Automatic control method and system for environment in breeding house

Abstract

The invention relates to the technical field of environment control, in particular to an automatic control method and system for the environment in a breeding house, and the method comprises the following steps: collecting a temperature value, a humidity value, a carbon dioxide concentration value, a power consumption value, a water resource consumption value and a feed consumption value through a sensor in the breeding house, and carrying out the noise filtering treatment; and executing data normalization processing to obtain pre-processed data. According to the method, the difference between the index and the target value is calculated, and the multi-objective optimization function is combined, so that accurate adjustment of the control parameters is realized. Therefore, key indexes such as temperature, humidity, carbon dioxide level and energy consumption are continuously monitored, equipment operation parameters are optimized, and energy efficiency and environment quality are improved. Particularly, due to real-time identification and adjustment of high-energy-consumption equipment, energy waste is reduced, the stability of the breeding environment is ensured, potential risks caused by environment fluctuation are reduced, and the breeding efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental control, and in particular to a method and system for automatically controlling the environment in a breeding house. Background Art

[0002] The field of environmental control technology encompasses a wide range of systems and devices designed to optimize and control climate and conditions within closed-loop environments, such as temperature, humidity, light intensity, and air quality. These technologies are used across multiple industries, but are particularly central to the design and maintenance of agriculture, animal husbandry, greenhouse cultivation, laboratory facilities, and comfortable living and working spaces.

[0003] Existing environmental control technologies are limited by fixed parameter settings, resulting in a time lag and difficulty responding in real time to rapidly changing farming environments. For example, in greenhouses or livestock farms, if temperature or humidity cannot be adjusted immediately based on actual data, this can lead to an unsuitable growth environment, impacting the health and productivity of the organisms. Therefore, improvements are needed. Summary of the Invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a method and system for automatically controlling the environment in a breeding house.

[0005] In order to achieve the above object, the present invention adopts the following technical solution, a method for automatically controlling the environment in a breeding house, comprising the following steps: Through sensors in the breeding house, temperature, humidity, carbon dioxide concentration, power consumption, water consumption, and feed consumption are collected, noise filtering is performed, and data normalization is performed to obtain pre-processed data; Based on the preprocessed data, calculating the differences between the temperature value, humidity value, and carbon dioxide concentration value and the target temperature value, target humidity value, and target carbon dioxide concentration value, calculating the differences between the power consumption value, water resource consumption value, and feed consumption value and the power target value, water resource target value, and feed target value, to obtain an environmental difference value set and an energy difference value set, performing a weighted operation on the environmental difference value set and the energy difference value set, establishing a multi-objective optimization function including the environmental difference value and the energy difference value, solving the multi-objective optimization function, and obtaining control parameters; Based on the control parameters, adjusting the operating parameters of the heating device, the cooling device, the ventilation device and the humidification device, setting the temperature setting value of the heating device, the temperature setting value of the cooling device, the wind speed setting value of the ventilation device and the humidity setting value of the humidification device; Collect equipment operation data in real time, record the start and stop time values and operating power values of the equipment, calculate the cumulative operating time value and cumulative energy consumption value of each equipment, obtain the equipment energy consumption data set, analyze the equipment energy consumption data set, identify high-energy consumption equipment and high-energy consumption operating modes, and adjust the start and stop time values and operating power values of high-energy consumption equipment.

[0006] Preferably, the steps of obtaining the pre-processed data are: The original data set is obtained by collecting temperature, humidity, carbon dioxide concentration, electricity consumption, water consumption and feed consumption values through sensors in the breeding house; Based on the original data set, the standard deviation of each data item is calculated, the degree of data variation is analyzed, and outliers exceeding two times the standard deviation are filtered out to obtain an outlier-filtered data set. The standard deviation calculation formula is: ; Among them, S i is the standard deviation of the i-th data, X ij is the jth data point of the i-th data type, For X i The average value of the data, on is the total number of data points; Based on the outlier-filtered data set, the data is transformed by subtracting the mean from each data point and dividing by the standard deviation to generate normalized preprocessed data.

[0007] Preferably, the steps for obtaining the environmental difference value set and the energy difference value set are: Based on the preprocessed data, temperature values, humidity values, carbon dioxide concentration values, electricity consumption values, water resource consumption values, and feed consumption values are selected to obtain a standardized data set; Based on the standardized data set, the difference between the target value and the target value is calculated using the following formula: ; in, is the temperature difference, is the humidity difference, is the carbon dioxide difference, , , are the target temperature value, target humidity value and target carbon dioxide concentration value respectively. , , are temperature, humidity and carbon dioxide concentration values; Based on the temperature difference, humidity difference and carbon dioxide difference, the differences between the electricity, water resources and feed consumption values and the target values are further calculated to form an environmental difference set and an energy difference set.

[0008] Preferably, the steps of obtaining the control parameters are: Performing a weighted operation based on the environmental difference value set and the energy difference value set to generate a weighted difference value set; According to the weighted difference, a multi-objective optimization function is established, and the formula is: ; in, and are the weight coefficients of environmental difference and energy difference, and represent the measured values of the i-th environmental parameter and the j-th resource parameter, respectively. and are the target values of the i-th environmental parameter and the j-th resource parameter, qn is the total number of environmental parameters, and m is the total number of resource parameters; Solving multi-objective optimization functions , and obtain the control parameters.

[0009] Preferably, based on the control parameters, the operating parameters of the heating device, the cooling device, the ventilation device and the humidifying device are adjusted, and the specific steps of setting the temperature setting value of the heating device, the temperature setting value of the cooling device, the wind speed setting value of the ventilation device and the humidity setting value of the humidifying device are as follows: Obtain control parameters from the multi-objective optimization function, adjust the operating parameters of the heating equipment, cooling equipment, ventilation equipment, and humidification equipment, and obtain updated equipment parameter settings; Setting a temperature setting value of a heating device and a temperature setting value of a cooling device based on the updated device parameter settings; Continue to use the updated device parameter settings to adjust the wind speed set point of the ventilation device and the humidity set point of the humidification device.

[0010] Preferably, the steps for obtaining the equipment energy consumption data set are: Real-time collection of start and stop time values and operating power values of heating equipment, cooling equipment, ventilation equipment, and humidification equipment to obtain the original operating data set; Based on the original operation data set, the cumulative operation time and cumulative energy consumption value of each device are calculated using the following formula: ; in, is the total energy consumption of device i, is the operating power of device i in the jth time period, is the running time of device i in the jth time period, is the energy efficiency adjustment coefficient, n is the total number of time periods during which the equipment is running during the target calculation period; Based on the total energy consumption, an equipment energy consumption data set is collated and formed.

[0011] Preferably, the specific steps of analyzing the equipment energy consumption data set, identifying high-energy-consuming equipment and high-energy-consuming operation modes, and adjusting the start / stop time values and operating power values of the high-energy-consuming equipment are as follows: Analyze the equipment energy consumption data set, compare the energy consumption of each device with the industry standard energy consumption through operating power and time data, identify high-energy-consuming devices, and obtain a list of high-energy-consuming devices; Based on the list of high-energy-consuming equipment, use statistical methods to analyze the relationship between operating time and energy consumption, extract energy consumption optimization points, and generate an optimization suggestion list; According to the optimization suggestion list, modify the start and stop times and operating power values of high-energy-consuming equipment.

[0012] The present invention provides an automatic control system, comprising: The environmental monitoring and adjustment module collects temperature, humidity, and carbon dioxide concentration values through sensors in the breeding house, performs noise filtering, performs data normalization, and calculates the difference between temperature, humidity, and carbon dioxide concentration and the target values to obtain an environmental difference data set; The energy consumption optimization module collects power consumption values, water resource consumption values, and feed consumption values based on the environmental difference data set, calculates the difference between the power target value, water resource target value, and feed target value, performs weighted operations, establishes a multi-objective optimization function, solves the multi-objective optimization function, and obtains the adjusted control parameter set; The equipment energy consumption management module adjusts the operating parameters of the heating equipment, cooling equipment, ventilation equipment and humidification equipment based on the adjusted control parameter set, collects equipment operation data in real time, records the start and stop time values and operating power values, calculates the cumulative operating time and energy consumption, obtains the equipment energy consumption data set, analyzes the energy-consuming equipment, and adjusts the start and stop time and operating power.

[0013] Compared with the prior art, the advantages and positive effects of the present invention are: This invention achieves precise adjustment of control parameters by calculating the difference between indicators and target values and incorporating a multi-objective optimization function. This allows for continuous monitoring of key indicators such as temperature, humidity, carbon dioxide levels, and energy consumption, while optimizing equipment operating parameters and improving energy efficiency and environmental quality. In particular, the real-time identification and adjustment of high-energy-consuming equipment reduces energy waste, ensures a stable aquaculture environment, mitigates potential risks caused by environmental fluctuations, and improves aquaculture efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 Schematic diagram of the steps of the present invention. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0016] See also Figure 1 The present invention provides a technical solution, a method for automatically controlling the environment in a breeding house, comprising the following steps: Through sensors in the breeding house, temperature, humidity, carbon dioxide concentration, power consumption, water consumption, and feed consumption are collected, noise filtering is performed, and data normalization is performed to obtain pre-processed data; Based on the preprocessed data, the differences between the temperature value, the humidity value, and the carbon dioxide concentration value and the target temperature value, the target humidity value, and the target carbon dioxide concentration value are calculated; the differences between the power consumption value, the water resource consumption value, and the feed consumption value and the power target value, the water resource target value, and the feed target value are calculated to obtain an environmental difference value set and an energy difference value set; a weighted operation is performed on the environmental difference value set and the energy difference value set; a multi-objective optimization function including the environmental difference value and the energy difference value is established; the multi-objective optimization function is solved to obtain control parameters; Adjust the operating parameters of the heating equipment, cooling equipment, ventilation equipment and humidification equipment based on the control parameters, set the temperature setting value of the heating equipment, the temperature setting value of the cooling equipment, the wind speed setting value of the ventilation equipment and the humidity setting value of the humidification equipment; Collect equipment operation data in real time, record the start and stop time values and operating power values of the equipment, calculate the cumulative operating time value and cumulative energy consumption value of each equipment, obtain the equipment energy consumption data set, analyze the equipment energy consumption data set, identify high-energy consumption equipment and high-energy consumption operating modes, and adjust the start and stop time values and operating power values of high-energy consumption equipment.

[0017] The steps for obtaining preprocessed data are: The original data set is obtained by collecting temperature, humidity, carbon dioxide concentration, electricity consumption, water consumption and feed consumption values through sensors in the breeding house; Based on the original data set, the standard deviation of each data item is calculated, the degree of data variation is analyzed, and outliers exceeding twice the standard deviation are filtered out to obtain an outlier-filtered data set. The standard deviation calculation formula is: ; Among them, S i is the standard deviation of the i-th data, X ij is the jth data point of the i-th data type, For X i The average value of the data, on is the total number of data points; Based on the outlier-filtered dataset, the data were transformed by subtracting the mean from each data point and dividing by the standard deviation to generate normalized preprocessed data.

[0018] Specifically, sensors are used to collect various data in the breeding house, including temperature, humidity, carbon dioxide concentration, and specific information on energy consumption. This data is collected through various sensors. For example, temperature sensors are used to obtain temperature data, humidity sensors are used to obtain humidity data, CO2 sensors are used to monitor carbon dioxide concentration, and electricity meters and water meters are used to monitor energy consumption.

[0019] The formula is useful in that it helps identify outliers in a data set by calculating the standard deviation of each data item, which is crucial for maintaining the quality and reliability of data processing; i The steps to obtain the parameters are: first calculate each data item X ij Average value , then calculate the square of the difference between each data point and the mean, sum these squares and divide by the total number of data points on to get the standard deviation; Calculation process: In the temperature data set, there are 5 data points: 20, 22, 19, 21, 20, and their average is 20.4, then: ;

[0020] The results show that the standard deviation is 1.02, which means that most of the data points fluctuate around the mean value of 20.4 by 1.02 degrees; Based on the filtered data set, each data point is normalized by subtracting its mean and dividing it by its standard deviation. This process improves the consistency and comparability of the data, allowing data to be effectively compared across different scales and ranges. The normalized data are suitable for more complex data analysis and machine learning algorithms because they conform to the standard format for algorithm processing. The final preprocessed data set not only reduces the deviation in data processing, but also enhances the interpretability and reliability of the data in subsequent applications. The output of this step is the normalized data.

[0021] The steps for obtaining the environmental difference value set and the energy difference value set are as follows: Based on the preprocessed data, the temperature, humidity, carbon dioxide concentration, electricity consumption, water consumption, and feed consumption values were selected to obtain a standardized data set. Based on the standardized data set, the difference between the target value and the target value is calculated using the following formula: ; in, is the temperature difference, is the humidity difference, is the carbon dioxide difference, , , are the target temperature value, target humidity value and target carbon dioxide concentration value respectively. , , are temperature, humidity and carbon dioxide concentration values; Based on the temperature difference, humidity difference and carbon dioxide difference, the differences between the electricity, water resources and feed consumption values and the target values are further calculated to form an environmental difference set and an energy difference set.

[0022] Specifically, the calculation process: the normalized temperature value monitored , target temperature value , humidity value , target humidity value , carbon dioxide concentration , target concentration , by plugging these values into the formula, the result is: ; The results indicate that there are small deviations between the actual measured values of temperature, humidity, and CO2 and the set targets, indicating that the environmental control system needs to be fine-tuned to achieve ideal farming conditions.

[0023] The steps to obtain the control parameters are: Performing weighted operations based on the environmental difference value set and the energy difference value set to generate a weighted difference value set; According to the weighted difference, a multi-objective optimization function is established, and the formula is: ; in, and are the weight coefficients of environmental difference and energy difference, and represent the measured values of the i-th environmental parameter and the j-th resource parameter, respectively. and are the target values of the i-th environmental parameter and the j-th resource parameter, qn is the total number of environmental parameters, and m is the total number of resource parameters; Solving multi-objective optimization functions , and obtain the control parameters.

[0024] Specifically, based on the environmental difference set and the energy difference set, a weighted difference set can be calculated by adjusting the weights of these data. In practical applications, real-time monitoring data of environmental parameters and energy parameters is involved. For example, in a breeding house, environmental parameters may include temperature, humidity and carbon dioxide levels, while energy parameters may cover electricity consumption, water resource usage and feed consumption, etc. Each parameter will be assigned a pre-set weight. The setting of these weights is based on past optimization results and operational efficiency analysis to ensure the optimal state of the breeding environment and good utilization of resources.

[0025] The usefulness of the formula is that it allows to optimize the efficiency of both the environment and energy use simultaneously, ensuring a balanced regulation of both by the system; and is the weight coefficient of the difference between environment and energy, representing their respective importance and priority. These weights are obtained through regression analysis based on historical data and expected goals. and They are real-time measurement values, directly obtained through sensors, and It is the target value, which is set according to seasonal changes and production needs; Calculation process: Setting , , , , measured , , the calculation process is: ; The result indicates that there is a gap between the current environmental and energy status and the target, and a value of 6 indicates that the control parameters need to be adjusted to reduce this gap.

[0026] After establishing the multi-objective optimization function, the gradient descent algorithm is used. This algorithm gradually reduces the value of the optimization function through iteration. First, the initial control parameters are set, and then the parameter values are adjusted according to the gradient direction of the optimization function. The calculation of the gradient depends on the real-time data of the environment and energy difference. In each iteration, the parameters are adjusted in the opposite direction of the gradient by a certain step size. The size of the step size has a key impact on the convergence speed and optimization effect. Usually, the step size will gradually decrease according to the number of iterations to avoid oscillation caused by over-adjustment. After multiple iterations, when the improvement of the function value is less than the set threshold or the maximum number of iterations is reached, the iteration stops. The control parameters at this time are considered to be the parameters closest to the optimal solution. This process requires continuous monitoring of real-time data and adjustment of model parameters based on real-time feedback to ensure the accuracy and real-time performance of the optimization process.

[0027] Based on the control parameters, the operating parameters of the heating equipment, cooling equipment, ventilation equipment and humidification equipment are adjusted, and the specific steps for setting the temperature setting value of the heating equipment, the temperature setting value of the cooling equipment, the wind speed setting value of the ventilation equipment and the humidity setting value of the humidification equipment are as follows: Obtain control parameters from the multi-objective optimization function, adjust the operating parameters of the heating equipment, cooling equipment, ventilation equipment, and humidification equipment, and obtain updated equipment parameter settings; Based on the updated device parameter settings, set the temperature setting value of the heating device and the temperature setting value of the cooling device; Continue to use the updated device parameter settings to adjust the wind speed setpoints for ventilation equipment and the humidity setpoints for humidification equipment.

[0028] Specifically, the control parameters extracted from the multi-objective optimization function are the target values of temperature, humidity, wind speed and humidity. These control parameters directly affect the operating efficiency of heating, cooling, ventilation and humidification equipment. In order to effectively adjust the operating parameters of these equipment, it is necessary to first interpret the relationship between the control parameters and equipment performance. The specific operations include identifying the response curve and operating limits of each device to ensure that the equipment operates in the optimal state. By adjusting the temperature set values of the heating and cooling equipment, as well as the corresponding settings of the ventilation and humidification equipment, refined management of environmental control can be achieved, thereby optimizing the environmental quality of the entire breeding house. Through this method, the update of equipment parameters is not just a simple adjustment, but is configured and optimized according to the specific control parameters to obtain the updated equipment parameter settings.

[0029] The steps for obtaining the equipment energy consumption dataset are as follows: Real-time collection of start and stop time values and operating power values of heating equipment, cooling equipment, ventilation equipment, and humidification equipment to obtain the original operating data set; Based on the original operation data set, the cumulative operation time and cumulative energy consumption value of each device are calculated using the following formula: ; in, is the total energy consumption of device i, is the operating power of device i in the jth time period, is the running time of device i in the jth time period, is the energy efficiency adjustment coefficient, n is the total number of time periods during which the equipment is running during the target calculation period; Based on the total energy consumption, the equipment energy consumption data set is organized and formed.

[0030] Specifically, the monitoring sensors for heating, cooling, ventilation, and humidification equipment involved in the real-time data collection process must be able to accurately record the start and stop times of each device, as well as the power consumption during operation. The collection of this data relies on the accurate installation and calibration of the sensors, and the data output by the sensors is first recorded in a database.

[0031] The formula is beneficial in that it introduces the energy efficiency adjustment coefficient , it can adjust the energy consumption calculation according to the actual usage of the equipment to reflect the efficiency reduction of the equipment over time and the frequency of use, which provides data support for equipment maintenance and optimization; Calculation process: Device i runs for 120 minutes in the jth time period with a power of 1500 watts. Its energy efficiency adjustment coefficient is 5% means that the efficiency of the equipment has decreased due to long-term use and improper maintenance. The calculation process is as follows: ; The results show that the actual energy consumption of the equipment after taking into account the reduced efficiency is 3150Wh, which is an increase compared to the energy consumption before adjustment. This data will help further evaluate the energy efficiency of the equipment and formulate energy-saving measures.

[0032] By collating the calculated cumulative energy consumption values for each device, a detailed overview of the device's energy consumption performance can be obtained. This dataset includes the total energy consumption of each device during a specific evaluation period. This data is often used in energy management systems to evaluate device operating efficiency and develop energy conservation and emission reduction strategies. Collating such datasets requires ensuring data integrity and accuracy, which usually involves cleaning, validating, and classifying the data to ensure report accuracy and support decision-making.

[0033] The specific steps for analyzing the equipment energy consumption data set, identifying high-energy-consuming equipment and high-energy-consuming operating modes, and adjusting the start and stop time values and operating power values of high-energy-consuming equipment are as follows: Analyze the equipment energy consumption data set, compare the energy consumption of each device with the industry standard energy consumption through operating power and time data, identify high-energy-consuming devices, and obtain a list of high-energy-consuming devices; Based on the list of high-energy-consuming equipment, use statistical methods to analyze the relationship between operating time and energy consumption, extract energy consumption optimization points, and generate a list of optimization suggestions; According to the optimization recommendation list, modify the start and stop times and operating power values of high-energy-consuming equipment.

[0034] Specifically, we analyze the equipment energy consumption dataset by first extracting the operating power and operating time data for each device. Through comparative analysis, we quantitatively compare the total energy consumption of each device with the industry standard. We use statistical analysis methods of standard deviation and mean to identify devices that deviate from the industry standard, thereby refining the list of devices with abnormally high energy consumption and obtaining a list of high-energy-consuming devices. Based on the resulting list of high-energy-consuming devices, we used multiple linear regression analysis to assess the relationship between operating time and energy consumption. We calculated the energy consumption density (energy consumption per unit time) of each device and, combined with the frequency and duration of device operation, performed trend line analysis on these data points to determine which devices consumed the most energy under specific operating modes. These key data points were then extracted as energy consumption optimization points, generating a list of optimization recommendations. According to the optimization suggestion list, the specific operation is to adjust the start and stop time of high-energy-consuming equipment, such as adjusting the operating time of high-energy-consuming equipment from peak hours when electricity prices are higher to off-peak hours, and at the same time reducing the maximum operating power of these equipment during peak hours. Specifically, it includes setting a maximum power threshold and operating time window for each device. These adjustments are based on the analysis of the historical operating data of the equipment to determine the operating time period during off-peak hours and lower the maximum power setting of the equipment.

[0035] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A method for automatically controlling the environment in a breeding house, characterized in that: The following steps are involved: Through sensors in the breeding house, temperature, humidity, carbon dioxide concentration, power consumption, water consumption, and feed consumption are collected, noise filtering is performed, and data normalization is performed to obtain pre-processed data; Based on the preprocessed data, calculating the differences between the temperature value, humidity value, and carbon dioxide concentration value and the target temperature value, target humidity value, and target carbon dioxide concentration value, calculating the differences between the power consumption value, water resource consumption value, and feed consumption value and the power target value, water resource target value, and feed target value, to obtain an environmental difference value set and an energy difference value set, performing a weighted operation on the environmental difference value set and the energy difference value set, establishing a multi-objective optimization function including the environmental difference value and the energy difference value, solving the multi-objective optimization function, and obtaining control parameters; Based on the control parameters, adjusting the operating parameters of the heating device, the cooling device, the ventilation device and the humidification device, setting the temperature setting value of the heating device, the temperature setting value of the cooling device, the wind speed setting value of the ventilation device and the humidity setting value of the humidification device; Collect equipment operation data in real time, record the start and stop time values and operating power values of the equipment, calculate the cumulative operating time value and cumulative energy consumption value of each equipment, obtain the equipment energy consumption data set, analyze the equipment energy consumption data set, identify high-energy consumption equipment and high-energy consumption operating modes, and adjust the start and stop time values and operating power values of high-energy consumption equipment.

2. The method for automatic control of the environment in a breeding house according to claim 1, characterized in that: The steps for obtaining the preprocessed data are: The original data set is obtained by collecting temperature, humidity, carbon dioxide concentration, electricity consumption, water consumption and feed consumption values through sensors in the breeding house; Based on the original data set, the standard deviation of each data item is calculated, the degree of data variation is analyzed, and outliers exceeding two times the standard deviation are filtered out to obtain an outlier-filtered data set. The standard deviation calculation formula is: ； Among them, S i is the standard deviation of the i-th data, X ij is the jth data point of the i-th data type, For X i The average value of the data, on is the total number of data points; Based on the outlier-filtered data set, the data is transformed by subtracting the mean from each data point and dividing by the standard deviation to generate normalized preprocessed data.

3. The method for automatic control of the environment in a breeding house according to claim 1, characterized in that: The steps for obtaining the environmental difference value set and the energy difference value set are as follows: Based on the preprocessed data, temperature values, humidity values, carbon dioxide concentration values, electricity consumption values, water resource consumption values, and feed consumption values are selected to obtain a standardized data set; Based on the standardized data set, the difference between the target value and the target value is calculated using the following formula: ； in, is the temperature difference, is the humidity difference, is the carbon dioxide difference, , , are the target temperature value, target humidity value and target carbon dioxide concentration value respectively. , , are temperature, humidity and carbon dioxide concentration values; Based on the temperature difference, humidity difference and carbon dioxide difference, the differences between the electricity, water resources and feed consumption values and the target values are further calculated to form an environmental difference set and an energy difference set.

4. The method for automatic control of the environment in a breeding house according to claim 1, characterized in that: The steps for obtaining the control parameters are: Performing a weighted operation based on the environmental difference value set and the energy difference value set to generate a weighted difference value set; According to the weighted difference, a multi-objective optimization function is established, and the formula is: ； in, and are the weight coefficients of environmental difference and energy difference, and represent the measured values of the i-th environmental parameter and the j-th resource parameter, respectively. and are the target values of the i-th environmental parameter and the j-th resource parameter, qn is the total number of environmental parameters, and m is the total number of resource parameters; Solving multi-objective optimization functions , and obtain the control parameters.

5. The method for automatic control of the environment in a breeding house according to claim 1, characterized in that: Based on the control parameters, the operating parameters of the heating device, the cooling device, the ventilation device and the humidifying device are adjusted, and the specific steps of setting the temperature setting value of the heating device, the temperature setting value of the cooling device, the wind speed setting value of the ventilation device and the humidity setting value of the humidifying device are as follows: Obtain control parameters from the multi-objective optimization function, adjust the operating parameters of the heating equipment, cooling equipment, ventilation equipment, and humidification equipment, and obtain updated equipment parameter settings; Setting a temperature setting value of a heating device and a temperature setting value of a cooling device based on the updated device parameter settings; Continue to use the updated device parameter settings to adjust the wind speed set point of the ventilation device and the humidity set point of the humidification device.

6. The method for automatic control of the environment in a breeding house according to claim 1, characterized in that: The steps for obtaining the equipment energy consumption dataset are as follows: Real-time collection of start and stop time values and operating power values of heating equipment, cooling equipment, ventilation equipment, and humidification equipment to obtain the original operating data set; Based on the original operation data set, the cumulative operation time and cumulative energy consumption value of each device are calculated using the following formula: ； in, is the total energy consumption of device i, is the operating power of device i in the jth time period, is the running time of device i in the jth time period, is the energy efficiency adjustment coefficient, n is the total number of time periods during which the equipment is running during the target calculation period; Based on the total energy consumption, an equipment energy consumption data set is collated and formed.

7. The method for automatic control of the environment in a breeding house according to claim 1, characterized in that: The specific steps of analyzing the equipment energy consumption data set, identifying high-energy-consuming equipment and high-energy-consuming operation modes, and adjusting the start and stop time values and operating power values of the high-energy-consuming equipment are as follows: Analyze the equipment energy consumption data set, compare the energy consumption of each device with the industry standard energy consumption through operating power and time data, identify high-energy-consuming devices, and obtain a list of high-energy-consuming devices; Based on the list of high-energy-consuming equipment, use statistical methods to analyze the relationship between operating time and energy consumption, extract energy consumption optimization points, and generate an optimization suggestion list; According to the optimization suggestion list, modify the start and stop times and operating power values of high-energy-consuming equipment.

8. An automated control system for the automated control method for the internal environment of a breeding house according to any one of claims 1 to 7, characterized in that: include: The environmental monitoring and adjustment module collects temperature, humidity, and carbon dioxide concentration values through sensors in the breeding house, performs noise filtering, performs data normalization, and calculates the difference between temperature, humidity, and carbon dioxide concentration and the target values to obtain an environmental difference data set; The energy consumption optimization module collects power consumption values, water resource consumption values, and feed consumption values based on the environmental difference data set, calculates the difference between the power target value, water resource target value, and feed target value, performs weighted operations, establishes a multi-objective optimization function, solves the multi-objective optimization function, and obtains the adjusted control parameter set; The equipment energy consumption management module adjusts the operating parameters of the heating equipment, cooling equipment, ventilation equipment and humidification equipment based on the adjusted control parameter set, collects equipment operation data in real time, records the start and stop time values and operating power values, calculates the cumulative operating time and energy consumption, obtains the equipment energy consumption data set, analyzes the energy-consuming equipment, and adjusts the start and stop time and operating power.

Images