Energy-saving control method and system for heating circulating pump

Abstract

The invention discloses an energy-saving control method and system for a heating circulating pump, and relates to the technical field of heating ventilation air conditioning and building energy conservation, in particular to the energy-saving control method and system for the heating circulating pump. Calculating the current actual thermal load demand of the system based on the temperature parameter, and comparing the current actual thermal load demand with a preset reference load curve to generate an initial target rotating speed instruction; meanwhile, whether the system is in a hydraulic unbalance state or not is judged according to the pressure parameters, if unbalance exists, the initial rotating speed instruction is corrected according to a pressure deviation-rotating speed compensation rule, a final target rotating speed instruction is obtained, and then the rotating speed of the circulating pump is adjusted. The system comprises a parameter acquisition module, a central processing unit and a variable frequency driving module. Through dual adjustment of the thermal load and the hydraulic state, precise control over the rotating speed of the circulating pump is achieved, and energy consumption is effectively reduced while the heating effect is guaranteed.

Description

Technical Field

[0001] This invention relates to the field of heating, ventilation, air conditioning and building energy conservation technology, specifically to an energy-saving control method and system for a heating circulation pump. Background Technology

[0002] Heating systems are a significant component of building energy consumption, with circulating pumps, as key equipment driving the circulation of the heat medium, accounting for a substantial portion of energy consumption. Traditional heating circulating pumps often employ fixed-speed operation or simple frequency conversion control based on a single parameter (such as the supply and return water pressure difference or temperature). While these methods achieve energy savings to some extent, they still have significant drawbacks: 1. Limited energy-saving effect and prone to hydraulic imbalance: Control based solely on the main pipe pressure difference or temperature cannot accurately reflect the real-time heat load demand of the system. To meet the heating effect of the most unfavorable loop (usually the heat dissipation unit farthest from the pump), the system often operates at high pressure difference and flow rate, resulting in excessively high available head in most near-end branches, requiring throttling through valves, causing a large amount of energy wasted on hydraulic imbalance. This "high flow rate, small temperature difference" operating mode not only keeps the pump's energy consumption high but also reduces the overall thermal efficiency of the system.

[0003] Control lag and poor adaptability: Control strategies based on fixed setpoints cannot cope with building thermal inertia, changes in outdoor weather, and dynamic heat load fluctuations caused by user behavior. System response lag either leads to room temperature fluctuations or results in prolonged operation at excessively high temperatures for the sake of stability, sacrificing energy-saving potential.

[0004] Lack of intelligent system state diagnosis and optimization: Existing control methods passively respond to parameter changes but cannot proactively diagnose whether the system is in an optimal operating state. For example, the system cannot determine on its own whether there is energy-saving potential due to changes in valve opening or pipeline resistance characteristics under the current heat load.

[0005] To overcome these problems, some improved control strategies have emerged in recent years, such as adjusting water temperature or pump speed based on outdoor temperature compensation. However, these strategies still focus primarily on the heat load side and fail to deeply integrate the regulation of the heating and hydraulic sides. They also lack effective online identification and dynamic compensation mechanisms for hydraulic imbalances within the system, resulting in the circulation pump's operating efficiency not reaching its optimal level. Summary of the Invention

[0006] The purpose of this invention is to provide an energy-saving control method and system for a heating circulation pump. By real-time monitoring of the system's heat load and hydraulic status, a two-factor dynamic adjustment is performed, and a periodic disturbance and load prediction mechanism is introduced to achieve precise on-demand heating, thereby minimizing pumping energy consumption while ensuring heating comfort.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an energy-saving control method and system for a heating circulating pump, comprising the following steps: The system collects temperature and pressure parameters from multiple key nodes in the heating system in real time. These key nodes include at least the heat source outlet, the supply and return water points of the system's furthest heat dissipation unit, and representative branch connection points located in the middle of the pipe network. The data collection process employs a timestamped synchronous measurement technique to ensure data consistency over time, providing a reliable foundation for subsequent analysis. Based on the temperature parameters, the current actual heat load demand of the system is calculated. This calculation process takes into account dynamic factors such as sudden changes in outdoor temperature and differences in heat consumption in different building areas, ensuring the real-time performance and accuracy of the heat load assessment. The actual heat load demand is compared with the preset reference load curve to generate an initial target speed command. The reference load curve is not fixed, but is periodically revised according to building type, historical operating data and user comfort feedback to make it more in line with actual needs. Based on the pressure parameters, it is determined whether the system is in a state of hydraulic imbalance; if imbalance exists, the initial target speed command is corrected according to the preset pressure deviation-speed compensation rule to generate the final target speed command; this judgment and correction process is repeated at a frequency of seconds to achieve rapid response to hydraulic conditions. According to the final target speed command, the operating speed of the circulating pump is adjusted; the speed adjustment is performed by a high-precision frequency converter to ensure that the flow supply is precisely matched with the actual needs of the system and to avoid energy waste caused by excessive circulation.

[0008] Furthermore, the specific steps for "calculating the current actual heat load demand of the system" include: using the return temperature of the furthest heat dissipation unit as the main feedback quantity, and combining it with the total supply and return water temperature difference, calculating the equivalent circulation flow rate required to maintain the set indoor temperature through a preset thermodynamic model, and converting it into a heat load demand value; the thermodynamic model fully considers the heat loss of the pipe network, the heat transfer characteristics of different pipe sections, and the impact of user-side adjustment behavior on the return water temperature, making the flow rate equivalent calculation more accurate; during the conversion process, correction coefficients for the specific heat capacity and density of the heating medium as a function of temperature are also introduced to further improve the calculation accuracy of the heat load demand value.

[0009] Furthermore, the basis for "determining whether the system is in a state of hydraulic imbalance" is as follows: monitoring the available pressure difference of at least two representative branches in the system; when the available pressure difference deviates from its preset threshold by more than a certain percentage and persists for a certain period of time, it is determined to be a hydraulic imbalance; the selection of representative branches needs to cover the near end, middle and far end of the system to comprehensively reflect the pressure distribution of the pipeline network; the limited percentage is dynamically set according to the design resistance characteristics of the branch, and a stricter percentage is used for resistance-sensitive branches; the certain period of time is used to filter out pressure fluctuations caused by brief adjustments of user valves, and is usually set to 5-15 minutes to improve the stability and reliability of the judgment.

[0010] Furthermore, the "pressure deviation-speed compensation rule" is as follows: when the available pressure difference of a certain branch is detected to be lower than the threshold, the initial target speed command is appropriately increased; the increase is positively correlated with the degree of loss of available pressure difference of the branch, but there is an upper limit to avoid the speed increasing too quickly; when the available pressure difference is higher than the threshold, the initial target speed command is appropriately reduced on the premise of satisfying the pressure difference at the most unfavorable point; the speed reduction process adopts a step-by-step slow reduction strategy, and after each adjustment, it is necessary to confirm that the pressure difference at the most unfavorable point is still higher than the lower limit of safe operation to ensure that the speed reduction will not cause new hydraulic imbalance problems.

[0011] Furthermore, it also includes a periodic disturbance adjustment step: during stable system operation, a small, brief negative disturbance is applied to the circulating pump speed at fixed time intervals, while monitoring the pressure change at the most unfavorable point; the disturbance amplitude is usually 2%-5% of the current speed, and the duration is controlled within 1-3 cycles; if the pressure change is not sensitive, that is, the pressure drop at the most unfavorable point does not reach the alarm threshold, it is determined that there is room for further speed reduction and energy saving in the system; this determination result will be fed back to the control logic for dynamic optimization of the reference load curve, specifically, under the same operating conditions in the future, the initial target speed corresponding to the reference load curve will be appropriately reduced.

[0012] Furthermore, the parameter acquisition module consists of temperature sensors and pressure sensors arranged at key nodes of the heating pipeline network, used to acquire the temperature and pressure parameters in real time; all sensors have moisture-proof, anti-interference and self-diagnostic functions, and their output signals are transmitted to the central processing unit after being processed by an isolation transmitter. The central processing unit, with its built-in memory and processor, is configured to execute the control logic as described in any one of claims 1 to 5 and generate a final target speed command; the unit is also equipped with a watchdog circuit to prevent the program from running away and to ensure the continuous and stable operation of the control system. The variable frequency drive module receives the final target speed command and drives the circulating pump motor to run at the corresponding speed. The module has soft start, overcurrent and overload protection functions, and its output frequency resolution is not less than 0.01Hz to ensure the accuracy of speed control.

[0013] Furthermore, the central processing unit also includes a load prediction submodule. This submodule predicts the trend of heat load changes based on the thermal inertia of the building envelope and short-term weather forecast data, and adjusts the baseline load curve accordingly. The prediction model comprehensively considers the building's thermal parameters, historical energy consumption data, and forecasts of temperature, wind speed, and solar radiation intensity for the next few hours. It generates a predicted heat load curve through a weighted algorithm, thereby achieving feedforward control of the circulating pump speed and reducing adjustment lag caused by external weather changes.

[0014] Furthermore, the system also includes a manual optimization interface, allowing operators to calibrate and fine-tune the preset baseline load curve and pressure threshold based on actual operating experience. This interface provides a graphical user interface that can intuitively display the current settings and system operating effects, and record all manual modification logs. Fine-tuning permissions are managed hierarchically, and modifications to key parameters require double confirmation to prevent accidental operations from affecting system safety.

[0015] Furthermore, the parameter acquisition module includes a virtual sensor calculation unit. This unit uses data measured by a limited number of physical sensors deployed in the pipeline network to calculate the temperature and pressure values ​​at locations where sensors are not directly installed, through a fluid dynamics calculation model. The fluid dynamics model is constructed based on the pipeline network topology, pipe diameter, local resistance coefficient, etc., and is solved in real time using the finite element method. The calculation results are used to supplement the data in the monitoring blind area, providing a more comprehensive basis for hydraulic condition judgment and reducing the dependence on the number of sensors deployed.

[0016] Furthermore, the operation logs generated by the system, including heat load curves, speed commands, energy consumption data, and hydraulic state assessment results, can be exported through a data interface to generate energy efficiency analysis reports. The log data is stored in a standard format and supports filtering and statistics by time interval, operating mode, etc. The energy efficiency analysis report can automatically calculate key performance indicators such as energy savings, system energy efficiency ratio, and hydraulic stability index, providing data support for operation management and energy-saving renovation.

[0017] This invention provides an energy-saving control method and system for a heating circulation pump, which has the following beneficial effects: 1. Achieve synergistic optimization of thermal and hydraulic balance to improve the overall energy efficiency of the system. This invention calculates actual heat load demand in real time and generates initial speed commands accordingly. This ensures that the heating capacity of the circulating pump matches the building's heat demand, avoiding energy waste caused by traditional methods that rely solely on a single temperature or fixed temperature difference control. More importantly, the system innovatively introduces a mechanism for judging and compensating for hydraulic imbalance. When abnormal pressure differences are detected in system branches, the pump speed is dynamically adjusted. This collaborative control strategy not only guarantees sufficient heat delivery but also actively maintains the hydraulic stability of the pipe network, effectively solving problems such as overheating of nearby users and insufficient heating of distant users caused by hydraulic imbalance. While meeting comfort requirements, it unlocks deep energy-saving potential at the system level, achieving an overall leap in energy efficiency.

[0018] Significantly enhances the system's adaptability to complex operating conditions and ensures stable heating quality. Traditional circulating pump control methods often exhibit sluggish response to dynamic hydraulic conditions caused by user adjustments and valve opening changes within the system, easily leading to pressure fluctuations and temperature unevenness. This invention, by continuously monitoring pressure parameters at key nodes, can quickly identify hydraulic imbalances caused by these factors. It then intervenes precisely based on preset pressure deviation-speed compensation rules, such as increasing the speed when the branch pressure differential is insufficient to ensure the available pressure head of the most unfavorable loop. This proactive and preventative control logic significantly enhances the heating system's ability to resist internal disturbances, ensuring that the heat medium is stably and reliably delivered to all terminals under any operating condition, thereby significantly improving the uniformity and stability of heating quality and preventing localized overheating or undercooling.

[0019] By continuously exploring energy-saving potential through active detection technology, dynamic optimization of energy efficiency can be achieved. The periodic disturbance adjustment step included in this invention is a highly forward-looking energy efficiency optimization method. During stable system operation, a small negative speed disturbance is actively applied, and the pressure change at the most unfavorable point is observed. Essentially, this is an online "diagnosis" of the system's actual resistance characteristics. If the pressure change is not sensitive, it indicates that the current speed has redundancy, and the system has room to reduce speed. This mechanism enables the control system to move beyond relying solely on a preset, fixed baseline curve, and instead possess self-learning and dynamic optimization capabilities. It can automatically and safely adjust operating parameters downwards based on actual changes in pipeline characteristics (such as scaling, blockage, or valve status changes), thereby continuously identifying and utilizing new energy-saving opportunities, keeping the system's energy efficiency consistently close to optimal.

[0020] Integrating predictive functions enables proactive control, improving system operating economy and equipment lifespan. Through its built-in load prediction submodule, this system surpasses traditional feedback control. It combines the thermal inertia of the building envelope with short-term weather forecast data to predict future heat load trends and adjust the baseline load curve accordingly. This means that the circulation pump's speed regulation is no longer a completely passive response to temperature changes, but can act in advance for a smooth transition. This proactive control effectively mitigates frequent system starts and stops or large fluctuations caused by sudden changes in external temperature, further reducing energy consumption. More importantly, it alleviates the mechanical and electrical stress on key equipment such as pumps, motors, and pipe valves, significantly extending equipment lifespan, reducing maintenance costs, and improving the overall economic efficiency of the heating system in the long run.

[0021] Construct a closed-loop optimization and data analysis system to provide decision support for long-term system operation and maintenance. This invention constructs a complete closed loop from data acquisition and intelligent analysis to command execution and effect evaluation. The virtual sensor computing unit in the parameter acquisition module uses a limited number of physical measurement points to extrapolate other location parameters through a model, reducing hardware costs while ensuring comprehensive monitoring. The system-generated operation log records comprehensive data such as heat load, rotational speed, energy consumption, and hydraulic status, and can generate energy efficiency analysis reports. This provides valuable data support for operation and management personnel, enabling them to clearly understand the system's energy efficiency performance, identify abnormal trends, and perform targeted calibration of preset parameters. This design upgrades a one-time equipment installation into a sustainable energy efficiency management platform, effectively supporting the refined and data-driven operation and maintenance of the heating system, ensuring that energy-saving effects are maintained and continuously optimized over the long term. Attached Figure Description

[0022] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0023] Figure 1 This is the main control logic flowchart of the present invention; Figure 2 This is a flowchart illustrating the heat load calculation logic of the present invention. Figure 3 This is a flowchart of the hydraulic imbalance judgment and speed compensation logic of the present invention; Figure 4 This is a flowchart of the periodic disturbance adjustment logic of the present invention; Figure 5 This is a diagram showing the system module composition and data flow of the present invention. Detailed Implementation

[0024] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses consistent with some aspects of this disclosure as detailed in the appended claims.

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0026] How to use: I. System Startup and Initial Setup 1. Equipment Installation and Inspection: First, ensure that the variable frequency drive module of the circulating pump is correctly connected to the central processing unit. Next, install temperature and pressure sensors at key nodes of the heating system (such as the heat source outlet, the return pipe of the furthest radiator, and representative branches), and confirm that their signals can be stably transmitted to the central processing unit.

[0027] Preset parameters: Operators perform initial settings through the system's "manual optimization interface." This includes: Set a baseline load curve: Based on the building type, area, insulation performance, and desired indoor temperature, set a theoretical heat load demand curve corresponding to different outdoor temperatures as the initial baseline for system adjustment.

[0028] Set a pressure threshold: Set a normal available differential pressure range (i.e., a threshold) for selected representative branches in the system. This threshold should ensure sufficient circulating pressure is available even at the most unfavorable point (usually the furthest or highest heat dissipation point in the system).

[0029] Calibrate other rules: Initially set parameters such as the compensation range, the "limited percentage" for determining hydraulic imbalance, and the "duration time" in the "pressure deviation-speed compensation rule". These initial values ​​can be based on design drawings or historical experience data.

[0030] II. Daily Automated Operation Process After the system completes its initial setup, it can run automatically. Its daily operation follows a cyclical pattern of the following steps: 1. Data Acquisition: The parameter acquisition module works continuously, collecting temperature and pressure data from each key node in real time through physical sensors.

[0031] For locations where sensors are not directly installed, the virtual sensor computing unit will be activated to calculate the estimated temperature and pressure values ​​at these locations using existing physical sensor data and the built-in fluid dynamics model, thereby gaining a more comprehensive understanding of the system status.

[0032] Heat load calculation and initial determination of target speed: After receiving the temperature parameters, the central processing unit prioritizes the return temperature of the furthest heat dissipation unit in the system as the core basis, and then combines it with the temperature difference between the main supply and return water pipes. It then uses a preset thermodynamic model to calculate the actual heat load value required to maintain the set room temperature at the current moment.

[0033] The calculated actual heat load is compared with the preset reference load curve to generate a preliminary pump speed command (i.e., the initial target speed command) aimed at meeting the heat demand.

[0034] Hydraulic balance judgment and speed command correction: The central processing unit simultaneously analyzes pressure parameters. It continuously monitors the available differential pressure of each representative branch to determine whether it deviates from the preset threshold for an extended period.

[0035] If the system is hydraulically balanced, the initial target speed command will be used as the final command.

[0036] If the available pressure difference of a branch is detected to be lower than the threshold, it indicates that the flow of that branch may be insufficient. The system will appropriately increase the initial target speed command according to the "pressure deviation-speed compensation rule" to increase the total circulation pressure and improve the imbalance.

[0037] If the available pressure difference is detected to be higher than the threshold, and on the premise of ensuring sufficient pressure at the most unfavorable point, the system will appropriately reduce the initial target speed command to achieve energy saving.

[0038] Speed ​​Execution: The revised final target speed command is sent to the frequency converter drive module.

[0039] The variable frequency drive module drives the circulating pump motor to operate precisely at the required speed, thereby providing circulating power as needed.

[0040] III. Use of Optimization and Maintenance Functions 1. Periodic perturbations to explore energy-saving potential: When the system is running stably, the central processing unit will automatically perform periodic disturbance adjustment. It will briefly and slightly reduce the speed of the circulating pump at fixed intervals (such as every few hours).

[0041] Simultaneously, the system closely monitors pressure changes at the most unfavorable point. If the pressure change is not significant, it indicates that the current speed is redundant, and the system has room for further speed reduction and energy saving. Based on this, the central processing unit will automatically and dynamically optimize the reference load curve so that it can issue a lower initial speed command under similar operating conditions in the future.

[0042] Using load forecasting for forward-looking regulation: The system's built-in load forecasting submodule begins operation. This submodule combines the thermal inertia characteristics of the building envelope with short-term weather forecast data (e.g., the next few hours).

[0043] Based on this information, it predicts the trend of heat load changes. For example, if the forecast shows that the afternoon temperature will rise, the submodule will fine-tune (reduce) the baseline load curve in advance, so that the system can reduce the pump speed in advance and smoothly, avoiding energy waste caused by delayed response and achieving more refined energy saving.

[0044] Manual intervention and calibration: Operators can manually optimize the interface to check the system's operating status at any time. If, based on actual operating experience, the automatic control effect is found to be unsatisfactory (such as certain areas being chronically cold or hot), the preset baseline load curve, pressure threshold, and various compensation parameters can be manually fine-tuned to make the system more closely match the actual operating conditions.

[0045] Energy efficiency analysis and report generation: The system automatically records and generates detailed operation logs, including historical heat load curves, speed commands, energy consumption data, and hydraulic condition assessment results.

[0046] Operators regularly export this data through the data interface to generate energy efficiency analysis reports, assess energy-saving effects, and provide data support for long-term system optimization and preventive maintenance.

[0047] Example: Example 1: Application in energy-saving renovation of secondary pipe networks in old residential communities In a certain city, an old residential community built in the 1990s had a traditional vertical single-pipe downstream heating system, which suffered from severe horizontal and vertical misalignment. During energy-saving renovations, this heating circulation pump energy-saving control system was installed.

[0048] How to use: First, technicians installed temperature sensors on the main supply and return water pipes of the heating station and pressure sensors at the building's heating inlet. Specifically, when selecting the "farthest heat dissipation unit," a radiator located on the top floor at the end of the network was chosen, and a high-precision temperature sensor was installed on its return water pipe as a key feedback point. Simultaneously, differential pressure sensors were installed on the supply and return water sections of several representative risers in the middle and near ends of the system to monitor the "usable differential pressure." Through "manual optimization," operators, based on the original design drawings and past complaint records (such as the top floor and farthest rooms consistently lacking heat), set relatively conservative pressure thresholds for each branch and set the initial value of the baseline load curve slightly higher than the theoretical value to prioritize heating performance.

[0049] After the system is put into automatic operation, the central processing unit reads the return water temperature at the furthest point in real time. On a cold snap night, the outdoor temperature dropped sharply, and the system's calculated "actual heat load demand" increased, resulting in a higher "initial target speed command." However, almost simultaneously, the system detected that the "available pressure difference" of the branch representing the top-floor user rapidly decreased and fell below the preset threshold, triggering a hydraulic imbalance judgment. Based on the "pressure deviation-speed compensation rule," the system did not directly adopt the initial command but instead generated a higher "final target speed command," driving the circulation pump to speed up and rapidly increasing the overall system head. This ensured the circulating water volume for the furthest and top-floor users, avoiding the complaints that would inevitably occur in such weather conditions in the past. During the day, when there is sufficient sunshine and the temperature rises, the system automatically reduces the pump speed and initiates "periodic disturbance adjustment." After a brief, slight reduction in speed, it finds that the pressure at the most unfavorable point stabilizes, indicating that the demand has indeed decreased. Therefore, it dynamically optimizes the baseline load curve, allowing the pump speed to operate even lower during off-peak hours, achieving significant energy savings. Based on a week's worth of operational data and user feedback, the operators fine-tuned the pressure threshold through the "manual optimization interface" to bring the system to its optimal balance.

[0050] Example 2: Refined Control Applied to New Large-Scale Commercial Complexes A newly built large commercial complex has a vast building area and diverse internal functional areas (shopping mall, cinema, restaurants, offices), resulting in complex and highly variable heat load demands. This energy-saving control system was integrated into the design phase.

[0051] How to use: The sensor network deployment in this project is extremely comprehensive. Temperature and pressure data collection points have been set up at air conditioning units, underfloor heating manifolds, and representative areas of each major functional zone. The virtual sensor computing unit played a crucial role, using limited physical sensor data to calculate environmental parameters in areas with high pedestrian traffic where equipment cannot be directly installed (such as the central plaza), providing more comprehensive data support for load calculation.

[0052] During system operation, the load forecasting submodule plays a particularly prominent role. For example, on a weekend morning, the system, based on weather forecasts, anticipates a significant increase in foot traffic and enhanced sunlight in the afternoon. Taking into account the building's significant thermal inertia, the submodule predicts that although heating is currently needed due to low temperatures, the main heat sources will be internal personnel, lighting, and equipment heat dissipation a few hours later. Therefore, it preemptively adjusts (reduces) the "baseline load curve." When the actual foot traffic arrives in the afternoon, the system's calculated "actual heat load demand" does not increase significantly, and the pump speed remains at a low level. Conversely, before and after closing time, the forecasting submodule predicts a rapid decrease in heat load and preemptively instructs the pump speed to gradually decrease, avoiding overheating. Simultaneously, the system continuously monitors the hydraulic conditions between the catering area (closed at night) and the 24-hour operating equipment room area. Through dynamic speed compensation, it ensures pressure balance between different time periods and demand areas, achieving refined energy distribution on demand and by zone, with overall energy efficiency far exceeding national standards.

[0053] Example 3: Rapid Response and Energy Saving in Places with Intermittent Heating A university gymnasium only maintains heating for staff on non-competition or event days, but needs to be heated rapidly to a comfortable temperature on event days. Therefore, it places high demands on the system's response speed and energy efficiency.

[0054] How to use: To address the intermittent and abrupt nature of the load, the system's parameter settings prioritize rapid response and avoidance of wasted energy. Several hours before the event, the administrator presets the heating time using the system. The load prediction submodule, combining the building's thermal inertia model and the event duration, generates a "baseline load curve" that rises sharply, maintains its position, and then drops sharply again. At the start of the event, the system rapidly calculates the actual heat load demand based on temperature sensors installed at the return air vents in the seating area and on the underfloor heating return pipes, driving the pumps to run at high speed to achieve rapid heating.

[0055] Once the venue temperature reaches the set value, the system enters a "stable operation period." At this time, the "periodic disturbance adjustment" function begins to operate frequently (e.g., every 30 minutes). The system actively applies a small, brief negative speed disturbance and monitors the pressure changes of the furthest heat dissipation unit. Due to the large space of the stadium and the well-defined pipe network resistance characteristics, the system detects that the pressure change after a small speed reduction is extremely weak, thus determining that there is significant energy-saving potential. Therefore, it continuously and dynamically optimizes the "baseline load curve," causing the pump speed to decrease stepwise during the maintenance phase until the optimal speed point is found that ensures both uniform temperature in the stands and minimal energy consumption. After the event, the system quickly reduces the speed to the standby heating level. This active detection-based control strategy overcomes the energy waste caused by the lag in traditional temperature control, achieving a balance between rapid response and energy-saving operation.

[0056] Example 4: Solving the hydraulic imbalance of hot air curtain circulation in large industrial spaces A large industrial plant uses a combination of centralized heating and hot air curtains for heating. The hot air curtains start and stop frequently and have high power consumption. Their sudden start or stop can cause severe hydraulic shock to the entire heating circulation system, leading to instantaneous pressure loss or overpressure in radiators in other areas.

[0057] How to use: In this scenario, the core task of the system is to maintain hydraulic stability. Pressure sensors are strategically placed near the main pipe of the hot air curtain assembly and on representative branches in other areas of the plant. The system's preset pressure threshold range is relatively wide to absorb short-term shocks. When a large hot air curtain suddenly activates, its branch requires a huge flow rate instantaneously, causing a sharp decrease in the available pressure differential of that branch and resulting in a sharp drop in pressure on the main pipe. The system's pressure acquisition module immediately detects this change and determines it as a severe hydraulic imbalance.

[0058] Based on the "pressure deviation-speed compensation rule," the system makes a significant positive correction to the "initial target speed command" calculated from the room temperature within milliseconds, generating an extremely high "final target speed command." The variable frequency drive module drives the circulating pump to rapidly increase its speed, compensating for the pressure loss caused by the opening of the air curtain and ensuring the normal circulation of other radiators in the system. After the air curtain stabilizes, the system pressure gradually returns to equilibrium, and the speed smoothly decreases to a level matching the heat load. When the air curtain closes, the process is reversed; the system rapidly reduces its speed to avoid overpressure in the pipe network. This dynamic and rapid pressure compensation mechanism ensures the stability and reliability of the entire plant heating system when facing significant internal disturbances.

[0059] Example 5: Coordinated Control for Multi-Heat Source Networked Operation of Regional Energy Stations A regional energy station is responsible for heating a small town. The heat source includes a gas boiler and an industrial waste heat recovery device. The pipeline network is long and the users are diverse.

[0060] How to use: This system focuses on system-level optimization and data analysis. The central processing unit collects temperature and pressure data from dozens of key nodes across the entire pipeline network, while virtual sensor computing units fill data gaps in remote branches. Based on meteorological data and heat consumption patterns at different times (day / night), the system generates a dynamic "baseline load curve." Operators, through a "manual optimization interface," set priority for utilizing waste heat based on the price and supply stability of gas and waste heat. This indirectly affects the generation of speed commands (e.g., allowing for wider pump speed optimization when waste heat is abundant).

[0061] During system operation, when a persistently low pressure is detected in the remote pipeline network supplied by the waste heat source, the system does not simply increase the speed of the main circulating pump (which could overheat nearby users and waste energy). Instead, it uses a precise compensation method based on the "pressure deviation-speed compensation rule," and coordinates the operation of peak-shaving gas boilers through the networked control system when necessary to achieve optimal matching between the heat source and the transmission and distribution system. The daily "operation log" generated by the system is exported for weekly energy efficiency analysis reports. By analyzing heat load curves, energy consumption data, and hydraulic status assessment results, management personnel discovered a persistent slight hydraulic imbalance in a certain branch line. Based on this, preventative flushing and maintenance of the pipeline network were arranged, improving system energy efficiency from the source. This system achieves collaborative control and continuous optimization of a complex multi-heat-source networked system.

[0062] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An energy-saving control method and system for a heating circulating pump, characterized in that, Includes the following steps: Real-time acquisition of temperature and pressure parameters at multiple key nodes in the heating system; Based on the temperature parameters, calculate the current actual heat load requirement of the system; The actual heat load requirement is compared with the preset reference load curve to generate an initial target speed command; Based on the pressure parameters, determine whether the system is in a state of hydraulic imbalance; If an imbalance exists, the initial target speed command is corrected according to the preset pressure deviation-speed compensation rule to generate the final target speed command; Adjust the operating speed of the circulating pump according to the final target speed command.

2. The energy-saving control method and system for a heating circulating pump according to claim 1, characterized in that: The specific steps for "calculating the current actual heat load demand of the system" include: using the return temperature of the furthest heat dissipation unit as the main feedback quantity, combined with the total supply and return water temperature difference, calculating the equivalent circulation flow rate required to maintain the set indoor temperature through a preset thermodynamic model, and converting it into a heat load demand value.

3. The energy-saving control method and system for a heating circulating pump according to claim 1, characterized in that: The basis for "determining whether the system is in a state of hydraulic imbalance" is: monitoring the available pressure difference of at least two representative branches in the system. When the available pressure difference deviates from its preset threshold by more than a certain percentage and continues for a certain period of time, it is determined to be a hydraulic imbalance.

4. The energy-saving control method and system for a heating circulating pump according to claim 1, characterized in that: The "pressure deviation-speed compensation rule" is as follows: when the available pressure difference of a certain branch is detected to be lower than the threshold, the initial target speed command is appropriately increased; when the available pressure difference is higher than the threshold, the initial target speed command is appropriately decreased under the premise of satisfying the pressure difference at the most unfavorable point.

5. The energy-saving control method and system for a heating circulating pump according to claim 1, characterized in that: It also includes a periodic disturbance adjustment step: during the stable operation of the system, a small, brief negative disturbance is applied to the speed of the circulating pump at fixed time intervals, while monitoring the pressure change at the most unfavorable point; if the pressure change is not sensitive, it is determined that there is room for further speed reduction and energy saving in the system, and the reference load curve is dynamically optimized accordingly.

6. An energy-saving control method and system for a heating circulating pump according to any one of claims 1 to 5, characterized in that, include: The parameter acquisition module consists of temperature and pressure sensors arranged at key nodes of the heating pipeline network, and is used to acquire the temperature and pressure parameters in real time. The central processing unit, with its built-in memory and processor, is configured to execute the control logic as described in any one of claims 1 to 5 and generate a final target speed command; The variable frequency drive module receives the final target speed command and drives the circulating pump motor to run at the corresponding speed.

7. The energy-saving control method and system for a heating circulating pump according to claim 6, characterized in that: The central processing unit also includes a load prediction submodule, which predicts the trend of heat load change based on the thermal inertia of the building envelope and short-term weather forecast data, and fine-tunes the baseline load curve accordingly.

8. The energy-saving control method and system for a heating circulating pump according to claim 6, characterized in that: The system also includes a manual optimization interface, allowing operators to calibrate and fine-tune the preset baseline load curve and pressure threshold based on actual operating experience.

9. The energy-saving control method and system for a heating circulating pump according to claim 6, characterized in that: The parameter acquisition module includes a virtual sensor calculation unit. This unit uses data measured by a limited number of physical sensors deployed in the pipeline network to calculate the temperature and pressure values ​​at locations where sensors are not directly installed, through a fluid dynamics calculation model.

10. The energy-saving control method and system for a heating circulating pump according to claim 6, characterized in that: The system generates operation logs, including heat load curves, speed commands, energy consumption data, and hydraulic state assessment results, which can be exported through a data interface to generate energy efficiency analysis reports.

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