Electric energy distribution method, device, electronic equipment and storage medium

Abstract

The present disclosure provides an electric energy distribution method, device, electronic device and storage medium, which relate to the field of intelligent microgrid technology. The method includes: when the preset power-off condition of the external power grid is met, obtaining the working rate and unit production income information of multiple power distribution factories; constructing an electric energy distribution model according to the working rate and unit production income information of each power distribution factory; iteratively optimizing the electric energy distribution model through the fireworks explosion algorithm of exponential explosion, and obtaining the electric energy distribution result of the microgrid according to the iteratively optimized electric energy distribution model. The present disclosure iteratively optimizes the electric energy distribution model according to the fireworks explosion algorithm of exponential explosion, so as to avoid the high-quality sparks generated by the fireworks explosion from only exploding in a smaller range, thereby falling into a local optimum. Therefore, the present disclosure determines a more optimal distribution plan for the limited electric energy stored in the microgrid, thereby ensuring the maximization of the production efficiency of each factory to be distributed.

Description

Background Art

[0002] Smart microgrid (also called microgrid) is a small power generation and distribution system. Smart microgrid can be connected to the external power grid (also called external power grid) or operate in isolation (i.e. island mode) when the external power grid is out of power to supply power to each power distribution factory. Therefore, smart microgrid technology can further ensure power supply, thereby reducing production interruptions caused by power outages.

[0003] However, when the microgrid supplies power to each power distribution factory, in order to maximize the use of limited power, it is necessary to distribute power according to the actual situation of each power distribution factory. Therefore, there is an urgent need for a power distribution method that can determine a better distribution plan for the limited power stored in the microgrid, so as to ensure the maximum production efficiency of each power distribution factory.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] The present disclosure provides an electric energy distribution method, device, electronic device and storage medium, which can determine a better distribution plan for the limited electric energy stored in the microgrid to a certain extent, thereby ensuring the maximization of the production efficiency of each factory to be distributed.

[0006] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by the practice of the present disclosure.

[0007] According to one aspect of an embodiment of the present disclosure, there is provided a method for distributing electric energy, comprising:

[0008] When a preset power-off condition of the external power grid is met, the working rate and unit production revenue information of multiple power distribution plants are obtained, wherein the external power grid is an external power grid relative to the microgrid;

[0009] According to the working rate and unit production revenue information of each power distribution plant, an electric energy distribution model is constructed, wherein the electric energy distribution model is used to determine the electric energy distribution result of distributing electric energy to each power distribution plant through the microgrid;

[0010] The electric energy distribution model is iteratively optimized through an exponential explosion fireworks explosion algorithm, and the electric energy distribution result of the microgrid is obtained according to the iteratively optimized electric energy distribution model.

[0011] In some embodiments of the present disclosure, the electric energy distribution method provided by the embodiments of the present disclosure further includes: when the preset power-off condition of the external power grid is met, obtaining the power storage amount of the microgrid within a target time period, the target time period being the time when the external power grid is powered off to the time when the external power grid is expected to resume power supply; determining whether the microgrid meets the conditions for electric energy distribution according to the power storage amount of the microgrid within the target time period;

[0012] The obtaining of the working rate and unit production income information of the plurality of plants to be distributed power includes: when the microgrid meets the conditions for power distribution, obtaining the working rate and unit production income information of the plurality of plants to be distributed power.

[0013] In some embodiments of the present disclosure, the electric energy distribution method provided by the embodiments of the present disclosure further includes: obtaining the task amount and task completion time of each power distribution plant; determining the power distribution urgency of each power distribution plant according to the task amount and task completion time of each power distribution plant; determining the power distribution urgency of the power distribution plant whose power distribution urgency is higher than the preset urgency threshold as the target power distribution plant;

[0014] The electric energy distribution method provided by the embodiment of the present disclosure includes: when the preset power-off condition of the external power grid is met, obtaining the working rate and unit production profit information of multiple target power distribution factories; constructing an electric energy distribution model according to the working rate and unit production profit information of each target power distribution factory, and the electric energy distribution model is used to determine the electric energy distribution result of allocating electric energy to each target power distribution factory through the microgrid.

[0015] In some embodiments of the present disclosure, the power distribution urgency of each power distribution plant is determined by the following formula:

[0016]

[0017] Among them, URG i represents the urgency of power distribution to the i-th power distribution plant, a i represents the task volume of the i-th power distribution plant, t i It represents the task completion time of the i-th power distribution plant, where i is a positive integer.

[0018] In some embodiments of the present disclosure, the electric energy distribution formula is constructed by the following formula:

[0019]

[0020]

[0021]

[0022] F=ω1×f surplus +ω2×fprofit +ω3×f task , f surplus ≥0;

[0023] Among them, f surplus represents the total remaining energy for energy distribution, f profit represents the total production revenue of the power distribution plant, F represents the power distribution model, and f task represents the total amount of tasks to be completed by the power distribution plant, β represents the transmission energy consumption, C T represents the amount of power stored in the target time period, x i Represents the electric energy allocated to each power distribution plant, Y i Represents the working rate of each power distribution plant, P i represents the unit production revenue information of each power distribution plant, Ai represents the explosion radius of the fireworks explosion algorithm, and ω1 is f surplus The coefficient of f profit The coefficient of f task The coefficient of ω1, ω2 and ω3 is 1.

[0024] In some embodiments of the present disclosure, the exponential explosion radius A of the fireworks explosion algorithm of the exponential explosion is determined by the following formula: i :

[0025] A i =R×e x ,

[0026] Among them, R is the exponential explosion radius constant, τ is the current iterative optimization number, and itr is the preset total number of iterations.

[0027] According to another aspect of the present disclosure, there is provided an electric energy distribution system, the system comprising: a supervision module, an energy storage management module and an energy scheduling module;

[0028] The supervision module is used to detect the working rate and unit production income information of each power distribution factory, and send a power distribution application request to the energy storage management module when the preset power outage condition of the external power grid is met, and the external power grid is an external power grid relative to the microgrid;

[0029] The energy storage management module is used to record the amount of energy storage of the microgrid in real time, and when receiving the power distribution application request sent by the supervision module, determine whether the microgrid meets the conditions for power distribution according to the amount of energy storage of the microgrid within a target time period, and the target time period is the time when the external power grid is powered off to the time when the external power grid is expected to resume power supply;

[0030] The energy scheduling module is used to construct an energy distribution model according to the working rate and unit production revenue information of each factory to be distributed when the microgrid meets the conditions for energy distribution, and iteratively optimize the energy distribution model through an exponential explosion fireworks explosion algorithm, and obtain the energy distribution result of the microgrid according to the iteratively optimized energy distribution model.

[0031] According to another aspect of the present disclosure, there is provided an electric energy distribution device, the device comprising:

[0032] The power distribution plant information acquisition module is used to obtain the working rate and unit production income information of multiple power distribution plants when the preset power outage conditions of the external power grid are met, and the external power grid is an external power grid relative to the microgrid;

[0033] An electric energy distribution model building module is used to build an electric energy distribution model according to the working rate and unit production revenue information of each power distribution plant, and the electric energy distribution model is used to determine the electric energy distribution result of distributing electric energy to each power distribution plant through the microgrid;

[0034] The power distribution model optimization module is used to iteratively optimize the power distribution model through an exponential explosion fireworks explosion algorithm, and obtain the power distribution result of the microgrid according to the iteratively optimized power distribution model.

[0035] In some embodiments of the present disclosure, the device further comprises:

[0036] A power storage acquisition module is used to acquire the power storage of the microgrid within a target time period when a preset power outage condition of the external power grid is met, and the target time period is from the time when the external power grid is powered off to the time when the external power grid is expected to resume power supply;

[0037] A condition determination module for electric energy distribution, used to determine whether the microgrid meets the conditions for electric energy distribution according to the amount of electric energy stored in the microgrid within the target time period;

[0038] The power distribution plant information acquisition module is used to obtain the working rate and unit production income information of multiple power distribution plants when the microgrid meets the conditions for power distribution.

[0039] In some embodiments of the present disclosure, the power distribution plant information acquisition module is further used to obtain the task volume and task completion time of each power distribution plant;

[0040] The device also includes:

[0041] The target power distribution plant determination module is used to determine the power distribution urgency of each power distribution plant according to the task volume and task completion time of each power distribution plant; the power distribution plant whose power distribution urgency is higher than the preset urgency threshold is determined as the target power distribution plant;

[0042] A module for acquiring information of power distribution plants, used to acquire the working rate and unit production income information of multiple target power distribution plants when the preset power outage conditions of the external power grid are met;

[0043] The electric energy distribution model construction module is used to construct an electric energy distribution model according to the working rate and unit production revenue information of each target power distribution plant. The electric energy distribution model is used to determine the electric energy distribution result of allocating electric energy to each target power distribution plant through the microgrid.

[0044] In some embodiments of the present disclosure, the target power distribution plant determination module is used to determine the power distribution urgency of each power distribution plant through the following formula:

[0045]

[0046] Among them, URG i represents the urgency of power distribution to the i-th power distribution plant, a i represents the task volume of the i-th power distribution plant, t i It represents the task completion time of the i-th power distribution plant, where i is a positive integer.

[0047] In some embodiments of the present disclosure, the electric energy distribution model construction module is used to construct the electric energy distribution formula by the following formula:

[0048]

[0049]

[0050]

[0051] F=ω1×f surplus +ω2×f profit +ω3×f task , f surplus ≥0;

[0052] Among them, f surplus represents the total remaining energy for energy distribution, f profit represents the total production revenue of the power distribution plant, F represents the power distribution model, and f task represents the total amount of tasks to be completed by the power distribution plant, β represents the transmission energy consumption, C T represents the amount of power stored in the target time period, x iRepresents the electric energy allocated to each power distribution plant, Y i Represents the working rate of each power distribution plant, P i represents the unit production revenue information of each power distribution plant, Ai represents the explosion radius of the fireworks explosion algorithm, and ω1 is f surplus The coefficient of f profit The coefficient of f task The coefficient of ω1, ω2 and ω3 is 1.

[0053] In some embodiments of the present disclosure, the power distribution model optimization module is used to determine the exponential explosion radius A of the fireworks explosion algorithm of the exponential explosion by the following formula: i :

[0054]

[0055] Among them, R is the exponential explosion radius constant, τ is the current iterative optimization number, and itr is the preset total number of iterations.

[0056] According to another aspect of the present disclosure, there is provided an electronic device, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the above-mentioned power distribution method by executing the executable instructions.

[0057] According to another aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned electric energy distribution method is implemented.

[0058] According to another aspect of the present disclosure, a computer program product or a computer program is provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the electric energy distribution method provided in various optional manners in any embodiment of the present disclosure.

[0059] The technical solution provided by the embodiment of the present disclosure constructs an electric energy distribution model according to the working rate and unit production revenue information of each power distribution factory, and iteratively optimizes the electric energy distribution model according to the fireworks explosion algorithm through exponential explosion, so as to avoid the high-quality sparks generated by the fireworks explosion from only exploding in a small range, thereby falling into a local optimum. Therefore, the embodiment of the present disclosure can determine a better distribution plan for the limited electric energy stored in the microgrid, thereby ensuring the maximization of the production efficiency of each power distribution factory.

[0060] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0062] Figure 1 A schematic diagram showing an implementation environment of an electric energy distribution method in an embodiment of the present disclosure;

[0063] Figure 2 A flow chart of a method for distributing electric energy in an embodiment of the present disclosure is shown;

[0064] Figure 3 A schematic diagram of an electric energy distribution system according to an embodiment of the present disclosure is shown;

[0065] Figure 4 A flow chart showing another method for distributing electric energy in an embodiment of the present disclosure is shown;

[0066] Figure 5 A flow chart showing a method for determining an electric energy distribution result in an embodiment of the present disclosure;

[0067] Figure 6 A schematic diagram of an electric energy distribution device according to an embodiment of the present disclosure is shown; and

[0068] Figure 7 A structural block diagram of an electronic device in an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0069] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the disclosure will be more comprehensive and complete and to fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0070] In addition, the accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0071] For ease of understanding, several terms involved in the present disclosure are explained below:

[0072] Micro-Grid: refers to a small power generation and distribution system composed of distributed power sources, energy storage devices, energy conversion devices, loads, monitoring and protection devices, etc. Micro-grids can be used to achieve flexible and efficient application of distributed power sources and solve the problem of grid connection of a large number of distributed power sources in various forms. The development and extension of micro-grids can fully promote the large-scale access of distributed power sources and renewable energy, and realize highly reliable supply of various energy forms to loads. It is an effective way to realize active distribution networks and enable the transition from traditional power grids to smart grids.

[0073] Island mode: When the external grid is interrupted by power outage due to electrical failure, natural factors or misoperation, the microgrid continues to transmit power to the external grid and forms an independent power supply island with the load. At this time, the power supply mode of the microgrid is island mode.

[0074] Figure 1 A schematic diagram showing an implementation environment that can be applied to the electric energy distribution method of the embodiment of the present disclosure.

[0075] like Figure 1 As shown, the implementation environment of the electric energy distribution method may include a microgrid 101, multiple power distribution plants 102, and a cloud platform 103. The microgrid 101 and the cloud platform 103 may be connected via a network. The network may be a wired network or a wireless network, which is not limited in the embodiments of the present disclosure.

[0076] Exemplarily, when the preset power-off condition of the external power grid is met, the cloud platform 103 can construct an energy distribution model through the energy distribution method provided by the embodiment of the present disclosure. In addition, the cloud platform 103 can iteratively optimize the above energy distribution model through the exponential explosion fireworks explosion algorithm, and obtain the energy distribution result of the microgrid 101 according to the iteratively optimized energy distribution model. After that, the microgrid 101 can distribute energy to multiple power distribution plants 102 based on the energy distribution result.

[0077] Optionally, the wireless network or wired network described above uses standard communication technology and / or protocol. The network is usually the Internet, but it can also be any network, including but not limited to a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a mobile, wired or wireless network, a dedicated network or any combination of a virtual private network). In some embodiments, technologies and / or formats including Hyper Text Mark-up Language (HTML), Extensible Markup Language (XML), etc. are used to represent data exchanged through the network. In addition, conventional encryption technologies such as Secure Socket Layer (SSL), Transport Layer Security (TLS), Virtual Private Network (VPN), Internet Protocol Security (IPsec) can also be used to encrypt all or some links. In other embodiments, customized and / or dedicated data communication technologies can also be used to replace or supplement the above data communication technologies.

[0078] The power distribution factory 102 may be any factory that uses electric energy to perform work or production. The embodiment of the present disclosure does not limit the production mode of the power distribution factory 102 and the types of products produced.

[0079] The cloud platform 103 can be deployed on an electronic device with computing and processing capabilities. Optionally, the electronic device can be a terminal or a server. Exemplarily, the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. The terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, etc., but is not limited to this. The terminal and the server can be directly or indirectly connected via wired or wireless communication, and this application is not limited here.

[0080] Those skilled in the art will know that Figure 1The number of microgrids 101, multiple power distribution plants 102, and cloud platforms 103 is only illustrative, and any number of microgrids 101, power distribution plants 102, and cloud platforms 103 may be provided according to actual needs. The embodiments of the present disclosure are not limited to this.

[0081] The present exemplary implementation is described in detail below with reference to the accompanying drawings and embodiments.

[0082] First, an embodiment of the present disclosure provides an electric energy distribution method, which can be executed by any electronic device with computing and processing capabilities.

[0083] Figure 2 A flow chart of a method for distributing electric energy in an embodiment of the present disclosure is shown as follows: Figure 2 As shown, the electric energy distribution method provided in the embodiment of the present disclosure includes the following steps S202 to S206.

[0084] S202, when a preset power-off condition of the external power grid is met, the working rate and unit production revenue information of multiple power distribution factories are obtained, and the external power grid is an external power grid relative to the microgrid.

[0085] The embodiments of the present disclosure do not limit the application scenarios. For example, the power distribution method provided by the embodiments of the present disclosure can be applied to any power distribution scenario for multiple power distribution plants that need to use power to work or produce. The external power grid is the power grid that originally provides power to the above-mentioned power distribution plants. When the preset power-off conditions of the external power grid are met, the cloud platform can control the disconnection of the external power grid from each power distribution plant, and can provide power to each power distribution plant through the method provided by the embodiments of the present disclosure.

[0086] The embodiments of the present disclosure do not limit the preset power-off condition of the external power grid. For example, when the external power grid sends the expected power-off information to the microgrid, the microgrid can determine that the preset power-off condition of the external power grid is met. Alternatively, when the microgrid detects that the power storage capacity of the external power grid is lower than the power storage capacity threshold of the external power grid, the microgrid can determine that the preset power-off condition of the external power grid is met.

[0087] The embodiments of the present disclosure are not limited to the power distribution factory, which may be any factory that uses electric energy to perform work or production. The embodiments of the present disclosure are not limited to the types of products produced by the power distribution factory, which may be screws, nuts, cups, clothes, etc.

[0088] In some embodiments, the work rate may be the time required to produce a single product such as screws, nuts, cups, clothes, etc. The unit production revenue information may be the revenue brought by producing a single product such as screws, nuts, cups, clothes, etc.

[0089] In some embodiments, the electric energy distribution method provided by the embodiments of the present disclosure may also include: when a preset power outage condition of the external power grid is met, obtaining the power storage amount of the microgrid within a target time period, the target time period being the time when the external power grid is powered off to the time when the external power grid is expected to resume power supply; based on the power storage amount of the microgrid within the target time period, determining whether the microgrid meets the conditions for electric energy distribution.

[0090] In an exemplary embodiment, the cloud platform can record the amount of power stored in the microgrid in real time. When the expected power outage condition of the external power grid is met, the amount of power stored in the target time period can be used to determine whether the microgrid meets the conditions for power distribution. In some embodiments, the amount of power stored in the target time period can be calculated using the following formula 1.

[0091] C T =C0+C bat =C0+C d +C c (1)

[0092] Among them, C T It is used to indicate the storage capacity within the target time period. C0 is the storage capacity of the microgrid when the external power grid is disconnected, that is, the storage capacity of the microgrid when the cloud platform controls the external power grid to be disconnected from each power distribution plant. bat is the variable of the microgrid storage capacity in the target time period. bat The value is equal to C d +C c . C d is the discharge amount of the microgrid during the target time period, C c is the charging capacity of the microgrid during the target time period.

[0093] It should be noted that Formula 1 needs to satisfy the power storage constraint and the charge and discharge power constraint. The power storage constraint can be C min <C T And C0≤C max Among them, C min σ can be the minimum value of the microgrid storage capacity, C max The maximum amount of electricity that can be stored in the microgrid.

[0094] In addition, the charge and discharge power constraint can be P cmax ≤P bat ≤P dmax , or it can be C cmax ≤C bat ≤C dmax Among them, P cmax The maximum power that can charge the microgrid. dmax The maximum power that can be discharged to the microgrid. C cmaxThe maximum amount of charge that can be provided to the microgrid. C dmax It can be the maximum value of the microgrid discharge capacity.

[0095] After determining the amount of power stored in the microgrid within the target time period, it is possible to determine whether the microgrid meets the conditions for power distribution based on the amount of power stored in the microgrid within the target time period. In an exemplary embodiment, an energy distribution coefficient σ can be set. Furthermore, it can be set that when C T >σ×C max When , the microgrid meets the conditions for power distribution.

[0096] The embodiment of the present disclosure does not limit the value of the power distribution coefficient σ, and the value of the power distribution coefficient σ can be limited based on experience or application scenarios. Exemplarily, the value range of the power distribution coefficient σ can be 0<σ<0.5. For example, the power distribution coefficient σ can be equal to 0.2 or 0.35.

[0097] It should be noted that the power storage capacity of the microgrid is limited. Therefore, in some embodiments, the various power distribution plants can be screened to obtain multiple target power distribution plants that need to be allocated power first. This can further obtain a better power distribution plan to ensure the maximum production efficiency of each power distribution plant.

[0098] In some embodiments, the task volume and task completion time of each factory to be powered by electricity are obtained; the power distribution urgency of each factory to be powered by electricity is determined according to the task volume and task completion time of each factory to be powered by electricity; and the factory to be powered by electricity whose power distribution urgency is higher than a preset urgency threshold is determined as the target factory to be powered by electricity.

[0099] In some embodiments, the power distribution urgency of each power distribution plant can be determined by the following formula 2:

[0100]

[0101] Among them, URG i represents the urgency of power distribution to the i-th power distribution plant, a i represents the task volume of the i-th power distribution plant, t i represents the task completion time of the i-th power distribution plant, i is a positive integer. i The value can be a i ≥0. And, the t i The value of can be t i >0.

[0102] In an exemplary embodiment, it can be assumed that there are n power distribution plants in total, so the value of i can be 1, 2, ..., n. Exemplarily, the task volume and task completion time of each power distribution plant at this time can be shown in Table 1 below.

[0103] Table 1

[0104]

[0105] As shown in Table 1, the task volume of each power distribution plant can be expressed as a1, a2, ..., a n The task completion time of each power distribution plant can be expressed as t1, t2, ..., t n After that, the values ​​in Table 1 can be substituted into Formula 2, and the power distribution urgency of the n power distribution plants can be calculated respectively: URG1, URG2, ..., URG n .

[0106] The embodiment of the present disclosure does not limit the value of the preset urgency threshold, and the value of the preset urgency threshold can be determined based on experience or application scenarios. For example, the value of the preset urgency threshold can be 300, or can be 90.

[0107] In a possible implementation, a task completion time threshold may also be set. When the power distribution urgency of a power distribution plant is higher than a preset urgency threshold, or the task completion time of the power distribution plant is less than the task completion time threshold, the power distribution plant is determined as the target power distribution plant. The disclosed embodiment does not limit the task completion time threshold. The value of the preset urgency threshold may be determined based on experience or application scenarios. For example, the task completion time threshold may be 5 minutes or 10 seconds.

[0108] S204, constructing an electric energy distribution model according to the working rate and unit production revenue information of each power distribution factory, and the electric energy distribution model is used to determine the electric energy distribution result of distributing electric energy to each power distribution factory through the microgrid.

[0109] In some embodiments, the power distribution formula is constructed by the following formulas 3 to 6:

[0110]

[0111]

[0112]

[0113] F=ω1×f surplus +ω2×f profit +ω3×f task , fsurplus ≥0 (6)

[0114] Among them, f surplus represents the total remaining energy for energy distribution, f profit represents the total production revenue of the power distribution plant, F represents the power distribution model, and f task represents the total amount of tasks to be completed by the power distribution plant, β represents the transmission energy consumption, C T represents the amount of power stored in the target time period, x i Represents the electric energy allocated to each power distribution plant, Y i Represents the working rate of each power distribution plant, P i It represents the unit production revenue information of each power distribution factory, and Ai represents the explosion radius of the fireworks explosion algorithm.

[0115] ω1 can be f surplus The coefficient of ω2 can be f profit The coefficient of ω3 can be f task The embodiment of the present disclosure does not limit the values ​​of ω1, ω2 and ω3, and the sum of ω1, ω2 and ω3 can be 1, and i is a positive integer.

[0116] The electric energy distribution method provided in the embodiment of the present disclosure is to surplus 、f profit 、f task The three parameters are used to construct the electric energy allocation formula. Therefore, when allocating electric energy, the embodiment of the present disclosure comprehensively considers the remaining electric energy for electric energy allocation, the total production income of the power distribution factory, and the total amount of task completion of the power distribution factory. Therefore, the embodiment of the present disclosure can determine a better allocation plan for the limited electric energy stored in the microgrid, thereby ensuring the maximization of the production efficiency of each power distribution factory.

[0117] In some embodiments, before obtaining the working rate and unit production income information of multiple power distribution plants, it can be determined whether the microgrid meets the conditions for power distribution. Therefore, obtaining the working rate and unit production income information of multiple power distribution plants can include: when the microgrid meets the conditions for power distribution, obtaining the working rate and unit production income information of multiple power distribution plants.

[0118] In some embodiments, before obtaining the working rate and unit production income information of multiple power distribution plants, a target power distribution list can be constructed first, that is, the target power distribution plants can be determined first. Therefore, the power distribution method provided by the embodiment of the present disclosure can include: when the preset power outage condition of the external power grid is met, the working rate and unit production income information of multiple target power distribution plants are obtained; according to the working rate and unit production income information of each target power distribution plant, a power distribution model is constructed, and the power distribution model is used to determine the power distribution result of allocating power to each target power distribution plant through the microgrid.

[0119] In some embodiments, in addition to obtaining the working rate and unit production revenue information of multiple power distribution plants, the output energy consumption of multiple target power distribution plants can also be obtained. In this case, the cloud platform can obtain information as shown in Table 2 below.

[0120] Table 2

[0121]

[0122] As shown in Table 2, for each power distribution plant, the output energy consumption E i , working speed Y i And unit production revenue information P i to obtain it.

[0123] S206, iteratively optimizing the power distribution model through an exponential explosion fireworks explosion algorithm, and obtaining a power distribution result of the microgrid according to the iteratively optimized power distribution model.

[0124] In some embodiments, the explosion radius A of the fireworks explosion algorithm can be calculated according to the following formula 6: i 'To confirm.

[0125]

[0126] in, It can be used as the adjustment constant of the explosion radius. ε is the minimum value of the machine. Setting the ε value can avoid errors caused by misoperation. min It can be the minimum fitness value in the current fireworks population, that is, F min =min(F(x i )). F(x i ) is x i The fitness value of .

[0127] It should be noted that for the fireworks algorithm that only uses Formula 6, the explosion radius of the fireworks is calculated based on the fitness value, which results in high-quality sparks only being able to explode in a smaller range, and is prone to falling into a local optimum. Therefore, the embodiment of the present disclosure uses an exponential explosion radius method, which can improve the diversity of high-quality fireworks in the early stage of optimization, and can not affect the convergence speed in the later stage of optimization.

[0128] In some embodiments, the exponential explosion radius A of the fireworks explosion algorithm of the exponential explosion is determined by the following formula 7: i :

[0129]

[0130] Wherein, R is the exponential explosion radius constant, τ is the current iteration optimization number, and itr is the preset total number of iterations. The disclosed embodiment does not limit the value of the exponential explosion radius constant, and the value of the exponential explosion radius constant can be limited based on experience or application scenarios.

[0131] For example, the number of explosion sparks S of the fireworks explosion algorithm can be determined according to the following formula 8: i .

[0132]

[0133] Wherein, M can be the adjustment constant of the number of explosion sparks. max It can be the maximum fitness value in the current fireworks population, that is, F max =max(F(x i )).

[0134] After that, you can use the A i With S i to generate exponential explosion fireworks.

[0135] In some embodiments, fireworks can be exploded and mutated based on the above formula 7 and formula 8 to calculate F and iteratively update the optimal value x of F. i (i=1、2、…、n)、F max 、F min According to the optimal value of F, we can determine x i The optimal value of (i=1, 2, ..., n).

[0136] For example, when fireworks explode, each group of fireworks randomly selects z dimensions for explosion operation, as shown in Formula 9. From Formula 9, it can be obtained that during the fireworks explosion, x ik Randomly select z dimensions for mutation operation, and get In formula 9 That is x ikExplosive sparks obtained through explosion.

[0137]

[0138] For example, in the fireworks mutation, each group of fireworks randomly selects z dimensions for mutation operation as shown in formula 10. From formula 10, it can be obtained that in the fireworks mutation process, x ik Randomly select z dimensions for mutation operation, and get In formula 10 That is x ik Mutation Sparks obtained through mutation.

[0139]

[0140] Among them, U(-1, 1) can be a random number between -1 and 1. N[-1, 1] is a random number with a mean and a variance of 1.

[0141] In addition, the fireworks with the best fitness value can be retained, and the next generation of fireworks can be selected from the remaining k-1 fireworks. After multiple iterations, x i (i=1, 2, ..., n) is the optimal value. The disclosed embodiment does not limit the method for selecting the next generation of fireworks. i The optimal value of (i=1, 2, ..., n) is the power distribution result of the microgrid.

[0142] The method provided by the embodiment of the present disclosure constructs an electric energy distribution model according to the working rate and unit production revenue information of each power distribution factory, and iteratively optimizes the electric energy distribution model according to the fireworks explosion algorithm through exponential explosion, so as to avoid the high-quality sparks generated by the fireworks explosion from only being able to explode in a smaller range, thereby falling into a local optimum. Therefore, the embodiment of the present disclosure can determine a better distribution plan for the limited electric energy stored in the microgrid, thereby ensuring the maximization of the production benefits of each power distribution factory.

[0143] In an exemplary embodiment, an electric energy distribution system provided by the present disclosure can be as follows: Figure 3 shown.

[0144] Exemplarily, each power distribution factory may include multiple production lines, and the products produced by any production line may be the same or different. The present disclosure does not limit the products produced by any production line, nor does it limit the number of production lines in each power distribution factory. In addition, the microgrid can generate electricity through solar energy, wind power, etc., and can store the generated electricity through multiple energy storage units. The cloud platform may include a supervision module, an energy storage management module, and an energy scheduling module.

[0145] Among them, the supervision module is used to detect the working rate and unit production income information of each power distribution factory, and when the preset power outage conditions of the external power grid are met, send a power distribution application request to the energy storage management module, and the external power grid is the external power grid relative to the microgrid. The energy storage management module is used to record the storage capacity of the microgrid in real time, and when receiving the power distribution application request sent by the supervision module, determine whether the microgrid meets the conditions for power distribution based on the storage capacity of the microgrid in the target time period. The target time period is from the time when the external power grid is out of power to the time when the external power grid is expected to resume power supply. The energy scheduling module is used to construct an energy distribution model based on the working rate and unit production income information of each power distribution factory when the microgrid meets the conditions for power distribution, and iteratively optimize the energy distribution model through the exponential explosion fireworks explosion algorithm, and obtain the energy distribution result of the microgrid based on the iteratively optimized energy distribution model.

[0146] It should be noted that the implementation methods of the various operations performed by the monitoring module, energy storage management module and energy scheduling module in the above-mentioned cloud platform can be referred to the corresponding descriptions of S202 to S204 above, and will not be repeated here.

[0147] In an exemplary embodiment, based on Figure 3 The power distribution system shown in the figure, the power distribution method provided by the embodiment of the present disclosure can be as follows Figure 4 shown.

[0148] S402, the supervision module monitors the power distribution of the external power grid in real time. When the preset power-off condition of the external power grid is met, the microgrid enters an island state, and the supervision module sends a power distribution application request to the energy storage management module.

[0149] In an exemplary embodiment, the external power grid distribution situation may include the power storage amount of the external power grid.

[0150] S404, the energy storage management module records the storage capacity of the microgrid in real time, determines the storage capacity of the microgrid within the target time period after receiving the power distribution application request, and notifies the energy scheduling module to distribute power when the conditions for power distribution are met.

[0151] S406, the energy dispatching module constructs a target distribution list according to the conditions of each power distribution factory, and constructs a power distribution model through factors such as the remaining power distributed by the microgrid, the total production revenue of the power distribution factory, and the total amount of task completion of the power distribution factory.

[0152] Exemplarily, constructing a target power distribution list based on the situation of each power distribution factory may include: determining the power distribution urgency of each power distribution factory based on the task volume and task completion time of each power distribution factory; and determining the power distribution urgency of the power distribution factory with a power distribution urgency higher than a preset urgency threshold as the target power distribution factory. The target power distribution list may include each target power distribution factory.

[0153] S408, iteratively optimizing the power distribution model through an exponential explosion fireworks explosion algorithm, and obtaining a power distribution result for distributing power to the power distribution plants in the power distribution list according to the iteratively optimized power distribution model.

[0154] The implementation methods of each step in this embodiment can refer to the corresponding steps in S202 to S208 above, which will not be repeated here.

[0155] In some embodiments, a flowchart of a method for determining an electric energy allocation result may be as follows: Figure 5 shown.

[0156] S502, input the target power distribution list.

[0157] S504, initialization parameters, exponential radius, number of iterations, fireworks, and current number of iterations.

[0158] S506, calculate the fitness value and save F max 、F min .

[0159] S508, generating explosion sparks through explosion and mutation.

[0160] S510, calculating the exponential explosion radius Ai and the number of explosion sparks S i .

[0161] S512, based on A i and S i Generates exponential fireworks.

[0162] S514, Update F max 、F min and the optimal value of F.

[0163] S516, determining the best fireworks among the exponential explosion sparks, the explosion sparks, and the variation sparks.

[0164] S518, selecting the next generation of fireworks from the remaining fireworks.

[0165] S520, iterating the fireworks explosion until the current number of iterations is greater than the preset number of iterations, outputting the current optimal value of F, thereby determining the power distribution result.

[0166] Based on the same inventive concept, the present disclosure also provides an electric energy distribution device in the following embodiments. Since the principle of solving the problem in the device embodiment is similar to that in the above method embodiment, the implementation of the device embodiment can refer to the implementation of the above method embodiment, and the repeated parts will not be repeated.

[0167] Figure 6 A schematic diagram of an electric energy distribution device in an embodiment of the present disclosure is shown. Figure 6 As shown, the device comprises:

[0168] The power distribution plant information acquisition module 601 is used to acquire the working rate and unit production income information of multiple power distribution plants when the preset power outage condition of the external power grid is met. The external power grid is an external power grid relative to the microgrid;

[0169] The electric energy distribution model building module 602 is used to build an electric energy distribution model according to the working rate and unit production income information of each power distribution plant, and the electric energy distribution model is used to determine the electric energy distribution result of allocating electric energy to each power distribution plant through the microgrid;

[0170] The power distribution model optimization module 603 is used to iteratively optimize the power distribution model through an exponential explosion fireworks explosion algorithm, and obtain the power distribution result of the microgrid according to the iteratively optimized power distribution model.

[0171] In some embodiments of the present disclosure, the device further comprises:

[0172] The power storage acquisition module is used to acquire the power storage of the microgrid within a target time period when the preset power outage condition of the external power grid is met. The target time period is from the time when the external power grid is powered off to the time when the external power grid is expected to resume power supply;

[0173] The power distribution condition determination module is used to determine whether the microgrid meets the power distribution conditions according to the power storage capacity of the microgrid within the target time period;

[0174] The power distribution plant information acquisition module 601 is used to obtain the working rate and unit production income information of multiple power distribution plants when the microgrid meets the conditions for power distribution.

[0175] In some embodiments of the present disclosure, the power distribution plant information acquisition module 601 is also used to obtain the task volume and task completion time of each power distribution plant;

[0176] The device also includes:

[0177] The target power distribution plant determination module is used to determine the power distribution urgency of each power distribution plant according to the task volume and task completion time of each power distribution plant; the power distribution plant whose power distribution urgency is higher than the preset urgency threshold is determined as the target power distribution plant;

[0178] The power distribution plant information acquisition module 601 is used to acquire the working rate and unit production income information of multiple target power distribution plants when the preset power outage condition of the external power grid is met;

[0179] The power distribution model building module 602 is used to build a power distribution model according to the working rate and unit production revenue information of each target power distribution plant. The power distribution model is used to determine the power distribution result of allocating power to each target power distribution plant through the microgrid.

[0180] In some embodiments of the present disclosure, the target power distribution plant determination module is used to determine the power distribution urgency of each power distribution plant through the above formula 2, where URG i represents the urgency of power distribution to the i-th power distribution plant, a i represents the task volume of the i-th power distribution plant, t i It represents the task completion time of the i-th power distribution plant, where i is a positive integer.

[0181] In some embodiments of the present disclosure, the power distribution model building module 602 is used to build a power distribution formula using the above formulas 3 to 6, where f surplus represents the total remaining energy for energy distribution, f profit represents the total production revenue of the power distribution plant, F represents the power distribution model, and f task represents the total amount of tasks to be completed by the power distribution plant, β represents the transmission energy consumption, C T represents the amount of power stored in the target time period, x i Represents the electric energy allocated to each power distribution plant, Y i Represents the working rate of each power distribution plant, P i represents the unit production revenue information of each power distribution plant, Ai represents the explosion radius of the fireworks explosion algorithm, and ω1 is f surplus The coefficient of f profit The coefficient of f task The coefficient of ω1, ω2 and ω3 is 1.

[0182] In some embodiments of the present disclosure, the power distribution model optimization module 603 is used to determine the exponential explosion radius A of the fireworks explosion algorithm of the exponential explosion by the above formula 7. i , where R is the exponential explosion radius constant, τ is the number of current iteration optimizations, and itr is the total number of preset iterations.

[0183] The device provided by the embodiment of the present disclosure constructs an electric energy distribution model according to the working rate and unit production revenue information of each power distribution factory, and iteratively optimizes the electric energy distribution model according to the fireworks explosion algorithm through exponential explosion, so as to avoid the high-quality sparks generated by the fireworks explosion from only being able to explode in a smaller range, thereby falling into a local optimum. Therefore, the embodiment of the present disclosure can determine a better distribution plan for the limited electric energy stored in the microgrid, thereby ensuring the maximization of the production benefits of each factory to be distributed.

[0184] Those skilled in the art will appreciate that various aspects of the present disclosure may be implemented as systems, methods or program products. Therefore, various aspects of the present disclosure may be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as "circuits", "modules" or "systems".

[0185] Refer to the following Figure 7 An electronic device 700 according to this embodiment of the present disclosure is described. Figure 7 The electronic device 700 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0186] like Figure 7 As shown, the electronic device 700 is in the form of a general computing device. The components of the electronic device 700 may include but are not limited to: at least one processing unit 710, at least one storage unit 720, and a bus 730 connecting different system components (including the storage unit 720 and the processing unit 710).

[0187] The storage unit stores program codes, which can be executed by the processing unit 710, so that the processing unit 710 executes the steps according to various exemplary embodiments of the present disclosure described in the above “Specific Implementation Methods” section of this specification.

[0188] The storage unit 720 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 7201 and / or a cache storage unit 7202 , and may further include a read-only storage unit (ROM) 7203 .

[0189] The storage unit 720 may also include a program / utility 7204 having a set (at least one) of program modules 7205, such program modules 7205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0190] Bus 730 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0191] The electronic device 700 may also communicate with one or more external devices 740 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 700, and / or communicate with any device that enables the electronic device 700 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 750. Furthermore, the electronic device 700 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 760. As shown, the network adapter 760 communicates with other modules of the electronic device 700 via a bus 730. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 700, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0192] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0193] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, which may be a readable signal medium or a readable storage medium. A program product capable of implementing the above-mentioned method of the present disclosure is stored thereon. In some possible implementations, various aspects of the present disclosure may also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to cause the terminal device to execute the steps according to various exemplary implementations of the present disclosure described in the above “Specific Implementation Methods” section of this specification.

[0194] More specific examples of computer-readable storage media in the present disclosure may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0195] In the present disclosure, a computer readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, wherein a readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A readable signal medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0196] Alternatively, the program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0197] In a specific implementation, the program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0198] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0199] In addition, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0200] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0201] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not disclosed in the present disclosure. The description and examples are to be regarded as exemplary only, and the true scope of the present disclosure is indicated by the appended claims.

Claims

1. A method for distributing electric energy, characterized in that: include: When a preset power-off condition of the external power grid is met, the working rate and unit production revenue information of multiple power distribution plants are obtained, wherein the external power grid is an external power grid relative to the microgrid; By f surplus 、f profit 、f task Three parameters are used to construct the power distribution model, among which, f surplus represents the total remaining energy for energy distribution, f profit represents the total production revenue of the power distribution plant, f task represents the total amount of tasks to be completed by the power distribution plant, f task The working rate is obtained by summing the product of the unit production revenue information of each power distribution plant and the allocated electric energy divided by the product of the task amount and the explosion radius of the fireworks explosion algorithm. The working rate is used to determine the total production revenue of the power distribution plant, the unit production revenue information is used to determine the total amount of tasks completed by the power distribution plant, and the electric energy distribution model is used to determine the electric energy distribution result of allocating electric energy to each power distribution plant through the microgrid; The electric energy distribution model is iteratively optimized through an exponential explosion fireworks explosion algorithm, and the electric energy distribution result of the microgrid is obtained according to the iteratively optimized electric energy distribution model.

2. The electric energy distribution method according to claim 1, characterized in that: The method further comprises: When the preset power-off condition of the external power grid is met, the amount of power stored in the microgrid within a target time period is obtained, and the target time period is from the time when the external power grid is powered off to the time when the external power grid is expected to resume power supply; Determining whether the microgrid meets the conditions for power distribution according to the power storage amount of the microgrid within the target time period; The obtaining of the working rate and unit production revenue information of the plurality of power distribution plants includes: When the microgrid meets the conditions for power distribution, the working rate and unit production income information of multiple factories to be distributed are obtained.

3. The electric energy distribution method according to any one of claims 1 or 2, characterized in that: The method further comprises: Obtain the task volume and task completion time of each power distribution plant; Determine the urgency of power distribution for each power distribution plant based on the task volume and task completion time of each power distribution plant; Determine the power distribution factories whose power distribution urgency is higher than the preset urgency threshold as target power distribution factories; The method comprises: When the preset power-off condition of the external power grid is met, the working rate and unit production income information of multiple target power distribution plants are obtained; According to the working rate and unit production revenue information of each target power distribution plant, an electric energy distribution model is constructed, and the electric energy distribution model is used to determine the electric energy distribution result of distributing electric energy to each target power distribution plant through the microgrid.

4. The electric energy distribution method according to claim 3, characterized in that: The urgency of power distribution for each power distribution plant is determined by the following formula: Among them, URG i represents the urgency of power distribution to the i-th power distribution plant, a i represents the task volume of the i-th power distribution plant, t i It represents the task completion time of the i-th power distribution plant, where i is a positive integer.

5. The electric energy distribution method according to claim 1, characterized in that: The electric energy distribution formula is constructed by the following formula: F=ω1×f surplus +ω2×f profit +ω3×f task ,f surplus ≥0; Among them, f surplus represents the total remaining energy for energy distribution, f profit represents the total production revenue of the power distribution plant, F represents the power distribution model, and f task represents the total amount of tasks to be completed by the power distribution plant, β represents the transmission energy consumption, C T represents the amount of power stored in the target time period, x i Represents the electric energy allocated to each power distribution plant, Y i Represents the working rate of each power distribution plant, P i A represents the unit production revenue information of each power distribution factory. i represents the explosion radius of the fireworks explosion algorithm, ω1 is f surplus The coefficient of f profit The coefficient of f task The coefficient of ω1, ω2 and ω3 is 1, a i Represents the task volume of the i-th power distribution plant.

6. The electric energy distribution method according to claim 5, characterized in that: The exponential explosion radius A of the exponential explosion fireworks explosion algorithm is determined by the following formula i : A i =R×e x , Among them, R is the exponential explosion radius constant, τ is the current iterative optimization number, and itr is the preset total number of iterations.

7. An electric energy distribution system, characterized in that: The system includes: a supervision module, an energy storage management module and an energy scheduling module; The supervision module is used to detect the working rate and unit production income information of each power distribution factory, and send a power distribution application request to the energy storage management module when the preset power outage condition of the external power grid is met, and the external power grid is an external power grid relative to the microgrid; The energy storage management module is used to record the amount of energy storage of the microgrid in real time, and when receiving the power distribution application request sent by the supervision module, determine whether the microgrid meets the conditions for power distribution according to the amount of energy storage of the microgrid within a target time period, and the target time period is the time when the external power grid is powered off to the time when the external power grid is expected to resume power supply; The energy dispatching module is used to dispatch the energy to the microgrid when the microgrid meets the conditions for power distribution. surplus 、f profit 、f task The power distribution model is constructed based on the three parameters, and the power distribution model is iteratively optimized through the exponential explosion fireworks explosion algorithm, and the power distribution result of the microgrid is obtained according to the iteratively optimized power distribution model, where f surplus represents the total remaining energy for energy distribution, f profit represents the total production revenue of the power distribution plant, f task represents the total amount of tasks to be completed by the power distribution plant, f task The working rate is obtained by summing the product of the unit production revenue information of each factory to be distributed and the allocated electric energy divided by the product of the task amount and the explosion radius of the fireworks explosion algorithm. The working rate is used to determine the total production revenue of the factory to be distributed, and the unit production revenue information is used to determine the total amount of tasks completed by the factory to be distributed.

8. An electric energy distribution device, characterized in that: include: The power distribution plant information acquisition module is used to obtain the working rate and unit production income information of multiple power distribution plants when the preset power outage conditions of the external power grid are met, and the external power grid is an external power grid relative to the microgrid; Power distribution model building blocks for surplus 、f profit 、f task Three parameters are used to construct the power distribution model, among which, f surplus represents the total remaining energy for energy distribution, f profit represents the total production revenue of the power distribution plant, f task represents the total amount of tasks to be completed by the power distribution plant, f task The working rate is obtained by summing the product of the unit production revenue information of each power distribution plant and the allocated electric energy divided by the product of the task amount and the explosion radius of the fireworks explosion algorithm. The working rate is used to determine the total production revenue of the power distribution plant, the unit production revenue information is used to determine the total amount of tasks completed by the power distribution plant, and the electric energy distribution model is used to determine the electric energy distribution result of allocating electric energy to each power distribution plant through the microgrid; The power distribution model optimization module is used to iteratively optimize the power distribution model through an exponential explosion fireworks explosion algorithm, and obtain the power distribution result of the microgrid according to the iteratively optimized power distribution model.

9. An electronic device, characterized in that: include: processor; as well as A memory, configured to store executable instructions of the processor; The processor is configured to execute the electric energy distribution method according to any one of claims 1 to 6 by executing the executable instructions.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the electric energy distribution method according to any one of claims 1 to 6 is implemented.

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