Multi-energy complementary generating capacity proportioning method, system, equipment and medium

Abstract

The invention provides a proportioning method, system and equipment for multi-energy complementary generating capacity and a medium, and belongs to the field of new energy, and the method comprises the steps: obtaining energy data of a target sea area; respectively calculating power generation capacity coefficients of wind energy, wave energy, tidal current energy and photovoltaic solar energy in the target area based on the energy data and the parameters of the energy harvesting device; setting a minimum generating capacity threshold value of the target sea area in a preset time period, and constructing a relation function between a total capacity factor and wind, wave, tidal current and a capacity coefficient of the photovoltaic energy harvesting device; and according to the relation function, calculating the weight that each energy meets the minimum generating capacity threshold and the standard deviation of the total capacity factor is minimum, and according to weight parameters, matching wind, wave, tidal current and photovoltaic field generating capacity. According to the proportioning method, the dependence on historical data quality can be reduced, the reliability of a proportioning result is improved, and the cost of transport capacity calculation is reduced.

Description

Technical Field

[0001] The present invention belongs to the field of new energy, and specifically relates to a method, system, equipment and medium for matching power generation of multiple energy sources complementarily. Background Art

[0002] With the continuous growth of global energy demand and the increasingly severe environmental problems, renewable energy has become a key choice for achieving sustainable development. Offshore renewable energy, especially wind energy, wave energy, tidal energy and solar energy, has gradually become an important part of the energy field due to its abundant resources and environmental friendliness. Compared with traditional energy, offshore renewable energy not only has great development potential, but also can effectively reduce dependence on fossil fuels. However, the development of offshore renewable energy faces many challenges, the most prominent of which is the volatility and intermittency of energy. Therefore, achieving effective complementarity between these energy sources to ensure the stability and continuity of the power system is an urgent problem to be solved in the current development of offshore new energy.

[0003] The existing technology for optimizing the ratio of multi-energy complementary power generation capacity mainly adopts multi-objective optimization, intelligent algorithms, and time series analysis. In multi-objective optimization, genetic algorithms and particle swarm optimization algorithms (PSO) are often used to balance power generation costs, reliability and environmental impact. Intelligent algorithms use machine learning, such as support vector machines (SVM) and deep learning, to predict the volatility of renewable energy generation, thereby optimizing the power generation ratio. By analyzing historical meteorological data, machine learning models can predict changes in wind and solar energy, further improving resource utilization. In time series analysis, the ARIMA model is used to predict output fluctuations of different energy sources to support dynamic scheduling and load forecasting.

[0004] However, the above methods have several major problems when evaluating the capacity ratio of four-energy complementary power generation. First, the computational complexity and cost are high. Especially in large-scale, multi-objective optimization, genetic algorithms and particle swarm optimization algorithms require a lot of computing resources, resulting in increased system operating costs. Secondly, machine learning models are insufficient in assessing long-term sustainability, especially as the energy structure changes, existing models are difficult to accurately respond to long-term climate change and changes in resource supply. In addition, the data is highly dependent, and the accuracy is highly dependent on the quality of historical data. Incomplete or inaccurate data will lead to prediction errors and affect the reliability of the matching results. Summary of the invention

[0005] In order to solve the defects existing in the prior art when allocating offshore energy power generation, the present invention provides a method, system, equipment and medium for allocating multi-energy complementary power generation.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] A method for matching the power generation of multiple energy sources, comprising the following steps:

[0008] Acquiring energy data of the target sea area, wherein the energy data specifically refers to data characterizing wind, wave, tidal current and photovoltaic field performance;

[0009] Calculate the power generation capacity factors of wind, wave, tidal current and photovoltaic in the target area respectively based on the energy data and the energy capture device parameters;

[0010] The minimum power generation threshold of the target sea area within a preset time period is set, and a relationship function between the total capacity factor of the power generation equipment and the power generation capacity coefficients of the wind, wave, tidal and photovoltaic are constructed. The weights of each energy that meets the minimum power generation threshold and has the smallest standard deviation of the total capacity factor are calculated according to the relationship function, and the wind, wave, tidal and photovoltaic power generation are proportioned according to the weights of each energy.

[0011] Preferably, the relationship function between the total capacity factor and the power generation capacity coefficients of wind, wave, tidal and photovoltaic is specifically:

[0012] CF t =αCF wind +(1-α)[βCF wave +(1-β)(γCF tidal +(1-γ)CF solar ];

[0013] Among them, CF t is the total capacity factor, CF wind CF wave CF tidal and CF solar are the power generation capacity coefficients of wind energy, wave energy, tidal energy and solar energy respectively; α is the wind energy weight; β is the wave energy weight; γ is the tidal energy weight.

[0014] Preferably, the wind, wave, tidal and photovoltaic power generation are proportioned according to the weight of each energy. In the process of adjusting the weight values ​​of wind, wave, tidal and photovoltaic, when α=1, wind energy is used alone for power generation; when α=0, β=1 and γ=0, wave energy is used alone for power generation; when α=0, β=0 and γ=1, tidal energy is used alone for power generation; when α=0, β=0 and γ=0, solar energy is used alone for power generation.

[0015] Preferably, the calculation formula of the power generation capacity coefficient is:

[0016]

[0017] in, It represents the average value of the power output of the energy harvesting device, calculated based on the actual energy parameters, P eis the rated power of the energy harvesting device.

[0018] Preferably, the standard deviation of the total capacity factor is calculated by the following formula:

[0019]

[0020] Where N is the total number of hours, x i is the total capacity factor at the ith hour, and μ is the average value of the total capacity factor.

[0021] The present invention also provides a multi-energy complementary power generation ratio system, which specifically includes:

[0022] The data acquisition module is used to acquire energy data of the target sea area, wherein the energy data specifically refers to data characterizing the performance of wind, waves, tidal currents and photovoltaic fields.

[0023] The data processing module is used to calculate the power generation capacity factors of wind, wave, tidal current and photovoltaic in the target area respectively based on the energy data and the parameters of the energy capture device.

[0024] A matching module is used to set a minimum power generation threshold value for the target sea area within a preset time period, construct a relationship function between the total capacity factor of the power generation equipment and the power generation capacity coefficients of the wind, wave, tidal and photovoltaic, calculate the weight of each energy that meets the minimum power generation threshold value and has the smallest standard deviation of the total capacity factor according to the relationship function, and match the wind, wave, tidal and photovoltaic power generation according to the weight of each energy.

[0025] The present invention also provides a computer device, including a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps described in the method for matching the power generation of multiple energy sources complementarily.

[0026] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is loaded by a processor, the steps described in the method for matching the power generation of multiple energy sources complementarily can be executed.

[0027] The method for matching the power generation amount of multiple energy sources provided by the present invention has the following beneficial effects:

[0028] The present invention calculates the power generation capacity coefficients of wind, wave, tidal and photovoltaic in the target area based on the energy data and energy capture device parameters of the target sea area, and establishes a relationship function with the total capacity factor according to the capacity coefficient. The energy weight that meets the minimum power generation threshold and has the smallest standard deviation of the total capacity factor is calculated based on the relationship function, and the power generation of wind energy, wave energy, tidal energy and photovoltaic field is matched according to the weight. The power generation is matched based on the power generation capacity coefficient of the energy capture device, which reduces the complexity of calculation and transportation cost, does not rely on historical data, and realizes long-term matching adjustment according to different seasons and energy structures, and the matching result is highly accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiment of the present invention and its design scheme, the following briefly introduces the drawings required for this embodiment. The drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 The present invention is a flow chart of a method for matching power generation of multiple energy sources complementary to each other.

[0031] Figure 2 Schematic diagram of the wind energy, wave energy, tidal energy and solar energy capacity coefficients in the four seasons of Archipelago A in 2020 in the present invention.

[0032] Figure 3 Schematic diagram of the A archipelago region division result in an embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the technical solution of the present invention and implement it, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the scope of protection of the present invention.

[0034] Example

[0035] The present invention provides a method for matching the power generation of multiple energy sources. Figure 1 As shown, specifically including:

[0036] S1. Obtain the wind, wave, tidal current and photovoltaic field data of the target area, taking Archipelago A as an example. Download the wind, wave, tidal current and photovoltaic field data files of the target area from ERA5 (ECMWF Reanalys is v5) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The data types include: wind speed, effective wave height, wave period, tidal current speed, sunshine intensity, photovoltaic irradiation, etc. According to the latitude and longitude range of the target area, select a period of time (such as historical data or forecast data). Preprocess the downloaded raw data to remove obvious outliers, such as extreme error values ​​or missing data.

[0037] S2. Determine the matching relationship between the energy capture device and the characteristics of wind energy, wave energy, tidal energy and solar energy, compare the rated wind speed of the wind turbine with the actual wind speed data of the target area, and ensure that the wind speed is within the working range of the wind turbine (the setting error does not exceed 10%). According to the working wave height and working cycle setting of the wave energy converter, ensure that the wave conditions (effective wave height, wave cycle) in the target area meet the requirements of the converter. According to the rated flow rate of the tidal energy converter, compare it with the tidal velocity in the target area, and ensure that the error does not exceed 10%. According to the area and conversion rate of the solar photovoltaic panel, calculate its power generation capacity and match it with the sunshine intensity data of the target area to ensure the working efficiency of the photovoltaic device. Based on the matching results of wind, waves, tidal currents and photovoltaics, the device specifications of the four energy sources in the target area are determined to be wind turbine EN-252 / 10.5, wave energy converter Wave Dragon, tidal energy converter NNU-300k, and N-type single crystal 210. According to the selected models, calculate the annual power generation and capacity factor of each model, and define the total capacity factor to evaluate the complementarity of the combination of four renewable energy power generation methods.

[0038] S3. Based on the energy data of the target area and the parameters of the energy capture device, the seasonal power generation capacity factors of wind, wave, tidal and photovoltaic are calculated respectively, such as Figure 2 As shown, the specific formula is as follows:

[0039]

[0040] in, represents the average value of the power output of the energy harvesting device, which is calculated based on the energy density of each energy source; P e It is the rated power of the energy harvesting device, which can be found in the technical manual of the energy converter.

[0041] S4. Calculate the standard deviation of the total capacity factor based on the hourly capacity factor and the average capacity factor, evaluate the stability and variability of the four energy sources, and analyze the proportion of each energy source that can produce the most stable power generation. The standard deviation of the total capacity factor is calculated using the following formula:

[0042]

[0043] Where N is the total number of hours, x i is the total capacity factor at the ith hour, and μ is the average value of the total capacity factor.

[0044] S5. Divide the A archipelago into regions, such as Figure 3 As shown. Find the weights of wind, wave, tidal and photovoltaic energy capture that meet the minimum power generation threshold and minimize the standard deviation of the total capacity factor, that is, the four-energy complementary power generation ratio. According to different time scales, the four-energy complementary power generation ratio can be achieved on a daily, monthly, quarterly and annual basis. According to regional needs, set an annual minimum power generation threshold of 500kW, which represents the minimum power generation requirement within a year. Define the relationship function between the total capacity factor (CFt) and the capacity coefficient of wind, wave, tidal and photovoltaic energy capture devices, specifically:

[0045] CF t =αCF wind +(1-α)[βCF wave +(1-β)(γCF tidal +(1-γ)CF solar ];

[0046] Among them, CF t is the total capacity factor, CF wind CF wave CF tidal and CF solar are the power generation capacity factors of wind energy, wave energy, tidal energy and solar energy respectively; α is the wind energy weight; β is the wave energy weight; γ is the tidal energy weight; α is the contribution of wind energy to the total capacity factor, (1-α)β is the contribution of wave energy to the total capacity factor, (1-α)(1-β)γ is the contribution of tidal energy to the total capacity factor, and (1-α)(1-β)(1-γ) is the contribution of solar energy to the total capacity factor.

[0047] When α=1, only wind power is used for power generation; when α=0, β=1 and γ=0, all power comes from wave power; when α=0, β=0 and γ=1, only tidal power is used for power generation; when α=0, β=0 and γ=0, only solar power is used for power generation.

[0048] The total capacity factor under different weights is calculated by adjusting the weights of the four energy sources (α, β, γ and 1-α-β-γ). tThe value of x i Substitute the standard deviation formula to calculate the standard deviation of the total capacity factor under different weights. Find the wind, wave, tidal and photovoltaic complementary power generation ratio that meets the minimum power generation threshold of 500kW and has the smallest standard deviation of the total capacity factor.

[0049] Based on actual demand, the power generation ratio of the four energies is adjusted on an annual time scale, as shown in Table 1.

[0050] Table 1 The percentage of each energy when the standard deviation of the total capacity factor in different sea areas is minimized

[0051]

[0052] The present invention also provides a multi-energy complementary power generation ratio system, which specifically includes:

[0053] The data acquisition module is used to obtain energy data of the target sea area, and the energy data specifically refers to data characterizing the performance of wind, waves, tidal currents and photovoltaic fields.

[0054] The data processing module is used to calculate the power generation capacity factors of wind, wave, tidal current and photovoltaic in the target area respectively based on the energy data and the parameters of the energy capture device.

[0055] The matching module is used to set the minimum power generation threshold of the target sea area within a preset time period, construct the relationship function between the total capacity factor of the power generation equipment and the power generation capacity coefficients of wind, wave, tidal and photovoltaic, calculate the weight of each energy that meets the minimum power generation threshold and has the smallest standard deviation of the total capacity factor according to the relationship function, and match the wind, wave, tidal and photovoltaic power generation according to the weight of each energy.

[0056] Each module in the above-mentioned multi-energy complementary power generation matching system can be implemented in whole or in part by software, hardware and their combination. Each module 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 each module above.

[0057] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps in an embodiment of a method for matching the power generation of multiple energy sources complementary to each other. The specific implementation method can be found in the method embodiment, which will not be described in detail here.

[0058] Furthermore, the present invention also provides a non-temporary computer-readable storage medium containing instructions, and a computer program is stored on the storage medium. For example, a memory containing instructions, the above instructions can be executed by a processor of a computer device to complete the above method. For example, a non-temporary computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device. When the computer program is executed by the processor, it can implement the steps in an embodiment of a method for matching the power generation of multiple energy sources complementarily. The specific implementation method can be found in the method embodiment, which will not be repeated here.

[0059] It will be appreciated by those skilled in the art that embodiments of the present invention may provide methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0060] The present invention is described with reference to flowcharts and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as a combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0061] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0062] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1A step that specifies a function in one or more boxes.

[0063] It should be pointed out that the specific implementation methods described above can enable those skilled in the art to understand the invention more comprehensively, but do not limit the invention in any way. Therefore, although the invention has been described in detail in this specification and embodiments, those skilled in the art should understand that the invention can still be modified or replaced by equivalents; and all technical solutions and improvements that do not deviate from the spirit and scope of the invention are included in the protection scope of the patent for the invention. Any figure mark in the claims should not be regarded as limiting the claims involved. Any simple change or equivalent replacement of the technical solution that can be obviously obtained by any technician familiar with the field within the technical scope disclosed in the present invention belongs to the protection scope of the present invention.

Claims

1. A method for matching the power generation of multiple energy sources, characterized in that: The following steps are involved: Acquiring energy data of the target sea area, wherein the energy data specifically refers to data characterizing wind, wave, tidal current and photovoltaic field performance; Calculate the power generation capacity factors of wind, wave, tidal current and photovoltaic in the target area respectively based on the energy data and the energy capture device parameters; The minimum power generation threshold of the target sea area within a preset time period is set, and a relationship function between the total capacity factor of the power generation equipment and the power generation capacity coefficients of the wind, wave, tidal and photovoltaic are constructed. The weights of each energy that meets the minimum power generation threshold and has the smallest standard deviation of the total capacity factor are calculated according to the relationship function, and the wind, wave, tidal and photovoltaic power generation are proportioned according to the weights of each energy.

2. A method for matching the power generation of multiple energy sources according to claim 1, characterized in that: The relationship function between the total capacity factor and the power generation capacity coefficients of wind, wave, tidal and photovoltaic is specifically: CF t =αCF wind +(1-α)[βCF wave +(1-β)(γCF tidal +(1-γ)CF solar ]; Among them, CF t is the total capacity factor, CF wind CF wave CF tidal and CF solar are the power generation capacity coefficients of wind energy, wave energy, tidal energy and solar energy respectively; α is the wind energy weight; β is the wave energy weight; γ is the tidal energy weight.

3. A method for matching the power generation of multiple energy sources according to claim 2, characterized in that: The wind, wave, tidal and photovoltaic power generation are proportioned according to the weight of each energy. In the process of adjusting the weight values ​​of wind, wave, tidal and photovoltaic, when α=1, wind energy is used alone for power generation; when α=0, β=1 and γ=0, wave energy is used alone for power generation; when α=0, β=0 and γ=1, tidal energy is used alone for power generation; when α=0, β=0 and γ=0, solar energy is used alone for power generation.

4. A method for matching the power generation of multiple energy sources according to claim 1, characterized in that: The calculation formula of the power generation capacity factor is: in, It represents the average value of the power output of the energy harvesting device, calculated based on the actual energy parameters, P e is the rated power of the energy harvesting device.

5. A method for matching the power generation of multiple energy sources according to claim 1, characterized in that: The standard deviation of the total capacity factor is specifically calculated by the following formula: Where N is the total number of hours, x i is the total capacity factor at the ith hour, and μ is the average value of the total capacity factor.

6. A system for matching the power generation of multiple energy sources, characterized in that: include: A data acquisition module is used to acquire energy data of the target sea area, wherein the energy data specifically refers to data characterizing wind, wave, tidal current and photovoltaic field performance; A data processing module, for calculating the power generation capacity factors of wind, wave, tidal current and photovoltaic in the target area respectively based on the energy data and the energy capture device parameters; A matching module is used to set a minimum power generation threshold value for the target sea area within a preset time period, construct a relationship function between the total capacity factor of the power generation equipment and the power generation capacity coefficients of the wind, wave, tidal and photovoltaic, calculate the weight of each energy that meets the minimum power generation threshold value and has the smallest standard deviation of the total capacity factor according to the relationship function, and match the wind, wave, tidal and photovoltaic power generation according to the weight of each energy.

7. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is loaded into a processor, it can execute the steps of the method according to any one of claims 1 to 5.

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