Park-level control method and system based on weather

Abstract

The invention discloses a weather-based park-level control method and system, and the method comprises the steps: collecting weather data, building power generation power prediction models of different weather types, and obtaining the power generation prediction power of different weather types; the method comprises the following steps: collecting park power generation power and power utilization power at different time points in real time, collecting and storing park power generation power and power utilization power historical data, and constructing a park power utilization power prediction model; and executing the park electricity utilization power prediction model according to the electricity generation prediction power of different weather types to realize intelligent control of park load. The method has the advantages of improving the energy utilization efficiency, reducing energy consumption and carbon emission, improving the operation efficiency and management level of the park, promoting technical innovation and industrial upgrading and the like, and is beneficial to achieving the purposes of energy conservation, emission reduction and sustainable development of the park.

Description

Background Art

[0002] With the development of science and technology, intelligent control technology has been widely used in the management of various parks. However, most of the existing intelligent control strategies are based only on the real-time operation data of the park, and do not make full use of weather forecast information, resulting in poor operation efficiency and energy consumption control of the park under certain weather conditions with large changes.

[0003] In the context of the current rapid development of intelligence, park management is undergoing a profound transformation from traditional models to intelligent and refined management. As the core driving force of this transformation, intelligent control technology has shown great potential in improving park operation efficiency, optimizing resource allocation, and reducing energy consumption. However, as you pointed out, existing intelligent control strategies often seem to be unable to cope with complex and changeable weather conditions. This is mainly because most of them rely only on the real-time operation data of the park, while ignoring the important external factor of weather forecast information.

[0004] Weather conditions have a direct and significant impact on the operation of the park. For example, in hot weather, the energy consumption of the air conditioning system will rise sharply; and on rainy days, insufficient natural light may lead to increased energy consumption for indoor lighting. In addition, extreme weather such as strong winds and heavy rains may also pose a threat to the safety of the park's infrastructure, and preventive and countermeasure measures need to be taken in advance. Therefore, incorporating weather forecast information into intelligent control strategies is the key to achieving more accurate and efficient park management.

[0005] The application of intelligent control technology in park management, especially in the field of energy management, has become a key means to improve park operation efficiency and reduce energy consumption. However, the existing intelligent control strategy mainly relies on the real-time operation data of the park and fails to make full use of weather forecast information, which to a certain extent limits its adaptability and effectiveness in dealing with large weather changes. The specific analysis is as follows:

[0006] 1. Importance of weather forecast information

[0007] Reducing uncertainty: Weather forecast information can help park managers understand the climate conditions in the future in advance, so that they can fully consider these conditions when formulating intelligent control strategies and reduce the uncertainty caused by weather changes.

[0008] Optimize energy consumption: By analyzing weather forecast information, the intelligent control system can timely adjust energy consumption patterns according to changes in weather conditions, achieving more accurate and efficient energy management.

[0009] 2. Limitations of existing intelligent control strategies

[0010] Reliance on real-time operating data: Existing intelligent control strategies mainly make decisions based on the real-time operating data of the park. These data can only reflect the current operating status but cannot predict future operating needs.

[0011] Insufficient ability to cope with weather changes: When weather conditions change significantly, the existing intelligent control strategy may not be able to adjust the control strategy in time, resulting in poor operational efficiency and energy consumption control of the park.

[0012] 3. Intelligent control strategy combined with weather forecast information

[0013] Integrate weather forecast information: Combining weather forecast information with the park’s real-time operating data as a basis for decision-making in intelligent control strategies can make intelligent control systems more flexible and adaptable.

[0014] Dynamically adjust control strategies: According to changes in weather forecast information, the intelligent control system can dynamically adjust the control strategy to achieve more accurate and efficient energy management.

[0015] 4. Implementation Path

[0016] Data fusion: It is necessary to integrate weather forecast information with real-time park operation data and establish a comprehensive data model so that the intelligent control system can fully consider the impact of various factors.

[0017] Algorithm optimization: The algorithm used by the intelligent control strategy needs to be optimized so that it can respond to weather changes more flexibly and improve the adaptability and effectiveness of the control strategy.

[0018] In short, with the continuous development and improvement of weather forecasting technology, combining it with intelligent control technology is expected to bring greater value and benefits to park management. By making full use of weather forecast information, the park's operational efficiency and energy consumption control effect can be further improved, and more intelligent and personalized park management can be achieved. Summary of the invention

[0019] The technical problem to be solved by the present invention is to provide a weather-based park-level control method and system in response to the deficiencies in the above-mentioned prior art, which is used to solve the technical problem that the existing intelligent control strategy is only based on the real-time operation data of the park and does not make full use of weather forecast information, resulting in poor operating efficiency and energy consumption control of the park under certain conditions of large weather changes.

[0020] The present invention adopts the following technical solutions:

[0021] A park-level control method based on weather includes the following steps:

[0022] Collect weather data, build power generation prediction models for different weather types, and obtain the predicted power generation for different weather types;

[0023] Collect the park's power generation and power consumption at different time points in real time, collect and store the park's power generation and power consumption historical data, and build a park power consumption prediction model;

[0024] The power consumption prediction model of the park is implemented according to the predicted power generation under different weather conditions to realize intelligent control of the park load.

[0025] Preferably, the predicted power generation under different weather types is obtained as follows:

[0026] According to the weather conditions, the weather is divided into thunderstorm, freezing and high temperature, and the radiation values ​​Sv1, Sv2 and Sv3 of the corresponding types of weather are collected respectively;

[0027] According to the weather radiation value collection time interval, the park power generation power Pfa corresponding to the time interval is obtained;

[0028] According to the weather type, a power generation prediction model for different weather types is built to predict the power generation prediction power P predicted at different times t under different weather types.

[0029] Preferably, the predicted power generation power P during thunderstorms 预Sv1 for

[0030]

[0031] Among them, n is the total number of model statistics, i is any one of the total number, Sv1 is the radiation value of thunderstorm weather, P Sv1 is the power generation corresponding to the historical thunderstorm days, is the average power generation on thunderstorm days, is the average radiation value on a thunderstorm day.

[0032] Preferably, the freezing weather power generation forecast power P 预Sv2 for:

[0033]

[0034] Among them, n is the total number of model statistics, i is any one of the total number of times, Sv2 is the radiation value of freezing weather, P Sv2 is the power generation corresponding to the historical freezing weather, is the average power generation in freezing weather, is the average radiation value on a thunderstorm day.

[0035] Preferably, the predicted power generation in high temperature weather P 预Sv3 for:

[0036]

[0037] Among them, n is the total number of model statistics, i is any one of the total number n, Sv3 is the radiation value of high temperature weather, P Sv3 is the power generation corresponding to the historical freezing weather, is the average power generation in freezing weather, is the average radiation value on a thunderstorm day.

[0038] Preferably, the construction of the park power consumption prediction model is specifically as follows:

[0039] According to the future weather conditions and radiation value forecast, the above prediction model is intelligently matched to predict the power generation at the collection point j in the next day;

[0040] Calculate the correlation index R by using the predicted power generation and the actual power generation 2 Whether it is close to 1 is used to judge the fitting degree of the weather type-power generation prediction model, providing an adjustment basis for model optimization;

[0041] Collect the total power consumption P1 of the park at different times t;

[0042] The power consumption model at different times t in the future is predicted based on the park power consumption P1 at different times.

[0043] Preferably, the correlation index R 2 for:

[0044]

[0045] Among them, R 2 Calculate the correlation index between the predicted power generation and the actual power generation, n is the total number of model statistics, i is any one of the total number n, Pi is the actual power generation for the i-th time, Pi is the predicted power generation for the i-th time, It indicates the average value of actual power generation when the total number of times is n.

[0046] Preferably, the power consumption model P at different times t in the future day 1预 for:

[0047]

[0048] Among them, n is the total number of model statistics, N is the last number in n, i is any one of the total number, P1 is the historical power consumption of the load that can be powered off, P 1预 is the predicted power consumption of the load that can be shut down in the next day, k is the proportion coefficient, P N is the last historical electricity consumption.

[0049] Preferably, the intelligent control of the park load is realized by:

[0050] Adjust the power load of the park according to the difference between the predicted power generation and the predicted power consumption of the park:

[0051] When the difference is greater than or equal to 0, the power load power is not regulated;

[0052] When the difference is less than 0, while ensuring the power supply to important loads, some loads that can be shut down can be shut down to ensure that the difference is greater than or equal to 0.

[0053] In a second aspect, an embodiment of the present invention provides a weather-based park-level control system, including:

[0054] The data module collects weather data, builds a power generation prediction model for different weather types, and obtains the predicted power generation for different weather types;

[0055] The acquisition module collects the park's power generation and power consumption at different time points in real time, collects and stores the park's power generation and power consumption historical data, and builds a park power consumption prediction model;

[0056] The control module predicts the power generation according to different weather types, executes the park power prediction model, and realizes intelligent control of the park load.

[0057] In a third aspect, a computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned weather-based park-level control method when executing the computer program.

[0058] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned weather-based park-level control method.

[0059] Compared with the prior art, the present invention has at least the following beneficial effects:

[0060] A weather-based park-level control method can more accurately predict the photovoltaic power generation under various weather conditions by establishing a power generation prediction model for different weather types, so as to better match the power demand of the park and reduce energy waste; by intelligently controlling the power load of the park, the power consumption can be adjusted according to the change of power generation, avoiding the increase of energy cost due to excess or insufficient power; by real-time monitoring of the power generation and power consumption of the park and adjusting the power load according to weather changes, it can effectively reduce the interruption and failure caused by unstable power supply and improve the stability and reliability of power supply; it helps to better integrate and utilize renewable energy, such as solar energy, and promote the development and application of green energy; by collecting and analyzing the historical data of power generation and power consumption of the park, it can provide data support for the energy management and optimization of the park and help decision makers make more scientific and reasonable decisions; the control strategy can be adjusted according to different weather conditions, with good adaptability and flexibility, and is suitable for various types of parks and different energy system configurations; the weather-based park-level control method promotes the development and application of technologies such as smart grids and big data analysis, and helps to promote technological innovation and industrial upgrading in related industries.

[0061] Furthermore, improve energy efficiency: by collecting weather data and predicting power generation under different weather conditions, the system can adjust and optimize the energy usage plan of the park in advance. This helps to ensure that excess power is effectively used when power generation is high, or take measures in advance to reduce unnecessary power consumption when power generation is insufficient, thereby improving overall energy efficiency.

[0062] Furthermore, the reliability of power supply is enhanced: the method can predict the power demand of the park under different weather conditions and perform intelligent regulation based on the predicted power generation. This helps to maintain the stability of the power supply of the park under extreme weather conditions (such as strong winds, heavy rains, etc.), reduce the risk of power outages caused by mismatch between supply and demand, and improve power supply reliability.

[0063] Furthermore, optimize energy costs: through accurate power generation and power consumption forecasts, the park can arrange power purchase, storage and use plans more reasonably. When the power generation capacity is higher than the power demand, the park can store or sell the excess power to the grid, and when the power demand is at a peak, it can use energy storage equipment or purchase external power to meet the demand, thereby optimizing energy costs.

[0064] Furthermore, it promotes the use of renewable energy: For parks that rely on renewable energy (such as solar energy and wind energy), this method can more accurately predict the power generation, allowing the park to better utilize these clean energy sources. On sunny or windy days, the park can make full use of renewable energy to generate electricity, reduce dependence on traditional energy, reduce carbon emissions, and promote sustainable development.

[0065] Furthermore, the level of intelligence in management decisions is improved: by building power generation and power consumption prediction models and combining them with weather data, park managers can make decisions based on more comprehensive information. This intelligent management method not only improves the scientificity and accuracy of decision-making, but also reduces the risk of human misjudgment.

[0066] Furthermore, improving user experience: Stable power supply and reasonable energy use plan can help improve the satisfaction of residents, businesses and employees in the park. By reducing power outages and lowering energy costs, the park can create a more comfortable and convenient working and living environment, thereby improving user experience.

[0067] Furthermore, it supports sustainable development goals: This control method encourages the park to adopt renewable energy, reduce dependence on traditional energy, and optimize energy efficiency. This helps to reduce the park's carbon emissions, reduce negative impacts on the environment, and support global sustainable development goals.

[0068] It can be understood that the beneficial effects of the second aspect mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0069] In summary, the method of the present invention has the advantages of improving energy utilization efficiency, reducing energy consumption and carbon emissions, improving the operational efficiency and management level of the park, and promoting technological innovation and industrial upgrading, which is helpful to achieve the park's energy conservation, emission reduction and sustainable development goals.

[0070] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings to be used in the description of the embodiments. Obviously, 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.

[0072] Figure 1 It is a schematic diagram of the process of the present invention;

[0073] Figure 2 A schematic diagram of a computer device provided by an embodiment of the present invention.

[0074] Figure 3 The present invention is a block diagram of an electronic device provided according to an embodiment. DETAILED DESCRIPTION

[0075] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0076] In the description of the present invention, it should be understood that the terms “include” and “comprises” indicate the presence of described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0077] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0078] It should be further understood that the term "and / or" used in the present specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes these combinations. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects are in an "or" relationship.

[0079] It should be understood that, although the terms first, second, third, etc. may be used to describe preset ranges, etc. in the embodiments of the present invention, these preset ranges should not be limited to these terms. These terms are only used to distinguish preset ranges from each other. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0080] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0081] Various structural schematic diagrams of the embodiments disclosed in the present invention are shown in the accompanying drawings. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clear expression. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0082] The present invention provides a park-level control method based on weather. By using weather forecast data, an intelligent linear regression fitting model is built to predict the power generation under different weather types and at different times. The correlation index R is calculated by comparing the power generation forecast power with the actual power generation power. 2 Whether it is close to 1 is used to judge the degree of fit of the weather type-power generation prediction model, providing an adjustment basis for model optimization; the intelligent prediction park power algorithm model based on linear regression of historical power consumption data and with correction function predicts the power consumption at different time points in the future day.

[0083] The present invention provides a park-level control method based on weather, comprising the following steps:

[0084] S1. Collect weather data;

[0085] Utilize data provided by weather forecast systems or meteorological departments, including but not limited to weather conditions and radiation values.

[0086] S2, strategy formulation;

[0087] S201, classifying the weather into several categories, such as thunderstorm, freezing and high temperature, according to the weather conditions, and collecting radiation values ​​Sv1, Sv2 and Sv3 of the corresponding types of weather respectively;

[0088] S202, obtaining the park power generation power Pfa at the corresponding time interval according to the weather radiation value collection time interval;

[0089] S203, building a power generation prediction model for different weather types according to the weather types to predict the power generation P predicted at different times t under different weather types;

[0090] Divide a day into j time points, and for each time point t j The prediction model is as follows:

[0091] Power Generation Prediction Model for Thunderstorm Days

[0092]

[0093] Among them, n is the total number of model statistics, i is any one of the total number, Sv1 is the radiation value of thunderstorm weather, PSv1 is the power generation corresponding to the historical thunderstorm days, is the average power generation on thunderstorm days, is the average radiation value on a thunderstorm day, P 预Sv1 The predicted power for thunderstorm days.

[0094] Freezing Weather Power Generation Prediction Model

[0095]

[0096] Among them, n is the total number of model statistics, i is any one of the total number of times, Sv2 is the radiation value of freezing weather, P Sv2 is the power generation corresponding to the historical freezing weather, is the average power generation in freezing weather, is the average radiation value on a thunderstorm day, P 预Sv2 Forecast power for freezing weather.

[0097] High temperature weather power generation prediction model

[0098]

[0099] Among them, n is the total number of model statistics, i is any one of the total number n, Sv3 is the radiation value of high temperature weather, P Sv3 is the power generation corresponding to the historical freezing weather, is the average power generation in freezing weather, is the average radiation value on a thunderstorm day, P 预Sv3 Forecast power for hot weather.

[0100] S204, intelligently matching the above prediction model according to future weather conditions and radiation value forecast to predict the power generation at the collection point j in the next day;

[0101] S205, calculating the correlation index R by using the predicted power generation and the actual power generation 2 Whether it is close to 1 is used to judge the fitting degree of the weather type-power generation prediction model, providing an adjustment basis for model optimization;

[0102] The calculation method is:

[0103]

[0104] Among them, R 2 Calculate the correlation index between the predicted power generation and the actual power generation, n is the total number of model statistics, i is any one of the total number n, Pi is the actual power generation for the i-th time, Pi is the predicted power generation for the i-th time, It indicates the average value of actual power generation when the total number of times is n.

[0105] S206, collecting the total power consumption P1 of the park at different times t;

[0106] S207, predicting the power consumption model at different times t in the future day according to the park power consumption P1 at different times;

[0107] Power consumption P1 prediction model for loads that can be powered off

[0108]

[0109] Among them, n is the total number of model statistics, N is the last number in n, i is any one of the total number, P1 is the historical power consumption of the load that can be powered off, P 1预 is the predicted power consumption of the load that can be powered off in the next day, k (0≤k≤100%) is the proportion coefficient (the proportion coefficient is adjusted artificially according to the prediction accuracy), P N is the last historical electricity consumption.

[0110] S208. Adjust the power load of the park according to the difference between the predicted power generation and the predicted power consumption of the park.

[0111] When the difference is greater than or equal to 0, the power load power will not be regulated; when the difference is less than 0, while ensuring the power supply to important loads, some loads that can be shut down will be shut down to ensure that the difference is greater than or equal to 0.

[0112] It will be appreciated by those skilled in the art that various aspects of the present invention may be implemented as a system, method or program product. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as a "circuit", "module" or "platform".

[0113] In yet another embodiment of the present invention, a weather-based park-level control system is provided, which can be used to implement the above-mentioned weather-based park-level control method. Specifically, the weather-based park-level control system includes a data module, a collection module and a control module.

[0114] Among them, the data module collects weather data, builds a power generation prediction model for different weather types, and obtains the power generation prediction for different weather types;

[0115] The acquisition module collects the park's power generation and power consumption at different time points in real time, collects and stores the park's power generation and power consumption historical data, and builds a park power consumption prediction model;

[0116] The control module predicts the power generation according to different weather types, executes the park power prediction model, and realizes intelligent control of the park load.

[0117] In another embodiment of the present invention, a terminal device is provided, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of the weather-based park-level control method, including:

[0118] Collect weather data, build power generation prediction models for different weather types, and obtain predicted power generation for different weather types; collect the park's power generation and power consumption at different time points in real time, collect and store the park's power generation and power consumption historical data, and build a park power consumption prediction model; execute the park power consumption prediction model according to the power generation prediction for different weather types to achieve intelligent control of the park's load.

[0119] In another embodiment of the present invention, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a terminal device for storing programs and data. It is understandable that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and the extended storage medium supported by the terminal device, and can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that more specific examples (non-exhaustive list) of the computer-readable storage medium here include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0120] Computer readable storage media also include data signals propagated in baseband or as part of a carrier wave, which carry readable program codes. Such propagated data signals can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable storage medium can also be any readable medium other than a readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or device. The program code contained on the readable storage medium can be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

[0121] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0122] The processor may load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the weather-based park-level control method in the above embodiment; the processor may load and execute the following steps:

[0123] Collect weather data, build power generation prediction models for different weather types, and obtain predicted power generation for different weather types; collect the park's power generation and power consumption at different time points in real time, collect and store the park's power generation and power consumption historical data, and build a park power consumption prediction model; execute the park power consumption prediction model according to the power generation prediction for different weather types to achieve intelligent control of the park's load.

[0124] See also Figure 2 , the terminal device is a computer device, and the computer device 60 of this embodiment includes: a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When the computer program 63 is executed by the processor 61, the weather-based park-level control method in the embodiment is implemented. To avoid repetition, it is not described one by one here. Alternatively, when the computer program 63 is executed by the processor 61, the functions of each model / unit in the weather-based park-level control system in the embodiment are implemented. To avoid repetition, it is not described one by one here.

[0125] The computer device 60 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will appreciate that Figure 2 This is only an example of the computer device 60 and does not constitute a limitation of the computer device 60. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, buses, etc.

[0126] The processor 61 may be a central processing unit (CPU), or other general-purpose processors, central processing units, graphics processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, data processing logic based on quantum computing, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0127] The memory 62 may be an internal storage unit of the computer device 60, such as a hard disk or memory of the computer device 60. The memory 62 may also be an external storage device of the computer device 60, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the computer device 60.

[0128] Furthermore, the memory 62 may include both an internal storage unit of the computer device 60 and an external storage device. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 may also be used to temporarily store data that has been output or is to be output.

[0129] Any reference to memory, database or other media used in the embodiments provided in the present application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0130] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0131] See also Figure 3 The terminal device 600 is an electronic device, and the electronic device is in the form of a general computing device. The components of the electronic device may include but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including the storage unit 620 and the processing unit 610), a display unit 640, etc.

[0132] The storage unit stores program codes, which can be executed by the processing unit 610, so that the processing unit 610 performs the steps according to various exemplary embodiments of the present invention described in the above method section of this specification. For example, the processing unit 610 can perform the following steps: Figure 1 Follow the steps shown in .

[0133] The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 6201 and / or a cache memory unit 6202 , and may further include a read-only memory unit (ROM) 6203 .

[0134] The storage unit 620 may also include a program / utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0135] Bus 630 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0136] The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 600, and / or communicate with any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 650. Furthermore, the electronic device 600 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 via a bus 630. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms, etc.

[0137] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention described and shown in the drawings here can usually be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0138] The weather-based park-level control method simulation aims to evaluate and optimize the control strategy by simulating the operation status of the park under different weather conditions, so as to improve the park's operating efficiency, energy conservation and emission reduction capabilities, and ability to cope with extreme weather.

[0139] Weather data acquisition and model building

[0140] Weather data acquisition:

[0141] The weather data of the park area is obtained through measured data from meteorological stations, historical data backtracking or weather model predictions, including temperature, humidity, precipitation, wind speed, wind direction, light, etc.

[0142] The data should be highly accurate and timely to ensure the reliability of the simulation results.

[0143] Weather model construction:

[0144] Based on the weather data obtained, a model that can accurately simulate weather changes in the area where the park is located is constructed. The model should be able to reflect the meteorological characteristics under different weather conditions and their impact on the park facilities.

[0145] Weather models can be built based on physical principles or statistical methods, and the choice depends on simulation requirements and data availability.

[0146] Park model and control system construction

[0147] Park model construction:

[0148] Use simulation software or platforms to build a virtual model of the park. The model should include all key facilities of the park, such as buildings, roads, green belts, drainage systems, energy supply systems, etc., and be able to interact with the weather model in real time.

[0149] The park model should have a high degree of realism and detail in order to accurately simulate the operation of the park under different weather conditions.

[0150] Control system construction:

[0151] According to the actual situation and control requirements of the park, a control system is built. The control system should be able to receive the output data of the weather model and perform real-time regulation of the park facilities according to the preset control strategy.

[0152] The control system should include various components such as sensors, actuators and controllers to realize data collection, processing and execution functions.

[0153] Simulation scene settings:

[0154] Set different weather scenes in the simulation environment, such as sunny, rainy, snowy, foggy, etc., and adjust weather parameters to simulate different weather conditions.

[0155] Set parameters such as simulation duration and simulation accuracy according to the simulation objectives.

[0156] Control strategy implementation:

[0157] Implement the preset control strategy in the simulation environment. The control strategy should be adjusted in real time according to the changes in weather conditions and the operating status of the park facilities.

[0158] Control strategies can include energy management, temperature control, lighting adjustment, drainage system optimization and many other aspects.

[0159] Simulation results collection:

[0160] Collect key data during the simulation, such as energy consumption, temperature distribution, humidity changes, drainage efficiency, etc.

[0161] The data should have high accuracy and completeness to facilitate subsequent analysis.

[0162] Result analysis:

[0163] Process and analyze the collected data to evaluate the effectiveness and feasibility of the control strategy.

[0164] Analyze the operation status and energy consumption of the park under different weather conditions to identify existing problems and bottlenecks.

[0165] Strategy Optimization:

[0166] According to the analysis results, the control strategy is optimized and adjusted. The optimization direction can include the improvement of control algorithm, the adjustment of equipment parameters, the optimization of energy distribution, etc.

[0167] The optimized control strategy should be simulated and verified again to ensure its effectiveness and reliability in practical applications.

[0168] In summary, the present invention provides a weather-based park-level control method and system, which accesses weather parameters of different dates and times from a weather or meteorological system, including but not limited to weather conditions and radiation values; collects the park's power generation and power consumption at different time points in real time, and collects and stores as much historical data on the park's power generation and power consumption as possible; according to different weather conditions, the system automatically executes different prediction models to implement intelligent control strategies for the park's load to ensure the safety, stability, and energy saving of the overall operation of the park.

[0169] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0170] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0171] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0172] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0173] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0174] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0175] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0176] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes 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 generate 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.

[0177] 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 1A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0178] 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 in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0179] The above contents are only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. A weather-based park-level control method, characterized in that: The following steps are involved: Collect weather data, build power generation prediction models for different weather types, and obtain the predicted power generation for different weather types; Collect the park's power generation and power consumption at different time points in real time, collect and store the park's power generation and power consumption historical data, and build a park power consumption prediction model; The power consumption prediction model of the park is implemented according to the predicted power generation under different weather conditions to realize intelligent control of the park load.

2. The weather-based park-level control method according to claim 1, characterized in that: The predicted power generation under different weather conditions is as follows: According to the weather conditions, the weather is divided into thunderstorm, freezing and high temperature, and the radiation values ​​Sv1, Sv2 and Sv3 of the corresponding types of weather are collected respectively; According to the weather radiation value collection time interval, the park power generation power Pfa corresponding to the time interval is obtained; According to the weather type, a power generation prediction model for different weather types is built to predict the power generation prediction power P predicted at different times t under different weather types.

3. The weather-based park-level control method according to claim 2, characterized in that: Predicted power generation during thunderstorms P 预Sv1 for Among them, n is the total number of model statistics, i is any one of the total number, Sv1 is the radiation value of thunderstorm weather, P Sv1 is the power generation corresponding to the historical thunderstorm days, is the average power generation on thunderstorm days, is the average radiation value on a thunderstorm day.

4. The weather-based park-level control method according to claim 2, characterized in that: Freezing weather power generation forecast P 预Sv2 for: Among them, n is the total number of model statistics, i is any one of the total number of times, Sv2 is the radiation value of freezing weather, P Sv2 is the power generation corresponding to the historical freezing weather, is the average power generation in freezing weather, is the average radiation value on a thunderstorm day.

5. The weather-based park-level control method according to claim 2, characterized in that: High temperature weather power generation forecast P 预Sv3 for: Among them, n is the total number of model statistics, i is any one of the total number n, Sv3 is the radiation value of high temperature weather, P Sv3 is the power generation corresponding to the historical freezing weather, is the average power generation in freezing weather, is the average radiation value on a thunderstorm day.

6. The weather-based park-level control method according to claim 1, characterized in that: The specific construction of the park power consumption prediction model is as follows: According to the future weather conditions and radiation value forecast, the above prediction model is intelligently matched to predict the power generation at the collection point j in the next day; Calculate the correlation index R by using the predicted power generation and the actual power generation 2 Whether it is close to 1 is used to judge the fitting degree of the weather type-power generation prediction model, providing an adjustment basis for model optimization; Collect the total power consumption P1 of the park at different times t; The power consumption model at different times t in the future is predicted based on the park power consumption P1 at different times.

7. The weather-based park-level control method according to claim 6, characterized in that: Correlation Index R 2 for: Among them, R 2 Calculate the correlation index between the predicted power generation and the actual power generation, n is the total number of model statistics, i is any one of the total number n, Pi is the actual power generation for the i-th time, Pi is the predicted power generation for the i-th time, It indicates the average value of actual power generation when the total number of times is n.

8. The weather-based park-level control method according to claim 6, characterized in that: The power consumption model P at different times t in the future day 1预 for: Among them, n is the total number of model statistics, N is the last number in n, i is any one of the total number, P1 is the historical power consumption of the load that can be powered off, P 1预 is the predicted power consumption of the load that can be shut down in the next day, k is the proportion coefficient, P N is the last historical electricity consumption.

9. The weather-based park-level control method according to claim 1, characterized in that: The intelligent control of the park load is realized as follows: Adjust the power load of the park according to the difference between the predicted power generation and the predicted power consumption of the park: When the difference is greater than or equal to 0, the power load power is not regulated; When the difference is less than 0, while ensuring the power supply to important loads, some loads that can be shut down can be shut down to ensure that the difference is greater than or equal to 0.

10. A weather-based park-level control system, characterized in that: include: The data module collects weather data, builds a power generation prediction model for different weather types, and obtains the predicted power generation for different weather types; The acquisition module collects the park's power generation and power consumption at different time points in real time, collects and stores the park's power generation and power consumption historical data, and builds a park power consumption prediction model; The control module predicts the power generation according to different weather types, executes the park power prediction model, and realizes intelligent control of the park load.

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