Scheduling method and scheduling device of optical storage integrated system and electronic equipment

Abstract

The invention provides a scheduling method and a scheduling device for an optical storage integrated system, and electronic equipment. The method comprises the following steps: a first acquisition step: acquiring a charge state sequence of the optical storage integrated system; a first determination step: at least according to the charge state sequence and a first preset relationship, obtaining an electricity purchase cost sequence at the current moment; a second determination step: obtaining an optimal power purchase cost matrix at least according to a plurality of power purchase cost sequences at the current moment; and a control step: performing scheduling control on the optical storage integrated system according to the optimal power purchase cost matrix. Wherein the first preset relation can avoid iterative operation of different charge states, so that the time complexity of a dynamic planning algorithm in the scheduling method is reduced, and the algorithm efficiency is further improved; the problem that in the prior art, an optical storage integrated system is limited by computing power complexity, optical storage integrated scheduling with the global lowest electricity purchase cost cannot be achieved, and economic benefits of clients can be maximized is solved.

Description

Technical Field

[0001] The present application relates to the technical field of scheduling of an integrated photovoltaic and storage system, and in particular to a scheduling method, a scheduling device, a computer-readable storage medium, and an electronic device for an integrated photovoltaic and storage system. Background Art

[0002] At present, photovoltaic systems use solar energy to generate electricity, which greatly reduces carbon emissions and customers' electricity costs. However, photovoltaic power generation is greatly affected by the weather and has great volatility and randomness. The energy storage system can solve this problem very well. Therefore, optimizing the control of photovoltaic storage integration can effectively improve the overall economic benefits of the system. Distributed photovoltaic and energy storage integrated power stations are currently in the early stages of industry development, and the methods of photovoltaic energy storage integrated scheduling have not been deeply developed. The current mainstream scheduling methods are as follows: Based on the principle of maximizing photovoltaic consumption, when photovoltaic power generation exceeds the load demand power, the energy storage is charged, and when the photovoltaic load does not meet the load demand power, the energy storage is discharged. The charging and discharging control of energy storage only considers photovoltaic power generation and load demand, and does not consider the current electricity price level; heuristic algorithms such as "genetic algorithm" and "simulated return algorithm" are used to optimize the charging and discharging strategy of energy storage, comprehensively consider photovoltaic power generation, load demand, and electricity price factors, and take the lowest "electricity purchase cost" of customers from the power grid as the optimization goal, and take the charging and discharging power of energy storage as the control variable.

[0003] The above methods have some defects: the energy storage system does not take electricity price factors into consideration and cannot effectively improve the economic benefits of the entire system and reduce customers' electricity costs; although heuristic algorithms are used to optimize economic benefits, heuristic algorithms are usually limited by computing power and cannot achieve global optimality, but can only achieve local optimality. Summary of the invention

[0004] The present application provides a scheduling method, a scheduling device, a computer-readable storage medium and an electronic device for an integrated photovoltaic and storage system, so as to solve the problem in the related art that the integrated photovoltaic and storage system is limited by the computing power complexity and cannot achieve the integrated photovoltaic and storage scheduling with the lowest global electricity purchase cost, so as to help customers maximize economic benefits.

[0005] According to one aspect of the present application, a scheduling method for an integrated photovoltaic and storage system is provided, comprising the following steps: a first acquisition step: acquiring a state of charge sequence of the integrated photovoltaic and storage system; a first determination step: obtaining a sequence of electricity purchase costs at a current moment based at least on the state of charge sequence and a first preset relationship; a second determination step: obtaining an optimal electricity purchase cost matrix based at least on a plurality of the electricity purchase cost sequences at the current moment; and a control step: scheduling and controlling the integrated photovoltaic and storage system based on the optimal electricity purchase cost matrix.

[0006] Optionally, obtaining the electricity purchase cost sequence at the current moment at least based on the charge state sequence and the first preset relationship includes: obtaining preset parameters of the photovoltaic storage integrated system within a preset time period, the preset parameters including a power generation power sequence, a load power sequence and an hourly electricity price sequence; obtaining the electricity purchase cost sequence at the current moment at least based on the preset parameters, the charge state sequence and the first preset relationship.

[0007] Optionally, obtaining the charge state sequence of the integrated photovoltaic and storage system includes: obtaining the charge state of the integrated photovoltaic and storage system at multiple first preset moments, with a first preset interval between adjacent first preset moments; and obtaining the charge state sequence based on the multiple charge states and a discretization algorithm.

[0008] Optionally, obtaining the electricity purchase cost sequence at the current moment at least based on the state of charge sequence and the first preset relationship includes: obtaining a state of charge matrix based on the state of charge sequence and the first preset relationship; obtaining a charge and discharge power matrix at the current moment based on the state of charge matrix and a second preset relationship; obtaining the electricity purchase cost sequence at the current moment based on the charge and discharge power matrix and the preset parameters.

[0009] Optionally, obtaining the optimal electricity purchasing cost matrix based on at least multiple electricity purchasing cost sequences at the current moment includes: obtaining the optimal electricity purchasing cost sequence at a third preset moment, the third preset moment being a moment before the current moment; obtaining the optimal electricity purchasing cost sequence at the current moment based on the optimal electricity purchasing cost sequence at the third preset moment and the electricity purchasing cost sequence at the current moment, the optimal electricity purchasing cost sequence at the current moment being composed of the minimum values ​​of the electricity purchasing costs under each of the charge states in the sum sequence, the sum sequence being the sum of the optimal electricity purchasing cost sequence at the third preset moment and the electricity purchasing cost sequence at the current moment; obtaining the optimal electricity purchasing cost matrix based on multiple optimal electricity purchasing cost sequences at the current moment.

[0010] Optionally, the scheduling method also includes: a second acquisition step: acquiring a time series of the integrated photovoltaic and storage system, the time series including multiple second preset moments, and a second preset interval between adjacent second preset moments; a judgment step: in the process of executing the second determination step, judging whether the current moment is the last moment of the time series; a loop step: when the judgment result of the judgment step indicates no, repeating the second determination step until stopping when the judgment result indicates yes.

[0011] Optionally, the scheduling method further includes: obtaining an optimal charging and discharging power sequence at the current moment according to the optimal electricity purchase cost sequence at each of the third preset moments and the electricity purchase cost sequence at the current moment.

[0012] According to another aspect of the present application, a scheduling device for an integrated photovoltaic and storage system is provided, comprising: a first acquisition module, used to execute an acquisition step: acquiring a charge state sequence and a time series of the integrated photovoltaic and storage system; a first determination module, used to execute a first determination step: obtaining a power purchase cost sequence at the current moment based at least on the charge state sequence and a first preset relationship; a second determination module, used to execute a second determination step: obtaining an optimal power purchase cost sequence based at least on a plurality of power purchase cost matrices at the current moment; and a control module, used to execute a control step: scheduling and controlling the integrated photovoltaic and storage system based on the optimal power purchase cost matrix.

[0013] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the above-mentioned scheduling method for the integrated optical-storage system.

[0014] According to another aspect of the present application, an electronic device is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include a scheduling method for executing the above-mentioned integrated photovoltaic and storage system.

[0015] Through the technical solution of the present application, a scheduling method for an integrated photovoltaic and storage system is provided. The method first executes a first acquisition step to acquire a state of charge sequence of the integrated photovoltaic and storage system, and then executes a first determination step to obtain a current electricity purchase cost sequence of the system at least according to the state of charge sequence and a first preset relationship, and then executes a second determination step according to multiple current electricity purchase cost sequences to obtain an optimal electricity purchase cost sequence, and finally executes a control step to schedule and control the system according to the optimal electricity purchase cost sequence; wherein the first preset relationship can avoid iterative operations on different states of charge, thereby reducing the time complexity of the dynamic programming algorithm in the scheduling method from O(mxn) to O(m), further improving the efficiency of the algorithm, solving the problem in the related art that the integrated photovoltaic and storage system is limited by the computing power complexity and cannot achieve the integrated photovoltaic and storage scheduling with the global lowest electricity purchase cost, thereby helping customers maximize economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0017] Figure 1 A hardware structure block diagram of a mobile terminal for executing a scheduling method for an integrated optical storage system provided in an embodiment of the present application is shown;

[0018] Figure 2 It is a flowchart of a scheduling method for an integrated photovoltaic and storage system provided according to an embodiment of the present application;

[0019] Figure 3 It is a flowchart of another scheduling method of an integrated photovoltaic and storage system provided according to an embodiment of the present application;

[0020] Figure 4 A structural block diagram of a scheduling device for an integrated photovoltaic and storage system provided according to an embodiment of the present application is shown.

[0021] The above drawings include the following reference numerals:

[0022] 102, processor; 104, memory; 106, transmission device; 108, input and output devices. DETAILED DESCRIPTION

[0023] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0024] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings 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 ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0025] 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 interchanged where appropriate, so as to describe the embodiments of the present application described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device 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.

[0026] In related technologies, the energy storage system does not take electricity price factors into consideration, and is unable to effectively improve the economic benefits of the entire system and reduce customers' electricity costs. Although heuristic algorithms are used to optimize economic benefits, heuristic algorithms are usually limited by computing power and cannot achieve global optimality, but can only achieve local optimality.

[0027] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0028] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 1 is a hardware structure block diagram of a mobile terminal for a scheduling method of an integrated photovoltaic and storage system according to an embodiment of the present invention. Figure 1 As shown, the mobile terminal may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0029] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the scheduling method of the integrated optical storage system in the embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, the above method is implemented. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the mobile terminal via a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The transmission device 106 is used to receive or send data via a network. The above-mentioned specific examples of the network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0030] Figure 2 1 is a flow chart of a scheduling method for an integrated photovoltaic and storage system according to an embodiment of the present application. Figure 2 As shown, in an embodiment of the present application, a scheduling method for an integrated photovoltaic and storage system is provided, such as Figure 2 As shown, the following steps are included:

[0031] First acquisition step S201: acquiring a state of charge sequence of the photovoltaic-storage integrated system;

[0032] First determination step S202: obtaining a current electricity purchase cost sequence based at least on the state of charge sequence and the first preset relationship;

[0033] Second determination step S203: obtaining an optimal electricity purchase cost matrix based on at least a plurality of the electricity purchase cost sequences at the current moment;

[0034] Control step S204: According to the above optimal power purchase cost matrix, the above photovoltaic energy storage integrated system is dispatched and controlled.

[0035] Through the above scheduling method, the first acquisition step is first executed to obtain the charge state sequence of the photovoltaic and storage integrated system, and then the first determination step is executed to obtain the power purchase cost sequence of the system at the current moment according to at least the charge state sequence and the first preset relationship, and then the second determination step is executed according to multiple power purchase cost sequences at the current moment to obtain the optimal power purchase cost sequence, and finally the control step is executed to schedule and control the above system according to the above optimal power purchase cost sequence; wherein the first preset relationship can avoid iterative operations on different charge states, thereby reducing the time complexity of the dynamic programming algorithm in the scheduling method from O(mxn) to O(m), further improving the algorithm efficiency, solving the problem in the related art that the photovoltaic and storage integrated system is limited by the computing power complexity and cannot achieve the photovoltaic and storage integrated scheduling with the global lowest power purchase cost, thereby helping customers maximize economic benefits.

[0036] In some optional embodiments, the above-mentioned acquisition of the charge state sequence of the photovoltaic and storage integrated system includes: acquiring the charge state of the above-mentioned photovoltaic and storage integrated system at multiple first preset moments, with a first preset interval between adjacent first preset moments; and obtaining the above-mentioned charge state sequence based on the multiple charge states and a discretization algorithm.

[0037] In the above optional implementation, the charging state of the photovoltaic and storage integrated system corresponding to each of the above first preset moments is 0.5% + 0.5% n, where n is the number of first preset moments before the current first preset moment. For example, the charging state of the photovoltaic and storage integrated system corresponding to the first first preset moment is 0.5%, the charging state of the photovoltaic and storage integrated system corresponding to the second first preset moment is 0.5% + 0.5%, and the charging state of the photovoltaic and storage integrated system corresponding to the third first preset moment is 0.5% + 0.5% × 2, and so on. The state of charge of the photovoltaic and storage integrated system is discretized at intervals of 0.5%. Discretization can be performed using a discretization algorithm to generate a SOC sequence of 0% to 100% (SOC, state of change, SOC represents the battery charging and discharging state, 0 means full discharge, and 100 means full charge).

[0038] In some optional embodiments, the electricity purchase cost sequence at the current moment is obtained at least based on the above-mentioned state of charge sequence and the first preset relationship, including: obtaining preset parameters of the above-mentioned integrated photovoltaic and storage system within a preset time period, the above-mentioned preset parameters including a power generation power sequence, a load power sequence and an hourly electricity price sequence; obtaining the electricity purchase cost sequence at the current moment at least based on the above-mentioned preset parameters and the above-mentioned state of charge sequence and the first preset relationship.

[0039] In the above optional implementation manner, the above preset time period can be a day, 24 hours, to obtain the power generation sequence pv, load power sequence I and hourly electricity price sequence v of the photovoltaic storage integrated system within 24 hours; based on the above preset parameters, SOC sequence, total installed capacity of the system c, the first preset interval t and the above charge state sequence, the first preset relationship and the second preset relationship, the electricity purchase cost sequence at the current moment can be obtained.

[0040] In some optional embodiments, the above-mentioned obtaining of the electricity purchase cost sequence at the current moment based at least on the above-mentioned state of charge sequence and the first preset relationship includes: obtaining a state of charge matrix based on the above-mentioned state of charge sequence and the first preset relationship; obtaining a charge and discharge power matrix at the above-mentioned current moment based on the above-mentioned state of charge matrix and the second preset relationship; obtaining the electricity purchase cost sequence at the above-mentioned current moment based on the above-mentioned charge and discharge power matrix and the above-mentioned preset parameters.

[0041] In the above optional implementation manner, the first preset relationship includes Cartesian product and matrix calculation, and the state of charge matrix A at the current moment is obtained according to the above-mentioned state of charge sequence and Cartesian product and matrix calculation, and the Cartesian product and matrix calculation is: A=SOC×SOC; according to the above-mentioned state of charge matrix A at the current moment, the total installed capacity of the system c and the first preset interval t, the system energy storage charging and discharging power matrix P at the current moment is obtained, and the second preset relationship includes: P=Ac / t; according to the system energy storage charging and discharging power matrix P at the current moment, the power generation power sequence pv, the load power sequence I, and the hourly electricity price sequence v, the current moment The electricity purchase cost sequence Cost[i] is obtained, Cost[i]=(pv[i]+PI[i])·v[i].

[0042] In some optional embodiments, the optimal power purchasing cost sequence matrix is ​​obtained at least based on multiple power purchasing cost sequences at the current moment, including: obtaining the optimal power purchasing cost sequence at a third preset moment, the third preset moment being the moment before the current moment; obtaining the optimal power purchasing cost sequence at the current moment based on the optimal power purchasing cost sequence at the third preset moment and the power purchasing cost sequence at the current moment, the optimal power purchasing cost sequence at the current moment being composed of the minimum values ​​of the power purchasing costs under each of the above-mentioned charge states in the sum sequence, the sum sequence being the sum of the optimal power purchasing cost sequence at the third preset moment and the power purchasing cost sequence at the current moment; obtaining the optimal power purchasing cost matrix based on multiple optimal power purchasing cost sequences at the current moment.

[0043] In the above optional implementation, the optimal power purchase cost sequence dp[i][cost] at the current moment is obtained by adding the optimal power purchase cost sequence dp[i-1][cost] at the previous moment to the power purchase cost sequence Cost[i] at the current moment, and then comparing the power purchase costs under each SOC state, the minimum value is the optimal power purchase cost sequence at the current moment, dp[i][cost]=min(dp[i-1][cost]+Cost[i]), and multiple optimal power purchase cost sequences at the current moment constitute the optimal power purchase cost matrix within the preset time period. For example, when the time is calculated with a time interval of 1s, the third preset time is 1s, and the current time is 2s; when the time is calculated with a time interval of 3s, the third preset time is 1s, and the current time is 4s.

[0044] In some optional embodiments, the scheduling method further includes: a second acquisition step: acquiring a time series of the integrated photovoltaic and storage system, the time series including a plurality of second preset moments, and a second preset interval between adjacent second preset moments; a judgment step: in the process of executing the second determination step, judging whether the current moment is the last moment of the time series; a loop step: in the case where the judgment result of the judgment step indicates no, repeating the second determination step until stopping when the judgment result indicates yes.

[0045] In the above optional implementation, the above second preset moment can be discretized every hour at the second preset interval for the next 24 hours, and the discretization process can be performed using a discretization algorithm to generate a time series T including multiple second preset moments. In the process of obtaining the optimal electricity purchase cost sequence at the current moment, the current moment i needs to be compared with the last second preset moment in the time series T to determine whether the current moment i exceeds the last second preset moment. If the current moment i does not exceed the last second preset moment, continue to obtain the optimal electricity purchase cost sequence of the next current moment. If the current moment i exceeds the last second preset moment, stop obtaining the optimal electricity purchase cost sequence. According to the optimal electricity purchase cost sequences of the above multiple current moments i, the final optimal electricity purchase cost matrix within the next 24 hours is obtained, and the system is scheduled according to the above optimal electricity purchase cost matrix, thereby achieving the lowest electricity purchase cost for users.

[0046] In some optional embodiments, the scheduling method further includes: obtaining the optimal charging and discharging power sequence at the current moment according to the optimal electricity purchase cost sequence at the third preset moment and the electricity purchase cost sequence at the current moment.

[0047] In the above optional implementation, in the process of obtaining the above state of charge sequence, the optimal energy storage state of charge at each first preset moment is obtained, and the sum of the optimal power purchase cost sequence dp[i-1][cost] at each third preset moment and the power purchase cost sequence Cost[i] at the current moment is recursively calculated to obtain the optimal charge and discharge power sequence dp[i][start soc] of the system energy storage at the current moment, dp[i][start soc] = argmin(dp[i-1][cost]+cost[i]), where argmin represents the minimum value of (dp[i-1][cost]+cost[i]). The above calculation is performed for each current moment to obtain the optimal charge and discharge power matrix in the next 24 hours. The optimal dispatch control is performed according to the optimal power purchase cost matrix and the optimal charge and discharge power matrix control system.

[0048] For example, Figure 3As shown, first obtain the preset parameters, including the power generation power sequence pv, the load power sequence I and the hourly electricity price sequence v; initialize the data, discretize the state of charge of the photovoltaic storage integrated system at intervals of 0.5%, and the discretization can be performed using a discretization algorithm to generate a 0% to 100% SOC sequence, and discretize the next 24 hours every 1 hour at a second preset interval. The discretization can be performed using a discretization algorithm to generate a time series T including multiple second preset moments; traverse the time series T, and calculate the state of charge matrix A at the current moment according to the above-mentioned state of charge sequence and the Cartesian product and matrix obtained at the current moment, and the Cartesian product and matrix calculation: A = SOC × SOC; obtain the system energy storage charging and discharging power matrix P at the current moment according to the above-mentioned state of charge matrix A at the current moment, the total installed capacity c of the system and the first preset interval t, and the second preset relationship includes: P = Ac / t; according to the system energy storage charging and discharging at the current moment The power matrix P, the power generation power sequence pv, the load power sequence I, and the hourly electricity price sequence v are used to obtain the current power purchase cost sequence Cost[i], Cost[i] = (pv[i] + PI[i]) · v[i]. The optimal power purchase cost sequence dp[i][cost] at the current moment is obtained by adding the optimal power purchase cost sequence dp[i-1][cost] at the previous moment to the power purchase cost sequence Cost[i] at the current moment. Then, by comparing the power purchase costs under each SOC state, the minimum value is the optimal power purchase cost sequence at the current moment, dp[i][cost] = min(dp[i-1][cost] + Cost[i]). The optimal power purchase cost sequence dp[i-1][cost] at each third preset moment and the sum of the power purchase cost sequence Cost[i] at the current moment are recursively calculated to obtain the optimal charging and discharging power sequence dp[i][start] of the system energy storage at the current moment. soc], dp[i][startsoc] = argmin(dp[i-1][cost] + cost[i]), where i is a certain moment in the time series. It is determined whether the current moment i is a moment exceeding the time series T. When the judgment result is no, the step of traversing the time series T is continued. When the judgment result is yes, the optimal power purchase cost matrix and the optimal charging and discharging power matrix are output, and the optimal dispatch control is performed according to the above two optimal matrix control systems.

[0049] The present application also provides a scheduling device for an integrated photovoltaic storage system in an embodiment, which is used to implement the above-mentioned embodiments and preferred implementations thereof, and will not be repeated hereafter. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0050] Figure 4 Schematic diagram of a scheduling device for an integrated photovoltaic and storage system according to an embodiment of the present application. Figure 4 As shown, a scheduling device for an integrated photovoltaic and storage system is provided, including: a first acquisition module 100, used to execute an acquisition step: acquiring a charge state sequence and a time series of the integrated photovoltaic and storage system; a first determination module 200, used to execute a first determination step: obtaining a power purchase cost sequence at the current moment based on at least the above-mentioned charge state sequence and a first preset relationship; a second determination module 300, used to execute a second determination step: obtaining an optimal power purchase cost matrix based on at least a plurality of the above-mentioned power purchase cost sequences at the current moment; and a control module 400, used to execute a control step: scheduling and controlling the integrated photovoltaic and storage system according to the above-mentioned optimal power purchase cost matrix.

[0051] The first acquisition module first executes the first acquisition step to acquire the state of charge sequence of the photovoltaic and storage integrated system, the first determination module then executes the first determination step, and obtains the power purchase cost sequence of the system at the current moment according to at least the above-mentioned state of charge sequence and the first preset relationship, the second determination module then executes the second determination step according to multiple power purchase cost sequences at the current moment to obtain the optimal power purchase cost matrix, and the control module finally executes the control step to schedule and control the above-mentioned system according to the above-mentioned optimal power purchase cost matrix; wherein the first preset relationship can avoid iterative operations on different states of charge, thereby reducing the time complexity of the dynamic programming algorithm in the scheduling method from O(mxn) to O(m), further improving the algorithm efficiency, solving the problem in the related art that the photovoltaic and storage integrated system is limited by the computing power complexity and cannot achieve the photovoltaic and storage integrated scheduling with the global lowest power purchase cost, and helping customers maximize economic benefits.

[0052] In some optional embodiments, the first determination module includes a first sub-acquisition module and a first sub-determination module, wherein the first sub-acquisition module is used to obtain preset parameters of the above-mentioned integrated photovoltaic and storage system within a preset time period, and the above-mentioned preset parameters include a power generation power sequence, a load power sequence and an hourly electricity price sequence; the first sub-determination module is used to obtain the electricity purchase cost sequence at the current moment based on at least the above-mentioned preset parameters, the above-mentioned charge state sequence and the first preset relationship.

[0053] In some optional embodiments, the acquisition module includes a second sub-acquisition module and a second sub-determination module, wherein the second sub-acquisition module is used to acquire the charge state of the above-mentioned integrated photovoltaic and storage system at multiple first preset moments, and there is a first preset interval between adjacent first preset moments; the second sub-determination module is used to obtain the above-mentioned charge state sequence based on the multiple above-mentioned charge states and a discretization algorithm.

[0054] In some optional embodiments, the first determination module includes a third sub-determination module, a fourth sub-determination module and a fifth sub-determination module, wherein the third sub-determination module is used to obtain a state of charge matrix based on the state of charge sequence and the first preset relationship; the fourth sub-determination module is used to obtain the charge and discharge power matrix at the current moment based on the state of charge matrix and the second preset relationship; the fifth sub-determination module is used to obtain the electricity purchase cost sequence at the current moment based on the charge and discharge power matrix and the preset parameters.

[0055] In some optional implementations, the second determination module includes a third sub-acquisition module, a sixth sub-determination module and a seventh sub-determination module, wherein the third sub-acquisition module is used to acquire the optimal electricity purchasing cost sequence at a third preset moment, and the third preset moment is the moment before the current moment; the sixth sub-determination module is used to obtain the optimal electricity purchasing cost sequence at the current moment based on the optimal electricity purchasing cost sequence at the third preset moment and the electricity purchasing cost sequence at the current moment, the optimal electricity purchasing cost sequence at the current moment being composed of the minimum values ​​of the electricity purchasing costs under the above-mentioned charge states in the sum sequence, and the sum sequence is the sum of the optimal electricity purchasing cost sequence at the third preset moment and the electricity purchasing cost sequence at the current moment; the seventh sub-determination module is used to obtain the optimal electricity purchasing cost matrix based on multiple optimal electricity purchasing cost sequences at the current moments.

[0056] In some optional embodiments, the scheduling device further includes a second acquisition module, a judgment module and a loop module, wherein the second acquisition module is used to acquire the time series of the integrated photovoltaic and storage system, the time series includes multiple second preset moments, and there is a second preset interval between adjacent second preset moments; the judgment module is used to judge whether the current moment is the last moment of the time series during the execution of the second determination step; the loop module is used to repeat the second determination step if the judgment result of the judgment step indicates no, and stop if the judgment result indicates yes.

[0057] In some optional embodiments, the sixth sub-determination module includes an eighth sub-determination module, and the eighth sub-determination module is used to obtain the optimal charging and discharging power sequence at the above-mentioned current moment based on the above-mentioned optimal electricity purchase cost sequence at each of the above-mentioned third preset moments and the above-mentioned electricity purchase cost sequence at the above-mentioned current moment.

[0058] An embodiment of the present application further provides a computer-readable storage medium, which includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the above-mentioned scheduling method for the integrated optical-storage system.

[0059] Specifically, the scheduling method of the photovoltaic storage integrated system includes:

[0060] First acquisition step S201: acquiring a state of charge sequence of the photovoltaic-storage integrated system;

[0061] First determination step S202: obtaining a current electricity purchase cost sequence based at least on the state of charge sequence and the first preset relationship;

[0062] Second determination step S203: obtaining an optimal electricity purchase cost matrix based on at least a plurality of the electricity purchase cost sequences at the current moment;

[0063] Control step S204: According to the above optimal power purchase cost matrix, the above photovoltaic energy storage integrated system is dispatched and controlled.

[0064] An embodiment of the present invention provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements at least the scheduling method for the integrated photovoltaic and storage system.

[0065] Specifically, the scheduling method of the photovoltaic storage integrated system includes:

[0066] First acquisition step S201: acquiring a state of charge sequence of the photovoltaic-storage integrated system;

[0067] First determination step S202: obtaining a current electricity purchase cost sequence based at least on the state of charge sequence and the first preset relationship;

[0068] Second determination step S203: obtaining an optimal electricity purchase cost matrix based on at least a plurality of the electricity purchase cost sequences at the current moment;

[0069] Control step S204: According to the above optimal power purchase cost matrix, the above photovoltaic energy storage integrated system is dispatched and controlled.

[0070] From the above description, it can be seen that the above embodiments of the present application achieve the following technical effects:

[0071] 1) Through the technical solution of the present application, a scheduling method for an integrated photovoltaic and storage system is provided, firstly, a first acquisition step is executed to acquire a state of charge sequence of the integrated photovoltaic and storage system, then a first determination step is executed, and a current electricity purchase cost sequence of the system is obtained at least according to the state of charge sequence and a first preset relationship, then a second determination step is executed according to multiple current electricity purchase cost sequences to obtain an optimal electricity purchase cost matrix, and finally a control step is executed to schedule and control the system according to the optimal electricity purchase cost matrix; wherein the first preset relationship can avoid iterative operations on different states of charge, thereby reducing the time complexity of the dynamic programming algorithm in the scheduling method from O(mxn) to O(m), further improving the efficiency of the algorithm, solving the problem in the related art that the integrated photovoltaic and storage system is limited by the computing power complexity and cannot achieve the integrated photovoltaic and storage scheduling with the global lowest electricity purchase cost, thereby helping customers maximize economic benefits.

[0072] 2) Through the technical solution of the present application, a scheduling device for an integrated photovoltaic and storage system is provided, wherein the first acquisition module first executes a first acquisition step to acquire a state of charge sequence of the integrated photovoltaic and storage system, the first determination module then executes the first determination step to obtain a current electricity purchase cost sequence of the system at least according to the state of charge sequence and the first preset relationship, the second determination module then executes the second determination step according to multiple current electricity purchase cost sequences to obtain an optimal electricity purchase cost matrix, and the control module finally executes a control step to schedule and control the system according to the optimal electricity purchase cost matrix; wherein the first preset relationship can avoid iterative operations on different states of charge, thereby reducing the time complexity of the dynamic programming algorithm in the scheduling method from O(mxn) to O(m), further improving the efficiency of the algorithm, solving the problem in the related art that the integrated photovoltaic and storage system is limited by the computing power complexity and cannot achieve the integrated photovoltaic and storage scheduling with the global lowest electricity purchase cost, thereby helping customers maximize economic benefits.

[0073] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0074] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A scheduling method for an integrated photovoltaic and storage system, characterized in that: The following steps are involved: The first acquisition step: acquiring a state of charge sequence of the photovoltaic and energy storage integrated system; The first determination step: obtaining a current electricity purchase cost sequence based at least on the state of charge sequence and the first preset relationship; The second determination step: obtaining an optimal electricity purchase cost matrix based on at least a plurality of electricity purchase cost sequences at the current moment; Control step: According to the optimal electricity purchase cost matrix, the photovoltaic storage integrated system is dispatched and controlled.

2. The scheduling method according to claim 1, characterized in that: The step of obtaining the electricity purchase cost sequence at the current moment at least according to the state of charge sequence and the first preset relationship includes: Obtaining preset parameters of the photovoltaic energy storage integrated system within a preset time period, wherein the preset parameters include a power generation sequence, a load power sequence, and an hourly electricity price sequence; The electricity purchase cost sequence at the current moment is obtained at least according to the preset parameters, the charge state sequence and the first preset relationship.

3. The scheduling method according to claim 2, characterized in that: The method of acquiring the state of charge sequence of the photovoltaic energy storage integrated system comprises: Acquire the charge state of the photovoltaic and energy storage integrated system at a plurality of first preset moments, with a first preset interval between adjacent first preset moments; The state of charge sequence is obtained according to the plurality of states of charge and a discretization algorithm.

4. The scheduling method according to claim 2, characterized in that: The step of obtaining the electricity purchase cost sequence at the current moment at least according to the state of charge sequence and the first preset relationship includes: Obtaining a state of charge matrix according to the state of charge sequence and a first preset relationship; According to the state of charge matrix and the second preset relationship, the charge and discharge power matrix at the current moment is obtained; according to the charge and discharge power matrix and the preset parameters, the electricity purchase cost sequence at the current moment is obtained.

5. The scheduling method according to claim 1, characterized in that: The step of obtaining an optimal electricity purchase cost matrix based on at least a plurality of electricity purchase cost sequences at the current moment includes: Obtaining an optimal electricity purchase cost sequence at a third preset moment, where the third preset moment is a moment before the current moment; According to the optimal electricity purchase cost sequence at the third preset moment and the electricity purchase cost sequence at the current moment, the optimal electricity purchase cost sequence at the current moment is obtained, wherein the optimal electricity purchase cost sequence at the current moment is composed of the minimum value of the electricity purchase cost at each of the charge states in the sum sequence, and the sum sequence is the sum of the optimal electricity purchase cost sequence at the third preset moment and the electricity purchase cost sequence at the current moment; The optimal electricity purchasing cost matrix is ​​obtained according to a plurality of optimal electricity purchasing cost sequences at the current moment.

6. The scheduling method according to claim 1, characterized in that: The scheduling method further includes: A second acquisition step: acquiring a time sequence of the photovoltaic and energy storage integrated system, wherein the time sequence includes a plurality of second preset moments, and a second preset interval is provided between adjacent second preset moments; Determining step: during the execution of the second determining step, determining whether the current moment is the last moment of the time series; Loop step: when the judgment result of the judgment step indicates no, repeatedly execute the second determination step until stopping when the judgment result indicates yes.

7. The scheduling method according to claim 5, characterized in that: The scheduling method further includes: According to the optimal electricity purchase cost sequence at each of the third preset moments and the electricity purchase cost sequence at the current moment, an optimal charging and discharging power sequence at the current moment is obtained.

8. A dispatching device for an integrated photovoltaic and storage system, characterized in that: include: The first acquisition module is used to execute the acquisition step: acquiring the charge state sequence and time sequence of the photovoltaic energy storage integrated system; A first determination module is used to perform a first determination step: obtaining a current electricity purchase cost sequence based at least on the state of charge sequence and a first preset relationship; A second determination module is used to perform a second determination step: obtaining an optimal electricity purchase cost matrix based on at least a plurality of electricity purchase cost sequences at the current moment; The control module is used to execute the control step: according to the optimal power purchase cost matrix, the photovoltaic storage integrated system is dispatched and controlled.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the scheduling method of the integrated photovoltaic and energy storage system according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include a method for executing the scheduling method of the integrated photovoltaic storage system described in any one of claims 1 to 7.

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