A chiller plant energy efficiency optimization system and method

Abstract

The application discloses a refrigeration machine room energy efficiency optimization system and method, relates to the technical field of machine room energy efficiency optimization, and comprises a load characteristic analysis module, an equipment combination screening module, a dynamic switching module and a cross-equipment collaborative optimization module. The load characteristic analysis module is used for outputting a load characteristic analysis result. The equipment combination screening module is used for screening an optimal equipment combination with the highest combination COP according to a current real-time load, wherein the total refrigeration capacity of the optimal equipment combination meets the demand. The dynamic switching module is used for triggering dynamic switching of the equipment combination. The cross-equipment collaborative optimization module adjusts core operation parameters of a cooling tower and a cooling / freezing water pump speed based on an operation state of the optimal equipment combination and outdoor temperature and humidity data through closed-loop control logic, so that operation environment parameters of the refrigeration machine are maintained in a preset target interval, and water flow and the refrigeration machine load are matched.

Description

Technical Field

[0001] This invention relates to the field of data center energy efficiency optimization technology, specifically a system and method for optimizing the energy efficiency of a refrigeration data center. Background Technology

[0002] In the current field of refrigeration room operation optimization, there is a common problem: equipment combination design lacks precise adaptation to annual cooling load and outdoor temperature and humidity changes. Many systems use single-capacity or single-type equipment configurations, making it difficult to balance operational efficiency across low, medium, and high load ranges. Furthermore, the selection of equipment combinations lacks scientific energy efficiency models, easily leading to mismatches between cooling capacity and load demand, and low energy efficiency ratios. In addition, equipment such as chillers, cooling towers, and water pumps in the computer room are mostly independently controlled, failing to achieve closed-loop coordinated regulation across equipment. Key parameters such as chiller condensing temperature and water flow rate cannot be dynamically adapted to load and environmental changes, often resulting in problems such as "high flow rate with small temperature difference" under low load and insufficient heat exchange under high load. Moreover, there is no clear energy efficiency breakpoint threshold for equipment combination switching, leading to frequent switching due to small load fluctuations, resulting in low overall energy efficiency and high energy consumption in the computer room, failing to achieve efficient and energy-saving operation under all operating conditions. Summary of the Invention

[0003] To achieve the above objectives, the present invention provides the following technical solution: a method for optimizing the energy efficiency of a refrigeration room, the method comprising:

[0004] Step S1: Collect the annual cooling load data and outdoor temperature and humidity of the refrigeration room, divide it into low, medium and high load ranges and analyze the duration and fluctuation frequency of each range. Based on the principles of load coverage integrity and optimal energy efficiency, design a combination of large and small capacity + fixed frequency + variable frequency equipment. Outdoor temperature and humidity are key environmental factors affecting cooling load demand and chiller operating efficiency.

[0005] Step S2: Establish an equipment energy efficiency database, obtain a single equipment energy efficiency ratio calculation model by fitting the equipment load rate-energy efficiency ratio curve, construct a combined energy efficiency ratio optimization model based on the current real-time load, and screen out the operating combination with the highest combined energy efficiency ratio that meets the load demand in terms of total cooling capacity.

[0006] Step S3: Define adjacent equipment combinations with continuous capacity coverage, calculate the combination switching threshold based on the energy efficiency breakpoint mathematical model, set the load fluctuation redundancy, and trigger equipment combination switching when the real-time load reaches the switching threshold.

[0007] Step S4: Based on the optimal equipment combination operating status selected in Step S2 and the outdoor temperature and humidity data collected in Step S1, the operating parameters of the cooling tower and the speed of the cooling / chilled water pump are adaptively adjusted through a closed-loop control logic of graded adjustment and dynamic verification. This ensures that the chiller condensing temperature is maintained within the target range and the water flow rate matches the chiller load demand, thereby achieving a closed-loop coordinated energy efficiency improvement of "equipment combination - environmental parameters - auxiliary equipment".

[0008] Furthermore, step S1 includes the following specific steps:

[0009] Step S11: Based on the annual cooling load data, extract the maximum cooling load value of the refrigeration room as the peak cooling load Q. max According to the proportion of cooling load to Q max The ratio is divided into three intervals, including the low load Q1∈[0,0.3Q]. max ], Medium load Q2∈(0.3Q max 0.7Q max High load Q3∈(0.7Q) max Q max ];

[0010] Step S12: Extract the load factor β∈[0.6,0.9] and determine the single unit capacity Q of the minimum capacity inverter. b1 The range of values ​​for Q b1 ∈[0.6Q 1max Q 1max ], where Q 1max =0.3Q max Inverter motors are prone to operational malfunctions such as poor oil return when the load rate is below 30%, and their energy efficiency drops sharply; when the load rate is above 90%, they approach overload; by setting Q... b1 ≥0.6Q 1max This ensures that the inverter load rate is always maintained within the safe and efficient range of β≥0.5 in the low load range; by collecting the performance curves of inverter manufacturers, models with an energy efficiency ratio greater than or equal to 4.5 at a load rate β∈[0.6,0.9] are selected.

[0011] Determine the single-unit capacity Q of a large-capacity fixed-frequency machine. d Q d ≥0.5*(Q) max -Q b1 ); deducting low-load dedicated capacity Q b1 Afterwards, the remaining capacity is mainly used to handle medium to high loads. Setting the capacity of the fixed-frequency generator to more than 50% of the remaining capacity is to avoid over-reliance on the variable-frequency generator to handle medium to high loads, reduce investment costs, and take advantage of the high energy efficiency of the fixed-frequency generator under rated load; the energy efficiency ratio of the fixed-frequency generator is greater than or equal to 4.8 when the rated load rate β=1.0.

[0012] Step S13: Calculate the minimum number of fixed-frequency units n and variable-frequency units m to satisfy the total capacity Q. t =n*Q d +m*Q b1 ≥Q max And n≥1, m≥1; Based on the above parameters, generate multiple candidate combinations of "number of fixed frequency machines + capacity of large-capacity fixed frequency machines + number of variable frequency machines + capacity of small-capacity variable frequency machines" that meet the conditions; If the proportion of low load is high, the parameters of small-capacity variable frequency machines need to be optimized; If the medium load fluctuates frequently, the number of variable frequency machines needs to be increased.

[0013] Step S14: Based on the equipment data under each candidate combination, calculate the average energy efficiency E for each load range included in the combination. k E k =(∑Q k,i ) / (∑P k,i ), k=1, 2, 3 correspond to low, medium, and high load ranges respectively, Q k,i P represents the total cooling capacity at time i within interval k. k,i This represents the total power consumption at time i within the k-th interval; using the formula: E a =a1*E1+a2*E2+a3*E3, calculate the annual average energy efficiency E a Where a1, a2, and a3 represent the duration percentages of each load interval; E1, E2, and E3 correspond to the average energy efficiency of the low, medium, and high load intervals; calculate the annual average energy efficiency of the candidate combinations to provide a quantitative basis for combination selection;

[0014] Step S15: Select the candidate combination with the highest Ea as the final mixing device combination.

[0015] Furthermore, step S2 includes the following specific steps:

[0016] Step S21: When the single device is a fixed-frequency unit, obtain the coefficient of performance (COP) of the fixed-frequency unit under rated load. 额 When the load rate deviates from the rated value, it should be corrected according to the manufacturer's curve, using the correction formula COP. dβ =COP 额 *k d *β; where k d This is the load correction factor for the fixed-frequency machine;

[0017] When a single device is a frequency converter, the "load rate - COP" curve of the device is fitted by a quadratic function, and the formula is COP. bβ =a×β²+b×β+d, where a, b, and d are fitting coefficients, and β∈[0.3,1.1];

[0018] When it is a combined device, COP 组合 =Total cooling capacity ∑Q j0 / Total power consumption ∑Pj Q j0 P represents the actual cooling capacity after the j-th device is started. j =Q j0 / COP j COP j This represents the energy efficiency ratio of the j-th operating device.

[0019] Step S22: Obtain the real-time cooling load Q L Set constraints, ∑(x j *Q j0 )≥Q L Q j0 =x j *Q j *β j ,

[0020] Where x j Let x represent the decision variable. j ∈{0,1}, when x j =1 indicates that device j is started, x j =0 indicates that device j is not started;

[0021] β j β represents the load factor of the j-th device. j =(x j *Q j0 ) / Q j ;β j ∈[βmin,βmax];

[0022] Q j This represents the rated capacity of the j-th device in the device set.

[0023] Set the objective function as COPmax, where COPmax = ∑(x j *Q j0 ) / ∑(x j *Q j0 / COP j (β j COP j (β j () represents the energy efficiency model of the equipment, indicating that the j-th equipment in the equipment set operates at a load factor β. j The energy efficiency ratio of a single unit;

[0024] Step S23: Enumerate all equipment combinations that satisfy the constraints and generate a candidate solution set; calculate the total cooling capacity Qt, total power consumption Pt, and combination COP for each combination in the candidate solution set; eliminate combinations with Qt... t L For invalid combinations, the combination with the highest COPmax among the remaining valid combinations is selected as the optimal running combination.​

[0025] Furthermore, step S3 includes the following steps:

[0026] Step S31: Continuous connection of capacity coverage means that the maximum output capacity of equipment combination A is the same as or the difference between the minimum output capacity of equipment combination B and the maximum output capacity of equipment combination A is less than or equal to the minimum unit capacity.

[0027] Step S32: Make the total power consumption of adjacent combinations A and B equal, and establish equation P. A (Q)=P B (Q), where P A (Q) is the total power consumption function of combination A under load Q, P B (Q) is the total power consumption function of combination B under load Q; using the formula: P A (Q)=Σ(Q Aj / COP Aj (β Aj )), P B (Q)=Σ(Q Bj / COP Bj (β Bj )), Q Aj Q represents the actual cooling capacity of the j-th device in combination A. Bj Let P represent the actual cooling capacity of the j-th device in combination B; solve the simultaneous equations P A (Q)=P B (Q), the energy efficiency breakpoint Q0 is obtained by solving (Q);

[0028] Step S33: Based on the energy efficiency breakpoint Q0, calculate the combined switching threshold Qw, Qw = Q0 + ΔQ, where ΔQ is the redundancy; ΔQ = 0.1 * Q 前组合最大容量 .

[0029] Furthermore, the closed-loop control logic in step S4 includes chiller-cooling tower linkage control and chiller-water pump linkage control, including the following processes:

[0030] The chiller-cooling tower linkage control includes real-time acquisition of core environmental parameters of the chiller operation, outdoor temperature and humidity parameters, and current operating parameters of the cooling tower; calculation of the deviation between the core environmental parameters of the chiller and the preset target range; adjustment of the airflow drive parameters and spray flow parameters of the cooling tower in stages according to the magnitude of the deviation, while taking into account the outdoor temperature and humidity for environmental adaptation correction to ensure that the adjustment actions match environmental changes and chiller requirements; and collection of parameters at preset intervals to verify whether the core environmental parameters of the chiller have returned to the target range. If they do not meet the target, the staged adjustment steps are repeated until the requirements are met.

[0031] The chiller-pump linkage control includes real-time acquisition of the optimal combination of total chiller load, individual chiller load rate, current pump operating parameters, and water flow temperature difference parameters; based on the total chiller load and the preset water flow temperature difference target, the target water flow rate is adapted to the current chiller load; according to the correlation between flow rate and speed, the pump speed is adjusted to match the target water flow rate, and corrections are made in conjunction with the individual chiller load rate. The purpose of the correction is to avoid the problem of "large flow rate and small temperature difference" under low load or insufficient heat exchange under high load; and water flow rate and temperature difference data are collected at preset intervals to verify whether they meet the target requirements. If there is a deviation, the speed is recalculated and adjusted.

[0032] A chiller room energy efficiency optimization system, the system includes a load characteristic analysis module, an equipment combination screening module, a dynamic switching module and a cross-equipment collaborative optimization module;

[0033] The load characteristic analysis module is used to collect annual cooling load data of the refrigeration room, outdoor temperature and humidity, divide low, medium and high load intervals, analyze the duration and fluctuation frequency of each interval, and output load characteristic analysis results.

[0034] Based on the load characteristic analysis results, the equipment combination screening module constructs a mixed equipment combination library of "large and small capacity + fixed frequency + variable frequency", establishes an equipment energy efficiency database and a combination COP optimization model, and selects the optimal equipment combination with the highest combination COP based on the current real-time load;

[0035] The dynamic switching module defines a combination of adjacent devices with continuous capacity coverage. It calculates the switching threshold based on the "energy efficiency breakpoint" mathematical model. When the real-time load exceeds the optimal range of the current combination or reaches the switching threshold, it triggers dynamic switching of the device combination.

[0036] The cross-device collaborative optimization module adjusts the core operating parameters of the cooling tower and the speed of the cooling / chilled water pumps through closed-loop control logic based on the operating status of the optimal equipment combination and outdoor temperature and humidity data, so that the operating environment parameters of the chiller are maintained within the preset target range and the water flow rate is matched with the chiller load.

[0037] Furthermore, the equipment combination screening module includes a combination generation unit and an optimal screening unit;

[0038] The combination generation unit is used to extract peak cooling load based on the annual cooling load data, divide different intervals, and determine the parameters of small-capacity variable frequency machines and large-capacity fixed frequency machines based on the interval data, as well as calculate the minimum number of fixed frequency machines and variable frequency machines that meet the screening conditions, and generate candidate combinations.

[0039] The optimal selection unit is used to calculate the annual average energy efficiency of each candidate combination, and selects the combination with the highest annual average energy efficiency as the optimal equipment combination.

[0040] Furthermore, the cross-device collaborative optimization module includes a chiller-cooling tower linkage unit and a chiller-water pump linkage unit;

[0041] The chiller-cooling tower linkage unit adjusts the cooling tower airflow drive parameters and spray flow rate through a closed-loop logic of "parameter acquisition - deviation calculation - graded adjustment - iterative verification" combined with outdoor temperature and humidity correction.

[0042] The chiller-pump linkage unit calculates the target flow rate based on the total chiller load and the preset water flow temperature difference target. It adjusts the water pump speed according to the relationship between flow rate and speed, and combines the single chiller load rate correction. Through dynamic verification, it ensures that the water flow parameters meet the target requirements.

[0043] Compared with the prior art, the beneficial effects of the present invention are:

[0044] This invention significantly improves the overall energy efficiency of the refrigeration room. Through scientific equipment combination and matching, dynamic screening and cross-equipment collaborative control, it ensures that the equipment operates in a high-efficiency state throughout the full load range and effectively reduces the energy consumption of the room. It avoids the energy waste caused by inefficient equipment operation and flow redundancy in the traditional operation mode, and achieves the goal of energy saving and consumption reduction.

[0045] This invention avoids adverse operating conditions such as equipment overload and inefficient operation by combining reasonable switching logic and precise parameter adjustment, thereby reducing equipment wear and tear. Based on a quantitative model and clear variable definition, it avoids errors caused by experience-based operations, thus improving the operability and replicability of the method.

[0046] A closed-loop optimization system is formed for the entire process, and a complete technical chain of "load analysis - combination screening - dynamic switching - collaborative optimization" is constructed to fill the shortcomings of traditional solutions in the whole process optimization. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of the structure of a method for optimizing the energy efficiency of a refrigeration room according to the present invention. Detailed Implementation

[0048] Example: Figure 1 As shown, the present invention provides a method for optimizing the energy efficiency of a refrigeration room, the method comprising:

[0049] Step S1: Collect the annual cooling load data and outdoor temperature and humidity of the refrigeration room, divide it into low, medium and high load ranges and analyze the duration and fluctuation frequency of each range. Based on the principles of load coverage integrity and optimal energy efficiency, design a combination of large and small capacity + fixed frequency + variable frequency equipment. Outdoor temperature and humidity are key environmental factors affecting cooling load demand and chiller operating efficiency.

[0050] Step S2: Establish an equipment energy efficiency database, obtain a single equipment energy efficiency ratio calculation model by fitting the equipment load rate-energy efficiency ratio curve, construct a combined energy efficiency ratio optimization model based on the current real-time load, and screen out the operating combination with the highest combined energy efficiency ratio that meets the load demand in terms of total cooling capacity.

[0051] Step S3: Define adjacent equipment combinations with continuous capacity coverage, calculate the combination switching threshold based on the energy efficiency breakpoint mathematical model, set the load fluctuation redundancy, and trigger equipment combination switching when the real-time load reaches the switching threshold.

[0052] Step S4: Based on the optimal equipment combination operating status selected in Step S2 and the outdoor temperature and humidity data collected in Step S1, the operating parameters of the cooling tower and the speed of the cooling / chilled water pump are adaptively adjusted through a closed-loop control logic of graded adjustment and dynamic verification. This ensures that the chiller condensing temperature is maintained within the target range and the water flow rate matches the chiller load demand, thereby achieving a closed-loop coordinated energy efficiency improvement of "equipment combination - environmental parameters - auxiliary equipment".

[0053] Step S1 includes the following specific steps:

[0054] Step S11: Based on the annual cooling load data, extract the maximum cooling load value of the refrigeration room as the peak cooling load Q. max According to the proportion of cooling load to Q max The ratio is divided into three intervals, including the low load Q1∈[0,0.3Q]. max ], Medium load Q2∈(0.3Q max 0.7Q max High load Q3∈(0.7Q) max Q max ];

[0055] Step S12: Extract the load factor β∈[0.6,0.9] and determine the single unit capacity Q of the minimum capacity inverter. b1 The range of values ​​for Q b1 ∈[0.6Q 1max Q 1max ], where Q 1max =0.3Q max Inverter motors are prone to operational malfunctions such as poor oil return when the load rate is below 30%, and their energy efficiency drops sharply; when the load rate is above 90%, they approach overload; by setting Q... b1 ≥0.6Q 1max This ensures that the inverter load rate is always maintained within the safe and efficient range of β≥0.5 in the low load range; by collecting the performance curves of inverter manufacturers, models with an energy efficiency ratio greater than or equal to 4.5 at a load rate β∈[0.6,0.9] are selected.

[0056] Determine the single-unit capacity Q of a large-capacity fixed-frequency machine.d Q d ≥0.5*(Q) max -Q b1 ); deducting low-load dedicated capacity Q b1 Afterwards, the remaining capacity is mainly used to handle medium to high loads. Setting the capacity of the fixed-frequency generator to more than 50% of the remaining capacity is to avoid over-reliance on the variable-frequency generator to handle medium to high loads, reduce investment costs, and take advantage of the high energy efficiency of the fixed-frequency generator under rated load; the energy efficiency ratio of the fixed-frequency generator is greater than or equal to 4.8 when the rated load rate β=1.0.

[0057] Step S13: Calculate the minimum number of fixed-frequency units n and variable-frequency units m to satisfy the total capacity Q. t =n*Q d +m*Q b1 ≥Q max And n≥1, m≥1; Based on the above parameters, generate multiple candidate combinations of "number of fixed frequency machines + capacity of large-capacity fixed frequency machines + number of variable frequency machines + capacity of small-capacity variable frequency machines" that meet the conditions; If the proportion of low load is high, the parameters of small-capacity variable frequency machines need to be optimized; If the medium load fluctuates frequently, the number of variable frequency machines needs to be increased.

[0058] Step S14: Based on the equipment data under each candidate combination, calculate the average energy efficiency E for each load range included in the combination. k E k =(∑Q k,i ) / (∑P k,i ), k=1, 2, 3 correspond to low, medium, and high load ranges respectively, Q k,i P represents the total cooling capacity at time i within interval k. k,i This represents the total power consumption at time i within the k-th interval; using the formula: E a =a1*E1+a2*E2+a3*E3, calculate the annual average energy efficiency E a Where a1, a2, and a3 represent the duration percentages of each load interval; E1, E2, and E3 correspond to the average energy efficiency of the low, medium, and high load intervals; calculate the annual average energy efficiency of the candidate combinations to provide a quantitative basis for combination selection;

[0059] Step S15: Select the candidate combination with the highest Ea as the final mixing device combination.

[0060] Step S2 includes the following specific steps:

[0061] Step S21: When the single device is a fixed-frequency unit, obtain the coefficient of performance (COP) of the fixed-frequency unit under rated load. 额 When the load rate deviates from the rated value, it should be corrected according to the manufacturer's curve, using the correction formula COP. dβ =COP 额 *k d *β; where kd This is the load correction factor for the fixed-frequency machine;

[0062] When a single device is a frequency converter, the "load rate - COP" curve of the device is fitted by a quadratic function, and the formula is COP. bβ =a×β²+b×β+d, where a, b, and d are fitting coefficients, and β∈[0.3,1.1];

[0063] When it is a combined device, COP 组合 =Total cooling capacity ∑Q j0 / Total power consumption ∑P j Q j0 P represents the actual cooling capacity after the j-th device is started. j =Q j0 / COP j COP j This represents the energy efficiency ratio of the j-th operating device.

[0064] Step S22: Obtain the real-time cooling load Q L Set constraints, ∑(x j *Q j0 )≥Q L Q j0 =x j *Q j *β j ,

[0065] Where x j Let x represent the decision variable. j ∈{0,1}, when x j =1 indicates that device j is started, x j =0 indicates that device j is not started;

[0066] β j β represents the load factor of the j-th device. j =(x j *Q j0 ) / Q j ;β j ∈[βmin,βmax];βmin=0.3,βmax=1.1;

[0067] Q j This represents the rated capacity of the j-th device in the device set.

[0068] Set the objective function as COPmax, where COPmax = ∑(x j *Q j0 ) / ∑(x j *Q j0 / COP j (β j COPj (β j () represents the energy efficiency model of the equipment, indicating that the j-th equipment in the equipment set operates at a load factor β. j The single-unit energy efficiency ratio; COP j (β j The calculation method is the same as that in the combined COP calculation, and is the same as COP. 组合 The difference is that it refers to the global index in the set of devices;

[0069] Step S23: Enumerate all equipment combinations that satisfy the constraints to generate a candidate solution set; calculate the total cooling capacity Qt, total power consumption Pt, and combined COP for each combination in the candidate solution set; eliminate combinations with Qt... t L For invalid combinations, the combination with the highest COPmax among the remaining valid combinations is selected as the optimal running combination.

[0070] As shown in the example: the equipment set D = {d1 (1000RT fixed frequency machine), d2 (1000RT fixed frequency machine), d3 (600RT variable frequency machine)}, then the rated capacity Q1 = 1000RT, Q2 = 1000RT, Q3 = 600RT;

[0071] If the candidate combination is "d1+d3", then j=1 corresponds to d1, j=2 corresponds to d3, and the actual cooling capacity is Q1=1000RT×β1 (β1 is the load rate of d1) and Q2=600RT×β2 (β2 is the load rate of d3).

[0072] Candidate combination 1 (d1+d3): x1=1, x3=1, x2=0;

[0073] β1 = 1.0 (d1 at full load), Q1 = 1000RT × 1.0 = 1000RT, COP1 = COP 1(1.0) =4.8;

[0074] β2=(1200-1000) / 600≈0.33, Q2=600RT×0.33≈200RT,

[0075] COP2=COP 3(0.33) =-0.5×0.33²+6.0×0.33≈3.8;

[0076] Total cooling capacity: Qt = 1000 + 200 = 1200 RT

[0077] Total power consumption:

[0078] Pt=(1000×3.517) / 4.8+(200×3.517) / 3.8≈732.7+182.4=915.1kW; ​

[0079] The combined COP = 4210 / 915.1 ≈ 4.6;

[0080] Candidate combination 2 (d3+d3, assuming the equipment set includes two 600RT frequency converters d3 and d4): x3=1, x4=1;

[0081] β3=1.0, β4=1.0, Q3=600RT, Q4=600RT, COP3=COP4=5.0;

[0082] Total cooling capacity Qt = 600 + 600 = 1200 RT

[0083] Total power consumption Pt = (600 × 3.517) / 5.0 × 2 = 843.6 kW;

[0084] The combined COP = 4218 / 843.6 ≈ 5.0;

[0085] Remove Q t L After eliminating invalid combinations, the combination with the highest COP is selected, i.e., combination 2 is selected in the example.

[0086] Step S3 includes the following steps:

[0087] Step S31: Continuous connection of capacity coverage means that the maximum output capacity of equipment combination A is the same as or the difference between the minimum output capacity of equipment combination B and the maximum output capacity of equipment combination A is less than or equal to the minimum unit capacity.

[0088] Step S32: Make the total power consumption of adjacent combinations A and B equal, and establish equation P. A (Q)=P B (Q), where P A (Q) is the total power consumption function of combination A under load Q, P B (Q) is the total power consumption function of combination B under load Q; using the formula: P A (Q)=Σ(Q Aj / COP Aj (β Aj )), P B (Q)=Σ(Q Bj / COP Bj (β Bj )), Q Aj Q represents the actual cooling capacity of the j-th device in combination A. Bj Let P represent the actual cooling capacity of the j-th device in combination B; solve the simultaneous equations P A (Q)=P B (Q), the energy efficiency breakpoint Q0 is obtained by solving (Q);

[0089] ​Step S33: Based on the energy efficiency breakpoint Q0, calculate the combined switching threshold Qw, Qw = Q0 + ΔQ, where ΔQ is the redundancy; ΔQ = 0.1 * Q 前组合最大容量 .

[0090] The closed-loop control logic in step S4 includes the chiller-cooling tower linkage control and the chiller-water pump linkage control, and includes the following processes:

[0091] The chiller-cooling tower linkage control includes real-time acquisition of core environmental parameters of the chiller operation, outdoor temperature and humidity parameters, and current operating parameters of the cooling tower; calculation of the deviation between the core environmental parameters of the chiller and the preset target range; adjustment of the airflow drive parameters and spray flow parameters of the cooling tower in stages according to the magnitude of the deviation, while taking into account the outdoor temperature and humidity for environmental adaptation correction to ensure that the adjustment actions match environmental changes and chiller requirements; and collection of parameters at preset intervals to verify whether the core environmental parameters of the chiller have returned to the target range. If they do not meet the target, the staged adjustment steps are repeated until the requirements are met.

[0092] As shown in the example: Real-time acquisition of chiller condensing temperature T1, outdoor temperature and humidity (dry bulb temperature T2, wet bulb temperature T3) collected and updated in real time in step S1, current cooling tower fan frequency f1, and spray flow rate L1;

[0093] Calculate the deviation value ΔT = T1 - T0 between the core environmental parameters of the chiller and the preset target range, where T0 is the target condensing temperature; the default is 30℃, which can be finely adjusted according to the chiller model.

[0094] When ΔT > 2℃ (T1 > 32℃), adjust the fan frequency as follows: fnew = f1 + min(10Hz, 0.5 × ΔT × 5Hz), and fnew ≤ 50Hz (fan rated frequency); if fnew has reached 50Hz but still does not meet T1 ≤ 32℃, then increase the spray flow rate Lnew = L1 × (1 + 0.1 × ΔT), and Lnew ≤ 1.5 × Lr, where Lr represents the rated flow rate of the spray pump; iterative correction: collect T1 every 5 minutes, and if ΔT > 2℃, repeat the above adjustment until T1 ≤ 32℃;

[0095] When ΔT < -2℃ (T1 < 28℃), adjust the fan frequency as follows: fnew = f1 - min(8Hz, 0.5 × |ΔT| × 5Hz), and fnew ≥ 20Hz (the minimum stable frequency of the fan); if fnew has reached 20Hz but T1 < 28℃, reduce the spray flow rate Lnew = L1 × (1 - 0.08 × |ΔT|), and Lnew ≥ 0.7 × Lr; iterative correction: collect T1 every 5 minutes, and if ΔT is still < -2℃, repeat the above adjustment until T1 ≥ 28℃;

[0096] When |ΔT|≤2℃ (28℃≤T1≤32℃): Maintain the current fan frequency and spray flow rate, and check the parameters every 10 minutes;

[0097] If the outdoor wet-bulb temperature Tw > 28℃, increase the fan frequency by an additional 5Hz on top of the above adjustments; if Tw < 22℃, decrease the fan frequency by an additional 5Hz to ensure the adjustments are adapted to environmental changes.

[0098] The chiller-pump linkage control includes real-time acquisition of the optimal combination of total chiller load, individual chiller load rate, current pump operating parameters, and water flow temperature difference parameters; based on the total chiller load and the preset water flow temperature difference target, the target water flow rate is adapted to the current chiller load; according to the correlation between flow rate and speed, the pump speed is adjusted to match the target water flow rate, and corrections are made in conjunction with the individual chiller load rate. The purpose of the correction is to avoid the problem of "large flow rate and small temperature difference" under low load or insufficient heat exchange under high load; and water flow rate and temperature difference data are collected at preset intervals to verify whether they meet the target requirements. If there is a deviation, the speed is recalculated and adjusted.

[0099] As shown in the example: Real-time acquisition of the total cooling capacity Qt of the chiller in the optimal combination in step 2, the load rate βi of a single chiller, the current cooling water pump speed n1, the chilled water pump speed n2, and the cooling / chilled water supply and return temperature difference ΔTw and ΔTh;

[0100] Based on the relationship between cooling capacity of the refrigeration system and water temperature difference, the target cooling water volume L is calculated. 目1 =Qt / (4.186×ρ×ΔT w0 ), target chilled water volume (L) 目2 =Qt / (4.186×ρ×ΔT h0 ), where ρ is the density of water (1000 kg / m³), ΔT w0 =5℃ (target cooling water temperature difference), ΔT h0 =6℃ (target temperature difference of chilled water);

[0101] Cooling water pump adjustment: Based on the direct proportional relationship between flow rate and speed (n) wnew =n1×(L 目1 / L w0 ), where L w0 Current cooling water volume (collected by a flow meter); n new n must satisfy cwmin ≤n new ≤n wmax (Rated speed of water pump ±30%)

[0102] Chilled water pump adjustment: Similarly n hnew =n2×(L 目2 / L h0 ), where / L h0The current chilled water volume (collected via a flow meter); n hnew n must satisfy hmin ≤n hnew ≤n hmax ;

[0103] Load factor adaptation correction: If the load factor βi of a single chiller is less than 0.5 (low load), reduce the water pump speed by 5%-8% based on the above calculation results to avoid "high flow rate and small temperature difference"; if βi is greater than 0.8 (high load), increase the water pump speed by 3%-5% to ensure sufficient heat exchange of the chiller.

[0104] Water volume and temperature difference data are collected every 3 minutes. If ΔTw deviates from the target value by ±1℃ and ΔTh deviates from the target value by ±0.5℃, the rotation speed is recalculated and adjusted.

[0105] A chiller room energy efficiency optimization system, the system includes a load characteristic analysis module, an equipment combination screening module, a dynamic switching module and a cross-equipment collaborative optimization module;

[0106] The load characteristic analysis module is used to collect annual cooling load data of the refrigeration room, outdoor temperature and humidity, divide low, medium and high load intervals, analyze the duration and fluctuation frequency of each interval, and output load characteristic analysis results.

[0107] Based on the load characteristic analysis results, the equipment combination screening module constructs a mixed equipment combination library of "large and small capacity + fixed frequency + variable frequency", establishes an equipment energy efficiency database and a combination COP optimization model, and selects the optimal equipment combination with the highest combination COP based on the current real-time load;

[0108] The dynamic switching module defines a combination of adjacent devices with continuous capacity coverage. It calculates the switching threshold based on the "energy efficiency breakpoint" mathematical model. When the real-time load exceeds the optimal range of the current combination or reaches the switching threshold, it triggers dynamic switching of the device combination.

[0109] The cross-device collaborative optimization module adjusts the core operating parameters of the cooling tower and the speed of the cooling / chilled water pumps through closed-loop control logic based on the operating status of the optimal equipment combination and outdoor temperature and humidity data, so that the operating environment parameters of the chiller are maintained within the preset target range and the water flow rate is matched with the chiller load.

[0110] The equipment combination screening module includes a combination generation unit and an optimal screening unit;

[0111] The combination generation unit is used to extract peak cooling load based on the annual cooling load data, divide different intervals, and determine the parameters of small-capacity variable frequency machines and large-capacity fixed frequency machines based on the interval data, as well as calculate the minimum number of fixed frequency machines and variable frequency machines that meet the screening conditions, and generate candidate combinations.

[0112] The optimal selection unit is used to calculate the annual average energy efficiency of each candidate combination, and selects the combination with the highest annual average energy efficiency as the optimal equipment combination.

[0113] The cross-device collaborative optimization module includes a chiller-cooling tower linkage unit and a chiller-water pump linkage unit;

[0114] The chiller-cooling tower linkage unit adjusts the cooling tower airflow drive parameters and spray flow rate through a closed-loop logic of "parameter acquisition - deviation calculation - graded adjustment - iterative verification" combined with outdoor temperature and humidity correction.

[0115] The chiller-pump linkage unit calculates the target flow rate based on the total chiller load and the preset water flow temperature difference target. It adjusts the water pump speed according to the relationship between flow rate and speed, and combines the single chiller load rate correction. Through dynamic verification, it ensures that the water flow parameters meet the target requirements.

Claims

1. A method for optimizing energy efficiency in a refrigeration room, characterized in that: The method includes: Step S1: Collect the annual cooling load data of the refrigeration room and the outdoor temperature and humidity, divide the low, medium and high load ranges and analyze the duration and fluctuation frequency of each range. Based on the principles of load coverage integrity and optimal energy efficiency, design a combination of large and small capacity + fixed frequency + variable frequency hybrid equipment. Step S2: Establish an equipment energy efficiency database, obtain a single equipment energy efficiency ratio calculation model by fitting the equipment load rate-energy efficiency ratio curve, construct a combined energy efficiency ratio optimization model based on the current real-time load, and screen out the operating combination with the highest combined energy efficiency ratio that meets the load demand in terms of total cooling capacity. Step S3: Define adjacent equipment combinations with continuous capacity coverage, calculate the combination switching threshold based on the energy efficiency breakpoint mathematical model, set the load fluctuation redundancy, and trigger equipment combination switching when the real-time load reaches the switching threshold. Step S3 includes the following steps: Step S31: The continuous connection of the capacity coverage range means that the maximum output capacity of the two device combinations A and B is the same as or the difference between the minimum output capacity of the device combination B and the minimum unit capacity. Step S32: Make the total power consumption of adjacent combinations A and B equal, and establish equation P. A (Q)=P B (Q), where P A (Q) is the total power consumption function of combination A under load Q, P B (Q) is the total power consumption function of combination B under load Q; using the formula: P A (Q)=Σ(Q Aj / COP Aj (β Aj )), P B (Q)=Σ(Q Bj / COP Bj (β Bj )), Q Aj Q represents the actual cooling capacity of the j-th device in combination A. Bj Let P represent the actual cooling capacity of the j-th device in combination B; solve the simultaneous equations P A (Q)=P B (Q), solving for the energy efficiency breakpoint Q0; COP Aj (β Aj ) represents the j-th device in the set of devices corresponding to combination A, at load factor β. j The single-unit energy efficiency ratio; COP Bj (β Bj ) represents the j-th device in the set of devices corresponding to combination B, at load factor β. j The energy efficiency ratio of a single unit; Step S33: Based on the energy efficiency breakpoint Q0, calculate the combined switching threshold Qw, Qw = Q0 + ΔQ, where ΔQ is the redundancy; ΔQ = 0.1 * Q 前组合最大容量 ; Step S4: Based on the optimal equipment combination operating status selected in Step S2 and the outdoor temperature and humidity data collected in Step S1, the operating parameters of the cooling tower and the speed of the cooling / chilled water pump are adaptively adjusted through a closed-loop control logic of graded adjustment and dynamic verification. This ensures that the chiller condensing temperature is maintained within the target range and the water flow rate matches the chiller load demand, thereby achieving a closed-loop coordinated energy efficiency improvement of "equipment combination - environmental parameters - auxiliary equipment".

2. The energy efficiency optimization method for a refrigeration room according to claim 1, characterized in that: Step S1 includes the following specific steps: Step S11: Based on the annual cooling load data, extract the maximum cooling load value of the refrigeration room as the peak cooling load Q. max According to the proportion of cooling load to Q max The system is divided into three intervals based on the ratio, and these three intervals include a low load Q1∈[0,0.3Q]. max ], Medium load Q2∈(0.3Q max 0.7Q max High load Q3∈(0.7Q) max Q max ]; Step S12: Extract the load factor β∈[0.6,0.9] and determine the single unit capacity Q of the minimum capacity inverter. b1 The range of values ​​for Q b1 ∈[0.6Q 1max Q 1max ], where Q 1max =0.3Q max By collecting performance curves from inverter manufacturers, models with an energy efficiency ratio greater than or equal to 4.5 at a load rate β∈[0.6,0.9] were selected. Determine the single-unit capacity Q of a large-capacity fixed-frequency machine. d Q d ≥0.5*(Q) max -Q b1 The energy efficiency ratio of a fixed-frequency unit is greater than or equal to 4.8 when the rated load rate β=1.

0. Step S13: Calculate the minimum number of fixed-frequency units n and variable-frequency units m to satisfy the total capacity Q. t =n*Q d +m*Q b1 ≥Q max And n≥1, m≥1; Based on the above parameters, generate multiple candidate combinations of "number of fixed frequency machines + capacity of large-capacity fixed frequency machines + number of variable frequency machines + capacity of small-capacity variable frequency machines" that meet the conditions; Step S14: Based on the equipment data under each candidate combination, calculate the average energy efficiency E for each load range included in the combination. k E k =(∑Q k,i ) / (∑P k,i ), k=1, 2, 3 correspond to low, medium, and high load ranges respectively, Q k,i P represents the total cooling capacity at time i within interval k. k,i This represents the total power consumption at time i within the k-th interval; using the formula: E a =a1*E1+a2*E2+a3*E3, calculate the annual average energy efficiency E a Where a1, a2, and a3 represent the duration percentages of each load range; E1, E2, and E3 correspond to the average energy efficiency of the low, medium, and high load ranges, respectively. Step S15: Select the candidate combination with the highest Ea as the final mixing device combination.

3. The energy efficiency optimization method for a refrigeration room according to claim 1, characterized in that: Step S2 includes the following specific steps: Step S21: When the single device is a fixed-frequency unit, obtain the coefficient of performance (COP) of the fixed-frequency unit under rated load. 额 When the load rate deviates from the rated value, it should be corrected according to the manufacturer's curve, using the correction formula COP. dβ =COP 额 *k d *β; where k d This is the load correction factor for the fixed-frequency machine; When a single device is a frequency converter, the "load rate - COP" curve of the device is fitted by a quadratic function, and the formula is COP. bβ =a×β²+b×β+d, where a, b, and d are fitting coefficients, and β∈[0.3,1.1]; When it is a combined device, COP 组合 =Total cooling capacity ∑Q j0 / Total power consumption ∑P j Q j0 P represents the actual cooling capacity after the j-th device is started. j =Q j0 / COP j COP j This represents the energy efficiency ratio of the j-th operating device. Step S22: Obtain the real-time cooling load Q L Set constraints, ∑(x j *Q j0 )≥Q L Q j0 =x j *Q j *β j , Where x j Let x represent the decision variable. j ∈{0,1}, when x j =1 indicates that device j is started, x j =0 indicates that device j is not started; β j β represents the load factor of the j-th device. j =(x j *Q j0 ) / Q j ;β j ∈[βmin,βmax]; Q j This represents the rated capacity of the j-th device in the device set. Set the objective function as COPmax, where COPmax = ∑(x j *Q j0 ) / ∑(x j *Q j0 / COP j (β j COP j (β j () represents the energy efficiency model of the equipment, indicating that the j-th equipment in the equipment set operates at a load factor β. j The energy efficiency ratio of a single unit; Step S23: Enumerate all equipment combinations that satisfy the constraints and generate a candidate solution set; calculate the total cooling capacity Qt, total power consumption Pt, and combination COP for each combination in the candidate solution set; eliminate combinations with Qt... t L For invalid combinations, the combination with the highest COPmax among the remaining valid combinations is selected as the optimal running combination.​ 4. The energy efficiency optimization method for a refrigeration room according to claim 1, characterized in that: The closed-loop control logic in step S4 includes chiller-cooling tower linkage control and chiller-water pump linkage control, including the following processes: The chiller-cooling tower linkage control includes real-time acquisition of core environmental parameters of chiller operation, outdoor temperature and humidity parameters, and current operating parameters of cooling tower. Calculate the deviation between the core environmental parameters of the chiller and the preset target range; Based on the magnitude of the deviation, the airflow drive parameters and spray flow parameters of the cooling tower are adjusted in stages. At the same time, environmental adaptation corrections are made in combination with outdoor temperature and humidity to ensure that the adjustment actions match environmental changes and chiller requirements. Parameters are collected at preset intervals to verify whether the core environmental parameters of the chiller have returned to the target range. If they do not meet the standards, the staged adjustment steps are repeated until the requirements are met. The chiller-water pump linkage control includes real-time acquisition of the optimal combination of total chiller load, individual chiller load rate, current water pump operating parameters, and water flow temperature difference parameters; based on the total chiller load and the preset water flow temperature difference target, the target water flow rate is adapted to the current chiller load; according to the correlation between flow rate and speed, the water pump speed is adjusted to match the target water flow rate, while also making corrections based on the individual chiller load rate, and water flow rate and temperature difference data are collected at preset intervals to verify whether they meet the target requirements. If there is a deviation, the speed is recalculated and adjusted.

5. A chiller room energy efficiency optimization system, using the chiller room energy efficiency optimization method according to any one of claims 1-4, characterized in that: The system includes a load characteristic analysis module, an equipment combination screening module, a dynamic switching module, and a cross-equipment collaborative optimization module. The load characteristic analysis module is used to collect annual cooling load data of the refrigeration room, outdoor temperature and humidity, divide low, medium and high load intervals, analyze the duration and fluctuation frequency of each interval, and output load characteristic analysis results. Based on the load characteristic analysis results, the equipment combination screening module constructs a mixed equipment combination library of "large and small capacity + fixed frequency + variable frequency", establishes an equipment energy efficiency database and a combination COP optimization model, and selects the optimal equipment combination with the highest combination COP based on the current real-time load; The dynamic switching module defines a combination of adjacent devices with continuous capacity coverage. It calculates the switching threshold based on the "energy efficiency breakpoint" mathematical model. When the real-time load exceeds the optimal range of the current combination or reaches the switching threshold, it triggers dynamic switching of the device combination. The cross-device collaborative optimization module adjusts the core operating parameters of the cooling tower and the speed of the cooling / chilled water pumps through closed-loop control logic based on the operating status of the optimal equipment combination and outdoor temperature and humidity data, so that the operating environment parameters of the chiller are maintained within the preset target range and the water flow rate is matched with the chiller load.

6. The energy efficiency optimization system for a refrigeration room according to claim 5, characterized in that: The equipment combination screening module includes a combination generation unit and an optimal screening unit; The combination generation unit is used to extract peak cooling load based on the annual cooling load data, divide different intervals, and determine the parameters of small-capacity variable frequency machines, determine the parameters of large-capacity fixed frequency machines, and calculate the minimum number of fixed frequency machines and variable frequency machines that meet the screening conditions based on the interval data, and generate candidate combinations. The optimal screening unit is used to calculate the annual average energy efficiency of each candidate combination and select the combination with the highest annual average energy efficiency as the optimal equipment combination.

7. The energy efficiency optimization system for a refrigeration room according to claim 6, characterized in that: The cross-device collaborative optimization module includes a chiller-cooling tower linkage unit and a chiller-water pump linkage unit; The chiller-cooling tower linkage unit adjusts the cooling tower airflow drive parameters and spray flow rate through a closed-loop logic of "parameter acquisition - deviation calculation - graded adjustment - iterative verification" combined with outdoor temperature and humidity correction. The chiller-water pump linkage unit calculates the target flow rate based on the total chiller load and the preset water flow temperature difference target, adjusts the water pump speed according to the correlation between flow rate and speed, and combines the single chiller load rate correction to ensure that the water flow parameters meet the target requirements through dynamic verification.

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