Figure 2 As shown, I is the current flowing through the superconducting magnet L SC When the fully controlled device, the fifth bipolar transistor T 5 and the sixth bipolar transistor T 6 When the superconducting magnet L SC Absorb electrical energy from capacitor C; in the fifth bipolar transistor T 5 and the sixth bipolar transistor T 6 When both are turned off, the superconducting magnet L SC The electric energy is released to the capacitor C. When only the fifth bipolar transistor T is turned on 5 and the sixth bipolar transistor T 6 In one of the cases, the superconducting magnet L SC The current through the sixth diode D 6 or the fifth diode D 5 A loop is formed. At this time, the superconducting magnet L SC It neither absorbs nor releases electrical energy.

[0093] The system of the embodiment of the present application constructs a chopper circuit by utilizing two bipolar transistors, two diodes and a superconducting magnet. Since the superconducting magnet has extremely low resistance, the energy loss in the chopper circuit can be greatly reduced, thereby improving the efficiency of the system's working transmission and power conversion. At the same time, the noise levels of the superconducting magnet and the semiconductor device are relatively low, which can greatly reduce the noise output by the chopper circuit, thereby further improving the reliability and stability of the system circuit.

[0094] In the existing technology, the design and manufacturing of superconducting energy storage systems are complex, and the equipment of the refrigeration system and the expensive materials make its cost relatively high. Therefore, an economical capacity configuration method is crucial to the large-scale application and promotion of superconducting energy storage.

[0095] In order to solve the above-mentioned defects in the prior art, the present application also provides a capacity configuration method of the aforementioned superconducting energy storage system.

[0096] Figure 3 is a flow chart of a method for configuring the capacity of a superconducting energy storage system provided in an embodiment of the present application, which can be applied to any of the superconducting energy storage systems in the aforementioned embodiments, such as Figure 3 As shown, the method includes:

[0097] Step S10, based on the inductance parameter information, rated current parameter information and electric energy parameter information required to be purchased by the superconducting energy storage system, the capacity configuration model of the superconducting energy storage system is determined; the electric energy parameter information is determined based on the power fluctuation information of the photovoltaic storage direct and flexible system on the high and low voltage DC bus and the output power of the superconducting energy storage system;

[0098] Step S20, obtaining a target fitness function based on the objective function of the capacity configuration model; the objective function is constructed with the goal of minimizing the investment cost and operating cost of the superconducting energy storage system;

[0099] Step S30, taking the fitness value of minimizing the target fitness function as the optimization target, iteratively solving the target fitness function, and determining the rated capacity of the superconducting magnet in the superconducting energy storage system.

[0100] Specifically, the inductance parameter information described in the embodiment of the present application refers to the inductance parameter information of the superconducting magnet L in the superconducting energy storage system. SC The inductance parameter L and its value range information. The value range information of the inductance parameter L can be determined according to the model of the superconducting magnet used.

[0101] The rated current parameter information described in the embodiment of the present application refers to the superconducting magnet L in the superconducting energy storage system. SC Rated current parameter I N Similarly, the rated current parameter I N The value range information of can also be determined according to the model of the superconducting magnet used.

[0102] The electric energy parameter information described in the embodiment of the present application refers to the quantitative information of the electric energy required to be purchased by the superconducting energy storage system under the power fluctuations generated by the high-voltage DC bus and / or the low-voltage DC bus. It can be specifically determined based on the power fluctuation information of the photovoltaic storage and direct-flexible system on the high and low voltage DC bus and the output power of the superconducting energy storage system.

[0103] In an embodiment of the present application, in step S10, before determining the capacity configuration model of the superconducting energy storage system based on the inductance parameter information, the rated current parameter information of the superconducting magnet in the superconducting energy storage system and the electric energy parameter information required to be purchased by the superconducting energy storage system, the method further includes:

[0104] Obtain the power fluctuation information of the high and low voltage DC bus of the PV-storage-direct-flexible system at each sampling time within the target period;

[0105] Based on the power fluctuation information at each sampling moment and the maximum output power of the superconducting energy storage system at each sampling moment, the electric energy parameter information required to be purchased by the superconducting energy storage system is determined.

[0106] Specifically, the target time period described in the embodiment of the present application refers to the duration of time that the superconducting energy storage system needs to emit compensation power, which can be recorded as T.

[0107] Furthermore, in the embodiment of the present application, the power fluctuation information of the high and low voltage DC bus of the PV-storage-direct-flexible system at each sampling time in the target period is obtained. It can represent the total power fluctuation of the high and low voltage DC bus, which can be recorded as △P i . Where i represents each sampling moment, and its value is 0, 1, 2, 3, ..., n. Figure 4 As shown, it is necessary to initialize the variables in advance to determine △P 0 = 0 and the initial capacity of the superconducting energy storage system .

[0108] Next, set the calculation time step to △t, then the number of sampling moments is n=T / △t.

[0109] At the same time, the maximum output power of the superconducting energy storage system at each sampling time It will decrease with the increase of discharge depth ɛ, which can be expressed as:

[0110] ;

[0111] in, represents the discharge depth of the superconducting energy storage system at the i-th sampling moment; Indicates the rated capacity of the superconducting energy storage system.

[0112] Among them, the discharge depth of the lower conductive energy storage system at the i-th sampling time is .

[0113] Among them, the capacity of the superconducting energy storage system at the i-th sampling time is .

[0114] It should be noted that the maximum real-time output power of the superconducting magnet is It can also be expressed by Determine, where U is the voltage across the capacitor C, which remains unchanged under control, and I determines the state of charge SOC of the superconducting energy storage system. Therefore, the lower the SOC, the smaller the power that the magnet can emit or absorb, and the worse the high-power compensation capability of the microgrid.

[0115] In order to ensure that the superconducting energy storage system can meet the power demand of the microgrid at any time, its output power must be guaranteed. Among them, ΔP represents the unbalanced power caused by the short-term reduction of photovoltaic power generation of the photovoltaic storage system or the start-up of high-power loads (such as motor loads), and the superscripts 1 and 2 represent the high and low voltage subsystems respectively.

[0116] Therefore, further, in the embodiment of the present application, it is necessary to determine the ΔP at each sampling time. i Is it greater than , that is, whether the total power fluctuation of the high and low voltage DC bus exceeds the current maximum output power of the superconducting energy storage system. If so, the amount of electricity that the superconducting energy storage system needs to purchase at the current sampling time can be expressed as: If not, then .

[0117] Therefore, in the target period T, the power parameter information required by the superconducting energy storage system is It can be expressed as: .

[0118] The method of the embodiment of the present application calculates the amount of electricity required to be purchased by the superconducting energy storage system at different sampling times by exploring the intrinsic connection between the DC bus power fluctuation and the output power of the superconducting energy storage system on a time scale. This can ensure the accuracy and reliability of the calculated parameter information data of the electric energy required to be purchased by the superconducting energy storage system, which is beneficial to improving the accuracy of the subsequent superconducting energy storage system capacity configuration results.

[0119] Based on the content of the above embodiment, as an optional embodiment, step S10, based on the inductance parameter information, rated current parameter information of the superconducting magnet in the superconducting energy storage system and the electric energy parameter information required to be purchased by the superconducting energy storage system, determines the capacity configuration model of the superconducting energy storage system, including:

[0120] Based on the inductance parameter information and the rated current parameter information of the superconducting energy storage system, the investment cost function of the superconducting energy storage system is determined, and based on the rated current parameter information of the superconducting energy storage system and the parameter information of the electric energy required to be purchased by the superconducting energy storage system, the operation cost function of the superconducting energy storage system is determined;

[0121] With the goal of minimizing the investment cost function and the operating cost function of the superconducting energy storage system, the objective function of the capacity configuration model is constructed, and the target constraint conditions are determined based on the value ranges corresponding to the inductance parameter information and the rated current parameter information of the superconducting energy storage system;

[0122] Based on the objective function and objective constraints, a capacity configuration model of the superconducting energy storage system is established.

[0123] Specifically, in the embodiment of the present application, based on the inductance parameter information and the rated current parameter information of the superconducting energy storage system, the rated capacity S of the superconducting magnet SMES It can be expressed as It can be seen that the superconducting magnet L SC The inductance L and rated current I N These are the two most intuitive economic parameters. Considering the energy parameter ΔE required to be purchased from the AC system calculated above, the total cost of the capacity configuration scheme of the superconducting energy storage system can be expressed as: F = F 投资 +YF 运行= F(L,I N, ΔE).

[0124] Among them, F 投资 and F 运行 They represent the investment cost and operating cost of the superconducting energy storage system, respectively, and Y is the service life. The investment cost of the superconducting energy storage system is related to the length and unit price of its superconducting tape, refrigeration equipment, etc., and can be regarded as related to the capacity S of the superconducting energy storage system. SMES is proportional to LI N 2 Proportional; operating costs mainly include transmission loss electric energy F 传输 Cost, power consumption of refrigeration equipment F 制冷 The cost of and the cost of purchased electricity ΔE, etc.

[0125] Among them, F 传输 =365(1-η)E 交互 , where η is the converter power transfer efficiency, E 交互 is the daily interactive power of the superconducting energy storage system, so F 传输 Determined by the system's daily power compensation requirements and the converter; F 制冷 It is generally positively correlated with the power of the superconducting energy storage system. Since this system determines that the terminal voltage U is constant, F 制冷 Can be regarded as I N Therefore, according to the inductance parameter information and rated current parameter information of the superconducting energy storage system, the investment cost function of the superconducting energy storage system can be determined, which can be expressed as:

[0126] F 投资 =k 1 LI N 2 ;

[0127] In the formula, k 1 Represents the cost coefficient of investing in superconducting energy storage system.

[0128] At the same time, according to the rated current parameter information of the superconducting energy storage system and the electric energy parameter information required to be purchased by the superconducting energy storage system, the operation cost function of the superconducting energy storage system can be determined, which can be expressed as:

[0129] F 运行 = k 2 I N + k 3 ΔE+ k 4 ;

[0130] In the formula, k 2 , k 3 , k 4They respectively represent the cost coefficient of electricity consumed by refrigeration equipment when the superconducting energy storage system is running, the cost coefficient of purchased electricity and the cost coefficient of transmission loss electricity.

[0131] Furthermore, according to the above investment cost function and operation cost function of the superconducting energy storage system, the objective function of the capacity configuration model can be constructed with the goal of minimizing the investment cost function and operation cost function of the superconducting energy storage system, which can be expressed as: minF(L,I N ,ΔE)= k 1 LI N 2 + k 2 I N + k 3 ΔE+ k 4 ;

[0132] Among them, k 1 , k 2 , k 3 , k 4 Represents cost coefficients. In actual processes, they are closely related to factors such as real-time electricity prices, system operating status, and seasons, and can be estimated empirically based on actual conditions.

[0133] In the embodiment of the present application, considering the superconducting magnet L in the superconducting energy storage system SC The inductance L and rated current I N The value range of , sets the target constraint condition as:

[0134] ;

[0135] Where, L max , L min They represent the superconducting magnet L SC The maximum and minimum values ​​of the inductance L can be set; They represent the superconducting magnet L SC Rated current I N Maximum and minimum values ​​can be set.

[0136] Furthermore, based on the objective function and objective constraints obtained above, a capacity configuration model of the superconducting energy storage system can be established, which can be specifically expressed as:

[0137] minF(L,I N ,ΔE)=min(k 1 LI N 2 + k 2 I N + k 3 ΔE+ k 4 ),

[0138] .

[0139] The method of the embodiment of the present application comprehensively considers the intrinsic relationship between the inductance and rated current parameters of the superconducting magnet in the superconducting energy storage system and its investment cost and operating cost, combines the value ranges of the two types of electrical parameters of the superconducting magnet, and aims to minimize the investment cost and operating cost of the superconducting energy storage system. A capacity configuration model of the superconducting energy storage system is established, which is conducive to ensuring the reliability and economy of model construction, so as to effectively obtain the optimal capacity configuration plan of the superconducting energy storage system through subsequent model optimization analysis.

[0140] Further, in an embodiment of the present application, in step S20, based on the objective function of the capacity configuration model, a target fitness function can be obtained, that is, the target fitness function can be expressed as:

[0141] fit = F(L,I N ,ΔE)= k 1 LI N 2 + k 2 I N + k 3 ΔE+ k 4 .

[0142] Further, in an embodiment of the present application, in step S30, an optimal solution search algorithm, such as a particle swarm optimization (PSO) algorithm, a genetic algorithm (GA), etc., can be used to minimize the fitness value of the target fitness function as the optimization target, and the target fitness function is iteratively solved. The optimal solution searched by the algorithm can determine the superconducting magnet L in the superconducting energy storage system. SC The rated capacity to be set.

[0143] The capacity configuration method of the superconducting energy storage system in the embodiment of the present application fully explores the correlation between the electrical parameter characteristics of the superconducting magnet of the superconducting energy storage system and its investment cost and operating cost, and uses an iterative optimization algorithm to obtain the optimal configuration of the superconducting energy storage system. Under the premise of ensuring the short-term high-power compensation requirement, it can effectively reduce the total cost of investment and operation of the superconducting energy storage system and achieve the optimal economy of the superconducting energy storage system.

[0144] Based on the content of the above embodiment, as an optional embodiment, step S30, taking the fitness value of the target fitness function minimized as the optimization target, iteratively solving the target fitness function to determine the rated capacity of the superconducting magnet in the superconducting energy storage system, includes:

[0145] Step S101, initializing each particle of the particle swarm optimization algorithm, the local optimal position of each particle, and the current global optimal particle based on the preset value range of the inductance parameter and the rated current parameter of the superconducting magnet in the superconducting energy storage system;

[0146] Step S102, substituting the inductance parameter information and rated current parameter information corresponding to each particle, and the electric energy parameter information required to be purchased by the superconducting energy storage system into the target fitness function to determine the fitness value of each particle;

[0147] Step S103, with the goal of minimizing the fitness value, updating the local best position of each particle and the global best particle in the current iteration process;

[0148] Step S104, determine whether the current number of iterations reaches the maximum number of iterations or whether the fitness value of the current global optimal particle converges; if not, update the position and speed of each particle and jump to step S103; if yes, execute step S105;

[0149] Step S105, obtaining a global optimal particle of the particle swarm optimization algorithm, and determining the rated capacity of the superconducting magnet in the superconducting energy storage system based on the inductance parameter information and the rated current parameter information corresponding to the global optimal particle.

[0150] Specifically, in the embodiments of the present application, the PSO algorithm is used as an example to introduce a specific implementation method of minimizing the fitness value of the target fitness function as the optimization target, and iteratively solving the target fitness function to determine the rated capacity of the superconducting magnet in the superconducting energy storage system.

[0151] Figure 5 is a flow chart of a method for configuring the capacity of a superconducting energy storage system based on a PSO algorithm provided in an embodiment of the present application, such as Figure 5 As shown, in the embodiment of the present application, in step S101, parameter initialization is performed. Specifically, the superconducting magnet L in the superconducting energy storage system SC The inductance parameter L and rated current parameter I N The preset value range of is used to randomly initialize each particle of the PSO algorithm and the local optimal position of each particle.

[0152] It can be understood that each particle carries a randomly initialized inductance parameter L and a rated current parameter I N data.

[0153] Further, in step S102, the fitness value fit of each particle is calculated to evaluate the particle individual. Specifically, according to the above embodiment, the electric energy parameter information required to be purchased by the superconducting energy storage system is determined. , the electric energy parameter information , the inductance parameter L and rated current parameter I carried by each particle N Data and various cost coefficients are substituted into the aforementioned target fitness function fit = F (L, I N ,ΔE), the fitness value of each particle can be calculated.

[0154] Then, in step S103, the global best particle is initialized. The global best particle is initialized according to the aforementioned initialized particles and the local best position of each particle.

[0155] Next, in step S104, the speed and position of each particle are updated. Specifically, the minimum fitness value fit is searched to update the speed and position of each particle in the current iteration process with the goal of minimizing the fitness value;

[0156] Next, in step S105, by evaluating the fitness of each particle at present, the value pBest of the local best position of each particle is determined and updated;

[0157] Furthermore, in step S106, the fitness value gBest of the global best particle in the current iteration is determined and updated from the local best position of each particle, wherein the smallest fitness value among all fitness values ​​pBest is gBest.

[0158] Furthermore, in step S107, it is determined whether the current number of iterations reaches the maximum number of iterations, or whether the fitness value gBest of the current global optimal particle converges. If not, it jumps to step S104, performs state estimation on each particle, adaptively controls algorithm parameters and executes elite learning strategy to complete the update of the speed and position of each particle in a new round of iterations, until the aforementioned step S107 is repeated.

[0159] Furthermore, in step S107, it is determined whether the current iteration number reaches the maximum iteration number or whether the fitness value gBest of the current global optimal particle converges. If so, it means that the algorithm iteration termination condition is met, and step S108 is executed.

[0160] Finally, in step S108, the optimal solution can be obtained, which is the global optimal particle of the current PSO algorithm. Based on the fitness value gBest of the global optimal particle, its corresponding inductance parameter L and rated current parameter I can be determined. N Data, and then finally we can get the superconducting magnet L in the superconducting energy storage system SC Rated capacity S SMES .

[0161] The method of the embodiment of the present application, by combining the optimal economic design of the aforementioned superconducting energy storage system, adopts the PSO algorithm to iteratively solve the target fitness function constructed based on the electrical parameter characteristics of the superconducting magnet of the superconducting energy storage system, which can further greatly improve the accuracy and efficiency of the optimal configuration of the capacity of the superconducting energy storage system.

[0162] Figure 6 Schematic diagram of the structure of the superconducting energy storage system provided in the embodiment of the present application applied in the double busbar structure optical storage direct and flexible system, such as Figure 6 As shown in the figure, the system adopts a single-pole connection and includes two voltage-level subsystems. The high-voltage subsystem includes a photovoltaic system, a battery energy storage system, a constant power load, an electric vehicle load, and a motor-type load; the low-voltage subsystem includes a battery energy storage system, a constant power load, and a motor-type load. The external AC grid is connected to the high-voltage subsystem through an AC / DC converter (VSC), and the superconducting energy storage system is connected to both the high-voltage and low-voltage subsystems. Through simulation fitting, the power absorbed by the constant power load in a certain period of time is (P L_min , P L_max ), the motor load starts during this period and absorbs a large amount of power from the microgrid. The steps of superconducting energy storage system capacity configuration are: first, determine the power shortage that superconducting energy storage should compensate for during this period according to the response power of the battery during this period and the power emitted by the photovoltaic system. Determine a group of groups within the target constraints and obtain the economic optimal solution through the steps of the aforementioned PSO algorithm.

[0163] In order to more clearly illustrate the optimal configuration of the superconducting energy storage capacity of the present application, another specific embodiment is described in detail below. In this embodiment, it is taken into account that there is a loss in the power transmission of the converter, and the photovoltaic system is affected by weather or other factors and has short-term fluctuations. By simulating and fitting the high-power fluctuations that occur in the photovoltaic system when the light intensity suddenly changes within a certain period of time, the steps for configuring the capacity of the superconducting energy storage system are: first, predict the power ΔP that the superconducting energy storage system needs to emit, and the specific steps are as follows:

[0164] Assume that the PV-storage direct-flexible system is in high-load operation at a certain moment. If the power transmission loss is ignored, then: P PV +P BESS= P LOAD Among them, the power generated by the photovoltaic cell and the battery is P PV and P BESS , P LOAD It indicates the total power absorbed by all loads in the system. If the sudden change of light intensity or other reasons causes P PV Reduced. At this time, due to the high-load operation of the system, the battery energy storage is difficult to supplement the unbalanced power during this period, and this power will be borne by the superconducting energy storage system.

[0165] By analyzing the long-term photovoltaic power generation curve in the region, it is possible to predict the maximum power fluctuation ΔP that may occur within time T. PV , then the power that the superconducting energy storage system needs to emit is ΔP=ΔP PV The above power is then corrected by the charging and discharging efficiency η of each converter. , calculate the power value that the superconducting energy storage system should emit Then, follow the above Figure 5 The steps of the embodiment shown in the figure are to determine a group of populations within the target constraints, determine the initial global optimum by calculating the fitness fit of each particle in the group, and then evaluate the offspring population obtained after individual learning and social learning of the initial population, and update the global optimal particle, and repeat until the maximum number of iterations is reached, and finally obtain the economic optimal solution to determine the superconducting magnet L in the superconducting energy storage system. SC Rated capacity S SMES The optimal configuration.

[0166] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0167] Based on the same inventive concept, the embodiment of the present application also provides a capacity configuration device for implementing the capacity configuration method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more capacity configuration device embodiments provided below can refer to the limitations on the capacity configuration method above, and will not be repeated here.

[0168] Figure 7 is a schematic diagram of the structure of a capacity configuration device for a superconducting energy storage system provided in an embodiment of the present application, which can be applied to any of the aforementioned superconducting energy storage systems, such as Figure 7 As shown, the capacity configuration device includes:

[0169] The first processing module 100 is used to determine the capacity configuration model of the superconducting energy storage system based on the inductance parameter information, rated current parameter information and electric energy parameter information required to be purchased by the superconducting energy storage system of the superconducting magnet in the superconducting energy storage system; the electric energy parameter information is determined based on the power fluctuation information of the photovoltaic storage direct and flexible system on the high and low voltage DC bus and the output power of the superconducting energy storage system;

[0170] The second processing module 200 is used to obtain a target fitness function based on the objective function of the capacity configuration model; the objective function is constructed with the goal of minimizing the investment cost and operation cost of the superconducting energy storage system;

[0171] The capacity configuration module 300 is used to iteratively solve the target fitness function by minimizing the fitness value of the target fitness function as the optimization target, and determine the rated capacity of the superconducting magnet in the superconducting energy storage system.

[0172] In one embodiment, the capacity configuration module 300 is used to perform the following steps:

[0173] Step S101, initializing each particle of the particle swarm optimization algorithm, the local optimal position of each particle, and the current global optimal particle based on the preset value range of the inductance parameter and the rated current parameter of the superconducting magnet in the superconducting energy storage system;

[0174] Step S102, substituting the inductance parameter information and rated current parameter information corresponding to each particle, and the electric energy parameter information required to be purchased by the superconducting energy storage system into the target fitness function to determine the fitness value of each particle;

[0175] Step S103, with the goal of minimizing the fitness value, updating the local best position of each particle and the global best particle in the current iteration process;

[0176] Step S104, determine whether the current number of iterations reaches the maximum number of iterations or whether the fitness value of the current global optimal particle converges; if not, update the position and speed of each particle and jump to step S103; if yes, execute step S105;

[0177] Step S105, obtaining a global optimal particle of the particle swarm optimization algorithm, and determining the rated capacity of the superconducting magnet in the superconducting energy storage system based on the inductance parameter information and the rated current parameter information corresponding to the global optimal particle.

[0178] In one embodiment, the capacity configuration device further includes:

[0179] The fluctuation information acquisition module is used to obtain the power fluctuation information of the high and low voltage DC bus of the PV-storage-DC-flexible system at each sampling time within the target period;

[0180] The electric energy parameter information determination module is used to determine the electric energy parameter information required to be purchased by the superconducting energy storage system based on the power fluctuation information at each sampling moment and the maximum output power of the superconducting energy storage system at each sampling moment.

[0181] In one of the embodiments, the first processing module is specifically used to determine the investment cost function of the superconducting energy storage system based on the inductance parameter information and the rated current parameter information of the superconducting energy storage system, and determine the operation cost function of the superconducting energy storage system based on the rated current parameter information of the superconducting energy storage system and the electric energy parameter information required to be purchased by the superconducting energy storage system; construct an objective function of the capacity configuration model with the goal of minimizing the investment cost function and the operation cost function of the superconducting energy storage system, and determine the target constraint conditions based on the value ranges corresponding to the inductance parameter information and the rated current parameter information of the superconducting energy storage system; and establish the capacity configuration model of the superconducting energy storage system based on the objective function and the target constraint conditions.

[0182] The capacity configuration device of the superconducting energy storage system in the embodiment of the present application fully exploits the correlation between the electrical parameter characteristics of the superconducting magnet of the superconducting energy storage system and its investment cost and operating cost, and uses an iterative optimization algorithm to obtain the optimal configuration of the superconducting energy storage system. Under the premise of ensuring the short-term high-power compensation requirement, it can effectively reduce the total cost of investment and operation of the superconducting energy storage system, and achieve the optimal economy of the superconducting energy storage system.

[0183] Each module in the above capacity configuration device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0184] Based on the method in the above embodiment, the embodiment of the present application provides an electronic device, such as Figure 8 As shown, the electronic device may include: a processor (Processor) 810, a communication interface (Communications Interface) 820, a memory (Memory) 830 and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other through the communication bus 840. The processor 810 can call the logic instructions in the memory 830 to execute the method in the above embodiment.

[0185] In addition, the logic instructions in the above-mentioned memory 830 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application.

[0186] Based on the method in the above embodiment, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method in the above embodiment.

[0187] Based on the method in the above embodiment, an embodiment of the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the method in the above embodiment.

[0188] It is understandable that the processor in the embodiment of the present application may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. The general-purpose processor may be a microprocessor or any conventional processor.

[0189] The method steps in the embodiments of the present application can be implemented by hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, and the software modules can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, mobile hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC.

[0190] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions may be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)), etc.

[0191] It should be understood that the various numerical numbers involved in the embodiments of the present application are only used for the convenience of description and are not used to limit the scope of the embodiments of the present application.

[0192] It should be understood that expressions such as "including" and "may include" that may be used in the present application indicate the existence of the disclosed functions, operations, or constituent elements, and do not limit one or more additional functions, operations, and constituent elements. In the present application, terms such as "including" and / or "having" may be interpreted as indicating specific characteristics, numbers, operations, constituent elements, components, or combinations thereof, but may not be interpreted as excluding the existence or possibility of adding one or more other characteristics, numbers, operations, constituent elements, components, or combinations thereof.

[0193] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A superconducting energy storage system applied to a direct-flexible optical energy storage system, characterized in that: The photovoltaic energy storage direct-flexible system includes a high-voltage direct current bus and a low-voltage direct current bus, and the superconducting energy storage system includes: A capacitor, a chopper circuit connected in parallel at both ends of the capacitor, and a first bidirectional DC converter and a second bidirectional DC converter connected in parallel at both ends of the capacitor through output ends; the input end of the first bidirectional DC converter is connected to the high-voltage DC bus; the input end of the second bidirectional DC converter is connected to the low-voltage DC bus; the chopper circuit is built based on a superconducting magnet, a bipolar transistor and a diode; The first bidirectional DC converter is used to control the charging and discharging state of the capacitor to compensate for the power fluctuation generated on the high-voltage DC bus side; the second bidirectional DC converter is used to control the charging and discharging state of the capacitor to compensate for the power fluctuation generated on the low-voltage DC bus side; the chopper circuit is used to utilize the superconducting magnet to absorb or release electrical energy to the capacitor to eliminate the voltage fluctuation generated at both ends of the capacitor.

2. The superconducting energy storage system applied to the direct-flexible optical energy storage system according to claim 1 is characterized in that: The first bidirectional DC converter includes a first bipolar transistor, a second bipolar transistor, a first inductor, a first diode connected in parallel between the emitter and the collector of the first bipolar transistor, and a second diode connected in parallel between the emitter and the collector of the second bipolar transistor; One end of the first inductor is connected to the high-voltage DC bus, and the other end is connected to the emitter of the first bipolar transistor and the collector of the second bipolar transistor; the collector of the first bipolar transistor is connected to the positive electrode of the capacitor, and the emitter of the second bipolar transistor and the negative electrode of the capacitor are connected to the ground; The second bidirectional DC converter includes a third bipolar transistor, a fourth bipolar transistor, a second inductor, a third diode connected in parallel between the emitter and the collector of the third bipolar transistor, and a fourth diode connected in parallel between the emitter and the collector of the fourth bipolar transistor; One end of the second inductor is connected to the low-voltage DC bus, and the other end is connected to the emitter of the third bipolar transistor and the collector of the fourth bipolar transistor; the collector of the third bipolar transistor is connected to the positive electrode of the capacitor, and the emitter of the fourth bipolar transistor is connected to the negative electrode of the capacitor.

3. The superconducting energy storage system applied to the direct-flexible optical energy storage system according to claim 2 is characterized in that: The chopper circuit includes a fifth bipolar transistor, a sixth bipolar transistor, a fifth diode, a sixth diode and a superconducting magnet; One end of the superconducting magnet is connected to the collector of the fifth bipolar transistor and the positive electrode of the fifth diode, the other end of the superconducting magnet is connected to the emitter of the sixth bipolar transistor and the negative electrode of the sixth diode, the positive electrode of the sixth diode, the emitter of the fifth bipolar transistor and the negative electrode of the capacitor are connected, and the collector of the sixth bipolar transistor, the negative electrode of the fifth diode and the positive electrode of the capacitor are connected; Wherein, when the fifth bipolar transistor and the sixth bipolar transistor are turned on at the same time, the superconducting magnet absorbs electric energy from the capacitor; when the fifth bipolar transistor and the sixth bipolar transistor are turned off at the same time, the superconducting magnet releases electric energy to the capacitor.

4. A capacity configuration method for a superconducting energy storage system according to any one of claims 1 to 3, characterized in that: include: Based on the inductance parameter information, rated current parameter information of the superconducting magnet in the superconducting energy storage system and the electric energy parameter information required to be purchased by the superconducting energy storage system, the capacity configuration model of the superconducting energy storage system is determined; the electric energy parameter information is determined based on the power fluctuation information of the photovoltaic storage direct and flexible system on the high and low voltage DC bus and the output power of the superconducting energy storage system; Based on the objective function of the capacity configuration model, a target fitness function is obtained; the objective function is constructed with the goal of minimizing the investment cost and operating cost of the superconducting energy storage system; Taking minimizing the fitness value of the target fitness function as an optimization target, the target fitness function is iteratively solved to determine the rated capacity of the superconducting magnet in the superconducting energy storage system.

5. The capacity configuration method according to claim 4, characterized in that: The step of taking minimizing the fitness value of the target fitness function as the optimization target, iteratively solving the target fitness function, and determining the rated capacity of the superconducting magnet in the superconducting energy storage system comprises: Step S101, initializing each particle of the particle swarm optimization algorithm, the local optimal position of each particle, and the current global optimal particle based on the preset value range of the inductance parameter and the rated current parameter of the superconducting magnet in the superconducting energy storage system; Step S102, substituting the inductance parameter information and the rated current parameter information corresponding to each of the particles, and the electric energy parameter information required to be purchased by the superconducting energy storage system into the target fitness function to determine the fitness value of each of the particles; Step S103, with the goal of minimizing the fitness value, updating the local optimal position of each particle and the global optimal particle in the current iteration process; Step S104, determining whether the current number of iterations has reached the maximum number of iterations or whether the fitness value of the current global optimal particle has converged; if not, updating the position and velocity of each particle and jumping to step S103; if yes, executing step S105; Step S105, obtaining a global optimal particle of a particle swarm optimization algorithm, and determining a rated capacity of a superconducting magnet in the superconducting energy storage system based on inductance parameter information and rated current parameter information corresponding to the global optimal particle.

6. The capacity configuration method according to claim 4, characterized in that: Before determining the capacity configuration model of the superconducting energy storage system based on the inductance parameter information, the rated current parameter information of the superconducting magnet in the superconducting energy storage system and the electric energy parameter information required to be purchased by the superconducting energy storage system, the method further includes: Obtaining power fluctuation information of the high and low voltage DC busbars of the PV-storage-DC-flexible system at each sampling time within a target period; Based on the power fluctuation information at each of the sampling moments and the maximum output power of the superconducting energy storage system at each of the sampling moments, the electric energy parameter information required to be purchased by the superconducting energy storage system is determined.

7. The capacity configuration method according to any one of claims 4 to 6, characterized in that: The method of determining the capacity configuration model of the superconducting energy storage system based on the inductance parameter information, the rated current parameter information and the electric energy parameter information required to be purchased by the superconducting energy storage system of the superconducting magnet in the superconducting energy storage system comprises: Based on the inductance parameter information and the rated current parameter information of the superconducting energy storage system, determining the investment cost function of the superconducting energy storage system, and based on the rated current parameter information of the superconducting energy storage system and the electric energy parameter information required to be purchased by the superconducting energy storage system, determining the operation cost function of the superconducting energy storage system; With the goal of minimizing the investment cost function and the operation cost function of the superconducting energy storage system, constructing the objective function of the capacity configuration model, and determining the target constraint conditions based on the value ranges corresponding to the inductance parameter information and the rated current parameter information of the superconducting energy storage system; Based on the objective function and the objective constraint conditions, a capacity configuration model of the superconducting energy storage system is established.

8. A capacity configuration device for a superconducting energy storage system according to any one of claims 1 to 3, characterized in that: include: The first processing module is used to determine the capacity configuration model of the superconducting energy storage system based on the inductance parameter information, rated current parameter information of the superconducting magnet in the superconducting energy storage system and the electric energy parameter information required to be purchased by the superconducting energy storage system; the electric energy parameter information is determined based on the power fluctuation information of the photovoltaic storage direct and flexible system on the high and low voltage DC bus and the output power of the superconducting energy storage system; A second processing module is used to obtain a target fitness function based on the objective function of the capacity configuration model; the objective function is constructed with the goal of minimizing the investment cost and operation cost of the superconducting energy storage system; The capacity configuration module is used to iteratively solve the target fitness function by minimizing the fitness value of the target fitness function as an optimization target, so as to determine the rated capacity of the superconducting magnet in the superconducting energy storage system.

9. An electronic device, characterized in that: include: at least one memory for storing a computer program; At least one processor is used to execute the program stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method according to any one of claims 4 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed on a processor, the processor is caused to execute the method according to any one of claims 4 to 7.

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