Energy efficiency optimization method, system, storage medium and electronic device for irrigation area

Abstract

The application discloses an energy efficiency optimization method and system of an irrigation area, a storage medium and an electronic device, and relates to the field of intelligent irrigation. The method comprises the following steps: acquiring crop information and soil information of each sub-area in an irrigation area, wherein the irrigation area is communicated with branch pipes of each sub-area through a main pipe; for any sub-area, determining an irrigation amount and an irrigation priority required by crops in the sub-area according to the crop information and the soil information; and generating a first irrigation plan of a connected area according to the irrigation amount and the irrigation priority of each sub-area, wherein the connected area is composed of at least two sub-areas, and the first irrigation plan comprises an irrigation mode of irrigating crops in each sub-area in the connected area at different time periods. The technical scheme provided by the application can realize overall energy efficiency optimization of an irrigation system.

Description

Technical Field

[0001] This application relates to the field of smart irrigation, specifically to a method, system, storage medium, and electronic device for optimizing energy efficiency in an irrigation area. Background Technology

[0002] With the increasing severity of global climate change and water scarcity, the efficiency and sustainability of agricultural irrigation have become significant challenges for agricultural development. In large-scale agricultural production, irrigated areas are often divided into multiple sub-regions, each potentially growing different types of crops and possessing varying soil conditions. How to ensure the efficient use of water and energy resources while meeting crop growth needs has become a key issue in modern agricultural management.

[0003] Currently, many irrigation systems use fixed schedules or simple sensor-triggered mechanisms to control irrigation. These systems typically initiate the irrigation process based on preset irrigation cycles or soil moisture thresholds. Some more advanced systems incorporate meteorological data and crop growth stage information to adjust irrigation plans. However, these methods are mostly designed for single regions or single crop types and are difficult to adapt to complex multi-regional, multi-crop planting environments.

[0004] Existing irrigation methods have significant shortcomings when dealing with large-scale, diverse irrigation areas. They often fail to adequately consider the differences between sub-regions and struggle to achieve optimal resource allocation at the overall level. Furthermore, these methods typically neglect factors such as energy consumption and economic costs, resulting in low irrigation efficiency and high operating costs. In practical applications, due to a lack of flexibility and adaptability, these methods struggle to dynamically adjust to real-time changes in environmental conditions and economic factors, thus failing to achieve overall energy efficiency optimization of the irrigation system. Summary of the Invention

[0005] This application provides a method, system, storage medium, and electronic device for optimizing the energy efficiency of an irrigation area, which can achieve overall energy efficiency optimization of the irrigation system.

[0006] In a first aspect, this application provides a method for optimizing energy efficiency in an irrigation area, comprising:

[0007] Obtain crop and soil information for each sub-region within the irrigation area, wherein the irrigation area is connected to branch pipes of each sub-region via a main pipe;

[0008] For any of the sub-regions, the required irrigation amount and irrigation priority for the crops in the sub-region are determined based on the crop information and soil information;

[0009] Based on the irrigation amount and irrigation priority corresponding to each sub-region, a first irrigation plan for the connected region is generated. The connected region consists of at least two sub-regions. The first irrigation plan includes an irrigation mode for irrigating crops in each sub-region of the connected region at different time periods.

[0010] Obtain current electricity price information and environmental information, and calculate adjustment coefficients for each of the connected regions based on the electricity price information and environmental information. The adjustment coefficients are used to characterize the energy efficiency of the first irrigation plan under the electricity price information and environmental information.

[0011] If the adjustment coefficient is greater than the threshold, the first irrigation plan is adjusted based on the electricity price information and the environmental information to obtain the second irrigation plan.

[0012] A second aspect of this application provides an energy efficiency optimization system for an irrigation area, comprising:

[0013] The irrigation information acquisition module is used to acquire crop and soil information of each sub-region in the irrigation area, wherein the irrigation area is connected to the branch pipes of each sub-region through the main pipe;

[0014] An irrigation demand determination module is used to determine, for any given sub-region, the required irrigation amount and irrigation priority for crops in the sub-region based on the crop information and soil information;

[0015] An irrigation plan generation module is used to generate a first irrigation plan for a connected region based on the irrigation amount and irrigation priority corresponding to each of the sub-regions. The connected region consists of at least two sub-regions. The first irrigation plan includes an irrigation mode for irrigating crops in each of the sub-regions of the connected region at different time periods.

[0016] A third aspect of this application provides a computer storage medium storing a plurality of instructions adapted for loading by a processor and executing the method steps described above.

[0017] A fourth aspect of this application provides an electronic device, comprising: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to execute the above-described method steps.

[0018] In summary, one or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0019] By acquiring crop and soil information for each sub-region and determining the required irrigation volume and priority for each sub-region based on this information, refined management of complex and diverse irrigation areas is achieved. This method overcomes the limitations of existing technologies in adapting to multi-regional and multi-crop planting environments, and can fully consider the differences between different sub-regions. By generating a first irrigation plan for connected regions, this method achieves unified scheduling for at least two sub-regions, optimizing resource allocation at the overall level. This irrigation model design based on connected regions not only improves water resource utilization efficiency but also optimizes the overall energy efficiency of the irrigation system while considering energy consumption.

[0020] Compared to existing technologies, this application, by flexibly adjusting irrigation patterns across different time periods, can better adapt to real-time changing environmental conditions. By considering irrigation priorities, this method can prioritize the irrigation needs of high-value or high-demand crops when water resources are limited, thereby achieving a balance between economic benefits and resource utilization. This dynamic adjustment mechanism solves the problems of inflexibility and adaptability in existing methods, enabling timely adjustments based on actual conditions and avoiding resource waste caused by fixed schedules or simple sensor-triggered mechanisms.

[0021] Furthermore, this method effectively reduces the system's operational complexity and energy consumption by integrating the irrigation needs of multiple sub-regions and formulating a unified irrigation plan. This holistic planning approach not only improves irrigation efficiency but also reduces operating costs, solving the problems of inefficiency and high costs caused by decentralized management in existing technologies. Attached Figure Description

[0022] Figure 1 This is a schematic flowchart of an energy efficiency optimization method for an irrigation area provided in an embodiment of this application;

[0023] Figure 2 This is a schematic diagram of the structure of an energy efficiency optimization system for an irrigation area provided in an embodiment of this application;

[0024] Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application.

[0025] Explanation of reference numerals in the attached drawings: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. Detailed Implementation

[0026] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0027] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0028] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0029] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating an energy efficiency optimization method for an irrigation area provided in an embodiment of this application. This method can be implemented using a computer program, a microcontroller, or run on an energy efficiency optimization system for the irrigation area. The computer program can be integrated into an application or run as a standalone utility application. Specifically, the method may include the following steps:

[0030] S101: Obtain crop and soil information for each sub-region within the irrigation area. The irrigation area is connected to the branch pipes of each sub-region via the main pipe.

[0031] The irrigation area refers to the entire planting area requiring intelligent irrigation management. This area is typically a continuous geographical space, such as farmland, a greenhouse, or a horticultural area. In this embodiment, it can be understood as a planting site divided into multiple sub-areas, each potentially growing different crops or at different growth stages. The irrigation area defines the management scope and boundaries of the intelligent irrigation system. By clearly defining the irrigation area, irrigation equipment can be deployed more effectively, irrigation plans can be arranged, and precise water resource allocation can be achieved.

[0032] Furthermore, a sub-region refers to a smaller, partitioned unit within an irrigation area, serving as the basic unit for achieving precise irrigation control. It can be understood as a regional unit within the irrigation area where the same crop is grown, is at the same growth stage, and has similar soil conditions. Each sub-region is typically supplied with water by a branch pipeline and equipped with an independent irrigation regulation device. The division of sub-regions fully considers factors such as crop type, growth stage, soil characteristics, and topography, ensuring relatively uniform irrigation needs within each sub-region. This division method is used to achieve precise irrigation control, ensuring that each region receives the appropriate amount of water according to its specific needs.

[0033] Furthermore, a hierarchical irrigation management structure is formed between the irrigation areas and sub-areas. The irrigation areas are connected to branch pipes in each sub-area via a main pipeline, forming a tree-like irrigation network. The main pipeline, as the backbone of the entire irrigation system, is responsible for distributing water from the irrigation area's inlet to each sub-area. Each sub-area is connected to the main pipeline via a branch pipe, which is equipped with irrigation regulating devices such as pressure regulating valves and flow controllers. These regulating devices can precisely control the amount and pressure of water entering each sub-area according to instructions from the control system.

[0034] Furthermore, there is an inclusion relationship between irrigation regions and subregions; that is, one irrigation region contains multiple subregions. The irrigation region represents the overall irrigation management unit, responsible for macro-level control and resource allocation, while the subregions are the specific irrigation implementation units, responsible for refined irrigation operations. This hierarchical structure allows the system to achieve both overall coordination and meet specific local needs.

[0035] In practical applications, the division of irrigation areas into sub-regions can be based on various factors. Take a large integrated farm as an example, which grows multiple crops, including rice, corn, and various vegetables. First, it can be roughly divided according to crop type, separating rice paddies, cornfields, and vegetable fields into different areas. Then, considering the differences in water requirements of the same crop at different growth stages, it can be further subdivided. For example, rice paddies can be divided into sub-regions based on the sowing time, representing the leafing stage, heading stage, and grain-filling stage.

[0036] For areas with complex terrain, topographical factors also need to be considered. For example, a cornfield may be partly on a hillside and partly on flat land, so it can be divided into two sub-regions: a hillside cornfield and a flat cornfield. For plots where various vegetables are grown, they can be divided according to the water requirements of different vegetables, such as a leafy vegetable area with high water requirements, a fruit vegetable area with medium water requirements, and a root vegetable area with low water requirements.

[0037] Finally, considering the influence of soil type, if there are significant soil differences within the same crop area, further subdivisions can be made. For example, in a flatland cornfield, if there are two soil types, sandy soil and clay soil, it can be further subdivided into sandy soil cornfields and clay soil cornfields.

[0038] This division subdivides the entire irrigation area into multiple sub-regions with similar irrigation needs. Each sub-region has specific irrigation requirements and is equipped with corresponding sensors and irrigation regulation devices. This refined division allows the entire irrigation system to provide precise irrigation based on the actual conditions of each sub-region, meeting the water requirements of different crops and different growth stages while adapting to differences in terrain and soil, thereby achieving optimal water resource utilization. This flexible division also allows the system to dynamically optimize according to seasonal changes and adjustments to planting plans, further improving the adaptability and efficiency of the intelligent irrigation system.

[0039] Crop information refers to a series of key data and parameters describing the growth status of crops and their growing environment. In the embodiments of this application, it can be understood as a comprehensive dataset that includes various factors affecting irrigation decisions.

[0040] Specifically, the system collects crop information through a sensor network deployed in each sub-region. These sensors include, but are not limited to, soil moisture sensors, temperature sensors, humidity sensors, and light intensity sensors. They monitor and record key parameters such as soil moisture, ambient temperature, air humidity, and light intensity within the sub-region in real time. Simultaneously, the system combines pre-input static information, such as crop type, soil type, and planting area, with crop growth information obtained through satellite remote sensing or drone aerial photography, to form a comprehensive crop information dataset. This allows the system to fully understand the real-time conditions and needs of each sub-region, enabling it to develop personalized irrigation plans tailored to the specific needs of different sub-regions.

[0041] Correspondingly, soil information refers to a comprehensive dataset describing the characteristics and state of soil within an irrigation area. In this embodiment, it can be understood as a set of key parameters reflecting the physical, chemical, and biological characteristics of soil in each sub-region, which directly affect the storage, movement, and utilization of water in the soil. Soil information is used to assess the soil's water retention capacity, permeability, and nutrient status, thereby optimizing irrigation strategies and water resource management.

[0042] Soil information typically includes multiple aspects such as soil type, texture, structure, porosity, organic matter content, pH value, electrical conductivity, and nutrient content. These characteristics collectively determine the soil's water retention and drainage capacity, thus affecting crop water absorption and utilization. For example, sandy soils have high permeability but poor water retention, potentially requiring more frequent but smaller irrigation amounts; while soils with high clay content have strong water retention but poor permeability, requiring less frequent but larger irrigation amounts.

[0043] In practical applications, soil information can be obtained through on-site sampling and analysis, sensor monitoring, or historical data accumulation. The system will combine this information with crop information and environmental conditions to develop the most suitable irrigation plan. For example, for sandy soil areas with poor water retention, the system may recommend precision irrigation methods such as drip irrigation and increase the frequency of irrigation.

[0044] S102: For any sub-region, determine the required irrigation amount and irrigation priority for crops in the sub-region based on crop information and soil information.

[0045] Irrigation priority refers to a quantitative indicator that determines the order and importance of irrigation for each sub-region under conditions of limited resources or time constraints. In this embodiment, it can be understood as a numerical value derived by comprehensively considering multiple factors, used to characterize the current urgency and importance of irrigation for each sub-region. Irrigation priority is a dynamically changing parameter that is continuously adjusted as crop growth stages, environmental conditions, and soil conditions change. The system determines the irrigation priority for each sub-region by analyzing and integrating information from multiple aspects, including crop water stress, growth stage, soil moisture content, economic value, expected yield impact, weather forecasts, and crop drought resistance.

[0046] Typically, irrigation priorities are expressed numerically, for example, using a scale of 1-10, where 10 represents the highest priority and 1 represents the lowest priority. The system assigns a specific priority value to each sub-region based on a comprehensive evaluation of the factors mentioned above. This quantification method enables the system to make optimal decisions when faced with complex irrigation demands. For example, when water resources are limited, the system prioritizes meeting the irrigation needs of high-priority areas; when multiple areas require irrigation simultaneously but the system's capacity is limited, higher-priority areas are scheduled for irrigation during more favorable time periods.

[0047] Based on the above embodiments, as an optional embodiment, the crop information includes crop type and crop growth stage, and the soil information includes soil moisture. In S102, the step of determining the required irrigation amount and irrigation priority of crops in the sub-region based on the crop information and soil information may further include the following steps:

[0048] S201: Determine the amount of irrigation required for crops in the sub-regions corresponding to the connected region based on the crop type and crop growth stage.

[0049] Specifically, a series of smart sensors and cameras can be deployed in each sub-region. The deployment of these devices follows a grid-like layout principle to ensure comprehensive coverage of the entire sub-region. The smart sensors mainly include soil moisture sensors, temperature sensors, and light sensors, which are typically buried in the soil or installed on supports near the crops. They can continuously monitor key parameters of the crop growth environment, providing important information for determining the crop's growth stage.

[0050] Correspondingly, high-definition cameras are installed at high points in each sub-region, such as utility poles or specially constructed monitoring towers. These cameras are equipped with wide-angle lenses and zoom capabilities, enabling them to capture panoramic images of the entire sub-region while also allowing for detailed observation of specific areas. In addition to capturing visible light images, the cameras are also equipped with near-infrared sensors to obtain normalized difference vegetation index (NDVI) data for crops, which is crucial for determining the crop's growth status and growth stage.

[0051] The aforementioned devices can be connected to the central control system via a wireless sensor network. Data transmission employs low-power wide-area network (LPWAN) technologies, such as LoRa or NB-IoT, to ensure stable and efficient data transmission in vast farmland environments.

[0052] After receiving the aforementioned data, the central control system first analyzes the images captured by the camera equipment using image recognition algorithms to identify the types of crops planted in each sub-region. This process utilizes a deep learning model, which has been trained on a large number of crop images and is capable of accurately identifying common crop varieties.

[0053] To determine the crop's growth stage, the system comprehensively utilizes multiple data sources. First, it analyzes the crop's external characteristics, such as plant height, leaf quantity, and morphology, using image data. Second, by combining environmental data such as soil moisture, temperature, and light intensity, the system can calculate accumulated temperature and the number of effective growing days. Third, NDVI data reflects the intensity of crop photosynthesis, thus inferring its growth stage. Finally, the system also references historical data such as planting dates, which can be obtained from the farm management system.

[0054] By integrating the aforementioned multi-dimensional information and combining it with a pre-established crop growth model, the system can accurately determine the current growth stage of each crop. For example, for corn, the system can precisely distinguish key growth stages such as seedling stage, jointing stage, tasseling stage, and grain-filling stage.

[0055] The crop growth model was trained using big data and machine learning techniques. The training process primarily utilized historical agricultural data, including crop planting records, growth observation data, and corresponding meteorological data from different regions and years. The training dataset covers the growth performance of various common crops under different climatic conditions.

[0056] The model training employed a supervised learning method, using planting date, accumulated temperature, and sunshine duration as input features, and the actual dates on which the crop reached each key growth stage as the target output. During training, ensemble learning algorithms such as random forests and gradient boosting trees could be used to effectively capture the complex nonlinear relationship between crop growth and environmental factors.

[0057] The model can be evaluated using cross-validation, which measures its accuracy by comparing the differences between the model's predicted growth stages and actual observed data. After multiple rounds of iterative optimization, a model capable of accurately predicting key crop growth stages was finally obtained.

[0058] It should be noted that crop growth model training and application are already mature technologies in the field of agricultural informatization. The method used in this embodiment is based on existing technology, and its main innovation lies in combining this model with simplified environmental monitoring and manual correction to achieve precise control in intelligent irrigation systems. Therefore, this embodiment will not elaborate on the specific algorithms and parameter selection for model training.

[0059] Furthermore, in another feasible embodiment, since acquiring information on crop types and growth stages within each sub-region of the irrigation area primarily focuses on identifying critical growth stages—those requiring adjustments to irrigation methods—the system can also extrapolate and confirm crop types based on initial data entered at planting time. At sowing or transplanting, farm managers input the crop types and planting dates for each sub-region into the intelligent irrigation system's database. This method is simple and direct, accurately reflects actual planting conditions, and avoids complex image recognition processes.

[0060] S202: Determine the irrigation priority for crops in a sub-region based on soil moisture and the amount of irrigation required by the crops.

[0061] Specifically, after determining the irrigation requirements of crops in a sub-region, the system further determines the irrigation priority of crops in that sub-region based on soil moisture and the required irrigation amount. This allows for more precise allocation of irrigation resources, ensuring efficient use of water resources while meeting the actual water needs of crops. Soil moisture, as a direct indicator of current soil moisture status, combined with the required irrigation amount for crops, can comprehensively reflect the urgency of actual irrigation needs in the sub-region.

[0062] In practice, the system first monitors soil moisture content in real time through a network of soil moisture sensors deployed in each sub-region. To quantify irrigation priority, the system establishes a comprehensive scoring model. This model uses the difference between soil moisture and crop water requirements as the main input parameter, while also considering factors such as crop growth stage sensitivity and economic value. For example, high-value crops in critical growth stages (such as flowering or fruiting) may be assigned a higher irrigation priority even if soil moisture is slightly below ideal. The model uses a weighted algorithm to integrate various factors into a priority score of 0-10, where 10 represents the highest priority, requiring immediate irrigation.

[0063] The prioritization method based on real-time soil moisture and crop water requirements allows irrigation systems to respond more flexibly to environmental changes and crop needs. For example, in the event of a sudden drought, even if some sub-areas were originally scheduled for later irrigation, the system can quickly adjust their priorities to ensure that the areas most in need of water receive timely irrigation. At the same time, this method also helps prevent over-irrigation, avoiding water waste and potential root hypoxia problems.

[0064] S103: Generate a first irrigation plan for the connected region based on the irrigation amount and irrigation priority corresponding to each sub-region. The connected region consists of at least two sub-regions. The first irrigation plan includes irrigation patterns for irrigating crops in each sub-region of the connected region at different time periods.

[0065] In this context, a connected region refers to a collection of multiple sub-regions interconnected by a common water source and pipeline network within an irrigation system. In this embodiment, it can be understood as an irrigation unit comprised of at least two sub-regions with similar irrigation needs or priorities, connected by a main pipeline. The concept of connected regions is used to optimize the overall operational efficiency of the irrigation system, achieving rational allocation of water resources and efficient utilization of energy.

[0066] Specifically, the formation of a connected region is based on several key factors: First, the sub-regions within the connected region are physically linked by the same main pipeline or adjacent branch pipelines, ensuring that water can be delivered to these regions simultaneously or continuously. Second, these sub-regions share certain similarities in irrigation needs, such as similar required irrigation volumes, similar irrigation priorities, or overlapping irrigation time windows. Finally, the total irrigation volume of the connected region should match the water supply capacity of the irrigation system, neither exceeding the maximum flow rate of the pumps nor being too small, which would lead to system inefficiency.

[0067] The concept of connected regions offers several advantages to irrigation systems. First, it allows for unified scheduling of multiple sub-regions, improving the continuity and efficiency of irrigation operations. For example, when a high-priority sub-region needs irrigation, the system can simultaneously schedule irrigation for other connected sub-regions, making full use of pump runtime, reducing start-stop frequency, and thus lowering energy consumption. Second, the concept of connected regions allows for more flexible balancing of the needs of different sub-regions. In situations with limited water resources, irrigation volumes can be fine-tuned within connected regions, ensuring that the overall water consumption remains constant while prioritizing the needs of critical areas.

[0068] Furthermore, the design of interconnected zones helps optimize the hydraulic performance of the irrigation system. By rationally organizing interconnected zones, water pressure and flow velocity in the pipe network can be maintained within ideal ranges, reducing energy loss and improving irrigation uniformity. At the same time, this organization method facilitates system fault diagnosis and maintenance; when an anomaly occurs in a particular interconnected zone, the problem can be quickly located and addressed without affecting the operation of the entire irrigation area.

[0069] The first irrigation plan refers to the preliminary irrigation scheme generated by the intelligent irrigation system based on initial data analysis and optimization algorithms. In this embodiment, it can be understood as a comprehensive irrigation execution guideline, detailing key parameters such as irrigation time, irrigation volume, and irrigation mode for each sub-region within the connected area. It guides the initial operation of the irrigation system and serves as the basis for subsequent dynamic optimization. Specifically, the first irrigation plan includes core elements such as time scheduling, irrigation volume allocation, irrigation mode selection, priority ranking, energy usage planning, and coordination of connected areas. These elements together constitute a comprehensive irrigation strategy aimed at both meeting crop growth needs and achieving efficient use of water and energy resources.

[0070] Based on the above embodiments, as an optional embodiment, in S103, the step of generating the first irrigation plan for the connected region according to the irrigation amount and irrigation priority corresponding to each sub-region may further include the following steps:

[0071] S301: Based on the priority and irrigation amount of each sub-region, determine at least two sub-regions to form a connected region, and the irrigation time of each sub-region within at least one time period.

[0072] Specifically, when generating the first irrigation plan for the connected region, at least two sub-regions are determined to form a connected region based on the priority and irrigation volume of each sub-region, and the irrigation time for each sub-region is scheduled within at least one time period. This process aims to fully utilize the physical structure and water resource allocation capacity of the irrigation system while considering the actual water requirements of the crops, thereby achieving more precise and efficient irrigation management.

[0073] In practice, the system first sorts all sub-regions according to irrigation priority, with higher-priority sub-regions being considered for inclusion in the connected region. Simultaneously, the system analyzes the irrigation needs of adjacent sub-regions, seeking combinations of sub-regions with similar irrigation requirements. This ensures that sub-regions within the connected region have a certain degree of similarity in irrigation needs, facilitating unified scheduling and resource allocation. During the selection process, the system also considers the maximum flow rate limit of the water pumps to ensure that the total irrigation demand of the connected region does not exceed the system's water supply capacity.

[0074] Once the connected regions are identified, the system allocates specific irrigation times for each sub-region. This process considers multiple factors, including the sub-region's priority, required irrigation volume, soil water absorption rate, and crop drought tolerance. The system attempts to schedule irrigation for high-priority sub-regions during optimal times, while simultaneously balancing water demand across the entire connected region through staggered scheduling. For example, sub-regions with high water demand but lower priority may be irrigated at night or during off-peak electricity hours, satisfying crop water needs while optimizing energy use.

[0075] Based on the above embodiments, as an optional embodiment, in S301: determining at least two sub-regions to form a connected region according to the priority and irrigation amount of each sub-region, and the irrigation time of each sub-region within at least one time period, the step may further include the following steps:

[0076] S401: Based on the priority ranking of each sub-region and the maximum flow rate of the water pump in the irrigation area, determine at least two sub-regions to form a connected region. The difference in irrigation volume between the sub-regions in the connected region is less than a threshold, and the total irrigation volume is less than or equal to the maximum flow rate of the water pump.

[0077] Specifically, in determining the connected regions and allocating irrigation time, at least two sub-regions are selected to form a connected region based on the priority ranking of each sub-region and the maximum flow rate of the water pump within the irrigation region. It is ensured that the difference in irrigation volume between sub-regions within the connected region is less than a threshold, and the total irrigation volume does not exceed the maximum flow rate of the water pump. The main objective is to fully utilize the hardware capabilities of the irrigation system while ensuring the uniformity of irrigation and the stable operation of the system.

[0078] In practice, the system first sorts all sub-regions according to the previously calculated irrigation priority. Starting with the highest priority sub-region, the system searches for adjacent sub-regions with similar irrigation volumes. An irrigation volume difference threshold is also introduced; the difference in irrigation volume between sub-regions within a connected area should be less than a preset threshold. This threshold is set based on the system's physical characteristics and operational experience, and is typically set as a certain percentage of the pump's maximum flow rate, such as 10% or 15%. The purpose of this is to ensure that each sub-region within a connected area receives a relatively balanced amount of water simultaneously, avoiding uneven irrigation caused by excessive water pressure differences.

[0079] Simultaneously, the system calculates the total irrigation volume of the selected sub-regions in real time, ensuring it does not exceed the pump's maximum flow rate. This guarantees the system operates within its physical capabilities, avoiding pump overload or insufficient water supply. If the total irrigation volume exceeds the pump's maximum flow rate after adding a new sub-region, the system will stop adding new sub-regions and designate the currently selected sub-region as a connected region.

[0080] S402: Generate the time window corresponding to the connected components.

[0081] In this context, a time window refers to a continuous period of time allocated to a specific connected region within an irrigation system for performing irrigation tasks. In this embodiment, it can be understood as an optimized time interval within which all sub-regions of the connected region can receive appropriate irrigation. The time window is used to coordinate and optimize the operation of the irrigation system, ensuring the efficient use of water and energy resources while meeting the growth needs of crops.

[0082] Specifically, the length of the time window is typically determined based on the optimal operating cycle of the water pump and the total irrigation demand of the sub-regions within the connected area. For example, if the optimal operating cycle of the water pump is 4 hours, and the total irrigation demand of the sub-regions within the connected area is approximately 4000 liters, then the system might generate a 4-hour time window. Within this time window, the system will further subdivide the specific irrigation time for each sub-region to ensure the even distribution of water resources.

[0083] S403: Allocate irrigation time for each sub-region based on the irrigation amount of each sub-region in the connected region.

[0084] Specifically, after generating the time window corresponding to the connected region, the system needs to rationally allocate the specific irrigation time for each sub-region based on the irrigation volume of each sub-region within the connected region. This is because it directly affects the efficiency of water resource utilization, crop growth, and the overall operational efficiency of the irrigation system. Rationally allocating irrigation time not only ensures that each sub-region receives the required amount of water but also optimizes pump operation, reduces energy consumption, and improves the uniformity of irrigation.

[0085] In practice, the system first calculates the total irrigation demand within the time window. For the selected combination of sub-regions, the system calculates their total irrigation demand D. total D total =∑(r∈W)D r Where W represents the current time window, and D i This represents the irrigation demand of the r-th sub-region within the time window. The system then allocates irrigation time proportionally based on the proportion of each sub-region's irrigation volume to the total demand. For each sub-region r in window W, its irrigation time T... i It can be done through formula T i =(D r / / D total )×T window Calculations show that T i T represents the i-th irrigation time in the first irrigation plan. window This indicates the length of the time window, i.e., the actual operating time, which is usually close to the previously determined optimal operating cycle T of the water pump. opt D r D represents the irrigation demand of the r-th sub-region within the time window. total This represents the total irrigation demand of the connected region.

[0086] The above-described proportional allocation method ensures the matching of irrigation time with irrigation demand, while also guaranteeing the continuous and stable operation of the water pump throughout the entire time window. For example, if there are three sub-regions within a time window, with irrigation demands of 1000 liters, 1500 liters, and 500 liters respectively, totaling 3000 liters, and the time window length is 3 hours, then the irrigation time for these three sub-regions will be allocated to 1 hour, 1.5 hours, and 0.5 hours respectively.

[0087] When allocating irrigation time, the system also considers additional factors to further optimize irrigation effectiveness. For example, for sub-areas with poor soil permeability, the system may divide their irrigation time into multiple short periods to prevent waterlogging. For certain special crops, the system may schedule irrigation during the most favorable time for water absorption, such as early morning or evening, based on their growth characteristics. Furthermore, the system considers the hydraulic characteristics of the pipeline network and rationally arranges the irrigation sequence to ensure that each sub-area receives stable water pressure and flow.

[0088] S302: Determine the irrigation mode for each sub-region based on the irrigation time and amount of each sub-region in the connected region. The irrigation mode includes sprinkler irrigation or drip irrigation.

[0089] Specifically, after determining the irrigation time and amount for each sub-region within the connected region, the system needs to further determine the specific irrigation mode for each sub-region. The selection of the irrigation mode is crucial for improving water resource utilization efficiency, meeting the needs of different crops and soil conditions, and achieving precision irrigation. In this embodiment, the irrigation modes mainly include sprinkler irrigation and drip irrigation. Each of these modes has its own advantages and applicable conditions, and the system needs to make an intelligent selection based on multiple factors.

[0090] In practice, the system first considers several key factors, including crop type, growth stage, soil characteristics, topography, irrigation time, and irrigation volume. For each sub-region, the system analyzes its specific conditions and needs. For example, for leafy vegetables or seedlings in their early growth stages, where uniform coverage of a large area is required, the system may prefer sprinkler irrigation. For inter-row crops such as fruit trees and grapes, or in situations where water resources are scarce and efficient water use is necessary, the system may choose drip irrigation.

[0091] In addition, the system also considers the impact of irrigation time and volume on irrigation mode selection. For example, if a sub-area has a short irrigation time but a large water demand, the system may choose sprinkler irrigation to quickly provide a large amount of water. For sub-areas requiring long-term, small-volume irrigation, drip irrigation may be more suitable because it can provide continuous, slow water supply and reduce water loss.

[0092] It is worth noting that the system does not simply select a fixed irrigation pattern for each sub-region, but rather dynamically adjusts the irrigation pattern according to crop growth stages and seasonal changes. For example, during critical growth periods of crops, the system may temporarily change the irrigation pattern to provide more precise water supply. This dynamic adjustment capability greatly improves the flexibility and adaptability of the irrigation system.

[0093] S303: Use the irrigation time and irrigation pattern of each sub-region in the connected region as the first irrigation plan.

[0094] In practice, the system will structure and organize the irrigation time and irrigation mode information of each sub-region within each connected area. The system will create a detailed irrigation instruction set for each sub-region, including irrigation start time, duration, irrigation mode used, and water volume control parameters. Simultaneously, the system will consider the irrigation sequence between sub-regions within the connected area to ensure the smoothness of the entire irrigation process and optimal utilization of system resources.

[0095] When generating the first irrigation plan, the system also considers some practical operational factors. For example, to reduce the frequent switching and adjustment of irrigation equipment, the system may try to arrange sub-areas using the same irrigation mode within consecutive time periods. In addition, the system will also reserve some buffer time in the plan to cope with possible equipment switching delays or other unforeseen circumstances, ensuring the continuity and reliability of the entire irrigation process.

[0096] In addition to specific irrigation instructions, the first irrigation plan also includes supplementary information. For example, the system prioritizes each irrigation operation, allowing it to quickly determine which irrigation tasks can be postponed and which must be executed on time in the event of resource constraints or unforeseen circumstances. The plan also includes projected water and energy consumption, which can be used for subsequent resource allocation and cost accounting.

[0097] Based on the above embodiments, as an optional embodiment, after generating the first irrigation plan, in order to further optimize the energy efficiency of the irrigation system and adapt to real-time changing environmental conditions, this embodiment introduces a dynamic adjustment mechanism based on electricity price information and environmental information. The core of this mechanism lies in using real-time data to drive fine-tuning of the initial irrigation plan, thereby achieving higher energy efficiency and better irrigation results.

[0098] This process may also include the following steps:

[0099] S104: Obtain current electricity price and environmental information.

[0100] Specifically, after generating the initial irrigation plan, the system further acquires current electricity price and environmental information to dynamically optimize the irrigation plan, thereby improving energy efficiency and irrigation effectiveness. Electricity price information directly impacts irrigation operation costs, while environmental information such as rainfall, temperature, and humidity affect the actual water needs of crops. By acquiring this information in real time, the system can more accurately adjust the irrigation plan, avoid unnecessary irrigation operations, and utilize off-peak electricity pricing periods for irrigation, thus reducing operating costs.

[0101] In practice, the system acquires this real-time information through multiple channels. For electricity price information, the system can establish a real-time data interface with the local power company's information system to obtain time-of-use electricity price data. This data typically includes the time period division and specific prices for peak and off-peak electricity pricing. Obtaining environmental information is more complex, as the system comprehensively utilizes multiple data sources. First, weather stations located within the irrigation area can provide real-time data on temperature, humidity, and wind speed. Second, the system connects to the regional meteorological department's forecasting system to obtain short-term weather forecasts, particularly rainfall predictions. Furthermore, the system can utilize satellite remote sensing data to obtain broader climate change trends.

[0102] The aforementioned real-time data is transmitted to the central control system via IoT technology. After data cleaning and preliminary processing, standardized datasets of electricity price and environmental information are generated. Electricity price information is typically expressed as a price per kilowatt-hour and the corresponding time period, while environmental information includes key parameters such as current temperature, humidity, wind speed, solar radiation intensity, and the probability and expected rainfall in the next 24 hours.

[0103] S105: Calculate the adjustment coefficient for each connected area based on electricity price information and environmental information. The adjustment coefficient is used to characterize the energy efficiency of the first irrigation plan under the electricity price information and environmental information.

[0104] The adjustment coefficient refers to a numerical indicator used to quantitatively assess the applicability of an irrigation plan under current electricity prices and environmental conditions. In this embodiment, it can be understood as a dynamic assessment parameter that comprehensively considers multiple dimensions of information, including electricity price fluctuations, rainfall forecasts, irrigation priorities, and time factors. It reflects the energy efficiency level of the first irrigation plan under real-time conditions and provides a quantitative basis for the dynamic adjustment of the irrigation plan.

[0105] In practical applications, the adjustment coefficient is not merely a static evaluation tool, but a driving force for the continuous optimization of the entire irrigation system. By continuously calculating and updating the adjustment coefficient, the system can promptly detect changes in the external environment, such as sudden weather changes or electricity price fluctuations, and quickly assess the impact of these changes on existing irrigation plans. This dynamic evaluation mechanism enables the irrigation system to maximize energy efficiency and reduce operating costs while ensuring normal crop growth.

[0106] Based on the above embodiments, as an optional embodiment, in S502, the step of calculating the adjustment coefficient of each connected area based on electricity price information and environmental information may further include the following steps:

[0107] Substitute the first irrigation plan corresponding to each connected area, along with the electricity price and rainfall corresponding to the first irrigation plan, into the adjustment coefficient calculation formula to obtain the adjustment coefficient for each connected area.

[0108] The formula for calculating the adjustment coefficient is as follows:

[0109] ;

[0110] In the formula, A represents the adjustment coefficient. This represents the electricity price of the k-th connected region in the j-th time period. Let P represent the standard electricity price, and let P represent the electricity price difference threshold, used to characterize the significance of the electricity price difference. This represents the precipitation in the k-th connected region during the j-th time period. This indicates the irrigation priority of the k-th connected region in the j-th time period. Indicates an indicator function, When it is 1, When it is 0, This represents the time difference between the j-th time period and the irrigation execution time. , as well as These represent the corresponding weighting coefficients, and λ represents the attenuation factor.

[0111] Specifically, the overall design of the adjustment coefficient calculation formula aims to create a comprehensive evaluation model for quantifying the applicability of current irrigation plans under real-time conditions. This formula integrates multiple key variables such as electricity price fluctuations, rainfall forecasts, irrigation priorities, and time factors, transforming these complex influencing factors into a single, comparable numerical indicator through mathematical methods. This enables the system to objectively and comprehensively evaluate the energy efficiency and resource utilization efficiency of irrigation plans. The formula mainly consists of the following parts:

[0112] Electricity price impact factors: ;

[0113] Specifically, the electricity price impact term is used to assess and quantify the impact of electricity price fluctuations on irrigation plans. It introduces a threshold mechanism, triggering adjustments only when the electricity price difference exceeds a preset threshold. This mechanism prevents the system from overreacting to small or short-term electricity price fluctuations, enhancing system stability and reliability. Secondly, by using a maximum value function, it ensures that the adjustment coefficient only increases when electricity prices rise significantly, while having no negative impact when prices fall or fluctuate slightly. This asymmetric design better aligns with practical cost optimization needs.

[0114] Furthermore, this design takes into account the differences in electricity price fluctuations across different regions and periods. By introducing weighting coefficients, system administrators can flexibly adjust the importance of electricity price factors based on local energy policies, seasonal electricity price changes, or price adjustments during special periods. This flexibility allows the system to adapt to the specific needs of different regions and periods, improving its applicability and practicality.

[0115] This system effectively addresses various electricity price fluctuation scenarios. In one exemplary scenario, during the summer peak electricity consumption period, a farm's irrigation system detected that the electricity price between 2 PM and 6 PM was 30% higher than usual, exceeding a preset 20% threshold. The system immediately increases the adjustment factor for this time period, indicating that irrigation tasks originally scheduled for this time may need to be rescheduled to the evening or early morning when electricity prices are lower. This not only significantly reduces energy costs but also balances the grid load, demonstrating the social benefits of intelligent irrigation systems.

[0116] In another exemplary scenario, some regions implement tiered electricity pricing policies, where electricity prices rise sharply after a certain consumption threshold is reached. Smart irrigation systems can monitor cumulative electricity consumption and, when approaching a higher price tier, increase the adjustment factor, suggesting that the remaining irrigation tasks be postponed to the next billing cycle, thereby effectively controlling overall electricity costs.

[0117] Rainfall impacts: ;

[0118] Specifically, the rainfall impact term is mainly used to assess and quantify the impact of predicted rainfall on irrigation plans. It directly considers the contribution of natural precipitation to crop water supply, enabling the irrigation system to more accurately replenish the water needed by crops and avoid resource waste caused by over-irrigation. Secondly, by introducing an indicator function, the system only considers the rainfall impact during the originally planned irrigation periods. This refined design ensures that the system does not react unnecessarily to rainfall during non-irrigation periods, improving the accuracy and flexibility of decision-making.

[0119] Furthermore, this design takes into account the differences in rainfall patterns and water resource conditions across different regions. By introducing weighting coefficients, system administrators can adjust the importance of rainfall factors based on local climate characteristics, water scarcity, or crop sensitivity to water. This adjustability allows the system to adapt to various climatic conditions, from arid to humid, enhancing its applicability and practical value.

[0120] In an exemplary scenario, in a water-scarce region, a smart irrigation system receives a weather forecast predicting moderate rainfall the following afternoon. The system immediately adjusts the rainfall for this period, suggesting that planned irrigation schedules be postponed or canceled to make the most of natural precipitation. This not only conserves precious water resources but also reduces the operating costs and energy consumption of the irrigation system.

[0121] In another exemplary scenario, in a region with variable climate, the system predicts intermittent light rain over the next few days. In this case, the system might suggest adjusting the irrigation plan to employ a more frequent but lower-volume irrigation strategy to supplement potentially insufficient rainfall while avoiding the negative effects of overwatering.

[0122] However, for some special crops, such as rice, their irrigation requirements differ from those of conventional crops. In such cases, even if rainfall is predicted, the system may maintain a certain irrigation level to keep the water level in the paddy field, demonstrating the system's intelligent adaptation to the characteristics of different crops.

[0123] Priority-affected items: ;

[0124] Specifically, the priority impact factor introduces the concept of irrigation priority, ensuring that the irrigation needs of important crops or key growth stages are prioritized. Secondly, through the time decay function, the system is more cautious about upcoming tasks, reducing disturbances to short-term plans and enhancing system stability and predictability. Thirdly, the design of the negative sign cleverly expresses the logic that high-priority tasks have a lower tendency to be adjusted, making the system more inclined to maintain the original plan when facing important tasks.

[0125] Furthermore, this design takes into account the differentiated needs of different crop types and growth stages. By adjusting weighting coefficients and attenuation factors, system administrators can balance the importance of priorities and time factors according to specific agricultural production needs. This flexibility allows the system to adapt to various complex agricultural production scenarios, improving its applicability and practical value.

[0126] For example, in a large integrated farm, there are multiple crops, including rice, corn, and vegetables. The system detects that drought is likely in the coming days, and electricity prices will also rise. The system will assign a higher irrigation priority to rice paddies in the heading stage. Even with the electricity price increase, the system will tend to maintain the rice irrigation schedule, perhaps with only slight adjustments to the irrigation timing, to ensure that water supply during this critical growth stage is not affected.

[0127] Furthermore, a decay factor λ is set in the priority impact term to finely control the decay rate of the time factor's influence on irrigation priority. The introduction of this factor reflects the intelligent irrigation system's in-depth consideration of time sensitivity, enabling the system to respond more flexibly to changes in irrigation demand at different time scales.

[0128] S106: If the adjustment coefficient is greater than the threshold, the first irrigation plan is adjusted based on electricity price information and environmental information to obtain the second irrigation plan.

[0129] Specifically, after calculating the adjustment coefficients of each connected region and comparing them with preset thresholds, if the adjustment coefficients are greater than the thresholds, the system will adjust the first irrigation plan based on electricity price information and environmental information to obtain the second irrigation plan.

[0130] In practice, the system analyzes the main factors causing the adjustment coefficient to increase, such as electricity price fluctuations or rainfall forecasts, and then adjusts the irrigation time periods for each sub-region accordingly. For example, if the electricity price increases significantly during a certain time period, the system may shift the irrigation task originally scheduled for that time period to a time period with lower electricity prices, while maintaining the irrigation pattern unchanged. If significant rainfall is predicted for a certain time period, the system may reduce the irrigation amount during that time period or cancel the irrigation task entirely, and adjust the irrigation amount for other time periods accordingly to ensure that the overall water requirements of the crops are met.

[0131] While adjusting irrigation time periods, the system also considers whether a change in irrigation mode is necessary. For example, if the adjusted irrigation time is shorter but the water demand remains the same, the system may switch from drip irrigation to sprinkler irrigation to provide sufficient water in a shorter time. Conversely, if the irrigation time is longer, it may switch from sprinkler irrigation to drip irrigation to distribute water resources more evenly and reduce evaporation losses. These adjustments are all fine-tuning within the framework of the initial irrigation plan, ensuring continuity and operability of the adjustments.

[0132] Throughout the adjustment process, the system ensures that the adjusted second irrigation plan maintains the coordination of irrigation among the sub-regions within the connected area. For example, when it is necessary to advance the irrigation time of a certain sub-region, the system will simultaneously consider the irrigation arrangements of other sub-regions within the connected area and may adjust the irrigation sequence of the entire connected area to maintain the continuity of pump operation and the stability of the network hydraulic performance.

[0133] Furthermore, when generating a second irrigation plan, the system fully considers key factors such as crop growth stage and soil moisture to ensure that the adjusted plan still meets the crop's basic water requirements. For example, for crops in critical growth stages, even during the adjustment process, the system will prioritize their irrigation needs, possibly only fine-tuning the irrigation time without significantly reducing the irrigation volume.

[0134] Based on the above embodiments, as an optional embodiment, in order to more finely control the changes in adjustment coefficients during the continuous optimization process of the intelligent irrigation system, this application introduces the concept of a smoothing factor. The smoothing factor is designed to address the problem of excessive fluctuations in adjustment coefficients that may be caused by rapid changes in irrigation priorities, thereby improving the stability and reliability of the system. This improvement reflects the system's in-depth consideration of changes in irrigation demand over time, making the adjustment of irrigation plans smoother and more continuous.

[0135] The smoothing factor is:

[0136] ;

[0137] In the formula, η represents the adjustment constant, which is used to characterize the influence of priority changes on the adjustment coefficient, I(c,t) represents the irrigation priority of the connected area at time t, and Δt represents the time difference.

[0138] Specifically, the smoothing factor has a base value of 1, meaning that under ideal conditions, it will not affect the original adjustment coefficient. However, when irrigation priority changes, the smoothing factor will decrease accordingly, thus playing a regulatory role. The priority difference in the formula reflects the magnitude of change in irrigation demand over a period of time. Dividing this difference by the time interval yields the rate of change in priority, reflecting the system's consideration of the time factor. By introducing an adjustment constant, system administrators can flexibly control the sensitivity of the smoothing factor to priority changes, enabling the system to adapt to different agricultural production scenarios.

[0139] In practical applications, the role of the smoothing factor can be understood through a specific scenario. Suppose corn is planted in a connected area of ​​a large farm. When the corn enters the critical tasseling stage, its irrigation priority rises rapidly. In a traditional system, this could lead to drastic adjustments to the irrigation plan, potentially causing a sudden and significant increase in irrigation volume in that area. This could not only waste water resources but also disrupt irrigation plans in other areas. However, by introducing a smoothing factor, the system will detect this rapid increase in priority, and the smoothing factor will decrease accordingly, thus slowing down the rate of increase in the adjustment coefficient.

[0140] For example, in a multi-crop integrated farm, different crops may be at different growth stages simultaneously, and their irrigation needs may change rapidly. A smoothing factor helps the system meet high-priority needs without excessively disrupting irrigation plans in other areas. For instance, when rice enters the furrow irrigation stage, it requires a large amount of water. The system, through the smoothing factor, will gradually adjust the irrigation plan, potentially increasing irrigation volume in the rice paddies over several days while simultaneously adjusting irrigation times in other areas, such as vegetable greenhouses, to ensure balanced use of overall water resources.

[0141] Furthermore, the design of smoothing factors can effectively cope with sudden weather changes. Suppose a weather forecast suddenly indicates heavy rainfall in the coming days; a traditional system might immediately and drastically reduce or cancel planned irrigation. However, by adjusting the smoothing factor, the system can respond more cautiously to this situation. It might gradually reduce irrigation, but not completely cancel it, in case of inaccurate rainfall forecasts or insufficient rainfall. This strategy avoids over-irrigation while ensuring crops do not suffer from water shortages in the event of a sudden drought.

[0142] Reference Figure 2 This application also provides an energy efficiency optimization system for an irrigation area, comprising:

[0143] The irrigation information acquisition module is used to acquire crop and soil information of each sub-region in the irrigation area, wherein the irrigation area is connected to the branch pipes of each sub-region through the main pipe;

[0144] An irrigation demand determination module is used to determine, for any given sub-region, the required irrigation amount and irrigation priority for crops in the sub-region based on the crop information and soil information;

[0145] An irrigation plan generation module is used to generate a first irrigation plan for a connected region based on the irrigation amount and irrigation priority corresponding to each of the sub-regions. The connected region consists of at least two sub-regions. The first irrigation plan includes an irrigation mode for irrigating crops in each of the sub-regions of the connected region at different time periods.

[0146] An irrigation plan adjustment module is used to acquire current electricity price information and environmental information; calculate adjustment coefficients for each connected region based on the electricity price information and environmental information, wherein the adjustment coefficients characterize the energy efficiency of the first irrigation plan under the electricity price information and environmental information; if the adjustment coefficients are greater than a threshold, the first irrigation plan is adjusted based on the electricity price information and environmental information to obtain a second irrigation plan.

[0147] Based on the above embodiments, as an optional embodiment, the irrigation demand determination module is further configured to determine the amount of irrigation required for crops in the sub-regions corresponding to the connected region according to the crop type and crop growth stage; and to determine the irrigation priority of crops in the sub-regions according to the soil moisture and the amount of irrigation required for the crops.

[0148] Based on the above embodiments, as an optional embodiment, the irrigation plan generation module is further configured to determine, according to the priority and irrigation amount of each sub-region, at least two sub-regions form a connected region, and the irrigation time of each sub-region within at least one time period; determine the irrigation mode of each sub-region according to the irrigation time and irrigation amount of each sub-region in the connected region, the irrigation mode including sprinkler irrigation or drip irrigation; and use the irrigation time and irrigation mode of each sub-region in the connected region as a first irrigation plan.

[0149] Based on the above embodiments, as an optional embodiment, the irrigation plan generation module is further configured to determine at least two of the sub-regions to form a connected region according to the priority order of each sub-region and the maximum flow rate of the water pump in the irrigation region, wherein the difference in irrigation amount of the sub-regions in the connected region is less than a threshold, and the total irrigation amount is less than or equal to the maximum flow rate of the water pump; generate a time window corresponding to the connected region; and allocate irrigation time for each sub-region according to the irrigation amount of each sub-region in the connected region.

[0150] Based on the above embodiments, as an optional embodiment, the irrigation plan adjustment module is further used to substitute the first irrigation plan corresponding to each of the connected areas, as well as the electricity price and rainfall corresponding to the first irrigation plan, into the adjustment coefficient calculation formula to obtain the adjustment coefficient of each of the connected areas;

[0151] The formula for calculating the adjustment coefficient is as follows:

[0152] ;

[0153] In the formula, A represents the adjustment coefficient. This represents the electricity price of the k-th connected region in the j-th time period. Let P represent the standard electricity price, and let P represent the electricity price difference threshold, used to characterize the significance of the electricity price difference. This represents the precipitation in the k-th connected region during the j-th time period. This indicates the irrigation priority of the k-th connected region in the j-th time period. Indicates an indicator function, When it is 1, When it is 0, This represents the time difference between the j-th time period and the irrigation execution time. , as well as These represent the corresponding weighting coefficients, and λ represents the attenuation factor.

[0154] Based on the above embodiments, as an optional embodiment, the irrigation plan adjustment module is further used to define a smoothing factor and adjust the adjustment coefficient through the smoothing factor;

[0155] The smoothing factor is:

[0156] ;

[0157] In the formula, η represents the adjustment constant, which is used to characterize the influence of priority changes on the adjustment coefficient, I(c,t) represents the irrigation priority of the connected area at time t, and Δt represents the time difference.

[0158] It should be noted that the above embodiments of the apparatus are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0159] This application also provides a computer storage medium that can store multiple instructions. The instructions are adapted to be loaded by a processor and executed as described in the above embodiments for the energy efficiency optimization method of the irrigation area. The specific execution process can be referred to the detailed description of the embodiments shown, which will not be repeated here.

[0160] This application also discloses an electronic device. (See reference...) Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0161] The communication bus 302 is used to enable communication between these components.

[0162] The user interface 303 may include a display interface and a camera interface. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0163] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0164] The processor 301 may include one or more processing cores. The processor 301 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and by calling data stored in the memory 305. Optionally, the processor 301 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 301 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface graphics, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 301 and may be implemented as a separate chip.

[0165] The memory 305 may include random access memory (RAM) or read-only memory. Optionally, the memory 305 may include a non-transitory computer-readable storage medium. The memory 305 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 305 may also be at least one storage device located remotely from the aforementioned processor 301. (Refer to...) Figure 3 The memory 305, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for an energy efficiency optimization method for irrigation areas.

[0166] exist Figure 3 In the illustrated electronic device 300, the user interface 303 is mainly used to provide an input interface for the user and to acquire user input data; while the processor 301 can be used to call an application program stored in the memory 305 for an energy efficiency optimization method for an irrigation area. When executed by one or more processors 301, the electronic device 300 performs one or more of the methods described in the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0167] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0168] In the various embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between apparatuses or units may be electrical or other forms.

[0169] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0170] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0171] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0172] The above description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and the disclosure of practical truths.

[0173] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for energy efficiency optimization of an irrigation area, characterized in that, include: Obtain crop and soil information for each sub-region within the irrigation area, wherein the irrigation area is connected to branch pipes of each sub-region via a main pipe; For any of the sub-regions, the required irrigation amount and irrigation priority for the crops in the sub-region are determined based on the crop information and soil information; Based on the irrigation amount and irrigation priority corresponding to each sub-region, a first irrigation plan for the connected region is generated. The connected region consists of at least two sub-regions. The first irrigation plan includes an irrigation mode for irrigating crops in each sub-region of the connected region at different time periods. Obtain current electricity price information and environmental information, and calculate adjustment coefficients for each of the connected regions based on the electricity price information and environmental information. The adjustment coefficients are used to characterize the energy efficiency of the first irrigation plan under the electricity price information and environmental information. If the adjustment coefficient is greater than the threshold, then based on the electricity price information and the environmental information, the first irrigation plan is adjusted to obtain the second irrigation plan; The step of generating a first irrigation plan for the connected region based on the irrigation amount and irrigation priority corresponding to each of the sub-regions includes: Based on the priority and irrigation amount of each sub-region, determine at least two sub-regions to form a connected region, and the irrigation time of each sub-region within at least one time period; Based on the irrigation time and irrigation amount of each sub-region in the connected region, the irrigation mode of each sub-region is determined, and the irrigation mode includes sprinkler irrigation or drip irrigation; The irrigation time and irrigation pattern of each sub-region in the connected region are used as the first irrigation plan; The step of determining at least two sub-regions to form a connected region based on the priority and irrigation amount of each sub-region, and the irrigation time of each sub-region within at least one time period, includes: Based on the priority order of each sub-region and the maximum flow rate of the water pump in the irrigation area, at least two sub-regions are determined to form a connected region, wherein the difference in irrigation volume between the sub-regions in the connected region is less than a threshold, and the total irrigation volume is less than or equal to the maximum flow rate of the water pump. Generate the time window corresponding to the connected region; Irrigation time is allocated to each sub-region based on the irrigation amount of each sub-region in the connected region.

2. The method for energy efficiency optimization of an irrigation area according to claim 1, characterized in that, The step of determining the required irrigation amount and irrigation priority for crops in the sub-region based on the crop information and soil information, wherein the crop information includes crop type and crop growth stage, and the soil information includes soil moisture, includes: Based on the crop type and crop growth stage, determine the irrigation amount required for crops in the sub-regions corresponding to the connected region; Irrigation priorities for crops in the sub-region are determined based on the soil moisture and the amount of irrigation required by the crops.

3. The method for energy efficiency optimization of an irrigation area according to claim 1, characterized in that, The time window represents a continuous time period allocated to the connected region, and the length of the time window is determined based on the optimal operating cycle of the water pump and the total irrigation demand of the sub-regions in the connected region.

4. The method for energy efficiency optimization of an irrigation area according to claim 1, characterized in that, The electricity price information includes electricity prices for each of the said time periods, and the environmental information includes rainfall for each of the said time periods. The step of calculating the adjustment coefficient for each of the said connected regions based on the electricity price information and the environmental information includes: Substituting the first irrigation plan corresponding to each of the connected regions, along with the electricity price and rainfall corresponding to the first irrigation plan, into the adjustment coefficient calculation formula, the adjustment coefficient for each of the connected regions is obtained. The formula for calculating the adjustment coefficient is as follows: ； In the formula, A represents the adjustment coefficient. This represents the electricity price of the k-th connected region in the j-th time period. Let P represent the standard electricity price, and let P represent the electricity price difference threshold, used to characterize the significance of the electricity price difference. This represents the precipitation in the k-th connected region during the j-th time period. This indicates the irrigation priority of the k-th connected region in the j-th time period. Indicates an indicator function, When it is 1, When it is 0, This represents the time difference between the j-th time period and the irrigation execution time. , as well as These represent the corresponding weighting coefficients, and λ represents the attenuation factor.

5. An energy efficiency optimization system for an irrigation area, characterized by, include: The irrigation information acquisition module is used to acquire crop and soil information of each sub-region in the irrigation area, wherein the irrigation area is connected to the branch pipes of each sub-region through the main pipe; An irrigation demand determination module is used to determine, for any given sub-region, the required irrigation amount and irrigation priority for crops in the sub-region based on the crop information and soil information; An irrigation plan generation module is used to generate a first irrigation plan for a connected region based on the irrigation amount and irrigation priority corresponding to each of the sub-regions. The connected region consists of at least two sub-regions. The first irrigation plan includes an irrigation mode for irrigating crops in each of the sub-regions of the connected region at different time periods. An irrigation plan adjustment module is used to acquire current electricity price information and environmental information; and to calculate adjustment coefficients for each of the connected regions based on the electricity price information and the environmental information, wherein the adjustment coefficients are used to characterize the energy efficiency of the first irrigation plan under the electricity price information and the environmental information. If the adjustment coefficient is greater than the threshold, then based on the electricity price information and the environmental information, the first irrigation plan is adjusted to obtain the second irrigation plan; The irrigation plan generation module is further configured to determine, based on the priority and irrigation amount of each sub-region, at least two sub-regions to form a connected region, and the irrigation time of each sub-region within at least one time period; determine the irrigation mode of each sub-region based on the irrigation time and irrigation amount of each sub-region in the connected region, wherein the irrigation mode includes sprinkler irrigation or drip irrigation; and use the irrigation time and irrigation mode of each sub-region in the connected region as a first irrigation plan. The irrigation plan generation module is further configured to determine at least two sub-regions to form a connected region based on the priority order of each sub-region and the maximum flow rate of the water pump in the irrigation region, wherein the difference in irrigation amount between the sub-regions in the connected region is less than a threshold and the total irrigation amount is less than or equal to the maximum flow rate of the water pump; generate a time window corresponding to the connected region; and allocate irrigation time for each sub-region based on the irrigation amount of each sub-region in the connected region.

6. An electronic device, comprising: The device includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method as described in any one of claims 1-4.

7. A computer storage medium, characterized in that The computer storage medium stores instructions that, when executed, perform the method as described in any one of claims 1-4.

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