An energy consumption control system for industrial aquaculture

Abstract

The application provides a factory aquaculture energy consumption control system, and belongs to the field of factory aquaculture. The system comprises a sensor layer, which is used to collect device operation data and environmental data of multiple devices in a factory aquaculture scene to be controlled; the device operation data and the environmental data are sent to a cloud service layer; the cloud service layer is used to receive the device operation data and the environmental data sent by the sensor layer; an optimization objective function is constructed by taking time-shiftable load constraints and trigger type load constraints as constraint conditions and minimizing the operation cost of the multiple devices in the factory aquaculture scene to be controlled as an optimization objective, and the respective operation strategies of the multiple devices are determined; the respective operation strategies of the multiple devices are sent to a device control layer; and the device control layer is used to perform energy consumption control on the multiple devices according to the respective operation strategies of the multiple devices. The system can formulate an operation strategy that takes into account the device operation mechanism and time-of-use electricity price, and reduces the energy consumption and operation cost of factory aquaculture.

Description

Technical Field

[0001] This invention belongs to the field of factory-scale aquaculture, specifically relating to an energy consumption control system for factory-scale aquaculture. Background Technology

[0002] Factory farming, as the most mechanized aquaculture model, relies on closed or semi-closed recirculating aquaculture systems. Through precise control of environmental parameters such as dissolved oxygen, water temperature, room temperature, pH, ammonia nitrogen, and turbidity, it improves the output per unit volume of water and food safety. Compared to traditional models, factory farming is characterized by a large number of ponds, spanning multiple fish species and growth stages, a wide variety of equipment, and high energy consumption. The long-term operation of energy-intensive equipment such as aeration and circulation pumps, heating, cooling, and ultraviolet sterilization leads to high energy consumption and operating costs, and also places higher demands on the coordination of monitoring and control. Therefore, there is an urgent need to develop energy consumption metering and optimization control systems to assist factory managers in achieving optimal control of the operation of all equipment throughout the entire process, thereby reducing energy consumption and costs.

[0003] Existing energy consumption control systems employ fixed threshold-based control strategies. When environmental parameters collected by sensors meet preset conditions, the corresponding equipment is started or stopped to avoid increased energy consumption from continuous operation. While this approach maintains the stability of the aquaculture environment, it manages both equipment that doesn't require long-term operation and equipment that does, using the same immediate response control strategy. This ignores the differences in the operating mechanisms of different equipment, leading to persistently high energy consumption in aquaculture. Consequently, it increases the cost of factory farming and hinders its application and promotion. Summary of the Invention

[0004] To address the problems of high energy consumption and high aquaculture costs associated with existing energy control systems, this invention provides an energy control system for factory-scale aquaculture.

[0005] To achieve the above objectives, the present invention provides the following technical solution: An energy consumption control system for factory-scale aquaculture includes: The sensor layer is used to collect equipment operation data and environmental data of multiple devices in the factory farming scenario to be controlled. These multiple devices include time-shiftable load devices and trigger-type load devices. The cloud service layer receives device operation data and environmental data sent by the sensor layer. Using time-shiftable load constraints and trigger-based load constraints as constraints, and minimizing the operating cost of multiple devices in the controlled factory farming scenario as the optimization objective, an optimization objective function is constructed based on the device operation data. The optimization objective function determines the corresponding operation strategy for each of the multiple devices. The operating cost is determined based on the energy consumption of the device within the time window and the time-of-use electricity price. The time-shiftable load constraint is used to limit the running time of the time-shiftable load device to remain constant and the running segment to be within a preset time window. The trigger-based load constraint is used to limit the environmental data corresponding to the trigger-based load device to be within a preset environmental condition threshold range. The device control layer is used to receive the respective operating policies of multiple devices sent by the cloud service layer, and to control the energy consumption of multiple devices according to their respective operating policies.

[0006] Optionally, in the energy consumption control system for factory-scale aquaculture provided by the present invention, the sensor layer includes sensors for dissolved oxygen, water temperature, ammonia nitrogen, pH, turbidity, conductivity, room temperature, and humidity, as well as an electricity meter for detecting the energy consumption of the equipment.

[0007] Optionally, in the energy consumption control system for factory-scale aquaculture provided by the present invention, the cloud service layer is further used to classify the equipment that needs to run continuously in the factory-scale aquaculture scenario into non-schedulable load equipment, the equipment whose running time can be adjusted in the factory-scale aquaculture scenario into time-shiftable load equipment, and the equipment whose start-stop status is determined based on environmental data in the factory-scale aquaculture scenario into trigger-type load equipment, according to the operating mechanism of multiple equipment in the factory-scale aquaculture scenario to be controlled.

[0008] Optionally, in the energy consumption control system for factory-scale aquaculture provided by the present invention, the non-schedulable load equipment includes a circulating water pump and an ultraviolet germicidal lamp, the time-shiftable load equipment includes a microfilter, and the trigger-type load equipment includes an aerator, an oxygen cone pump, a heat pump, an internal and external circulation fan, and a heat lamp.

[0009] Optionally, in the energy consumption control system for factory-scale aquaculture provided by the present invention, the cloud service layer is also used to adjust the environmental condition threshold according to the fish species type and stocking density corresponding to the factory-scale aquaculture scenario to be controlled, and update the triggered load constraint based on the adjusted environmental condition threshold.

[0010] Optionally, in the energy consumption control system for factory-scale aquaculture provided by the present invention, the system also includes a component development platform; The component development platform provides a visual canvas for users to configure equipment in the controlled factory farming scenario. The configured equipment then builds the equipment management strategy for the controlled factory farming scenario and sends the equipment management strategy to the equipment control layer. The device control layer is also used to receive device management policies and to control the energy consumption of multiple devices according to the device management policies.

[0011] Optionally, in the energy consumption control system for factory-scale aquaculture provided by the present invention, the front end of the component development platform is built based on Vue 3, Element Plus and Vite technologies, and the back end of the component development platform adopts Node.js and MySQL architecture.

[0012] Optionally, in the energy consumption control system for factory-scale aquaculture provided by the present invention, the system further includes a communication gateway layer; The communication gateway layer uses an industrial IoT gateway that supports the MQTT protocol to upload the device operation data and environmental data collected by the sensor layer to the cloud service layer.

[0013] Optionally, the present invention provides an energy consumption control system for factory-scale aquaculture, wherein the communication gateway layer and the cloud service layer achieve data interaction through an API service gateway, wherein the API service gateway supports the MQTT protocol and the WebSocket protocol and provides a unified data interface.

[0014] Optionally, in the energy consumption control system for factory-scale aquaculture provided by the present invention, the system further includes a visualization unit; The visualization unit is used to acquire the device operation data and environmental data collected by the sensor layer, and output and display the device operation data and environmental data.

[0015] The energy consumption control system for factory-scale aquaculture provided by this invention has the following beneficial effects: The energy consumption control system for factory-scale aquaculture provided by this invention monitors the environment through sensors and optimizes equipment by classifying it into two categories: time-shiftable equipment automatically adjusts to operate during periods of low electricity prices; and trigger-based equipment only starts when environmental conditions exceed limits. The system cloud automatically calculates and executes the optimal switching strategy based on real-time electricity prices and aquaculture constraints, minimizing energy costs while ensuring production safety. Specifically, because this invention can distinguish between time-shiftable and trigger-based load equipment through a cloud service layer and construct an optimization function based on this to minimize operating costs, it can formulate a refined operating strategy that considers both equipment operating mechanisms and time-of-use electricity prices. This not only achieves significant energy savings and reduces electricity expenses by optimizing equipment operating times, but also reduces overall aquaculture costs and equipment wear by avoiding ineffective start-ups and over-operation. This lowers the energy consumption and operating costs of factory-scale aquaculture, helping to overcome its high-cost bottleneck and thus promoting the wider application of factory-scale aquaculture. Attached Figure Description

[0016] To more clearly illustrate the embodiments and design schemes of the present invention, the accompanying drawings required for this embodiment will be briefly described below. The drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A schematic diagram of an energy consumption control system for factory-scale aquaculture provided in an embodiment of the present invention; Figure 2 This invention provides a component development platform for an energy consumption control system for factory-scale aquaculture, as illustrated in an embodiment of the invention. Figure 3 This is an example of device power consumption and power usage suggestion output provided in an embodiment of the present invention; Figure 4 This is an example of the indoor environmental parameter output of the energy consumption control system for factory-scale aquaculture provided in this embodiment of the invention; Figure 5 This is an example of the turbidity output of the microfiltration tank in the energy consumption control system for factory-scale aquaculture provided in this embodiment of the invention; Figure 6 This is one example of the fishpond parameter monitoring results provided by the energy consumption control system for factory-scale aquaculture in this embodiment of the invention; Figure 7 This is a second example of the monitoring results of fishpond parameters in the energy consumption control system for factory-scale aquaculture provided in this embodiment of the invention. Figure 8 This is the third example of fishpond parameter monitoring results provided by the energy consumption control system for factory-scale aquaculture in this embodiment of the invention. Figure 9 This is an example of a comparison chart of real-time power consumption before and after scenario construction in Scenario 1 provided by an embodiment of the present invention; Figure 10 Example of a comparison chart of cumulative power consumption before and after scenario construction in Scenario 1 provided by an embodiment of the present invention; Figure 11 This is an example of a comparison chart of real-time power consumption before and after scenario construction in Scenario 2 provided in this embodiment of the invention; Figure 12 This is an example of a comparison chart of cumulative power consumption before and after scenario construction in Scenario 2 provided in an embodiment of the present invention. Detailed Implementation

[0018] To enable those skilled in the art to better understand and implement the technical solutions of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and should not be construed as limiting the scope of protection of the present invention.

[0019] Example 1 This invention provides an energy consumption control system for factory-scale aquaculture, specifically as follows: Figure 1 As shown, taking the energy consumption control system for factory-scale aquaculture as an example, it includes the following modules: The sensor layer is used to collect equipment operation data and environmental data from multiple devices in the controlled factory farming scenario. These devices include time-shiftable load devices and trigger-based load devices. The equipment operation data and environmental data are then sent to the cloud service layer. The sensor layer includes sensors for dissolved oxygen, water temperature, ammonia nitrogen, pH, turbidity, conductivity, room temperature, humidity, and electricity meters to detect the energy consumption of the devices.

[0020] The cloud service layer receives device operation data and environmental data sent by the sensor layer. Using time-shiftable load constraints and trigger-based load constraints as conditions, and minimizing the operating cost of multiple devices in the controlled factory farming scenario as the optimization objective, it constructs an optimization objective function based on the device operation data. This objective function determines the corresponding operating strategies for each device. The operating cost is determined based on the device's energy consumption and time-of-use electricity price within a time window. Time-shiftable load constraints limit the runtime of time-shiftable load devices to a constant duration and ensure the runtime falls within a preset time window. Trigger-based load constraints limit the environmental data corresponding to trigger-based load devices to fall within a preset environmental condition threshold range. The operating strategies for each device are then sent to the device control layer. The cloud service layer is also used to classify equipment in the controlled factory farming scenario into three categories based on their operating mechanisms: equipment requiring continuous operation is classified as unschedulable load equipment; equipment whose operating time can be adjusted is classified as time-shiftable load equipment; and equipment whose start / stop status is determined based on environmental data is classified as trigger-based load equipment. Unschedulable load equipment includes circulating water pumps and ultraviolet germicidal lamps; time-shiftable load equipment includes microfilters; and trigger-based load equipment includes aerators, oxygen cone pumps, heat pumps, internal and external circulation fans, and heat lamps. The cloud service layer is also used to adjust environmental condition thresholds based on the fish species and stocking density corresponding to the controlled factory farming scenario, and to update trigger-based load constraints based on the adjusted environmental condition thresholds.

[0021] For example, the cloud service layer is a data platform implemented based on the communication gateway layer. Its main functions include at least real-time data collection and storage, as well as the generation and optimization of electricity consumption recommendation models. The cloud service layer receives data from the communication gateway, performs centralized storage and processing, and supports the management of the real-time and historical databases of the big data platform. Specifically, the electricity consumption recommendation model analyzes the operating mechanisms of time-shiftable and trigger-based loads in factory farming systems, establishes a dynamic mechanism model of environmental parameters, and combines this with the time-of-use electricity pricing mechanism of the location to construct an optimization objective function that minimizes operating costs, forming an electricity consumption recommendation model that can adaptively adjust parameters according to the characteristics of different scenarios.

[0022] Specifically, in the dispatchability analysis of electrical equipment, based on operating characteristics and adjustment potential, system equipment is divided into two categories: undispatchable loads and dispatchable loads, as shown in Table 1: Table 1 Load Characteristics Table Unschedulable loads cannot have their operating time arbitrarily adjusted and must maintain their original operating state, lacking energy-saving potential; examples include circulating water pumps, lighting, and ultraviolet lamps. Scheduled loads, on the other hand, can flexibly adjust their operating time or state within a certain range, possessing a certain demand response adjustment capability. By rationally scheduling the operation of such loads, the power grid demand can be balanced during peak electricity consumption periods. Based on this, scheduled loads can be further subdivided into time-shiftable loads and trigger-based loads. Time-shiftable loads can flexibly schedule their operating time within a certain range; trigger-based loads determine the operating state of control equipment based on whether a trigger variable exceeds a threshold, such as turning it on or off. Taking dissolved oxygen control as an example, when the dissolved oxygen concentration in the water is lower than a set value, the oxygen generator automatically starts to provide the necessary oxygen for the fish in the aquaculture pond.

[0023] Based on the above classification, to maintain normal aquaculture operations, non-time-shiftable loads cannot be controlled, and therefore no electricity consumption recommendations can be given. However, time-shiftable and trigger-type loads can provide electricity consumption recommendations. Taking a factory-scale aquaponics scenario as an example, a model is created, and the model is solved with the goal of minimizing power consumption. This yields the optimal start-up time for time-shiftable loads, where a day is divided into 96 time periods, each lasting 15 minutes. For trigger-type loads, a mechanistic model considering the scenario environment is used. Taking room temperature as an example, various factors affecting room temperature and the cooling or heating effects of the evaporative cooling pad or heat pump are considered to maintain the room temperature at a set temperature, thus obtaining the optimal start-up time for the evaporative cooling pad or heat pump.

[0024] For example, in the model of time-shiftable loads, for time-shiftable loads that cannot be interrupted during the time shift process, the operating state of the equipment at any time t is represented by a binary variable. This indicates that the value is 1 when the device is in operation, and 0 otherwise, as shown in formula (1): (1) in, The optimized start time for time-shiftable loads that cannot be interrupted during the time-shift process. Let be the optimized end time of the time-shiftable load, i be the equipment number, and u be the time-shift window index of the time-shiftable load. Furthermore, to ensure that the operating duration of the equipment remains unchanged before and after load shifting, constraints as shown in Equation (2) are added to the model of the time-shiftable load:

[0025] (2) in, The start time before time-shiftable load optimization. The end time before time-shiftable load optimization. This is the start time of the time window for time-shiftable loads. This is the end time of the time-shiftable load time window. To ensure that the optimized new start and end times meet the boundary constraints of the time-shiftable time window, and to guarantee that the load cannot be stopped once it starts running, limitations are imposed. and This ensures that the load always operates within the predetermined time window when adjusting its operating time, and does not exceed the allowed time range.

[0026] Furthermore, for time-shiftable loads that can be interrupted during the time-shifting process, it is possible to divide them into multiple time periods for operation, and the operating state of the device at any time t can be represented by a binary variable. This indicates that the value is 1 when the device is in operation, and 0 otherwise, as shown in formula (3): (3) in, The optimized start time for time-shiftable loads that can be interrupted during the time-shift process. This is the optimized end time for time-shiftable loads. Optimized selection. The new start and end times of each time period must meet the boundary constraints of the time-shiftable time window, and at the same time The runtime of each time period must satisfy the total runtime, i.e. and .

[0027] For triggered loads, their operating status is affected by the operating environment, and their operating cycle is not predetermined before optimization, but is mainly limited by the setpoints of the triggering conditions. For example, when the ambient temperature is below a set threshold range, heating equipment starts operating, and when the ambient temperature reaches the specified value, it stops operating. Taking an aquaponics system as an example, the triggered load response model mainly includes temperature-controlled loads such as heat pumps, fishpond heating rods, and evaporative cooling fan systems, and dissolved oxygen control loads such as aerators. The temperature-controlled loads are determined based on the type of aquaponics and its physiological characteristics, with the set thresholds determined by the model. As shown in formula (4):

[0028] (4) in, Let b be the value of the starting element at time t. This represents the threshold set for the b-th trigger condition. Specifically, when setting the trigger condition for temperature-controlled load, the indoor temperature setting threshold range and the trend of indoor temperature change can be considered as discrimination conditions. This is the general triggering model for temperature-controlled load heat pumps in winter. As shown in formula (5). To maintain the water temperature in the fishpond and ensure the healthy growth of the fish, a fishpond heating rod is used for heating, and its triggering model... As shown in formula (6):

[0029] (5) (6) in, and These represent the sets of operating times for greenhouse heating equipment and fishpond water heating equipment during winter, determined by the suitable temperature range for the growth stages of the aquatic species. For example, the equipment remains on when the temperature is decreasing and below the set temperature, or when the temperature is increasing but still within the set suitable temperature range.

[0030] The summer temperature control load mainly refers to the evaporative cooling pad fan system, which is used to regulate the indoor temperature of the greenhouse aquaponics factory in summer. The triggering model of the evaporative cooling pad fan system is shown in formula (7): (7) in, This refers to a set of times when greenhouse cooling equipment operates during the summer. For example, the equipment remains on when the room temperature is rising and above the set temperature, or when it is falling but still within the suitable range of the set temperature.

[0031] Furthermore, in the aquaponics system, the operation of the aerator is determined by the dissolved oxygen concentration in the fishpond. When the dissolved oxygen concentration is below a set value, the aerator turns on; conversely, it turns off when the concentration is above a set value, triggering the model. As shown in formula (8):

[0032] (8) in, Let be the concentration of dissolved oxygen in the fishpond at time t. Set the dissolved oxygen concentration value for the fish pond.

[0033] Based on the above model, the optimization objective function is set as finding a new start time for each schedulable load in order to reduce operating costs, as shown in formula (9): (9) In this system, the rescheduling of each schedulable load is considered an independent event. When i is a time-shiftable load, load modeling is performed according to formulas (1), (2), and (3); when i is a temperature-controlled load, load modeling is performed according to formulas (4), (5), (6), and (7); and when i is a dissolved oxygen controlled load, load modeling is performed according to formula (8). The system sets the scheduling time step to 15 minutes and uses 24 hours as the complete scheduling cycle. The calculation of operating costs depends on the local time-of-use electricity price. Rated power of load Quantity of load Factors such as operating status are considered, and the decision variable is the operating status of the load at each moment. .

[0034] The equipment control layer is used to control the energy consumption of multiple devices according to their respective operating strategies; it also receives equipment management strategies and controls the energy consumption of multiple devices accordingly. Specifically, the equipment control layer uses a PLC to control the start / stop and frequency conversion of circulating water pumps, aerators, oxygen cone pumps, microfilters, heat pumps, internal and external circulating fans, heat lamps, and ultraviolet germicidal lamps.

[0035] The component development platform provides a visual canvas for users to configure equipment in the controlled factory farming scenario. The configured equipment then builds the equipment management strategy for the controlled factory farming scenario and sends the strategy to the equipment control layer. The front-end of the component development platform is built using Vue 3, Element Plus, and Vite technologies, while the back-end uses a Node.js and MySQL architecture.

[0036] Specifically, such as Figure 2 As shown, the configuration development platform provides a flexible and visual configuration environment, allowing users to categorize components into six types according to actual scenarios: system components, connection components, scene material selection, automation equipment selection, fishpond configuration selection, and species selection. These components are then pieced together using a canvas to realize data flow and control relationships between devices within the scene.

[0037] For example, the system component bar includes basic functional components such as connectors, text boxes, and timestamps. These components allow users to connect various modules within the system and display data, supporting functions such as visualizing information flow, time management, and text input / output, ensuring clear system logic and convenient operation. The connection component bar includes physical components such as pipes and bends for connecting equipment and the system. Users can flexibly configure the connection relationships between devices, simulating actual water flow and paths to form a complete system connection structure. The scene material selection bar includes scene construction materials such as glass and plastic film. Users can select appropriate materials to construct the aquaculture environment according to the actual needs of different aquaculture scenarios. For example, in a greenhouse aquaculture system, glass or plastic film can be selected as the external structural material to form a reasonable spatial layout and insulation effect. The automation equipment selection bar includes automated control equipment such as water pumps, aerators, and microfilters. Users can select different types of automated equipment according to their aquaculture needs and connect and configure them with other components to achieve automated control and data monitoring functions. The fishpond configuration selection bar includes aquaculture ponds of different sizes and types. Users can select appropriate fishpond configurations, such as buffer ponds and nitrification ponds, according to the needs of different aquaculture scenarios, and configure suitable water flow control and equipment layout. The species selection bar allows users to choose suitable environmental configurations and parameters based on the fish or vegetable species being farmed. The system supports automatic adjustment of environmental parameters based on species selection to ensure optimal growth conditions for the aquaculture targets. The canvas is the core of the tool; users can drag and drop required components to designated locations and use the toolbar and configuration information bar to set specific functions. After development, users can save, preview, and view the interface effects, and finally publish it for use by other systems or platforms. Furthermore, each component corresponds to a mapping object and has a unique identifier in the configuration management module. Each component can run independently and be controlled according to the power consumption recommendation model to achieve independent energy consumption optimization control.

[0038] The communication gateway layer employs an industrial IoT gateway supporting the MQTT protocol. This gateway uploads equipment operation and environmental data collected by the sensor layer to the cloud service layer. Data interaction with the cloud service layer is achieved through an API service gateway, which supports MQTT and WebSocket protocols and provides a unified data interface. For example, the communication gateway layer uses Modbus and MQTT protocols to exchange data with the PLC in the field, collecting real-time equipment operating status and sensor data. After converting the data into a unified format, it uploads it to the cloud for storage, processing, and analysis via a network connection.

[0039] For example, the communication gateway layer uses Modbus and MQTT protocol standards to achieve real-time data acquisition, unifying and aggregating the massive amounts of data generated by the sensor layer. The backend, based on Node.js, MySQL, and a server technology stack, is responsible for database access, data integration with other third-party business systems, user management, authentication and authorization mechanisms, data processing, and chart display. The frontend uses Vue 3, Element Plus, and Vite technology stacks to implement the user interface, supporting chart display, real-time data monitoring, and remote operation functions, providing a smooth user experience.

[0040] The visualization unit is used to acquire and display the device operation data and environmental data collected by the sensor layer. For example, ... Figure 3-9 As shown, the visualization unit includes at least water quality monitoring, energy consumption analysis, component management, and equipment status monitoring functions, supporting remote operation and scheduling management by users. Among them, such as... Figure 3 As shown, the visualization unit can output the power consumption of each load in the system and power consumption suggestions; such as Figure 4 As shown, the visualization unit can also output current indoor environmental parameters such as temperature and humidity, and perform a preliminary analysis to determine whether these environmental parameters are within acceptable limits; furthermore, as... Figure 5 As shown, for key equipment, such as microfilters in aquaculture, the turbidity status is output; and, as... Figure 6 , Figure 7 and Figure 8 As shown, it can output the current parameters of each fishpond in real time, such as water temperature, pH value, and dissolved oxygen content. Furthermore, to facilitate user monitoring and analysis, the collected data is stored as historical data and can be retrieved and displayed based on user needs, as shown in Table 2:

[0041] Table 2 shows historical data. It is important to emphasize that in the configuration graphical user interface for multi-scenario energy consumption metering in factory-scale digital fisheries, the relationships between components and their participation in actual scenarios are dynamic, especially the integration of circulating water equipment. Only when these devices are explicitly configured as part of the circulating water system in the configuration development platform do they truly participate in the system's control and management. For example, in the configuration interface, users need to connect various equipment components such as pumps, aerators, and filtration systems to the designated circulating water system framework through drag-and-drop and configuration methods, ensuring interconnectivity and data flow between devices.

[0042] Before configuration, the circulating water equipment and related components in the system do not directly interact with other parts of the system. This approach ensures that, in actual operation, only equipment configured into the circulating water system can be controlled and monitored within the system, avoiding the involvement of redundant or ineffective equipment. Simultaneously, through this flexible configuration-based approach, users can accurately define and adjust the function, operating parameters, and interactions between each device, thereby achieving precise energy efficiency optimization and automated control.

[0043] Furthermore, to ensure data security, all data transmission during communication employs the TLS encryption protocol to prevent data tampering or theft during transmission. The platform also incorporates a multi-layered authentication and access control mechanism, ensuring that only authorized users can access and operate critical system functions. All data acquisition and control commands undergo rigorous verification and approval processes to ensure that every operation complies with security regulations. The platform also supports regular data backup and recovery functions to guarantee the integrity and security of data from the sensor layer in factory farming.

[0044] In summary, the energy consumption control system for factory-scale aquaculture provided by this invention is customized for different factory-scale aquaculture scenarios, enabling it to quickly adapt to the needs of different aquaculture models. Through modular design and component reuse, users can flexibly adjust the system configuration according to specific scenario requirements, reducing deployment time and costs, thereby flexibly adapting to different factory-scale aquaculture scenarios and improving the system's adaptability and scalability.

[0045] Furthermore, the energy consumption control system for factory-scale aquaculture provided by this invention combines time-of-use pricing and demand response mechanisms to provide an electricity consumption suggestion model, optimize the operating hours and load allocation of equipment, and minimize energy consumption and effectively reduce electricity costs while ensuring a stable aquaculture environment, thereby achieving efficient energy consumption optimization and management.

[0046] Furthermore, the energy consumption control system for factory-scale aquaculture provides an intuitive visual interface, allowing users to easily manage and control various aquaculture equipment. The system supports remote monitoring, scheduling, and automated control, providing real-time feedback on equipment operating status and enabling timely strategy adjustments to ensure the efficient operation and stability of the aquaculture system, reducing manual intervention and thus achieving simplified equipment management and remote control.

[0047] Example 2 Specifically, taking a fish-vegetable symbiotic recirculating aquaculture system (RVRA) in northern China as an example, this invention further illustrates the cost control capabilities of the RVRA energy consumption control system provided by this invention. The external structure of this RVRA system is a plastic greenhouse, including multiple aquaculture ponds, hydroponic vegetable racks, circulating water pumps, aerators, oxygen cone pumps, microfilters, heat pumps, evaporative cooling pads, internal and external circulating fans, and ultraviolet germicidal lamps. The fish species is Siberian sturgeon, and the vegetable species is butter lettuce. For a typical summer day in mid-July, before the scenario is built using the configurable graphical user interface, a rough-and-ready operating mode based on aquaculture experience is adopted. After the scenario is built using the configurable graphical user interface, the energy consumption requirements and production scheduling requirements of various devices within the scenario are analyzed in real time through a cloud-based power consumption suggestion model, combined with a demand response scheme, to generate optimized control strategies. The cloud model automatically calculates the optimal start-stop timing and operating power for each device based on real-time electricity prices, load forecasts, and equipment operating status, thereby determining energy-saving strategies.

[0048] Once the optimization plan is generated, the cloud platform sends relevant control commands to the field device PLCs via API, ensuring that the equipment operates automatically according to the optimization strategy. The energy consumption comparison for a summer day after setting up the scenario through the configuration graphical user interface is shown below, including real-time power consumption and cumulative power consumption. Figure 9 and Figure 10 As shown, after setting up the scenario through the configurable graphical user interface, the total daily power consumption decreased from 328.57 kWh to 279.69 kWh, a reduction of 56.96 kWh, saving 14.8%, and the electricity cost decreased by 48.6 yuan, saving 19.3%. Furthermore, after setting up the scenario through the configurable graphical user interface, the 15-day fish mortality rate remained almost unchanged, decreasing from 0.53% to 0.55%. This significant energy-saving effect demonstrates that after setting up the scenario, the configurable graphical user interface optimizes the scheduling of time-shiftable loads, rescheduling them to periods with lower electricity prices, and reduces unnecessary equipment operating time through threshold control of triggered loads, effectively lowering energy costs.

[0049] Furthermore, taking a factory-style recirculating aquaculture system (RAS) located in southern China as an example, this invention illustrates the cost control capability of the RAS energy consumption control system provided by this invention. The external structure of this RAS is a glass greenhouse, including multiple rearing ponds, circulating water pumps, aerators, microfilters, evaporative cooling pads, internal and external circulating fans, and ultraviolet germicidal lamps. The fish species is largemouth bass. For a typical summer day in mid-July, before completing the scenario setup via the configured graphical user interface, a rudimentary operational mode based on aquaculture experience is adopted within the current RAS scenario.

[0050] After the scene is built using the configurable graphical user interface, the real-time power consumption and cumulative power consumption are as follows: Figure 11 and Figure 12 As shown, the total daily power consumption decreased from 215.6 kWh to 192.9 kWh, a reduction of 22.7 kWh, saving 10.5%, and the electricity cost decreased by 22.6 yuan, saving 13.9%. After configuring the graphical user interface scenario, the fish mortality rate remained unchanged at 0.40% over 15 days. The results indicate that the configurable graphical user interface has good environmental adaptability and can flexibly adjust load scheduling strategies according to the specific needs of different aquaculture scenarios, achieving energy-saving and consumption-reducing goals under different scenarios.

[0051] Those skilled in the art will understand that embodiments of the present invention can provide methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0052] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0053] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0054] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0055] It should be noted that the specific embodiments described above enable those skilled in the art to more fully understand the present invention, but do not limit the present invention in any way. Therefore, although the present invention has been described in detail in this specification and embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the present invention; and all technical solutions and improvements that do not depart from the spirit and scope of the present invention are covered within the protection scope of the present invention patent. No reference numerals in the claims should be construed as limiting the scope of the claims. Any simple variations or equivalent substitutions of technical solutions that can be readily obtained by those skilled in the art within the scope of the technology disclosed in the present invention are within the protection scope of the present invention.

Claims

1. A factory-scale aquaculture energy consumption control system, characterized in that, include: The sensor layer is used to collect equipment operation data and environmental data of multiple devices in the factory farming scenario to be controlled, wherein the multiple devices include time-shiftable load devices and trigger-type load devices; The cloud service layer receives device operation data and environmental data sent by the sensor layer. Using time-shiftable load constraints and trigger-based load constraints as constraints, and minimizing the operating cost of multiple devices in the controlled factory farming scenario as the optimization objective, an optimization objective function is constructed based on the device operation data. This objective function then determines the corresponding operating strategies for each of the multiple devices. The operating cost is determined based on the device's energy consumption and time-of-use electricity price within a time window. The time-shiftable load constraint limits the time-shiftable load device's operating duration to remain constant and ensures that the operating period falls within a preset time window. The trigger-based load constraint limits the environmental data corresponding to the trigger-based load device to fall within a preset environmental condition threshold range. The device control layer is used to receive the respective operating strategies of multiple devices sent by the cloud service layer, and to control the energy consumption of the multiple devices according to the respective operating strategies of the multiple devices.

2. The energy consumption control system for factory-scale aquaculture according to claim 1, characterized in that, The cloud service layer is also used to adjust the environmental condition threshold according to the fish species type and stocking density corresponding to the factory farming scenario to be controlled, and to update the triggered load constraint based on the adjusted environmental condition threshold.

3. The energy consumption control system for factory-scale aquaculture according to claim 1, characterized in that, The sensor layer includes sensors for dissolved oxygen, water temperature, ammonia nitrogen, pH, turbidity, conductivity, room temperature, and humidity, as well as an electricity meter to detect the energy consumption of the detection equipment.

4. The energy consumption control system for factory-scale aquaculture according to claim 1, characterized in that, The cloud service layer is also used to classify, based on the operating mechanism of multiple devices in the controlled industrialized farming scenario, the devices that need to run continuously in the controlled industrialized farming scenario into non-schedulable load devices, the devices whose running time can be adjusted in the controlled industrialized farming scenario into time-shiftable load devices corresponding to time-shiftable load constraints, and the devices whose start-stop status is determined based on the environmental data in the controlled industrialized farming scenario into trigger-based load devices corresponding to trigger-based load constraints.

5. The energy consumption control system for factory-scale aquaculture according to claim 4, characterized in that, The non-schedulable load equipment includes a circulating water pump and an ultraviolet germicidal lamp; the time-shiftable load equipment includes a microfiltration machine; and the trigger-type load equipment includes an aerator, an oxygen cone pump, a heat pump, an internal and external circulation fan, and a heat-insulating lamp.

6. The energy consumption control system for factory-scale aquaculture according to claim 1, characterized in that, The system also includes a component development platform; The component development platform provides a visual canvas for users to configure equipment in the controlled factory farming scenario. The configured equipment then builds the equipment management strategy for the controlled factory farming scenario and sends the equipment management strategy to the equipment control layer. The device control layer is also used to receive the device management strategy and to control the energy consumption of the multiple devices according to the device management strategy.

7. The energy consumption control system for factory-scale aquaculture according to claim 6, characterized in that, The front end of the component development platform is built on Vue 3, Element Plus and Vite technologies, while the back end of the component development platform adopts Node.js and MySQL architecture.

8. The energy consumption control system for factory-scale aquaculture according to claim 1, characterized in that, The system also includes a communication gateway layer; The communication gateway layer adopts an industrial IoT gateway that supports the MQTT protocol, which is used to upload the device operation data and environmental data collected by the sensor layer to the cloud service layer.

9. The energy consumption control system for factory-scale aquaculture according to claim 8, characterized in that, The communication gateway layer and the cloud service layer interact with each other through an API service gateway, which supports the MQTT and WebSocket protocols and provides a unified data interface.

10. The energy consumption control system for factory-scale aquaculture according to claim 1, characterized in that, The system also includes a visualization unit; The visualization unit is used to acquire the device operation data and environmental data collected by the sensor layer, and output and display the device operation data and environmental data.

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