Programmable bidirectional DC power supply system based on quantum simulation algorithm

Abstract

The present invention relates to the field of power supply technology, and further to a programmable bidirectional DC power supply system based on a quantum simulation algorithm. The system comprises: a system model building unit, a quantum simulation unit and a control operation unit; the system model building unit is used to define a model of a bidirectional DC power supply system; the initial parameters of the battery are set, and the battery behavior is simulated using quantum simulation, wherein the battery state is represented by a density matrix; it is also used to build the Hamiltonian of the inverter, and the inverter operation is simulated using quantum simulation; the control operation unit is used to control the inverter operation at each time according to the state of the bidirectional DC power supply system at each time, so as to control the operation of the bidirectional DC power supply system. The present invention achieves more efficient energy conversion by introducing a quantum simulation algorithm. Quantum simulation technology can more accurately simulate the behavior of batteries, inverters and loads, optimize the energy transmission path, and thus improve the overall efficiency of the system.

Description

Technical Field

[0001] The present invention belongs to the technical field of power supply, and in particular relates to a programmable bidirectional direct current power supply system based on a quantum simulation algorithm. Background Art

[0002] Bidirectional DC power supply system is an important application field in the field of power electronics today. It can realize the bidirectional transmission of electric energy and has the advantages of high efficiency conversion, low loss and wide application. Such a system usually includes batteries, inverters and loads to convert DC power into AC power and vice versa. However, traditional bidirectional DC power supply systems face a series of technical challenges and problems in practical applications, which limit their performance and application scope.

[0003] In traditional bidirectional DC power systems, there is a large energy loss during energy conversion and transmission, resulting in low overall system efficiency. This limits its application in some high-efficiency application fields, such as renewable energy systems and electric vehicles. The control of bidirectional DC power systems involves multiple subsystems, including battery management, inverter control, and load management. Traditional control strategies are complex and difficult to achieve efficient and precise control, which easily leads to system stability problems. In practical applications, the energy management of the battery and the operating strategy of the inverter need to be dynamically adjusted according to different needs, and it is difficult for traditional systems to achieve intelligent energy management and optimization. When the system fails or is abnormal, traditional bidirectional DC power systems usually find it difficult to quickly diagnose the root cause of the problem, resulting in high repair and maintenance costs. Summary of the invention

[0004] The main purpose of the present invention is to provide a programmable bidirectional DC power supply system based on a quantum simulation algorithm. The present invention reduces the loss in the energy conversion process by introducing a quantum simulation algorithm, and achieves more efficient energy conversion. Quantum simulation technology can more accurately simulate the behavior of batteries, inverters and loads, optimize the energy transmission path, and thus improve the overall efficiency of the system.

[0005] In order to solve the above problems, the technical solution of the present invention is achieved as follows:

[0006] A programmable bidirectional direct current power supply system based on a quantum simulation algorithm, the system comprising: a system model building unit, a quantum simulation unit and a control operation unit; the system model building unit is used to define a model of the bidirectional direct current power supply system, the model comprising: a battery, an inverter and a load; the quantum simulation unit is used to build the Hamiltonian of the battery, the Hamiltonian of the DC side link of the inverter and the Hamiltonian of the load; the initial parameters of the battery are set, and the battery behavior is simulated by quantum simulation, wherein the battery state is represented by a density matrix; the system model building unit is used to build the Hamiltonian of the inverter and the inverter operation is simulated by quantum simulation; the control operation unit is used to calculate the current and voltage of the battery, the current and voltage of the inverter, and the current and voltage of the load when the quantum simulation unit simulates the battery behavior and the inverter operation, so as to obtain the system state of the bidirectional direct current power supply system at each time, simulate the time evolution of the bidirectional direct current power supply system according to the system state, so as to calculate the state of the bidirectional direct current power supply system at different times, and control the inverter to work at each time according to the state of the bidirectional direct current power supply system at each time, so as to control the operation of the bidirectional direct current power supply system.

[0007] Furthermore, the density matrix Use the following formula to express it:

[0008] ;

[0009] The density matrix is ​​a Hermitian matrix whose diagonal elements represent the occupation probability of energy levels; if there are energy level, then is a Matrix of Indicates energy level and energy level The probability of occupation between and Each is an integer from 1 to N.

[0010] Furthermore, the Hamiltonian of the battery Use the following formula to express it:

[0011] ;

[0012] in, and are the energies of the states of the electrons in the battery, respectively; is the energy of the missing state of the electron.

[0013] Furthermore, quantum simulation is used to simulate battery behavior through the following formula:

[0014] ;

[0015] in, is the annihilation operator of the battery; is the generation operator of the battery; is the battery life; is Planck's constant; is an imaginary unit; Represents the rate of change of the density matrix.

[0016] Further, the method of using quantum simulation to simulate the inverter operation includes: setting the initial time Initially, the quantum state of the inverter is composed of an initial density matrix Description: Use the following formula to calculate the time evolution operator of the inverter To simulate inverter operation:

[0017] ;

[0018] in, is the Hamiltonian of the inverter; The time limit.

[0019] Furthermore, the Hamiltonian of the inverter Use the following formula to express it:

[0020] ;

[0021] in, It is The energy level splitting frequency of a bit changes with time, indicating the evolution of the energy level of the bit in time; is the interaction term, which indicates that At that time, bits and The interaction strength of the bits; and They are The Pauli matrix of bits Quantity and Quantity.

[0022] Furthermore, the control calculation unit uses the following formula to calculate the current and voltage of the battery:

[0023] ;

[0024] in, The density matrix representing the battery contains the probability distribution information of the battery between different energy levels and quantum states; and They are the annihilation operator and the creation operator of the battery, which are used to change the quantum state of the battery by increasing or decreasing the number of electrons or energy; Represents the battery's particle number operator, used to calculate the number of particles in the battery; represents the battery current, which is calculated by tracking the expected value of the number of particles in the battery; The particle number operator representing the battery The trace of gives the expected number of electrons in the battery; the current is the rate of change of the number of electrons; represents the battery voltage, calculated by tracking the expected value of the battery's energy; The Hamiltonian of the battery The trace of the density matrix of the battery gives the expected value of the energy of the battery; the voltage is the rate of change of energy; the current and voltage of the inverter are calculated using the following formula:

[0025] ;

[0026] in, The density matrix of the DC link represents the quantum state of the DC link, and includes the probability distribution information of the DC link between different energy levels and quantum states; and They are the annihilation and creation operators of the DC side link, respectively, which are used to change the quantum state of the DC side link by increasing or decreasing the number of electrons or energy; represents the particle number operator of the inverter, which is used to calculate the number of particles in the DC link; represents the DC side current of the inverter, which is calculated by tracking the expected value of the number of particles in the DC side link; Particle number operator representing the inverter of the DC link traces; represents the DC side voltage of the inverter, which is calculated by tracking the energy expectation value of the DC side link; Hamiltonian of the DC link The trace of the density matrix of the DC link; the current and voltage of the load are calculated using the following formulas:

[0027] ;

[0028] in, is the density matrix of the load; and They are the annihilation operator and the creation operator of the load respectively; The particle number operator representing the load; Indicates load current; The particle number operator in the load traces; Indicates the load voltage; Hamiltonian representing the load Trace of the density matrix with the loadings.

[0029] Furthermore, suppose the system state of the bidirectional DC power supply system is ; The expression is:

[0030] ;

[0031] Using vector singular value decomposition, we can calculate The transpose of the left singular vector matrix, singular value matrix and right singular vector matrix of ; the time evolution of the bidirectional DC power supply system is simulated based on Trotter decomposition using the following formula:

[0032] ;

[0033] in, Indicates the number of time steps, indicating that the time arrive The total time evolution of One hour walk is the number of matrix rows of the total Hamiltonian; represents the time evolution operator, representing different subparts of the total Hamiltonian In a time step Internal influence; ; Indicates time arrive Status at the time; represents the time increment; part of the total Hamiltonian is equal to the sum of the elements in each row of the matrix of the total Hamiltonian.

[0034] Further, according to the bidirectional DC power supply system at time Status , and the bidirectional DC power system is obtained at time The current and voltage of the load, the current and voltage of the inverter, and the current and voltage of the battery are used to control the operation of the inverter of the bidirectional DC power supply system using a set control algorithm.

[0035] Furthermore, the control algorithm is a feedback control algorithm.

[0036] The programmable bidirectional DC power supply system based on quantum simulation algorithm of the present invention has the following beneficial effects: In the traditional bidirectional DC power supply system, the loss in the process of energy conversion and transmission is large, which limits its application in the field of high-efficiency applications. The present invention adopts quantum simulation technology, which can reduce the loss in the process of energy conversion and improve the energy conversion efficiency of the system. This is of great significance for applications that require efficient power conversion, such as battery energy storage systems and solar inverters. The bidirectional DC power supply system of the present invention introduces an intelligent energy management strategy, and realizes intelligent energy management of batteries through quantum simulation technology. The system can adjust the charging and discharging strategy of the battery in real time according to the dynamic power demand and supply situation, thereby maximizing the cycle life and energy utilization rate of the battery. This is particularly important for fields such as renewable energy systems and electric vehicles, and helps to improve the sustainability and economy of the system. The present invention adopts a feedback control algorithm to realize intelligent control of the inverter. By real-time monitoring of the system status and adjusting the working parameters of the inverter according to the feedback information, the system can better adapt to different working conditions and requirements. This not only improves the performance and stability of the system, but also reduces maintenance and operating costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A schematic diagram of the system structure of a programmable bidirectional DC power supply system based on a quantum simulation algorithm provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0039] Example 1: Reference Figure 1, a programmable bidirectional DC power supply system based on a quantum simulation algorithm, the system comprising: a system model building unit, a quantum simulation unit and a control operation unit; the system model building unit is used to define a model of the bidirectional DC power supply system, the model comprising: a battery, an inverter and a load; the quantum simulation unit is used to build the Hamiltonian of the battery, the Hamiltonian of the DC side link of the inverter and the Hamiltonian of the load; set the initial parameters of the battery, use quantum simulation to simulate the battery behavior, wherein the battery state is represented by a density matrix; and also used to build the Hamiltonian of the inverter, and use quantum simulation to simulate the inverter operation; the control operation unit is used to calculate the current and voltage of the battery, the current and voltage of the inverter, and the current and voltage of the load when the quantum simulation unit simulates the battery behavior and simulates the inverter operation, so as to obtain the system state of the bidirectional DC power supply system at each time, simulate the time evolution of the bidirectional DC power supply system according to the system state, so as to calculate the state of the bidirectional DC power supply system at different times, and control the inverter to work at each time according to the state of the bidirectional DC power supply system at each time, so as to control the operation of the bidirectional DC power supply system.

[0040] Specifically, battery simulation is based on the principle of quantum simulation, which is a method of using quantum computers to simulate quantum physical systems or other physical systems. In battery simulation, Hamiltonian is used to describe the quantum state evolution of the bidirectional DC power system. Hamiltonian is a mathematical operator that describes the energy of a quantum system, usually expressed as a mathematical formula. First, it is necessary to construct the Hamiltonian of the bidirectional DC power system. This Hamiltonian is an energy expression of the bidirectional DC power system, including energy terms inside the battery, interaction terms with the external environment, and possible control terms. The form of the Hamiltonian will depend on the type of battery and the required accuracy. Use the constructed Hamiltonian to simulate the quantum state evolution of the bidirectional DC power system. On a quantum computer, the effect of the Hamiltonian can be simulated by applying appropriate quantum gates. This allows the quantum state of the bidirectional DC power system to evolve in time, thereby capturing the behavior of the battery. The battery state is usually represented by a density matrix. The density matrix is ​​a mathematical tool for describing quantum states, which contains all information about the system, including its probability distribution and coherence. Through the density matrix, the state information of the battery at different time points can be obtained. The results of battery simulation can be used to optimize the control strategy of the bidirectional DC power supply system. For example, the charging and discharging strategies can be adjusted according to the simulation results to improve the performance and efficiency of the system.

[0041] By simulating the operation of the inverter, the output current and voltage of the inverter can be calculated. This output information can help understand the response of the inverter under different input conditions and the characteristics of the output waveform. Through the results of the inverter operation simulation, the control strategy of the bidirectional DC power supply system can be optimized. For example, the switching frequency, duty cycle and modulation method of the inverter can be adjusted according to the simulation results to improve the performance and efficiency of the system.

[0042] The system state is simulated as a time-varying process, typically using discrete time steps. At each time step, the state of the system is updated to reflect the various physical processes in the system, including the operation of the battery and inverter and changes in the load. At each time step, the state of the system (such as battery voltage, current, and inverter output) is updated based on the simulation results. These updates take into account the simulated physical processes as well as the impact of the inverter control strategy. Based on the simulated system state, the control algorithm is applied to determine the operation of the inverter to achieve the specific control objectives of the system. The control strategy can be optimized and adjusted as needed to meet the performance and efficiency requirements of the system.

[0043] Based on the quantum simulation algorithm to simulate the behavior of the battery and inverter and the real-time calculation of the system state, the control operation unit can calculate the current and voltage of the battery and inverter, as well as the current and voltage of the load. Then, it can be used for the time evolution simulation of the system to calculate the state of the system at different times and control the operation of the inverter according to the system state. The bidirectional DC power supply system of the present invention is programmable because it uses a quantum simulation algorithm, which allows the simulation parameters, control strategies and system configurations to be flexibly adjusted to meet the needs of different applications. Therefore, the system can be programmed and customized according to specific tasks or scenarios. The system is able to monitor the status of the battery, inverter and load in real time, as well as control according to the monitoring results. This allows the system operator to better understand the actual operation of the system and adjust the working mode of the inverter in real time to meet the needs of the system.

[0044] Example 2: Density Matrix Use the following formula to express it:

[0045] ;

[0046] The density matrix is ​​a Hermitian matrix whose diagonal elements represent the occupation probability of energy levels; if there are energy level, then is a Matrix of Indicates energy level and energy level The probability of occupation between and Each is an integer from 1 to N.

[0047] Specifically, the density matrix is a The matrix of represents the number of energy levels in the battery. The elements of this matrix Indicates the energy level and energy level These occupation probabilities represent the distribution of the quantum state of the battery at different energy levels. The density matrix is a Hermitian matrix, meaning that it is self-conjugated, i.e., where represents complex conjugation. This ensures that the elements of the density matrix satisfy physical requirements while preserving the properties of the quantum state. The diagonal elements of the density matrix are Indicates the energy level The occupation probability of the particle is The probability of the off-diagonal elements Indicates the energy level and energy level The correlations between them describe the quantum interference and coherence between different energy levels. It can be used to describe the quantum state of the battery. By manipulating and evolving the density matrix, the behavior of the battery under different conditions can be simulated, including processes such as charging, discharging, and energy storage. The use of the density matrix is ​​particularly important in quantum simulation. It can be used to simulate the evolution of the quantum state of the battery to understand and optimize the performance of the battery. Quantum simulation can be performed on a quantum computer to improve the accuracy of the simulation of battery behavior.

[0048] Example 3: Hamiltonian of a battery Use the following formula to express it:

[0049] ;

[0050] in, and are the energies of the states of the electrons in the battery, respectively; is the energy of the missing state of the electron.

[0051] Specifically, the Hamiltonian is a The matrix represents the quantum state of the bidirectional DC power supply system. In this matrix, and Represents the energy of the two states of electrons in the battery. Usually, Corresponding to the excited state of the electron (occupiedstate), corresponds to the ground state (unoccupiedstate) of the electron. Hamiltonian In and is the energy of the electron energy level. These two energy levels correspond to the two states of the electron in the battery, which describe the energy state of the electron in the battery. Hamiltonian The energy level structure reflects the energy distribution of electrons in the bidirectional DC power supply system. corresponds to the occupied state of the electron in the battery, and corresponds to the unoccupied state of the electron. The energy difference between these two energy levels can affect the behavior of the electron and the performance of the battery. By using the Hamiltonian , which can simulate the quantum state evolution of electrons in a bidirectional DC power system. This helps to understand the energy level transitions, electronic excitations and de-excitations of electrons in batteries, as well as the effects of these processes on battery performance. Hamiltonian The use of is particularly important in quantum simulation. It can be used to simulate the evolution of electronic energy levels inside the battery to understand the battery's performance, charging and discharging processes, and the dynamic behavior of electrons in the battery. Hamiltonian is an important concept in quantum mechanics, which represents the total energy operator of a system. In a bidirectional DC power supply system, is a The matrix represents the quantum state of the electron in the battery. This matrix form shows that the bidirectional DC power supply system has two quantum states, one corresponding to the energy The electronic state and the other corresponding to the energy The electron-missing state. Energy level represents the energy of the ground or available state of electrons in a battery, while energy levels Represents the energy of the missing state of an electron. Usually, will be lower, indicating that the energy of the electron in the excited state is higher, while Indicates that the electron has lost state or energy in the battery. The Hamiltonian of the battery is represented in matrix form, where the diagonal elements represent the energy levels of the system. The matrix form makes it easy to handle the energy levels of the bidirectional DC power system in quantum computing for simulation and analysis. This Hamiltonian describes a two-level system in which the electrons in the battery can only be in one of two possible states, namely or This simple model can be used to describe many basic behaviors in batteries.

[0052] Example 4: Quantum simulation is used to simulate battery behavior using the following formula:

[0053] ;

[0054] in, is the annihilation operator of the battery; is the generation operator of the battery; is the battery life; is Planck's constant; is an imaginary unit; Represents the rate of change of the density matrix.

[0055] Specifically, This term represents the density matrix The rate of change over time is the time derivative of the density matrix. The density matrix is ​​a tool used to describe the quantum state of a bidirectional DC power system, and it contains information about all possible quantum states. This term tells us how to update the density matrix over time to reflect the evolution of the quantum state. - i ℏ [ H bat , ρ bat ] This section describes the Hamiltonian in a bidirectional DC power system. With the density matrix The physical significance of the commutator is that it represents the relationship between the Hamiltonian and the density matrix of the quantum system. Through this term, we can understand how the quantum state in the bidirectional DC power supply system evolves with the action of the Hamiltonian. is Planck's constant, are imaginary units, and they play an important role in quantum mechanics. This section describes the annihilation operator in a bidirectional DC power system. and the generation operator These operators are often used to describe the decoherence process of quantum states, where electrons may be lost or decayed. This term takes into account the lifetime of the bidirectional DC power system. The effect on the quantum state is the time that the electron stays in the battery. The purpose of this formula is to describe the evolution of the quantum state over time in the bidirectional DC power system. First, through the Hamiltonian term, it takes into account how the quantum state in the bidirectional DC power system changes with the dynamic evolution of the system. Secondly, through the annihilation operator and production operator terms, it takes into account the decoherence process of the quantum state in the battery, which is related to the loss or attenuation of electrons. By solving this equation, the time evolution of the quantum state in the battery can be simulated to understand how quantum effects in the bidirectional DC power system affect its performance and life.

[0056] Embodiment 5: The method of using quantum simulation to simulate inverter operation includes: setting the initial time Initially, the quantum state of the inverter is composed of an initial density matrix Description: Use the following formula to calculate the time evolution operator of the inverter To simulate inverter operation:

[0057] ;

[0058] in, is the Hamiltonian of the inverter; The time limit.

[0059] Specifically, this simulation process starts from the initial time Starting from this, the quantum state of the inverter is given by the initial density matrix Description. This initial density matrix represents the quantum state of the inverter at the initial moment and contains the possible quantum state information in the system. The Hamiltonian of the inverter is an energy operator that describes the energy level structure and dynamics of the inverter system. This Hamiltonian usually changes with time. The time evolution operator is Used to simulate the inverter over a period of time It is calculated by the Hamiltonian In the time interval [0, T ] It is calculated by integrating the is the upper limit of simulation time. The time evolution of the inverter system, including the evolution of the quantum state, is represented. is Planck's constant, which plays an important role in quantum mechanics and is often used to relate classical physics to quantum physics. is a mathematical function that converts the time evolution operator The time integral in is transformed into an operator. The role of this exponential function is to map the time-evolving quantum state to a new point in time. This formula uses quantum simulation to simulate the inverter operation. Quantum simulation allows us to simulate the time evolution of quantum systems, including how quantum states change over time. By calculating the time evolution operator , we can understand the operation and evolution of the inverter system over a given period of time. By simulating the inverter operation, we can understand the evolution of the quantum state in the inverter system. By solving this equation, we can obtain the quantum state of the inverter at different points in time, so that we can analyze the performance, efficiency and control method of the inverter.

[0060] Example 6: Hamiltonian of the inverter Use the following formula to express it:

[0061] ;

[0062] in, It is The energy level splitting frequency of a bit changes with time, indicating the evolution of the energy level of the bit in time; is the interaction term, which indicates that At that time, bits and The interaction strength of the bits; and They are The Pauli matrix of bits Quantity and Quantity.

[0063] Specifically, It is The energy level splitting frequency of a bit indicates the evolution of the energy level of the bit over time. It reflects whether the energy level structure of the bit changes at different time points. This term is usually used to describe the process of energy level transition and energy level splitting. is the interaction term, which indicates that Time bits and The interaction strength between bits. It describes the coupling effect between bits and can be used to analyze the mutual influence between bits. In quantum computing, these interaction terms are often used to implement quantum gate operations. and It is The Pauli matrix of bits Quantity and components. The Pauli matrices are a set of matrices that describe the properties of quantum spin systems. In this formulation, they are used to construct the Hamiltonian of the inverter to account for the different spin orientations and interactions between bits. and is the summation symbol, which means to sum all the bits. represents the total number of bits in the system. This sum ensures that the inverter Hamiltonian takes into account the interactions between all bits. The inverter Hamiltonian It describes the energy level structure and interaction of the entire inverter system. This Hamiltonian is an important part of quantum simulation and is used to simulate the inverter operation and analyze the quantum state evolution of the system. and , the behavior of the inverter can be changed, thereby achieving different quantum operations and control methods.

[0064] Embodiment 7: The control operation unit uses the following formula to calculate the current and voltage of the battery:

[0065] ;

[0066] in, The density matrix representing the battery contains the probability distribution information of the battery between different energy levels and quantum states; and They are the annihilation operator and the creation operator of the battery, which are used to change the quantum state of the battery by increasing or decreasing the number of electrons or energy; Represents the battery's particle number operator, used to calculate the number of particles in the battery; represents the battery current, which is calculated by tracking the expected value of the number of particles in the battery; The particle number operator representing the battery The trace of gives the expected number of electrons in the battery; the current is the rate of change of the number of electrons; represents the battery voltage, calculated by tracking the expected value of the battery's energy; The Hamiltonian of the battery The trace of the density matrix of the battery gives the expected value of the energy of the battery; the voltage is the rate of change of energy; the current and voltage of the inverter are calculated using the following formula:

[0067] ;

[0068] in, The density matrix of the DC link represents the quantum state of the DC link, and includes the probability distribution information of the DC link between different energy levels and quantum states; and They are the annihilation and creation operators of the DC side link, respectively, which are used to change the quantum state of the DC side link by increasing or decreasing the number of electrons or energy; represents the particle number operator of the inverter, which is used to calculate the number of particles in the DC link; represents the DC side current of the inverter, which is calculated by tracking the expected value of the number of particles in the DC side link; Particle number operator representing the inverter of the DC link traces; represents the DC side voltage of the inverter, which is calculated by tracking the energy expectation value of the DC side link; Hamiltonian of the DC link The trace of the density matrix of the DC link; the current and voltage of the load are calculated using the following formulas:

[0069] ;

[0070] in, is the density matrix of the load; and They are the annihilation operator and the creation operator of the load respectively; The particle number operator representing the load; Indicates load current; The particle number operator in the load traces; Indicates the load voltage; Hamiltonian representing the load Trace of the density matrix with the loadings.

[0071] Specifically, the quantum state of the battery can be expressed using the density matrix This density matrix contains the probability distribution information of the battery between different energy levels and quantum states. In a bidirectional DC power system, the state of the battery is crucial to the operation and performance of the entire system. and the generation operator Used to change the quantum state of the battery by increasing or decreasing the number of electrons or energy. In a bidirectional DC power system, the change in the quantum state of the battery will affect the current and voltage of the system. Used to calculate the expected value of the number of electrons in the battery. The current is the rate of change of the number of electrons, so by tracking the expected value of the particle number operator, the current information of the battery can be obtained. The Hamiltonian of the battery describes the energy level structure and dynamics of the battery. After multiplying with the density matrix, the energy expectation value of the battery can be calculated, which will be used to calculate the voltage. By calculating the particle number operator In the density matrix The expected value on the expected value can be used to obtain the expected value of the number of electrons in the battery, and thus the battery current. The current represents the rate of change of the number of electrons, which is very important for understanding the flow of electrons inside the battery. In a bidirectional DC power supply system, the battery current directly affects the output and performance of the system. The battery voltage is the rate of change of the internal energy of the battery. By calculating the Hamiltonian In the density matrix The expected value on the battery can be used to obtain the expected value of the battery's energy, and thus the battery's voltage. The change in voltage is related to the change in energy inside the battery, which is crucial for the normal operation and performance analysis of the bidirectional DC power supply system. The performance of the bidirectional DC power supply system is closely related to the state and operation of the battery. By calculating the current and voltage, the battery state can be monitored, the system's power supply capacity and stability can be evaluated, and the system's design and control strategy can be optimized.

[0072] The inverter current represents the rate of change of the electron flow in the DC link. The time evolution operator through the inverter is The flow of electrons in the inverter can be simulated. The calculation of current is very important for monitoring the current characteristics of the DC link and evaluating the efficiency of the inverter. The voltage of the inverter represents the energy change rate of the DC link. By calculating the Hamiltonian of the DC link With the trace of the density matrix, the voltage information of the DC side link can be obtained. The calculation of voltage helps to understand the changes in electric energy in the system and the voltage characteristics of the inverter. The inverter is one of the core components in the bidirectional DC power supply system. By calculating the current and voltage, the status and operation of the inverter can be monitored, its performance and efficiency can be evaluated, and the design and control strategy of the system can be optimized. This helps to ensure the stable operation of the inverter under different working conditions. The calculation of the current and voltage of the inverter is part of quantum simulation. Quantum simulation is a method of simulating quantum systems using quantum computing, which helps to understand and optimize quantum effects in bidirectional DC power supply systems.

[0073] By calculating the particle number operator In the density matrix The expected value on the load can be used to obtain the current of the load. The current represents the rate of change of the population, which is important for understanding the flow of particles (usually electrons) in the load. The calculation of the current helps to understand the power demand of the load and the flow of electrons in the load. The voltage of the load represents the rate of change of the energy of the load. By calculating the Hamiltonian In the density matrix The expected value on the load can be used to obtain the expected energy value of the load, and thus the voltage of the load. The change in voltage is related to the change in energy in the load, which is very important for understanding the power balance of the system and the voltage characteristics of the load. The current and voltage calculation of the load helps to evaluate the performance of the power system, understand the power demand and working status of the load, and provide key information for the design and control of the system.

[0074] Example 8: Assume that the system state of the bidirectional DC power supply system is ; The expression is:

[0075] ;

[0076] Using vector singular value decomposition, we can calculate The transpose of the left singular vector matrix, singular value matrix and right singular vector matrix of ; the time evolution of the bidirectional DC power supply system is simulated based on Trotter decomposition using the following formula:

[0077] ;

[0078] in, Indicates the number of time steps, indicating that the time arrive The total time evolution of One hour walk is the number of matrix rows of the total Hamiltonian; represents the time evolution operator, representing different subparts of the total Hamiltonian In a time step Internal influence; ; Indicates time arrive Status at the time; represents the time increment; part of the total Hamiltonian is equal to the sum of the elements in each row of the matrix of the total Hamiltonian.

[0079] Specifically, SVD decomposition transforms the complex system state matrix Decomposed into three matrices, where the singular value matrix Contains the singular values ​​of the system state, which reflect the importance of the system state. By selecting the singular vector with the largest singular value, the dimension of the system state can be reduced while retaining the main characteristics of the system state. This helps to simplify the problem and reduce computational complexity. By analyzing the left singular vector matrix and the transpose of the right singular vector matrix , we can understand the characteristics of the system state in different directions. This helps to identify important states or patterns in the system, thus better understanding the behavior and performance of the system. For example, it can be used to detect anomalies or failures in the system.

[0080] In quantum mechanics, the time evolution of a system is usually described by a Hamiltonian. Contains all energy terms in the bidirectional DC power system, such as the Hamiltonian of the DC link , Hamiltonian of the load and the battery's Hamiltonian These energy terms describe the energy structure and interactions of the components in the system. Trotter decomposition is a numerical method used to approximate the time evolution of the system by decomposing the time evolution of the total Hamiltonian into multiple small time steps. Specifically, the time evolution operator is used to describe the total Hamiltonian In a time step The impact within is a subpart of the total Hamiltonian. The total time evolution is divided into The time increment of each small time step is This means that the total time evolution is from time arrive Approximated as The accumulation of steps over hours. By continuously applying Time evolution operator , can simulate the time arrive The evolution of the system state at all times results in a new state This process can be performed iteratively, thus simulating the time evolution of the entire system.

[0081] Trotter decomposition allows the total time evolution to be approximated as the accumulation of multiple small time steps, thereby improving computational efficiency while maintaining a certain degree of accuracy. This is particularly useful for dealing with complex quantum systems, where accurate numerical evolution can become very expensive. By simulating the evolution of the system state from one time point to another, the state of the bidirectional DC power system at different times can be understood. This helps to analyze the dynamic behavior and performance of the system. Trotter decomposition can be used for control and optimization strategies of the system. By changing the time evolution operator of each small time step, control of the system can be achieved, such as optimizing the performance of the power system or maintaining the stability of the system.

[0082] Embodiment 9: According to the bidirectional DC power supply system at time Status , and the bidirectional DC power system is obtained at time The current and voltage of the load, the current and voltage of the inverter, and the current and voltage of the battery are used to control the operation of the inverter of the bidirectional DC power supply system using a set control algorithm.

[0083] Specifically, first of all, according to the time Status , obtain the information of the load current and voltage, inverter current and voltage, and battery current and voltage of the bidirectional DC power supply system at that moment. These parameters reflect the system The actual state at the moment. Use the set control algorithm to determine the working strategy of the inverter. In this case, the control algorithm is a feedback control algorithm. The feedback control algorithm generally includes the following steps: Measure the current state of the system, including load current and voltage, inverter current and voltage, and battery current and voltage. Compare the measured value with the set value or expected value to determine whether the system is in the desired state. Calculate the error or deviation between the measured value and the set value. Take control decisions based on the error signal to adjust the operation of the inverter, such as changing the output power or frequency of the inverter to bring the system state to the desired state. According to the decision of the control algorithm, adjust the operating parameters of the inverter to achieve the desired system state. This may involve changing the output voltage, frequency, or other operations of the inverter.

[0084] As the inverter adjusts its operation, the state of the system changes accordingly. Therefore, at the end of each time step, the state of the system needs to be updated so that it can be used in the next time step.

[0085] Embodiment 10: The control algorithm is a feedback control algorithm.

[0086] Specifically, in Example 10, a feedback control algorithm is used to control the inverter of the bidirectional DC power supply system. The key feature of the feedback control algorithm is to adjust the control strategy according to the feedback information of the current state of the system so that the system maintains the desired state or reaches the desired state. The specific steps include: measuring the current state of the system, including the load current and voltage, the inverter current and voltage, and the battery current and voltage. Determine the target state that the system should reach, which can be a specific current, voltage or power value, or achieve a specific control goal, such as maximum power point tracking (MPPT). Compare the measured value with the target value, calculate the error or deviation, and reflect the difference between the current state of the system and the desired state. Take a control decision based on the error signal and adjust the operating parameters of the inverter to reduce the error. This may involve changing the output voltage, frequency, operating mode, etc. of the inverter. Continuously monitor the system state and dynamically adjust the control strategy based on the feedback information to ensure that the system is always maintained near the desired state. Adjust the operation of the inverter in real time according to the feedback information to adapt to changes in the system state, thereby maintaining the stability and performance of the system.

[0087] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A programmable bidirectional DC power supply system based on quantum simulation algorithm, characterized in that: The system comprises: a system model building unit, a quantum simulation unit and a control operation unit; the system model building unit is used to define a model of a bidirectional DC power supply system, the model comprising: a battery, an inverter and a load; the quantum simulation unit is used to build the Hamiltonian of the battery, the Hamiltonian of the DC side link of the inverter and the Hamiltonian of the load; set the initial parameters of the battery, use quantum simulation to simulate the battery behavior, wherein the battery state is represented by a density matrix; and also used to build the Hamiltonian of the inverter, and use quantum simulation to simulate the inverter operation; the control operation unit is used to calculate the current and voltage of the battery, the current and voltage of the inverter, and the current and voltage of the load when the quantum simulation unit simulates the battery behavior and simulates the inverter operation, so as to obtain the system state of the bidirectional DC power supply system at each time, simulate the time evolution of the bidirectional DC power supply system according to the system state, so as to calculate the state of the bidirectional DC power supply system at different times, and control the inverter to work at each time according to the state of the bidirectional DC power supply system at each time, so as to control the operation of the bidirectional DC power supply system; the density matrix ρ bat Use the following formula to express it: The density matrix is ​​a Hermitian matrix whose diagonal elements represent the occupation probability of energy levels; if there are N energy levels in the battery, then ρ bat is an N×N matrix; ρ mn represents the occupation probability between energy level m and energy level n; m and n are integers from 1 to N; the Hamiltonian H of the battery bat Use the following formula to express it: Among them, E0 is the energy of the state of the electron in the battery; E1 is the energy of the missing state of the electron; quantum simulation is used to simulate the battery behavior through the following formula: Among them, a is the annihilation operator of the battery; is the generation operator of the battery; τ is the life of the battery; is Planck's constant; i is the imaginary unit; represents the rate of change of the density matrix; the method of using quantum simulation to simulate the inverter operation includes: starting from the initial time 0, the quantum state of the inverter is composed of a certain initial density matrix ρ inv (0) Description: Use the following formula to calculate the time evolution operator U of the inverter: inv (t) To simulate inverter operation: Among them, H inv (t) is the Hamiltonian of the inverter; T is the time limit; the Hamiltonian of the inverter H inv (t) is expressed using the following formula: Among them, ω j (t) is the energy level splitting frequency of the jth bit, which changes with time and represents the evolution of the bit energy level over time; J jk (t) is the interaction term, which represents the interaction strength between the jth bit and the kth bit at time t; and are the z component and x component of the j-th bit of the Pauli matrix respectively; the control operation unit uses the following formula to calculate the current and voltage of the battery: Among them, ρ bat represents the density matrix of the battery, which contains the probability distribution information of the battery between different energy levels and quantum states; a and They are the annihilation operator and the creation operator of the battery, which are used to change the quantum state of the battery by increasing or decreasing the number of electrons or energy; Represents the battery particle number operator, which is used to calculate the number of particles in the battery; I bat (t) represents the battery current, which is calculated by tracking the expected value of the number of particles in the battery; The particle number operator representing the battery The trace of V gives the expected number of electrons in the battery; the current is the rate of change of the number of electrons; V bat (t) represents the battery voltage, which is calculated by tracking the expected energy value of the battery; Tr(ρ bat H bat ) represents the Hamiltonian H of the battery bat The trace of the density matrix of the battery gives the expected value of the energy of the battery; the voltage is the rate of change of energy; the current and voltage of the inverter are calculated using the following formula: Among them, ρ dc-link represents the density matrix of the DC link, represents the quantum state of the DC link, and contains the probability distribution information of the DC link between different energy levels and quantum states; β and They are the annihilation and creation operators of the DC side link, respectively, which are used to change the quantum state of the DC side link by increasing or decreasing the number of electrons or energy; I represents the particle number operator of the inverter, which is used to calculate the number of particles in the DC link; dc-link (t) represents the DC side current of the inverter, which is calculated by tracking the expected value of the number of particles in the DC side link; Particle number operator representing the inverter of the DC link traces; V dc-link (t) represents the DC side voltage of the inverter, which is calculated by tracking the expected energy value of the DC side link; Tr(ρ dc-link H dc-link ) represents the Hamiltonian H of the DC link dc-link The trace of the density matrix of the DC link; the current and voltage of the load are calculated using the following formulas: Among them, ρ load is the density matrix of the load; γ and They are the annihilation operator and the creation operator of the load respectively; The particle number operator representing the load; I load (t) represents the load current; The particle number operator in the load traces; V load (t) represents the load voltage; Tr(ρ load H load ) represents the Hamiltonian H of the load load Trace of the density matrix with the loadings.

2. The programmable bidirectional DC power supply system based on quantum simulation algorithm as claimed in claim 1, characterized in that: Assume that the system state of the bidirectional DC power supply system is A(t); the expression of A(t) is: A(t)= {(I load (t),V load (t)),(I dc-link (t),V dc-link (t)),(V bat (t),I bat (t))}; Using vector singular value decomposition, the transpose of the left singular vector matrix, singular value matrix, and right singular vector matrix of A(t) is calculated; the time evolution of the bidirectional DC power supply system is simulated based on Trotter decomposition using the following formula: Among them, N steps represents the number of time steps, which means that the total time evolution from time t to t+δt is divided into N steps Hourly walk; N steps is the number of matrix rows of the total Hamiltonian; represents the time evolution operator, representing different sub-parts of the total Hamiltonian H j Effects within a time step δt; Total Hamiltonian = H dc-link +H load +H bat ; B(t+δt) represents the state from time t to t+δt; δt represents the time increment; the part of the total Hamiltonian H j is equal to the sum of the elements in each row of the matrix of the total Hamiltonian.

3. The programmable bidirectional DC power supply system based on quantum simulation algorithm as claimed in claim 2, characterized in that: According to the state B(t+δt) of the bidirectional DC power supply system at time t+δt, the current and voltage of the load, the current and voltage of the inverter, and the current and voltage of the battery of the bidirectional DC power supply system at time t+δt are obtained, so as to control the operation of the inverter of the bidirectional DC power supply system using the set control algorithm.

4. The programmable bidirectional DC power supply system based on quantum simulation algorithm as claimed in claim 3, characterized in that: The control algorithm is a feedback control algorithm.

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