An edge control system for energy saving optimization of large central air conditioning systems

Abstract

This invention relates to the field of central air conditioning control technology, specifically to an edge control system for energy-saving optimization of large-scale central air conditioning systems. The edge control system includes an edge computing main control unit, a chilled water parameter acquisition unit, a building thermal inertia acquisition unit, a fresh air humidity acquisition unit, a pipeline fluid parameter acquisition unit, a viscosity-temperature characteristic power loss calculation unit, an effective heat load correction unit, an optimal output power calculation unit, and an execution drive unit. Each acquisition unit is connected to the edge computing main control unit, each calculation unit is connected sequentially, and the execution drive unit is connected to the optimal output power calculation unit. This invention reconstructs the edge control logic of the central air conditioning system through the progressive collaboration of multi-level calculation units and the linkage processing of multi-dimensional parameters, achieving precise matching between control parameters and actual operating conditions, and optimizing the system's operation control logic.

Description

Technical Field

[0001] This invention relates to the field of central air conditioning control technology, specifically to an edge control system for energy-saving optimization of large central air conditioning systems. Background Technology

[0002] Existing edge control systems for large-scale central air conditioning systems rely solely on the indoor-outdoor temperature difference as the core adjustment basis. They fail to incorporate factors such as the viscosity-temperature losses of chilled water during pipe transport, the thermal inertia and hysteresis of the building envelope, and the impact of fresh air humidity on heat exchange. Furthermore, there is no progressive linkage between these three key operating parameters and control commands. The control system can only passively adjust single parameters, failing to match the coupled changes of multiple physical quantities in actual central air conditioning operation. This results in discrepancies between control commands and the actual heat load requirements of the system. The edge-end control calculations cannot accurately reflect the real operating conditions of large-scale building central air conditioning systems, indicating inherent flaws in the control logic.

[0003] Based on the above problems, there is an urgent need for a central air conditioning edge control solution that can link multi-dimensional physical parameters and construct progressive calculation logic to solve the technical problems of single control logic and inaccurate parameter matching in the existing system. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing an edge control system for energy-saving optimization of large-scale central air conditioning systems. The edge control system includes an edge computing main control unit, a chilled water parameter acquisition unit, a building thermal inertia acquisition unit, a fresh air humidity acquisition unit, a pipeline fluid parameter acquisition unit, a viscosity-temperature characteristic power loss calculation unit, an effective heat load correction unit, an optimal output power calculation unit, and an execution drive unit. The chilled water parameter acquisition unit, the building thermal inertia acquisition unit, the fresh air humidity acquisition unit, the pipeline fluid parameter acquisition unit, the viscosity-temperature characteristic power loss calculation unit, the effective heat load correction unit, the optimal output power calculation unit, and the execution drive unit are all connected to the optimal output power calculation unit.

[0005] Preferably, the edge computing main control unit includes an embedded edge processor, which is connected to a chilled water parameter acquisition unit, a building thermal inertia acquisition unit, a fresh air humidity acquisition unit, a pipeline fluid parameter acquisition unit, and a viscosity-temperature characteristic power loss calculation unit.

[0006] More preferably, the chilled water parameter acquisition unit includes a real-time chilled water dynamic viscosity acquisition component, a chilled water density acquisition component, a chilled water flow rate acquisition component, a pipe cross-sectional area acquisition component, a pipe equivalent length acquisition component, a pipe inner diameter acquisition component, and a circulating water pump efficiency acquisition component. The real-time chilled water dynamic viscosity acquisition component is connected to an embedded edge processor, the chilled water density acquisition component is connected to an embedded edge processor, and the chilled water flow rate acquisition component is connected to an embedded edge processor.

[0007] More preferably, the building thermal inertia acquisition unit includes a normalized building thermal inertia coefficient acquisition component, a real-time thermal inertia lag time acquisition component, an indoor real-time temperature acquisition component, an indoor set temperature acquisition component, and a reference temperature acquisition component. The normalized building thermal inertia coefficient acquisition component is connected to an embedded edge processor, and the real-time thermal inertia lag time acquisition component is connected to an embedded edge processor.

[0008] More preferably, the viscosity-temperature characteristic power loss calculation unit is equipped with a pipeline additional power loss formula, the pipeline additional power loss formula is as follows: , The Adding power loss to the pipeline, the The dimensionless correction coefficient, the For real-time cryogenic hydrodynamic viscosity, the For reference to the dynamic viscosity of chilled water, the The density of chilled water, the The chilled water flow rate, the The cross-sectional area of ​​the pipe is... For the equivalent length of the pipe, the The inner diameter of the pipe, the For circulating water pump efficiency.

[0009] More preferably, the effective heat load correction unit establishes a data transmission link with the viscosity-temperature characteristic power loss calculation unit, the effective heat load correction unit receives the pipeline additional power loss data output by the viscosity-temperature characteristic power loss calculation unit, and the effective heat load correction unit receives the collected data output by the building thermal inertia acquisition unit.

[0010] More preferably, the optimal output power calculation unit establishes a data transmission link with the effective heat load correction unit, the optimal output power calculation unit receives the correction data output by the effective heat load correction unit, the optimal output power calculation unit receives the acquisition data output by the fresh air humidity acquisition unit, and the optimal output power calculation unit receives the acquisition data output by the pipeline fluid parameter acquisition unit.

[0011] More preferably, the execution drive unit includes a compressor drive component, a water pump drive component, and a fresh air valve drive component. The compressor drive component is connected to the optimal output power calculation unit, the water pump drive component is connected to the optimal output power calculation unit, and the fresh air valve drive component is connected to the optimal output power calculation unit.

[0012] More preferably, the edge computing main control unit includes a coefficient calibration unit, which is connected to the embedded edge processor, a viscosity-temperature characteristic power loss calculation unit, an effective heat load correction unit, and an optimal output power calculation unit.

[0013] More preferably, the edge computing main control unit includes a data storage component, which is connected to an embedded edge processor, a viscosity-temperature characteristic power loss calculation unit, an effective heat load correction unit, and an optimal output power calculation unit.

[0014] The technical effects include: This invention breaks through the limitations of existing central air conditioning systems that rely solely on temperature regulation by setting up a sequentially linked viscosity-temperature characteristic power loss calculation unit, an effective heat load correction unit, and an optimal output power calculation unit. It incorporates three types of parameters—chilled water viscosity-temperature characteristics, building thermal inertia, and fresh air humidity—into the edge control system, constructing a progressive calculation logic. This solves the core problems of existing systems, such as simplistic control logic and mismatch between control commands and actual heat load. The coordinated operation of the multi-dimensional acquisition and calculation units ensures that edge control commands closely match the system's actual operating conditions, achieving precise adaptation between control parameters and operating status, and optimizing the overall control logic of the central air conditioning system. Attached Figure Description

[0015] Figure 1 Connection diagram of the core unit of the edge control system for energy-saving optimization of large central air conditioning systems; Figure 2 This is a block diagram of the edge computing main control unit sub-components and external connections; Figure 3 Block diagram of the chilled water parameter acquisition unit; Figure 4 A block diagram showing the components of a building thermal inertia acquisition unit; Figure 5 A flowchart illustrating the progressive linkage and data interaction of the system's computing units; Figure 6 This is a block diagram showing the composition and control connection of the drive unit. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0017] Existing large-scale central air conditioning control systems only adjust based on indoor temperature differences, without considering factors such as the viscosity-temperature characteristics of chilled water and the thermal inertia of buildings, resulting in low control accuracy and energy waste.

[0018] Based on this, please refer to Figures 1-6 This embodiment provides an edge control system for energy-saving optimization of large-scale central air conditioning systems, including an edge computing main control unit, a chilled water parameter acquisition unit, a building thermal inertia acquisition unit, a fresh air humidity acquisition unit, a pipeline fluid parameter acquisition unit, a viscosity-temperature characteristic power loss calculation unit, an effective heat load correction unit, an optimal output power calculation unit, and an execution drive unit. The chilled water parameter acquisition unit, the building thermal inertia acquisition unit, the fresh air humidity acquisition unit, the pipeline fluid parameter acquisition unit, the viscosity-temperature characteristic power loss calculation unit, the effective heat load correction unit, the optimal output power calculation unit, and the optimal output power calculation unit are all connected to the edge computing main control unit. The edge control system constructs a complete edge control system through multi-unit collaboration. Each unit has a clear division of labor and works in close coordination. The edge computing master control unit, as the core, undertakes the core functions of data processing and command distribution. The chilled water parameter acquisition unit, the building thermal inertia acquisition unit, the fresh air humidity acquisition unit, and the pipeline fluid parameter acquisition unit respectively collect various key operating parameters, providing data support for the viscosity-temperature characteristic power loss calculation unit, the effective heat load correction unit, and the optimal output power calculation unit. The viscosity-temperature characteristic power loss calculation unit, the effective heat load correction unit, and the optimal output power calculation unit sequentially complete data calculations, and the execution drive unit implements control commands. All units are closely linked to form a complete control closed loop. The edge control system abandons the traditional single-dimensional temperature control design concept and incorporates chilled water fluid characteristics, building thermal characteristics, and fresh air humidity characteristics into the control logic. Through the hierarchical linkage of multiple units, a new control architecture is formed. Without any unit, the complete control process from data acquisition, loss calculation, heat load correction to power optimization cannot be completed. It breaks through the inherent limitations of existing control systems at the architectural level and adapts to the long-term, high-load, and multi-scenario operation requirements of large central air conditioning systems.

[0019] The existing edge computing master control unit has an unreasonable structural design, resulting in low data processing efficiency.

[0020] Based on this, the edge computing main control unit includes an embedded edge processor. The embedded edge processor is connected to a chilled water parameter acquisition unit, a building thermal inertia acquisition unit, a fresh air humidity acquisition unit, a pipeline fluid parameter acquisition unit, and a viscosity-temperature characteristic power loss calculation unit. The embedded edge processor, as the core processing component, is directly connected to each acquisition unit and computing unit, responsible for data reception, processing, and command transmission, simplifying the data transmission path. The embedded edge processor has local data processing capabilities, eliminating reliance on the cloud for computation, reducing transmission latency. Its direct connection to each unit avoids signal loss in intermediate transmission stages, ensuring the stability and accuracy of data transmission. The embedded edge processor adopts a local real-time processing mode, parsing and distributing all acquired data at the edge, eliminating the need to upload to a remote server for computation, significantly shortening the data processing cycle. Simultaneously, it establishes direct point-to-point connections with each functional unit, avoiding data distortion caused by multi-level relays, ensuring that the parameters transmitted to each computing unit are consistent with the original data obtained by the acquisition unit, providing a fundamental guarantee for subsequent accurate computation.

[0021] In existing technologies, the collection of chilled water parameters is incomplete, leading to large deviations in subsequent calculation results.

[0022] Based on this, the chilled water parameter acquisition unit includes a real-time chilled water dynamic viscosity acquisition component, a chilled water density acquisition component, a chilled water flow velocity acquisition component, a pipe cross-sectional area acquisition component, a pipe equivalent length acquisition component, a pipe inner diameter acquisition component, and a circulating water pump efficiency acquisition component. The real-time chilled water dynamic viscosity acquisition component, the chilled water density acquisition component, and the chilled water flow velocity acquisition component are all connected to the embedded edge processor. The real-time chilled water dynamic viscosity acquisition component captures the dynamic changes in chilled water dynamic viscosity in real time. Chilled water dynamic viscosity fluctuates continuously with ambient temperature and water quality, and is a core variable affecting pipe resistance loss. The real-time chilled water dynamic viscosity acquisition component continuously acquires the real-time value of this parameter through the fluid viscosity detection principle, providing uninterrupted feedback on viscosity changes. The chilled water density acquisition component acquires the chilled water density parameter. Chilled water density directly affects the kinetic energy of fluid flow and is a necessary parameter for power loss calculation. The chilled water density acquisition component stably acquires this parameter through a density sensing module. The chilled water flow velocity acquisition component collects the flow velocity parameters of chilled water within the pipeline. Changes in flow velocity directly correlate with fluid resistance and transport efficiency within the pipeline, and this component monitors flow velocity fluctuations in real time. The pipeline cross-sectional area acquisition component collects the cross-sectional area parameters of the pipeline's interior, the pipeline equivalent length acquisition component collects the equivalent length parameters of the pipeline, and the pipeline inner diameter acquisition component collects the inner diameter parameters of the pipeline. These three types of pipeline structural parameters are fixed and unique, serving as the fundamental physical parameters for calculating pipeline resistance, and can be stored and used long-term after collection. The circulating water pump efficiency acquisition component collects the operating efficiency parameters of the circulating water pump. Circulating water pump efficiency changes with operating time and load conditions, directly affecting the actual power loss value. Each acquisition component collects key parameters related to chilled water and pipelines, comprehensively covering chilled water viscosity-temperature characteristics, flow state, and pipeline structural parameters, with no missing parameters or acquisition blind spots, providing comprehensive and accurate data support for subsequent power loss calculations.

[0023] In the existing technology, the collection of building thermal inertia-related parameters is inaccurate, leading to deviations in heat load calculation.

[0024] Based on this, the building thermal inertia acquisition unit includes a normalized building thermal inertia coefficient acquisition component, a real-time thermal inertia lag time acquisition component, a real-time indoor temperature acquisition component, an indoor set temperature acquisition component, and a reference temperature acquisition component. The normalized building thermal inertia coefficient acquisition component is connected to an embedded edge processor, and the real-time thermal inertia lag time acquisition component is also connected to the embedded edge processor. The normalized building thermal inertia coefficient acquisition component acquires basic building thermal inertia parameters. The normalized building thermal inertia coefficient is determined by the material, thickness, and heat storage capacity of the building envelope and is a core indicator reflecting the magnitude of building thermal inertia. The normalized building thermal inertia coefficient acquisition component obtains standardized coefficient values ​​through a building thermal performance testing module, eliminating parameter differences caused by different building structures. The real-time thermal inertia lag time acquisition component captures the dynamic changes in thermal inertia lag. Building thermal inertia causes a time lag in indoor temperature regulation. The lag time changes in real time with the outdoor environment and indoor load. The real-time thermal inertia lag time acquisition component continuously monitors the fluctuations in lag time, providing a dynamic basis for heat load correction. The indoor real-time temperature acquisition component collects real-time temperature parameters of the indoor space, while the indoor set temperature acquisition component collects set temperature parameters of the indoor space. The difference between the two is the fundamental variable for heat load calculation. Both the indoor real-time temperature acquisition component and the indoor set temperature acquisition component employ high-precision temperature sensing modules to ensure the accuracy of temperature parameter acquisition. The reference temperature acquisition component collects reference temperature parameters for system operation. The reference temperature is a standardized baseline temperature value used to unify the calculation standards for temperature parameters. All acquisition components work collaboratively without data conflicts or acquisition errors, ensuring the accuracy of building thermal inertia-related parameters and providing stable data support for subsequent effective heat load calculations.

[0025] In the existing technology, the calculation of additional power loss in pipelines is inaccurate, which leads to deviations in system power matching.

[0026] Based on this, the viscosity-temperature characteristic power loss calculation unit is equipped with a pipeline additional power loss formula, which is as follows: ; The Adding power loss to the pipeline, the The dimensionless correction coefficient, the For real-time cryogenic hydrodynamic viscosity, the For reference to the dynamic viscosity of chilled water, the The density of chilled water, the The chilled water flow rate, the The cross-sectional area of ​​the pipe is... For the equivalent length of the pipe, the The inner diameter of the pipe, the This refers to the efficiency of the circulating water pump. The theoretical basis of this formula comes from Darcy-Weisbach's formula in fluid mechanics. Friction loss is directly related to fluid viscosity, flow velocity, and pipe size. As the core heat transfer fluid in a central air conditioning system, chilled water's dynamic viscosity changes nonlinearly with ambient temperature. Traditional pipe loss calculation methods only consider flow velocity and pipe size as variables, without incorporating viscosity-temperature characteristics into the loss calculation system. This leads to a significant deviation between the calculated results and actual pipe losses, failing to reflect the true energy loss status. The logical derivation of the formula is as follows: First, the basic calculation logic of friction loss is determined using Darcy-Weisbach's formula. Friction loss is directly proportional to the friction coefficient, pipe length, fluid density, and the square of the flow velocity, and inversely proportional to the pipe inner diameter. Based on this, a direct correlation is established between the friction coefficient and the ratio of the real-time dynamic viscosity and the reference dynamic viscosity of the chilled water. Viscosity change is the core cause of friction coefficient fluctuations, and this ratio can accurately quantify the influence of viscosity-temperature characteristics on resistance. Then, combining the direct proportionality between volumetric flow rate, flow velocity, and pipe cross-sectional area, the fluid resistance loss is converted into the power loss that the circulating water pump needs to overcome. The power loss is the product of the resistance loss and the volumetric flow rate. Finally, the influence factor of circulating water pump efficiency is integrated; the higher the efficiency of the circulating water pump, the smaller the power loss required to overcome the same resistance. Through the integration and derivation of the above steps, a complete formula for calculating additional power loss in the pipeline is finally formed. This method is used to quantify the core impact of chilled water viscosity-temperature characteristics on pipeline resistance. The ratio of real-time dynamic viscosity to reference dynamic viscosity can intuitively reflect the resistance fluctuations caused by viscosity changes. It is dimensionless and the value changes with temperature in real time. It integrates flow parameters such as chilled water density, flow velocity, pipe cross-sectional area, and equivalent length, reflecting the kinetic energy loss during fluid flow and the energy consumption due to pipeline transport distance. It is the core calculation part of power loss. By combining the pipe's inner diameter and the circulating water pump's efficiency, the effect of pipe structural dimensions and pump operating efficiency on power loss is corrected. A larger pipe inner diameter and higher pump efficiency result in lower power loss. The dimensionless correction coefficient, obtained through extensive experimental fitting, is used to adapt to actual losses under different pipe diameters, fluid states, and operating conditions, eliminating errors between theoretical calculations and actual operation. The core innovation of this formula lies in incorporating the viscosity-temperature characteristics of chilled water as a core variable into the calculation of pipeline power loss. This breaks through the limitations of traditional methods that rely solely on flow velocity and pipe size for loss calculation. Through the coupled calculation of multiple physical parameters, it achieves accurate quantification of additional pipeline power loss. All parameters are acquired in real-time by corresponding acquisition components, ensuring that the calculation results closely match the actual operating state of the system. During the calculation process, the dimensions of each parameter strictly adhere to the principle of homogeneity, maintaining uniformity on both sides of the equation without any dimensional conflicts. This provides accurate loss data for subsequent heat load correction and is a fundamental calculation step for achieving system energy-saving optimization.

[0027] The existing technology lacks a clear logic for correcting effective heat load, leading to inaccurate heat load calculations.

[0028] Based on this, the effective heat load correction unit is equipped with an effective heat load correction formula, which is: ; The For effective heat load, the For the theoretical heat load, the The dimensionless correction coefficient, the The normalized building thermal inertia coefficient, the For real-time thermal inertia hysteresis time, the For reference to thermal inertia hysteresis time, the The indoor real-time temperature, the To set the indoor temperature, the For reference temperature, the The dimensionless correction coefficient, the For real-time heat exchange efficiency, the This formula is based on the heat load calculation theory and fluid loss compensation principle of building thermal engineering. Traditional central air conditioning heat load is simply calculated based on the temperature difference between indoor and outdoor environments, without considering the temperature regulation deviation caused by the thermal inertia lag of the building envelope, and without converting the power loss of chilled water pipes into heat load compensation. As a result, the calculated heat load value is seriously inconsistent with the actual indoor cooling demand, leading to system energy waste or insufficient cooling effect. The logical derivation of the formula is as follows: First, the theoretical heat load calculated using traditional temperature difference is used as the basis for calculation. Then, a multi-level correction factor for building thermal inertia is introduced. The normalized building thermal inertia coefficient, the ratio of real-time thermal inertia lag time to reference thermal inertia lag time, and the ratio of the difference between real-time indoor temperature and set temperature to reference temperature are continuously multiplied to form a building thermal inertia-specific correction term. This correction term can accurately compensate for the heat load calculation deviation caused by thermal inertia. Next, a compensation term for pipe additional power loss and the ratio of real-time heat exchange efficiency to reference heat exchange efficiency is added. This converts the previously calculated pipe power loss into a heat load compensation value. Pipe loss is considered ineffective energy consumption in the system and requires heat load compensation to achieve power matching. Finally, the theoretical heat load correction term and the pipe loss compensation term are integrated to obtain an effective heat load that fits the actual operating requirements. In the formula... The theoretical heat load, calculated using traditional temperature difference, is the basic value for heat load calculation and reflects the basic cooling demand caused by indoor temperature deviation.

[0029] For the building thermal inertia correction section, the normalized building thermal inertia coefficient reflects the heat storage and release capacity of the building envelope. The larger the coefficient, the stronger the thermal inertia and the more obvious the temperature regulation lag. The ratio of the real-time thermal inertia lag time to the reference thermal inertia lag time directly reflects the degree of temperature regulation lag. The longer the lag time, the greater the correction range. The difference between the real-time indoor temperature and the set temperature reflects the basic deviation of the heat load. The three factors are combined with the dimensionless correction coefficient to complete the accurate correction of building thermal inertia and eliminate the calculation error caused by thermal inertia. For the pipeline loss compensation section, the additional pipeline power loss obtained from the previous viscosity-temperature characteristic power loss calculation unit is combined with the ratio of real-time heat exchange efficiency to reference heat exchange efficiency to convert it into a heat load compensation value. The ratio of real-time heat exchange efficiency to reference heat exchange efficiency corrects the impact of efficiency fluctuations during the heat exchange process on loss compensation. The lower the heat exchange efficiency, the larger the loss compensation value, ensuring that the compensation result closely matches the actual heat exchange state. The core innovation of this formula lies in simultaneously incorporating building thermal inertia and pipeline power loss into the heat load correction system, breaking the limitations of traditional single-dimensional temperature correction, and achieving accurate conversion of theoretical heat load to actual effective heat load. All parameters are derived from real-time data from various acquisition units, and the dimensions of each parameter are completely consistent during the calculation process, with no calculation conflicts. This provides heat load data that closely matches the actual operating requirements of the system for subsequent optimal output power calculation, and is the core link connecting loss calculation and power optimization.

[0030] The existing technology has an imperfect logic for calculating the optimal output power, which leads to a mismatch between the system output power and the actual demand.

[0031] Based on this, the optimal output power calculation unit is configured with a system optimal output power formula, which is: .

[0032] The For the optimal output power of the system, the As the benchmark energy efficiency ratio, the The dimensionless correction coefficient, the The moisture content of the fresh air, the For reference moisture content, the For ambient temperature, the The dimensionless correction coefficient, the The Reynolds number of the chilled water flow regime is... The critical Reynolds number is used. The theoretical basis of this formula comes from the energy efficiency optimization theory of refrigeration systems and the principle of fluid flow control. Traditional central air conditioning output power calculation is determined only by the simple ratio of heat load to benchmark energy efficiency ratio, without considering the nonlinear effect of fresh air humidity on heat exchange efficiency, nor paying attention to the pipe efficiency loss caused by the deviation of chilled water flow from laminar flow state. This results in the system output power being too high, generating ineffective energy consumption, or the output power being too low, failing to meet the cooling demand. The logical derivation of the formula is as follows: First, the system's baseline output power is obtained by using the ratio of the effective heat load to the baseline energy efficiency ratio. This baseline output power is the theoretical power value that meets basic cooling requirements. Then, a nonlinear correction factor for fresh air humidity and ambient temperature is introduced. An exponential function weakens the correction effect of humidity under extreme high-temperature conditions, aligning with the changing patterns of humidity in actual cooling operation. Simultaneously, a quadratic correction factor for the chilled water flow state Reynolds number and critical Reynolds number is introduced. Fluid flow deviating from laminar flow significantly increases pipe resistance; the quadratic function accurately quantifies the efficiency loss caused by flow state deviation, reducing ineffective power redundancy. Finally, the optimal system output power, suitable for all operating conditions, is obtained by continuously multiplying the two correction factors by the baseline output power. In the formula... The baseline output power is the basic calculated value of the system output power, determined by the ratio of the effective heat load to the baseline energy efficiency ratio, reflecting the basic power required to meet actual cooling needs. For the fresh air humidity correction section, the difference between the fresh air humidity and the reference humidity reflects the impact of humidity on heat exchange efficiency. The higher the humidity, the lower the heat exchange efficiency, requiring an increase in output power to compensate for the efficiency loss. The exponential function setting makes the humidity correction effect more significant as the ambient temperature is closer to the reference temperature. When the ambient temperature is too high, the correction effect gradually weakens, which perfectly matches the actual cooling operation law of large central air conditioning. In the fluid flow regime correction section, the difference between the chilled water flow regime Reynolds number and the critical Reynolds number reflects the degree to which the fluid flow regime deviates from laminar flow. Once the Reynolds number exceeds the critical Reynolds number, the fluid becomes turbulent, and pipe resistance increases significantly. The quadratic function form means that the greater the flow regime deviation, the lower the power redundancy, actively reducing ineffective power consumption and avoiding energy waste. The core innovation of this formula lies in integrating multi-dimensional correction logic based on fresh air humidity, ambient temperature, and chilled water flow regime. This achieves precise matching between system output power and actual heat load and operating conditions, breaking through the limitations of traditional single heat load matching. All parameters are collected and calculated in real time by the corresponding acquisition units. During the calculation process, the dimensions fully comply with homogeneity requirements, with no calculation errors. This provides precise power control basis for the execution drive unit and is the core calculation link for achieving system energy-saving optimization.

[0033] The existing technology has an imperfect execution drive unit structure, which leads to inaccurate implementation of control commands.

[0034] Based on this, the execution drive unit includes a compressor drive component, a water pump drive component, and a fresh air valve drive component. The compressor drive component, the water pump drive component, and the fresh air valve drive component are all connected to the optimal output power calculation unit. The compressor drive component receives the control signal output by the optimal output power calculation unit and adjusts the compressor's operating frequency and output power according to the optimal output power value. As the core refrigeration equipment of the central air conditioning system, the compressor's output power directly determines the cooling capacity. The compressor drive component achieves precise adjustment of the compressor's operating state through power closed-loop control, eliminating power overshoot or undershoot. The water pump drive component receives the control signal output by the optimal output power calculation unit and adjusts the water pump's operating speed according to the optimal output power value. The water pump speed is directly related to the chilled water delivery flow rate and circulation efficiency. The water pump drive component achieves dynamic adjustment of the water pump's operating state through speed closed-loop control to match the chilled water delivery requirements. The fresh air valve drive component receives the control signal from the optimal output power calculation unit and adjusts the opening angle of the fresh air valve according to the optimal output power value. The opening angle of the fresh air valve determines the amount and humidity of fresh air entering. The fresh air valve drive component achieves precise adjustment of the fresh air volume through angle closed-loop control to match the system's heat exchange efficiency requirements. Each drive component corresponds to and controls the core execution equipment of the central air conditioning system, with no execution blind spots or control overlap. It accurately implements the control actions output by the optimal output power calculation unit, realizes synchronous and coordinated control of multiple devices, ensures comprehensive and accurate implementation of control commands, improves the coordination and accuracy of system control, and guarantees the precise execution of the optimal output power.

[0035] In existing technologies, the formula correction coefficients cannot be adaptively adjusted, leading to long-term deviations in calculation results.

[0036] Based on this, the edge computing main control unit includes a coefficient calibration unit, which is connected to the embedded edge processor, the viscosity-temperature characteristic power loss calculation unit, the effective heat load correction unit, and the optimal output power calculation unit. The coefficient calibration unit receives real-time operating data transmitted from the embedded edge processor, including the original parameters of the acquisition unit, the calculation results of the calculation unit, and the operating status data of the execution drive unit. It performs real-time comparison and analysis between the theoretical calculation results of each calculation unit and the actual operating parameters of the system. Based on the deviation value of the comparison results, it dynamically outputs a dimensionless correction coefficient calibration signal, independently calibrating the dimensionless correction coefficients in the viscosity-temperature characteristic power loss calculation unit, the effective heat load correction unit, and the optimal output power calculation unit. The calibration process is performed in real-time without delay, ensuring that the calculation logic of each formula continuously matches the actual operating conditions of the system. After the system has been running for a long time, equipment aging, changes in operating conditions, and changes in the environment can cause deviations in the initial correction coefficients. The coefficient calibration unit eliminates the calculation errors caused by long-term operation through continuous comparison and calibration, adapts to the operating status of different seasons, different loads, and different environments, ensures the long-term accuracy of the calculation results of each formula, avoids control failures caused by coefficient deviations, and improves the stability and continuity of system operation.

[0037] In existing technologies, computational data cannot be stored effectively, making data tracing and logic optimization inconvenient.

[0038] Based on this, the edge computing main control unit includes a data storage component connected to an embedded edge processor, a viscosity-temperature characteristic power loss calculation unit, an effective heat load correction unit, and an optimal output power calculation unit. The data storage component stores in real-time the raw data collected by the chilled water parameter acquisition unit, building thermal inertia acquisition unit, fresh air humidity acquisition unit, and pipeline fluid parameter acquisition unit, including all operating parameters such as real-time chilled water dynamic viscosity, chilled water density, normalized building thermal inertia coefficient, and fresh air humidity. The data storage format is standardized, with no data loss or distortion. The data storage component also stores in real-time the computational data from the viscosity-temperature characteristic power loss calculation unit, effective heat load correction unit, and optimal output power calculation unit, including all computational results such as pipeline additional power loss, effective heat load, and optimal system output power, completely recording the computational process and numerical changes. Finally, the data storage component stores in real-time the control command data from the execution drive unit, including all execution commands such as compressor control signals, water pump control signals, and fresh air valve control signals, retaining full-dimensional information of the control process. The data storage component retains complete operational data of the system from data acquisition and processing to instruction execution, providing comprehensive and reliable data support for system operation status tracing, correction coefficient calibration logic optimization, and equipment fault diagnosis. Maintenance personnel can quickly locate system operation problems through the stored data, optimize operation logic and control strategies, improve the convenience and efficiency of system operation and maintenance, and ensure the long-term stable operation of the system.

[0039] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. An edge control system for energy saving optimization of large central air conditioning systems, characterized in that, The edge control system includes an edge computing master control unit, a chilled water parameter acquisition unit, a building thermal inertia acquisition unit, a fresh air humidity acquisition unit, a pipeline fluid parameter acquisition unit, a viscosity-temperature characteristic power loss calculation unit, an effective heat load correction unit, an optimal output power calculation unit, and an execution drive unit. The chilled water parameter acquisition unit is connected to the edge computing master control unit, the building thermal inertia acquisition unit is connected to the edge computing master control unit, the fresh air humidity acquisition unit is connected to the edge computing master control unit, the pipeline fluid parameter acquisition unit is connected to the edge computing master control unit, the viscosity-temperature characteristic power loss calculation unit is connected to the edge computing master control unit, the effective heat load correction unit is connected to the viscosity-temperature characteristic power loss calculation unit, the optimal output power calculation unit is connected to the effective heat load correction unit, and the execution drive unit is connected to the optimal output power calculation unit.

2. The edge control system for energy saving optimization of large central air conditioning system according to claim 1, wherein, The edge computing main control unit includes an embedded edge processor, which is connected to a chilled water parameter acquisition unit, a building thermal inertia acquisition unit, a fresh air humidity acquisition unit, a pipeline fluid parameter acquisition unit, and a viscosity-temperature characteristic power loss calculation unit.

3. The edge control system for energy-saving optimization of large central air conditioning systems according to claim 2, characterized in that, The chilled water parameter acquisition unit includes a real-time chilled water dynamic viscosity acquisition component, a chilled water density acquisition component, a chilled water flow velocity acquisition component, a pipe cross-sectional area acquisition component, a pipe equivalent length acquisition component, a pipe inner diameter acquisition component, and a circulating water pump efficiency acquisition component. The real-time chilled water dynamic viscosity acquisition component is connected to an embedded edge processor, the chilled water density acquisition component is connected to an embedded edge processor, and the chilled water flow velocity acquisition component is connected to an embedded edge processor.

4. The edge control system for energy-saving optimization of large central air conditioning systems according to claim 3, characterized in that, The building thermal inertia acquisition unit includes a normalized building thermal inertia coefficient acquisition component, a real-time thermal inertia lag time acquisition component, an indoor real-time temperature acquisition component, an indoor set temperature acquisition component, and a reference temperature acquisition component. The normalized building thermal inertia coefficient acquisition component is connected to an embedded edge processor, and the real-time thermal inertia lag time acquisition component is connected to an embedded edge processor.

5. The edge control system for energy-saving optimization of large central air conditioning systems according to claim 4, characterized in that, The viscosity-temperature characteristic power loss calculation unit is equipped with a pipeline additional power loss formula, which is as follows: ， The Adding power loss to the pipeline, the The dimensionless correction coefficient, the For real-time cryogenic hydrodynamic viscosity, the For reference to the dynamic viscosity of chilled water, the The density of chilled water, the The chilled water flow rate, the The cross-sectional area of ​​the pipe is... For the equivalent length of the pipe, the The inner diameter of the pipe, the For circulating water pump efficiency.

6. The edge control system for energy-saving optimization of large central air conditioning systems according to claim 5, characterized in that, The effective heat load correction unit establishes a data transmission link with the viscosity-temperature characteristic power loss calculation unit. The effective heat load correction unit receives the pipeline additional power loss data output by the viscosity-temperature characteristic power loss calculation unit, and the effective heat load correction unit receives the collected data output by the building thermal inertia acquisition unit.

7. The edge control system for energy-saving optimization of large central air conditioning systems according to claim 6, characterized in that, The optimal output power calculation unit establishes a data transmission link with the effective heat load correction unit. The optimal output power calculation unit receives the correction data output by the effective heat load correction unit, the optimal output power calculation unit receives the acquisition data output by the fresh air humidity acquisition unit, and the optimal output power calculation unit receives the acquisition data output by the pipeline fluid parameter acquisition unit.

8. The edge control system for energy-saving optimization of large central air conditioning systems according to claim 7, characterized in that, The execution drive unit includes a compressor drive component, a water pump drive component, and a fresh air valve drive component. The compressor drive component is connected to the optimal output power calculation unit, the water pump drive component is connected to the optimal output power calculation unit, and the fresh air valve drive component is connected to the optimal output power calculation unit.

9. The edge control system for energy-saving optimization of large central air conditioning systems according to claim 8, characterized in that, The edge computing main control unit includes a coefficient calibration unit, which is connected to the embedded edge processor, a viscosity-temperature characteristic power loss calculation unit, an effective heat load correction unit, and an optimal output power calculation unit.

10. The edge control system for energy-saving optimization of large central air conditioning systems according to claim 9, characterized in that, The edge computing main control unit includes a data storage component, which is connected to an embedded edge processor, a viscosity-temperature characteristic power loss calculation unit, an effective heat load correction unit, and an optimal output power calculation unit.

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