New Energy Development Prediction Method, Device, Equipment and Storage Medium

Abstract

The present invention discloses a new energy development prediction method, device, equipment and storage medium. The method evaluates the consumption capacity of new energy by obtaining the maximum consumption amount of new energy and the operation cost of the new energy system, and establishes a new energy evaluation index system; preprocesses the data of the new energy source domain and the task domain, and establishes a new energy prediction system according to the preprocessed target data; establishes a new energy pricing model, and conducts new energy system development and prediction according to the new energy evaluation index system, the new energy prediction system and the new energy pricing model, which can ensure the feasibility and profitability of new energy in development and application, promote new energy consumption, improve the utilization ratio of new energy, avoid excessive consumption of new energy, save power generation costs, improve the accuracy of new energy development prediction, and improve the speed and efficiency of new energy development prediction.

Description

Technical Field

[0001] The present invention relates to the technical field of new electrical energy, and particularly to a new energy development prediction method, device, equipment and storage medium. Background Technique

[0002] With the proposal of the concept of the energy Internet and the development of the power market, more and more companies have flocked into the power energy market; various companies cooperate with the power grid or seek new energy development for profit in the market; generally speaking, major Internet companies all have the trend and measures to participate in the energy industry, develop towards the "new energy Internet business form", and promote their own diversification. These Internet companies with customer-oriented thinking are trying to enter the energy field.

[0003] Traditional power grid enterprises are typical asset-driven enterprises. With the rapid development of the national economy, various new things have continuously emerged. Society is in a critical period of transforming the development mode and optimizing the economic structure; currently, the development of the power grid faces challenges in the development of energy technology and competition in the new business form; due to different local conditions, new energy has different adaptabilities in various regions and user areas, and power companies lack a correct and effective method to evaluate the feasibility and value of new energy, resulting in low new energy development efficiency and low accuracy of evaluation and prediction. Summary of the Invention

[0004] The main purpose of the present invention is to provide a new energy development prediction method, device, equipment and storage medium, aiming to solve the technical problems in the prior art of lacking a correct and effective method to evaluate the feasibility and value of new energy, low new energy development efficiency, and low accuracy of evaluation and prediction.

[0005] In the first aspect, the present invention provides a new energy development prediction method, and the new energy development prediction method includes the following steps:

[0006] Obtain the maximum new energy consumption and the new energy system operation cost, evaluate the consumption capacity of new energy according to the maximum new energy consumption and the new energy system operation cost, and establish a new energy evaluation index system;

[0007] Preprocess the data of the new energy source domain and the task domain, and establish a new energy prediction system according to the preprocessed target data;

[0008] Establish a new energy pricing model, and conduct new energy system development and prediction according to the new energy evaluation index system, the new energy prediction system and the new energy pricing model.

[0009] Optionally, the step of obtaining the maximum new energy consumption and the new energy system operation cost, evaluating the consumption capacity of new energy according to the maximum new energy consumption and the new energy system operation cost, and establishing a new energy evaluation index system includes:

[0010] Obtain the new energy output power of the new energy's electrical energy and the electrical output power of the power system within a preset time period, and determine the maximum new energy consumption according to the new energy output power and the electrical output power.

[0011] Obtain the motor output power, the energy consumption cost of the motor group, and the environmental cost, and determine the operating cost of the new energy system according to the motor output power, the energy consumption cost of the motor group, and the environmental cost.

[0012] Evaluate the consumption capacity of the new energy according to the maximum new energy consumption and the operating cost of the new energy system to obtain an evaluation result, and establish a new energy evaluation index system according to the evaluation result.

[0013] Optionally, the step of obtaining the new energy output power of the new energy's electrical energy and the electrical output power of the power system within a preset time period, and determining the maximum new energy consumption according to the new energy output power and the electrical output power includes:

[0014] Obtain the new energy output power of the new energy's electrical energy and the electrical output power of the power system within a preset time period;

[0015] Obtain the maximum new energy consumption through the following formula according to the new energy output power and the electrical output power:

[0016]

[0017] where is the maximum new energy consumption, is the preset time period, and are the preset output weights, is the electrical output power of the power system at time t, is the new energy output power of the new energy's electrical energy at time t.

[0018] Optionally, the step of obtaining the motor output power, the energy consumption cost of the motor group, and the environmental cost, and determining the operating cost of the new energy system according to the motor output power, the energy consumption cost of the motor group, and the environmental cost includes:

[0019] Obtain the motor output power, the energy consumption cost of the motor group, and the environmental cost;

[0020] Obtain the operating cost of the new energy system through the following formula according to the motor output power, the energy consumption cost of the motor group, and the environmental cost:

[0021]

[0022] where is the operating cost of the new energy system, is the preset time period, N is the number of motors in the power system, is the energy consumption cost of the motor group, is the motor output force of the nth motor at time t, is the environmental cost, is the additional cost of the mth part.

[0023] Optionally, the consumption capacity of the new energy is evaluated according to the maximum consumption of the new energy and the operating cost of the new energy system to obtain an evaluation result, and a new energy evaluation index system is established according to the evaluation result, including:

[0024] Obtain the historical data of the power grid operation, and determine the new energy probability distribution data according to the historical data;

[0025] Obtain the daily average load of the current power grid, and calculate the power loss according to the daily average load of the current power grid;

[0026] Determine the actually consumable new energy power according to the new energy probability distribution data, the power loss, the maximum consumption of the new energy and the operating cost of the new energy system;

[0027] Evaluate the consumption capacity of the new energy through the actually consumable new energy power to obtain an evaluation result, and establish a new energy evaluation index system according to the evaluation result.

[0028] Optionally, the data of the new energy source domain and the task domain are preprocessed, and a new energy prediction system is established according to the preprocessed target data, including:

[0029] Preprocess the source domain data of the new energy source domain, and perform deep learning on the preprocessed source domain data according to the deep learning model to obtain the source domain deep learning features;

[0030] Preprocess the idle task domain data of the idle task domain to obtain the idle task domain features, input the source domain deep learning features and the idle task domain features into the fixed feature layer, input the fixed features into the transfer learning model, and fine-tune the parameters outside the fixed layer to obtain the fixed features;

[0031] Perform deep learning on the sufficient task domain data of the sufficient task domain according to the deep learning model to obtain the task domain deep learning features;

[0032] Use the source domain deep learning features, the fixed features and the task domain deep learning features as the target data, and predict the new energy usage in the future period according to the target data to generate a new energy prediction system.

[0033] Optionally, establishing the new energy pricing model and performing new energy system development and prediction according to the new energy evaluation index system, the new energy prediction system, and the new energy pricing model includes:

[0034] Obtaining the current electricity consumption according to the following formula:

[0035]

[0036] where L is the current electricity consumption, t,1 represents the electricity consumption after response, E is a 3*3 matrix, is the change in electricity consumption at each moment, and P is the electricity price at a certain moment;

[0037] Obtaining the objective function corresponding to the customer satisfaction according to the following formula:

[0038]

[0039] where Y is the objective function, is the new energy consumption before change, is the new energy consumption after change, is the total new energy consumption, is the customer satisfaction, , is the total electricity cost before response, is the total electricity cost after response;

[0040] Adjusting the current electricity consumption and the current electricity price according to the objective function, and establishing a new energy pricing model according to the adjusted electricity consumption and electricity price;

[0041] Performing new energy system development and prediction according to the new energy evaluation index system, the new energy prediction system, and the new energy pricing model.

[0042] In a second aspect, to achieve the above object, the present invention also proposes a new energy development and prediction device, and the new energy development and prediction device includes:

[0043] An evaluation module, configured to obtain the maximum new energy consumption and the operation cost of the new energy system, evaluate the consumption capacity of the new energy according to the maximum new energy consumption and the operation cost of the new energy system, and establish a new energy evaluation index system;

[0044] A preprocessing module, configured to preprocess the data of the new energy source domain and the task domain, and establish a new energy prediction system according to the preprocessed target data;

[0045] A development and prediction module, configured to establish a new energy pricing model, and perform new energy system development and prediction according to the new energy evaluation index system, the new energy prediction system, and the new energy pricing model.

[0046] In a third aspect, to achieve the above object, the present invention further provides a new energy development prediction device, which includes: a memory, a processor, and a new energy development prediction program stored on the memory and executable on the processor, and the new energy development prediction program is configured to implement the steps of the new energy development prediction method as described above.

[0047] In a fourth aspect, to achieve the above object, the present invention further provides a storage medium, on which a new energy development prediction program is stored, and when the new energy development prediction program is executed by a processor, it implements the steps of the new energy development prediction method as described above.

[0048] The new energy development prediction method proposed by the present invention obtains the maximum new energy consumption and the operation cost of the new energy system, evaluates the consumption capacity of the new energy based on the maximum new energy consumption and the operation cost of the new energy system, and establishes a new energy evaluation index system; preprocesses the data of the new energy source domain and the task domain, and establishes a new energy prediction system based on the preprocessed target data; establishes a new energy pricing model, and conducts new energy system development and prediction based on the new energy evaluation index system, the new energy prediction system, and the new energy pricing model, which can timely conduct hierarchical evaluation of the new energy consumption capacity, ensure the feasibility and profitability of the new energy in development and application, promote new energy consumption, improve the new energy utilization ratio, avoid excessive consumption of new energy, save power generation costs, improve the accuracy of new energy development prediction, and improve the speed and efficiency of new energy development prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the device structure of the hardware operating environment related to the embodiment solution of the present invention;

[0050] Figure 2 It is a schematic flowchart of the first embodiment of the new energy development prediction method of the present invention;

[0051] Figure 3 It is a schematic flowchart of the second embodiment of the new energy development prediction method of the present invention;

[0052] Figure 4 It is a schematic flowchart of the third embodiment of the new energy development prediction method of the present invention;

[0053] Figure 5 It is a schematic flowchart of the specific ability grading evaluation system in the new energy development prediction method of the present invention;

[0054] Figure 6 It is a schematic flowchart of the fourth embodiment of the new energy development prediction method of the present invention;

[0055] Figure 7 This is a functional block diagram of the first embodiment of the new energy development prediction device of the present invention.

[0056] The implementation, functional features and advantages of the object of the present invention will be further described in conjunction with the embodiments with reference to the accompanying drawings. Specific Embodiments

[0057] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0058] The solution of the embodiment of the present invention is mainly: by obtaining the maximum accommodation amount of new energy and the operation cost of the new energy system, evaluating the accommodation ability of new energy according to the maximum accommodation amount of new energy and the operation cost of the new energy system, and establishing a new energy evaluation index system; preprocessing the data of the new energy source domain and the task domain, and establishing a new energy prediction system according to the preprocessed target data; establishing a new energy pricing model, and performing new energy system development and prediction according to the new energy evaluation index system, the new energy prediction system and the new energy pricing model, which can timely classify and evaluate the accommodation ability of new energy, ensure the feasibility and profitability of new energy in development and application, promote new energy consumption, improve the utilization ratio of new energy, avoid excessive consumption of new energy, save power generation costs, improve the accuracy of new energy development prediction, improve the speed and efficiency of new energy development prediction, and solve the technical problems in the prior art of lacking correct and effective evaluation of the feasibility and value of new energy, low new energy development efficiency, and low evaluation prediction accuracy.

[0059] Referring to Figure 1 , Figure 1 This is a schematic diagram of the device structure of the hardware operating environment involved in the solution of the embodiment of the present invention.

[0060] As Figure 1 shown, the device may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display) and an input unit such as a keyboard (Keyboard). Optionally, the user interface 1003 may further include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a Wi-Fi interface). The memory 1005 may be a high-speed RAM memory or a stable memory (Non-Volatile Memory), such as a disk memory. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0061] Those skilled in the art can understand,Figure 1 The device structure shown does not constitute a limitation on the device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0062] As Figure 1 shown, the memory 1005, as a storage medium, may include an operating device, a network communication module, a user interface module, and a new energy development prediction program.

[0063] The device of the present invention calls the new energy development prediction program stored in the memory 1005 through the processor 1001, and performs the following operations:

[0064] Obtain the maximum new energy consumption and the operating cost of the new energy system, evaluate the consumption capacity of the new energy based on the maximum new energy consumption and the operating cost of the new energy system, and establish a new energy evaluation index system;

[0065] Preprocess the data of the new energy source domain and the task domain, and establish a new energy prediction system based on the preprocessed target data;

[0066] Establish a new energy pricing model, and conduct new energy system development and prediction based on the new energy evaluation index system, the new energy prediction system, and the new energy pricing model.

[0067] The device of the present invention calls the new energy development prediction program stored in the memory 1005 through the processor 1001, and also performs the following operations:

[0068] Obtain the new energy output force of the electric energy of the new energy and the electric output force of the power system within a preset time period, and determine the maximum new energy consumption based on the new energy output force and the electric output force;

[0069] Obtain the motor output force, the energy consumption cost of the motor group, and the environmental cost, and determine the operating cost of the new energy system based on the motor output force, the energy consumption cost of the motor group, and the environmental cost;

[0070] Evaluate the consumption capacity of the new energy based on the maximum new energy consumption and the operating cost of the new energy system, obtain an evaluation result, and establish a new energy evaluation index system based on the evaluation result.

[0071] The device of the present invention calls the new energy development prediction program stored in the memory 1005 through the processor 1001, and also performs the following operations:

[0072] Obtain the new energy output force of the electric energy of the new energy and the electric output force of the power system within a preset time period;

[0073] The maximum new - energy consumption is obtained from the new - energy output and the power output through the following formula:

[0074]

[0075] where, is the maximum new - energy consumption, is the preset time period, and are the preset output weights, is the power output of the power system at time t, is the new - energy output of the new - energy power source of the new energy at time t.

[0076] The device of the present invention, through the processor 1001, calls the new - energy development prediction program stored in the memory 1005, and also performs the following operations:

[0077] Obtain the motor output, the energy consumption cost of the motor group, and the environmental cost;

[0078] The operation cost of the new - energy system is obtained from the motor output, the energy consumption cost of the motor group, and the environmental cost through the following formula:

[0079]

[0080] where, is the operation cost of the new - energy system, is the preset time period, N is the number of motors in the power system, is the energy consumption cost of the motor group, is the motor output of the n - th motor at time t, is the environmental cost, is the additional cost of the m - th part.

[0081] The device of the present invention, through the processor 1001, calls the new - energy development prediction program stored in the memory 1005, and also performs the following operations:

[0082] Obtain the historical data of the power - grid operation, and determine the new - energy probability distribution data according to the historical data;

[0083] Obtain the daily average load of the current power grid, and calculate the power loss according to the daily average load of the current power grid;

[0084] Determine the actually consumable new - energy power according to the new - energy probability distribution data, the power loss, the maximum new - energy consumption, and the operation cost of the new - energy system;

[0085] Evaluate the consumption capacity of the new energy through the actually consumable new - energy power to obtain an evaluation result, and establish a new - energy evaluation index system according to the evaluation result.

[0086] The device of the present invention calls the new energy development prediction program stored in the memory 1005 through the processor 1001, and also performs the following operations:

[0087] Preprocess the source domain data of the new energy source domain, and perform deep learning on the preprocessed source domain data according to the deep learning model to obtain source domain deep learning features;

[0088] Preprocess the idle task domain data of the idle task domain to obtain idle task domain features, input the source domain deep learning features and the idle task domain features into the fixed feature layer, input the fixed features into the transfer learning model, and fine-tune the parameters outside the fixed layer to obtain fixed features;

[0089] Perform deep learning on the sufficient task domain data of the sufficient task domain according to the deep learning model to obtain task domain deep learning features;

[0090] Use the source domain deep learning features, the fixed features and the task domain deep learning features as target data, and predict the new energy usage in the future period according to the target data to generate a new energy prediction system.

[0091] The device of the present invention calls the new energy development prediction program stored in the memory 1005 through the processor 1001, and also performs the following operations:

[0092] Obtain the current electricity consumption according to the following formula:

[0093]

[0094] where L is the current electricity consumption, t,1 represents the electricity consumption after response, E is a 3*3 matrix, is the change in electricity consumption at each moment, and P is the electricity price at a certain moment;

[0095] Obtain the objective function corresponding to the customer satisfaction according to the following formula:

[0096]

[0097] where Y is the objective function, is the new energy consumption before change, is the new energy consumption after change, is the total new energy consumption, is the customer satisfaction, , is the total electricity bill before response, is the total electricity bill after response;

[0098] Adjust the current power consumption and current electricity price according to the objective function, and establish a new energy pricing model based on the adjusted power consumption and electricity price.

[0099] Conduct new energy system development and prediction based on the new energy evaluation index system, the new energy prediction system, and the new energy pricing model.

[0100] Through the above solutions in this embodiment, by obtaining the maximum new energy consumption and the operation cost of the new energy system, evaluate the consumption capacity of new energy according to the maximum new energy consumption and the operation cost of the new energy system, and establish a new energy evaluation index system; preprocess the data of the new energy source domain and task domain, and establish a new energy prediction system according to the preprocessed target data; establish a new energy pricing model, and conduct new energy system development and prediction based on the new energy evaluation index system, the new energy prediction system, and the new energy pricing model, which can timely conduct hierarchical evaluation of the new energy consumption capacity, ensure the feasibility and profitability of new energy in development and application, promote new energy consumption, improve the utilization ratio of new energy, avoid excessive consumption of new energy, save power generation costs, improve the accuracy of new energy development prediction, and improve the speed and efficiency of new energy development prediction.

[0101] Based on the above hardware structure, an embodiment of the new energy development prediction method of the present invention is proposed.

[0102] Refer to Figure 2 , Figure 2 which is a schematic flowchart of the first embodiment of the new energy development prediction method of the present invention.

[0103] In the first embodiment, the new energy development prediction method includes the following steps:

[0104] Step S10: Obtain the maximum new energy consumption and the operation cost of the new energy system, evaluate the consumption capacity of new energy according to the maximum new energy consumption and the operation cost of the new energy system, and establish a new energy evaluation index system.

[0105] It should be noted that the new energy evaluation index should include five aspects, namely new energy consumption, new energy curtailment, new energy curtailment rate, new energy generation hours, and economy. If we want to evaluate these five aspects of a new energy, we need to focus on the maximum new energy consumption and the operation cost of the power system.

[0106] It can be understood that after obtaining the maximum new energy consumption and the operation cost of the new energy system, we can evaluate the consumption capacity of new energy, and then construct a new energy evaluation index system according to the corresponding evaluation results of the consumption capacity.

[0107] Step S20: Preprocess the data of the new energy source domain and the task domain, and establish a new energy prediction system based on the preprocessed target data.

[0108] It can be understood that after preprocessing the data in the new energy source domain and the task domain, interference data can be filtered out, and then a new energy prediction system can be established based on the preprocessed target data.

[0109] Step S30: Establish a new energy pricing model, and conduct new energy system development and prediction based on the new energy evaluation index system, the new energy prediction system, and the new energy pricing model.

[0110] It should be understood that by constructing a pricing model for new energy pricing, new energy system development and new energy system prediction can be carried out based on the new energy evaluation index system, the new energy prediction system, and the new energy pricing model.

[0111] Furthermore, the specific steps of step S30 include the following steps:

[0112] Obtain the current electricity consumption according to the following formula:

[0113]

[0114] where L is the current electricity consumption, t,1 represents the electricity consumption after response, E is a 3*3 matrix, is the change in electricity consumption at each moment, and P is the electricity price at a certain moment;

[0115] Obtain the objective function corresponding to customer satisfaction according to the following formula:

[0116]

[0117] where Y is the objective function, is the new energy consumption before change, is the new energy consumption after change, is the total new energy consumption, is the customer satisfaction, ,

[0118] Adjust the current electricity consumption and the current electricity price according to the objective function, and establish a new energy pricing model based on the adjusted electricity consumption and electricity price;

[0119] Conduct new energy system development and prediction based on the new energy evaluation index system, the new energy prediction system, and the new energy pricing model.

[0120] It should be noted that in the electricity market environment, users can adjust their electricity consumption in real time according to the market electricity price to reduce their electricity bills. Generally speaking, users' responses to electricity prices mainly include two forms: ① Single response; refers to the user's electricity consumption in a certain period, which is only related to the electricity price at that time; such as residential lighting electricity consumption, when the electricity price is high, residents can choose to turn off the lights and reduce electricity consumption; ② Multi-time response; refers to the user's electricity consumption in a certain period, which is not only related to the electricity price at that time, but also to the electricity price at other times; such as the production electricity consumption of an enterprise, this value will not stop production due to high electricity prices. Instead, the enterprise will adjust its production plan according to the electricity price to reduce production costs. This note focuses on the analysis of new energy prediction methods by power companies, and therefore pays more attention to the former, that is, single response, and focuses on the usage of electricity users.

[0121] It is understandable that, in the most naive understanding, when electricity prices rise, users will naturally reduce their usage. In the explanation, a price elasticity coefficient equation of demand is used to describe it; let are the mutual elastic coefficient and the self elastic coefficient respectively, i, j are the moments, is the electricity consumption in period i, represents the electricity price at time i, j, etc. represent the changes in electricity consumption and electricity prices at each moment, thus, the following expression can be obtained.

[0122]

[0123]

[0124] From the above two formulas, we can get

[0125]

[0126] Let L represent the power consumption, t,1 represents the power consumption after the response, and E is a 3*3 matrix. Substitute the known data to obtain the predicted response result.

[0127] Satisfaction also affects the use of new energy. Customer satisfaction varies at different prices.

[0128] In this description, K is defined as satisfaction, is the total electricity cost before response, is the total electricity cost after the response,

[0129]

[0130] Let Y be the objective function, representing the maximum satisfaction and efficiency

[0131] in respectively represent the energy consumption before and after the change

[0132]

[0133] It should be understood that in recent years, with the continuous development of the power grid, the new energy integration ability has been continuously improved, and more and more new energy power has been incorporated into the large power grid, and the proportion of new energy in power generation has also increased; however, the rapid development of new energy has also brought certain risks to the operation of the power system. For example, the anti-peak characteristics of new energy output have increased the peak regulation pressure of the power grid, resulting in an increase in the phenomenon of wind curtailment and light curtailment; therefore, promoting new energy consumption and improving the utilization ratio of new energy are gradually becoming the focus of attention of power companies; focusing on the feasibility and profitability of new energy development and application in the power field, comprehensively considering the maximum amount of new energy consumption, the coal consumption cost and environmental cost of generator sets, reasonably designing a new energy consumption capacity grading evaluation system, establishing a model through transfer learning, and constructing a function in accordance with the price elasticity theory, so as to solve the problems of new energy consumption, new energy prediction, new energy pricing, etc. existing in the power field.

[0134] Through the above solution of this embodiment, by obtaining the maximum new energy consumption and the operation cost of the new energy system, evaluating the consumption capacity of new energy according to the maximum new energy consumption and the operation cost of the new energy system, and establishing a new energy evaluation index system; preprocessing the data of the new energy source domain and the task domain, and establishing a new energy prediction system according to the preprocessed target data; establishing a new energy pricing model, and developing and predicting the new energy system according to the new energy evaluation index system, the new energy prediction system and the new energy pricing model, it is possible to timely conduct a grading evaluation of the new energy consumption capacity, ensure the feasibility and profitability of new energy development and application, promote new energy consumption, improve the utilization ratio of new energy, avoid the excessive consumption of new energy, save the power generation cost, improve the accuracy of new energy development prediction, and improve the speed and efficiency of new energy development prediction.

[0135] Furthermore,[ Figure 3 is a schematic flow chart of the second embodiment of the new energy development prediction method of the present invention. As Figure 3 shown, based on the first embodiment, the second embodiment of the new energy development prediction method of the present invention is proposed. In this embodiment, the step S10 specifically includes the following steps:

[0136] Step S11: Obtain the new energy output of the electric energy of new energy and the power output of the power system within a preset time period, and determine the maximum new energy consumption according to the new energy output and the power output.

[0137] It should be noted that the preset time period is a preset prediction time period, such as the next few weeks or months, etc., and this embodiment does not limit it. That is, within the preset time period, the new energy output of the electric energy of the new energy and the electric energy output of the power system are obtained, and then the maximum new energy consumption can be determined according to the new energy output and the electric energy output.

[0138] Further, step S11 specifically includes the following steps:

[0139] Obtain the new energy output of the electric energy of the new energy and the electric energy output of the power system within the preset time period;

[0140] Obtain the maximum new energy consumption through the following formula according to the new energy output and the electric energy output:

[0141]

[0142] Wherein, is the maximum new energy consumption, is the preset time period, and are the preset output weights, is the electric energy output of the power system at time t, is the new energy output of the electric energy of the new energy at time t.

[0143] It should be understood that new energy consumption refers to a state, which is the state of the electric energy produced by new energy and the electric energy in the system. The complete consumption of new energy does not mean that the system completely accepts the electric energy produced by new energy. Given that the system cannot rely entirely on new energy or traditional energy, we do not expect the electric energy in the system to be fully adapted and integrated with the electric energy produced by new energy. Instead, we expect the electric energy in the system to reach a balanced state with the electric energy of new energy, so as to achieve a higher integration efficiency and benefit. The maximum new energy consumption can be obtained through the above formula.

[0144] Step S12: Obtain the motor output force, the energy consumption cost of the motor group, and the environmental cost, and determine the operating cost of the new energy system according to the motor output force, the energy consumption cost of the motor group, and the environmental cost.

[0145] It can be understood that the motor output force is the magnitude of the motor conversion ability, that is, the magnitude of converting electric power into mechanical power output. The energy consumption of the motor group is the cost of the energy consumed by the motor group, and the environmental cost is the electricity consumption cost in the power market environment. The operating cost of the new energy system is determined through the motor output force, the energy consumption cost of the motor group, and the environmental cost.

[0146] Further, the step S12 specifically includes the following steps:

[0147] Obtain the motor output force, the energy consumption cost of the motor group, and the environmental cost;

[0148] Obtain the operating cost of the new energy system according to the motor output force, the energy consumption cost of the motor group, and the environmental cost through the following formula:

[0149]

[0150] Wherein, is the operating cost of the new energy system, is the preset time period, N is the number of motors in the power system, is the energy consumption cost of the motor group, is the motor output force of the nth motor at time t, is the environmental cost, is the additional cost of the mth part.

[0151] It should be noted that the system operating cost is a large part of the power cost. This embodiment does not focus on the traditional operating cost of the system itself, but focuses on the additional system operating cost generated by the new energy under the addition of the new energy. The operating cost of the new energy system is divided into its own operating cost and additional cost, and the additional cost is divided into:

[0152] 1. Reserve cost: The system retains sufficient standby generating units to fill the output gaps of new energy in seasons, regions, and time periods. The standby generating units bear more start-stop tasks, low power generation efficiency and other costs

[0153] 2. Balancing cost: To solve the intermittency and volatility problems of new energy, make the dispatchable units undertake more frequency regulation, rapid ramping and other auxiliary services, and the system retains more spinning reserves (spinning reserves specifically refer to generators operating normally maintaining the rated speed, ready to be connected to the grid at any time, or already connected to the grid but only carrying a part of the load, and can increase the output to the rated capacity at any time).

[0154] 3. Connection cost: The cost of connecting a new energy power plant to the power grid.

[0155] 4. Grid cost: The long-distance transmission grid cost and system loss, and the grid equipment cost.

[0156] Furthermore, the above four operating costs can be respectively denoted as 、 、 、 , and the operating cost of the new energy system can be obtained through the above formula; according to the above two formulas, the operating cost of the new energy system and the maximum new energy consumption can be obtained, and the new energy consumption capacity grading evaluation can be carried out.

[0157] Step S13: Evaluate the consumption capacity of new energy based on the maximum consumption amount of new energy and the operating cost of the new energy system to obtain an evaluation result, and establish a new energy evaluation index system according to the evaluation result.

[0158] It should be understood that by evaluating the consumption capacity of new energy through the maximum consumption amount of new energy and the operating cost of the new energy system, an evaluation result of the consumption capacity can be obtained, and then a new energy evaluation index system can be established according to the evaluation result.

[0159] In this embodiment, through the above solution, the new energy output force of the electric energy of new energy and the electric energy output force of the power system are obtained within a preset time period, and the maximum consumption amount of new energy is determined according to the new energy output force and the electric energy output force; the motor output force, the energy consumption cost of the motor group, and the environmental cost are obtained, and the operating cost of the new energy system is determined according to the motor output force, the energy consumption cost of the motor group, and the environmental cost; the consumption capacity of new energy is evaluated based on the maximum consumption amount of new energy and the operating cost of the new energy system to obtain an evaluation result, and a new energy evaluation index system is established according to the evaluation result, which can quickly construct a new energy evaluation index system, timely conduct a hierarchical evaluation of the new energy consumption capacity, and ensure the feasibility and profitability of new energy in development and application.

[0160] Furthermore, Figure 4 is a schematic flowchart of the third embodiment of the new energy development prediction method of the present invention. As Figure 4 shown, the third embodiment of the new energy development prediction method of the present invention is proposed based on the second embodiment. In this embodiment, the step S13 specifically includes the following steps:

[0161] Step S131: Obtain the historical data of the power grid operation, and determine the new energy probability distribution data according to the historical data.

[0162] It should be noted that based on the historical data of the power grid operation, the new energy probability distribution data can be determined and obtained from the historical data.

[0163] Step S132: Obtain the daily average load of the current power grid, and calculate the power loss according to the daily average load of the current power grid.

[0164] It can be understood that the daily average load of the current power grid during the operation of the power grid is obtained, and then the power loss can be calculated according to the daily average load of the current power grid.

[0165] Step S133: Determine the actually consumable new energy power according to the new energy probability distribution data, the power loss, the maximum consumption amount of new energy, and the operating cost of the new energy system.

[0166] It should be understood that the actual consumable new - energy power can be determined by the new - energy probability distribution data, the power loss, the maximum accommodation amount of new - energy, and the operation cost of the new - energy system, that is, the actual consumable new - energy power is judged according to the maximum accommodation space of the power system.

[0167] Step S134: Evaluate the accommodation ability of new - energy through the actual consumable new - energy power to obtain an evaluation result, and establish a new - energy evaluation index system according to the evaluation result.

[0168] It can be understood that by evaluating the accommodation ability of new - energy through the actual consumable new - energy power, an evaluation result can be obtained, and a new - energy evaluation index system is established through the evaluation result. See Figure 5 , Figure 5 which is a schematic flow chart of the specific ability - grading evaluation system in the new - energy development prediction method of the present invention. As Figure 5 shown, after automatically inputting historical data and the grid load characteristics, automatically calculate the probability of various new - energy outputs, and then automatically calculate the daily average grid load and the remaining peak - shaving capacity, and then obtain the combined new - energy output state, perform automated calculations, determine whether the combined new - energy output state is completed. Otherwise, re - obtain the combined new - energy output state. If so, perform loss - power analysis and judge the grid accommodation ability to end the process.

[0169] Through the above - mentioned solution in this embodiment, by obtaining the historical data of grid operation, determine the new - energy probability distribution data according to the historical data; obtain the current daily average grid load, and calculate the power loss according to the current daily average grid load; determine the actual consumable new - energy power according to the new - energy probability distribution data, the power loss, the maximum accommodation amount of new - energy, and the operation cost of the new - energy system; evaluate the accommodation ability of new - energy through the actual consumable new - energy power to obtain an evaluation result, and establish a new - energy evaluation index system according to the evaluation result; it can quickly construct a new - energy evaluation index system, timely perform grading evaluation on the new - energy accommodation ability, and ensure the feasibility and profitability of new - energy in development and application.

[0170] Furthermore, Figure 6 which is a schematic flow chart of the fourth embodiment of the new - energy development prediction method of the present invention. As Figure 6 shown, based on the first embodiment, the fourth embodiment of the new - energy development prediction method of the present invention is proposed. In this embodiment, the step S20 specifically includes the following steps:

[0171] Step S21: Pre - process the source - domain data of the new - energy source domain, and perform deep learning on the pre - processed source - domain data according to the deep - learning model to obtain the source - domain deep - learning features.

[0172] It should be noted that after preprocessing the source domain data of the new energy source domain, preprocessed source domain data can be obtained. At the same time, pre-training settings can be carried out. After model training, a deep learning model can be obtained. Through the deep learning model, deep learning can be performed on the preprocessed source domain data, and then source domain deep learning features can be obtained.

[0173] Step S22: Preprocess the idle task domain data of the idle task domain to obtain idle task domain features. Input the source domain deep learning features and the idle task domain features into the fixed feature layer, input the fixed features into the transfer learning model, and fine-tune the parameters outside the fixed layer to obtain fixed features.

[0174] It should be understood that the idle task domain is a task domain with a small number of tasks. After preprocessing the idle task domain data of the idle task domain and performing fine-tuning training settings, idle task domain features can be obtained. By inputting the source domain deep learning features and the idle task domain features into the fixed feature layer, inputting the fixed features into the transfer learning model, and fine-tuning the parameters outside the fixed layer, fixed features can be obtained.

[0175] Step S23: Perform deep learning on the sufficient task domain data of the sufficient task domain according to the deep learning model to obtain task domain deep learning features.

[0176] It can be understood that through the pre-training settings of the sufficient task domain data, a deep learning model can be obtained through model training. Furthermore, through the deep learning model, deep learning can be performed on the sufficient task domain data of the sufficient task domain, and task domain deep learning features can be obtained.

[0177] In specific implementation, data can be preprocessed first, a small part of the data can be extracted, and the training settings can be fine-tuned. After adjusting the training settings, the fixed feature layer is fixed, the transfer learning model is used, and the parameters outside the fixed layer are adjusted to obtain the prediction result.

[0178] Step S24: Use the source domain deep learning features, the fixed features, and the task domain deep learning features as target data, and predict the new energy usage situation in the future period according to the target data to generate a new energy prediction system.

[0179] It should be understood that by using the source domain deep learning features, the fixed features, and the task domain deep learning features as target data, the new energy usage situation in the future period can be predicted according to the target data, thereby generating a new energy prediction system.

[0180] In specific implementation, it is necessary to make predictions for the next few weeks or months based on the usage of current or recent new energy, introduce the concept of transfer learning based on deep learning to solve the problem of insufficient training data during the prediction process, and ensure the prediction accuracy.

[0181] It can be understood that in the research on the application of artificial intelligence in the system, the following situations are often encountered: ① As time goes by, the original sample data becomes unavailable; ② There are only a very small number of labeled samples, which are not enough to complete the training of the network; ③ The network trained well after a long time is no longer applicable to the same problem in other regions; The existence of these problems is because both deep learning and reinforcement learning have domain verticality, that is, the more vertical and detailed this domain is, the better the effect, and usually the cost of training a model is relatively large; Transfer learning is a machine learning method that uses existing knowledge to solve problems in different but related fields; Transfer existing knowledge to solve new problems, the more similar the source task and the target task are, the easier the transfer is, and the better the transfer effect is; Transfer learning needs to be combined with other machine learning methods, which can, to a certain extent, solve the basic assumption that the machine learning method depends on the data generation mechanism not changing with the environment, and also provides a solution for small sample scenarios.

[0182] Through the above solution, in this embodiment, the source domain data of the new energy source domain is preprocessed, and deep learning is performed on the preprocessed source domain data according to the deep learning model to obtain the source domain deep learning features; the idle task domain data of the idle task domain is preprocessed to obtain the idle task domain features, the source domain deep learning features and the idle task domain features are input into the fixed feature layer, the fixed features are input into the transfer learning model, and the parameters outside the fixed layer are fine-tuned to obtain the fixed features; deep learning is performed on the sufficient task domain data of the sufficient task domain according to the deep learning model to obtain the task domain deep learning features; the source domain deep learning features, the fixed features and the task domain deep learning features are used as target data, and the usage of new energy in the future period is predicted according to the target data to generate a new energy prediction system, which can timely conduct a hierarchical evaluation of the new energy consumption capacity, ensure the feasibility and profitability of new energy in development and application, promote new energy consumption, improve the utilization ratio of new energy, avoid excessive consumption of new energy, save power generation costs, and improve the accuracy of new energy development prediction.

[0183] Correspondingly, the present invention further provides a new energy development prediction device.

[0184] Refer to Figure 7 , Figure 7 which is the functional module diagram of the first embodiment of the new energy development prediction device of the present invention.

[0185] In the first embodiment of the new energy development prediction device of the present invention, the new energy development prediction device includes:

[0186] An evaluation module 10, configured to obtain the maximum new energy consumption and the operation cost of the new energy system, evaluate the consumption capacity of the new energy according to the maximum new energy consumption and the operation cost of the new energy system, and establish a new energy evaluation index system.

[0187] A preprocessing module 20, configured to preprocess the data of the new energy source domain and the task domain, and establish a new energy prediction system according to the preprocessed target data.

[0188] A development prediction module 30, configured to establish a new energy pricing model, and perform new energy system development and prediction according to the new energy evaluation index system, the new energy prediction system, and the new energy pricing model.

[0189] The evaluation module 10 is further configured to obtain the new energy output force of the electric energy of the new energy and the electric energy output force of the power system within a preset time period, determine the maximum new energy consumption according to the new energy output force and the electric energy output force; obtain the motor output force, the energy consumption cost of the motor group, and the environmental cost, and determine the operation cost of the new energy system according to the motor output force, the energy consumption cost of the motor group, and the environmental cost; evaluate the consumption capacity of the new energy according to the maximum new energy consumption and the operation cost of the new energy system, obtain an evaluation result, and establish a new energy evaluation index system according to the evaluation result.

[0190] The evaluation module 10 is further configured to obtain the new energy output force of the electric energy of the new energy and the electric energy output force of the power system within a preset time period;

[0191] The maximum new energy consumption is obtained according to the new energy output force and the electric energy output force through the following formula:

[0192]

[0193] Wherein, is the maximum new energy consumption, is the preset time period, and are preset output weights, is the electric energy output force of the power system at time t, is the new energy output force of the electric energy of the new energy at time t.

[0194] The preprocessing module 20 is further configured to obtain the motor output force, the energy consumption cost of the motor group, and the environmental cost;

[0195] The operating cost of the new energy system is obtained through the following formula based on the motor output force, the energy consumption cost of the motor group, and the environmental cost:

[0196]

[0197] Wherein, is the operating cost of the new energy system, is the preset time period, N is the number of motors in the power system, is the energy consumption cost of the motor group, is the motor output force of the nth motor at time t, is the environmental cost, is the additional cost of the mth part.

[0198] The preprocessing module 20 is further configured to obtain historical data of grid operation, determine new energy probability distribution data according to the historical data; obtain the current daily average load of the grid, calculate the power loss according to the current daily average load of the grid; determine the actually consumable new energy power according to the new energy probability distribution data, the power loss, the maximum new energy consumption, and the operating cost of the new energy system; evaluate the new energy consumption capacity through the actually consumable new energy power to obtain an evaluation result, and establish a new energy evaluation index system according to the evaluation result.

[0199] The preprocessing module 20 is further configured to preprocess the source domain data of the new energy source domain, perform deep learning on the preprocessed source domain data according to a deep learning model to obtain source domain deep learning features; preprocess the idle task domain data of the idle task domain to obtain idle task domain features, input the source domain deep learning features and the idle task domain features into a fixed feature layer, input the fixed features into a transfer learning model, and fine-tune the parameters outside the fixed layer to obtain fixed features; perform deep learning on the sufficient task domain data of the sufficient task domain according to the deep learning model to obtain task domain deep learning features; use the source domain deep learning features, the fixed features, and the task domain deep learning features as target data, and predict the new energy usage in the future period according to the target data to generate a new energy prediction system.

[0200] The development prediction module 30 is further configured to obtain the current power consumption through the following formula:

[0201]

[0202] Wherein, L is the current power consumption, t,1 represents the power consumption after response, E is a 3*3 matrix, is the change in power consumption at each moment, and P is the electricity price at a certain moment;

[0203] Obtain the objective function corresponding to customer satisfaction according to the following formula:

[0204]

[0205] Wherein, Y is the objective function, is the new energy consumption before change, is the new energy consumption after change, is the total new energy consumption, is the customer satisfaction, , is the total electricity cost before response, is the total electricity cost after response;

[0206] Adjust the current electricity consumption and current electricity price according to the objective function, and establish a new energy pricing model based on the adjusted electricity consumption and electricity price;

[0207] Carry out new energy system development and prediction according to the new energy evaluation index system, the new energy prediction system and the new energy pricing model.

[0208] Among them, the steps implemented by each functional module of the new energy development prediction device can refer to each embodiment of the new energy development prediction method of the present invention, which will not be elaborated here.

[0209] In addition, an embodiment of the present invention also proposes a storage medium, on which a new energy development prediction program is stored. When the new energy development prediction program is executed by a processor, the following operations are implemented:

[0210] Obtain the maximum new energy consumption and the operation cost of the new energy system, evaluate the consumption capacity of the new energy according to the maximum new energy consumption and the operation cost of the new energy system, and establish a new energy evaluation index system;

[0211] Preprocess the data of the new energy source domain and the task domain, and establish a new energy prediction system according to the preprocessed target data;

[0212] Establish a new energy pricing model, and carry out new energy system development and prediction according to the new energy evaluation index system, the new energy prediction system and the new energy pricing model.

[0213] Furthermore, when the new energy development prediction program is executed by a processor, the following operations are also implemented:

[0214] Obtain the new energy output power of the electric energy of the new energy and the electric power output power of the power system within a preset time period, and determine the maximum new energy consumption according to the new energy output power and the electric power output power;

[0215] Obtain the motor output force, the energy consumption cost of the motor group, and the environmental cost, and determine the operating cost of the new energy system according to the motor output force, the energy consumption cost of the motor group, and the environmental cost;

[0216] Evaluate the consumption capacity of new energy based on the maximum consumption of new energy and the operating cost of the new energy system, obtain an evaluation result, and establish a new energy evaluation index system according to the evaluation result.

[0217] Furthermore, when the new energy development prediction program is executed by a processor, the following operations are also implemented:

[0218] Obtain the new energy output force of the electric energy of new energy and the electric power output force of the power system within a preset time period;

[0219] Obtain the maximum consumption of new energy through the following formula according to the new energy output force and the electric power output force:

[0220]

[0221] where, is the maximum consumption of new energy, is the preset time period, and are the preset output weights, is the electric power output force of the power system at time t, is the new energy output force of the electric energy of new energy at time t.

[0222] Furthermore, when the new energy development prediction program is executed by a processor, the following operations are also implemented:

[0223] Obtain the motor output force, the energy consumption cost of the motor group, and the environmental cost;

[0224] Obtain the operating cost of the new energy system through the following formula according to the motor output force, the energy consumption cost of the motor group, and the environmental cost:

[0225]

[0226] where, is the operating cost of the new energy system, is the preset time period, N is the number of motors in the power system, is the energy consumption cost of the motor group, is the motor output force of the nth motor at time t, is the environmental cost, is the additional cost of the mth part.

[0227] Furthermore, when the new energy development prediction program is executed by a processor, the following operations are also implemented:

[0228] Obtain historical data of power grid operation, and determine new energy probability distribution data according to the historical data;

[0229] Obtain the daily average load of the current power grid, and calculate the power loss according to the daily average load of the current power grid;

[0230] Determine the actually consumable new energy power according to the new energy probability distribution data, the power loss, the maximum new energy consumption, and the operation cost of the new energy system;

[0231] Evaluate the absorption capacity of new energy through the actually consumable new energy power, obtain an evaluation result, and establish a new energy evaluation index system according to the evaluation result.

[0232] Furthermore, when the new energy development prediction program is executed by a processor, the following operations are also implemented:

[0233] Preprocess the source domain data of the new energy source domain, perform deep learning on the preprocessed source domain data according to a deep learning model, and obtain source domain deep learning features;

[0234] Preprocess the idle task domain data of the idle task domain, obtain idle task domain features, input the source domain deep learning features and the idle task domain features into a fixed feature layer, input the fixed features into a transfer learning model, and fine-tune the parameters outside the fixed layer to obtain fixed features;

[0235] Perform deep learning on the sufficient task domain data of the sufficient task domain according to the deep learning model, and obtain task domain deep learning features;

[0236] Use the source domain deep learning features, the fixed features, and the task domain deep learning features as target data, and predict the new energy usage in the future period according to the target data to generate a new energy prediction system.

[0237] Furthermore, when the new energy development prediction program is executed by a processor, the following operations are also implemented:

[0238] Obtain the current power consumption according to the following formula:

[0239]

[0240] where L is the current power consumption, t,1 represents the power consumption after response, E is a 3*3 matrix, is the change in power consumption at each moment, and P is the electricity price at a certain moment;

[0241] Obtain the objective function corresponding to customer satisfaction according to the following formula:

[0242]

[0243] Among them, Y is the objective function, is the new energy consumption before change, is the new energy consumption after change, is the total new energy consumption, is the customer satisfaction, , is the total electricity cost before response, is the total electricity cost after response;

[0244] Adjust the current electricity consumption and the current electricity price according to the objective function, and establish a new energy pricing model based on the adjusted electricity consumption and electricity price;

[0245] Develop and predict the new energy system according to the new energy evaluation index system, the new energy prediction system and the new energy pricing model.

[0246] Through the above solutions in this embodiment, by obtaining the maximum new energy consumption and the operation cost of the new energy system, evaluating the consumption capacity of the new energy according to the maximum new energy consumption and the operation cost of the new energy system, and establishing a new energy evaluation index system; preprocessing the data of the new energy source domain and the task domain, and establishing a new energy prediction system according to the preprocessed target data; establishing a new energy pricing model, and developing and predicting the new energy system according to the new energy evaluation index system, the new energy prediction system and the new energy pricing model, it is possible to timely conduct a hierarchical evaluation of the new energy consumption capacity, ensure the feasibility and profitability of the new energy in development and application, promote new energy consumption, improve the utilization ratio of new energy, avoid excessive consumption of new energy, save the power generation cost, improve the accuracy of new energy development prediction, and improve the speed and efficiency of new energy development prediction.

[0247] It should be noted that in this article, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article or device including that element.

[0248] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0249] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be similarly included in the patent protection scope of the present invention.

Claims

1. A new energy development prediction method, characterized in that, The new energy development prediction method includes: Obtain the maximum new energy consumption and the operation cost of the new energy system, evaluate the consumption capacity of the new energy according to the maximum new energy consumption and the operation cost of the new energy system, and establish a new energy evaluation index system; Preprocess the data of the new energy source domain and the task domain, and establish a new energy prediction system according to the preprocessed target data; Establish a new energy pricing model, and conduct new energy system development and prediction according to the new energy evaluation index system, the new energy prediction system and the new energy pricing model; Among them, the preprocessing of the data of the new energy source domain and the task domain, and the establishment of a new energy prediction system according to the preprocessed target data include: Preprocess the source domain data of the new energy source domain, and perform deep learning on the preprocessed source domain data according to the deep learning model to obtain source domain deep learning features; Preprocess the idle task domain data of the idle task domain to obtain idle task domain features, input the source domain deep learning features and the idle task domain features into a fixed feature layer, input the fixed features into a transfer learning model, and fine-tune the parameters outside the fixed layer to obtain fixed features; Perform deep learning on the sufficient task domain data of the sufficient task domain according to the deep learning model to obtain task domain deep learning features; Use the source domain deep learning features, the fixed features and the task domain deep learning features as target data, and predict the new energy usage in the future period according to the target data to generate a new energy prediction system; Among them, the establishment of a new energy pricing model, and the new energy system development and prediction according to the new energy evaluation index system, the new energy prediction system and the new energy pricing model include: Obtain the current electricity consumption according to the following formula: Among them, L is the current power consumption, t,1 represents the power consumption after response, E is a 3*3 matrix, which is the change in power consumption at each moment, and P is the electricity price at a certain moment; Obtain the objective function corresponding to the customer satisfaction according to the following formula: Among them, Y is the objective function, is the new energy consumption before the change, is the new energy consumption after the change, is the total new energy consumption, is the customer satisfaction, , is the total electricity cost before the response, is the total electricity cost after the response; Adjust the current electricity consumption and the current electricity price according to the objective function, and establish a new energy pricing model according to the adjusted electricity consumption and electricity price; Conduct new energy system development and prediction according to the new energy evaluation index system, the new energy prediction system and the new energy pricing model.

2. The new energy development prediction method according to claim 1, wherein The obtaining of the maximum new energy consumption and the operation cost of the new energy system, the evaluation of the consumption capacity of the new energy according to the maximum new energy consumption and the operation cost of the new energy system, and the establishment of a new energy evaluation index system include: Obtain the new energy output force of the electric energy of the new energy and the electric power output force of the power system within a preset time period, and determine the maximum new energy consumption according to the new energy output force and the electric power output force; Obtain the motor output force, the energy consumption cost of the motor group and the environmental cost, and determine the operation cost of the new energy system according to the motor output force, the energy consumption cost of the motor group and the environmental cost; Evaluate the consumption capacity of the new energy according to the maximum new energy consumption and the operation cost of the new energy system to obtain an evaluation result, and establish a new energy evaluation index system according to the evaluation result.

3. The new energy development prediction method according to claim 2, wherein The new energy output power that obtains the electric energy of new energy within a preset time period, and the electric power output power of the power system, and determining the maximum new energy consumption according to the new energy output power and the electric power output power includes: Obtaining the new energy output power that obtains the electric energy of new energy within a preset time period, and the electric power output power of the power system; Obtaining the maximum new energy consumption through the following formula according to the new energy output power and the electric power output power: Among them, is the maximum accommodation of new energy, is the preset time period, and are the preset output weights, is the power output of the power system at time t, is the new energy output of the new energy power at time t.

4. The new energy development prediction method according to claim 2, characterized in that The obtaining the motor output power, the energy consumption cost of the motor group and the environmental cost, and determining the operation cost of the new energy system according to the motor output power, the energy consumption cost of the motor group and the environmental cost includes: Obtaining the motor output power, the energy consumption cost of the motor group and the environmental cost; Obtaining the operation cost of the new energy system through the following formula according to the motor output power, the energy consumption cost of the motor group and the environmental cost: Among them, is the operating cost of the new energy system, is the preset time period, N is the number of motors in the power system, is the energy consumption cost of the motor group, is the motor output force of the nth motor at time t, is the environmental cost, is the additional cost of the mth part.

5. The new energy development prediction method according to claim 2, wherein The evaluating the consumption capacity of new energy according to the maximum new energy consumption and the operation cost of the new energy system, obtaining an evaluation result, and establishing a new energy evaluation index system according to the evaluation result includes: Obtaining the historical data of the power grid operation, and determining the new energy probability distribution data according to the historical data; Obtaining the daily average load of the current power grid, and calculating the power loss according to the daily average load of the current power grid; Determining the actually consumable new energy power according to the new energy probability distribution data, the power loss, the maximum new energy consumption and the operation cost of the new energy system; Evaluating the consumption capacity of new energy through the actually consumable new energy power, obtaining an evaluation result, and establishing a new energy evaluation index system according to the evaluation result.

6. A new energy development prediction device, characterized in that, The new energy development prediction device includes: An evaluation module, configured to obtain the maximum new energy consumption and the operation cost of the new energy system, evaluate the consumption capacity of new energy according to the maximum new energy consumption and the operation cost of the new energy system, and establish a new energy evaluation index system; A preprocessing module, configured to preprocess the data of the new energy source domain and the task domain, and establish a new energy prediction system according to the preprocessed target data; A development prediction module, configured to establish a new energy pricing model, and perform new energy system development and prediction according to the new energy evaluation index system, the new energy prediction system and the new energy pricing model; The preprocessing module is further configured to preprocess the source domain data of the new energy source domain, perform deep learning on the preprocessed source domain data according to a deep learning model to obtain source domain deep learning features; preprocess the idle task domain data of the idle task domain to obtain idle task domain features, input the source domain deep learning features and the idle task domain features into a fixed feature layer, input the fixed features into a transfer learning model, and fine-tune the parameters outside the fixed layer to obtain fixed features; perform deep learning on the sufficient task domain data of the sufficient task domain according to the deep learning model to obtain task domain deep learning features; use the source domain deep learning features, the fixed features and the task domain deep learning features as target data, and predict the new energy usage situation in the future period according to the target data to generate a new energy prediction system; The development prediction module is further configured to obtain the current power consumption according to the following formula: Among them, L is the current electricity consumption, t,1 represents the electricity consumption after response, E is a 3×3 matrix, which is the change in electricity consumption at each moment, and P is the electricity price at a certain moment; Obtain the objective function corresponding to the customer satisfaction according to the following formula: Among them, Y is the objective function, is the new energy consumption before the change, is the new energy consumption after the change, is the total new energy consumption, is the customer satisfaction, , is the total electricity cost before the response, is the total electricity cost after the response; adjust the current electricity consumption and the current electricity price according to the objective function, establish a new energy pricing model according to the adjusted electricity consumption and electricity price; conduct new energy system development and prediction according to the new energy evaluation index system, the new energy prediction system and the new energy pricing model.

7. A new energy development prediction device, characterized in that, The new energy development prediction device includes: a memory, a processor, and a new energy development prediction program stored on the memory and executable on the processor, the new energy development prediction program being configured to implement the steps of the new energy development prediction method according to any one of claims 1 to 5.

8. A storage medium, characterized in that, A new energy development prediction program is stored on the storage medium, and when the new energy development prediction program is executed by a processor, the steps of the new energy development prediction method according to any one of claims 1 to 5 are implemented.

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