Numerical simulation and energy flow optimization method of coupled network under energy interconnection mode based on demand-side load

Abstract

The present application provides a method for numerical simulation and energy flow optimization of a coupling network in an energy interconnection mode based on demand-side load, which relates to the field of energy flow optimization, including: whenever a signal is received that the mains port has entered a target state, the current power of each battery in the battery group is obtained; if the corresponding upper power limit is not reached, the target time period is determined; the solar cell group is controlled to charge the battery group with the start time of the target time period as the charging start time, and the solar cell group is controlled to supply power to the target building complex during the time other than charging the battery group within T. The present application realizes the reasonable scheduling of each power supply port in the coupling network in the energy interconnection mode, so that during the low-power consumption period, the waste of mains power is reduced, and a large amount of electric energy is stored for the battery group by using the solar cell group, so that as much clean energy as possible can be used during the non-low-power consumption period. The utilization efficiency of electric energy is improved.

Description

Background Art

[0002] In the existing power supply system, due to the imbalance between power production and consumption, there is often a low period of electricity consumption. During this period, the power grid's power generation is significantly greater than the consumption, resulting in a large amount of electricity being wasted without being effectively utilized. This waste of electricity not only increases the operating costs of power companies, but also creates an unnecessary burden on the environment, which is contrary to the current global concept of energy conservation, emission reduction, and green development.

[0003] In order to effectively solve this problem and make full use of clean energy, in recent years, the integrated power supply scheme combining batteries, solar energy and city electricity has gradually become a research hotspot. Solar energy can be used to charge batteries and power other devices; at the same time, during the low electricity consumption period, the battery can use excess electricity to charge and realize the translation and storage of electricity. As a clean and renewable energy, solar energy does not produce pollutants during its power generation process and is an ideal green energy. However, solar power generation is greatly affected by weather conditions, is intermittent and unstable, and needs to be combined with other energy forms to ensure the continuity and stability of power supply. Therefore, in the scenario where the city electricity, batteries and solar energy are simultaneously powering other devices, how to design a reasonable power supply scheme to maximize the use of clean energy and reduce the waste of electricity during the low electricity consumption period to achieve continuous and sufficient power supply to the demand side is an urgent problem to be solved. Summary of the invention

[0004] In response to the above technical problems, the present application provides a method, device, medium and electronic equipment for numerical simulation and energy flow optimization of a coupling network in an energy interconnection mode based on demand-side load, which at least partially solves the problems existing in the prior art.

[0005] In a first aspect of the present application, a method for numerical simulation and energy flow optimization of a coupling network in an energy interconnection mode based on demand-side load is provided, and the method is applied to a target charging system; the target charging system includes a server and a coupling network in an energy interconnection mode; the coupling network in the energy interconnection mode includes a solar cell group, a battery group and a mains port; wherein the solar cell group is used to power the battery group or the target building group; the battery group is used to power the target building group; the mains port is used to power the target building group; the server is used to perform the following steps:

[0006] S100, whenever a signal is received that the AC power port enters a target state, and the AC power port is not currently used to power the target building complex; the current power of each battery in the battery pack is obtained; the target state is that the power generation corresponding to the AC power port is greater than the power demand corresponding to the AC power port; the signal that the AC power port enters a target state includes a predicted duration T of the target state.

[0007] S200, if the current power level of any storage battery does not reach the corresponding power upper limit value; control the solar cell group to determine the target time period according to a preset time period determination method.

[0008] S300, control the solar cell group to charge the battery group with the start time of the target time period as the charging start time, until the current power of each battery in the battery group reaches the corresponding upper limit of power, and control the solar cell group to supply power to the target building complex during the time other than charging the battery group within T; and control the AC power port to supply power to the target building complex within T.

[0009] This application has at least the following beneficial effects:

[0010] The coupling network numerical simulation and energy flow optimization method in the energy interconnection mode based on demand-side load provided in the present application is applied to the target charging system, which is based on server control, wherein the solar cell group can power both the battery group and the target building group, the battery group is used to power the target building group, and the mains port is used to power the target building group. However, due to the imbalance between electricity production and consumption, the mains power will have non-valley periods when the consumption is greater than the power generation and valley periods when the power generation is significantly greater than the consumption. During the valley period of the mains power usage (i.e., the target state), and the mains power port is not currently used to power the target building group, a large amount of electric energy of the mains power port is not effectively utilized. Therefore, when a signal that the mains power port enters the target state (the mains power enters the valley period of the usage point) is received, first, a time period is selected within the duration of the mains power valley period to use the solar cell group to charge the battery group. Here, it is because during the valley period of electricity usage, the mains power port can be used to power the target building group. Therefore, during this period, the solar cell group can be used to select a time period to charge the battery group, so that the battery group can supply power to the target building group when the power consumption is not low, reducing the pressure on the use of the mains electricity. In addition to the time when the solar cell group supplies power to the battery group during the duration of the mains power trough period, it can also supply power to the target building group at the same time as the mains port, so that the mains power is used as little as possible during the power consumption trough period. The coupling network numerical simulation and energy flow optimization method under the energy interconnection mode based on the demand side load provided in the present application uses a server to realize the reasonable scheduling of each power supply port in the coupling network under the energy interconnection mode, so that during the power consumption trough period, the waste of the mains power is reduced, and the solar cell group is used to reserve a large amount of electric energy for the battery group, so that as much clean energy as possible can be used during the non-power consumption trough period. Improve the utilization efficiency of electric energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 A flow chart of a method for numerical simulation of coupled networks and energy flow optimization in an energy interconnection mode based on demand-side load provided in an embodiment of the present application. DETAILED DESCRIPTION

[0013] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0014] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0015] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present application, it should be understood by those skilled in the art that an aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of aspects described herein may be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein may be used to implement this device and / or practice this method.

[0016] Please refer to Figure 1As shown, an embodiment of the present application provides a method for numerical simulation and energy flow optimization of a coupling network in an energy interconnection mode based on demand-side load, and the method is applied to a target charging system; the target charging system includes a server and a coupling network in an energy interconnection mode; the coupling network in the energy interconnection mode includes a solar cell group, a battery group and a mains port; wherein the solar cell group is used to charge the battery group or to supply power to a target building group; the battery group is used to supply power to a target building group; the mains port is used to supply power to a target building group; the server is used to perform the following steps:

[0017] S100, whenever a signal is received that the AC power port enters a target state, and the AC power port is not currently used to power the target building complex; the current power of each battery in the battery pack is obtained; the target state is that the power generation corresponding to the AC power port is greater than the power demand corresponding to the AC power port; the signal that the AC power port enters a target state includes a predicted duration T of the target state.

[0018] Specifically, T can be predicted by a person skilled in the art based on relevant knowledge in the art, and will not be described in detail here. The target building complex includes several buildings, each of which is provided with a solar cell group, and each solar cell group has a corresponding battery group. At the same time, each building is also connected to a mains power port.

[0019] S200, if the current power level of any storage battery does not reach the corresponding power upper limit value; control the solar cell group to determine the target time period according to a preset time period determination method.

[0020] Specifically, the upper limit of the power can be 85% of the total power of the battery. Here, the charging efficiency of the battery is higher in the early stage of charging and lower in the later stage of charging. Therefore, a reasonable upper limit of the power is set to improve the overall charging efficiency. Here, a time period is selected during the duration of the low power consumption period of the mains electricity to use the solar cell group to charge the battery group. Here, it is because during the low power consumption period, the mains port can be used to power the target building complex. Therefore, during this period, the solar cell group can be used to select a time period to charge the battery group, so that the battery group can power the target building complex when it is not in the low power consumption period, thereby reducing the pressure on the use of the mains electricity.

[0021] S300, control the solar cell group to charge the battery group with the start time of the target time period as the charging start time, until the current power of each battery in the battery group reaches the corresponding upper limit of power, and control the solar cell group to supply power to the target building complex during the time other than charging the battery group within T; and control the AC power port to supply power to the target building complex within T.

[0022] In an exemplary embodiment of the present application, the method for determining the preset time period includes:

[0023] S210, obtaining the average power generated by the solar cell group per minute within T to obtain a corresponding power generation curve C.

[0024] Specifically, a power generation curve C of the solar cell group during the duration of the low power consumption period of the city power is obtained. The X-axis corresponding to the power generation curve C is time, and the Y-axis is the generated power.

[0025] S220 , determining a target time period according to C and the current power shortage f (ΔSOC) of the battery pack.

[0026] Specifically, step S220 includes:

[0027] S221, if PC ≥ α f(ΔSOC), then according to C and the optimal charging power Z corresponding to the battery pack, the initial time period list G=(G1, G2, …, G i , …, G n ), i=1, 2, ..., n, where n is the number of initial time periods; G i is the i-th initial period; G i =(SG i ,EG i );SG i G i The corresponding start time; EG i G i The corresponding end time; the solar cell group is in G i The average power generation per minute within T is greater than Z; PC is the total power generation of the solar cell group within T; α is the power conversion efficiency; f(ΔSOC) is the current lack of power in the battery group.

[0028] Here, if PC ≥ α f(ΔSOC), that is, the total power generation of the solar cell group in the T time period is greater than or equal to the current power shortage of the battery group, indicating that the solar cell group can have surplus power in addition to charging the battery group in the T time period; it can be used to power the target building complex. At this time, firstly obtain several initial time periods in which the corresponding average power generation per minute is greater than the optimal charging power.

[0029] S222: Determine a target time period according to G and a preset fusion time interval ΔA.

[0030] Here, step S222 also includes:

[0031] S2221, if G is not empty, then traverse G, if SG i+1-EG i <ΔA, then for G i and G i+1 The key period list set MG = (MG1, MG2, ..., MG j , …, MG m );j=1,2,…,m;where m is the number of critical periods; MG j =(SMG j , EMG j ); SMG j For MG j Corresponding start time; EMG j For MG j The corresponding end time; ΔA is the preset fusion time interval.

[0032] Since there may be some discrete points in the above capacity power curve C, here, if the time interval between any two adjacent initial time periods is less than the preset fusion time interval, the power value corresponding to the time interval may be a discrete point. At this time, the two adjacent initial time periods are fused into a new time period to obtain the key time period list set MG.

[0033] S2222, if EMG j -SMG j ≥ZC+ZY, then MG j is determined as the target time period; ZC is the time required for the battery pack to be fully charged at the optimal charging power Z; and ZY is the reserved charging time.

[0034] Specifically, if EMG j -SMG j ≥ZC+ZY, it means that the duration of the critical period (corresponding to the initial period in which the average power generation per minute is greater than the optimal charging power) is longer than the time required for the battery pack to be fully charged at the optimal charging power Z (plus the reserved time). As an example: the reserved time can be 1 minute. That is, MG j During the corresponding time period, when the solar cell group is used to charge the battery group during the critical period, the battery group can be charged at the optimal charging power Z. At this time, the charging efficiency is the highest, that is, the shorter the time required to complete the charging, the longer the solar cell group can charge the target building group. The mains electricity can be used as little as possible during the low electricity consumption period, thereby improving the utilization rate of clean resources.

[0035] In an exemplary embodiment of the present application, after step S2221, the method further includes:

[0036] S2223: If each corresponding time length in MG is smaller than the sum of ZC and ZY, determine the target time period according to the key time period with the longest corresponding time length in MG.

[0037] Wherein, step S2223 further includes:

[0038] S22231, if each corresponding time length in MG is less than the sum of ZC and ZY, and MG j It is the key period with the longest duration in MG.

[0039] Specifically, in this embodiment, there are several initial time periods in which the corresponding average power generation per minute is greater than the optimal charging power, but the duration corresponding to each initial time period is less than the time required for full charging at the optimal charging power Z (plus the reserved time). However, if the battery is not fully charged at one time, that is, shallow charging and shallow discharge, it will damage the battery life. In this embodiment, on the one hand, in order to ensure that the battery can be fully charged at one time, on the other hand, the charging time can be as short as possible. First, the key time period with the longest corresponding time length in MG is selected. Priority is given to ensuring that the battery is charged for as long as possible at the optimal charging power Z.

[0040] S22232, according to MG j and ZC, obtain the list of time periods to be selected YG=(YG q , YG h ), the selected time period with the largest total power generation in YG is determined as the target time period; where YG q =(SYG j , EMG j ); SMG j -SYG j =c1 ZC; YG h =(SMG j , EYG j ); EYG j -EMG j =c1 ZC; c1 is based on MG j The first extension coefficient determined by T; c1>1.

[0041] Specifically, in order to further shorten the charging time, after determining the longest critical period in MG, j The start time of the corresponding time period is extended forward by a period of time (c1 ZC), and MG j The corresponding end time is extended backward by the same length of time (c1 ZC), the candidate time period with the largest total power generation in the two updated time periods is determined as the target time period, that is, the total charging time required is the shortest. The length of time extended forward or backward is c1 ZC, where c1 is based on MG j The first elongation factor determined by T. That is, MG j The larger the proportion of the corresponding duration to T, the smaller c1 is. Conversely, the larger it is.

[0042] In this embodiment, when the time corresponding to each key period cannot complete the time required to fully charge the battery pack at the optimal charging power Z, the key period with the longest time length is first selected, and the corresponding target time period is obtained after extending the key period forward or backward for a period of time, so that the charging time corresponding to the obtained target time period is the shortest. That is, the longer the solar cell group charges the target building group, the less city electricity can be used during the low electricity consumption period, thereby improving the utilization rate of clean resources.

[0043] In an exemplary embodiment of the present application, the step S222 further includes:

[0044] S2224, if G is empty, obtain the target window MC, and use MC as the sliding window, slide MC along the X-axis direction corresponding to the power generation curve according to the set sliding step Δd, so as to obtain the corresponding sliding total power list HD=(HD1, HD2, ..., HD x ,…,HD y ); x = 1, 2, ..., y; where y is the total amount of sliding power; HD x The time period SD corresponding to the sliding window sliding at the xth sliding step length x The total amount of electricity obtained according to the production power curve.

[0045] Where MC=c2 ZC; c2 is the second extension coefficient determined based on C and Z; c1<c2.

[0046] S2225, taking the time period corresponding to MAX(HD) as the target time period; wherein MAX() is a preset maximum value determination function.

[0047] Specifically, if G is empty, it means that within T, the average power corresponding to any minute is less than the optimal charging power Z. At this time, in order to reduce the charging time as much as possible, MC is first determined based on c2 and ZC, and MC is used as a sliding window. According to the set sliding step Δd, it slides along the X-axis direction corresponding to the capacity power curve to obtain a number of sliding total power. Here, MC is the predicted charging completion time. If the corresponding total power is greater within a certain sliding period, it means that if the start time of the period is used as the start time of the battery charging, the time required may be shorter. Therefore, the time period corresponding to MAX (HD) is used as the target time period.

[0048] It should be noted that c2 is a second elongation coefficient determined according to C and Z. If C is closer to Z as a whole, c2 is smaller, and vice versa. However, c1<c2.

[0049] In this embodiment, within T, the average power corresponding to any minute is less than the optimal charging power Z. At this time, according to the predicted charging completion time, the set sliding step Δd is slid along the X-axis direction corresponding to the capacity power curve, and the time period with the larger total power in a certain time period is selected as the target time period, so as to minimize the charging time required for the solar cell group to charge the battery. That is, the longer the solar cell group charges the target building group, the less city electricity can be used during the low electricity consumption period, and the utilization rate of clean resources can be improved.

[0050] In an exemplary embodiment of the present application, after step S210, the method further includes:

[0051] S230, if PC<α f(ΔSOC), the solar cell group is controlled to charge the battery group within T; and the mains port is controlled to supply power to the target building complex within T.

[0052] Specifically, if PC<α f(ΔSOC), it means that the total power generation of the solar cell group in the T time period is less than the current power shortage of the battery group. At this time, the solar cell group is controlled to charge the battery group within T; and the mains port is controlled to supply power to the target building group within T. So that the battery group can obtain as much power as possible within T. In order to use the battery to supply power to the target building group during the non-low power consumption period.

[0053] In an exemplary embodiment of the present application, after step S100, the method further includes:

[0054] S400, if the current power level of each storage battery reaches the corresponding upper power limit value; then control the solar cell group and the mains power port to supply power to the target building complex within T.

[0055] Specifically, if the current power of each storage battery reaches the corresponding power upper limit, that is, there is no need to use the solar cell group to charge the storage battery group, at this time, the solar cell group and the mains port are controlled to supply power to the target building group within T, so as to use as little mains power as possible during the low power consumption period, and make full use of clean energy.

[0056] An embodiment of the present application further provides a computer program product, which includes program code. When the program product is run on an electronic device, the program code is used to enable the electronic device to execute the steps of the method according to various exemplary embodiments of the present application described above in this specification.

[0057] In addition, although the steps of the method in the present application 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.

[0058] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software, or by combining software with necessary hardware. Therefore, the technical solution according to the implementation method of the present application 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 method of the present application.

[0059] In an exemplary embodiment of the present application, an electronic device capable of implementing the above method is also provided.

[0060] Those skilled in the art will appreciate that various aspects of the present application may be implemented as a system, method or program product. Therefore, various aspects of the present application may be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to as "circuit", "module" or "system" herein.

[0061] The electronic device according to this embodiment of the present application is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0062] The electronic device is presented in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: the at least one processor mentioned above, the at least one storage device mentioned above, and a bus connecting different system components (including storage devices and processors).

[0063] The storage stores program codes, which can be executed by the processor, so that the processor executes the steps described in the above “Exemplary Method” section of this specification according to various exemplary embodiments of the present application.

[0064] The memory may include readable media in the form of volatile memory, such as random access memory (RAM) and / or cache memory, and may further include read only memory (ROM).

[0065] The storage may also include a program / utility having a set (at least one) of program modules, such program modules 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.

[0066] The bus may represent one or more of several types of bus structures including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures.

[0067] The electronic device may also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may communicate with one or more devices that enable a user to interact with the electronic device, and / or may communicate with any device (e.g., routers, modems, etc.) that enables the electronic device to communicate with one or more other computing devices. This communication may be performed through an input / output (I / O) interface. In addition, the electronic device 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) through a network adapter. As shown in the figure, the network adapter communicates with other modules of the electronic device through a bus. 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, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0068] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software, or by combining software with necessary hardware. Therefore, the technical solution according to the implementation method of the present application 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 method of the present application.

[0069] In an exemplary embodiment of the present application, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present specification is stored. In some possible implementations, various aspects of the present application can also be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary implementations of the present application described in the above "Exemplary Method" section of the present specification.

[0070] The program product may adopt any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, a system, device or component of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0071] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which 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. Readable signal media 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.

[0072] The program code embodied on the readable 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.

[0073] Program code for performing the operations of the present application 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).

[0074] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present application, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0075] It should be noted that, although several modules or units of the equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present application, 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 being embodied by multiple modules or units.

[0076] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A numerical simulation and energy flow optimization method for coupled networks in an energy interconnection mode based on demand-side load, It is characterized in that The method is applied to a target charging system; the target charging system comprises a server and a coupling network in an energy interconnection mode; the coupling network in the energy interconnection mode comprises a solar cell group, a battery group and a mains port; wherein the solar cell group is used to charge the battery group or to supply power to a target building group; the battery group is used to supply power to a target building group; the mains port is used to supply power to a target building group; the server is used to perform the following steps: S100, whenever a signal is received that the mains port enters a target state, and the mains port is not currently used to power the target building group; the current power of each battery in the battery pack is obtained; the target state is that the power generation corresponding to the mains port is greater than the power demand corresponding to the mains port; the signal that the mains port enters the target state includes the predicted duration T of the target state; S200, if the current power of any storage battery does not reach the corresponding power upper limit value, control the solar cell group to determine the target time period according to a preset time period determination method; S300, controlling the solar cell group to charge the storage battery group with the start time of the target time period as the charging start time, until the current power of each storage battery in the storage battery group reaches the corresponding power upper limit value, and controlling the solar cell group to supply power to the target building group during the time other than charging the storage battery group within T; and controlling the mains power port to supply power to the target building group within T; The method for determining the preset time period includes: S210, obtaining the average power generated by the solar cell group per minute within T to obtain a corresponding power generation curve C; S220, determining a target time period according to C and the current power shortage f (ΔSOC) of the battery pack; The step S220 includes: S221, if PC ≥ α*f(ΔSOC), then according to C and the optimal charging power Z corresponding to the battery pack, the initial time period list G = (G 1 , G 2 , …, G i , …, G n ), i=1, 2, ..., n, where n is the number of initial time periods; G i is the i-th initial period; G i =(SG i ,EG i );SG i G i The corresponding start time; EG i G i The corresponding end time; the solar cell group is in G i The average power generation per minute in T is greater than Z; PC is the total power generation of the solar cell group in T; α is the power conversion efficiency; S222, determining a target time period according to G and a preset fusion time interval ΔA; The step S222 comprises: S2221, if G is not empty, then traverse G, if SG i+1 -EG i <ΔA, then for G i and G i+1 Fusion is performed to obtain the key period list set MG=(MG 1 ,MG 2 , …, MG j , …, MG m );j=1,2,…,m;where m is the number of critical periods; MG j =(SMG j , EMG j ); SMG j For MG j Corresponding start time; EMG j For MG j The corresponding end time; S2222, if EMG j -SMG j ≥ZC+ZY, then MG j Determined as the target time period; ZC is the time required for the battery pack to be fully charged at the optimal charging power Z; ZY is the reserved charging time; After step S2221, the method further includes: S2223, if each corresponding time length in MG is less than the sum of ZC and ZY, determine the target time period according to the key time period with the longest corresponding time length in MG; The step S2223 includes: S22231, if each corresponding time length in MG is less than the sum of ZC and ZY, and MG j It is the key period with the longest duration in MG; S22232, according to MG j and ZC, obtain the list of time periods to be selected YG=(YG q , YG h ), the selected time period with the largest total power generation in YG is determined as the target time period; where YG q =(SYG j , EMG j ); SMG j -SYG j =c 1 *ZC;YG h =(SMG j , EYG j ); EYG j -EMG j =c 1 *ZC;c 1 According to MG j The first elongation coefficient determined by T; c 1 >1; The step S222 further includes: S2224, if G is empty, obtain the target window MC, and use MC as the sliding window, slide MC along the X-axis direction corresponding to the production power curve according to the set sliding step Δd to obtain the corresponding sliding total power list HD=(HD 1 , HD 2 ,…,HD x ,…,HD y ); x = 1, 2, ..., y; where y is the total amount of sliding power; HD x The time period SD corresponding to the sliding window sliding at the xth sliding step length x The total amount of electricity obtained according to the power curve of the production capacity; S2225, taking the time period corresponding to MAX(HD) as the target time period; wherein MAX() is a preset maximum value determination function; MC=c 2 *ZC;c 2 is the second elongation coefficient determined based on C and Z; c 1 <c 2 .

2. According to claim 1, the numerical simulation and energy flow optimization method of the coupling network in the energy interconnection mode based on the demand side load, It is characterized in that After step S210, the method further includes: S230, if PC<α*f(ΔSOC), then control the solar cell group to charge the battery group within T; and control the mains port to supply power to the target building complex within T.

3. According to claim 1, the numerical simulation and energy flow optimization method of the coupling network in the energy interconnection mode based on the demand side load, It is characterized in that After step S100, the method further includes: S400, if the current power level of each storage battery reaches the corresponding upper power limit value; then control the solar cell group and the mains power port to supply power to the target building complex within T.

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