Energy-saving air conditioner water pump energy management method and system

Abstract

The application relates to an energy-saving air conditioner water pump energy management method and system. The method comprises the following steps: acquiring the electric energy input parameter, flow parameter and lift parameter of each water pump, and calculating the operation efficiency of each water pump based on the electric energy input parameter, flow parameter and lift parameter; acquiring the flow parameter and pressure difference parameter of a pipe network target branch, and calculating the local hydraulic resistance of the pipe network target branch based on the flow parameter and pressure difference parameter of the pipe network target branch; acquiring the cold quantity demand of each functional area, and determining the minimum total flow and total lift combination of the water pump system based on the cold quantity demand of each functional area and the local hydraulic resistance of the pipe network target branch; and adjusting the operation frequency of one water pump or water pump combination based on the operation efficiency of each water pump and the minimum total flow and total lift combination of the water pump system, so that the operation energy consumption of the water pump system is minimized. Therefore, the root cause of energy consumption increase can be accurately diagnosed, and targeted optimization measures can be taken.

Description

Technical Field

[0001] This application relates to the field of energy management technology, and more specifically, to an energy management method and system for an energy-saving air conditioning water pump. Background Technology

[0002] Water pumps in central air conditioning systems play a crucial role in delivering chilled or cooling water. As the system operates for longer periods, some initially unnoticed problems begin to emerge, posing a significant challenge to existing energy-saving management strategies. Firstly, in cooling water systems using open cooling towers, and in some chilled water systems, scale, biofilm, or corrosion products gradually form inside the pipe network. These deposits roughen the pipe walls, reducing the effective flow cross-sectional area. This change in pipe roughness and effective cross-sectional area directly leads to a significant increase in resistance to water flow within the network. Hydraulic models originally designed for smooth pipes and specific cross-sectional areas are no longer applicable. To meet the cooling demands of the terminal equipment, the pumps must overcome greater system resistance than before. This means that, for the same flow rate demand, the pumps need to output a higher head to deliver water to various areas. If the control system continues to use the initial energy-saving logic, adjusting pump speed solely based on the total cooling load, even under lower cooling loads, the pump speed and power consumption will significantly increase compared to the initial system phase in order to maintain the necessary supply and return water pressure difference or terminal flow rate.

[0003] Meanwhile, during long-term operation, the pump's internal components, such as impellers, bearings, and seals, will wear and age. This wear leads to a gradual decrease in the pump's mechanical and hydraulic efficiency. This means that even if the pipeline resistance remains unchanged, the pump will consume more electrical energy to output the same flow rate and head. When both increased pipeline resistance and decreased pump efficiency occur simultaneously, the problem becomes more complex and difficult to diagnose. The control system receives a signal of increased pump power consumption, but it cannot accurately distinguish whether this increased power is primarily due to increased pipeline resistance, decreased pump efficiency, or a combination of both, with each contributing a certain percentage. This uncertainty renders traditional energy-saving management methods based on total load completely ineffective. The system cannot accurately determine whether the current high energy consumption is due to increased actual demand, deteriorating pipeline performance, or declining pump performance. Therefore, it cannot take targeted optimization measures.

[0004] The end result is that although the system appears to be operating at "energy efficiency," the actual energy consumption per unit of cooling capacity has significantly worsened, leading to persistently high operating costs. Maintenance personnel are facing a "black box"—they know the energy consumption is high, but struggle to pinpoint the root cause, let alone effectively implement refined energy management. This situation not only increases operating costs and shortens equipment lifespan but may also impact the comfort of the building's interior. Summary of the Invention

[0005] This application discloses an energy management method and system for energy-saving air conditioning water pumps, which aims to solve the dilemma of increased energy consumption, failure of traditional energy-saving management methods, and difficulty for operation and maintenance personnel to accurately diagnose the root cause of problems caused by increased pipeline resistance and decreased pump efficiency during long-term operation of central air conditioning systems.

[0006] The technical solution of this application is as follows:

[0007] In a first aspect, this application discloses an energy management method for an energy-saving air conditioning water pump, comprising the following steps:

[0008] Obtain the power input parameters, flow parameters, and head parameters of each water pump, and calculate the operating efficiency of each water pump based on the power input parameters, flow parameters, and head parameters;

[0009] Obtain the flow rate and differential pressure parameters of the target branch of the pipeline network, and calculate the local hydraulic resistance of the target branch of the pipeline network based on the flow rate and differential pressure parameters of the target branch of the pipeline network;

[0010] Obtain the cooling demand of each functional area, and based on the cooling demand of each functional area and the local hydraulic resistance of the target branch of the pipeline network, determine the minimum total flow rate and total head combination of the pump system.

[0011] Based on the operating efficiency of each pump and the minimum total flow and total head combination of the pump system, adjust the operating frequency of a pump or pump combination to minimize the energy consumption of the pump system.

[0012] Optionally, the steps of obtaining the electrical input parameters, flow rate parameters, and head parameters of each water pump, and calculating the operating efficiency of each water pump based on these parameters include:

[0013] Obtain the voltage, current, power factor, flow rate, and head parameters for each water pump;

[0014] The electrical input power of the water pump is obtained based on voltage parameters, current parameters, and power factor.

[0015] The hydraulic output power of the water pump is obtained based on flow rate parameters and head parameters;

[0016] The operating efficiency of each water pump is calculated based on the electrical input power and the hydraulic output power.

[0017] Optionally, the steps for obtaining the electrical input power of the water pump based on voltage parameters, current parameters, and power factor include:

[0018] The electrical input power of the water pump can be obtained using the following formula:

[0019] P_electricity = V × I × cosφ × √3

[0020] Where P_electric is the electrical input power, √3 is a constant for calculating three-phase AC, V is the voltage parameter, I is the current parameter, and cosφ is the power factor.

[0021] The steps to obtain the hydraulic output power of a water pump based on flow rate and head parameters include:

[0022] The hydraulic output power of the water pump can be obtained using the following formula:

[0023] P_hydraulic force = ρ × g × Q × H

[0024] Where P_hydraulic is the hydraulic output power, ρ is the density of water, g is the gravitational acceleration, Q is the flow rate parameter, and H is the head parameter;

[0025] The steps for calculating the operating efficiency of each water pump based on the electrical input power and hydraulic output power include:

[0026] The operating efficiency is calculated using the following formula:

[0027] η = P_hydraulic / P_electric

[0028] Where η represents the operating efficiency.

[0029] Optionally, the steps to obtain the cooling requirements of each functional area include:

[0030] The cooling demand is calculated based on the real-time occupancy rate of each functional area, the indoor temperature setpoint, the lighting load, the IT equipment load, and the characteristics of the terminal equipment in each area.

[0031] Optional energy management methods for air conditioning water pumps also include:

[0032] To obtain the operating status or instruction information of heat source equipment within a specific functional area;

[0033] Based on the operating status or command information of heat source equipment, predict the intensity and duration of local heat load peaks in specific functional areas, and generate a pre-compensation strategy for cooling demand.

[0034] Before the heat load peak affects the local temperature, adjust the cooling demand of specific functional areas according to the cooling demand pre-compensation strategy;

[0035] Monitor the actual temperature and flow rate changes in specific functional areas, evaluate the effect of cooling pre-compensation, and correct the minimum total flow rate and total head combination of the water pump system based on the evaluation results;

[0036] The steps for adjusting the operating frequency of a pump or pump combination, based on the operating efficiency of each pump and the minimum total flow and total head combination of the pump system, include:

[0037] The operating frequency of a pump or pump combination is adjusted based on the operating efficiency of each pump and the modified minimum total flow and total head combination of the pump system.

[0038] Optionally, the steps for generating a cooling demand pre-compensation strategy include:

[0039] The heat load increment is obtained based on the intensity and duration of the heat load peak;

[0040] The pre-compensated traffic increment is obtained using the following formula:

[0041] ΔQ_pre-compensation = ΔP_heat / (ρ×c_p×ΔT×ε)

[0042] Wherein, ΔQ_pre-compensation is the pre-compensation flow increment, ΔP_heat is the heat load increment, ρ is the density of water, c_p is the specific heat capacity of water, ΔT is the supply and return water temperature difference, and ε is the heat exchange efficiency of a specific functional area.

[0043] A pre-compensation strategy for cooling demand is generated based on the increase in flow rate, duration, and the initial adjustment range of the actuators in the corresponding specific functional areas.

[0044] Optionally, adjusting the cooling capacity requirements of specific functional areas includes:

[0045] An electrically operated regulating valve controlling a specific functional area gradually increases the valve opening by a preset increment at a preset frequency within a predicted time period; and / or

[0046] Increase the speed of the circulating water pump in a specific functional area.

[0047] Optionally, the steps of obtaining the electrical input parameters, flow rate parameters, and head parameters of each water pump, and calculating the operating efficiency of each water pump based on these parameters include:

[0048] Establish an energy conversion benchmark for each water pump;

[0049] Real-time acquisition of flow and head parameters for each water pump;

[0050] Based on real-time acquired flow and head parameters, combined with energy conversion benchmarks, the expected electrical input power of each water pump is calculated.

[0051] The operating efficiency of each pump is calculated using the expected electrical input power and the real-time flow and head parameters.

[0052] Optionally, the steps for establishing an energy conversion baseline for each water pump include:

[0053] Each water pump is driven by a frequency converter to ensure stable operation at multiple characteristic operating points;

[0054] For each characteristic operating point, obtain the corresponding flow parameters and head parameters, and calculate the hydraulic output power based on the flow parameters and head parameters to obtain the electrical input power;

[0055] Calculate the ideal efficiency for each characteristic operating point, fit the ideal efficiency for all characteristic operating points, and establish an energy conversion benchmark for each pump.

[0056] Secondly, this application also discloses an energy-saving air conditioning water pump energy management system, which includes:

[0057] The parameter acquisition module is used to acquire the electrical input parameters, flow parameters, and head parameters of each water pump.

[0058] The pump efficiency calculation module is used to calculate the operating efficiency of each pump based on electrical energy input parameters, flow rate parameters, and head parameters.

[0059] The branch parameter acquisition module is used to acquire the flow and differential pressure parameters of the target branch in the pipeline network;

[0060] The local resistance calculation module is used to calculate the local hydraulic resistance of the target branch of the pipeline network based on the flow parameters and pressure difference parameters of the target branch.

[0061] The cooling demand acquisition module is used to acquire the cooling demand of each functional area;

[0062] The target determination module is used to determine the minimum total flow rate and total head combination of the pump system based on the cooling demand of each functional area and the local hydraulic resistance of the target branch of the pipeline network.

[0063] The operation strategy adjustment module is used to adjust the operating frequency of a pump or pump combination based on the operating efficiency of each pump and the minimum total flow and total head combination of the pump system, so as to minimize the energy consumption of the pump system. Beneficial effects

[0064] The energy management method for air conditioning water pumps disclosed in this application acquires the electrical input parameters, flow parameters, and head parameters of each water pump and calculates its operating efficiency. This allows for real-time monitoring of the actual operating status and energy efficiency of the water pumps, effectively solving the problem of increased energy consumption due to decreased pump efficiency during long-term operation. Simultaneously, by acquiring the flow and differential pressure parameters of the target branch in the pipeline network and calculating its local hydraulic resistance, this application can accurately assess the actual operating condition of the pipeline network, overcoming the limitations of traditional methods that fail due to changes in pipeline resistance. Based on this, and combining the cooling demand of each functional area with the local hydraulic resistance of the pipeline network, this application can determine the minimum total flow and total head combination of the water pump system, ensuring that cooling demand is met while avoiding unnecessary energy waste. Finally, based on the operating efficiency of each water pump and the minimum total flow and total head combination of the water pump system, this application can dynamically adjust the operating frequency of a water pump or a combination of water pumps to minimize the energy consumption of the water pump system.

[0065] In summary, the method presented in this application comprehensively and dynamically considers the dual impacts of individual pump efficiency degradation and increased pipeline resistance, breaking away from the traditional "black box" management model based on total load. This enables refined and adaptive energy management of air conditioning pump systems. Through this method, the system can accurately diagnose the root causes of increased energy consumption and take targeted optimization measures, thereby significantly reducing the actual unit cooling energy consumption of the central air conditioning system, effectively controlling operating costs, extending equipment lifespan, and improving building comfort. Attached Figure Description

[0066] Figure 1 This is a flowchart illustrating an energy management method for an energy-saving air conditioning water pump, provided as an embodiment of this application.

[0067] Figure 2 yes Figure 1 The flowchart of step S1 shown is a schematic diagram of an embodiment.

[0068] Figure 3 This is a flowchart illustrating another energy-saving air conditioning water pump energy management method provided in this application embodiment.

[0069] Figure 4 yes Figure 3 The flowchart of one embodiment of step S6 is shown.

[0070] Figure 5 yes Figure 3 The flowchart of one embodiment of step S7 is shown.

[0071] Figure 6 yes Figure 1 A flowchart illustrating another embodiment of step S1 is shown.

[0072] Figure 7 yes Figure 6 A flowchart illustrating another embodiment of step S111 is shown.

[0073] Figure 8 This is a schematic diagram of the structure of an energy-saving air conditioning water pump energy management system provided in an embodiment of this application. Detailed Implementation

[0074] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0075] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0076] In traditional central air conditioning systems, water pumps, as key equipment for transporting chilled or cooling water, typically rely on variable frequency technology for energy management. Pump output is adjusted based on total cooling load demand to achieve energy savings. However, as the system operates over time, scale, biofilm, or corrosion products can increase hydraulic resistance within the piping network. Simultaneously, wear and aging of pump components reduce their operating efficiency. These issues render traditional load-based energy management methods ineffective, as the system cannot accurately identify the causes of increased energy consumption. This leads to a significant deterioration in actual unit cooling capacity energy consumption and persistently high operating costs.

[0077] For this, please refer to Figure 1 This application proposes an energy management method for an energy-saving air conditioning water pump, comprising the following steps:

[0078] Step S1: Obtain the power input parameters, flow parameters, and head parameters of each water pump, and calculate the operating efficiency of each water pump based on the power input parameters, flow parameters, and head parameters.

[0079] Step S2: Obtain the flow rate and differential pressure parameters of the target branch of the pipeline network, and calculate the local hydraulic resistance of the target branch of the pipeline network based on the flow rate and differential pressure parameters of the target branch of the pipeline network.

[0080] Step S3: Obtain the cooling demand of each functional area, and based on the cooling demand of each functional area and the local hydraulic resistance of the target branch of the pipeline network, determine the minimum total flow rate and total head combination of the pump system.

[0081] Step S4: Based on the operating efficiency of each pump and the minimum total flow and total head combination of the pump system, adjust the operating frequency of a pump or pump combination to minimize the energy consumption of the pump system.

[0082] This application minimizes the energy consumption of the pump system by comprehensively considering the individual efficiency of the pump, the local resistance of the pipeline network, and the real-time cooling demand of each functional area, and dynamically adjusting the pump operating frequency. This effectively solves the problem of energy management failure in the context of system aging and performance degradation.

[0083] The energy management method for air conditioning water pumps proposed in this application aims to optimize the operating efficiency of air conditioning water pump systems through refined management. Here, "electrical input parameters" typically refer to electrical quantities such as voltage, current, and power factor required for pump operation; "flow parameters" refer to the volume of water flowing through the pump or pipeline per unit time; "head parameters" refer to the height the pump can lift water or the pressure difference it can overcome; and "operating efficiency" is an indicator measuring the effectiveness of the pump in converting electrical energy into hydraulic energy. "Target branch of the pipeline network" refers to a specific supply or return water path in the air conditioning water system; "pressure difference parameters" refer to the pressure difference between the two ends of the target branch of the pipeline network; and "local hydraulic resistance" refers to the energy loss caused by friction, bends, valves, etc., in the target branch of the pipeline network. "Cooling demand" refers to the cooling capacity required by each functional area to maintain the set temperature; and "minimum total flow and total head combination of the pump system" refers to the minimum total flow and total head required by the pump system to meet the cooling demand of all functional areas and overcome pipeline resistance.

[0084] In practical implementation, the first step is to obtain the electrical input parameters, flow rate parameters, and head parameters of each water pump. Electrical input parameters can be monitored in real time by installing an electricity meter or power analyzer on the pump's power supply line; for example, voltage, current, and power factor can be recorded manually or collected through an automated system. Flow rate parameters can be obtained by installing a flow meter at the pump outlet or on the pipeline; for example, an ultrasonic flow meter or electromagnetic flow meter can be used. Head parameters can be calculated by installing pressure sensors at the pump's inlet and outlet, combined with the pump's installation height difference; for example, pressure gauge data can be read manually or data can be transmitted to the control system via sensors. Based on these parameters, the operating efficiency of each water pump can be calculated. For example, the operating efficiency can be obtained by measuring the pump's electrical input power and hydraulic output power, and then dividing the hydraulic output power by the electrical input power.

[0085] Secondly, it is necessary to obtain the flow rate and differential pressure parameters of the target branch in the pipeline network. Flow rate parameters can be obtained by installing flow meters on the target branch, for example, using an insertion flow meter. Differential pressure parameters can be obtained by installing differential pressure sensors at both ends of the target branch; for example, data can be manually read from the differential pressure gauges or transmitted to the control system via sensors. Based on these parameters, the local hydraulic resistance of the target branch can be calculated. For example, the resistance coefficient of the branch can be calculated using flow rate and differential pressure data, combined with fluid mechanics formulas.

[0086] Secondly, it is necessary to obtain the cooling demand of each functional area. Cooling demand can be obtained in various ways. For example, it can be estimated based on factors such as real-time temperature, set temperature, personnel density, and equipment load of each functional area, or it can be obtained directly through a building energy management system (BEMS). For instance, cooling demand can be calculated manually or automatically by the system based on historical data and predictive models, combined with current environmental parameters. Based on the cooling demand of each functional area and the local hydraulic resistance of the target branch of the pipe network, the minimum total flow rate and total head combination of the pump system can be determined. For instance, the minimum total flow rate and total head that meet the demand can be determined by iterative calculation or table lookup based on the sum of the cooling demand of all functional areas and the hydraulic characteristic curve of the pipe network.

[0087] Finally, based on the operating efficiency of each pump and the minimum total flow rate and total head combination of the pump system, the operating frequency of one pump or pump combination is adjusted. For example, based on the efficiency curve of each pump and the current total flow rate and total head requirements, the most efficient pump combination can be selected through an optimization algorithm, and its inverter output frequency can be adjusted to minimize the energy consumption of the pump system. For example, a genetic algorithm or particle swarm optimization algorithm can be used to search for the optimal pump operating frequency combination while meeting system requirements.

[0088] Traditional methods often fail to accurately determine the cause of increased energy consumption after a period of system operation due to increased pipeline resistance and decreased pump efficiency, resulting in significantly reduced energy-saving effects. This application, by introducing real-time monitoring and calculation of pump operating efficiency and local hydraulic resistance in the pipeline network, can accurately identify specific aspects of system performance degradation, thereby enabling targeted optimization. For example, when a significant decrease in the efficiency of a pump is detected, the system can prioritize the operation of other high-efficiency pumps or prompt maintenance personnel to inspect the affected pump. When excessive local resistance in the pipeline network is detected, the system can adjust the pump operating strategy to adapt to the new resistance characteristics or prompt maintenance personnel to perform pipeline cleaning. This refined management approach ensures that the pump system always operates at optimal energy efficiency, effectively reducing operating costs and extending equipment lifespan. The core innovation of this application lies in its organic integration of individual pump performance, pipeline system characteristics, and terminal cooling demand, forming a closed-loop intelligent energy management system that achieves comprehensive, accurate, and dynamic optimization of the energy consumption of the air conditioning pump system.

[0089] In some of the embodiments described above in this application, in order to achieve energy management of air conditioning water pumps, it is necessary to obtain the electrical input parameters, flow parameters, and head parameters of each water pump, and calculate the operating efficiency of each water pump based on these parameters. However, in actual operation, how to specifically and accurately obtain these parameters and perform efficiency calculations is the key to ensuring the effective operation of the entire energy management system.

[0090] For this, please refer to Figure 2 This application further proposes a specific scheme for the step S1 above: obtaining the electrical energy input parameters, flow rate parameters, and head parameters of each water pump, and calculating the operating efficiency of each water pump based on the electrical energy input parameters, flow rate parameters, and head parameters, including the following steps:

[0091] Step S11: Obtain the voltage parameters, current parameters, power factor, flow rate parameters, and head parameters for each water pump.

[0092] Step S12: Obtain the electrical input power of the water pump based on voltage parameters, current parameters, and power factor.

[0093] Step S13: Obtain the hydraulic output power of the water pump based on the flow rate parameters and head parameters.

[0094] Step S14: Calculate the operating efficiency of each water pump based on the electrical input power and hydraulic output power.

[0095] Specifically, obtaining the voltage, current, power factor, flow rate, and head parameters of each water pump involves collecting key data in real time during pump operation using various sensors and instruments deployed within the pump system. For example, voltage and current parameters can be measured using voltage and current sensors, while the power factor can be obtained using a power factor meter or smart meter. Flow rate parameters are typically measured by a flow meter installed on the pump's outlet pipe, and head parameters can be calculated by measuring the pressure difference between the pump's inlet and outlet, combined with fluid density and gravitational acceleration. Accurate acquisition of these parameters is fundamental for subsequent calculations.

[0096] Obtaining the water pump's electrical input power based on voltage, current, and power factors can be understood as calculating the actual electrical energy consumed by the pump using electrical principles. For a three-phase AC system, the electrical input power is typically the product of voltage, current, and power factor, multiplied by a constant (such as √3). The purpose is to quantify the energy absorbed by the pump from the power grid during operation.

[0097] Furthermore, obtaining the hydraulic output power of a water pump based on flow rate and head parameters refers to calculating the effective power of the pump's work on the fluid using fluid mechanics principles. Hydraulic output power is typically the product of water density, gravitational acceleration, flow rate, and head parameters. Its purpose is to quantify the effective portion of the pump's conversion of electrical energy into fluid kinetic and potential energy.

[0098] In practical applications, calculating the operating efficiency of each water pump based on the electrical input power and hydraulic output power involves calculating the ratio of hydraulic output power to electrical input power. Operating efficiency is a key indicator for measuring the energy conversion performance of a water pump; a higher value indicates a higher efficiency in converting electrical energy into hydraulic energy and lower energy loss.

[0099] The above technical solutions enable more accurate and reliable acquisition of the operating efficiency of each water pump. This avoids errors caused by parameter estimation or simplified models, thereby improving the decision-making accuracy of the entire energy-saving air conditioning water pump management system. Through refined management of water pump efficiency, the operating status of the pumps can be more effectively identified and optimized, laying a solid foundation for minimizing the energy consumption of the water pump system and ultimately enhancing the overall energy-saving effect of the system.

[0100] In some embodiments of this application, to more accurately obtain the operating efficiency of each water pump, specifically, in step S12 above: the technical solution of obtaining the electrical input power of the water pump based on voltage parameters, current parameters, and power factor can be implemented in the following way. The electrical input power of the water pump is obtained through the following formula:

[0101] P_electricity = V × I × cosφ × √3

[0102] Where P_electricity represents the electrical input power, √3 is a constant used in calculations for three-phase AC power, V is the voltage parameter, I is the current parameter, and cosφ is the power factor. Specifically, the electrical input power P_electricity is an indicator of the electrical energy consumed by the water pump. Its calculation is based on the voltage parameter V, current parameter I, and power factor cosφ of the three-phase AC power, multiplied by √3 to reflect the characteristics of the three-phase system. The voltage parameter V and current parameter I can be obtained in real time by measuring with voltmeters and ammeters installed on the water pump's power supply line, while the power factor cosφ can be obtained using a power factor meter or power analyzer.

[0103] In step S13 above, the technical solution for obtaining the hydraulic output power of the pump based on flow rate and head parameters can be implemented in the following way: The hydraulic output power of the pump is obtained using the following formula:

[0104] P_hydraulic force = ρ × g × Q × H

[0105] Where P_hydraulic is the hydraulic output power, ρ is the density of water, g is the acceleration due to gravity, Q is the flow rate parameter, and H is the head parameter. Specifically, the hydraulic output power P_hydraulic represents the effective power of the pump in doing work on the fluid, and its calculation involves the water density ρ, the acceleration due to gravity g, the pump's flow rate parameter Q, and the head parameter H provided by the pump. The flow rate parameter Q can be measured using a flow meter, and the head parameter H can be obtained by measuring the pressure difference between the pump's inlet and outlet and converting it into head height. The water density ρ and the acceleration due to gravity g are usually known constants.

[0106] In step S14 above, the technical solution for calculating the operating efficiency of each water pump based on the electrical input power and hydraulic output power can be implemented in the following way: The operating efficiency is calculated using the following formula:

[0107] η = P_hydraulic / P_electric

[0108] Where η represents the operating efficiency. Operating efficiency η is the ratio of the pump's hydraulic output power P_hydraulic to its electrical input power P_electric, used to quantify the pump's efficiency in converting electrical energy into hydraulic energy. A higher ratio indicates a higher energy conversion efficiency and lower energy consumption.

[0109] This application's solution, by explicitly defining the calculation formulas for electrical input power P_electric and hydraulic output power P_hydraulic, enables the precise quantification of the pump's operating efficiency η. The calculation of electrical input power P_electric considers the characteristics of three-phase alternating current, ensuring an accurate reflection of actual electrical energy consumption. The calculation of hydraulic output power P_hydraulic is based on fluid mechanics principles, accurately assessing the effective work done by the pump on the fluid. It is precisely because of these precise calculations that the operating efficiency η of each pump can be reliably determined, providing a solid data foundation for subsequent adjustments to minimize the energy consumption of the pump system. This approach avoids operational strategy deviations caused by inaccurate efficiency calculations, thereby ensuring that the pump system always operates near its optimal energy efficiency point.

[0110] In step S3 above, the technical solution for obtaining the cooling capacity requirements of each functional area may include the following methods.

[0111] The cooling demand is calculated based on the real-time occupancy rate of each functional area, the indoor temperature setpoint, the lighting load, the IT equipment load, and the characteristics of the terminal equipment in each area.

[0112] Real-time occupancy rate refers to the number of people or the degree of space utilization within a specific functional area at a given moment, which can be obtained through data from sources such as infrared sensors, access control systems, or personnel counting systems. Indoor temperature setpoint refers to the desired temperature preset by the user or system for that functional area, typically set by the building management system or user interface. Lighting load refers to the heat load generated by lighting equipment operating within the functional area, which can be estimated based on the power and operating time of the lighting equipment. IT equipment load refers to the heat load generated by information technology equipment such as computers, servers, and monitors operating within the functional area, which can be calculated based on the rated power and actual operating status of the equipment. Characteristics of area terminal equipment refer to parameters such as cooling capacity, air volume, and heat exchange efficiency of terminal equipment such as fan coil units and air conditioning units within the functional area under different operating conditions; these parameters are usually provided by the equipment manufacturer or obtained through on-site testing.

[0113] By comprehensively considering the real-time occupancy rate of each functional area, indoor temperature setpoints, lighting load, IT equipment load, and the characteristics of regional terminal equipment, the actual cooling demand of each functional area can be more accurately assessed. Traditional methods may rely solely on simple temperature sensors or preset values, making it difficult to accurately reflect dynamically changing load conditions. By introducing these multi-dimensional parameters, a more refined cooling demand model can be constructed, making the calculated cooling demand closer to reality. This provides a more accurate input for determining the minimum total flow rate and total head combination of the subsequent water pump system. As a result, the water pump system can adjust its operating frequency according to more realistic load demands, avoiding over-cooling or under-cooling, and ensuring that the system minimizes energy consumption while meeting comfort requirements.

[0114] In some embodiments described above in this application, the energy management method for energy-saving air conditioning water pumps typically optimizes and adjusts based on real-time cooling demand and system operating status to minimize the energy consumption of the water pump system. However, in practical applications, certain functional areas may experience sudden, short-term peaks in heat load, such as a large influx of people or the sudden activation of high-power equipment. If only real-time data is relied upon for response, the system may not be able to adjust in time, leading to temperature fluctuations in localized areas, affecting user comfort, and potentially causing energy waste due to response lag.

[0115] For this, please refer to Figure 3 This application further proposes an energy management method for an energy-saving air conditioning water pump, which includes the following steps:

[0116] Step S5: Obtain the operating status or instruction information of the heat source equipment within a specific functional area.

[0117] Step S6: Based on the operating status or command information of the heat source equipment, predict the intensity and duration of the local heat load peak in a specific functional area, and generate a pre-compensation strategy for cooling demand.

[0118] Step S7: Before the heat load peak affects the local temperature, adjust the cooling demand of specific functional areas according to the cooling demand pre-compensation strategy.

[0119] Step S8: Monitor the actual temperature and flow rate changes in specific functional areas, evaluate the effect of cooling pre-compensation, and correct the minimum total flow rate and total head combination of the water pump system based on the evaluation results.

[0120] In step S4 above, the technical solution of adjusting the operating frequency of a pump or pump combination based on the operating efficiency of each pump and the minimum total flow and total head combination of the pump system can be further achieved by adjusting the operating frequency of a pump or pump combination based on the operating efficiency of each pump and the modified minimum total flow and total head combination of the pump system.

[0121] Specifically, acquiring the operating status or command information of heat source equipment within a specific functional area refers to obtaining, in real time, information such as the on / off status, power settings, and operating modes of equipment (e.g., projectors, servers, conference room lighting, kitchen equipment, etc.) that may cause local heat load spikes through sensors, communication interfaces, or control systems. This information can serve as a basis for predicting heat load spikes. Predicting the intensity and duration of local heat load spikes in a specific functional area based on the operating status or command information of heat source equipment, and generating a pre-compensation strategy for cooling demand, can be understood as the system predicting the potential increase in heat load and its duration in the area over a future period based on known equipment power, operating patterns, historical data, and current equipment status. For example, when a conference room projector is detected to be turned on, the system can estimate the heat load increment based on the projector's rated power and the conference duration. This generates a corresponding pre-compensation strategy for cooling demand, which may include the pre-compensated cooling load increment, duration, and adjustment schemes for corresponding actuators (such as electric regulating valves and circulating water pumps).

[0122] In practical applications, the system implements pre-compensation strategies before the predicted heat load peak actually occurs and causes an increase in indoor temperature. For example, by increasing the chilled water flow rate of the terminal equipment in the area or reducing the supply water temperature, the system can prepare for the upcoming heat load and avoid temperature fluctuations. Furthermore, after the pre-compensation strategy is implemented, the system continuously monitors parameters such as the actual temperature, return water temperature, and terminal flow rate in the area. By comparing the actual results with the preset targets, the accuracy and effectiveness of the pre-compensation strategy are evaluated. If deviations exist, the minimum total flow rate and total head combination of the pump system are dynamically corrected based on the evaluation results to ensure that the system can maintain optimal overall energy consumption while meeting cooling demand. Thus, based on the operating efficiency of each pump and the corrected minimum total flow rate and total head combination of the pump system, the operating frequency of a pump or pump combination is adjusted, ensuring that the pump system can still minimize overall energy consumption by optimizing the pump operating frequency, even after considering the total flow rate and total head requirements following the pre-compensation for local heat load peaks.

[0123] Through the above technical solution, this application can significantly improve the response speed and control accuracy of the air conditioning water pump energy management system. The system no longer relies solely on real-time cooling demand for passive adjustments, but can proactively predict and respond to localized heat load peaks, effectively avoiding indoor temperature fluctuations and decreased user comfort caused by response lag. Furthermore, through evaluation and correction of the pre-compensation effect, the system can continuously optimize its predictive model and control strategy, further improving energy utilization efficiency, reducing unnecessary energy consumption, and ensuring the comfort of specific functional areas, achieving a dual optimization of energy saving and comfort.

[0124] In some preferred embodiments, a specific example is given below. Suppose that in a conference room of a large office building, important video conferences are typically held at 9:00 AM and 2:00 PM, during which high-powered projectors and multiple computers are used, and a large number of people may arrive. Traditional methods might only gradually increase the cooling supply after the conference has started, when the conference room temperature begins to rise, resulting in an initially high temperature. Using the solution of this application, the system can obtain conference schedule information from the conference room reservation system in advance, or monitor the power status of the projector. For example, 15 minutes before the conference starts, the system detects that the conference room reservation information shows an upcoming conference, or detects that the projector is powered on but not yet turned on. Based on this, the system predicts that the conference room will experience a heat load peak of approximately 2 hours and an intensity of X kilowatts. Subsequently, the system generates a cooling demand pre-compensation strategy based on the prediction result, for example, gradually increasing the chilled water flow rate of the conference room's terminal equipment 10 minutes before the conference starts, or slightly decreasing the supply water temperature. When the meeting officially begins and the projector and computer are running at full speed, the cooling supply to the conference room is already in place, ensuring the indoor temperature remains near the set value and preventing a significant rise in temperature. During the meeting, the system continuously monitors the actual temperature and chilled water flow rate in the conference room. If a slight upward trend in the actual temperature is detected, indicating that the pre-compensation strategy may be slightly insufficient, the system will fine-tune the minimum total flow rate and total head combination of the water pump system based on the monitoring results. For example, it might slightly increase the total flow rate requirement to ensure more precise subsequent cooling supply. In this way, not only is comfort guaranteed during the meeting, but energy waste caused by over-compensation or under-compensation is also avoided.

[0125] In some of the embodiments described above in this application, a pre-compensation strategy for cooling demand is proposed to predict the intensity and duration of local heat load peaks in specific functional areas based on the operating status or command information of heat source equipment. However, in its implementation, if the specific impact of heat load peaks on cooling demand is not accurately quantified, the generated pre-compensation strategy may not achieve the best results, leading to insufficient or excessive cooling supply, affecting the stability of indoor temperature and energy utilization efficiency.

[0126] For this, please refer to Figure 4 This application further proposes specific steps for the technical solution of step S6 above: generating a pre-compensation strategy for cooling demand, including the following steps:

[0127] Step S61: Obtain the heat load increment based on the intensity and duration of the heat load peak.

[0128] Step S62: Obtain the pre-compensated traffic increment using the following formula:

[0129] ΔQ_pre-compensation = ΔP_heat / (ρ×c_p×ΔT×ε)

[0130] Wherein, ΔQ_pre-compensation is the pre-compensation flow increment, ΔP_heat is the heat load increment, ρ is the density of water, c_p is the specific heat capacity of water, ΔT is the supply and return water temperature difference, and ε is the heat exchange efficiency of a specific functional area.

[0131] Step S63: Generate a pre-compensation strategy for cooling demand based on the flow increment, duration, and the initial adjustment range of the actuator in the corresponding specific functional area.

[0132] Specifically, when a localized heat load peak is anticipated in a specific functional area, the first step is to accurately determine the heat load increment ΔP_heat based on the intensity and duration of the peak. This heat load increment ΔP_heat can be understood as the additional heat load added to the area within a specific time period due to personnel activity, equipment operation, or other heat sources. In practical applications, this heat load increment ΔP_heat can be estimated using preset equipment power, personnel heat dissipation, or through historical data analysis and predictive models.

[0133] The pre-compensation flow increment ΔQ_pre-compensation is obtained through a thermodynamic formula. The parameters in the formula are all physical constants or measurable system operating parameters. The purpose is to convert the heat load increment ΔP_heat into the actual required refrigerant flow increment to accurately meet the increased cooling demand.

[0134] Therefore, after obtaining the pre-compensated flow increment ΔQ_pre-compensation, and combining the duration of the heat load peak with the initial adjustment range of actuators (such as electric regulating valves, circulating water pumps, etc.) within a specific functional area, a specific cooling demand pre-compensation strategy can be generated. This strategy can be a series of control commands used to adjust the operating state of the actuators in advance before the heat load peak arrives, so as to achieve the required flow increment and thus achieve the purpose of pre-compensation.

[0135] The above technical solution enables precise and intelligent generation of pre-compensation strategies for cooling demand. This solution significantly improves the accuracy of pre-compensation, avoiding problems such as temperature increases due to insufficient compensation or energy waste caused by overcompensation. By accurately calculating the required flow increment, the system can more effectively cope with sudden heat load peaks, thereby maintaining stable indoor temperatures, improving user experience, and further optimizing the overall energy consumption performance of the air conditioning water pump system.

[0136] In some preferred embodiments, a specific example is given below. Suppose that a large meeting is scheduled to be held in a conference room of an office building within the next 30 minutes, causing the heat load in that area to increase by 10 kilowatts for 2 hours.

[0137] First, based on the meeting schedule and historical data, the system obtains the heat load increment ΔP_heat as 10 kW, with a duration of 2 hours.

[0138] Secondly, the system obtained the following water density ρ as 997 kg / m³, water specific heat capacity c_p as 4.18 kJ / (kg·K), supply and return water temperature difference ΔT as 5 K, and heat exchange efficiency ε as 0.85.

[0139] Next, the system uses the formula ΔQ_pre-compensation = ΔP_heat / (ρ × c_p × ΔT × ε) to perform calculations:

[0140] ΔQ_pre-compensation = 10 kW / (997 kg / m³ × 4.18 kJ / (kg·K) × 5 K × 0.85) ≈0.00056 m³ / s.

[0141] Finally, based on the calculated pre-compensation flow increment of 0.00056 m³ / s, a duration of 2 hours, and the initial adjustment range of the electric regulating valve at the end of the conference room, the system generates a cooling demand pre-compensation strategy. This strategy may instruct the electric regulating valve of the conference room to be gradually increased 15 minutes before the start of the meeting, so that it reaches the preset opening increment at the start of the meeting to provide additional cooling, and to maintain this opening during the meeting, thereby stabilizing the temperature of the conference room in advance before the heat load peak arrives.

[0142] In some embodiments described above in this application, a pre-compensation strategy for cooling demand in specific functional areas is proposed to adjust the cooling demand of these areas based on the cooling demand before the local temperature is affected by heat load spikes. However, without a clearly defined adjustment mechanism, the implementation of this adjustment step may lack sufficient precision and responsiveness, thereby affecting the actual effectiveness of the pre-compensation strategy and the overall performance of the energy management system.

[0143] For this, please refer to Figure 5 This application further proposes specific steps for the technical solution of adjusting the cooling capacity demand of a specific functional area in step S7 above, including:

[0144] Step S71: Control the electric regulating valve of a specific functional area to increase the valve opening step size at a preset frequency within a predicted time period, gradually increasing the opening by a preset degree; and / or

[0145] Step S72: Increase the speed of the circulating water pump in the specific functional area.

[0146] Specifically, an electric regulating valve is a device that receives electrical signals and adjusts its valve opening accordingly, precisely controlling the refrigerant flow through a given area by changing the valve opening. The predicted time period refers to the predicted duration of a localized heat load peak based on the operating status or command information of the heat source equipment. Within this time period, the electric regulating valve will gradually and smoothly increase the valve opening at a preset frequency, such as at regular time intervals, until a preset opening is reached to meet the pre-compensated cooling demand. This gradual increase helps avoid drastic fluctuations in cooling supply and ensures system stability.

[0147] Increasing the speed of the circulating water pump in a specific functional area can be understood as increasing the motor speed driving the pump through equipment such as a frequency converter. This increased pump speed directly leads to an increase in its head and flow rate, thereby improving the refrigerant circulation and cooling capacity of that functional area. In practical applications, depending on the intensity and duration of the cooling demand pre-compensation strategy, one can selectively use methods such as adjusting the opening of the electric regulating valve, increasing the circulating water pump speed, or a combination of both, to achieve a precise and rapid response to the cooling demand of a specific functional area.

[0148] This application's solution effectively addresses the potential issues of insufficient precision and response speed in the basic solution's cooling capacity adjustment steps by providing a specific cooling capacity adjustment execution mechanism. Specifically, when the system anticipates an impending heat load peak in a specific functional area, the cooling demand pre-compensation strategy generates a corresponding incremental cooling capacity demand. At this point, by gradually increasing the valve opening of the electric regulating valve, the refrigerant flow into that area can be directly and precisely adjusted, ensuring that the cooling capacity supply matches the actual incremental demand. This gradual adjustment method avoids system shocks and temperature fluctuations that may be caused by sudden, large-scale adjustments. Simultaneously, by increasing the speed of the circulating water pump in the specific functional area, the refrigerant circulation volume and delivery pressure in that area can be rapidly increased, thereby quickly enhancing the cooling capacity supply to cope with sudden or intense heat load peaks. The combination or individual use of these two mechanisms makes the cooling capacity adjustment process more flexible, precise, and efficient, ensuring that the required cooling capacity compensation can be provided in a timely and accurate manner before the arrival of heat load peaks.

[0149] Through the above technical solution, this application enables refined and dynamic management of cooling demand in specific functional areas. Compared to merely proposing the abstract concept of "adjusting cooling demand," this solution provides concrete execution methods, allowing the cooling pre-compensation strategy to be implemented efficiently and accurately. This not only significantly improves the system's response speed and control accuracy to local heat load peaks, but also effectively avoids indoor temperature fluctuations caused by insufficient or excessive cooling supply, thereby enhancing user comfort. Furthermore, by precisely controlling the cooling supply, unnecessary energy waste can be avoided, further optimizing the operating energy consumption of the water pump system and achieving more energy-efficient air conditioning water pump energy management.

[0150] In some preferred embodiments, a specific example is given below. Suppose that a large number of people are expected to enter a conference room (a specific functional area) in an office building within the next 30 minutes, resulting in a significant increase in local heat load. Based on system prediction and a cooling demand pre-compensation strategy, the conference room requires additional cooling supply. In this case, the energy-saving air conditioning water pump energy management method of this application will perform the following adjustment steps:

[0151] First, the electric regulating valve controlling the terminal equipment (such as fan coil units) in the conference room is gradually increased from the current value (e.g., 50%) to 80% over the next 15 minutes at a rate of 2% per minute. This gradual adjustment ensures a smooth increase in cooling supply and avoids drastic temperature fluctuations.

[0152] Meanwhile, to further enhance the cooling capacity, the system can increase the speed of the circulating water pump in the area where the conference room is located, for example, from 1200 rpm to 1400 rpm, and maintain this speed until the heat load peak ends.

[0153] By precisely controlling the opening of the electric regulating valve and increasing the speed of the circulating water pump, the conference room receives sufficient pre-compensation for cooling before a large number of people enter, effectively maintaining a stable indoor temperature and ensuring a comfortable environment during the meeting. This also avoids the energy waste that may result from passive adjustments only after the peak heat load arrives.

[0154] Traditional energy management methods for air conditioning water pumps typically require the real-time deployment and monitoring of multiple sensors to obtain comprehensive operational data when acquiring the electrical input, flow, and head parameters of each pump and calculating its operating efficiency. This approach can face challenges such as complex sensor deployment, high data acquisition costs, and difficulty in guaranteeing data accuracy under certain operating conditions, thus affecting the precise adjustment of the water pump system to minimize energy consumption. Failure to address these issues may lead to inaccurate assessments of pump operating efficiency, consequently impacting the overall energy-saving effect and operational stability of the air conditioning water pump system.

[0155] For this, please refer to Figure 6 This application further proposes a specific step for optimizing step S1 above: obtaining the electrical energy input parameters, flow rate parameters, and head parameters of each water pump, and calculating the operating efficiency of each water pump based on the electrical energy input parameters, flow rate parameters, and head parameters, which includes:

[0156] Step S111: Establish the energy conversion benchmark for each water pump.

[0157] Step S112: Obtain the flow rate and head parameters of each water pump in real time.

[0158] Step S113: Based on the real-time acquired flow and head parameters, and combined with the energy conversion benchmark, calculate the expected electrical input power of each water pump.

[0159] Step S114: Calculate the operating efficiency of each pump using the expected electrical input power and the real-time acquired flow and head parameters.

[0160] Specifically, establishing an energy conversion benchmark for each water pump involves acquiring performance data of the pump under different operating conditions, such as the correspondence between flow rate parameters, head parameters, and electrical input power, through a series of controlled experiments or simulations before the pump is put into operation or within a specific maintenance cycle. This data can be fitted into performance curves or stored in lookup tables to form a model characterizing the inherent energy conversion characteristics of the water pump. Once this benchmark is established, it can be used as a reference in subsequent operation to calculate the electrical input power of the water pump.

[0161] Real-time acquisition of the flow and head parameters of each water pump refers to continuously monitoring the actual operating status of the pumps and obtaining their instantaneous flow and head parameters through flow meters and pressure sensors installed at the pump inlet and outlet or on the pipeline. These parameters directly reflect the hydraulic output power of the pumps and are also key inputs for calculating the electrical input power based on energy conversion benchmarks.

[0162] In practical applications, calculating the expected electrical input power of each pump based on real-time acquired flow and head parameters, combined with an energy conversion benchmark, involves using a pre-established energy conversion benchmark and real-time monitored flow and head parameters as input. Through methods such as table lookup, interpolation, or model calculation, the theoretical electrical input power that the pump should consume under current operating conditions is predicted. This calculation method avoids direct real-time measurement of electrical input parameters, simplifying the data acquisition process.

[0163] Furthermore, calculating the operating efficiency of each pump using the expected electrical input power and the real-time acquired flow and head parameters means, after obtaining the estimated expected electrical input power, combining it with the real-time acquired flow and head parameters, and calculating the current operating efficiency of the pump according to the definition of pump efficiency (the ratio of hydraulic output power to electrical input power). The hydraulic output power can be calculated from the flow and head parameters.

[0164] This application's solution calculates pump operating efficiency by introducing an energy conversion benchmark and extrapolating the expected electrical input power based on real-time acquired flow and head parameters. The principle behind this approach is that each pump, during its design and manufacturing process, has an inherent and predictable correlation between its hydraulic performance and electrical energy consumption. This correlation is quantified and modeled using a pre-established energy conversion benchmark. In actual operation, when the pump's flow and head parameters are acquired in real-time, these hydraulic parameters accurately reflect the pump's current operating point. By combining this with the known energy conversion benchmark, the expected electrical input power of the pump at that operating point can be extrapolated. This extrapolation method avoids the need for real-time, high-precision measurement of electrical input parameters, reduces reliance on sensors and system complexity, and provides stable and reliable efficiency calculation results, offering an accurate basis for subsequent pump operating frequency adjustments.

[0165] Through the above technical solution, this application effectively solves the problems of complexity, high cost, and limited data accuracy caused by directly measuring all parameters in real time in traditional methods. By establishing an energy conversion benchmark and combining it with real-time hydraulic parameters to calculate the electrical input power, the configuration of on-site sensors can be simplified, reducing system implementation and maintenance costs. Furthermore, since the energy conversion benchmark is usually established in a controlled environment, its accuracy and stability are high, thus improving the reliability and accuracy of pump operating efficiency calculations. This allows for more precise and effective adjustments to minimize the operating energy consumption of the pump system, enhancing the intelligence level and energy-saving effect of the entire air conditioning pump energy management system.

[0166] In some preferred embodiments, a specific example is given below. Assume an air conditioning water pump system includes a water pump 100. Before the water pump 100 is put into operation, its performance is tested, and its flow rate, head, and corresponding electrical input power are recorded at different speeds and loads. For example, at a speed of 1450 rpm, with a flow rate of 100 m³ / h and a head of 20 m, the measured electrical input power is 10 kW; with a flow rate of 120 m³ / h and a head of 22 m, the measured electrical input power is 12 kW. These data points are fitted to establish an energy conversion benchmark for the water pump 100. This benchmark can be a mathematical model or a performance curve.

[0167] In actual operation, the system only needs to monitor the flow rate and head parameters of pump 100 in real time. For example, when the real-time monitored flow rate of pump 100 is 110 m³ / h and the head is 21 m, the system will calculate the expected electrical input power of pump 100 under this operating condition based on the pre-established energy conversion benchmark. Assume the calculated expected electrical input power is 11 kW. Simultaneously, based on the real-time flow rate of 110 m³ / h and head of 21 m, the hydraulic output power of pump 100 can be calculated. For example, if the density of water ρ is taken as 1000 kg / m³ and the gravitational acceleration g is taken as 9.8 m / s², then the hydraulic output power P_hydraulic = ρ × g × Q × H = 1000 × 9.8 × (110 / 3600) × 21 ≈ 6.26 kW. Finally, the operating efficiency η of pump 100 can be calculated as P_hydraulic / P_electric = 6.26kW / 11kW ≈ 56.9%. In this way, the operating efficiency of the pump can be accurately evaluated without real-time measurement of electrical input parameters, providing data support for subsequent energy-saving control.

[0168] In some embodiments described above in this application, a method is proposed to establish an energy conversion benchmark for each water pump, and based on real-time acquired flow and head parameters, combined with the energy conversion benchmark, to estimate the expected electrical input power of each water pump, and then calculate the operating efficiency of each water pump. For details, please refer to [link to relevant documentation]. Figure 7 The technical solution for establishing the energy conversion benchmark for each water pump in step S111 above may include the following steps:

[0169] Step S1111: Drive each water pump through a frequency converter to make it operate stably at multiple characteristic operating points.

[0170] Step S1112: For each characteristic operating point, obtain the corresponding flow rate parameters and head parameters, and calculate the hydraulic output power based on the flow rate parameters and head parameters to obtain the electrical energy input power.

[0171] Step S1113: Calculate the ideal efficiency for each characteristic operating point, fit the ideal efficiency for all characteristic operating points, and establish an energy conversion benchmark for each water pump.

[0172] Specifically, driving each water pump with a frequency converter means using variable frequency speed control technology to precisely control the motor speed of the water pump, thereby enabling it to operate stably at multiple characteristic operating points that represent different working conditions. These characteristic operating points typically cover the typical flow rate and head combinations that the water pump may encounter in actual applications, ensuring that the established benchmark can comprehensively reflect the performance characteristics of the water pump.

[0173] For each characteristic operating point, obtaining the corresponding flow rate and head parameters involves using flow meters and pressure sensors installed at the pump inlet and outlet or on the pipeline to measure and record the pump's flow rate and head values ​​at that specific operating point in real time. Based on these flow rate and head parameters, the pump's hydraulic output power, i.e., the effective power of the pump doing work on the fluid, can be calculated. Simultaneously, the pump's electrical input power at that operating point is obtained through electricity metering equipment, i.e., the electrical energy consumed by the pump from the power grid.

[0174] Furthermore, calculating the ideal efficiency at each characteristic operating point involves comparing the calculated hydraulic output power with the acquired electrical input power at that point to obtain the pump's energy conversion efficiency. Fitting the ideal efficiency across all characteristic operating points involves using mathematical modeling methods, such as polynomial fitting, curve fitting, or machine learning algorithms, to process these discrete ideal efficiency data points and establish a continuous efficiency characteristic curve or model that describes the pump's efficiency across its entire operating range. The fitted curve or model is then defined as the energy conversion benchmark for each pump.

[0175] The proposed solution involves systematically calibrating the performance of the water pump before or periodically putting it into actual operation. This involves driving the pump with a frequency converter to operate stably at multiple preset characteristic operating points, and accurately measuring the hydraulic output power and electrical input power at each operating point to calculate the ideal efficiency at that point. By fitting these discrete ideal efficiency data, a continuous energy conversion curve or model, i.e., an energy conversion benchmark, can be constructed. This benchmark accurately reflects the energy conversion characteristics of the water pump under different operating conditions. Therefore, in actual operation, when the pump's flow rate and head parameters are acquired in real time, the expected electrical input power of the pump can be accurately calculated using this energy conversion benchmark, thereby calculating its operating efficiency. This method avoids direct real-time measurement of electrical input parameters, simplifies the data acquisition process, and ensures the accuracy of efficiency calculations.

[0176] The above technical solution enables the establishment of a precise energy conversion benchmark for each water pump. This benchmark allows for accurate calculation of the pump's expected electrical input power and operating efficiency in subsequent energy management processes simply by acquiring the pump's flow and head parameters in real time. This simplifies real-time monitoring and reduces the cost of sensor deployment and maintenance. Furthermore, by calibrating and fitting the benchmark at multiple characteristic operating points, the established energy conversion benchmark exhibits higher accuracy and robustness, more realistically reflecting the pump's performance under various actual operating conditions. This provides a reliable data foundation for optimizing the pump system's operation, thereby achieving more refined energy management and energy-saving effects.

[0177] Please see Figure 8 This application proposes an energy-saving air conditioning water pump energy management system, the system 80 comprising:

[0178] The parameter acquisition module 81 is used to acquire the electrical input parameters, flow parameters, and head parameters of each water pump.

[0179] The pump efficiency calculation module 82 is used to calculate the operating efficiency of each pump based on the electrical energy input parameters, flow parameters, and head parameters.

[0180] The branch parameter acquisition module 83 is used to acquire the flow parameters and differential pressure parameters of the target branch in the pipeline network.

[0181] The local resistance calculation module 84 is used to calculate the local hydraulic resistance of the target branch of the pipeline network based on the flow parameters and pressure difference parameters of the target branch.

[0182] The cooling demand acquisition module 85 is used to acquire the cooling demand of each functional area.

[0183] The target determination module 86 is used to determine the minimum total flow rate and total head combination of the pump system based on the cooling demand of each functional area and the local hydraulic resistance of the target branch of the pipeline network.

[0184] The operation strategy adjustment module 87 is used to adjust the operating frequency of a pump or pump combination based on the operating efficiency of each pump and the minimum total flow and total head combination of the pump system, so as to minimize the energy consumption of the pump system.

[0185] The energy-saving air conditioning water pump energy management system proposed in this application aims to solve the problem of energy consumption management failure caused by increased pipeline resistance and decreased pump efficiency after long-term operation of traditional central air conditioning water pump energy management methods. Through modular design, this system can acquire the water pump operating status and pipeline hydraulic characteristics in real time and accurately, and dynamically optimize the water pump system's operating strategy based on the actual cooling demand of each functional area. Specifically, the system comprehensively senses the operating data of the water pump and pipeline through parameter acquisition module 81 and branch parameter acquisition module 83; quantitatively evaluates water pump performance and pipeline resistance through water pump efficiency calculation module 82 and local resistance calculation module 84; further, it clarifies the minimum operating requirements of the system through cooling demand acquisition module 85 and operating target determination module 86; finally, the operating strategy adjustment module 87 intelligently adjusts the water pump operating frequency based on the comprehensive evaluation results, thereby ensuring that the water pump system meets cooling demand while minimizing operating energy consumption. This systematic management approach effectively improves the overall energy efficiency and operational stability of the air conditioning water pump system.

[0186] In some embodiments of this application, the aforementioned energy-saving air conditioning water pump energy management system can be deployed in the control center of the central air conditioning system or integrated into the building energy management system (BEMS), and interact with field equipment through sensor networks, data acquisition units and control actuators.

[0187] Specifically, the parameter acquisition module 81 may include a series of sensors and data acquisition devices, such as voltage sensors, current sensors, and power factor sensors for acquiring electrical energy input parameters, flow meters for acquiring flow parameters, and pressure sensors for acquiring head parameters. These sensors are configured at corresponding locations on each water pump to monitor and acquire pump operating data in real time. For example, voltage and current sensors may be clamp meters or built-in current transformers, flow meters may be ultrasonic or electromagnetic flow meters, and pressure sensors may be diffused silicon pressure transmitters. The acquired data can be transmitted to the central processing unit via wired or wireless communication.

[0188] The pump efficiency calculation module 82 can be a software module integrated into the central processing unit or a dedicated calculation unit. This module is configured to receive electrical input parameters, flow rate parameters, and head parameters from the parameter acquisition module. Based on these parameters, the pump efficiency calculation module can calculate the operating efficiency of each pump. For example, the module can determine the operating efficiency based on the ratio of electrical input power (calculated from voltage, current, and power factor) to hydraulic output power (calculated from flow rate and head). In some implementations, the module can preset or dynamically update the pump's performance curves to improve the accuracy of the efficiency calculation.

[0189] The branch parameter acquisition module 83 may include a flow meter and a differential pressure sensor installed on the target branch of the pipeline network. The flow meter is used to measure the amount of water flowing through the branch, and the differential pressure sensor is used to measure the pressure difference between the two ends of the branch. For example, the flow meter may be a turbine flow meter, and the differential pressure sensor may be a diaphragm differential pressure transmitter. These devices transmit real-time data to the system.

[0190] The local resistance calculation module 84 can be a software module configured to receive flow rate and differential pressure parameters from the branch parameter acquisition module. This module calculates the local hydraulic resistance of the target branch in the pipe network based on fluid mechanics principles, such as the Darcy-Weisbach formula or empirical formulas. For example, this module can deduce the current resistance coefficient based on flow rate and differential pressure data, combined with information such as pipe geometry and roughness.

[0191] The cooling demand acquisition module 85 can be a data interface module or a calculation module. This module is configured to acquire the cooling demand of each functional area from the building energy management system, area controller, or manual input interface. For example, this module can receive signals from area temperature sensors, occupancy sensors, and user-defined values, and, in conjunction with a preset load model, estimate the cooling demand required for each area. In some implementations, this module can also be linked to a weather forecasting system to predict cooling demand.

[0192] The target determination module 86 can be an optimization algorithm module. This module is configured to receive cooling demand from each functional area of ​​the cooling demand acquisition module, and local hydraulic resistance of the target branch of the pipe network from the local resistance calculation module. Based on these inputs, the module can comprehensively consider all constraints, such as minimum flow requirements of terminal equipment and supply / return water temperature difference, to determine the minimum total flow rate and total head combination of the pump system while meeting all cooling demand and overcoming pipe network resistance. For example, the module can use linear programming, nonlinear programming, or heuristic algorithms to solve for the optimal flow rate and head combination.

[0193] The operation strategy adjustment module 87 can be a control output module. This module is configured to receive the operating efficiency of each pump from the pump efficiency calculation module, and the minimum total flow and total head combination of the pump system from the operation target determination module. Based on this information, the module can intelligently select one or more pumps to operate and adjust the operating frequency of their inverters to minimize energy consumption while meeting the overall pump system's operational targets. For example, the module can select the optimal pump combination and operating frequency based on the pump efficiency curves and current system requirements, using dynamic programming or rule-based control strategies. The module's output signal can directly control the frequency setpoint of the pump inverter.

[0194] The energy-saving air conditioning water pump energy management system proposed in this application represents a significant technological advancement compared to existing technologies that rely solely on adjusting pump speed based on total cooling load. Traditional methods, after long-term system operation, suffer from increased hydraulic resistance due to scale and biofilm accumulation within the pipe network, as well as impeller wear and decreased efficiency in the pumps themselves. This makes it impossible to accurately determine the root cause of increased energy consumption, resulting in significantly reduced energy-saving effects and persistently high operating costs.

[0195] The above are merely embodiments of this application and are not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. An energy management method for an energy-saving air conditioning water pump, characterized in that, include: The power input parameters, flow rate parameters, and head parameters of each water pump are obtained, and the operating efficiency of each water pump is calculated based on the power input parameters, flow rate parameters, and head parameters. Obtain the flow rate and differential pressure parameters of the target branch of the pipeline network, and calculate the local hydraulic resistance of the target branch of the pipeline network based on the flow rate and differential pressure parameters of the target branch of the pipeline network; Obtain the cooling demand of each functional area, and based on the cooling demand of each functional area and the local hydraulic resistance of the target branch of the pipeline network, determine the minimum total flow rate and total head combination of the pump system. Based on the operating efficiency of each pump and the minimum total flow and total head combination of the pump system, the operating frequency of a pump or pump combination is adjusted to minimize the energy consumption of the pump system. The energy management method for the energy-saving air conditioning water pump also includes: To obtain the operating status or instruction information of heat source equipment within a specific functional area; Based on the operating status or command information of the heat source equipment, the intensity and duration of local heat load peaks in specific functional areas are predicted, and a pre-compensation strategy for cooling demand is generated. Before the heat load peak affects the local temperature, the cooling demand of specific functional areas is adjusted according to the cooling demand pre-compensation strategy. Monitor the actual temperature and flow rate changes in specific functional areas, evaluate the effect of cooling pre-compensation, and correct the minimum total flow rate and total head combination of the water pump system based on the evaluation results; The step of adjusting the operating frequency of a pump or pump combination based on the operating efficiency of each pump and the minimum total flow and total head combination of the pump system includes: The operating frequency of a pump or pump combination is adjusted based on the operating efficiency of each pump and the modified minimum total flow and total head combination of the pump system. The steps for generating the cooling demand pre-compensation strategy include: The heat load increment is obtained based on the intensity and duration of the heat load peak; The pre-compensated traffic increment is obtained using the following formula: ΔQ_pre-compensation = ΔP_heat / (ρ×c_p×ΔT×ε) Wherein, ΔQ_pre-compensation is the pre-compensation flow rate increment, ΔP_heat is the heat load increment, ρ is the density of water, c_p is the specific heat capacity of water, ΔT is the supply and return water temperature difference, and ε is the heat exchange efficiency of a specific functional area. A pre-compensation strategy for cooling demand is generated based on the flow increment, duration, and the initial adjustment range of the actuator in the corresponding specific functional area. The steps of obtaining the electrical input parameters, flow rate parameters, and head parameters of each water pump, and calculating the operating efficiency of each water pump based on the electrical input parameters, flow rate parameters, and head parameters, include: Establish an energy conversion benchmark for each water pump; Real-time acquisition of flow and head parameters for each water pump; Based on the real-time acquired flow and head parameters, and combined with the energy conversion benchmark, the expected electrical input power of each water pump is calculated. The operating efficiency of each pump is calculated using the expected electrical input power and the real-time acquired flow and head parameters. The steps for establishing the energy conversion benchmark for each water pump include: Each water pump is driven by a frequency converter to ensure stable operation at multiple characteristic operating points; For each characteristic operating point, obtain the corresponding flow parameters and head parameters, and calculate the hydraulic output power based on the flow parameters and head parameters to obtain the electrical input power; Calculate the ideal efficiency for each characteristic operating point, fit the ideal efficiency for all characteristic operating points, and establish an energy conversion benchmark for each pump.

2. The energy management method for an energy-saving air conditioning water pump according to claim 1, characterized in that, The steps for obtaining the cooling requirements of each functional area include: The cooling demand is calculated based on the real-time occupancy rate of each functional area, indoor temperature setpoint, lighting load, IT equipment load, and the characteristics of the terminal equipment in the area.

3. The energy management method for an energy-saving air conditioning water pump according to claim 1, characterized in that, The steps for adjusting the cooling requirements of specific functional areas include: An electrically operated regulating valve controlling a specific functional area gradually increases the valve opening by a preset increment at a preset frequency within a predicted time period; and / or Increase the speed of the circulating water pump in a specific functional area.

4. An energy-saving air conditioning water pump energy management system, characterized in that, This system is used to execute the energy management method for energy-saving air conditioning water pumps according to any one of claims 1-3, the system comprising: The parameter acquisition module is used to acquire the electrical input parameters, flow parameters, and head parameters of each water pump. The pump efficiency calculation module is used to calculate the operating efficiency of each pump based on the electrical energy input parameters, flow rate parameters, and head parameters. The branch parameter acquisition module is used to acquire the flow and differential pressure parameters of the target branch in the pipeline network; The local resistance calculation module is used to calculate the local hydraulic resistance of the target branch of the pipeline network based on the flow parameters and pressure difference parameters of the target branch of the pipeline network. The cooling demand acquisition module is used to acquire the cooling demand of each functional area; The target determination module is used to determine the minimum total flow rate and total head combination of the pump system based on the cooling demand of each functional area and the local hydraulic resistance of the target branch of the pipeline network. The operation strategy adjustment module is used to adjust the operating frequency of a pump or pump combination based on the operating efficiency of each pump and the minimum total flow and total head combination of the pump system, so as to minimize the energy consumption of the pump system.

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