Energy saving and power saving control method, device, computer equipment and storage medium

Abstract

The present application relates to an energy-saving and power-saving control method, device, computer equipment and storage medium, and belongs to the field of power grid technology. The method includes: obtaining historical power supply data information on the power supply side, and classifying the historical power supply data information on the power supply side based on the peak and valley time-of-use electricity price to obtain a target data set; according to the target data set, constructing a distributed energy-saving and power-saving control framework, the distributed energy-saving and power-saving control framework includes at least one control node generated based on the CPU; obtaining the predicted power supply required within the target time period; based on the required power supply, using the control node generated based on the CPU to control the energy storage equipment and / or power generation equipment corresponding to each control node. The present application aims to improve the efficiency and accuracy of energy-saving and power-saving control.

Description

Technical Field

[0001] The present application relates to the field of power grid technology, and in particular to an energy-saving and power-saving control method, device, computer equipment and storage medium. Background Art

[0002] At present, the price difference between peak and valley electricity is getting bigger and bigger, and the energy storage market facing the user side has broad prospects. In the early stage of building a power-saving energy storage system, it is urgent to propose a distribution model that is tailored to the electricity consumption characteristics of different regions and stages. Traditional energy storage distribution plans are often obtained by manually consulting regional electricity price policies and roughly calculating them based on electricity consumption characteristics. There is no uniformity and large errors, which makes it impossible to effectively control energy-saving nodes.

[0003] Therefore, there is an urgent need to propose an energy-saving and power-saving control method, device, computer equipment and storage medium that can improve the accuracy and efficiency of control efficiency. Summary of the invention

[0004] Based on this, it is necessary to provide an energy-saving and power-saving control method, device, computer equipment and storage medium that can improve the efficiency and accuracy of energy-saving and power-saving control in response to the above technical problems.

[0005] In one aspect, a method for energy saving and power saving control is provided, the method comprising:

[0006] Acquire historical power supply data information on the power supply side, and classify the historical power supply data information on the power supply side based on the peak and valley time-of-use electricity prices to obtain a target data set;

[0007] According to the target data set, a distributed energy-saving and power-saving control framework is constructed, wherein the distributed energy-saving and power-saving control framework includes at least one control node generated based on a CPU;

[0008] Obtain the predicted power supply required within the target time period;

[0009] Based on the required power supply, the control node generated based on the CPU is used to control the energy storage device and / or power generation device corresponding to each control node.

[0010] Optionally, historical power supply data information on the power supply side is obtained, and the historical power supply data information on the power supply side is classified based on the peak and valley time-of-use electricity prices, and the target data set obtained includes:

[0011] Acquire historical power supply data information of the power supply side in the target area, wherein the historical power supply data information of the power supply side includes at least power generation, energy storage, energy storage power generation, and power supply growth rate at multiple time nodes;

[0012] Obtain the time period corresponding to the peak and valley time-of-use electricity price in the target area;

[0013] Classify the historical power supply data information on the power supply side according to the collection time of the historical power supply data information on the power supply side and the time period to obtain a first data set and a second data set;

[0014] A first target data set is generated based on the first data set and the second data set.

[0015] Optionally, the method further includes:

[0016] Acquire historical power supply data information of the power supply side in the target area, wherein the historical power supply data information of the power supply side at least includes the location information of the power generation equipment and its corresponding maximum power generation, the location information of the energy storage equipment and its corresponding maximum storage capacity;

[0017] The power generation equipment is sorted in a positive order according to the maximum power generation, and the energy storage equipment is sorted in a reverse order according to the maximum storage capacity;

[0018] Based on the sorting order of the power generation equipment and the energy storage equipment, a one-to-one mapping relationship is formed between one power generation equipment and multiple energy storage equipment, and the formed mapping relationship is numbered according to the reverse sorting order of the energy storage equipment;

[0019] Based on the labeled mapping relationship, a second target data set is generated.

[0020] Optionally, building a distributed energy-saving and power-saving control framework according to the target data set includes:

[0021] The mapping relationship after the labeling is obtained, and the probability of forming a connection relationship between the target power generation device and each energy storage device is determined by using a probability function, wherein the probability function includes:

[0022]

[0023] in, represents the target power generation equipment, represents the target energy storage device, Indicates the historical connection times between the target energy storage device and the target power generation device. Indicates the target energy storage device The probability of forming a connection relationship with the target power generation equipment, Indicates a label;

[0024] In response to detecting that the probability value is greater than or equal to a preset threshold, the target power generation device and the target energy storage device are connected, and a first control node and a second control node generated based on the CPU are respectively set at the power generation device node and the energy storage device node, wherein the first control node is used to control the power generation of the power generation device, and the second control node is used to control the power generation of the energy storage device;

[0025] The distributed energy-saving and power-saving control framework is generated by connecting a plurality of control nodes generated based on the CPU via a general control node and based on a plurality of connection relationships and the general control node.

[0026] Optionally, a method for predicting the amount of power required within a target time period includes:

[0027] Constructing a power supply prediction model, the power supply prediction model comprising:

[0028]

[0029] in, It represents the ratio of power generation to energy storage power generation. represents the growth rate of power supply, Indicates time, represents the output value of the power supply prediction model;

[0030] The product of the output value of the power supply prediction model and a preset multiple is defined as the power supply required within the target time period.

[0031] Optionally, before using the control node generated based on the CPU to control the energy storage and / or power supply corresponding to each control node, the method further includes:

[0032] Construct an objective function and constraints, wherein the objective function includes:

[0033]

[0034] The constraints include:

[0035]

[0036] in, Indicates the loss value between the power-consuming equipment and the power-generating equipment. Indicates the loss value between the electrical equipment and the energy storage equipment. Indicates the loss value between the power generation equipment and the energy storage equipment, Represents the solution domain, which is used to describe the points with connection relationships in the distributed energy-saving and power-saving control framework. Indicates time, Represents the electricity cost, Represent the energy storage and power supply respectively, Represents the objective function.

[0037] Optionally, based on the required power supply, using the control node generated based on the CPU to control the energy storage device and / or power generation device corresponding to each control node includes:

[0038] Based on the required power supply, a power supply signal is sent to a line control node that meets a preset objective function value standard to control the energy storage device and / or the power generation device to supply power.

[0039] In another aspect, an energy-saving and power-saving control device is provided, the device comprising:

[0040] A data acquisition module is used to acquire historical power supply data information on the power supply side, and classify the historical power supply data information on the power supply side based on the peak and valley time-of-use electricity prices to obtain a target data set;

[0041] A construction module, used to construct a distributed energy-saving and power-saving control framework according to the target data set, wherein the distributed energy-saving and power-saving control framework includes at least one control node generated based on a CPU;

[0042] A prediction module, used to obtain the power supply required within the predicted target time period;

[0043] The control module is used to control the energy storage device and / or power generation device corresponding to each control node based on the required power supply amount and using the control node generated based on the CPU.

[0044] In another aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following steps are implemented:

[0045] Acquire historical power supply data information on the power supply side, and classify the historical power supply data information on the power supply side based on the peak and valley time-of-use electricity prices to obtain a target data set;

[0046] According to the target data set, a distributed energy-saving and power-saving control framework is constructed, wherein the distributed energy-saving and power-saving control framework includes at least one control node generated based on a CPU;

[0047] Obtain the predicted power supply required within the target time period;

[0048] Based on the required power supply, the control node generated based on the CPU is used to control the energy storage device and / or power generation device corresponding to each control node.

[0049] In another aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0050] Acquire historical power supply data information on the power supply side, and classify the historical power supply data information on the power supply side based on the peak and valley time-of-use electricity prices to obtain a target data set;

[0051] According to the target data set, a distributed energy-saving and power-saving control framework is constructed, wherein the distributed energy-saving and power-saving control framework includes at least one control node generated based on a CPU;

[0052] Obtain the predicted power supply required within the target time period;

[0053] Based on the required power supply, the control node generated based on the CPU is used to control the energy storage device and / or power generation device corresponding to each control node.

[0054] The above-mentioned energy-saving and power-saving control method, device, computer equipment and storage medium, the method includes: obtaining historical power supply data information on the power supply side, and classifying the historical power supply data information on the power supply side based on the peak and valley time-of-use electricity prices to obtain a target data set; according to the target data set, constructing a distributed energy-saving and power-saving control framework, the distributed energy-saving and power-saving control framework includes at least one control node generated based on the CPU; obtaining the predicted required power supply within the target time period; based on the required power supply, using the control node generated based on the CPU to control the energy storage equipment and / or power generation equipment corresponding to each control node. The present application aims to improve the efficiency and accuracy of energy-saving and power-saving control. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A diagram showing an application environment of an energy-saving and power-saving control method in an embodiment;

[0056] Figure 2 A schematic flow chart of an energy-saving and power-saving control method in one embodiment;

[0057] Figure 3 A structural block diagram of an energy-saving and power-saving control device in an embodiment;

[0058] Figure 4 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0060] It should be understood that in the description of the present application, unless the context clearly requires otherwise, words such as "include", "comprises", and the like throughout the specification should be interpreted as including rather than being exclusive or exhaustive; that is, as including but not limited to.

[0061] It should also be understood that the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of this application, unless otherwise specified, "plurality" means two or more.

[0062] It should be noted that the terms "S1", "S2", etc. are only used for the purpose of describing the steps, and do not specifically refer to the order or sequence, nor are they used to limit the present application. They are only for the convenience of describing the method of the present application, and cannot be understood as indicating the order of the steps. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in this field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present application.

[0063] The energy-saving and power-saving control method provided in this application can be applied to Figure 1 In the application environment shown, the terminal 102 communicates with the data processing platform set on the server 104 through the network, wherein the terminal 102 can be but not limited to various personal computers, laptops, smart phones, tablet computers and portable wearable devices, and the server 104 can be implemented by an independent server or a server cluster composed of multiple servers.

[0064] In one embodiment, Figure 2 As shown, a method for energy saving and power saving control is provided, and the method is applied to Figure 1 The terminal in is used as an example to illustrate, including the following steps:

[0065] S1: Obtain historical power supply data information on the power supply side, and classify the historical power supply data information on the power supply side based on peak and valley time-of-use electricity prices to obtain a target data set.

[0066] It should be noted that the target data set includes a first target data set and a second target data set, the first target data set refers to a power consumption data set, the second target data set refers to a structure data set, and the historical power supply data information on the power supply side includes at least power generation, energy storage, energy storage power generation, power supply growth rate, and power generation equipment location information and its corresponding maximum power generation, energy storage equipment location information and its corresponding maximum storage capacity at multiple time nodes;

[0067] In some specific implementations, historical power supply data information of the power supply side is obtained, and the historical power supply data information of the power supply side is classified based on the peak and valley time-of-use electricity prices, and the target data set obtained includes:

[0068] Obtain historical power supply data information on the power supply side of the target area, where the target area refers to an area within a certain range;

[0069] Obtain the time period corresponding to the peak and valley time-of-use electricity price in the target area, where the time period can be from 22:00 to 8:00 in the morning, which is determined according to the peak and valley time-of-use electricity price in the area;

[0070] According to the collection time of the historical power supply data information of the power supply side and the time period, the historical power supply data information of the power supply side is classified to obtain a first data set and a second data set, wherein the first data set and the second data set are data in the corresponding peak and valley time periods respectively;

[0071] A first target data set is generated based on the first data set and the second data set.

[0072] In some embodiments, the method further comprises:

[0073] Obtain historical power supply data information on the power supply side of the target area

[0074] The power generation equipment is sorted in forward order according to the maximum power generation, and the energy storage equipment is sorted in reverse order according to the maximum energy storage capacity. For example, if the maximum power generation capacity is 50, 45, 30, the order is 50, 45, 30, and if the maximum energy storage capacity is 50, 45, 30, the order is 30, 45, 50;

[0075] Based on the sorting order of power generation equipment and energy storage equipment, a one-to-one mapping relationship is formed between a power generation equipment and multiple energy storage equipment, and the formed mapping relationship is numbered according to the reverse sorting order of the energy storage equipment, that is, a power generation equipment can establish a connection relationship with multiple energy storage equipment for generating electricity for the energy storage equipment, and its number is based on the sorting order of the energy storage equipment, such as 30 is marked as 1, etc.;

[0076] Based on the labeled mapping relationship, a second target data set is generated.

[0077] S2: constructing a distributed energy-saving and power-saving control framework according to the target data set, wherein the distributed energy-saving and power-saving control framework includes at least one control node generated based on a CPU.

[0078] In some specific implementations, constructing a distributed energy-saving and power-saving control framework according to the target data set includes:

[0079] The mapping relationship after the labeling is obtained, and the probability of forming a connection relationship between the target power generation device and each energy storage device is determined by using a probability function, wherein the probability function includes:

[0080]

[0081] in, represents the target power generation equipment, represents the target energy storage device, Indicates the historical connection times between the target energy storage device and the target power generation device. Indicates the target energy storage device The probability of forming a connection relationship with the target power generation equipment, Indicates a label;

[0082] In response to detecting that the probability value is greater than or equal to a preset threshold, the target power generation device and the target energy storage device are connected, and a first control node and a second control node generated based on the CPU are respectively set at the power generation device node and the energy storage device node, wherein the first control node is used to control the power generation of the power generation device, and the second control node is used to control the power generation of the energy storage device. The preset threshold can be set according to actual needs, such as 50%;

[0083] By connecting multiple control nodes generated based on the CPU through the main control node, and based on multiple connection relationships and the main control node, the distributed energy-saving and power-saving control framework is generated, that is, the power generation equipment and energy storage equipment that meet the probability value requirements are connected, and the corresponding CPU control node is set on the connection link to effectively control the power generation.

[0084] S3: Obtain the predicted power supply required within the target time period.

[0085] It should be noted that the forecasting methods for the power supply required within the target time period include:

[0086] Constructing a power supply prediction model, the power supply prediction model comprising:

[0087]

[0088] in, It represents the ratio of power generation to energy storage power generation. represents the growth rate of power supply, Indicates time, represents the output value of the power supply prediction model;

[0089] The product of the output value of the power supply prediction model and a preset multiple is defined as the power supply required within the target time period, wherein the preset multiple can be set according to actual needs, such as 110 times.

[0090] S4: Based on the required power supply, use the control node generated based on the CPU to control the energy storage device and / or power generation device corresponding to each control node.

[0091] It should be noted that, before using the control node generated based on the CPU to control the energy storage and / or power supply corresponding to each control node, the method further includes:

[0092] Construct an objective function and constraints, wherein the objective function includes:

[0093]

[0094] The constraints include:

[0095]

[0096] in, Indicates the loss value between the power-consuming equipment and the power-generating equipment. Indicates the loss value between the electrical equipment and the energy storage equipment. Indicates the loss value between the power generation equipment and the energy storage equipment, Represents the solution domain, which is used to describe the points with connection relationships in the distributed energy-saving and power-saving control framework. Indicates time, Represents the electricity cost, Represent the energy storage and power supply respectively, Represents the objective function.

[0097] In some specific implementations, based on the required power supply, using the control node generated based on the CPU to control the energy storage device and / or power generation device corresponding to each control node includes:

[0098] Based on the required power supply, a power supply signal is sent to the line control node that meets the preset objective function value standard, that is, the situation where the sum of the loss value and the cost is low, so as to control the energy storage device and / or the power generation equipment to supply power. Based on this, the nodes that need power supply can be powered, avoiding unnecessary power supply loss of a large amount of energy.

[0099] In the above energy-saving and power-saving control method, the method includes: obtaining historical power supply data information on the power supply side, and classifying the historical power supply data information on the power supply side based on the peak and valley time-of-use electricity prices to obtain a target data set; based on the target data set, constructing a distributed energy-saving and power-saving control framework, the distributed energy-saving and power-saving control framework includes at least one control node generated based on the CPU; obtaining the predicted required power supply within the target time period; based on the required power supply, using the control node generated based on the CPU to control the energy storage equipment and / or power generation equipment corresponding to each control node. This application aims to improve the efficiency and accuracy of energy-saving and power-saving control.

[0100] It should be understood that although Figure 2The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 2 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0101] In one embodiment, Figure 3 As shown, an energy-saving and power-saving control device is provided, comprising: a data acquisition module, a construction module, a prediction module and a control module, wherein:

[0102] A data acquisition module is used to acquire historical power supply data information on the power supply side, and classify the historical power supply data information on the power supply side based on the peak and valley time-of-use electricity prices to obtain a target data set;

[0103] A construction module, used to construct a distributed energy-saving and power-saving control framework according to the target data set, wherein the distributed energy-saving and power-saving control framework includes at least one control node generated based on a CPU;

[0104] A prediction module, used to obtain the power supply required within the predicted target time period;

[0105] The control module is used to control the energy storage device and / or power generation device corresponding to each control node based on the required power supply amount and using the control node generated based on the CPU.

[0106] As a preferred implementation, in the embodiment of the present invention, the data acquisition module is specifically used for:

[0107] Acquire historical power supply data information of the power supply side in the target area, wherein the historical power supply data information of the power supply side includes at least power generation, energy storage, energy storage power generation, and power supply growth rate at multiple time nodes;

[0108] Obtain the time period corresponding to the peak and valley time-of-use electricity price in the target area;

[0109] Classify the historical power supply data information on the power supply side according to the collection time of the historical power supply data information on the power supply side and the time period to obtain a first data set and a second data set;

[0110] A first target data set is generated based on the first data set and the second data set.

[0111] As a preferred implementation, in the embodiment of the present invention, the data acquisition module is further used to:

[0112] Acquire historical power supply data information of the power supply side in the target area, wherein the historical power supply data information of the power supply side at least includes the location information of the power generation equipment and its corresponding maximum power generation, the location information of the energy storage equipment and its corresponding maximum storage capacity;

[0113] The power generation equipment is sorted in a positive order according to the maximum power generation, and the energy storage equipment is sorted in a reverse order according to the maximum storage capacity;

[0114] Based on the sorting order of the power generation equipment and the energy storage equipment, a one-to-one mapping relationship is formed between one power generation equipment and multiple energy storage equipment, and the formed mapping relationship is numbered according to the reverse sorting order of the energy storage equipment;

[0115] Based on the labeled mapping relationship, a second target data set is generated.

[0116] As a preferred implementation, in the embodiment of the present invention, the building module is further used for:

[0117] The mapping relationship after the labeling is obtained, and the probability of forming a connection relationship between the target power generation device and each energy storage device is determined by using a probability function, wherein the probability function includes:

[0118]

[0119] in, represents the target power generation equipment, represents the target energy storage device, Indicates the historical connection times between the target energy storage device and the target power generation device. Indicates the target energy storage device The probability of forming a connection relationship with the target power generation equipment, Indicates a label;

[0120] In response to detecting that the probability value is greater than or equal to a preset threshold, the target power generation device and the target energy storage device are connected, and a first control node and a second control node generated based on the CPU are respectively set at the power generation device node and the energy storage device node, wherein the first control node is used to control the power generation of the power generation device, and the second control node is used to control the power generation of the energy storage device;

[0121] The distributed energy-saving and power-saving control framework is generated by connecting a plurality of control nodes generated based on the CPU via a general control node and based on a plurality of connection relationships and the general control node.

[0122] As a preferred implementation, in the embodiment of the present invention, the prediction module is specifically used for:

[0123] Constructing a power supply prediction model, the power supply prediction model comprising:

[0124]

[0125] in, It represents the ratio of power generation to energy storage power generation. represents the growth rate of power supply, Indicates time, represents the output value of the power supply prediction model;

[0126] The product of the output value of the power supply prediction model and a preset multiple is defined as the power supply required within the target time period.

[0127] As a preferred implementation, in the embodiment of the present invention, the control module is specifically used for:

[0128] Construct an objective function and constraints, wherein the objective function includes:

[0129]

[0130] The constraints include:

[0131]

[0132] in, Indicates the loss value between the power-consuming equipment and the power-generating equipment. Indicates the loss value between the electrical equipment and the energy storage equipment. Indicates the loss value between the power generation equipment and the energy storage equipment, Represents the solution domain, which is used to describe the points with connection relationships in the distributed energy-saving and power-saving control framework. Indicates time, Represents the electricity cost, Represent the energy storage and power supply respectively, Represents the objective function.

[0133] As a preferred implementation, in the embodiment of the present invention, the control module is further used for:

[0134] Based on the required power supply, a power supply signal is sent to a line control node that meets a preset objective function value standard to control the energy storage device and / or the power generation device to supply power.

[0135] For the specific definition of the energy-saving and power-saving control device, please refer to the definition of the energy-saving and power-saving control method above, which will not be repeated here. Each module in the above energy-saving and power-saving control device can be implemented in whole or in part by software, hardware and a combination thereof. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0136] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an energy-saving and power-saving control method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0137] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0138] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0139] S1: Acquire historical power supply data information on the power supply side, and classify the historical power supply data information on the power supply side based on the peak and valley time-of-use electricity prices to obtain a target data set;

[0140] S2: constructing a distributed energy-saving and power-saving control framework according to the target data set, wherein the distributed energy-saving and power-saving control framework includes at least one control node generated based on a CPU;

[0141] S3: Obtain the predicted power supply required within the target time period;

[0142] S4: Based on the required power supply, use the control node generated based on the CPU to control the energy storage device and / or power generation device corresponding to each control node.

[0143] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0144] Acquire historical power supply data information of the power supply side in the target area, wherein the historical power supply data information of the power supply side includes at least power generation, energy storage, energy storage power generation, and power supply growth rate at multiple time nodes;

[0145] Obtain the time period corresponding to the peak and valley time-of-use electricity price in the target area;

[0146] Classify the historical power supply data information on the power supply side according to the collection time of the historical power supply data information on the power supply side and the time period to obtain a first data set and a second data set;

[0147] A first target data set is generated based on the first data set and the second data set.

[0148] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0149] Acquire historical power supply data information of the power supply side in the target area, wherein the historical power supply data information of the power supply side at least includes the location information of the power generation equipment and its corresponding maximum power generation, the location information of the energy storage equipment and its corresponding maximum storage capacity;

[0150] The power generation equipment is sorted in a positive order according to the maximum power generation, and the energy storage equipment is sorted in a reverse order according to the maximum storage capacity;

[0151] Based on the sorting order of the power generation equipment and the energy storage equipment, a one-to-one mapping relationship is formed between one power generation equipment and multiple energy storage equipment, and the formed mapping relationship is numbered according to the reverse sorting order of the energy storage equipment;

[0152] Based on the labeled mapping relationship, a second target data set is generated.

[0153] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0154] The mapping relationship after the labeling is obtained, and the probability of forming a connection relationship between the target power generation device and each energy storage device is determined by using a probability function, wherein the probability function includes:

[0155]

[0156] in, represents the target power generation equipment, represents the target energy storage device, Indicates the historical connection times between the target energy storage device and the target power generation device. Indicates the target energy storage device The probability of forming a connection relationship with the target power generation equipment, Indicates a label;

[0157] In response to detecting that the probability value is greater than or equal to a preset threshold, the target power generation device and the target energy storage device are connected, and a first control node and a second control node generated based on the CPU are respectively set at the power generation device node and the energy storage device node, wherein the first control node is used to control the power generation of the power generation device, and the second control node is used to control the power generation of the energy storage device;

[0158] The distributed energy-saving and power-saving control framework is generated by connecting a plurality of control nodes generated based on the CPU via a general control node and based on a plurality of connection relationships and the general control node.

[0159] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0160] Constructing a power supply prediction model, the power supply prediction model comprising:

[0161]

[0162] in, It represents the ratio of power generation to energy storage power generation. represents the growth rate of power supply, Indicates time, represents the output value of the power supply prediction model;

[0163] The product of the output value of the power supply prediction model and a preset multiple is defined as the power supply required within the target time period.

[0164] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0165] Construct an objective function and constraints, wherein the objective function includes:

[0166]

[0167] The constraints include:

[0168]

[0169] in, Indicates the loss value between the power-consuming equipment and the power-generating equipment. Indicates the loss value between the electrical equipment and the energy storage equipment. Indicates the loss value between the power generation equipment and the energy storage equipment, Represents the solution domain, which is used to describe the points with connection relationships in the distributed energy-saving and power-saving control framework. Indicates time, Represents the electricity cost, Represent the energy storage and power supply respectively, Represents the objective function.

[0170] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0171] Based on the required power supply, a power supply signal is sent to a line control node that meets a preset objective function value standard to control the energy storage device and / or the power generation device to supply power.

[0172] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0173] S1: Acquire historical power supply data information on the power supply side, and classify the historical power supply data information on the power supply side based on the peak and valley time-of-use electricity prices to obtain a target data set;

[0174] S2: constructing a distributed energy-saving and power-saving control framework according to the target data set, wherein the distributed energy-saving and power-saving control framework includes at least one control node generated based on a CPU;

[0175] S3: Obtain the predicted power supply required within the target time period;

[0176] S4: Based on the required power supply, use the control node generated based on the CPU to control the energy storage device and / or power generation device corresponding to each control node.

[0177] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0178] Acquire historical power supply data information of the power supply side in the target area, wherein the historical power supply data information of the power supply side includes at least power generation, energy storage, energy storage power generation, and power supply growth rate at multiple time nodes;

[0179] Obtain the time period corresponding to the peak and valley time-of-use electricity price in the target area;

[0180] Classify the historical power supply data information on the power supply side according to the collection time of the historical power supply data information on the power supply side and the time period to obtain a first data set and a second data set;

[0181] A first target data set is generated based on the first data set and the second data set.

[0182] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0183] Acquire historical power supply data information of the power supply side in the target area, wherein the historical power supply data information of the power supply side at least includes the location information of the power generation equipment and its corresponding maximum power generation, the location information of the energy storage equipment and its corresponding maximum storage capacity;

[0184] The power generation equipment is sorted in a positive order according to the maximum power generation, and the energy storage equipment is sorted in a reverse order according to the maximum storage capacity;

[0185] Based on the sorting order of the power generation equipment and the energy storage equipment, a one-to-one mapping relationship is formed between one power generation equipment and multiple energy storage equipment, and the formed mapping relationship is numbered according to the reverse sorting order of the energy storage equipment;

[0186] Based on the labeled mapping relationship, a second target data set is generated.

[0187] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0188] The mapping relationship after the labeling is obtained, and the probability of forming a connection relationship between the target power generation device and each energy storage device is determined by using a probability function, wherein the probability function includes:

[0189]

[0190] in, represents the target power generation equipment, represents the target energy storage device, Indicates the historical connection times between the target energy storage device and the target power generation device. Indicates the target energy storage device The probability of forming a connection relationship with the target power generation equipment, Indicates the label;

[0191] In response to detecting that the probability value is greater than or equal to a preset threshold, the target power generation device and the target energy storage device are connected, and a first control node and a second control node generated based on the CPU are respectively set at the power generation device node and the energy storage device node, wherein the first control node is used to control the power generation of the power generation device, and the second control node is used to control the power generation of the energy storage device;

[0192] The distributed energy-saving and power-saving control framework is generated by connecting a plurality of control nodes generated based on the CPU via a general control node and based on a plurality of connection relationships and the general control node.

[0193] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0194] Constructing a power supply prediction model, the power supply prediction model comprising:

[0195]

[0196] in, It represents the ratio of power generation to energy storage power generation. represents the growth rate of power supply, Indicates time, represents the output value of the power supply prediction model;

[0197] The product of the output value of the power supply prediction model and a preset multiple is defined as the power supply required within the target time period.

[0198] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0199] Construct an objective function and constraints, wherein the objective function includes:

[0200]

[0201] The constraints include:

[0202]

[0203] in, Indicates the loss value between the power-consuming equipment and the power-generating equipment. Indicates the loss value between the electrical equipment and the energy storage equipment. Indicates the loss value between the power generation equipment and the energy storage equipment, Represents the solution domain, which is used to describe the points with connection relationships in the distributed energy-saving and power-saving control framework. Indicates time, Represents the electricity cost, Represent the energy storage and power supply respectively, Represents the objective function.

[0204] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0205] Based on the required power supply, a power supply signal is sent to a line control node that meets a preset objective function value standard to control the energy storage device and / or the power generation device to supply power.

[0206] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0207] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0208] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. An energy-saving and power-saving control method, characterized in that: The method comprises: Acquire historical power supply data information on the power supply side, and classify the historical power supply data information on the power supply side based on the peak and valley time-of-use electricity prices to obtain a target data set; According to the target data set, a distributed energy-saving and power-saving control framework is constructed, wherein the distributed energy-saving and power-saving control framework includes at least one control node generated based on a CPU; Obtain the predicted power supply required within the target time period; Based on the required power supply, the energy storage device and / or power generation device corresponding to each control node is controlled by using the control node generated based on the CPU; The historical power supply data information of the power supply side is obtained, and the historical power supply data information of the power supply side is classified based on the peak and valley time-of-use electricity prices, and the target data set is obtained, including: Acquire historical power supply data information of the power supply side in the target area, wherein the historical power supply data information of the power supply side includes at least power generation, energy storage, energy storage power generation, and power supply growth rate at multiple time nodes; Obtain the time period corresponding to the peak and valley time-of-use electricity price in the target area; Classify the historical power supply data information on the power supply side according to the collection time of the historical power supply data information on the power supply side and the time period to obtain a first data set and a second data set; Based on the first data set and the second data set, generate a first target data set; The method further comprises: Acquire historical power supply data information of the power supply side in the target area, wherein the historical power supply data information of the power supply side at least includes the location information of the power generation equipment and its corresponding maximum power generation, the location information of the energy storage equipment and its corresponding maximum storage capacity; The power generation equipment is sorted in a positive order according to the maximum power generation, and the energy storage equipment is sorted in a reverse order according to the maximum storage capacity; Based on the sorting order of the power generation equipment and the energy storage equipment, a one-to-one mapping relationship is formed between one power generation equipment and multiple energy storage equipment, and the formed mapping relationship is numbered according to the reverse sorting order of the energy storage equipment; Based on the labeled mapping relationship, generate a second target data set; According to the target data set, building a distributed energy-saving and power-saving control framework includes: The mapping relationship after the labeling is obtained, and the probability of forming a connection relationship between the target power generation device and each energy storage device is determined by using a probability function, wherein the probability function includes: in, represents the target power generation equipment, represents the target energy storage device, Indicates the historical connection times between the target energy storage device and the target power generation device. Indicates the target energy storage device The probability of forming a connection relationship with the target power generation equipment, Indicates the label; In response to detecting that the probability value is greater than or equal to a preset threshold, the target power generation device and the target energy storage device are connected, and a first control node and a second control node generated based on the CPU are respectively set at the power generation device node and the energy storage device node, wherein the first control node is used to control the power generation of the power generation device, and the second control node is used to control the power generation of the energy storage device; Connecting a plurality of control nodes generated based on the CPU through a general control node, and generating the distributed energy-saving and power-saving control framework based on a plurality of connection relationships and the general control node; Methods for predicting the amount of power required during the target time period include: Constructing a power supply prediction model, the power supply prediction model comprising: in, It represents the ratio of power generation to energy storage power generation. represents the growth rate of power supply, Indicates time, represents the output value of the power supply prediction model; The product of the output value of the power supply prediction model and a preset multiple is defined as the power supply required within the target time period; Before using the control node generated based on the CPU to control the energy storage and / or power supply corresponding to each control node, the method further includes: Construct an objective function and constraints, wherein the objective function includes: The constraints include: in, Indicates the loss value between the power-consuming equipment and the power-generating equipment. Indicates the loss value between the electrical equipment and the energy storage equipment. Indicates the loss value between the power generation equipment and the energy storage equipment, Represents the solution domain, which is used to describe the points with connection relationships in the distributed energy-saving and power-saving control framework. Indicates time, Represents the electricity cost, Represent the energy storage and power supply respectively, Represents the objective function.

2. The energy-saving and power-saving control method according to claim 1, characterized in that: Based on the required power supply, using the control node generated based on the CPU to control the energy storage device and / or power generation device corresponding to each control node includes: Based on the required power supply, a power supply signal is sent to a line control node that meets a preset objective function value standard to control the energy storage device and / or the power generation device to supply power.

3. An energy-saving and power-saving control device for implementing the energy-saving and power-saving control method according to claim 1 or 2, characterized in that: The device comprises: A data acquisition module is used to acquire historical power supply data information on the power supply side, and classify the historical power supply data information on the power supply side based on the peak and valley time-of-use electricity prices to obtain a target data set; A construction module, used to construct a distributed energy-saving and power-saving control framework according to the target data set, wherein the distributed energy-saving and power-saving control framework includes at least one control node generated based on a CPU; A prediction module, used to obtain the power supply required within the predicted target time period; The control module is used to control the energy storage device and / or power generation device corresponding to each control node based on the required power supply amount and using the control node generated based on the CPU.

4. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to claim 1 or 2 is implemented.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to claim 1 or 2 is implemented.

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