CN104566765A

CN104566765A - Overall energy saving control method of central air conditioner

Info

Publication number: CN104566765A
Application number: CN201310485773.9A
Authority: CN
Inventors: 黄治钟; 张日耀
Original assignee: KARSUN INTERNATIONAL GROUP HOLDING Ltd
Current assignee: KARSUN INTERNATIONAL GROUP HOLDING Ltd
Priority date: 2013-10-16
Filing date: 2013-10-16
Publication date: 2015-04-29

Abstract

The invention discloses an overall energy saving control method a central air conditioner. The method is characterized by including: generating the behavior feature models of each equipment and the operating environment of the central air conditioner, updating the feature models, performing optimization calculation while the central air conditioner water system balance and heat and mass balance conditions are satisfied and on the basis of behavior feature predicting models, and executing optimal operating work conditions. The prediction-based overall energy saving control method of the central air conditioner has the advantages that the operation data of each equipment and the operating environment, the structure-uniformed and universal behavior feature predicting models of each equipment and the operating environment are generated and updated on the basis of the system identification technology, the behavior feature predicting models can constantly approach the actual operating features of each equipment and the operating environment in an online manner, and the equipment which is used for a long time and has performance degradation and deviation can be accurately predicted; the central air conditioner water system balance and heat and mass balance conditions are introduced into the prediction, and overall work condition optimization is achieved.

Description

Central air conditioning integrated energy-saving control method

Technical field

The present invention relates to Energy Saving Control, particularly central air conditioning integrated energy-saving control method.

Background technology

Along with socioeconomic development, the ratio of building energy consumption shared by entire society's total energy consumption is more and more higher, reach about 30%, and in whole building energy consumption, air-conditioning energy consumption has accounted for about 40% ~ 50%, therefore fully excavate Energy Saving of Central Air-conditioning space, not only can bring huge energy saving profit, be also conducive to realizing current day by day arduous target for energy-saving and emission-reduction simultaneously.

The design of current central air conditioner system is many carries out type selection calculation according to design load, and design load is basic close to annual peak load, in whole year operation, often the most of the time is in partial load condition to central air conditioning equipment selected by these design conditions, not only may there is disadvantageous operating condition at running on the lower load in equipment, and self energy consumption of whole central air conditioner system also can increase.

Conventional central air-conditioning robot control system(RCS) is mainly for different equipment, as handpiece Water Chilling Units, water pump, cooling tower and air-conditioning box, control respectively, on the one hand because control device is single, not only cannot ensure the overall efficiency of single equipment group, on the other hand, this traditional control mode cannot influencing each other in reflection system between distinct device, while likely causing a certain device energy conservation, significantly increasing appears in the energy consumption of whole air-conditioning system.

In addition, the existing energy-saving control method for central air conditioner based on forecast model and system, there is forecast model complexity, lack versatility, update mode is coarse, lack the problems such as unified control system, all belong to the Energy Saving Control of local, and most forecast model has no idea to consider that the problem of decay or offset of performance appears in system delay, equipment performance after long-term use completely.

Summary of the invention

Object of the present invention, to overcome the deficiencies in the prior art, a kind of central air conditioning integrated energy-saving control method based on prediction is provided, can to greatest extent on the basis of existing performance meeting each equipment of central air-conditioning, the running status of each equipment of adjustment central air-conditioning, thus central air-conditioning is in the most energy-conservation and the most reliable operation conditions all the time.

For realizing above object, the present invention is realized by following technical scheme:

Central air conditioning integrated energy-saving control method, is characterized in that, the method comprises the following steps:

Adopt identification technology, the input parameter of each equipment of setting central air conditioner system is as input vector, and the output parameter of each equipment of setting central air conditioner system, as output vector, generates and stores each equipment T of central air conditioner system respectively in the debug phase ₀the behavioral trait forecast model in moment, for predicting the output parameter of each equipment;

Adopt identification technology, the input parameter of setting central air conditioner system running environment is as input vector, and the output parameter of setting central air conditioner system running environment, as output vector, generates in the debug phase and stores central air conditioner system running environment T ₀the behavioral trait model in moment, for predicting the refrigeration duty of central air-conditioning;

Running central air-conditioning, is a sense cycle with t1, gathers and stores the related data of each equipment of central air-conditioning and running environment, as or by calculate obtain input, the real time data of output vector;

Be energy optimization cycle adopt identification technology with t2, principle in setting range, the behavioral trait forecast model of each equipment of online updating and the behavioral trait forecast model of running environment is according to keeping the deviation of the prediction data of output vector and the real time data of output vector; Call the behavioral trait forecast model of current time running environment, the refrigeration duty of the central air-conditioning of prediction subsequent time; When the epidemic disaster condition needs of satisfied indoor setting and central air conditioner system water system balance and heat and mass balance, be target to the maximum with the total Energy Efficiency Ratio of central air-conditioning, be optimized calculating, obtain the optimal operating condition of each equipment of central air-conditioning;

Optimal operating condition is performed by each equipment of central air conditioner system.

Preferably, the behavioral trait forecast model of described each equipment and the behavioral trait forecast model of running environment are behavioral trait matrix, described behavioral trait matrix reflects the logical relation between each input vector and corresponding output vector, for unknown in a certain input vector or output vector, other all input vectors and (or) output vector known when, predict Unknown worm vector or output vector, behavioral trait matrix line number and columns are the integer being more than or equal to 1.

Preferably, the algorithm of described behavioral trait matrix is Y=BF (AX), Y is output vector, and X is input vector, and A, B are behavioral trait matrix, and F is characteristic function, for any bounded and continuous derivatived functions.

Preferably, described behavioral trait matrix comprises the behavioral trait matrix of the behavioral trait matrix of handpiece Water Chilling Units, the behavioral trait matrix of cooling water pump, chilled water pump behavioral trait matrix, the behavioral trait matrix of cooling tower, the behavioral trait matrix of surface cooler and tail-end blower fan.

Preferably, the input vector of described handpiece Water Chilling Units comprises the supply water temperature of the refrigeration duty of central air-conditioning, cooling water, the supply water temperature of chilled water, and output vector is the Energy Efficiency Ratio of handpiece Water Chilling Units; The input vector of described chilled water pump comprises chilled-water flow ratio, and output vector comprises the power of motor of chilled water pump; The input vector of described cooling water pump comprises cooling water flow ratio, and output vector comprises the power of cooling water pump motor; The input vector of described cooling tower comprises outdoor air humiture, and cooling water flow, cooling water supply, return water temperature, and output vector comprises blower fan of cooling tower power; The input vector of described surface cooler comprises the air ' s wet bulb temperature, air quantity, chilled water supply water temperature and the chilled-water flow by surface cooler that enter surface cooler, and output vector comprises the heat exchange amount of surface cooler; The input vector of described blower fan is the air quantity ratio by blower fan, and output vector comprises the power of blower fan.

Preferably, the input vector of described running environment comprises outdoor air wet and dry bulb temperature, corresponding measurement moment, and output vector comprises the refrigeration duty of central air conditioner system.

Preferably, the input vector of described running environment also comprises outdoor solar radiation value.

Preferably, described t1 is 10 ~ 120 seconds.

Preferably, described central air conditioning water system thermal balance is shown with following formula table:

m_{cw} \cdot C_{p} \cdot (T_{cws} - T_{cwr}) = Q \cdot \frac{1 + COP}{COP}

Described heat and mass balance shows with following formula table:

Q = {\overset{\cdot}{m}}_{a} \cdot (h_{r} - h_{s}) + {\overset{\cdot}{m}}_{o} \cdot (h_{o} - h_{r})

{\overset{\cdot}{m}}_{r} = {\overset{\cdot}{m}}_{a} - {\overset{\cdot}{m}}_{o}

Wherein:

COP: cold Energy Efficiency Ratio

C _p: specific heat of water, constant 4.186

M _cw: cooling water flow

send into the air output in room

outdoor resh air requirement

return air amount

T _cws: cooling water supply temperature

T _cwr: cooling water return water temperature

H _a: surface cooler air intake enthalpy

H _s: air-supply enthalpy

H _o: fresh air enthalpy

H _r: return air enthalpy

Q: central air-conditioning refrigeration duty.

Preferably, according to the algorithm of behavioral trait matrix, the Q/COP in described central air conditioning water system equation of equilibrium is set as output vector Y _{water system}, by matrix [1m _cwc _p(T _cws-T _cwr) Q] ^tbe set as input vector, thus generate the behavioral trait matrix B of water system _{water system}, B _{water system}=[01-1];

According to the algorithm of behavioral trait matrix by the matrix in described tail end of central air conditioner heat and mass balance formula be set as output vector Y _end, by matrix be set as X _end, thus generate the behavioral trait matrix B of air conditioning terminal system _end,

Preferably, the online updating of described behavioral trait forecast model, comprises the following steps:

In the debug phase, choose W the continuous each equipment of sense cycle central air conditioner system and the input vector of running environment and the real time data of output vector to combine according to the structure of each behavioral trait matrix, and calculate according to the algorithm of behavioral trait forecast model, by the result of calculating stored in database, generate T ₀the behavioral trait forecast model in moment, in order to calling in the next energy optimization cycle, W be greater than 1 integer;

Transfer the real time data of each input vector that each sense cycle stores, call T ₀each behavioral trait forecast model in moment, the corresponding output vector of each sense cycle is predicted, obtain the prediction data of the corresponding output vector of each sense cycle, calculate and store the prediction deviation of each sense cycle output vector prediction data and corresponding output vector real time data;

Initial time T in the next energy optimization cycle ₁, calculate and comprise T ₁time be engraved in the prediction deviation sum of interior front K sense cycle continuously, as accumulative prediction deviation, K be more than or equal to 1 integer, K is less than W; T ₁moment is later than T ₀moment.

When accumulative prediction deviation is greater than setting range, read the central air-conditioning relevant device of W-1 sense cycle before the T1 moment or the input vector of running environment and the real time data of output vector, same to T ₁the input vector of the relevant device that the moment detects or running environment and the real time data composition data assemblies of output vector, adopt identification technology, generate T ₁the behavioral trait forecast model in moment replaces T ₀the behavioral trait forecast model in moment, called in order to the next energy optimization cycle;

When prediction deviation is less than or equal to setting range, continue to adopt T ₀the behavioral trait forecast model in moment, called in order to the next energy optimization cycle;

In arbitrary energy optimization cycle afterwards, the above-mentioned method repeatedly adopted, according to keeping the deviation of the prediction data of output vector and the real time data of output vector to be in principle in setting range, whether decision upgrades current behavioral trait forecast model.

Preferably, described time interval t2 is 10 ~ 60 minutes.

Preferably, described W is 200 ~ 2000.

Preferably, described K is 10 ~ 300.

Preferably, described optimized algorithm, comprise and calculate the Energy Efficiency Ratio of central air conditioner system in the input vector combinations of values situation that each equipment is different, the numerical value of input vector corresponding time maximum using Energy Efficiency Ratio is as the optimal operating condition of central air-conditioning, and described Energy Efficiency Ratio is the refrigeration duty of central air-conditioning and the ratio of each electrical equipment power sum.

Central air conditioning integrated energy-saving control system in the present invention, gather the service data of each equipment and running environment, generate based on identification technology and more new construction unified, the forecast model of general each equipment and running environment behavioral trait, constantly can approach the actual motion characteristic of each equipment and running environment online, even if longer to service time, to occur performance degradation, offset of performance equipment also can Accurate Prediction.Also introduce central air conditioning water system balance and heat and mass balance restriction condition participation prediction simultaneously, reach the object optimizing operating mode on the whole.Central air conditioning integrated energy-saving control system of the present invention, can realize controlling the energy-conservation of central air conditioning water system and wind system based on above-mentioned forecast model and Forecasting Methodology, the whole energy optimization to central air-conditioning can be realized on the basis reflecting each equipment current performance accurately, avoid occurring that single equipment energy consumption reduces, the situation that central air-conditioning integral energy consumption rises, really realizes air-conditioning system global optimization.

Accompanying drawing explanation

Fig. 1 is the structural representation of energy-saving control method for central air conditioner equipment therefor of the present invention

Fig. 2 is the fundamental diagram of all devices of energy-saving control method for central air conditioner of the present invention

Fig. 3 is surface cooler behavioral trait hardware algorithm device schematic diagram of the present invention

Fig. 4 is energy-saving control method for central air conditioner flow chart of the present invention

Detailed description of the invention

Below in conjunction with accompanying drawing, invention is described in detail:

As shown in Figure 1, central air conditioner system is generally divided into water system and wind system, the water circulation connecting line that water system comprises handpiece Water Chilling Units 91, chilled water pump 92, cooling water pump 93, cooling tower 94 and closes.Wind system comprises air conditioning terminal blower fan 95 and surface cooler 96 and blow pipeline 98 and air draft pipeline 97.Intelligent electric meter 5 is electrically connected with handpiece Water Chilling Units 91, chilled water pump 92, cooling water pump 93, cooling tower 94, air conditioning terminal blower fan 95 respectively, can show the power of above-mentioned electrical equipment in real time.

In central air conditioner system process of refrigerastion, handpiece Water Chilling Units 91 prepares the chilled water of uniform temperature, and the chilled water of low temperature is delivered to the surface cooler 96 of wind system via water circulation connecting line, carry out heat exchange with air-supply.Air conditioning terminal blower fan 95, according to the actual needs of indoor temperature and humidity, controls air output, i.e. cold.Chilled water through with air-supply heat exchange after temperature rise, pump into handpiece Water Chilling Units by chilled water pump 92, more again freeze through handpiece Water Chilling Units 91, recycle.The heat that handpiece Water Chilling Units 91 produces at work is absorbed by recirculated cooling water, cooling water cooling tower 94 outdoor pumps into handpiece Water Chilling Units 91 through cooling water pump 92, absorb during handpiece Water Chilling Units 91 works the heat produced, be back to outdoor cooling tower 94 again, carry out heat exchange with outside atmosphere, be finally dispersed in atmospheric environment.

L1 shown in Fig. 1 is air-supply trend: outdoor new wind enters air-supply pipeline, mix with a part of return air in air draft pipeline, form mixed wind, mixed wind is through surface cooler, heat exchange is carried out with chilled water, there is the change of humiture, send into indoor room by air conditioning terminal blower fan with certain air quantity, form air-supply; L2 is return air trend: the air of indoor room enters discharge air pipe line, and some mixes with the new wind in air-supply pipeline via the connecting line between air draft pipeline with air-supply pipeline, and all the other parts are discharged to room atmosphere from exhaust duct exit.

Central air conditioning integrated energy-saving control device as shown in Figure 1, Figure 2, Figure 3 shows in the present invention comprises: checkout gear, data acquisition and control device and industrial computer 1 and actuating unit.

Checkout gear comprises cooling-water temperature sensor 10, flow sensor 11, outdoor temperature humidity sensor 12 and wind system Temperature Humidity Sensor 13, chilled water differential pressure pickup 14, air flow sensor 20.Wherein cooling-water temperature sensor 10 comprises the first cooling-water temperature sensor 101, second cooling-water temperature sensor 102, the 3rd cooling-water temperature sensor 103, the 4th cooling-water temperature sensor 104; First cooling-water temperature sensor 101 is installed on chilled water return main 915 outer wall, for detecting the return water temperature T of chilled water _chwr, the second cooling-water temperature sensor 102 is arranged on chilled water water main 916 outer wall, for detecting chilled water supply water temperature T _chws, the 3rd cooling-water temperature sensor 103 is arranged on cooling water return main outer wall, for detecting cooling water return water temperature T _cwr, the 4th cooling-water temperature sensor 104 is arranged on cooling water supply pipe outer wall, for detecting cooling water supply temperature T _cws; Flow sensor 11 wherein comprises first flow sensor 111, second quantity sensor 112, and the straight length of first flow sensor 111 chilled water water main, for detecting chilled-water flow second quantity sensor 112 installs the straight length of cooling water house steward, for detecting cooling water flow flow m _ew; Wind system Temperature Humidity Sensor 13 wherein comprises air-supply Temperature Humidity Sensor 131, return air Temperature Humidity Sensor 132, mixed wind-warm syndrome humidity sensor 133, with indoor temperature and humidity sensing 134, air-supply Temperature Humidity Sensor 131 is arranged in the pipeline that in ajutage 98, close blower fan 95 exports, for detecting wet and dry bulb temperature and the relative humidity of air-supply, air-supply enthalpy h can be obtained by calculating _s, return air Temperature Humidity Sensor 132 is arranged on the middle part of exhaust duct 97, for detecting wet and dry bulb temperature and the relative humidity of return air, can obtain return air enthalpy by calculating; Mixed wind-warm syndrome humidity sensor 133 is arranged on the position of ajutage 97 near surface cooler 96, for detecting mixed wind, also be wet and dry bulb temperature and the relative humidity of surface cooler air intake, surface cooler air intake enthalpy can be obtained by calculating, indoor temperature and humidity sensor 134 is arranged on the relevant position of air-conditioned room, for wet and dry bulb temperature in sensing chamber and relative humidity; Outdoor temperature humidity sensor 12 is installed on the position near cooling tower 94 air inlet, for wet and dry bulb temperature and the relative humidity of sensing chamber's outer air; The two ends of chilled water differential pressure pickup 14 are arranged on chilled water water main and return main respectively, and for monitoring the operating pressure of central air conditioner system, guarantee system is run in safe range.Air flow sensor 20 is installed in the pipeline of ajutage 98, for detecting air output all sensors are all connected with Programmable Logic Controller 2 communication, and Programmable Logic Controller 2 gathers all data and is transferred to industrial computer 1.The communication unit (not shown) that handpiece Water Chilling Units 91 carries is for reading handpiece Water Chilling Units 91 internal operation parameter, comprise the chilled water temperature of condenser refrigerant pressure and temperature, evaporimeter refrigerant pressure and temperature, percentage of current, turnover evaporimeter, the turnover cooling water temperature of condenser and switch control rule amount and running status (as loaded, fault and operation etc.), and above-mentioned data are sent to the serial server 3 be connected with its communication, by serial server 3, above-mentioned data are transferred to industrial computer 1.

Data acquisition and control device comprise Programmable Logic Controller 2 and serial server 3, and Programmable Logic Controller 2 is connected with all sensor communication in checkout gear, for gathering all data that each sensor detects.Serial server 3 is connected by the communication component of Modbus agreement and handpiece Water Chilling Units 91 and intelligent electric meter 5 communication, each electrical equipment instantaneous power of service data and central air-conditioning for gathering handpiece Water Chilling Units 91.Programmable Logic Controller 2, serial server 5 are connected with industrial computer respectively, the service data collecting central air conditioner system can be sent to industrial computer 1, are processed by industrial computer 1 pair of data; Programmable Logic Controller 2 accepts the data operation result that industrial computer 1 sends, i.e. optimal operating condition, the actuating unit that the control respectively that programs is connected by communication with it, performs this optimal operating condition.Serial server 5 accepts the optimal operating condition of cold in the data operation result of industrial computer 1 transmission, controls handpiece Water Chilling Units 91 and performs this optimal operating condition.

Industrial computer 1 is connected with Programmable Logic Controller 2, serial server 3 communication respectively, receives the service data that Programmable Logic Controller 2 and serial server 3 collect, screens, combines service data, calculation process.In central air conditioner system actual moving process, according to the structure of each equipment behavior feature matrix preset and central air-conditioning running environment matrix, every 1 minute by one group of relevant (input, output vector) real-time running data stored in database.Utilize data in database with 15 minutes for one-period, identification is carried out to the forecast model of each equipment of central air conditioner system, call the up-to-date equipment behavior feature matrix that identification obtains and the refrigeration duty calling next cycle that the prediction of central air-conditioning service condition behavioural matrix obtains simultaneously, target is to the maximum with the total Energy Efficiency Ratio of central air-conditioning, be optimized calculating, prediction obtains the optimal operating condition of each equipment of central air-conditioning, and optimal operating condition is sent to Programmable Logic Controller 2 and serial server 3, by Programmable Logic Controller 2, serial server 3 controls actuating unit and performs this optimal operating condition.

Actuating unit comprises handpiece Water Chilling Units switching value valve 6, water bypass 7, chilled water control valve 8, chilled water by-passing valve 9, chilled water pump frequency converter 15, cooling water pump frequency converter 16, blower fan of cooling tower frequency converter 17, air conditioning terminal fan frequency converter 18, and air-valve 19.Air-valve 19 comprises new air-valve 191, air returning valve 192, exhaust valve 193.

Some handpiece Water Chilling Units switching value valves 6 be connected with Programmable Logic Controller 2 communication handpiece Water Chilling Units chilled water outlet pipe 911 and cooling water inlet pipe 912 are installed respectively pipeline on, for handpiece Water Chilling Units shut down after water-blocking path; Water bypass 7 is connected with Programmable Logic Controller 2 communication, being arranged on the connecting pipeline 913 between cooling water confession, return main, for regulating cooling water return water temperature (entering the water temperature of cooling tower), ensureing the safe operation of cooling tower.Chilled water by-passing valve is installed chilled water and is supplied back on the connecting pipeline 914 between house steward, and for regulating the operating pressure of the water system of central air conditioner system, guarantee system is run in safe range.Chilled water control valve 8 is connected with Programmable Logic Controller 2 communication, is arranged on chilled water pipe on the pipeline of surface cooler 96, for controlling the chilled-water flow entering surface cooler

Chilled water pump frequency converter 15, cooling water pump frequency converter 16, blower fan of cooling tower frequency converter 17, air conditioning terminal fan frequency converter 18 is connected with Programmable Logic Controller 2 communication by Modbus485 agreement, be electrically connected with chilled water pump 92, cooling water pump 93, blower fan of cooling tower 941, air-conditioning end blower fan 95 respectively simultaneously, instruction for accepting Programmable Logic Controller 2 controls the rotating speed of chilled water pump 92, cooling water pump 93, blower fan of cooling tower 941, air conditioning terminal blower fan 95, meets the optimal operating condition of central air conditioner system.New air-valve 191, air returning valve 192, exhaust valve 193 are connected by communication with Programmable Logic Controller 2 respectively, wherein new air-valve 191 is arranged on the import department of the new wind of central air-conditioning wind system, exhaust valve 193 is arranged on the exit of air draft pipeline 97, air returning valve 192 is arranged on air draft pipeline 97 with on the path of air-supply pipeline 98, for controlling the mixed wind enthalpy of air conditioning terminal, it is used to meet optimal operating condition.

As shown in Figure 4, the operating procedure of the central air conditioning integrated energy-saving control method based on prediction of the present invention, in actual Energy Saving Control process, first behavior identification technique is adopted to set the forecast model structural parameters of each equipment and running environment and input, output vector, generate the behavioral trait matrix structure of each equipment and running environment, stored in the database of industrial computer 1; In debug phase and follow-up commencement of commercial operation stage, every 1 minute, by detect all kinds of inputs, in the database of output parameter data in chronological order stored in industrial computer 1, the debug phase call the input of 600 consecutive periods, output parameter data carry out identification to behavioral trait matrix structure, form the current best behavioral trait matrix of each equipment and running environment respectively, by each behavioral trait matrix stored in database.

In first energy optimization cycle, call each best behavioral trait matrix stored in the input parameter measured data of each equipment of current time central air-conditioning and running environment and database, obtain the prediction data of the output parameter of each equipment and running environment, the predicted value of each output parameter and measured data are compared, if the deviation of output parameter predicted value and measured data is less than the zone of reasonableness of setting, then best behavioral trait matrix remains unchanged, if output parameter predicted value and measured data exceed the zone of reasonableness of setting, then call the input of current time, the input in output parameter measured value and current time front 599 cycles, the measured value of output parameter carries out identification again to each behavioral trait matrix, the result of identification is as current best behavioral trait matrix.

Call the best behavioral trait matrix of running environment, obtain next cycle of operation central air conditioner system refrigeration duty, i.e. refrigeration requirement, call the best behavioral trait matrix of handpiece Water Chilling Units, cooling water pump, chilled water pump, cooling tower, surface cooler and tail-end blower fan simultaneously, object function is to the maximum, by chilled water supply water temperature T with central air-conditioning integral Energy Efficiency Ratio _chws, cooling water supply temperature T _cws, cooling water return water temperature T _cwr, central air conditioner system refrigeration duty Q, outdoor resh air requirement air-supply wet and dry bulb temperature and room wet and dry bulb temperature etc. as independent variable, and just can to the behavioral trait of central air-conditioning carry out global optimization than maximum as object function using central air conditioner system total energy consumption effect, obtain the most energy-conservation method of operation.

After completing overall energy optimization, obtain the operating point of each equipment of the highest correspondence of central air-conditioning operational efficiency, control each equipment of central air-conditioning by actuating equipment of the present invention and perform this operating point.

Carry out primary energy consumption optimization every 15 minutes, obtain the operating condition in next cycle, and perform this optimal operating condition.

The present invention is in actual motion, and the generation of its behavioral trait matrix and renewal adopt identification technology to carry out in the following manner:

System Discrimination refers to the Mathematical Modeling determining descriptive system behavior according to the input and output of system, its objective is the differentiation in the future using the input and output of measuring (or can be calculated by measurement data) of system up to now to go prognoses system to export.

Central air conditioning integrated energy-saving control method based on prediction of the present invention, according to the object of identification, the output vector of the setting each equipment of central air conditioner system and running environment, i.e. behavior characterisitic parameter, the change that output vector can be caused to occur each equipment and running environment can survey parameter accordingly, be set to input vector.When adopting System Identification technology to predict the output vector of arbitrary equipment of running environment or central air-conditioning, its behavioral trait can be described namely by the form of math equation:

Y=B·F（A·X）+E

Wherein: Y is equipment or running environment behavioral trait parameter, i.e. output vector, and X is the input vector of this equipment or running environment, X, Y all obtain data by experiment or measurement; A, B are the behavioral trait matrix that behavioral trait parameter Y is corresponding, and A is linear combination matrix, and B is weighting matrix, and E is residual error; F is characteristic function, can be any bounded and the function can led continuously, and be generally the trigonometric function of Monotone Bounded or the rational function containing trigonometric function, the form of embodying is:

A = {[\begin{matrix} a_{11} & a_{12} & a_{13} & . . . & a_{1 n} & a_{1 (n + 1)} \\ a_{21} & a_{22} & a_{23} & . . . & a_{2 n} & a_{2 (n + 1)} \\ a_{31} & a_{32} & a_{33} & . . . & a_{3 n} & a_{3 (n + 1)} \\ . & . & . & . & . & . \\ . & . & . & . & . & . \\ . & . & . & . & . & . \\ a_{m 1} & a_{m 2} & a_{m 3} & . . . & a_{mn} & a_{m (n + 1)} \end{matrix}]}_{M \times (N + 1)},

B = {[\begin{matrix} b_{11} & b_{12} & b_{13} & . . . & b_{1 n} & b_{1 (m + 1)} \\ b_{21} & b_{22} & b_{23} & . . . & b_{2 n} & b_{1 (m + 1)} \\ b_{31} & b_{32} & b_{33} & . . . & b_{3 n} & b_{1 (m + 1)} \\ . & . & . & . & . & . \\ . & . & . & . & . & . \\ . & . & . & . & . & . \\ b_{l 1} & b_{l 2} & b_{l 3} & . . . & b_{\ln} & b_{l (m + 1)} \end{matrix}]}^{T}_{L \times (M + 1)},

E = [\begin{matrix} ϵ_{1} \\ ϵ_{2} \\ . \\ . \\ . \\ ϵ_{L} \end{matrix}], X = {[\begin{matrix} X_{1} \\ X_{2} \\ . \\ . \\ . \\ X_{n} \\ 1 \end{matrix}]}_{N + 1}, F = {[\begin{matrix} f \\ f \\ . \\ . \\ . \\ f \\ 1 \end{matrix}]}_{M + 1}

Wherein M, L are any positive integer, and N is the number of equipment input parameter in input vector, and T represents matrix transpose.

The input vector data obtained according to sampling when central air-conditioning debugging or operation and output vector data, by optimized algorithm, set different matrix A and B, make the output vector data of prediction and the output vector data deviation of actual measurement and E minimum, namely by calculating

Mi \underset{\cdot}{n} E^{T} \cdot E = Σ {(Y - B \cdot F (A \cdot X))}^{T} \cdot (Y - B \cdot F (A \cdot X))

After optimizing and calculating best behavioral trait matrix A and B, behavioral trait parameter can be expressed as: Y=BF(AX), after the concrete data of known behavioral trait matrix A, B and input vector, just can predict output vector, i.e. behavior characterisitic parameter Y.Thus reach the object of prediction.

The hardware unit of surface cooler behavioral trait algorithm as shown in Figure 3, for surface cooler, the acquisition of its behavioral trait matrix adopts following steps:

1) according to the object of surface cooler behavioral trait algorithm, that it needs to describe is heat output Q in diabatic process _{surface cooler}, setting output vector is heat output Q _{surface cooler}, that is:

Y _{surface cooler}=Q _{surface cooler}

2) according to surface cooler heat transfer process feature, what affect surface cooler heat output is mainly surface cooler air intake wet-bulb temperature, air output, chilled water supply water temperature and the water yield, and setting input vector is

Wherein, T _chwsfor chilled water supply water temperature, DEG C, recorded by cooling-water temperature sensor 101; T _mwbfor surface cooler air intake wet-bulb temperature, DEG C, recorded by mixed wind-warm syndrome humidity sensor 133; for chilled-water flow, kg/s, is recorded by flow sensor 111; for air output, kg/s, is recorded by air flow sensor 20, Q _{surface cooler}for surface cooler heat exchange amount, kW, its numerical value should equal its refrigeration duty should bear, at known air output and surface cooler air intake enthalpy and air-supply enthalpy when, Q _{surface cooler}by calculating;

3) according to the formation of output vector and input vector, setting behavioral trait matrix A _{surface cooler}and B _{surface cooler}be respectively the matrix of 5x5 and 1x6, characteristic function is f (a)=1.219 × arctan (0.9a), and wherein a is arbitrary component of gained column vector after AX is multiplied;

4), after having set, software generates behavioral trait matrix A automatically _{surface cooler}and B _{surface cooler}, after running behavior characteristics algorithm, 600T(cycle stored in debug phase automatic reading database) pretreatment air output chilled-water flow show cold ball air intake wet-bulb temperature T _mwb, chilled water supply water temperature T _chwsand surface cooler heat output Q _{surface cooler}, to behavioral trait matrix A _{surface cooler}and B _{surface cooler}carrying out identification, namely making surface cooler heat output Q by optimizing calculating acquisition _{surface cooler}prediction data and the minimum behavioral trait matrix A of measured data deviation _{surface cooler}and B _{surface cooler}, and stored in database.

The behavioral trait matrix of surface cooler can be generated, A by above step _{surface cooler}and B _{surface cooler}in each energy optimization cycle, different air outputs, chilled-water flow, surface cooler air intake wet-bulb temperature and chilled water supply water temperature numerical value are set, in conjunction with the behavioral trait matrix A obtained _{surface cooler}and B _{surface cooler}can caluclate table cooler heat output Q under various conditions _{surface cooler}, it predicts the outcome and supplies central air-conditioning integral energy optimization algorithm to call the overall energy optimization carrying out central air-conditioning.

As in a certain optimization cycle, the behavioral trait matrix A of surface cooler the best _{surface cooler}and B _{surface cooler}be respectively:

The surface cooler heat output Q under different running status just can be calculated according to behavioral trait algorithm Y=BF (AX) _{surface cooler}.As worked as air output and chilled-water flow be respectively 14kg/s and 12kg/s, surface cooler chilled water supply water temperature is 7 DEG C, when air intake wet-bulb temperature is 24 DEG C, can caluclate table cooler heat output be 331.4kW according to behavioral trait algorithm, and may wish that chilled water supply water temperature suitably improves in overall energy optimization is calculated, chilled water supply water temperature under this kind of operating mode is increased to 8.5 DEG C, then utilizes behavioral trait algorithm can caluclate table cooler heat output Q _{surface cooler}for 306.9kW.By that analogy, can to the heat output Q under any reasonable conditions of surface cooler _{surface cooler}predict.

For the behavioral trait matrix of other equipment of central air-conditioning or running environment, as long as adopt identification technique to set the input of its behavioral trait, the formation of output vector, the method that just can generate according to above-mentioned surface cooler behavioral trait matrix set, identification and application.In the present embodiment:

The output vector Y of handpiece Water Chilling Units behavioral trait _cold=COP _cold, COP _coldfor the Energy Efficiency Ratio of handpiece Water Chilling Units, input vector:

X _cold=[chilled water supply water temperature T _chwscooling water supply temperature T _cwsrefrigeration duty Q 1] ^t

The output vector Y of chilled water pump behavioral trait _{chilled water pump}=P _{chilled water pump}, P _{chilled water pump}for chilled water pump power, input vector:

Chilled water metered flow for chilled water pump metered flow under design of air conditioning operating mode, chilled water pump power reads by intelligent electric meter, chilled-water flow recorded by flow sensor 111;

The output vector Y of cooling water pump behavioral trait _{cooling water pump}=P _{cooling water pump}, P _{cooling water pump}for cooling water pump power, input vector:

Cooling water metered flow for coolant pump metered flow corresponding under design of air conditioning operating mode, cooling water pump power reads by intelligent electric meter, cooling water flow recorded by flow sensor 112;

The output vector Y of cooling tower behavioral trait _{cooling tower}=P _{blower fan of cooling tower}, P _{blower fan of cooling tower}for blower fan of cooling tower power, input vector:

P _{blower fan of cooling tower}read by intelligent electric meter, outdoor air temperature bulb temperature passes device 12 by outdoor temperature humidity and records; Cooling water flow recorded by flow sensor 112, cooling water supply temperature T _cwsrecorded by cooling-water temperature sensor 103, cooling water return water temperature T _cwrrecorded by cooling-water temperature sensor 104;

The output vector Y of air conditioning terminal blower fan behavioral trait _{tail-end blower fan}=P _{tail-end blower fan}, P _{tail-end blower fan}for air conditioning terminal power of fan, input vector:

Wherein, the specified air output of air conditioning terminal for the nominal air delivery under air conditioning terminal fan design operating mode, P _{tail-end blower fan}read by intelligent electric meter, air output recorded by air flow sensor 20;

Running environment behavioral trait output vector Y _{running environment}=Q, Q are cooling load of the air-conditioning system, input vector X _{running environment}=[outdoor air wet and dry bulb temperature measures the moment 1] ^twherein the measurement moment is generated automatically by software, outdoor air wet and dry bulb temperature is recorded by outdoor temperature humidity sensor 12, and cooling load of the air-conditioning system Q, when the needing of known outdoor air wet and dry bulb temperature and Indoor Dry bulb temperature and relative temperature and indoor temperature and relative humidity, can obtain by calculating.

Due to the natural wastage of each equipment of system and the change of self performance thereof, cause initial behavioral trait matrix always can Accurate Prediction output vector, the running environment of same central air-conditioning, i.e. natural environment, also and astable constant, therefore the present invention also adopts following Dynamic Identification mode to dynamically update behavioral trait matrix by software, dynamically updates in the following ways:

In central air-conditioning running, each equipment is according to the operating condition of current the best, the measured value (comprising input vector and output vector) being gathered each service data by each sensor is stored in the database of industrial computer 1 according to time sequencing with the time interval of 1 minute, the handpiece Water Chilling Units of current time is stored in reading database, chilled water pump, cooling water pump, cooling tower, surface cooler, the input vector of the behavioral trait matrix of air conditioning terminal blower fan and running environment and the system running environment of current time, predict the predicted value of each equipment and transportation environment output vector, calculate the deviation of output vector predicted value and measured value, i.e. prediction deviation, and stored in database.In an energy optimization cycle, first the forecasting accuracy of current behavioral trait matrix is judged: cumulative front 10 the continuous prediction deviations of current time, draw accumulative prediction deviation:

E = Σ_{i = 0}^{N} Err (i)

Wherein E is accumulative prediction deviation, the prediction deviation that front i-th sense cycle of %, Err (i) current time calculates, and K is the cumulative quantity of prediction deviation, and the present embodiment is taken as 10.

Should not be greater than 70% by the rationally accumulative prediction deviation of software set 10 sense cycle, work as E<70%, judge that current behavioral trait Matrix prediction result is accurate, without the need to upgrading; When E >=70%, judge that predicting the outcome of current behavioral trait matrix is inaccurate, then again read the historical data (input vector and output vector measured value) of current time several sense cycle front, the present embodiment adopts 599 cycles, the data assemblies of 600 sense cycle is formed together with the data of current time, identification technique is adopted to generate new behavioral trait matrix, for later prediction.

Can be guaranteed in the energy optimization cycle each time by the above-mentioned Dynamic Identification for equipment behavior characteristic, the accuracy of the behavioral trait Matrix prediction called is the highest, can react the real conditions of each equipment performance and running environment accurately.

In order to realize the overall energy consumption prediction to central air-conditioning of the present invention, the restriction condition suffered by when being run by central air-conditioning by software introduces energy optimization computational process, and be mainly the heat and mass balance condition of water system and wind system, its expression-form is:

Water system balance:

m_{cw} \cdot C_{p} \cdot (T_{cws} - T_{cwr}) = Q \cdot \frac{1 + COP}{COP}

Air conditioning terminal heat and mass balance:

Q = {\overset{\cdot}{m}}_{a} \cdot (h_{r} - h_{s}) + {\overset{\cdot}{m}}_{o} \cdot (h_{o} - h_{r})

{\overset{\cdot}{m}}_{r} = {\overset{\cdot}{m}}_{a} - {\overset{\cdot}{m}}_{o}

Wherein: Q is central air-conditioning refrigeration duty, kW; h _r, h _oand h _sbe respectively return air, new wind and air-supply enthalpy, kJ/kg; with be respectively air conditioning terminal fan delivery, resh air requirement and return air air quantity, kg/s; h _s, h _oand h _rbe respectively air-supply enthalpy, fresh air enthalpy and return air enthalpy, kJ/kg dry air, C _pfor specific heat of water;

The present invention, except adopting system identifying method, beyond the behavioral trait matrix forming each equipment and running environment, according to the expression way of behavioral trait algorithm by above-mentioned is equations turnedly also:

Water system thermal balance:

Input vector

Output vector

Water system behavioral trait matrix B _{water system}=[0 1-1] is a constant

Air conditioning terminal heat and mass balance:

Input vector

Output vector

End behavioral trait matrix

By above-mentioned B _endand B _{water system}also stored in database, each equipment of comprehensive central air-conditioning and water system and air conditioning terminal system heat and mass balance behavioral trait equation, just can obtain the behavioral trait of whole central air-conditioning:

Optimize in computational process at air-conditioning energy consumption, given as T _chws, T _cws, T _cwr, Q, the wet and dry bulb temperature of air-supply, the wet and dry bulb temperature of outdoor air and room wet and dry bulb temperature, call A _cold, B _cold, A _{chilled water pump}, B _{chilled water pump}, A _{cooling tower}, B _{cooling tower}, A _{tail-end blower fan}, B _{tail-end blower fan}, A _{surface cooler}, B _{surface cooler}, B _{water system}and B _endin behavioral trait matrix, just can solve above-mentioned central air-conditioning behavioral trait group.On this basis in conjunction with optimized algorithm, by T _chws, T _cws, T _cwr, Q, the wet and dry bulb temperature of outdoor air and room wet and dry bulb temperature etc. as independent variable, and just can be optimized the behavioral trait of whole central air-conditioning so that the total Energy Efficiency Ratio of central air-conditioning is maximum as object function, obtain the most energy-conservation operating condition.

Optimization computational process and the executive mode thereof of the present embodiment optimum fortune operating mode is described in detail below in conjunction with data:

As certain central air-conditioning, the specified refrigeration duty Q of a handpiece Water Chilling Units _specifiedwith Energy Efficiency Ratio COP _coldbe respectively 3767kW and 5.24, chilled water pump metered flow and rated power are respectively 650m ³/ h and 75kW, metered flow and the rated power of cooling water pump are respectively 800m ³/ h and 90kW, cooling tower rated power is 45kW, and the specified refrigeration duty of 10 air conditioning terminal surface coolers is 360kW, and blower fan rated power and nominal air delivery are 18kW and 51670m ³/ h.

Detect that the outdoor dry-bulb temperature of current time and relative humidity are 33 DEG C and 67% by outdoor temperature humidity sensor 12, corresponding wet-bulb temperature and enthalpy (obtaining as calculated) are 27.7 DEG C and 87kJ/kg, the optimum operation environmental behaviour feature matrix A stored in calling data storehouse _{running environment}and B _{running environment}can know that the refrigeration duty of central air-conditioning in next cycle of operation is 2700kW by computing, detect that space air dry-bulb temperature and relative humidity are 26 DEG C and 60% by indoor temperature and humidity sensor 133, corresponding water capacity (calculate and obtain) and enthalpy (calculate and obtain) are 12.8g/kg and 59kJ/kg, under above-mentioned indoor and outdoor surroundings condition, suppose chilled water supply water temperature T _chwsbe 8.4 DEG C, cooling water supply and return water temperature T _cwsand T _cwrbe 35.5 DEG C and 29.8 DEG C, the resh air requirement of each air-conditioning box for 3kg/s, air conditioning terminal wind pushing temperature and relative humidity are respectively 15 DEG C and 95% ,the behavioral trait matrix that can obtain current time central air conditioning water system and air conditioning terminal in conjunction with above-mentioned parameter is as follows:

The behavioral trait matrix of each equipment the best simultaneously stored in database is respectively:

Handpiece Water Chilling Units behavioral trait matrix:

Cooling tower behavioral trait matrix:

Surface cooler behavioral trait matrix:

Chilled water pump behavioral trait matrix:

Cooling water pump behavioral trait matrix:

Tail-end blower fan behavioral trait matrix:

The characteristic function adopted in the said equipment behavioral trait matrix computations process is the characteristic function in aforementioned surface cooler embodiment.

And complete following computational process:

1) single air conditioning terminal air output is calculated return air amount mixed rheumatism bulb temperature T _mwbaccording to air conditioning terminal behavioral trait matrix B _end, outdoor resh air requirement the refrigeration duty of outdoor air enthalpy and space air enthalpy and this cycle of operation central air-conditioning, cold Q, in conjunction with air conditioning terminal behavioral trait algorithm, can calculate single air-conditioning box air output for 10.33kg/s, return air amount for 7.33kg/s, mixed wind-warm syndrome humidity sensor can record mixed air temperature and relative humidity is respectively 26.9 DEG C and 69.8%, corresponding mixed rheumatism bulb temperature T _mwbit is 22.7 DEG C;

2) handpiece Water Chilling Units Energy Efficiency Ratio COP is calculated _cold

According to refrigerating capacity Q, the chilled water supply water temperature T of this cycle of operation central air-conditioning _chws, cooling water supply temperature T _cwsthe input vector of three variable compositions

And handpiece Water Chilling Units behavioral trait matrix A _coldand B _cold, can calculate handpiece Water Chilling Units COP cold is 5.2;

3) chilled-water flow is calculated

According to surface cooler air intake wet-bulb temperature T _mwb, air quantity chilled water supply water temperature T _chwswith the freezing water yield the input vector of composition surface cooler behavioral trait matrix A _{surface cooler}and B _{surface cooler}and the refrigerating capacity Q of this energy consumption optimization cycle, the chilled-water flow that can obtain each air-conditioning box is 14.8kg/s, the total flow of 10 air conditioning terminals for 148kg/s;

4) cooling water flow is calculated

According to cooling water supply and return water temperature T _cwsand T _cwr, cooling system amount Q and cold COP, Bound moisture system action feature matrix, cooling water flow for 134.8kg/s;

5) chilled water pump and cooling water pump power is calculated

According to the chilled-water flow calculated in conjunction with chilled water pump behavioral trait matrix A _{chilled water pump}and B _{chilled water pump}, chilled water pump power P can be calculated _{chilled water pump}for 55.2kW;

According to the cooling water flow calculated in conjunction with cooling water pump behavioral trait matrix A _{cooling water pump}and B _{cooling water pump}, cooling water pump power P can be calculated _{cooling water pump}for 50.1kW;

6) air conditioning terminal power of fan is calculated

According to the 1st) step calculate air conditioning terminal air quantity air conditioning terminal blower fan behavioral trait matrix A _{blower fan}and B _{blower fan}, can calculate single air conditioning terminal power of fan is 7.7kW, 10 air conditioning terminal blower fan general power P _{blower fan}for 77kW;

7) cooling tower power is calculated

According to the 4th) step calculate cooling water inflow m _cw, cooling water supply and return water temperature T _cwsand T _cwr, and the input vector of outdoor air wet bulb temperature composition utilize cooling tower behavioral trait matrix A _{cooling tower}and B _{cooling tower}, calculate blower fan of cooling tower power P _{cooling tower}for 31.3kW;

8) comprehensive above-mentioned result of calculation, calculates central air-conditioning integral energy consumption and total Energy Efficiency Ratio COP _{central air-conditioning}

The each air-conditioning box air output of air conditioning terminal is 10.33kg/s, and chilled water and cooling water flow are respectively 148l/s and 134.8l/s, the COP of handpiece Water Chilling Units _coldbe 5.2, power is 519kW, and the power of chilled water pump, cooling water pump and cooling tower is respectively 55.2kW, 50.1kW and 31.3kW, and in air conditioning terminal, the power of blower fan is 77kW, and therefore the total energy consumption of whole system is:

P _system=519kW+55.2kW+50.1kW+31.3kW+78kW=733.6kW

9) so under above-mentioned indoor and outdoor temperature and humidity conditions, different chilled water supply water temperature T is constantly set _chws, cooling water supply and return water temperature T _cwsand T _cwrwith the resh air requirement of each air-conditioning box air conditioning terminal wind pushing temperature and relative humidity just can complete the prediction to the whole behavioral trait of system under above-mentioned indoor and outdoor temperature and humidity conditions, obtain different result of calculation, the total Energy Efficiency Ratio COP of namely different central air-conditioning _{central air-conditioning}.

Under being chosen at above-mentioned indoor and outdoor temperature and humidity conditions by software, the chilled water supply water temperature T that the result of calculation that the systematic energy efficiency ratio that prediction obtains is the highest is corresponding _chws, cooling water supply and return water temperature T _cwsand T _cwr, chilled-water flow the resh air requirement of each air-conditioning box air conditioning terminal wind pushing temperature and relative humidity, as the operating condition of optimum, send instruction by industrial computer 1 to Programmable Logic Controller 2 and serial server 3, control each frequency converter and motor-driven valve makes each central air conditioning equipment perform above-mentioned optimal operating condition.

After optimal operating condition when acquisition Energy Efficiency Ratio is maximum, each equipment controls according to following requirement:

1) by cooling water return water temperature T _cwrsend to Programmable Logic Controller as cooling tower outlet water temperature setting value, then send instruction by Programmable Logic Controller to fan frequency converter, the rotating speed of final controlled cooling model tower blower fan;

2) by cooling water supply temperature T _cwscooling water supply temperature setting value as cooling water pump sends to Programmable Logic Controller, then sends instruction by Programmable Logic Controller to cooling water pump frequency converter, the final rotating speed controlling controlled cooling model water pump

3) by chilled water supply water temperature T _chwssend to serial server as handpiece Water Chilling Units water outlet temperature setting value, then send instruction by serial server to the control unit of handpiece Water Chilling Units, control the leaving water temperature of handpiece Water Chilling Units

4) by chilled-water flow send to Programmable Logic Controller as chilled water pump flow setting value, then send instruction by Programmable Logic Controller to chilled water pump frequency converter, the final rotating speed controlling chilled water pump

5) by each air-conditioning box air output send to Programmable Logic Controller as air conditioning terminal compressor flow setting value, then send instruction by Programmable Logic Controller to air conditioning terminal blower fan, final control air conditioning terminal rotation speed of fan.

6) wind enthalpy h will be mixed _aprogrammable Logic Controller is sent to as air conditioning terminal air-valve setting value, then by the new air-valve of Controlled by Programmable Controller, exhaust valve and air returning valve aperture.

After Programmable Logic Controller and the operation of communication server according to each equipment of above-mentioned optimal operating condition set value calculation central air conditioner system, each checkout equipment (sensor) detects the actual operating data running environment data of central air-conditioning, and be stored to industrial computer, every 15 minutes, an identification is carried out to each behavioral trait matrix, makes predicting the outcome of behavioral trait matrix remain best; Repeat above-mentioned optimization computational process simultaneously, find out central air-conditioning tie up to the indoor and outdoor surroundings condition of current runtime under optimized operation operating mode, and again to perform.The present invention is directed to air-conditioning system to run and energy-conservation feature, adopt the energy optimization algorithm based on system action prediction, behavioral trait respectively for various equipment and load etc. carries out identification, and in energy optimization system operation, constantly calculate to its error, ensure that Systematical control accurately and reliably, the realization of strong guarantee air-conditioning system energy conservation object on the whole; Meanwhile, on the behavioral trait basis of obtaining parts, behavior prediction optimization is carried out to whole air-conditioning system, conservative control system cloud gray model, ensure that whole system operates in the highest running status point of Energy Efficiency Ratio, ensure that the realization of target for energy-saving and emission-reduction.

Claims

1. central air conditioning integrated energy-saving control method, is characterized in that, the method comprises the following steps:

2. central air conditioning integrated energy-saving control method according to claim 1, it is characterized in that: the behavioral trait forecast model of described each equipment and the behavioral trait forecast model of running environment are behavioral trait matrix, described behavioral trait matrix reflects the logical relation between each input vector and corresponding output vector, for unknown in a certain input vector or output vector, other all input vectors and (or) output vector known when, Unknown worm vector or output vector are predicted, behavioral trait matrix line number and columns are the integer being more than or equal to 1.

3. central air conditioning integrated energy-saving control method according to claim 2, it is characterized in that: the algorithm of described behavioral trait matrix is Y=BF (AX), Y is output vector, X is input vector, A, B are behavioral trait matrix, F is characteristic function, for any bounded and the function can led continuously.

4. central air conditioning integrated energy-saving control method according to claim 2, is characterized in that: described behavioral trait matrix comprises the behavioral trait matrix of the behavioral trait matrix of handpiece Water Chilling Units, the behavioral trait matrix of cooling water pump, chilled water pump behavioral trait matrix, the behavioral trait matrix of cooling tower, the behavioral trait matrix of surface cooler and tail-end blower fan.

5. central air conditioning integrated energy-saving control method according to claim 4, it is characterized in that: the input vector of described handpiece Water Chilling Units comprises the supply water temperature of the refrigeration duty of central air-conditioning, cooling water, the supply water temperature of chilled water, output vector comprises the Energy Efficiency Ratio of handpiece Water Chilling Units; The input vector of described chilled water pump comprises chilled-water flow ratio, and output vector comprises the power of motor of chilled water pump; The input vector of described cooling water pump comprises cooling water flow ratio, and output vector comprises the power of cooling water pump motor;

The input vector of described cooling tower comprises outdoor air humiture, cooling water flow, cooling water confession, return water temperature, and output vector comprises blower fan of cooling tower power; The input vector of described surface cooler comprises the air ' s wet bulb temperature, air quantity, chilled water supply water temperature and the chilled-water flow by surface cooler that enter surface cooler, and output vector comprises the heat exchange amount of surface cooler; The input vector of described tail-end blower fan comprises the air quantity ratio by tail-end blower fan, and output vector comprises the power of tail-end blower fan.

6. central air conditioning integrated energy-saving control method according to claim 1, is characterized in that, the input vector of described running environment comprises outdoor air wet and dry bulb temperature, corresponding measurement moment, and output vector comprises the refrigeration duty of central air conditioner system.

7. central air conditioning integrated energy-saving control method according to claim 6, its characteristic is, the input vector of described running environment also comprises outdoor sun total radiation intensity level.

8. central air conditioner system whole energy control method according to claim 1, is characterized in that, described t1 is 10 seconds to 120 seconds.

9. central air conditioner system whole energy control method according to claim 1, is characterized in that: described central air conditioning water system water balance shows with following formula table:

m_{cw} \cdot C_{p} \cdot (T_{cws} - T_{cwr}) = Q \cdot \frac{1 + COP}{COP}

Described heat and mass balance shows with following formula table:

Q = {\overset{\cdot}{m}}_{a} \cdot (h_{r} - h_{s}) + {\overset{\cdot}{m}}_{o} \cdot (h_{o} - h_{r})

{\overset{\cdot}{m}}_{r} = {\overset{\cdot}{m}}_{a} - {\overset{\cdot}{m}}_{o}

Wherein:

COP: cold Energy Efficiency Ratio

C _p: specific heat of water, constant 4.186

M _cw: cooling water flow

send into the air output in room

outdoor resh air requirement

return air amount

T _cws: cooling water supply temperature

T _cwr: cooling water return water temperature

H _a: surface cooler air intake enthalpy

H _s: air-supply enthalpy

H _o: fresh air enthalpy

H _r: return air enthalpy

Q: central air-conditioning refrigeration duty.

10. central air conditioner system whole energy control method according to claim 9, is characterized in that:

According to the algorithm of behavioral trait matrix, the Q/COP in described central air conditioning water system equation of equilibrium is set as output vector Y _{water system}, by matrix [1m _cWc _p(T _cWS-T _cW), Q] ^tbe set as input vector, thus generate the behavioral trait matrix B of water system _{water system}, B _{water system}=[01-1];

11. central air conditioner system whole energy control methods according to claim 1, it is characterized in that, the online updating of described behavioral trait forecast model, comprises the following steps:

When accumulative prediction deviation is greater than setting range, read T ₁the central air-conditioning relevant device of W-1 sense cycle or the input vector of running environment and the real time data of output vector before moment, same to T ₁the input vector of the relevant device that the moment detects or running environment and the real time data composition data assemblies of output vector, adopt identification technology, generate T ₁the behavioral trait forecast model in moment replaces T ₀the behavioral trait forecast model in moment, called in order to the next energy optimization cycle;

In arbitrary energy optimization cycle afterwards, the above-mentioned method repeatedly adopted, according to keeping the deviation of the prediction data of output vector and the real time data of output vector to be in principle in setting range, whether decision upgrades current behavioral trait forecast model

12. central air conditioning integrated energy-saving control methods according to claim 1, is characterized in that: described time interval t2 is 10 to 60 minutes.

13. central air conditioning integrated energy-saving control methods according to claim 11, is characterized in that: described W is 200 to 2000.

14. central air conditioning integrated energy-saving control methods according to claim 11, is characterized in that: described K is 10 to 300.

15. central air conditioner system whole energy control methods according to claim 1, it is characterized in that: described optimized algorithm, comprise and calculate the Energy Efficiency Ratio of central air conditioner system in the input vector combinations of values situation that each equipment is different, the numerical value of input vector corresponding time maximum using Energy Efficiency Ratio is as the optimal operating condition of central air-conditioning, and described Energy Efficiency Ratio is the refrigeration duty of central air-conditioning and the ratio of each electrical equipment power sum.