TWI414734B - Dynamic modeling method, monitoring method for chilling system and device for monitoring chilling system - Google Patents
Dynamic modeling method, monitoring method for chilling system and device for monitoring chilling system Download PDFInfo
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本發明係關於冰水主機之特性模型建立方法。The invention relates to a method for establishing a characteristic model of an ice water host.
運用於大型商辦大樓和工廠之空調冰水系統主要是由冰水主機、冰水泵浦、冷卻水泵浦，以及冷卻水塔所組成，其中以冰水主機之能源需求量為最高。以一總裝置冷凍噸數(RT)為21,000之12吋晶圓廠為例，產生空調冰水總用電量約佔全廠用電之26%，而冰水主機佔該總用電量之50%。因此，若能確保冰水主機均在最高效率範圍上操作，則可減少可觀的能源損耗。The air-conditioning ice water system used in large commercial buildings and factories is mainly composed of ice water main engine, ice water pump, cooling water pump, and cooling water tower. The energy demand of the ice water main unit is the highest. For example, a 12-inch wafer fab with a total installed refrigeration tonnage (RT) of 21,000, for example, produces about 26% of the total electricity consumption of air-conditioning ice water, and the ice water host accounts for the total electricity consumption. 50%. Therefore, if you ensure that the ice water main unit operates at the highest efficiency range, you can reduce the considerable energy loss.
製造商所提供之冰水主機特性曲線一般均在非實際安裝現場上直接測試而取得。由於受到管路系統與操作模式之影響，以製造商提供之特性曲線進行操作，經常使冰水主機無法在最高效率範圍上運轉，導致能源使用效率降低。因此，通常冰水主機安裝後，會透過現場實際運轉資料，重新建立冰水主機特性曲線。The chiller host characteristic curves provided by the manufacturer are generally obtained by direct testing on a non-physical installation site. Due to the influence of the piping system and the operation mode, operating with the characteristic curve provided by the manufacturer often makes it impossible for the ice water main unit to operate at the highest efficiency range, resulting in a decrease in energy efficiency. Therefore, after the ice water main unit is installed, the ice water host characteristic curve will be re-established through the actual operation data of the site.
目前冰水主機特性曲線之建立可利用兩種模型：回歸模型及人工智慧模型。然而，此兩種模型具有以下之缺點：(1)需準備一定數量的運轉資料，過少運轉資料將無法將模型建立起來。以例言：若為3階多項式，則至少需要4筆不同的RT運轉資料，方可建立曲線；(2)如Y.H. Song等人之論文(Young-hak Song,Yasunori Akashi,Jurng-Jae Yee,2007,“Energy performance of a cooling plant system using the inverter chiller for industrial building,”Energy and Building,Vol. 39,Issue 3,Pages 289-297)中闡述，不同冷卻水回水溫度，需使用不同階數的回歸模型，造成模型建立的困難度。(3)當性能曲線具有小區域特徵(如：兩個谷值)時，回歸模型之階數將快速增加，致使運算量、資料需求量均會大幅增加；而使用人工智慧模型亦需要較多運算資料，以模擬小區域特徵。At present, the establishment of the ice water host characteristic curve can use two models: regression model and artificial intelligence model. However, these two models have the following disadvantages: (1) A certain amount of operational data needs to be prepared, and too little operational data will not be able to establish the model. For example: if it is a 3rd-order polynomial, at least 4 different RT operation data are needed to establish a curve; (2) such as YH Song et al. (Young-hak Song, Yasunori Akashi, Jurng-Jae Yee, 2007, "Energy performance of a cooling plant system using the inverter chiller for industrial building," Energy and Building, Vol. 39, Issue 3, Pages 289-297), different cooling water return water temperature, need to use different orders The regression model causes the difficulty of model building. (3) When the performance curve has small regional characteristics (such as two valleys), the order of the regression model will increase rapidly, resulting in a large increase in the amount of calculation and data demand; and the use of artificial intelligence models also requires more Calculate data to simulate small area features.
除上述問題外，運用回歸模型與人工智慧模型，在冰水主機特性模型建立上時，均需要長時間之訓練資料。另一方面，冰水主機在運轉一段長時間後，需維修保養。然而，冰水主機經過維修保養後，其實際主機運轉特性會與建模時之特性有所差異。在此狀況下，原有的特性曲線需要進行調整，而使用回歸模型與人工智慧模型來建立的特性曲線，將再一次進行長時間的訓練，而無法對特性曲線直接進行局部地與動態地調整修正。In addition to the above problems, the use of regression models and artificial intelligence models, when the ice water host feature model is established, requires a long training data. On the other hand, the ice water main engine needs to be repaired after a long period of operation. However, after the ice water main unit is repaired and maintained, its actual main engine running characteristics will differ from the characteristics at the time of modeling. Under this circumstance, the original characteristic curve needs to be adjusted, and the characteristic curve established by using the regression model and the artificial intelligence model will once again be trained for a long time, and the characteristic curve cannot be directly and dynamically adjusted locally. Corrected.
根據上述問題，本發明一實施例提出一種冰水主機動態特性模型建立方法，其包含下列步驟：獲取一冰水主機之一冰水回水溫度、一冰水出水溫度、一冷卻水回水溫度、一流量和一用電量；根據該冰水回水溫度，該冰水出水溫度，該流量和該用電量，計算一實際運轉效率值；取得複數個控制點，其中該些控制點代表一合成曲線動態特性模型；利用一擾動量，計算各該控制點在一移動方向向量中相應之一元素值，其中各該控制點單獨地以相應之元素值調整後，所得之一計算合成曲線動態特性模型較該合成曲線動態特性模型更趨近該實際運轉效率值；提供一移動變數，並以該移動變數與該移動方向向量之乘積調整該些控制點，藉此獲得逼近該實際運轉效率值之一合成曲線動態特性模型；以及在各迭代計算中，根據一變數最小值搜尋法，決定該移動變數之值。According to the above problem, an embodiment of the present invention provides a method for establishing a dynamic characteristic model of an ice water host, which comprises the following steps: acquiring an ice water return water temperature, an ice water water discharge temperature, and a cooling water return water temperature of an ice water host. a flow rate and a power consumption amount; according to the ice water return water temperature, the ice water outlet water temperature, the flow rate and the electricity consumption amount, calculating an actual operation efficiency value; obtaining a plurality of control points, wherein the control points represent a synthetic curve dynamic characteristic model; using a disturbance amount, calculating a corresponding element value of each control point in a moving direction vector, wherein each of the control points is individually adjusted by a corresponding element value, and one of the obtained calculated curves is calculated The dynamic characteristic model is closer to the actual operational efficiency value than the synthetic curve dynamic characteristic model; a moving variable is provided, and the control points are adjusted by the product of the moving variable and the moving direction vector, thereby obtaining the approximate operational efficiency One of the values of the composite curve dynamics model; and in each iterative calculation, the moving variable is determined according to a variable minimum search method Value.
本發明另一實施例提出一種冰水主機監控方法，其包含下列步驟：獲取一冰水回水溫度、一冰水出水溫度、一冷卻水回水溫度、一流量和一用電量；根據該冰水回水溫度，該冰水出水溫度，該流量和該用電量，計算部份負載比及實際運轉效率值；取得複數個控制點，其中該些控制點決定一代表合成曲線動態特性模型；利用一擾動量，計算各該控制點之一移動方向向量中相應之一元素值，其中各該控制點單獨地以相應之元素值調整後，所得之一計算合成曲線動態特性模型較該合成曲線動態特性模型更趨近該實際運轉效率值；提供一移動變數，並以該移動變數與該移動方向向量之乘積調整該些控制點，藉此獲得逼近該實際運轉效率值之一合成曲線動態特性模型；在各迭代計算中，根據一變數最小值搜尋法，決定該移動變數；以及當一迭代中止要件滿足時，產生一新的代表合成曲線動態特性模型。Another embodiment of the present invention provides a method for monitoring an ice water host, comprising the steps of: obtaining an ice water return water temperature, an ice water water outlet temperature, a cooling water return water temperature, a flow rate, and a power consumption; The ice water return water temperature, the ice water water discharge temperature, the flow rate and the electricity consumption amount, calculate a partial load ratio and an actual operation efficiency value; obtain a plurality of control points, wherein the control points determine a representative synthetic curve dynamic characteristic model Using a disturbance amount, calculating a corresponding one of the element values in one of the movement direction vectors of each of the control points, wherein each of the control points is individually adjusted by the corresponding element value, and one of the obtained calculations is a synthetic curve dynamic characteristic model compared to the synthesis The curve dynamic characteristic model is closer to the actual operating efficiency value; a moving variable is provided, and the control points are adjusted by the product of the moving variable and the moving direction vector, thereby obtaining a synthetic curve dynamic that approximates the actual operating efficiency value Characteristic model; in each iterative calculation, the moving variable is determined according to a variable minimum search method; and when an iteration abort element is satisfied Generating a new dynamic characteristic model representing composite curve.
本發明另一實施例提出一種冰水主機監控裝置，其包含一擷取裝置、一運算裝置以及一顯示裝置。擷取裝置可獲取一冰水主機之運轉資訊。運算裝置可根據該運轉資訊，計算冰水主機之一實際運轉效率值，和調整複數個控制點，以使由該複數個控制點所決定之一合成曲線動態特性模型趨近該實際運轉效率值。顯示裝置則顯示代表該運轉資訊之一代表合成曲線動態特性模型。Another embodiment of the present invention provides an ice water host monitoring device including a capture device, an arithmetic device, and a display device. The pick-up device can obtain information on the operation of an ice water host. The computing device may calculate an actual operating efficiency value of one of the ice water hosts according to the operation information, and adjust a plurality of control points such that a composite curve dynamic characteristic model determined by the plurality of control points approaches the actual operating efficiency value . The display device displays a synthetic curve dynamic characteristic model representing one of the operational information.
利用合成曲線建立之冰水主機動態特性模型可在所需變更的區域進行局部更新，即可動態地建立冰水主機特性模型。此外，若要更精準的描述冰水主機的特性而增加控制點時，亦不至於使曲線的次方無限制的增加，而導致計算成本的增加。The ice water host dynamic characteristic model established by the synthetic curve can be dynamically updated in the area of the required change, and the ice water host characteristic model can be dynamically established. In addition, if the control point is added more accurately to describe the characteristics of the ice water host, the increase of the calculation cost will not be caused by the unrestricted increase of the power of the curve.
圖1顯示本發明一實施例之冰水主機監測系統1之連接示意圖。圖2顯示本發明一實施例之冰水主機監測系統1之示意圖。參照圖1與圖2所示，冰水主機監測系統1可連接至冰水主機或廠務監控系統(FMCS)2，透過冰水主機2上之感測器或廠務資料庫，以擷取裝置11獲取冰水主機相關運轉資訊，該資訊包含有冰水主機2之用電量W、冰水回水溫度Tchi 、冰水出水溫度Tcho 、冷卻水回水溫度Tcwi ，以及冰水流量Qcho 等運轉資訊。透過所擷取得之資訊計算得冰水主機動態之實際冰水主機運轉效能(KPIreal )、輸出冷凍噸(RT)與部份負載比PLRcurrent ，以及在當冷卻回水溫度下透過B-spline特性模型取得之冰水主機運轉效能(KPImodel )模型值，然後，將前述運轉資訊即時地顯示在連接一顯示裝置14上之可視化介面，以協助操作人員進行冰水主機2之操作。1 shows a connection diagram of a chilled water host monitoring system 1 according to an embodiment of the present invention. 2 shows a schematic diagram of an ice water host monitoring system 1 according to an embodiment of the present invention. Referring to FIG. 1 and FIG. 2, the ice water host monitoring system 1 can be connected to an ice water host or a factory monitoring system (FMCS) 2, through the sensor or factory database on the ice water host 2, to capture The device 11 acquires operation information related to the ice water host, and the information includes the power consumption W of the ice water host 2, the ice water return water temperature T chi , the ice water water temperature T cho , the cooling water return water temperature T cwi , and the ice water Operation information such as traffic Q cho . Calculate the actual ice water main operation efficiency (KPI real ), output frozen tons (RT) and partial load ratio PLR current from the ice water host dynamics through the information obtained, and pass the B-spline when cooling the return water temperature The KPI model value obtained by the characteristic model is then displayed on the visual interface connected to a display device 14 to assist the operator in the operation of the chilled water host 2.
運算裝置12則可利用前述之運轉資訊、計算得冰水主機動態之實際冰水主機運轉效能(KPIreal )、輸出冷凍噸(RT)與部份負載比PLRcurrent ，上述實際運轉效能數據可藉由下列公式(1)、公式(2)及公式(3)表示：The computing device 12 can use the foregoing operational information, calculate the actual ice water host operating efficiency (KPI real ), the output freezing ton (RT) and the partial load ratio PLR current , and the actual operating performance data can be borrowed. It is represented by the following formula (1), formula (2), and formula (3):
RT =(T chi -T cho )×Q ch (2) RT = ( T chi - T cho ) × Q ch (2)
其中，KPIreal 為該實際運轉效率值，RT為冰水主機輸入之冷凍噸數，Tchi 為冰水回水溫度，Tcho 為冰水出水溫度，Qcho 為流量，W為用電量，PLR(Partial Loading Ratio)為部份負載比，RTspecific 為冰水主機2之額定冷凍噸，而Tcwi 為冷卻水回水溫度。Among them, KPI real is the actual operating efficiency value, RT is the frozen tonnage input by the ice water main unit, T chi is the ice water return water temperature, T cho is the ice water outlet temperature, Q cho is the flow rate, and W is the electricity consumption. The PLR (Partial Loading Ratio) is a partial load ratio, RT specific is the rated freezing ton of the ice water host 2, and T cwi is the cooling water return water temperature.
此運算裝置亦包含演算建立可代表前述運轉資訊之冰水主機B-spline動態特性模型，B-spline曲線的定義以及最適曲線的修正方式，單一冷卻水回水溫度以一B-spline曲線表示其冰水主機動態特性模型，亦可將其特性模型以一B-spline曲面表達其冷卻水回水溫度之參數。The computing device also includes a calculation to establish a B-spline dynamic characteristic model of the ice water host which can represent the aforementioned operation information, a definition of the B-spline curve and a correction method of the optimum curve, and the single cooling water return water temperature is represented by a B-spline curve. The ice water host dynamic characteristic model can also express its characteristic model as a B-spline surface to express its cooling water return water temperature parameters.
本發明可利用任何合成曲線進行建立合成曲線動態特性模型，本案實施例雖以B-spine曲線或曲面來建置模型，然其他合成曲線例如Bezier曲線亦可以類似方法流程建置模型，因此本說明書不再針對Bezier曲線建模流程，進行說明。The invention can use any synthetic curve to establish a dynamic curve model of the synthetic curve. In the embodiment of the present invention, the model is built by a B-spine curve or a curved surface, and other synthetic curves such as a Bezier curve can also be built in a similar method flow, so this specification The Bezier curve modeling process is no longer described.
完成建置之冰水主機特性模型及其相關參數資料(冰水主機之額定冷凍噸)，則會儲存在一儲存裝置15(例如：硬碟或磁帶機等)中，並顯示在顯示裝置14上，以供操作所需。The completed ice water host characteristic model and its related parameter data (the rated freezing tons of the ice water host) are stored in a storage device 15 (for example, a hard disk or a tape drive, etc.) and displayed on the display device 14 On, for operation.
如圖3所示，運算裝置12亦被建構以利用儲存裝置15內之實際運轉效能數據，以及歷次建立之冰水主機動態特性模型，藉由趨勢統計分析手法，取得冰水主機動態特性模型之變化趨勢，並在一運轉效率值之變異量超過一門檻值時，透過警示裝置13，警告操作人員。此外，運算裝置12亦被建構在相同操作狀況下，藉由比較前、後兩段時間之效率值分佈，取得設備運轉效能資料變化趨勢，透過設備運轉效能以及特性曲線，可得知其效能是否於高效率運轉區間，藉此可透過改變相關運轉參數，使其運轉於高效率區間，達到運轉節能之目的。As shown in FIG. 3, the computing device 12 is also configured to utilize the actual operational performance data in the storage device 15 and the historically established ice water host dynamics model to obtain the ice water host dynamic characteristic model by trend statistical analysis. The trend is changed, and when the variation of the operational efficiency value exceeds a threshold, the operator is warned by the warning device 13. In addition, the computing device 12 is also constructed under the same operating conditions. By comparing the efficiency value distributions of the two periods before and after, the trend of the equipment operating efficiency data is obtained, and whether the performance is obtained through the operating performance and the characteristic curve of the device. In the high-efficiency operation section, it is possible to operate in a high-efficiency section by changing the relevant operating parameters to achieve energy saving.
在一實施例中，擷取裝置11可包含複數個輸入埠，其中該些輸入埠相應地連接冰水主機2上之感測器、或對應於其廠務運轉系統或中央監控系統。運算裝置12可包含中央處理器及記憶體，其中中央處理器、記憶體及該些輸入埠可利用一匯流排進行資料傳遞。顯示裝置14可包含螢幕。儲存裝置15可包含硬碟。In an embodiment, the capture device 11 can include a plurality of input ports, wherein the inputs are correspondingly connected to sensors on the ice water host 2, or to their factory operation system or central monitoring system. The computing device 12 can include a central processing unit and a memory, wherein the central processing unit, the memory, and the input ports can utilize a bus bar for data transfer. Display device 14 can include a screen. The storage device 15 can include a hard disk.
圖4顯示本發明一實施例之冰水主機動態特性模型建立方法之流程圖。4 is a flow chart showing a method for establishing a dynamic model of a glacial water host according to an embodiment of the present invention.
在步驟S40中，首先獲得冰水主機2之一冰水回水溫度(Tchi )、一冰水出水溫度(Tcho )、冷卻水回水溫度(Tcwi )、一冰水流量(Qcho )和一用電量(W)等運轉資訊，並計算其冰水主機2之冷凍噸與部份負載比(PLR)，其中前述溫度、水流量及用電量直接量測而得，或者從廠務監控系統中獲得。In step S40, first, an ice water return water temperature (T chi ), an ice water outlet water temperature (T cho ), a cooling water return water temperature (T cwi ), and an ice water flow rate (Q cho ) of the ice water host 2 are obtained. And operating information such as a power consumption (W), and calculating the freezing tonnage and partial load ratio (PLR) of the ice water host 2, wherein the temperature, water flow and power consumption are directly measured, or Obtained in the factory monitoring system.
在步驟S41中，根據前述公式(1)和(2)計算一實際運轉效率值(KPIreal )。In step S41, an actual operational efficiency value (KPI real ) is calculated according to the aforementioned formulas (1) and (2).
在步驟S42中，定義或取得複數個控制點，其中該複數個控制點決定出代表冰水主機運轉特性之一代表B-spline動態特性模型。當以建立表示冰水主機2之特性曲線之冰水主機動態特性模型(KPImodel =Bspline(PLR)於特定冷卻水回水溫度)時，則利用下列公式(4)和(5)。In step S42, a plurality of control points are defined or obtained, wherein the plurality of control points determine that one of the running characteristics of the ice water host represents a B-spline dynamic characteristic model. When the icy water host dynamic characteristic model (KPI model = Bspline (PLR) at a specific cooling water return water temperature) indicating the characteristic curve of the glazed water main unit 2 is established, the following formulas (4) and (5) are utilized.
其中，n為控制點數目，k為B-spline曲線函數之次方，Pi 為B-spline曲線函數之控制點，Ni,k 為B-spline的混合函數，其可表示為。Where n is the number of control points, k is the power of the B-spline curve function, P i is the control point of the B-spline curve function, and N i,k is the mixed function of B-spline, which can be expressed as .
由於B-spline曲線的特性是可局部控制及改變曲線形狀功能，以及增加曲線的控制點時，曲線方程式項次不會因此而增加。由於此兩項之特性，使得當以B-spline曲線建立冰水主機特性模型時，可有效的使曲線在所需變更的區域進行局部更新，即可動態地建立冰水主機特性模型。此外，若要更精準的描述冰水主機的特性而增加曲線的控制點時，亦不至於使曲線的次方無限制的增加，而導致計算成本的增加。B-spline曲線更可讓使用者於所關注的任意位置上，設定或***曲線控制點，以使曲線成為所期待的曲線形狀。Since the characteristics of the B-spline curve are that the function of the curve shape can be locally controlled and changed, and the control points of the curve are increased, the curve equations do not increase accordingly. Due to the characteristics of these two items, when the ice water host characteristic model is established by the B-spline curve, the curve can be effectively updated in the area of the required change, and the ice water host characteristic model can be dynamically established. In addition, if the characteristics of the ice water host are more accurately described and the control points of the curve are increased, the increase of the calculation cost will not be caused by the unrestricted increase of the power of the curve. The B-spline curve allows the user to set or insert a curve control point at any position of interest to make the curve the desired curve shape.
若考慮冷卻水回水溫度時，則須以下列公式(8)來建立冰水主機動態特性模型(KPImodel =Bspline(Tcwi ,PLR))。If the cooling water return water temperature is considered, the ice water host dynamic characteristic model (KPI model = Bspline (T cwi , PLR)) must be established by the following formula (8).
B-spline動態特性模型可為使用中之冰水主機動態特性模型，B-spline動態特性模型亦可為以複數個值為定值之初始控制點計算而得之初始動態特性模型。若B-spline動態特性模型為初始動態特性模型，則可在決定控制點之數目後，給定控制點一固定初始值，例如：1。若將控制點組合成一特性矩陣(Performance Surface of Matrix,PSM )表示，則PSM 1×n =[1,1,...,1]1×n ，n為控制點數目，此時KPImodel =1。The B-spline dynamic characteristic model can be the dynamic characteristic model of the ice water host in use, and the B-spline dynamic characteristic model can also be an initial dynamic characteristic model calculated by using a plurality of initial control points whose values are fixed. If the B-spline dynamic characteristic model is the initial dynamic characteristic model, after determining the number of control points, the control point is given a fixed initial value, for example: 1. If the control points are combined into a Performance Surface of Matrix ( PSM ) representation, then PSM 1 × n = [1, 1, ..., 1] 1 × n , where n is the number of control points, at this time KPI model = 1.
在步驟S43中，計算各控制點之一最適移動方向，其中所有控制點之最適移動方向可組合成一移動方向向量s ，而s 可係由下列公式(9)和(10)所計算。In step S43, an optimum moving direction of one of the control points is calculated, wherein the optimum moving direction of all the control points can be combined into a moving direction vector s , and s can be calculated by the following formulas (9) and (10).
f =|COP mod el -COP real | (9) f =| COP mod el - COP real | (9)
各控制點的移動方向的計算係式(10)得知，各控制點相應之移動方向向量元素值為f/xi ，即將i 控制點進行一擾動量dx，其餘控制點維持原值，並將於步驟S40所得之部份負載比(PLR)條件，代入由此新控制點所建構之計算B-spline曲線動態特性模型，取得此新控制點下之KPImodel 值，並計算f=f(x)-f(x+x)下之函數值，若此值為正值，表示此一擾動量，使透過此新控制點之B-spline動態特性模型所得之效率值更趨近於在步驟S41計算所得之實際運轉效率值，亦即此B-spline曲線特性亦趨似於實際之冰水主機運轉特性，此擾動所造成之移動方向為正確之方向。The calculation formula of the moving direction of each control point (10) knows that the corresponding moving direction vector element value of each control point is f/ x i , that is, the i control point performs a disturbance amount dx, the remaining control points maintain the original value, and the partial load ratio (PLR) condition obtained in step S40 is substituted into the calculated B-spline curve constructed by the new control point. Dynamic characteristic model, obtain the KPI model value under this new control point, and calculate f=f(x)-f(x+ x) the value of the function below, if the value is positive, indicating the amount of disturbance, so that the efficiency value obtained by the B-spline dynamic characteristic model of the new control point is closer to the actual operational efficiency calculated in step S41. The value, that is, the B-spline curve characteristic also tends to be the actual ice water host operating characteristic, and the moving direction caused by this disturbance is the correct direction.
在步驟S44與S45中，提供一移動變數α。利用移動變數α與最適移動方向向量之乘積值調整控制點，藉此獲得逼近實際運轉效率值之一B-spline動態特性模型。控制點之調整是以迭代方式，逐漸獲得可代表在步驟S41計算所得之實際運轉效率值之新的B-spline動態特性模型。若以數學表示，則可以下列公式(11)表示。In steps S44 and S45, a movement variable α is provided. The control point is adjusted by the product of the moving variable α and the optimum moving direction vector, thereby obtaining a B-spline dynamic characteristic model that approximates the actual operating efficiency value. The adjustment of the control point is an iterative manner in which a new B-spline dynamics model representative of the actual operational efficiency value calculated at step S41 is gradually obtained. If expressed mathematically, it can be expressed by the following formula (11).
PSM k +1 =PSM k +α ×s (11) PSM k +1 = PSM k + α × s (11)
其中，k為迭代次數(iteration)。移動變數α為用於調整控制點的移動步長(step length)，其可由一變數最小值搜尋法例如：牛頓法(Newton method)、黃金切割(Golden Section Search)、類神經演算法、基因演算法或費邦那西搜尋法(Fibonacci Search)等方法決定。Where k is the iteration number. The movement variable α is a step length for adjusting the control point, which can be searched by a variable minimum value method such as Newton method, Golden Section Search, nerve-like algorithm, gene calculus. Method or Fibonacci Search method (Fibonacci Search) and other methods.
參照圖5所示，為獲得代表在步驟S41計算所得之實際運轉效率值之新的B-spline動態特性模型，則須使公式(9)之f值為最小。為此，可利用單變數最小值搜尋法搜尋使f值為最小之移動變數α。若使用黃金切割法，則先確定一區間[a,b]，其中a和b可為前一次迭代之搜尋值。然後，在圖5中(b-a)×τ(=0.382)區間中選擇新的移動變數αi 進行計算，即可將區間[a,b]縮減1-τ倍。反覆重複前述步驟，即可獲得使公式(9)之f值為最小之KPIreal 。Referring to Fig. 5, in order to obtain a new B-spline dynamic characteristic model representing the actual operational efficiency value calculated in step S41, the f value of equation (9) must be minimized. To this end, the single variable minimum value search method can be used to search for the movement variable α which minimizes the f value. If the gold cutting method is used, an interval [a, b] is determined first, where a and b are the search values of the previous iteration. Then, by selecting a new moving variable α i in the interval of (ba) × τ (=0.382) in Fig. 5, the interval [a, b] can be reduced by 1-τ times. By repeating the foregoing steps repeatedly, KPI real which minimizes the f value of the formula (9) can be obtained.
在步驟S46，根據公式(11)，計算複數個調整控制點。In step S46, a plurality of adjustment control points are calculated according to formula (11).
在步驟S47中，根據步驟S46所得之複數個調整控制點，計算出一調整後之B-spline動態特性模型。In step S47, an adjusted B-spline dynamic characteristic model is calculated according to the plurality of adjustment control points obtained in step S46.
在步驟S48中，根據公式(9)，計算步驟S47之調整後之B-spline動態特性模型與步驟S41計算而得之實際運轉效率值(KPIreal )間之一第一差異值。In step S48, a first difference value between the adjusted B-spline dynamic characteristic model of step S47 and the actual operational efficiency value (KPI real ) calculated in step S41 is calculated according to formula (9).
在步驟S49中，根據公式(9)，計算一前次調整後之B-spline動態特性模型與該實際運轉效率值間之一第二差異值。In step S49, according to formula (9), a second difference value between a previously adjusted B-spline dynamic characteristic model and the actual operational efficiency value is calculated.
在步驟S50為迭代之中止要件，此迭代中止要件的定義可為比較第一差異值與第二差異值，若此量差異值小於一設定之數值，則中止迭代流程，或可定義為當第一差異值小於一設定值，則中止迭代流程，或可定義為迭代之次數，當迭代次數大於一設定之數值，則中止迭代流程。當未達到迭代中止要件時，表示尚未取得最佳化之B-spline動態特性模型，此時回到步驟S45，以計算新的移動變數α。In step S50, it is an iterative suspension requirement. The definition of the iterative suspension requirement may be to compare the first difference value with the second difference value. If the quantity difference value is less than a set value, the iterative process is aborted, or may be defined as If the difference value is less than a set value, the iterative process is aborted, or may be defined as the number of iterations. When the number of iterations is greater than a set value, the iterative process is aborted. When the iterative suspension requirement is not reached, it indicates that the optimized B-spline dynamic characteristic model has not been obtained, and then returns to step S45 to calculate a new movement variable α.
在步驟S51中，當滿足迭代中止要件時，則將步驟S47計算之調整後之B-spline動態特性模型列為一新的代表B-spline動態特性模型。In step S51, when the iterative suspension requirement is satisfied, the adjusted B-spline dynamic characteristic model calculated in step S47 is listed as a new representative B-spline dynamic characteristic model.
在一實施例中，B-spline動態特性模型為初始動態特性模型，則可在決定控制點之數目後，給定控制點一定值，例如：1。若將控制點組合成一特性矩陣(Performance Surface of Matrix,PSM )表示，則=[1,1,...,1]1xn ，n為控制點數目，此時KPImodel =1。之後，依照前述S40至S50之步驟，計算出代表B-spline動態特性模型。In an embodiment, the B-spline dynamic characteristic model is an initial dynamic characteristic model, and after determining the number of control points, a certain value of the control point is given, for example: 1. If the control points are combined into a Performance Surface of Matrix ( PSM ) representation, then =[1,1,...,1] 1xn , where n is the number of control points, at which point KPI model =1. Then, according to the steps S40 to S50 described above, a representative B-spline dynamic characteristic model is calculated.
圖6顯示本發明一實施例之冰水主機監控方法之流程圖。在步驟S60中，首先獲得冰水主機2之一冰水回水溫度(Tchi )、一冰水出水溫度(Tcho )、冷卻水回水溫度(Tcwi )、一冰水流量(Qcho )和一用電量(W)，並計算其冰水主機2之冷凍噸與部份負載比(PLR)，其中前述溫度、水流量及用電量直接量測而得，或者從廠務監控系統中獲得。FIG. 6 is a flow chart showing a method for monitoring an ice water host according to an embodiment of the present invention. In step S60, first, an ice water return water temperature (T chi ), an ice water outlet water temperature (T cho ), a cooling water return water temperature (T cwi ), and an ice water flow rate (Q cho ) of the ice water host 2 are obtained. And a power consumption (W), and calculate the freezing tonnage and partial load ratio (PLR) of the ice water host 2, wherein the aforementioned temperature, water flow and power consumption are directly measured, or from the factory monitoring Obtained in the system.
在步驟S61中，根據前述公式(1)和(2)計算一實際運轉效率值(KPIreal )。In step S61, an actual operational efficiency value (KPI real ) is calculated according to the aforementioned formulas (1) and (2).
在步驟S62中，取得複數個控制點，其中該複數個控制點決定出代表冰水主機運轉特性之一代表B-spline動態特性模型KPImodel =Bspline(PLR)或KPImodel =Bspline(Tcwi ,PLR)。In step S62, a plurality of control points are obtained, wherein the plurality of control points determine that one of the running characteristics of the ice water host represents a B-spline dynamic characteristic model KPI model = Bspline (PLR) or KPI model = Bspline (T cwi , PLR).
在步驟S63中，計算各控制點之一最適移動方向，其中所有控制點之最適移動方向可組合成一向量s ，而s 可係由下列公式(9)和(10)所計算。In step S63, an optimum moving direction of one of the control points is calculated, wherein the optimum moving direction of all the control points can be combined into a vector s , and s can be calculated by the following formulas (9) and (10).
f =|COP mod el -COP real | (9) f =| COP mod el - COP real | (9)
各控制點的移動方向的計算係式(10)得知，各控制點相應之移動方向向量元素值為f/xi ，即將i控制點進行一擾動量dx，其餘控制點維持原值，並將於步驟S60所得之部份負載比(PLR)條件，代入由此新控制點所建構之B-spline曲線動態特性模型，取得此新控制點下之KPImodel 值，並計算f=f(x)-f(x+x)下之函數值，若此值為正值，表示此一擾動量，使透過此新控制點之B-spline動態特性模型所得之效率值更趨近於在步驟S61計算所得之實際運轉效率值，亦即此B-spline曲線特性亦趨似於實際之冰水主機運轉特性，此擾動所造成之移動方向為正確之方向。The calculation formula of the moving direction of each control point (10) knows that the corresponding moving direction vector element value of each control point is f/ x i , that is, the i control point performs a disturbance amount dx, the remaining control points maintain the original value, and the partial load ratio (PLR) condition obtained in step S60 is substituted into the B-spline curve dynamic constructed by the new control point. Characteristic model, obtain the KPI model value under this new control point, and calculate f=f(x)-f(x+ x) the value of the function below, if the value is positive, indicating the amount of disturbance, so that the efficiency value obtained by the B-spline dynamic characteristic model of the new control point is closer to the actual operational efficiency calculated in step S61. The value, that is, the B-spline curve characteristic also tends to be the actual ice water host operating characteristic, and the moving direction caused by this disturbance is the correct direction.
在步驟S64與S65中，提供一移動變數α。如公式(11)所示，利用移動變數α與各控制點之最適移動方向向量之乘積值調整控制點，藉此獲得逼近實際運轉效率值之一B-spline動態特性模型。控制點之調整是以迭代方式，逐漸獲得可代表在步驟S61計算所得之實際運轉效率值之新的B-spline動態特性模型。In steps S64 and S65, a movement variable α is provided. As shown in the formula (11), the control point is adjusted by the product value of the movement variable α and the optimum moving direction vector of each control point, thereby obtaining a B-spline dynamic characteristic model which approximates one of the actual operational efficiency values. The adjustment of the control points is in an iterative manner, gradually obtaining a new B-spline dynamics model representative of the actual operational efficiency values calculated at step S61.
在步驟S66，根據公式(11)，計算複數個調整控制點。In step S66, a plurality of adjustment control points are calculated according to formula (11).
在步驟S67中，根據步驟S66所得之複數個調整控制點，計算出一調整後之B-spline動態特性模型。In step S67, an adjusted B-spline dynamic characteristic model is calculated according to the plurality of adjustment control points obtained in step S66.
在步驟S68中，根據公式(9)，計算步驟S67之調整後之B-spline動態特性模型與步驟S61計算而得之實際運轉效率值(KPIreal )間之一第一差異值。In step S68, a first difference value between the adjusted B-spline dynamic characteristic model of step S67 and the actual operational efficiency value (KPI real ) calculated in step S61 is calculated according to formula (9).
在步驟S69中，根據公式(9)，計算一前次調整後之B-spline動態特性模型與該實際運轉效率值間之一第二差異值。In step S69, according to formula (9), a second difference value between a previously adjusted B-spline dynamic characteristic model and the actual operational efficiency value is calculated.
在步驟S70為迭代之中止要件，此迭代中止要件的定義可為比較第一差異值與第二差異值，若此量差異值小於一設定之數值，則中止迭代流程，或可定義為當第一差異值小於一設定值，則中止迭代流程，或可定義為迭代之次數，當迭代次數大於一設定之數值，則中止迭代流程。當未達到迭代中止要件時，表示尚未取得最佳化之B-spline動態特性模型，此時回到步驟S65，以計算新的移動變數α。In step S70, it is an iterative suspension requirement. The definition of the iterative suspension requirement may be comparing the first difference value with the second difference value. If the quantity difference value is less than a set value, the iteration process is aborted, or may be defined as If the difference value is less than a set value, the iterative process is aborted, or may be defined as the number of iterations. When the number of iterations is greater than a set value, the iterative process is aborted. When the iterative suspension requirement is not reached, it indicates that the optimized B-spline dynamic characteristic model has not been obtained, and the process returns to step S65 to calculate a new movement variable α.
在步驟S71中，當滿足迭代中止要件時，則將步驟S67計算之調整後之B-spline動態特性模型列為一新的代表B-spline動態特性模型。In step S71, when the iterative suspension requirement is satisfied, the adjusted B-spline dynamic characteristic model calculated in step S67 is listed as a new representative B-spline dynamic characteristic model.
在步驟S72中，根據新的代表B-spline動態特性模型與原先之代表B-spline動態特性模型之比較結果，決定是否提出異常警告。在一實施例中，當新的代表B-spline動態特性模型與原先之代表B-spline動態特性模型間之差異大於一門檻值時，提出警告。In step S72, based on the comparison result between the new representative B-spline dynamic characteristic model and the original representative B-spline dynamic characteristic model, it is determined whether or not an abnormal warning is raised. In an embodiment, a warning is issued when the difference between the new representative B-spline dynamics model and the original representative B-spline dynamics model is greater than a threshold.
在另一實施例中，冰水主機監測系統1可進一步計算出複數個舊的代表B-spline動態特性模型與新的代表B-spline動態特性模型上，在一部份負載比下之複數個理論運轉效率值；以及計算該複數個理論運轉效率值之變異量，且如果該變異量大於一門檻值時，產生一警告。In another embodiment, the ice water host monitoring system 1 can further calculate a plurality of old representative B-spline dynamic characteristic models and a new representative B-spline dynamic characteristic model, a plurality of theories under a partial load ratio An operational efficiency value; and a variation of the plurality of theoretical operational efficiency values, and a warning if the variance is greater than a threshold.
在另一實施例中，冰水主機監測系統1可統計在一部份負載比下之複數筆實際運轉效率值，若該些實際運轉效率值之變異量大於一門檻值時，產生一警告。In another embodiment, the ice water host monitoring system 1 can count the actual operating efficiency values of the plurality of pens at a partial load ratio, and generate a warning if the variation of the actual operating efficiency values is greater than a threshold.
新的代表B-spline動態特性模型可與動態特性模型與原先之代表B-spline動態特性模型顯示在顯示裝置14，以供操作人員監看動態特性模型之變化趨勢。The new representative B-spline dynamic characteristic model can be displayed on the display device 14 with the dynamic characteristic model and the original representative B-spline dynamic characteristic model for the operator to monitor the trend of the dynamic characteristic model.
本揭露之技術內容及技術特點已揭示如上，然而熟悉本項技術之人士仍可能基於本揭露之教示及揭示而作種種不背離本創作精神之替換及修飾。因此，本揭露之保護範圍應不限於實施例所揭示者，而應包括各種不背離本創作之替換及修飾，並為以下之申請專利範圍所涵蓋。The technical content and technical features of the present disclosure have been disclosed above, but those skilled in the art can still make various substitutions and modifications without departing from the spirit and scope of the present invention. Therefore, the scope of the present disclosure is not to be construed as limited by the scope of
1．．．冰水主機監測系統1. . . Ice water host monitoring system
2．．．冰水主機2. . . Ice water host
11．．．擷取裝置11. . . Pickup device
12．．．運算裝置12. . . Arithmetic device
13．．．警示裝置13. . . Warning device
14．．．顯示裝置14. . . Display device
15．．．儲存裝置15. . . Storage device
S40~S51．．．流程步驟S40~S51. . . Process step
S60~S72．．．流程步驟S60~S72. . . Process step
圖1顯示本發明一實施例之冰水主機監測系統之連接示意圖；1 is a schematic diagram showing the connection of an ice water host monitoring system according to an embodiment of the present invention;
圖2顯示本發明一實施例之冰水主機監測系統之示意圖；2 is a schematic view showing an ice water host monitoring system according to an embodiment of the present invention;
圖3例示本發明一實施例之冰水主機動態特性模型之變化趨勢及前、後兩段時間之效率值分佈；FIG. 3 illustrates a change trend of the dynamic characteristics model of the ice water host and an efficiency value distribution of the front and rear time periods according to an embodiment of the present invention;
圖4顯示本發明一實施例之冰水主機動態特性模型建立方法之流程圖；4 is a flow chart showing a method for establishing a dynamic characteristic model of an ice water host according to an embodiment of the present invention;
圖5例示以黃金切割法搜尋最小移動變數；及Figure 5 illustrates the search for minimum movement variables by gold cutting; and
圖6顯示本發明一實施例之冰水主機監控方法之流程圖。FIG. 6 is a flow chart showing a method for monitoring an ice water host according to an embodiment of the present invention.
S40~S51．．．流程步驟S40~S51. . . Process step
Claims (21)
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| TW99135168A TWI414734B (en) | 2010-10-15 | 2010-10-15 | Dynamic modeling method, monitoring method for chilling system and device for monitoring chilling system |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI619910B (en) * | 2017-01-23 | 2018-04-01 | 神達電腦股份有限公司 | Ice water host control method |
| TWI795279B (en) * | 2022-04-27 | 2023-03-01 | 中國鋼鐵股份有限公司 | A method for regulating and controlling energy-saving operation of a chiller machine |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI727606B (en) * | 2020-01-14 | 2021-05-11 | 東元電機股份有限公司 | System of estimating maintenance time of chiller and the method thereof |
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| CN1796884A (en) * | 2004-12-30 | 2006-07-05 | 杭州华碧能源科技有限公司 | On site control device for cold water main unit in energy saving control system of central air conditioner |
| CN1869532A (en) * | 2006-04-25 | 2006-11-29 | 广州市地下铁道总公司 | Automatic control method for central cold supply system |
| CN101089503A (en) * | 2007-07-06 | 2007-12-19 | 北京时代嘉华环境控制科技有限公司 | Quality and regulation control method and system for chill station of central air conditioner |
| TW200951379A (en) * | 2009-07-30 | 2009-12-16 | Chunghwa Telecom Co Ltd | Function detection method |
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| CN1869532A (en) * | 2006-04-25 | 2006-11-29 | 广州市地下铁道总公司 | Automatic control method for central cold supply system |
| CN101089503A (en) * | 2007-07-06 | 2007-12-19 | 北京时代嘉华环境控制科技有限公司 | Quality and regulation control method and system for chill station of central air conditioner |
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| TWI619910B (en) * | 2017-01-23 | 2018-04-01 | 神達電腦股份有限公司 | Ice water host control method |
| TWI795279B (en) * | 2022-04-27 | 2023-03-01 | 中國鋼鐵股份有限公司 | A method for regulating and controlling energy-saving operation of a chiller machine |
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| TW201215824A (en) | 2012-04-16 |
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