Power distribution method, device and equipment for optical storage and charging integrated direct-current micro-grid

Abstract

The invention discloses a power distribution method, device and equipment for an optical storage and charging integrated direct current micro-grid, and relates to the application field of high conversion efficiency of a high-efficiency optical storage and charging integrated direct current micro-grid, and the method comprises the steps: constructing a basic constraint condition and a target constraint condition of a target direct current micro-grid; constructing a total loss power target function for performing power distribution on the target DC micro-grid, wherein objects to be subjected to power distribution comprise an energy storage module and a charging pile module; based on a basic constraint condition and the target constraint condition, adopting an equal incremental rate criterion, taking the minimum total loss power of an object to be subjected to power distribution of the target optical storage and charging integrated direct current micro-grid architecture as a target, and solving a total loss power target function to obtain the optimal power distribution of the optical storage and charging integrated direct current micro-grid architecture. And obtaining the distribution power of the object to be subjected to power distribution corresponding to the different operation state modes. According to the method, the more accurate distribution power of the object to be subjected to power distribution can be obtained through optimization, the lowest total loss power is obtained, the loss rate is reduced, and energy is saved.

Description

Technical Field

[0001] This invention relates to the application field of high-efficiency photovoltaic-storage-charging integrated DC microgrids to achieve high conversion efficiency, and particularly to a power distribution method, device, storage medium, and electronic equipment for photovoltaic-storage-charging integrated DC microgrids. Background Technology

[0002] When the total power and direction at the grid connection point of a high-efficiency photovoltaic-storage-charging integrated DC microgrid are constant, the traditional method of optimizing the power allocation of each charging pile module and energy storage module connected to the load is to distribute the power evenly or randomly under the premise of meeting basic constraints. This results in excessive power distribution loss, waste of electrical energy and increased grid operating costs. Summary of the Invention

[0003] In view of this, the present invention provides a power distribution method, device, storage medium and electronic equipment for an integrated photovoltaic, energy storage and charging DC microgrid, the main purpose of which is to solve the problem of random power distribution in the current integrated photovoltaic, energy storage and charging DC microgrid, which leads to a large power loss rate.

[0004] To address the aforementioned problems, this application provides a power allocation method for an integrated photovoltaic-storage-charging DC microgrid, comprising:

[0005] The basic constraints for constructing a target DC microgrid integrating photovoltaic, energy storage and charging, and the target constraints corresponding to different operating state modes of the target DC microgrid;

[0006] Construct a total loss target function for power allocation to the target DC microgrid, wherein the objects to be allocated power include energy storage modules and charging pile modules;

[0007] Based on the basic constraints and the target constraints, the equal incremental rate criterion is adopted, and the total power loss of the target photovoltaic-storage-charging integrated DC microgrid architecture is minimized as the objective. The objective function of the total power loss is solved to obtain the allocated power of the target power distribution object corresponding to different operating state modes.

[0008] Optionally, the basic constraints include instantaneous balance of positive and negative power on the DC bus, constant total power and power direction at the grid connection point, no control over changes in photovoltaic power generation over time, adjustable energy storage power and power direction, and adjustable charging module power.

[0009] Optionally, the target constraints corresponding to the different operating state modes of constructing the target DC microgrid specifically include:

[0010] When the operating state mode is such that the sum of the grid-connected power and the photovoltaic power of the target DC microgrid is greater than the charging pile load power, the target constraint conditions are constructed based on the first sum of the charging pile load power and the energy storage power, and the second sum of the grid-connected power and the photovoltaic power.

[0011] When the operating state mode is such that the sum of the grid-connected power of the target DC microgrid and the photovoltaic power generation is less than the load power of the charging pile, the target constraint condition is constructed based on the first difference between the load power of the charging pile and the energy storage power and the second sum.

[0012] When the operating state mode is such that the sum of the grid-connected power of the target DC microgrid and the load power of the charging pile is less than the photovoltaic power generation, the target constraint condition is constructed based on the first sum and the second difference between the grid-connected power and the photovoltaic power generation.

[0013] When the operating state mode is such that the sum of the grid-connected power of the target DC microgrid and the load power of the charging pile is greater than the photovoltaic power generation, the target constraint conditions are constructed based on the third difference between the energy storage power and the load power of the charging pile and the second difference.

[0014] Optionally, the construction of the total loss power objective function for power allocation of the target DC microgrid specifically includes:

[0015] Obtain the first curve of load rate versus conversion efficiency for each of the power allocation objects;

[0016] Based on the load rate conversion efficiency data, a second curve of load power versus loss power of the object to be allocated power is obtained;

[0017] Based on the second curve, a function is constructed to obtain a first function of the load power and loss power of the object to be power allocated.

[0018] The total power loss objective function is obtained by performing addition operations on each of the first functions.

[0019] Optionally, based on the basic constraints and the target constraints, the method employs the constant incremental rate criterion, with the goal of minimizing the total power loss of the target photovoltaic-storage-charging integrated DC microgrid architecture, and solves the objective function for the total power loss to obtain the allocated power of the target power distribution object corresponding to different operating states. Specifically, this includes:

[0020] By differentiating each of the first functions, the load power loss incremental power rate function of the power allocation object is obtained.

[0021] Based on the basic constraints, the target constraints corresponding to different operating state modes, and the incremental power loss rate function of each load, the total power loss objective function is solved using a binary iterative algorithm to obtain the allocated power of the power allocation object corresponding to different operating state modes.

[0022] Optionally, the step of solving the total power loss objective function using a binary iterative algorithm based on the basic constraints, the target constraints corresponding to different operating state modes, and the incremental power loss rate function of each load power mode, to obtain the allocated power of the power allocation object corresponding to different operating state modes, specifically includes:

[0023] Step 1: Within the constraints of the basic constraints and the target constraints, initialize the incremental rate interval to obtain the lower bound and upper bound of the initial incremental rate interval.

[0024] Step 2: Calculate the mean value based on the lower bound of the initial growth rate interval and the upper bound of the initial growth rate interval to obtain the initial micro-growth rate;

[0025] Step 3: Perform calculations based on the initial incremental rate and the load power loss incremental rate function to obtain the initial allocated power value for each of the objects to be allocated power, corresponding to the initial incremental rate.

[0026] Step 4: Perform addition operations on the initial allocated power values ​​to obtain the initial total load power;

[0027] Step 5: When the absolute value of the difference between the initial total load power and the total load power limit is less than a preset threshold, proceed to step 7; when the absolute value of the difference between the initial total load power and the total load power limit is greater than the preset threshold, update the initial incremental rate interval boundary value based on the initial incremental rate.

[0028] Step Six: Based on the updated initial increment interval limit value, repeat steps Two to Five to update the initial allocation power value of each of the objects to be allocated power, to obtain the current allocation power value, and update the initial total load power to obtain the current total load power value; iterate in a loop until the absolute value of the difference between the current total load power and the total load power limit value is less than a preset threshold, then determine the current allocation power value as the allocation power of the object to be allocated power.

[0029] Step 7: Determine the initial or current allocated power value as the allocated power for the object to be allocated power.

[0030] To address the aforementioned problems, this application provides a photovoltaic-storage-charging integrated DC microgrid power distribution device, comprising:

[0031] The constraint construction module is used to construct the basic constraint conditions of the target DC microgrid integrating photovoltaic, energy storage and charging, as well as the target constraint conditions corresponding to different operating state modes of the target DC microgrid.

[0032] The objective function construction module is used to construct the total loss power objective function for power allocation to the target DC microgrid, wherein the objects to be allocated power include energy storage modules and charging pile modules.

[0033] The solution module is used to solve the total power loss objective function based on the basic constraints and the target constraints, using the constant incremental rate criterion and taking the minimum total power loss of the target photovoltaic-storage-charging integrated DC microgrid architecture as the objective, to obtain the allocated power of the target power distribution object corresponding to different operating state modes.

[0034] Optionally, the constraint construction module is specifically used to include the following basic constraints: the positive and negative power of the DC bus reaches instantaneous balance; the total power value and power direction at the grid connection point are constant; the photovoltaic power generation power changes over time without control; the energy storage power value and power direction are adjustable; and the charging module power value is adjustable.

[0035] To address the aforementioned problems, this application provides a storage medium storing a computer program, which, when executed by a processor, implements the steps of the aforementioned photovoltaic-storage-charging integrated DC microgrid power distribution method.

[0036] To address the aforementioned problems, this application provides an electronic device, comprising at least a memory and a processor. The memory stores a computer program, and the processor, when executing the computer program in the memory, implements the steps of the aforementioned photovoltaic-storage-charging integrated DC microgrid power distribution method.

[0037] The beneficial effects of this application are as follows: This application constructs basic constraints for a target DC microgrid integrating photovoltaic, energy storage, and charging, as well as target constraints corresponding to different operating states of the target DC microgrid. With the goal of minimizing the total power loss of the power allocation targets within the target DC microgrid architecture, a total power loss objective function is constructed for power allocation to the target DC microgrid. The power allocation targets include energy storage modules and charging pile modules. Based on the basic constraints and the target constraints, the total power loss objective function is solved using a constant incremental rate criterion to obtain the allocated power for the power allocation targets corresponding to different operating states. The method of this application can optimize and obtain more accurate allocated power for the power allocation targets, thereby achieving the lowest total power loss, reducing the loss rate, and saving electrical energy.

[0038] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0039] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0040] Figure 1 A schematic flowchart of a power distribution method for an integrated photovoltaic, energy storage, and charging DC microgrid provided in an embodiment of this application is shown.

[0041] Figure 2 A schematic flowchart of a power distribution method for an integrated photovoltaic, energy storage, and charging DC microgrid, according to another embodiment of this application, is shown.

[0042] Figure 3(a) shows a schematic diagram of the load rate-conversion efficiency curve of the 20kW charging pile module of this application at a voltage of 750V;

[0043] Figure 3(b) shows a schematic diagram of the load rate-conversion efficiency curve of the 40kW charging pile module of this application at a voltage of 750V;

[0044] Figure 3(c) shows a schematic diagram of the load rate-conversion efficiency curve of a 20kW energy storage module under 750V voltage according to an embodiment of this application;

[0045] Figure 4This invention illustrates a schematic diagram of load distribution among multiple modules in a charging station according to equal loss power and equal incremental rate, based on an embodiment of this application.

[0046] Figure 5 A structural block diagram of an integrated photovoltaic, energy storage, and charging DC microgrid power distribution device according to another embodiment of this application is shown. Detailed Implementation

[0047] Various embodiments and features of this application are described herein with reference to the accompanying drawings.

[0048] It should be understood that various modifications can be made to the embodiments described herein. Therefore, the above description should not be considered as limiting, but merely as an example of embodiments. Other modifications within the scope and spirit of this application will be apparent to those skilled in the art.

[0049] The accompanying drawings, which are included in and form part of this specification, illustrate embodiments of the present application and, together with the general description of the present application given above and the detailed description of the embodiments given below, serve to explain the principles of the present application.

[0050] These and other features of this application will become apparent from the following description of preferred forms of embodiments given as non-limiting examples, with reference to the accompanying drawings.

[0051] It should also be understood that although this application has been described with reference to some specific examples, those skilled in the art can certainly implement many other equivalent forms of this application.

[0052] The above and other aspects, features and advantages of this application will become more apparent when taken in conjunction with the accompanying drawings and in view of the following detailed description.

[0053] Specific embodiments of this application are described thereafter with reference to the accompanying drawings; however, it should be understood that the claimed embodiments are merely examples of this application, which may be implemented in various ways. Well-known and / or repeated functions and structures are not described in detail to avoid unnecessary or redundant details that would obscure this application. Therefore, the specific structural and functional details claimed herein are not intended to be limiting, but merely serve as the basis and representative basis for the claims to teach those skilled in the art to use this application in a variety of substantially any suitable detailed structures.

[0054] This specification may use the phrases “in one embodiment,” “in another embodiment,” “in yet another embodiment,” or “in other embodiments,” all of which may refer to one or more of the same or different embodiments according to this application.

[0055] This application provides a power distribution method for an integrated photovoltaic, energy storage, and charging DC microgrid, such as... Figure 1Shown, including:

[0056] Step S101: Construct the basic constraints of the target DC microgrid integrating photovoltaic, energy storage and charging, and construct the target constraints corresponding to different operating state modes of the target DC microgrid;

[0057] In the specific implementation process of this step, the basic constraints include instantaneous balance of positive and negative power on the DC bus, constant total power and power direction at the grid connection point, no control over the time variation of photovoltaic power generation, adjustable energy storage power and power direction, and adjustable charging module power. Different operating state modes include a first state mode when the grid connection point power acts as a microgrid power source and a second state mode when the grid connection point power acts as a microgrid load. The first state mode includes a first operating state mode where the sum of the grid connection point power and the photovoltaic power generation is greater than the charging pile load power; and a second operating state mode where the sum of the grid connection point power and the photovoltaic power generation is less than the charging pile load power. The second state mode includes a third operating state mode where the sum of the grid connection point power and the charging pile load power of the target DC microgrid is less than the photovoltaic power generation, and a fourth operating state mode where the sum of the grid connection point power and the charging pile load power is greater than the photovoltaic power generation. Target constraints are constructed for the first, second, third, and fourth operating state modes respectively.

[0058] Step S102: With the goal of minimizing the total power loss of the target photovoltaic-storage-charging integrated DC microgrid architecture, construct a total power loss objective function for power allocation optimization of the target DC microgrid. The target power loss objects include energy storage modules and charging pile modules.

[0059] In this step, the first curve of load rate and conversion efficiency of each of the objects to be allocated power is obtained; the load rate and conversion efficiency data are processed to obtain the second curve of load power and loss power of the objects to be allocated power; a function is constructed based on the second curve to obtain the first function of load power and loss power of the objects to be allocated power; and the first function is added to each of the first functions to obtain the target function of total loss power.

[0060] Step S103: Based on the basic constraints and the target constraints, the objective function of the total power loss is solved using the constant incremental rate criterion to obtain the allocated power of the power to be allocated object corresponding to different operating state modes.

[0061] In this step, the derivative of each of the first functions is calculated to obtain the load power loss incremental rate function of the object to be allocated power; based on the basic constraints, the target constraints corresponding to different operating state modes, and the load power loss incremental rate function, the total power loss objective function is solved using a binary iterative algorithm to obtain the allocated power of the object to be allocated corresponding to different operating state modes.

[0062] This application constructs basic constraints for a target DC microgrid integrating photovoltaic, energy storage, and charging, as well as target constraints corresponding to different operating modes of the target DC microgrid. With the goal of minimizing the total power loss of the power allocation targets within the target DC microgrid architecture, a total power loss objective function is constructed for power allocation to the target DC microgrid. The power allocation targets include energy storage modules and charging pile modules. Based on the basic and target constraints, the total power loss objective function is solved using a constant incremental rate criterion to obtain the allocated power for each power allocation target under different operating modes. This method can optimize and obtain a more accurate allocated power for the power allocation targets, thereby achieving the lowest total power loss, reducing the loss rate, and saving electrical energy.

[0063] Another embodiment of this application provides a different power distribution method for an integrated photovoltaic, energy storage, and charging DC microgrid, such as... Figure 2 Shown, including:

[0064] Step S201: Construct the basic constraints for the integrated photovoltaic, energy storage, and charging target DC microgrid;

[0065] In the specific implementation process of this step, when the total power and direction at the grid connection point of the high-efficiency photovoltaic-storage-charging integrated DC microgrid are constant, the basic constraints include the instantaneous balance of positive and negative power of the DC bus, the constant total power value and power direction at the grid connection point, the uncontrolled change of photovoltaic power generation over time, the adjustable energy storage power value and power direction, and the adjustable charging module power value.

[0066] Step S202: Construct the target constraints corresponding to different operating state modes of the target DC microgrid;

[0067] In the specific implementation process of this step, when the operating state mode is the first operating state mode, that is, when the sum of the grid-connected power and photovoltaic power of the target DC microgrid is greater than the charging pile load power, constraint conditions are constructed based on the first sum of the charging pile load power and energy storage power, and the second sum of the grid-connected power and photovoltaic power, to obtain the target constraint conditions; when the power at the grid-connected point of the target DC microgrid is constant (including power value and power direction), its power value is P. AFE When the photovoltaic module is in working mode and its operation is uncontrollable, while the energy storage module and charging pile module are in controllable mode, and the grid-connected power is used as the microgrid power source, the sum of the grid-connected power and the photovoltaic power generation of the target DC microgrid is greater than the charging pile load power, i.e., P... AFE +P PV >P EV When the photovoltaic power generation is large, energy storage can operate as a load to maintain the instantaneous balance of positive and negative power on the DC bus, that is, to ensure that P AFE +P PV =P EV +P ESS Among them, P AFE P is the power at the grid connection point. PV For photovoltaic power generation, P EV For the charging pile load power, P ESS This represents the energy storage capacity; therefore, at a certain moment during microgrid operation, the load P of the charging pile module can be obtained. EV With energy storage module load P ESS The first sum is a definite value P c This refers to the total load power limit; the photovoltaic power generation varies over time and is not controlled. In this scenario, the photovoltaic power generation can be considered a fixed value at a certain moment. During actual operation, this value can be read from the photovoltaic system in real time. At this time, the first sum is equal to the grid-connected power P. AFE With photovoltaic power generation P PV The second sum is denoted as P. C =P AFE +P PV When the operating state mode is such that the sum of the grid-connected power and photovoltaic power of the target DC microgrid is greater than the load power of the charging pile, the mathematical expression of the target constraint is as shown in the following formula (1):

[0068] P EV +P ESS =P C (1)

[0069] When the operating state mode is the second operating state mode, that is, when the sum of the grid-connected power of the target DC microgrid and the photovoltaic power generation is less than the charging pile load power, the target constraint condition is constructed based on the first difference between the charging pile load power and the energy storage power and the second sum; that is, when the charging pile power is large and the photovoltaic power generation is small, the energy storage can be discharged as a power source to maintain the instantaneous balance of positive and negative power of the DC bus, that is, to make P AFE +P PV +P ESS =P EV Or P AFE +P PV =P EV -P ESS Therefore, at a certain moment during the operation of the microgrid, the load P of the charging pile module can be obtained. EV With energy storage module load P ESS The first difference is a definite value P c , that is, the total load power limit; the photovoltaic power generation changes with time and is not controlled. In this scenario, the photovoltaic power generation can be regarded as the actual operating value at a certain moment. This value can be read from the photovoltaic system in real time. When the operating state mode is that the sum of the grid connection point power of the target DC microgrid and the photovoltaic power generation is less than the load power of the charging pile, the mathematical expression of the target constraint can be expressed by the following formula (2):

[0070] P EV -P ESS =P C (2)

[0071] When the operating state mode is the third operating state mode, that is, when the sum of the grid-connected power of the target DC microgrid and the load power of the charging pile is less than the photovoltaic power generation, based on the first sum and the grid-connected power P... AFE With the photovoltaic power generation P PV The second difference is used to construct the constraint conditions, resulting in the target constraint conditions; when the grid connection point power is used as the microgrid load, that is, the microgrid acts as a power source to supply power to the grid, and P AFE +P EV >P PV When the photovoltaic power generation is high and the charging pile power is low, the energy storage can discharge and operate as a load to maintain the instantaneous balance of positive and negative power on the DC bus, that is, to ensure that P AFE +P EV +P ESS =P PV Or P AFE -P PV =-(P ESS +P EV ), PAFE -P PV For P c That is, the total load power limit. Therefore, at a certain moment during the operation of the microgrid, the first sum of the load of the charging pile module and the load of the energy storage module is a certain value, that is, the total load power limit. When the operating state mode is that the sum of the grid connection point power of the target DC microgrid and the load power of the charging pile is less than the photovoltaic power generation, the mathematical expression of the target constraint can be expressed by the following formula (3):

[0072] -(P ESS +P EV ) = P C (3)

[0073] When the operating state mode is the fourth operating state mode, that is, when the sum of the grid-connected power of the target DC microgrid and the load power of the charging pile is greater than the photovoltaic power generation, the target constraint condition is constructed based on the third difference and the second difference between the energy storage power and the load power of the charging pile. That is, when the photovoltaic power generation is relatively small and the charging pile power is relatively large, the energy storage can discharge to operate as a power source to maintain the instantaneous balance of positive and negative power on the DC bus, i.e., to ensure that P... AFE +P EV =P PV +P ESS Or P AFE -P PV =P ESS -P EV , P AFE -P PV For P C Therefore, at a certain moment during the operation of the microgrid, the difference between the load of the charging pile module and the load of the energy storage module is a certain value. The target constraint under this operating condition can be expressed by the following formula (4):

[0074] P ESS -P EV =P C (4)

[0075] Step S203: Obtain the first curve of load rate versus conversion efficiency for each of the power allocation objects;

[0076] In the specific implementation process of this step, the first curve of load rate and conversion efficiency of each power allocation object can be obtained by viewing historical operation data in real time. Each power allocation object will have a different rated output power. Power allocation objects with the same rated output power but different power supply circuits may operate under different output voltages. The load rate-conversion efficiency curve of the power allocation object will be different due to different rated output power and different output voltage. That is, the rated power and the output voltage together correspond to a load rate-conversion efficiency curve. As shown in Figure 3(a), the load rate-conversion efficiency curve of the 20kW charging pile module under 750V voltage is shown in Figure 3(b); the load rate-conversion efficiency curve of the 40kW charging pile module under 750V voltage is shown in Figure 3(c); the load rate-conversion efficiency curve of the 20kW energy storage module under 750V voltage is shown in Figure 3(c).

[0077] Step S204: Based on the load rate conversion efficiency data, perform calculations to obtain a second curve of the load power and loss power of the object to be allocated power;

[0078] In the specific implementation process of this step, the above load rate-conversion rate curve data is converted into a second curve of load power (kW)-loss power (kW) according to the physical meaning. The mathematical expression of the conversion formula is as follows (5):

[0079] P Δ =(P i / R c )*(1-R c (5)

[0080] Among them, P i =R L *P e ;P i R is the load power (kW); L For load factor; P e P is the module's rated output power. Δ Power loss (kW); R c This represents the conversion rate.

[0081] Step S205: Based on the second curve, construct a function to obtain a first function of the load power and loss power of the object to be power-allocated;

[0082] In the specific implementation process of this step, the load power-loss power function is named F(x); a mathematical interpolation algorithm is used to fit a fifth-order polynomial function using the module load power (kW)-loss power (kW) data, with parameters accurate to 12 decimal places and the error R square value less than 0.999, meeting the requirements of practical application. The fitting functions of the load power-loss power increment rate of modules with different rated power and different working voltage are uniformly numbered and called the first function of different types of modules. There are N types of load power-loss power modules, each corresponding to the first function of N load power-loss power, and the mathematical expression of the first function is as shown in the following formula (6):

[0083]

[0084] Among them, F 1(x1) -F N(xN) x represents power loss (kW); x represents load power (kW); a1-a N b1-b N c1 - c N d1-d N and e1-e N f1-f N Represents the coefficients of each polynomial.

[0085] Step S206: Perform addition operations on each of the first functions to obtain the total power loss objective function;

[0086] In the specific implementation process of this step, the first functions are added together to obtain the target function; the mathematical expression of the total power loss target function is as follows (7):

[0087]

[0088] Step S207: Based on the basic constraints and the target constraints, the equal incremental rate criterion is adopted, and the total loss power of the target photovoltaic-storage-charging integrated DC microgrid architecture is minimized as the objective. The objective function of the total loss power is solved to obtain the allocated power of the target power allocation object corresponding to different operating state modes.

[0089] In the specific implementation of this step, the rigorous proof of the constant incremental rate criterion is obtained through mathematical derivation: Suppose there are n objects to be allocated power, each bearing a load of P1, P2, ... P... n (kW), and the corresponding module power loss is F1, F2...F n (kW), then the mathematical expression for the total module power loss is as shown in the following formula (8):

[0090]

[0091] The total load power P ∑f The mathematical expression for is shown in the following formula (9):

[0092]

[0093] To ensure that the module's total output meets the load power limit P L Under the condition that F = F, the total power loss is minimized, even if F = F min At this point, the Lagrange multiplier rule can be applied to solve the problem. The mathematical expression of the Lagrange equation is shown in the following formula (10):

[0094]

[0095] Where F is the total module power loss; λ is the Lagrange multiplier; For constraint functions.

[0096] The power balance condition is the corresponding constraint condition, as shown in the following formula (11):

[0097] P1+P2+…P n -P L =0 (11)

[0098] Alternatively, the power balance condition is the corresponding constraint condition as shown in the following formula (12):

[0099]

[0100] Therefore, the condition for minimizing the total module power loss is that the partial derivative of equation (8) with respect to power is zero, as shown in equation (13) below:

[0101]

[0102] Because P L Since the output power of the modules is constant and independent of each other, the following formulas (14)-(17) can be derived:

[0103]

[0104]

[0105] Right now

[0106]

[0107] Each module operates independently, so the power loss of each module is only related to its own output power. Therefore, the above formula can be written as the following mathematical expression (18).

[0108]

[0109] Therefore, we can obtain formula (19):

[0110]

[0111] That is: b1 = b2 = ... = b n =λ;

[0112] Therefore, the criterion for economically optimizing the power distribution of modules operating in parallel in a charging station is that the incremental rates b1, b2, ..., b of each module are... n They should be equal, and equal to the incremental rate λ of the entire station. For example... Figure 4 The diagram shows the load distribution among multiple modules in a charging station based on equal loss power and equal incremental rate. In actual operation, the values ​​of the load power-loss power incremental rate curves of the modules participating in power distribution optimization in the charging station can be pre-formed into a table and stored in a computer. When performing power distribution optimization calculations, the load power value corresponding to a certain loss power incremental rate of a certain module can be directly obtained by looking up the table. This can speed up the calculation and adapt to the time scale requirements of on-site operation.

[0113] Differentiating each of the first functions yields the load power loss incremental rate function of the object to be power allocated; the mathematical expression of the load power loss incremental rate function is shown in the following formula (20):

[0114]

[0115] in, Represents the incremental rate of power loss; x represents the load power (kW); a1-a N b1-b N c1 - c N d1-d N and e1 - e N Represents the coefficients of each polynomial.

[0116] According to formula (20), there are N different types of module load power (kW) - loss power incremental rate functions, numbered B1, B2, ... B N The charging station has the following N types of load power-loss power incremental rate functions for the objects to be allocated power, and the mathematical expression is shown in the following formula (21):

[0117]

[0118] Where, x N The load power of the object to be power allocated; B N This is the load power - loss power incremental rate function. Each type of load power (kW) - loss power incremental rate function has Mn power supply circuits to be allocated power; that is, the first type of load power (kW) - loss power incremental rate function has M1 power supply circuits, the second type of load power (kW) - loss power incremental rate function has M2 power supply circuits, and the nth type of load power (kW) - loss power incremental rate function has Mn power supply circuits.

[0119] Based on the aforementioned basic constraints, the target constraints corresponding to different operating state modes, and the incremental power loss rate function of each load, a binary iterative algorithm is used to solve the total power loss objective function to obtain the allocated power for the power allocation objects corresponding to different operating state modes. Specifically, the steps include:

[0120] Step 1: Within the constraints of the basic constraints and the target constraints, initialize the incremental rate interval to obtain the lower bound and upper bound of the initial incremental rate interval; first, take two values ​​as the lower bound B of the initial incremental rate interval. 11 The upper bound of the initial incremental rate interval, B 21 (The first subscript of the numerical interval boundary indicates the numerical value, 1 represents the smaller value, and 2 represents the larger value; the second subscript of the numerical interval boundary indicates the iteration number), which serves as the numerical interval of the incremental rate for the first iteration, and satisfies the following condition (22):

[0121] P Σ11 <P c <P Σ21 (22)P Σ11 P Σ21 The incremental rate B 11 B 21 The corresponding total load power, P c This is the limit value for total load power.

[0122] Step 2: Perform mean calculation based on the lower bound of the initial growth rate interval and the upper bound of the initial growth rate interval to obtain the initial micro-growth rate; the mathematical expression for the mean calculation can be expressed by the following formula (23):

[0123] b1=(B 11 +B 21 ) / 2(23)

[0124] Where b1 is the initial incremental rate calculated in the first iteration.

[0125] Step 3: Perform calculations based on the initial incremental rate and the load power loss incremental rate function to obtain the initial allocated power value for each of the objects to be allocated power, corresponding to the initial incremental rate.

[0126] Based on the incremental rate b1, the total load power P corresponding to the incremental rate can be obtained through the load power-loss power incremental rate fitting function. Σz Based on the load power-loss power increment rate fitting function for different types of power supply modules, the load power x corresponding to the initial increment rate b1 for different types of power supply modules is calculated. i Then calculate the load power P of the same type of module. Σi The mathematical expression for load power can be expressed by the following formula (24):

[0127] P Σn =x n *M n (twenty four)

[0128] Among them, M n The number of power supply circuits for objects of the same type to be allocated power is determined; in order to obtain the initial allocated power value for each of the objects to be allocated power corresponding to the initial incremental rate.

[0129] Step 4: Perform addition operations on the initial allocated power values ​​to obtain the initial total load power;

[0130] The loads of the objects to be power-allocated are summed, and the mathematical expression is as shown in formula (25):

[0131] P Σz =P Σ1 +P Σ2 +……+P Σn (25)

[0132] Get and b n The corresponding total load power P Σz To obtain the initial total allocated power value for each of the objects to be allocated power, corresponding to the initial incremental rate;

[0133] Step 5: When the absolute value of the difference between the initial total load power and the total load power limit is less than a preset threshold, proceed to Step 7; when the absolute value of the difference between the initial total load power and the total load power limit is greater than the preset threshold, update the initial incremental rate interval boundary value based on the initial incremental rate; when the absolute value of the difference between the initial total load power and the total load power limit is less than the preset threshold, determine the initial allocated power value as the allocated power for the object to be allocated. When the absolute value of the difference between the initial total load power and the total load power limit is greater than the preset threshold, a second iteration is required. The preset threshold can be 0.5kW, and the preset threshold can be set according to actual needs. The initial incremental rate interval boundary value is updated based on the initial incremental rate to obtain the incremental rate interval for the second iteration. Specifically, when the difference between the initial total load power and the total load power limit is greater than zero, the upper boundary value of the initial incremental rate interval is updated based on the initial incremental rate, that is, the initial incremental rate b1 replaces the upper boundary value of the initial incremental rate interval to form the incremental rate value interval for the second iteration round [B]. 12 B 22 At this time, B 12 =B 11 B 22 =b1; When the difference between the initial total load power and the total load power limit is less than zero, the lower bound of the initial increment rate interval is updated based on the initial increment rate to obtain the increment rate interval for the second iteration, that is, the initial increment rate b1 replaces the lower bound of the initial increment rate interval to form the increment rate value interval for this iteration round [B 12 B 22 At this time, B 12 =b1,B 22 =B 21 ;

[0134] Step 6: Based on the updated lower bound of the initial increment interval, repeat steps 2 to 5 to update the initial allocation power value of each of the objects to be allocated power, to obtain the current allocation power value, and update the initial total load power, to obtain the current total load power value; iterate in a loop until the absolute value of the difference between the current total load power and the total load power limit is less than a preset threshold, then determine the current allocation power value as the allocation power of the object to be allocated power.

[0135] Step 7: Determine the initial or current allocated power value as the allocated power for the object to be allocated power.

[0136] This application constructs basic constraints for a target DC microgrid integrating photovoltaic, energy storage, and charging, as well as target constraints corresponding to different operating modes of the target DC microgrid. With the goal of minimizing the total power loss of the power allocation targets within the target DC microgrid architecture, a total power loss objective function is constructed to optimize power allocation for the target DC microgrid. The power allocation targets include energy storage modules and charging pile modules. Based on the basic and target constraints, and using a constant incremental rate criterion, the total power loss objective function is solved to obtain the allocated power for each power allocation target under different operating modes. This method can optimize and obtain more accurate allocated power for the power allocation targets, reduce the loss rate, achieve the lowest total power loss, and save energy.

[0137] Another embodiment of this application provides a power distribution device for an integrated photovoltaic, energy storage, and charging DC microgrid, such as... Figure 5 As shown, it includes:

[0138] Constraint construction module 1 is used to construct the basic constraints of the target DC microgrid integrating photovoltaic, energy storage and charging, as well as the target constraints corresponding to different operating state modes of the target DC microgrid.

[0139] Objective function construction module 2 is used to construct a total loss power objective function for power allocation optimization of the target DC microgrid, wherein the objects to be allocated power include energy storage modules and charging pile modules;

[0140] Solution module 3 is used to solve the total power loss objective function based on the basic constraints and the target constraints, using the constant incremental rate criterion and with the goal of minimizing the total power loss of the target photovoltaic-storage-charging integrated DC microgrid architecture, to obtain the allocated power of the target power distribution object corresponding to different operating state modes.

[0141] In the specific implementation process, the constraint construction module 1 is specifically used for: the basic constraint conditions include the instantaneous balance of positive and negative power of DC bus, the constant total power value and power direction at the grid connection point, the uncontrolled change of photovoltaic power generation power over time, the adjustable power value and power direction of energy storage, and the adjustable power value of charging module.

[0142] In specific implementation, the constraint construction module 1 is further used to: construct constraint conditions based on the first operating state mode (i.e., the sum of the grid-connected power and photovoltaic power of the target DC microgrid is greater than the charging pile load power) to obtain target constraint conditions; and construct constraint conditions based on the first sum of the charging pile load power and energy storage power, and the second sum of the grid-connected power and photovoltaic power, when the operating state mode is the second operating state mode (i.e., the sum of the grid-connected power and photovoltaic power of the target DC microgrid is less than the charging pile load power) based on the first difference between the charging pile load power and energy storage power, and the second sum. Conditions are constructed to obtain target constraints. When the operating state mode is the third operating state mode, that is, when the sum of the grid-connected power of the target DC microgrid and the load power of the charging pile is less than the photovoltaic power generation, constraints are constructed based on the first sum and the second difference between the grid-connected power and the photovoltaic power generation to obtain target constraints. When the operating state mode is the fourth operating state mode, that is, when the sum of the grid-connected power of the target DC microgrid and the load power of the charging pile is greater than the photovoltaic power generation, constraints are constructed based on the third difference between the energy storage power and the load power of the charging pile and the second difference to obtain target constraints.

[0143] In the specific implementation process, the total power loss target function construction module 2 is specifically used to: obtain the first curve of load rate and conversion efficiency of each of the objects to be allocated power; perform calculation processing based on the load rate and conversion efficiency data to obtain the second curve of load power and power loss of the objects to be allocated power; construct a function based on the second curve to obtain the first function of load power and power loss of the objects to be allocated power; and perform addition operations on each of the first functions to obtain the total power loss target function.

[0144] In the specific implementation process, the solution module 3 is specifically used to: differentiate each of the first functions to obtain the load power loss incremental rate function of the object to be allocated power; and solve the total power loss objective function using a binary iterative algorithm based on the basic constraints, the target constraints corresponding to different operating state modes, and the load power loss incremental rate function to obtain the allocated power of the object to be allocated corresponding to different operating state modes.

[0145] In the specific implementation process, the solution module 3 is further used for: Step 1, within the constraint range of the basic constraint condition and the target constraint condition, initializing the incremental rate interval to obtain the lower bound value and the upper bound value of the initial incremental rate interval; Step 2, performing mean calculation processing based on the lower bound value and the initial incremental rate interval to obtain the initial incremental rate; Step 3, performing calculation processing based on the initial incremental rate and the load power loss power incremental rate function to obtain the initial allocation power value of each of the power allocation objects corresponding to the initial incremental rate; Step 4, performing addition operation processing on each of the initial allocation power values ​​to obtain the initial total load power; Step 5, when the absolute value of the difference between the initial total load power and the total load power limit value is less than a preset threshold, Step 7: When the absolute value of the difference between the initial total load power and the total load power limit is greater than a preset threshold, update the initial incremental rate interval boundary value based on the initial incremental rate; Step 6: Based on the updated initial incremental rate interval boundary value, repeat steps 2 to 5 to update the initial allocation power value of each of the objects to be allocated power, to obtain the current allocation power value, and update the initial total load power, to obtain the current total load power value; iterate in a loop until the absolute value of the difference between the current total load power and the total load power limit is less than a preset threshold, then determine the current allocation power value as the allocation power of the object to be allocated power; Step 7: Determine the initial or current allocation power value as the allocation power of the object to be allocated power.

[0146] This application constructs basic constraints for a target DC microgrid integrating photovoltaic, energy storage, and charging, as well as target constraints corresponding to different operating modes of the target DC microgrid. With the goal of minimizing the total power loss of the power allocation targets within the target DC microgrid architecture (including energy storage modules and charging pile modules), a total power loss objective function is constructed for power allocation to the target DC microgrid. Based on the basic and target constraints, the total power loss objective function is solved using a constant incremental rate criterion to obtain the allocated power for each power allocation target under different operating modes. This method can optimize and obtain more accurate allocated power for the power allocation targets, reduce the loss rate, achieve the lowest total power loss, and save electrical energy.

[0147] Another embodiment of this application provides a storage medium storing a computer program, which, when executed by a processor, implements the following method steps:

[0148] Step 1: Construct the basic constraints of the target DC microgrid integrating photovoltaic, energy storage and charging, and construct the target constraints corresponding to different operating state modes of the target DC microgrid.

[0149] Step 2: Construct a total loss target function for power allocation to the target DC microgrid, wherein the objects to be allocated power include energy storage modules and charging pile modules;

[0150] Step 3: Based on the basic constraints and the target constraints, the equal incremental rate criterion is adopted to minimize the total power loss of the target photovoltaic-storage-charging integrated DC microgrid architecture. The objective function of the total power loss is solved to obtain the allocated power of the target power distribution object corresponding to different operating state modes.

[0151] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0152] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0153] The specific implementation process of the above method steps can be found in the embodiment of the above arbitrary photovoltaic-storage-charging integrated DC microgrid power allocation method, which will not be repeated here.

[0154] This application constructs basic constraints for a target DC microgrid integrating photovoltaic, energy storage, and charging, as well as target constraints corresponding to different operating modes of the target DC microgrid. With the goal of minimizing the total power loss of the power allocation targets within the target DC microgrid architecture (including energy storage modules and charging pile modules), a total power loss objective function is constructed for power allocation to the target DC microgrid. Based on the basic and target constraints, the total power loss objective function is solved using a constant incremental rate criterion to obtain the allocated power for each power allocation target under different operating modes. This method can optimize and obtain more accurate allocated power for the power allocation targets, reduce the loss rate, achieve the lowest total power loss, and save energy.

[0155] Another embodiment of this application provides an electronic device, which can be a server. The electronic device includes a processor, a memory, a network interface, and a database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external clients via a network connection. When the processor executes the program of the electronic device, it implements the functions or steps of a power distribution method for an integrated photovoltaic, energy storage, and charging DC microgrid on the server side.

[0156] In one embodiment, an electronic device is provided, which can be a client. The electronic device includes a processor, memory, a network interface, a display screen, and an input device connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with an external server via a network connection. When the program is executed by the processor, it implements the functions or steps of a power distribution method for an integrated photovoltaic-storage-charging DC microgrid on the client side.

[0157] Another embodiment of this application provides an electronic device, including at least a memory and a processor. The memory stores a computer program, and the processor, when executing the computer program in the memory, performs the following method steps:

[0158] Step 1: Construct the basic constraints of the target DC microgrid integrating photovoltaic, energy storage and charging, and construct the target constraints corresponding to different operating state modes of the target DC microgrid.

[0159] Step 2: Construct a total loss target function for power allocation to the target DC microgrid, wherein the objects to be allocated power include energy storage modules and charging pile modules;

[0160] Step 3: Based on the basic constraints and the target constraints, the equal incremental rate criterion is adopted to minimize the total power loss of the target photovoltaic-storage-charging integrated DC microgrid architecture. The objective function of the total power loss is solved to obtain the allocated power of the target power distribution object corresponding to different operating state modes.

[0161] The specific implementation process of the above method steps can be found in the embodiment of the above arbitrary photovoltaic-storage-charging integrated DC microgrid power allocation method, which will not be repeated here.

[0162] The above embodiments are merely exemplary embodiments of this application and are not intended to limit this application. The scope of protection of this application is defined by the claims. Those skilled in the art can make various modifications or equivalent substitutions to this application within its substance and scope of protection, and such modifications or equivalent substitutions should also be considered to fall within the scope of protection of this application.

Claims

1. A power distribution method for an integrated photovoltaic, energy storage, and charging DC microgrid, characterized in that, include: The basic constraints for constructing a target DC microgrid integrating photovoltaic, energy storage and charging, and the target constraints corresponding to different operating state modes of the target DC microgrid; Construct a total loss target function for power allocation to the target DC microgrid, wherein the objects to be allocated power include energy storage modules and charging pile modules; Based on the basic constraints and the target constraints, the equal incremental rate criterion is adopted, and the total power loss of the target photovoltaic-storage-charging integrated DC microgrid architecture is minimized as the objective. The objective function of the total power loss is solved to obtain the allocated power of the target power distribution object corresponding to different operating state modes.

2. The method as described in claim 1, characterized in that, The basic constraints include instantaneous balance of positive and negative power on the DC bus, constant total power and power direction at the grid connection point, no control over changes in photovoltaic power generation over time, adjustable energy storage power and power direction, and adjustable charging module power.

3. The method as described in claim 1, characterized in that, The target constraints corresponding to the different operating state modes of constructing the target DC microgrid specifically include: When the operating state mode is such that the sum of the grid-connected power and the photovoltaic power of the target DC microgrid is greater than the charging pile load power, the target constraint conditions are constructed based on the first sum of the charging pile load power and the energy storage power, and the second sum of the grid-connected power and the photovoltaic power. When the operating state mode is such that the sum of the grid-connected power of the target DC microgrid and the photovoltaic power generation is less than the load power of the charging pile, the target constraint condition is constructed based on the first difference between the load power of the charging pile and the energy storage power and the second sum. When the operating state mode is such that the sum of the grid-connected power of the target DC microgrid and the load power of the charging pile is less than the photovoltaic power generation, the target constraint condition is constructed based on the first sum and the second difference between the grid-connected power and the photovoltaic power generation. When the operating state mode is such that the sum of the grid-connected power of the target DC microgrid and the load power of the charging pile is greater than the photovoltaic power generation, the target constraint conditions are constructed based on the third difference between the energy storage power and the load power of the charging pile and the second difference.

4. The method as described in claim 1, characterized in that, The construction of the total loss power objective function for power allocation of the target DC microgrid specifically includes: Obtain the first curve of load rate versus conversion efficiency for each of the power allocation objects; Based on the load rate conversion efficiency data, a second curve of load power versus loss power of the object to be allocated power is obtained; Based on the second curve, a function is constructed to obtain a first function of the load power and loss power of the object to be power allocated. The total power loss objective function is obtained by performing addition operations on each of the first functions.

5. The method as described in claim 4, characterized in that, Based on the basic constraints and the target constraints, the method employs the constant incremental rate criterion, aiming to minimize the total power loss of the target photovoltaic-storage-charging integrated DC microgrid architecture, and solves the objective function for the total power loss to obtain the allocated power of the target power allocation object corresponding to different operating state modes. Specifically, this includes: By differentiating each of the first functions, the load power loss incremental power rate function of the power allocation object is obtained. Based on the basic constraints, the target constraints corresponding to different operating state modes, and the incremental power loss rate function of each load, the total power loss objective function is solved using a binary iterative algorithm to obtain the allocated power of the power allocation object corresponding to different operating state modes.

6. The method as described in claim 5, characterized in that, The total power loss objective function is solved using a binary iterative algorithm based on the basic constraints, the target constraints corresponding to different operating state modes, and the incremental power loss rate function of each load, to obtain the allocated power of the power allocation object corresponding to different operating state modes, specifically including: Step 1: Within the constraints of the basic constraints and the target constraints, initialize the incremental rate interval to obtain the lower bound and upper bound of the initial incremental rate interval. Step 2: Calculate the mean value based on the lower bound of the initial growth rate interval and the upper bound of the initial growth rate interval to obtain the initial micro-growth rate; Step 3: Perform calculations based on the initial incremental rate and the load power loss incremental rate function to obtain the initial allocated power value for each of the objects to be allocated power, corresponding to the initial incremental rate. Step 4: Perform addition operations on the initial allocated power values ​​to obtain the initial total load power; Step 5: When the absolute value of the difference between the initial total load power and the total load power limit is less than a preset threshold, proceed to step 7; when the absolute value of the difference between the initial total load power and the total load power limit is greater than the preset threshold, update the initial incremental rate interval boundary value based on the initial incremental rate. Step Six: Based on the updated initial increment interval limit value, repeat steps Two to Five to update the initial allocation power value of each of the objects to be allocated power, to obtain the current allocation power value, and update the initial total load power to obtain the current total load power value; iterate in a loop until the absolute value of the difference between the current total load power and the total load power limit value is less than a preset threshold, then determine the current allocation power value as the allocation power of the object to be allocated power. Step 7: Determine the initial or current allocated power value as the allocated power for the object to be allocated power.

7. A power distribution device for an integrated photovoltaic-storage-charging DC microgrid, characterized in that, include: The constraint construction module is used to construct the basic constraint conditions of the target DC microgrid integrating photovoltaic, energy storage and charging, as well as the target constraint conditions corresponding to different operating state modes of the target DC microgrid. The objective function construction module is used to construct the total loss power objective function for power allocation to the target DC microgrid, wherein the objects to be allocated power include energy storage modules and charging pile modules. The solution module is used to solve the total power loss objective function based on the basic constraints and the target constraints, using the constant incremental rate criterion and taking the minimum total power loss of the target photovoltaic-storage-charging integrated DC microgrid architecture as the objective, to obtain the allocated power of the target power distribution object corresponding to different operating state modes.

8. The apparatus as claimed in claim 7, characterized in that, The constraint construction module is specifically used to ensure that the basic constraints include instantaneous balance of positive and negative power of the DC bus, constant total power value and power direction at the grid connection point, no control over changes in photovoltaic power generation over time, adjustable energy storage power value and power direction, and adjustable charging module power value.

9. A storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the steps of the photovoltaic-storage-charging integrated DC microgrid power distribution method according to any one of claims 1-6.

10. An electronic device, characterized in that, It includes at least a memory and a processor, wherein the memory stores a computer program, and the processor, when executing the computer program in the memory, implements the steps of the photovoltaic-storage-charging integrated DC microgrid power distribution method according to any one of claims 1-6.

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