Self-adaptive hydraulic balance adjusting method and device based on meteorological element collaboration

Abstract

The invention discloses a self-adaptive hydraulic balance adjusting method and device based on meteorological element collaboration, and the method comprises the steps: obtaining the operation data and meteorological element data of a regional heat supply system, including the return water temperature, circulating pump frequency, valve opening and outdoor temperature information of each unit; preprocessing the acquired data information, eliminating abnormal data by adopting a Pauta method, and supplementing missing data by using a Lagrange interpolation method to ensure the integrity and continuity of the data; constructing a meteorological element collaborative adaptive fuzzy control model, and performing hydraulic balance regulation and control by adopting an adaptive optimization algorithm; in a regional heat supply system, a meteorological element cooperative control algorithm is adopted to adjust the opening degree of a valve of each unit in real time, it is ensured that the return water temperature of each unit tends to be consistent, and hydraulic balance is achieved; the effect of a meteorological element cooperative control algorithm is evaluated according to an experimental result, indoor temperature balance of a user is controlled, and a small-flow and large-temperature-difference operation mode is achieved by adjusting the frequency of a circulating pump.

Description

Technical Field

[0001] The present invention relates to the field of district heating technology, and in particular to a secondary network adaptive hydraulic balance method and device based on meteorological element coordination, which is suitable for hydraulic balance regulation of the secondary network in a district heating system, improving user comfort and achieving energy conservation and emission reduction. Background Art

[0002] With the development of society and the continuous improvement of technology, winter heating basically adopts the secondary network heating method of heat exchange station. The distribution of the secondary pipe network is complex. The indoor temperature of users close to the outlet of the heat exchange station is often high, while the indoor temperature of users far away is low, which seriously affects the comfort of users. At the same time, in order to reduce the user complaint rate, the heating company has to increase the frequency of the circulation pump of the heat exchange station to meet the indoor temperature requirements of remote users, causing nearby users to open windows to dissipate heat, which greatly wastes energy. One of the important factors that cause uneven indoor temperature of users is the hydraulic balance problem of the heating pipe network. Therefore, how to solve the hydraulic imbalance of the secondary network has become a research hotspot in the heating field in recent years.

[0003] The existing hydraulic balance adjustment methods have the following limitations: the traditional return water temperature method relies on preset fixed parameters (such as valve opening threshold, temperature difference threshold), cannot perceive dynamic parameters such as pipe network pressure distribution and heat load fluctuation in real time, and lacks data interaction and coordination mechanism between various regulating valves. In addition, the existing methods have high requirements on valve performance, which increases cost investment; the existing methods do not consider the impact of sudden changes in outdoor temperature on the balance of the secondary network, resulting in untimely and inaccurate control, which in turn leads to the inability to effectively solve the hydraulic imbalance problem. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention discloses an adaptive hydraulic balance adjustment method based on the coordination of meteorological elements, which specifically includes the following steps:

[0005] Obtain the operation data and meteorological element data of the district heating system, including the return water temperature, circulation pump frequency, valve opening and outdoor temperature information of each unit;

[0006] The acquired data information is preprocessed, the Raida method is used to eliminate abnormal data, and the Lagrange interpolation method is used to supplement the missing data to ensure the integrity and continuity of the data;

[0007] Construct an adaptive fuzzy control model for the coordination of meteorological elements;

[0008] Adopt adaptive optimization algorithm for hydraulic balance control;

[0009] In the district heating system, the meteorological elements coordinated control algorithm is used to adjust the opening of each unit valve in real time to ensure that the return water temperature of each unit is consistent and hydraulic balance is achieved;

[0010] Evaluate the effect of the meteorological element collaborative control algorithm according to the experimental results, control the indoor temperature of the user to be balanced, and realize the operation mode of small flow rate and large temperature difference by adjusting the frequency of the circulation pump.

[0011] Furthermore, construct an adaptive fuzzy control model for meteorological element collaboration, and the process includes:

[0012] Determine the input variables: the return water temperature (T rw ) and the outdoor temperature (T out );

[0013] Determine the output variable: the valve opening adjustment amount (ΔV rw );

[0014] Design fuzzy sets and membership functions, and define the fuzzy sets of the input and output;

[0015] Formulate fuzzy control rules, and determine the adjustment strategy of the valve opening based on the dynamic collaborative relationship between the return water temperature and meteorological elements;

[0016] Adopt the Mamdani inference mechanism for fuzzy inference, and perform defuzzification through the centroid method to generate specific valve opening adjustment instructions.

[0017] Furthermore, when constructing an adaptive fuzzy control model for meteorological element collaboration:

[0018] Determine the fuzzy sets of the input variables and output variables. The fuzzy set of the return water temperature is {VL, L, M, H, VH}, the fuzzy set of the outdoor temperature is {VL, L, M, H, VH}, and the fuzzy set of the valve opening adjustment amount is {RR, R, N, I, II};

[0019] Formulate fuzzy control rules, and determine the adjustment strategy of the valve opening based on different combinations of the return water temperature and the outdoor temperature;

[0020] Adopt the Mamdani inference mechanism for fuzzy inference, and perform defuzzification through the centroid method to generate specific valve opening adjustment instructions.

[0021] Furthermore, when using the adaptive optimization algorithm for hydraulic balance regulation: Obtain the meteorological element change data in real time, judge whether collaborative control adjustment is required. If adjustment is required, then transfer the values of the meteorological elements and the return water temperature to the fuzzy controller, calculate a set of optimal valve opening adjustment instructions in combination with the collaborative control strategy, and transfer them to the controlled system to adjust the return water temperature, so that the return water temperature of each valve reaches the expected value, and realize the hydraulic balance adjustment of the system.

[0022] Further, read the database of the district heating system to obtain the real-time data of the return water temperature and the circulating pump frequency of each unit; read the meteorological database to obtain the outdoor temperature data to ensure the real-time and collaborative nature of the data; temporarily store the collected data in the local buffer for subsequent processing.

[0023] An adaptive hydraulic balance adjustment device based on meteorological element collaboration, comprising:

[0024] A data acquisition module for obtaining real-time data information of the return water temperature, outdoor temperature and circulating pump frequency of each unit from the district heating system;

[0025] A data preprocessing module for detecting abnormal data and filling in missing data in the collected data information to ensure the integrity and continuity of the data;

[0026] An adaptive optimization module for obtaining the change of outdoor temperature in real time and judging whether fuzzy control adjustment is needed;

[0027] A fuzzy control module for constructing a fuzzy controller, designing fuzzy sets and membership functions, formulating fuzzy control rules, and generating valve opening adjustment instructions through fuzzy inference;

[0028] A control execution module for receiving the adjustment instruction and controlling the valve opening to ensure that the return water temperatures of each unit tend to be consistent.

[0029] A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the adaptive hydraulic balance adjustment method based on meteorological element collaboration are implemented.

[0030] A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the steps of the adaptive hydraulic balance adjustment method based on meteorological element collaboration are implemented.

[0031] Due to the adoption of the above technical solution, an adaptive hydraulic balance adjustment method and device based on meteorological element collaboration provided by the present invention significantly improve the adaptability of the system to complex environmental changes through the dynamic collaboration of meteorological parameters and outdoor temperature; based on the fuzzy control method, it can effectively cope with the dynamic changes during the operation of the system, such as the known pipe network pressure distribution, heat load fluctuation, etc., and solve the problem that the traditional return water temperature method depends on preset fixed parameters, resulting in coexistence of local overshoot and global imbalance; by adopting an adaptive algorithm, the adaptability can dynamically monitor the change of outdoor temperature, making the regulation more accurate and timely. Description of the Drawings

[0032] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0033] Figure 1 Flow chart of the adaptive hydraulic balance adjustment method based on meteorological element coordination of the present invention

[0034] Figure 2 The data processing flow chart of the method of the present invention is

[0035] Figure 3 The structure diagram of the adaptive fuzzy control model in the method of the present invention is

[0036] Figure 4 The flowchart of the adaptive optimization algorithm in the method of the present invention is

[0037] Figure 5 Schematic diagram of the installation of the regulating valve in the method of the present invention

[0038] Figure 6 Schematic diagram of the installation of the hydraulic balance control device of the regional heating system in the method of the present invention DETAILED DESCRIPTION

[0039] In order to make the technical solutions and advantages of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention:

[0040] like Figure 1 The method for adaptive hydraulic balance regulation based on meteorological element coordination shown in the figure specifically comprises the following steps:

[0041] S1: Obtaining the operating data and meteorological element data of the regional heating system, obtaining the operating data and meteorological element data of the regional heating system, including but not limited to the return water temperature, circulation pump frequency, valve opening, outdoor temperature and other data of each unit.

[0042] S2: Preprocess the raw data obtained from S1, use the Laida method to eliminate abnormal data, and use the Lagrange interpolation method to supplement the missing data to ensure the integrity and continuity of the data.

[0043] S3: Construct an adaptive fuzzy control model for coordinated meteorological elements, determine the input variables (return water temperature and outdoor temperature) and output variables (valve opening adjustment), design fuzzy sets and membership functions, formulate fuzzy control rules, and determine the valve opening adjustment strategy based on the dynamic coordinated relationship between return water temperature and multiple meteorological elements.

[0044] S4: Introduce an adaptive optimization algorithm to obtain the changing data of meteorological elements in real time and determine whether collaborative control adjustment is required. If adjustment is needed, transfer the values of multiple meteorological elements and the return water temperature to the fuzzy controller. Combining with the collaborative control strategy, calculate a set of optimal valve opening adjustment instructions, transfer them to the controlled system, and adjust the return water temperature to make the return water temperature of each valve reach the expected value, realizing the hydraulic balance adjustment of the system.

[0045] S5: Implement the meteorological element collaborative control algorithm in the district heating system, adjust the opening of each unit valve in real time, ensure that the return water temperature of each unit tends to be consistent, and achieve hydraulic balance.

[0046] S6: According to the experimental results, evaluate the effect of the meteorological element collaborative control algorithm, ensure the balance of the indoor temperature of users, and realize the operation mode of small flow and large temperature difference by adjusting the frequency of the circulation pump, further saving electric energy.

[0047] Steps S1 / S2 / S3 / S4 / S5 / S6 are executed sequentially;

[0048] Furthermore, the process of obtaining the sample data is as follows:

[0049] S11: Connect to the database of the district heating system to obtain real-time data such as the return water temperature and the frequency of the circulation pump of each unit.

[0050] S12: Connect to the meteorological database to obtain outdoor temperature data to ensure the real-time and collaborative nature of the data.

[0051] S13: Temporarily store the collected data in the local buffer for subsequent processing.

[0052] Furthermore, perform data processing on the sample data. The data processing flow chart is as Figure 2 shown, and the process is as follows:

[0053] S21: Perform preprocessing on the data, and use the method of Leida (3σ criterion) to detect and remove abnormal data.

[0054] S22: For the missing data that exists after abnormal data processing or originally, use the Lagrange interpolation method to fill it.

[0055] S23: Standardize the data to ensure that the dimensions and physical meanings of the input variables are consistent, and avoid failures of the model due to data dimension problems.

[0056] Furthermore: Construct an adaptive fuzzy control model. The structure diagram of the fuzzy controller is as Figure 3 , and the process is as follows:

[0057] S31: Determine the fuzzy sets of the input variables and output variables. The fuzzy set of the return water temperature is {VL, L, M, H, VH}, the fuzzy set of the outdoor temperature is {VL, L, M, H, VH}, and the fuzzy set of the valve opening adjustment amount is {RR, R, N, I, II}.

[0058] S32: Formulate fuzzy control rules, and determine the adjustment strategy of the valve opening based on different combinations of the return water temperature and the outdoor temperature.

[0059] S33: Conduct fuzzy inference using the Mamdani inference mechanism, and perform defuzzification by the centroid method to generate specific valve opening adjustment instructions.

[0060] Furthermore: Introduce an adaptive optimization algorithm to optimize the fuzzy controller. The flowchart of the adaptive algorithm is as Figure 4 shown, and the specific steps are as follows:

[0061] S41: Obtain the meteorological element change data in real time, and determine whether collaborative control adjustment is required.

[0062] S42: If adjustment is required, transfer the values of the meteorological elements and the return water temperature to the fuzzy controller, and calculate a set of optimal valve opening adjustment instructions in combination with the collaborative control strategy.

[0063] S43: Transfer the adjustment instructions to the controlled system to adjust the return water temperature, so that the return water temperature of each valve reaches the expected value, and realize the hydraulic balance adjustment of the system.

[0064] Furthermore: Implement the adaptive fuzzy control algorithm in the district heating system, and adjust the opening of each unit valve in real time to ensure that the return water temperature of each unit tends to be consistent and realize hydraulic balance. The specific steps are as follows:

[0065] S51: Install intelligent regulating valves in the district heating system, as Figure 5 shown, and collect the return water temperature of each unit in real time, Figure 5 which is the installation schematic diagram of the regulating valve.

[0066] S52: According to the adaptive fuzzy control algorithm, adjust the opening of each unit valve in real time to ensure that the return water temperature of each unit tends to be consistent.

[0067] S53: By adjusting the frequency of the circulating pump, realize the operation mode of small flow and large temperature difference, and further save electric energy.

[0068] Furthermore: According to the experimental results, evaluate the effect of the adaptive fuzzy control algorithm, ensure the balance of the indoor temperature of users, and realize the operation mode of small flow and large temperature difference by adjusting the frequency of the circulating pump, and further save electric energy.

[0069] As Figure 6A hydraulic balance control device for a district heating system, comprising

[0070] A data acquisition module: used to obtain real-time data such as the return water temperature, outdoor temperature, and circulation pump frequency of each unit from the district heating system.

[0071] A data preprocessing module: used to detect abnormal data and fill in missing data for the collected raw data to ensure the integrity and continuity of the data.

[0072] An adaptive optimization module: used to obtain the change in outdoor temperature in real time and determine whether fuzzy control adjustment is required.

[0073] A fuzzy control module: used to construct a fuzzy controller, design fuzzy sets and membership functions, formulate fuzzy control rules, and generate valve opening adjustment instructions through fuzzy inference.

[0074] A control execution module: receives the adjustment instruction, controls the valve opening, and ensures that the return water temperatures of each unit tend to be consistent.

[0075] A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the adaptive hydraulic balance adjustment method based on meteorological element collaboration are implemented.

[0076] A computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the steps of the adaptive hydraulic balance adjustment method based on meteorological element collaboration are implemented.

[0077] As mentioned above, it is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. An adaptive hydraulic balance adjustment method based on meteorological element collaboration, characterized in that Including: Obtain the operation data of the district heating system and meteorological element data, including the return water temperature, circulating pump frequency, valve opening degree and outdoor temperature information of each unit; Preprocess the obtained data information, eliminate abnormal data by the method of Pauta criterion, and supplement missing data by the Lagrange interpolation method to ensure the integrity and continuity of the data; Construct an adaptive fuzzy control model coordinated with meteorological elements; Adopt an adaptive optimization algorithm for hydraulic balance regulation; In the district heating system, adopt a meteorological element coordinated control algorithm to adjust the opening degree of each unit valve in real time, ensure that the return water temperature of each unit tends to be consistent, and achieve hydraulic balance; Evaluate the effect of the meteorological element coordinated control algorithm according to the experimental results, control the balance of the indoor temperature of users, and realize the operation mode of small flow and large temperature difference by adjusting the circulating pump frequency.

2. The adaptive hydraulic balance adjustment method based on meteorological element collaboration according to claim 1, wherein: Construct an adaptive fuzzy control model coordinated with meteorological elements, and the process includes: Determine the input variables: the return water temperature (T rw ) of the valve and the outdoor temperature (T out ); Determine the output variable: valve opening adjustment amount (ΔV rw ); Design fuzzy sets and membership functions, and define the fuzzy sets of inputs and outputs; Formulate fuzzy control rules, and determine the adjustment strategy of the valve opening degree based on the dynamic coordination relationship between the return water temperature and meteorological elements; Adopt the Mamdani inference mechanism for fuzzy inference, and perform defuzzification by the centroid method to generate specific valve opening degree adjustment instructions.

3. The adaptive hydraulic balance adjustment method based on meteorological element collaboration according to claim 2, characterized in that: When constructing an adaptive fuzzy control model coordinated with meteorological elements: Determine the fuzzy sets of input variables and output variables. The fuzzy set of the return water temperature is {VL, L, M, H, VH}, the fuzzy set of the outdoor temperature is {VL, L, M, H, VH}, and the fuzzy set of the valve opening degree adjustment amount is {RR, R, N, I, II}; Formulate fuzzy control rules, and determine the adjustment strategy of the valve opening degree based on different combinations of the return water temperature and the outdoor temperature; Adopt the Mamdani inference mechanism for fuzzy inference, and perform defuzzification by the centroid method to generate specific valve opening degree adjustment instructions.

4. A self - adaptive hydraulic balance adjustment method based on meteorological element collaboration according to claim 1, characterized in that: When adopting an adaptive optimization algorithm for hydraulic balance regulation: Obtain the change data of meteorological elements in real time, judge whether coordinated control adjustment is needed. If adjustment is needed, transfer the values of meteorological elements and the return water temperature to the fuzzy controller, calculate a set of optimal valve opening degree adjustment instructions in combination with the coordinated control strategy, and transfer them to the controlled system to adjust the return water temperature, so that the return water temperature of each valve reaches the expected value and realize the hydraulic balance adjustment of the system.

5. The adaptive hydraulic balance adjustment method based on meteorological element collaboration according to claim 1, wherein: Read the database of the district heating system to obtain the real-time data of the return water temperature and circulating pump frequency of each unit; read the meteorological database to obtain the outdoor temperature data to ensure the real-time and coordination of the data; temporarily store the collected data in the local buffer for subsequent processing.

6. An adaptive hydraulic balance adjustment device based on meteorological element collaboration, characterized in that Including: A data acquisition module for obtaining the real-time data information of the return water temperature, outdoor temperature and circulating pump frequency of each unit from the district heating system; A data preprocessing module for detecting abnormal data and filling missing data in the collected data information to ensure the integrity and continuity of the data; An adaptive optimization module for obtaining the change of outdoor temperature in real time and judging whether fuzzy control adjustment is needed; The fuzzy control module is used to construct a fuzzy controller, design fuzzy sets and membership functions, formulate fuzzy control rules, and generate valve opening adjustment instructions through fuzzy inference; The control execution module receives the adjustment instructions, controls the valve opening, and ensures that the return water temperatures of all units tend to be consistent.

7. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, the steps of an adaptive hydraulic balance adjustment method based on meteorological element collaboration as described in any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, the steps of an adaptive hydraulic balance adjustment method based on meteorological element collaboration as described in any one of claims 1 to 5 are implemented.

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