CN116558049A - System and optimal control method based on central air conditioner load dynamic prediction - Google Patents
System and optimal control method based on central air conditioner load dynamic prediction Download PDFInfo
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 182
- 238000005265 energy consumption Methods 0.000 claims abstract description 76
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- 238000004378 air conditioning Methods 0.000 claims abstract description 33
- 238000005057 refrigeration Methods 0.000 claims abstract description 21
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- 239000003570 air Substances 0.000 claims description 98
- 230000017525 heat dissipation Effects 0.000 claims description 15
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
- F24F11/46—Improving electric energy efficiency or saving
- F24F11/47—Responding to energy costs
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/70—Control systems characterised by their outputs; Constructional details thereof
- F24F11/80—Control systems characterised by their outputs; Constructional details thereof for controlling the temperature of the supplied air
- F24F11/83—Control systems characterised by their outputs; Constructional details thereof for controlling the temperature of the supplied air by controlling the supply of heat-exchange fluids to heat-exchangers
- F24F11/85—Control systems characterised by their outputs; Constructional details thereof for controlling the temperature of the supplied air by controlling the supply of heat-exchange fluids to heat-exchangers using variable-flow pumps
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- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
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- Y02B30/70—Efficient control or regulation technologies, e.g. for control of refrigerant flow, motor or heating
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Abstract
The invention belongs to the technical field of heating ventilation air conditioning and automatic control, and particularly relates to a system and an optimization control method based on central air conditioning load dynamic prediction, wherein a cold load dynamic prediction model is established based on indoor variable parameters, outdoor variable parameters and model input parameters and is used for acquiring a cold load predicted value at the next moment; based on energy consumption equipment related to a central air-conditioning refrigeration system, establishing a system equipment energy consumption model; based on the predicted value of the cold load at the next moment as an input value of the energy consumption model of the system equipment, establishing a comprehensive energy consumption model of the system; based on the parameter constraint relation of the comprehensive energy efficiency of the system and the predicted value of the cold load at the next moment, a control optimization model of the central air conditioning refrigeration system is established, and the operation control strategy of a cold water unit, a chilled water pump, a cooling water pump and a cooling tower in a refrigerating machine room is optimized by establishing a dynamic prediction model of the cold load, an energy consumption model of system equipment and a control optimization model, so that the comprehensive energy efficiency can be optimized.
Description
Technical Field
The invention relates to the technical field of heating ventilation air conditioning and automatic control, in particular to a system based on central air conditioning load dynamic prediction and an optimal control method.
Background
The energy consumption of the large-scale public air conditioner is high, and the control optimization aims at adjusting the number of equipment opening and parameters such as water supply temperature, temperature difference, motor frequency, water flow and the like under the condition that the end load requirement is met so as to improve the overall energy efficiency of the system. In the prior art, automatic control such as remote startup and shutdown, water pump fan frequency conversion and the like is realized mainly through a BA machine room group control system, and a relatively accurate system energy consumption model and an optimal control method are lacked, so that the linkage control feedback of each device is lagged, supply and demand are not matched under the variable working condition running state of the system, manual operation is still needed, and the actual running comprehensive energy efficiency is relatively low.
In view of the foregoing, there is a need for a system and an optimization control method based on dynamic load prediction of a central air conditioner, which can coordinate intelligent optimization control of an automatic control system to realize accurate matching of supply and demand of a refrigeration machine room system, and is efficient and energy-saving to operate.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a system and an optimal control method based on the dynamic load prediction of a central air conditioner, which aim to solve the problems that the energy consumption of the existing large-scale public air conditioner is relatively high, the linkage control feedback of each device is lagged, the supply and demand are not matched, the manual operation is still needed, the actual operation comprehensive energy efficiency is relatively low, and the like.
In order to solve the technical problems, the invention adopts the following technical scheme:
a system and an optimization control method based on central air conditioner load dynamic prediction establish a cold load dynamic prediction model based on indoor variable parameters, outdoor variable parameters and model input parameters for obtaining a cold load predicted value at the next moment; based on energy consumption equipment related to a central air-conditioning refrigeration system, establishing a system equipment energy consumption model; taking the predicted value of the cold load at the next moment as an input value of a system equipment energy consumption model, and establishing a system comprehensive energy consumption model; based on the parameter constraint relation of the comprehensive energy efficiency of the system and the predicted value of the cold load at the next moment, a control optimization model of the central air conditioner refrigerating system is established and is used for optimizing the operation control strategy and parameters of the central air conditioner.
Preferentially, the indoor variable parameters comprise indoor personnel, indoor temperature, illumination and equipment power consumption; the outdoor variable parameters comprise outdoor dry bulb temperature, humidity, outdoor natural wind speed and outdoor solar radiation; the model input parameters comprise data mining cleaning, influence factor determination based on indoor and outdoor variable correlation analysis and principal component analysis determination input parameters.
Preferably, the correlation analysis is adopted to preliminarily screen the indoor variable parameters, the outdoor variable parameters and the model input parameters, so as to obtain the actual input parameters of the cold load dynamic prediction model, and the artificial neural network or the support vector regression prediction method is adopted to obtain the cold load predicted value at the next moment.
Preferably, the system equipment energy consumption model comprises a refrigerating unit energy consumption model, a cooling tower energy consumption model, a chilled water pump energy consumption model and a cooling water pump energy consumption model.
Preferably, the parameters in the refrigeration unit energy consumption model include:
evaporator refrigeration capacity: q (Q) e_chw =C P ×m chw ×(T chw_t -T chw_s ),
In which Q e_chw The refrigerating capacity of the evaporator of a single refrigerating unit is kW; c (C) P Specific heat capacity for chilled water; t (T) chw_r The return water temperature of the chilled water is in units of ℃; t (T) chw_s Water supply temperature for chilled waterDegree, units of deg.c; m is m chw The unit kg/s is the circulation flow of chilled water; condenser heat dissipation capacity: q (Q) e_ch =C P ×m cw ×(T cw_t -T cw_s ),
In which Q e_ch The heat dissipation capacity of a condenser of a single refrigerating unit is kW; c (C) P Specific heat capacity for cooling water; t (T) cw_r The unit is the temperature of the return water of the cooling water; t (T) cw_s The water supply temperature for the cooling water is given in the unit of DEG C; m is m cw The unit is kg/s for cooling water circulation flow;
according to the heat balance relation: q (Q) e_ch =Q e_chw +P ch ,
Wherein P is ch The power consumption of a compressor of a single refrigerating unit is kW;
compressor power consumption: p (P) ch =Q e_chw /COP ch ,
In the formula, COP ch The refrigerating energy efficiency of the refrigerating unit is achieved;
COP ch functional relation:
in the method, in the process of the invention,the load rate of the refrigerating unit is; t (T) chw_s The water supply temperature for the evaporator is given in units of ℃; t (T) cw_r The return water temperature of the condenser is given in the unit of DEG C;
COP ch fitting a curve function:wherein a is 0 ~a 4 Regression coefficients for the fitting function;
the sum of the refrigerating capacity of a plurality of refrigerating units needs to meet the terminal cold load demand: sigma Q e_chw =Q e0 ,
In which Q e0 And in order to predict the cold load, the result of the cold load dynamic prediction model is input.
Preferably, the cooling tower heat dissipation capacity model: the calculation is performed according to the classical heat transfer unit number (epsilon-NTU) method,
wherein, c s The specific heat capacity kg/(kJ. ℃) is determined for the average saturated air; h is a s,w,i ,h s,w,o Respectively the saturation enthalpy values of inlet air and outlet air; t is t w,i ,t w,o The temperature of the inlet air and the outlet air dry ball are respectively;
wherein m is a The quality and the air quantity of the fan are; c pw The constant pressure specific heat capacity of water; m is the heat capacity rate; m is m w,i For the mass flow of water into the cooling tower, the unit is kg/s;
wherein ε a The heat exchange efficiency is achieved; h is a a,0 ,h a,i Respectively the enthalpy values of the inlet air and the outlet air; h is a s,w,i Is the saturation enthalpy of the inlet air;
NTU is the number of heat transfer units; m is the heat capacity ratio;
the relation between the circulating water quantity and the fan air quantity is as follows:
wherein, the range of c is 0.5 to 5; n ranges from-1.1 to 0.35; m is m cw Is the flow of cooling water; NTU is the number of heat transfer units;
cooling tower wind energy consumption model: p (P) fun =b 0 +b 1 m a +b 2 m 2 a ,
Wherein P is fun The power consumption of the fan is kW; m is m a The mass air quantity of the fan is kg/s; b 0 ~b 2 Fitting coefficients;
according to the air quantity m of the fan da The relation with the frequency f or the rotation speed n is converted into:
wherein m is a0 The rated working condition air quantity of the fan is kg/s; m is m a1 The unit is kg/s of the air quantity of the running working condition of the fan; n is n fun0 The unit is r/min which is the rated working condition rotating speed of the fan; n is n fun1 The unit is r/min which is the rotation speed of the running working condition of the fan; f (f) fun0 The unit is HZ which is the rated working condition frequency of the fan; f (f) fun1 The unit is HZ which is the operating condition frequency of the fan;
wherein P is fun0 The power consumption is the rated working condition of the fan, and the unit is kW; p (P) fun1 The power consumption is the power consumption of the fan under the operation condition, and the unit is kW;
preferably, the chilled water pump energy consumption model: p (P) chwp =c 0 +c 1 m chwp +c 2 m chwp 2 Wherein, c 0 ~c 2 Fitting coefficients;
wherein m is chwp0 The unit is kg/s for rated working condition water flow of the chilled water pump; m is m chwp1 The unit is kg/s for the running condition water flow of the chilled water pump; n is n chwp0 The unit is r/min which is the rated working condition rotating speed of the chilled water pump; n is n chwp1 The unit is r/min which is the running working condition rotating speed of the chilled water pump; f (f) chwp0 The unit is HZ which is the rated working condition frequency of the chilled water pump; f (f) fun1 For freezingThe running working condition frequency of the water pump is HZ;
wherein P is chwp0 The power consumption is the rated working condition power consumption of the chilled water pump, and the unit is kW; p (P) chwp1 The power consumption is the power consumption of the running working condition of the chilled water pump, and the unit is kW;
preferably, the cooling water pump energy consumption model: p (P) cwp =d 0 +d 1 m cwp +d 2 m cwp 2 Wherein d is 0 ~d 2 In order to fit the coefficients of the coefficients,
P cwp the unit is kW for the power consumption of the cooling water pump; m is m cwp The unit is kg/s for cooling water mass flow;
wherein m is cwp0 The unit is kg/s for rated working condition water flow of the chilled water pump; m is m cwp1 The unit is kg/s for the running condition water flow of the chilled water pump; n is n cwp0 The unit is r/min which is the rated working condition rotating speed of the chilled water pump; n is n cwp1 The unit is r/min which is the running working condition rotating speed of the chilled water pump; f (f) cwp0 The unit is HZ which is the rated working condition frequency of the chilled water pump; f (f) cwp0 The unit is HZ which is the operating condition frequency of the chilled water pump;
wherein P is cwp0 The power consumption is the rated working condition of the cooling water pump, and the unit is kW; p (P) cwp1 And the unit of the power consumption is kW for the operation condition of the cooling water pump.
Preferably, the total energy consumption model is as follows:
wherein P is tot The total energy consumption of the refrigerating machine room system is kW; p (P) ch The unit is kW for the power consumption of the refrigerating unit; p (P) fun The power consumption of the cooling tower fan is kW; p (P) chwp The unit of the power consumption of the chilled water pump is kW; p (P) cwp The power consumption of the cooling water pump is kW; n (N) 1 ~N 4 The number of the refrigerating units, the cooling towers, the chilled water pumps and the cooling water pumps is respectively set; z is Z i Z is the device on state i =0 or 1,0 is unopened, 1 is on;
the comprehensive energy efficiency model of the system is as follows: COP of ss =Q e0 /P tot In the formula, COP ss The comprehensive energy efficiency of the system is realized; q (Q) e0 The unit is kW which is the predicted load of the central air conditioner; p (P) tot The total energy consumption of the refrigeration machine room system is in kW.
Preferably, the optimization target setting of the control optimization model of the central air-conditioning refrigeration system is as follows:
the mathematical model is as follows:
wherein P is tot The total energy consumption of the refrigerating machine room system is kW; p (P) ch The unit is kW for the power consumption of the refrigerating unit; p (P) fun The power consumption of the cooling tower fan is kW; z is Z i Z is the device on state i =0 or 1,0 is unopened, 1 is on; p (P) chwp The unit of the power consumption of the chilled water pump is kW; p (P) cwp The power consumption of the cooling water pump is kW;
maxCOP ss =max(Q e0 /P tot );
in the formula, COP ss For the comprehensive energy efficiency of the system, Q e0 The predicted load of the central air conditioner is kW; p (P) tot The total energy consumption of the refrigeration machine room system is kW;
constraint condition setting:
constraint of refrigerating capacity of central air conditioning system: the refrigeration capacity needs to meet the constraint of the cold load demand:
in which Q e_chw The refrigerating capacity of an evaporator of a single refrigerating unit is kW; z is Z i Z is the device on state i =0 or 1,0 is unopened, 1 is on; q (Q) e0 The predicted load of the central air conditioner is kW;
the frequency modulation range corresponding to the variable frequency water pump and the fan of the central air conditioning system is required to be within the specified range of equipment operation, and the constraint is as follows:
wherein f fun For fan frequency f chwp For the frequency of the chilled water pump, f cwp The frequency of the cooling water pump;
inlet and outlet water temperature constraint of central air conditioning system: the temperature of the chilled water is required to be within the set range of the controller, if the temperature of the chilled water is too high, the energy efficiency of the refrigerating unit can be reduced, and because the cold and hot towers exchange heat with the ambient air, the temperature of the chilled water is higher than the wet bulb temperature of the environment, and is generally considered according to the approximation degree of not less than 3 ℃, the energy efficiency is restricted to:
wherein T is chw_s Supply water temperature for refrigerating unit chilled water, T cw_s For the inlet temperature of cooling water of the refrigerating unit, T wb For the ambient wet bulb temperature around the cooling tower, min is the minimum value of the water temperature setting and max is the maximum value of the water temperature setting.
Constraint among devices of the central air conditioning system: the cooling load is generated by the end user, the chilled water exchanges heat with indoor air at the end equipment to generate a refrigerating effect, the temperature of the chilled water is increased, the chilled water is circulated to the side of an evaporator of the refrigerating unit for heat exchange through a water pump, the temperature of the chilled water is reduced, the cooling water is circulated to take away the heat dissipation of the condenser, and the heat is dissipated to the outdoor air through a fan of the cooling tower.
The refrigerating unit evaporator generates refrigerating capacity to meet the terminal cold load demand:in which Q e_chw The refrigerating capacity of an evaporator of a single refrigerating unit is kW, Z i Z is the device on state i =0 or 1,0 is unopened, 1 is on, Q e0 The predicted load of the central air conditioner is kW;
the evaporator absorbs heat in the chilled water: q (Q) e_chw =C P ×m chw ×(T chw_r -T chw_s ),
In which Q e_chw The refrigerating capacity of an evaporator of a single refrigerating unit is kW; c (C) P For the specific heat capacity of the chilled water, 4.18kJ/kg. ℃; t (T) chw_s The water supply temperature for the evaporator is given in units of ℃; t (T) cw_r The return water temperature of the condenser is given in the unit of DEG C;
cooling water carries the heat dissipation capacity of the condenser: q (Q) e_chw +P ch =C P ×m cw ×(T cw_r -T cw_s ) In which Q e_chw The refrigerating capacity of the evaporator of a single refrigerating unit is kW; c (C) P Specific heat capacity for chilled water; m is m cw The unit is kg/s for cooling water mass flow; t (T) cw_s 、T cw_r The temperature of the water for cooling water is given in the unit of DEG C;
relationship between cooling water pump and cooling tower: q (Q) e_chw +P ch =ε a m a (h s,w,i -h a,i )=m a (h a,o -h a,i ) In which Q e_chw The refrigerating capacity of the evaporator of a single refrigerating unit is kW; p (P) ch The power consumption of a compressor of a single refrigerating unit is kW; epsilon a The heat exchange efficiency is achieved; m is m a The mass air quantity of the fan is kg/s; h is a a,o ,h a,i Respectively the enthalpy values of the inlet air and the outlet air; h is a s,w,i Is the saturation enthalpy of the inlet air;
and (3) establishing an overall optimization model: combining the optimization target and the constraint condition to obtain an overall optimization model
maxCOP Ss =max(Q e0 /P tot ),
P in the formula tot The total energy consumption of the refrigerating machine room system is kW; p (P) ch The unit is kW for the power consumption of the refrigerating unit; p (P) fun The power consumption of the cooling tower fan is kW; p (P) chwp The unit of the power consumption of the chilled water pump is kW; p (P) cwp The power consumption of the cooling water pump is kW; n (N) 1 ~N 4 The number of the refrigerating units, the cooling towers, the chilled water pumps and the cooling water pumps is respectively set; z is Z i Z is the device on state i =0 or 1,0 is unopened, on, 1 is on;
in which Q e_chw The refrigerating capacity of an evaporator of a single refrigerating unit is kW; z is Z i Z is the device on state i =0 or 1,0 is unopened, 1 is on; q (Q) e0 The unit is kW which is the predicted load of the central air conditioner; c (C) P Specific heat capacity for chilled water; m is m chw The unit is kg/s for the mass flow of chilled water; t (T) chw_s 、T chw_r The temperature of the return water for the chilled water is given in the unit of DEG C; t (T) cw_s 、T cw_r The temperature of the water for cooling water is given in the unit of DEG C; p (P) ch The power consumption of a compressor of a single refrigerating unit is kW; m is m cw The unit is kg/s for cooling water mass flow; h is a a,o ,h a,i Respectively the enthalpy values of the inlet air and the outlet air; f (f) fun The unit is HZ for the fan frequency of the cooling tower; f (f) chwp The unit is HZ for the frequency of the chilled water pump; f (f) cwp The unit is HZ for cooling water pump frequency.
The beneficial effects of the invention include:
the invention is based on a central air-conditioning refrigeration system, and can realize comprehensive energy efficiency optimization by establishing a cold load dynamic prediction model, a system equipment energy consumption model and a control optimization model and optimizing operation control strategies of a cold water unit, a chilled water pump and a cooling tower in a refrigerating machine room in cooperation with actual control requirements of a building automatic control system.
Drawings
Fig. 1 is a schematic diagram of the principle of the present invention.
Fig. 2 is a schematic diagram of the principle of the present invention for predicting the cooling load.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, which are generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, as provided in the accompanying drawings, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, are intended to be within the scope of the present application.
The invention is further described in detail below with reference to fig. 1-2:
a system and an optimization control method based on central air conditioner load dynamic prediction establish a cold load dynamic prediction model based on indoor variable parameters, outdoor variable parameters and model input parameters for obtaining a cold load predicted value at the next moment; based on energy consumption equipment related to a central air-conditioning refrigeration system, establishing a system equipment energy consumption model; based on the predicted value of the cold load at the next moment as an input value of the energy consumption model of the system equipment, establishing a comprehensive energy consumption model of the system; based on parameter constraint relation of comprehensive energy efficiency of system and predicted value of cold load at next moment, control optimization of central air conditioning refrigerating system is establishedModel for optimizing operation control strategy and parameters of central air conditioner, T in FIG. 1 chw_s 、T chw_r For supplying back water temperature of chilled water, m _chw Is the flow of the chilled water; t (T) cw_s 、T cw_r For cooling water supply and return water temperature, m _cw Is the flow of cooling water; t (T) n_s 、T n_r Return air temperature for terminal equipment, m _n Circulating air quantity for terminal equipment; h is a _ai 、h _ao For the enthalpy value of the side inlet air and the outlet air of the fan of the cooling tower, m _a The air quantity of the fan of the cooling tower; t (T) wb Is the outdoor air wet bulb temperature; q (Q) _t ,Q _t+1 And respectively calculating load predicted values at the time t and the time t+1 by using a genetic algorithm to obtain an optimal control strategy finally, comparing the total system energy consumption and the comprehensive efficiency of the model calculation result and the measured data at different time points, and verifying the system model and the energy-saving optimization effect of the central air conditioner. Based on a system optimization control model, the optimal control of the cooling water flow, the control frequency of a cooling tower fan and a circulating water pump motor, the outlet water temperature of the cooling water, the inlet water temperature of the cooling water and the start and stop of various devices in the system can be realized.
The indoor variable parameters comprise indoor personnel change, indoor temperature, illumination and equipment power consumption; the outdoor variable parameters comprise outdoor dry bulb temperature, humidity, outdoor natural wind speed and outdoor solar radiation; the model input parameters comprise data mining cleaning, influence factor determination based on indoor and outdoor variable correlation analysis and principal component analysis determination input parameters.
The method comprises the steps of adopting correlation analysis to preliminarily screen indoor variable parameters, outdoor variable parameters and model input parameters to obtain actual input parameters of a cold load dynamic prediction model, adopting an artificial neural network or a support vector regression prediction method to obtain cold load prediction values at the next moment, analyzing influences of indoor and outdoor variable parameters on cold and heat loads, wherein the outdoor variable parameters comprise outdoor dry bulb temperature, wind speed, solar radiation and the like, indoor variables comprise people, time-by-time electricity consumption and the like, simultaneously considering influences of historical values of various variables on the cold and heat loads, adopting correlation analysis to preliminarily screen main influence factors to obtain actual input parameters of the model, and adopting an artificial neural network or a support vector regression prediction method to obtain cold load prediction values at the future moment, wherein a load prediction result is used as an input value of a system operation regulation optimization control model so as to improve comprehensive energy efficiency of the system.
The system equipment energy consumption model comprises a refrigerating unit energy consumption model, a cooling tower energy consumption model, a chilled water pump energy consumption model and a cooling water pump energy consumption model.
Model 2: establishing a system equipment energy consumption model
(1) Refrigerating unit energy consumption model generator refrigerating capacity: q (Q) e_chw =C P ×m chw ×(T chwr -T chw_s ) (1)
In the above, Q e_chw The refrigerating capacity of an evaporator of a single refrigerating unit is kW; c (C) P For the specific heat capacity of the chilled water, 4.18kJ/kg. ℃; t (T) chw_r The temperature is the return water temperature of the chilled water; t (T) chw_s Water supply temperature for chilled water, c.
Condenser heat dissipation capacity: q (Q) e_ch =C P ×m cw ×(T cw_r -T cw_s ) (2)
In the above, Q e_ch The heat dissipation capacity of a condenser of a single refrigerating unit is kW; c (C) p For the specific heat capacity of cooling water, 4.18kJ/kg. ℃; t (T) cw_r The temperature of the return water of the cooling water is set at DEG C; t (T) cw_s Water supply temperature for cooling water, DEG C.
According to the heat balance relation: q (Q) e_ch =Q e_chw +P ch (3)
In the above, P ch The power consumption of the compressor of a single refrigerating unit is kW.
Compressor power consumption: p (P) ch =Q e_chw /COP ch (4)
In the above, COP ch The refrigerating energy efficiency of the refrigerating unit is related to the equipment structure and the operation condition, and the COP can be specifically fitted ch With the equipment load rate, and the water temperature passing through and before the evaporatorIs a functional relation of (a).
COP ch Functional relation: COP of ch =f(φ,T chw_s ,T cw_r ) (5)
In the above description, phi is the load rate of the refrigerating unit, T chw_s Water supply temperature for evaporator, T cw_r Is the return water temperature of the condenser.
COP ch Fitting a curve function: COP of ch =a 0 +a 1 φ+a 2 φ 2 +a 3 (T chw_s -T cw_r )+a 4 (T chw_s -T cw_r ) 2 (6)
In the above, a 0 ~a 4 To fit the regression coefficients of the functions, the specific values may be obtained by fitting the device performance parameters.
The sum of the refrigerating capacity of a plurality of refrigerating units needs to meet the terminal cold load demand: sigma Q e_chw =Q e0 (7)
In the above, Q e0 To predict the cold load, the result of the dynamic load prediction model is input.
(2) Cooling tower energy consumption model
Cooling tower heat dissipation capacity model: the heat radiation characteristics of the cooling tower are related to various factors such as a cooling tower structure, an outdoor wet bulb temperature, a circulating water amount, a cooling tower water inlet temperature, a fan air volume and the like, and the relation formula of the circulating water amount and the fan air volume is as follows by referring to a cooling tower epsilon-NTU calculation model:
in the above formula, c and n fitting parameters can be obtained by fitting cooling tower test data provided by manufacturers, the range of c is generally 0.5-5, the range of n is generally-1.1-0.35, NTU is the number of heat transfer units, and can be calculated according to a classical heat transfer unit number (epsilon-NTU) method, and NTU is calculated according to formulas (8-1) - (8-4).
In the above, ε a For heat exchange efficiency, m is heat capacity, c s Constant pressure specific heat capacity kg/(kJ. ℃) for average saturated air, c pw For a constant pressure specific heat capacity of water, 4.18 kg/(kJ. ℃) h are taken a,o ,h a,i Respectively the enthalpy values of the inlet air and the outlet air, h s,w,i ,h s,w,o Respectively the saturation enthalpy value of inlet air and outlet air, t w,i ,t w,o The temperature of the inlet and outlet air dry balls is calculated to be c through a method of 8-1 s C, adding s M is calculated by substituting equation 8-2, and ε is calculated by substituting equation 8-3 for m a Will epsilon a Carried into 8-4, calculate NTU
Cooling tower wind energy consumption model: p (P) fun =b 0 +b 1 m a +b 2 m 2 a (9)
In the above, P fun The power consumption of the fan is kW; m is m a The mass air quantity of the fan is kg/s. b 0 ~b 2 And the fitting coefficient can be obtained by fitting according to the air quantity and fan energy performance parameter data provided by manufacturers. In actual control, the power supply frequency of the fan is changed to control the rotating speed of the fan, so that the air quantity is adjusted, and the frequency modulation range is generally 25-50 Hz. Because the actual air quantity is difficult to measure, the air quantity m of the fan can be used a The relation with the frequency f or the rotation speed n is converted into:
(3) Energy consumption model of chilled water pump
The refrigerating system chilled water pump generally adopts a centrifugal pump, and the power-flow characteristic relation can be fitted according to a quadratic polynomial:
and (3) a frozen water pump energy consumption model: p (P) chwp =c 0 +c 1 m chw +c 2 m chw 2 (11)
In the above, c 0 ~c 2 And fitting according to the equipment performance parameters provided by the manufacturer to obtain the fitting coefficient.The rotation speed of the refrigerating pump motor can be controlled by changing the power supply frequency of the refrigerating pump motor through a frequency converter so as to realize the adjustment of water flow, and the frequency adjustment range is generally 30-50 Hz.
(4) Cooling water pump energy consumption model
A cooling water pump of a refrigeration system generally adopts a centrifugal pump, and the power-flow characteristic relation can be fitted according to a quadratic polynomial:
cooling water pump energy consumption model: p (P) chp =d 0 +d 1 m cw +d 2 m cw 2 (13)
In the above, d 0 ~d 2 And fitting according to the equipment performance parameters provided by the manufacturer to obtain the fitting coefficient. The rotating speed of the cooling pump can be controlled by changing the power supply frequency of the cooling pump so as to realize the adjustment of water flow, and the frequency adjustment range is 30-50 Hz.
(5) Total energy consumption model of system
The total energy consumption of the refrigerating machine room system comprises the total energy consumption of four devices, namely a water chilling unit, a cooling tower fan, a chilled water pump and a cooling water pump, and the total energy consumption model is as follows:
in the above, P tot The total energy consumption of the refrigeration machine room system is kW; p (P) ch The power consumption of the refrigerating unit is kW; p (P) fun The power consumption of a cooling tower fan is kW; p (P) chwp The power consumption of the chilled water pump is kW; p (P) cwp The power consumption of the cooling water pump is kW; n (N) 1 ~N 4 The number of the refrigerating units, the cooling towers, the chilled water pumps and the cooling water pumps is respectively set; z is Z i In order to be in the on-state of the device,Z i =0 or 1,0 is unopened, 1 is on.
The comprehensive energy efficiency model of the central air conditioning system is as follows: COP of ss =Q e0 /P tot (16)
In the above, COP ss For the comprehensive energy efficiency of the system, Q e0 The predicted load of the central air conditioner is kW; p (P) tot And (5) the total energy consumption of the refrigeration machine room system is kW.
Model 3: establishing a control optimization model
The total energy consumption of the central air conditioning system is the sum of the energy consumption of four main equipment, certain parameters of different equipment are increased or reduced to change the energy consumption of the system, an overall optimization model of the central air conditioning refrigerating system is established through the constraint relation of the parameters, and then the overall optimization model is utilized to optimize the operation control strategy and parameters of the central air conditioner. Establishing an optimization model according to the optimization target, the constraint relation of each parameter and the constraint relation among the devices:
optimizing target setting:
the aim of the optimal control strategy for running the central air conditioning system equipment is to enable the total energy consumption of the whole system to be the lowest on the premise of meeting load requirements and normal running of the equipment, and meanwhile, the comprehensive system efficiency is the highest, and the mathematical model is as follows:
maxCOP ss =max(Q e0 /P tot ) (18)
(2) Constraint condition setting:
constraint of refrigerating capacity of central air conditioning system: the refrigeration capacity needs to meet the constraint of the cold load demand:
the frequency modulation range corresponding to the variable frequency water pump and the fan of the central air conditioning system is required to be within the specified range of equipment operation, and the constraint is as follows:
inlet and outlet water temperature constraint of central air conditioning system: the temperature of the chilled water is required to be within the set range of the controller, if the temperature of the chilled water is too high, the energy efficiency of the refrigerating unit can be reduced, and because the cold and hot towers exchange heat with the ambient air, the temperature of the chilled water is higher than the wet bulb temperature of the environment, and is generally considered according to the approximation degree of not less than 3 ℃, the energy efficiency is restricted to:
in the above, T chw_s Supply water temperature for refrigerating unit chilled water, T cw_s For the inlet temperature of cooling water of the refrigerating unit, T wb For the ambient wet bulb temperature around the cooling tower, min is the minimum value of the water temperature setting and max is the maximum value of the water temperature setting.
Constraint among devices of the central air conditioning system: the cooling load is generated by the end user, the chilled water exchanges heat with indoor air at the end equipment to generate a refrigerating effect, the temperature of the chilled water is increased, the chilled water is circulated to the side of an evaporator of the refrigerating unit for heat exchange through a water pump, the temperature of the chilled water is reduced, the cooling water is circulated to take away the heat dissipation of the condenser, and the heat is dissipated to the outdoor air through a fan of the cooling tower.
The refrigerating unit evaporator generates refrigerating capacity to meet the terminal cold load demand:
the evaporator absorbs heat in the chilled water: q (Q) e_chw =C P ×m chw ×(T chw_r -T chw_s ) (23)
Cooling water carries the heat dissipation capacity of the condenser: q (Q) e_chw +P ch =C P ×m cw ×(T cw_r -T cw_s ) (24)
Relationship between cooling water pump and cooling tower: q (Q) e_chw +P ch =ε a m a (h s,w,i -h a,i )=m a (h a,o -h a,i ) (25)
And (3) establishing an overall optimization model: combining the optimization target and the constraint condition to obtain an overall optimization model
maxCOP ss =max(Q e0 /P tot ), (27)
Model solving algorithm
And calculating the completed central air-conditioning refrigerating system model and the optimization model by utilizing a genetic algorithm to finally obtain an optimal control strategy, comparing the total system energy consumption and the comprehensive efficiency of the model calculation result and the measured data at different time points, and verifying the system model and the energy-saving optimization effect of the central air conditioner. Based on a system optimization control model, the optimal control of the cooling water flow, the control frequency of a cooling tower fan and a circulating water pump motor, the outlet water temperature of the cooling water, the inlet water temperature of the cooling water and the start and stop of various devices in the system can be realized.
The foregoing examples merely represent specific embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that, for those skilled in the art, several variations and modifications can be made without departing from the technical solution of the present application, which fall within the protection scope of the present application.
Claims (10)
1. A system and an optimization control method based on central air conditioner load dynamic prediction are characterized in that a cold load dynamic prediction model is established based on indoor variable parameters, outdoor variable parameters and model input parameters and is used for obtaining a cold load predicted value at the next moment; based on energy consumption equipment related to a central air-conditioning refrigeration system, establishing a system equipment energy consumption model; taking the predicted value of the cold load at the next moment as an input value of a system equipment energy consumption model, and establishing a system comprehensive energy consumption model; based on the parameter constraint relation of the comprehensive energy efficiency of the system and the predicted value of the cold load at the next moment, a control optimization model of the central air conditioner refrigerating system is established and is used for optimizing the operation control strategy and parameters of the central air conditioner.
2. The system and the optimal control method based on the central air conditioning load dynamic prediction according to claim 1, wherein the indoor variable parameters comprise indoor personnel, indoor temperature and lighting and equipment power consumption; the outdoor variable parameters comprise outdoor dry bulb temperature, humidity, outdoor natural wind speed and outdoor solar radiation; the model input parameters comprise data mining cleaning, influence factor determination based on indoor and outdoor variable correlation analysis and principal component analysis determination input parameters.
3. The system and the optimization control method based on the central air conditioner load dynamic prediction according to claim 2 are characterized in that correlation analysis is adopted to preliminarily screen indoor variable parameters, outdoor variable parameters and model input parameters, actual input parameters of a cold load dynamic prediction model are obtained, and an artificial neural network or support vector regression two prediction methods are adopted to obtain a cold load predicted value at the next moment.
4. The system and the optimization control method based on the central air conditioning load dynamic prediction according to claim 1, wherein the system equipment energy consumption model comprises a refrigerating unit energy consumption model, a cooling tower energy consumption model, a chilled water pump energy consumption model and a cooling water pump energy consumption model.
5. The system and the optimization control method based on the central air conditioning load dynamic prediction according to claim 1, wherein parameters in the refrigerating unit energy consumption model comprise:
evaporator refrigeration capacity: q (Q) e_chw =C P ×m chw ×(T chw_r -T chw_s ),
In which Q e_chw The refrigerating capacity of the evaporator of a single refrigerating unit is kW; c (C) P Specific heat capacity for chilled water; t (T) chw_r The return water temperature of the chilled water is in units of ℃; t (T) chw_s The water supply temperature is the unit of the chilled water; m is m chw The unit kg/s is the circulation flow of chilled water; condenser heat dissipation capacity: q (Q) e_ch =C P ×m cw ×(T cw_r -T cw_s ),
In which Q e_ch The heat dissipation capacity of a condenser of a single refrigerating unit is kW; c (C) P Specific heat capacity for cooling water; t (T) cw_r The unit is the temperature of the return water of the cooling water; t (T) cw_s The water supply temperature for the cooling water is given in the unit of DEG C; m is m cw The unit is kg/s for cooling water circulation flow;
according to the heat balance relation: q (Q) e_ch =Q e_chw +P ch ,
Wherein P is ch The power consumption of a compressor of a single refrigerating unit is kW;
compressor power consumption: p (P) ch =Q e_chw /COP ch ,
In the formula, COP ch The refrigerating energy efficiency of the refrigerating unit is achieved;
COP ch functional relation:
in the method, in the process of the invention,the load rate of the refrigerating unit is; t (T) chw_s The water supply temperature for the evaporator is given in units of ℃; t (T) cw_r The return water temperature of the condenser is given in the unit of DEG C;
COP ch fitting a curve function:wherein a is 0 ~a 4 Regression coefficients for the fitting function;
the sum of the refrigerating capacity of a plurality of refrigerating units needs to meet the terminal cold load demand: sigma Q e_chw =Q e0 ,
In which Q e0 And in order to predict the cold load, the result of the cold load dynamic prediction model is input.
6. The system and the optimization control method based on the central air conditioning load dynamic prediction according to claim 1, wherein the cooling tower heat dissipation capacity model is as follows: the calculation is performed according to the classical heat transfer unit number (epsilon-NTU) method,
wherein, c s The specific heat capacity kg/(kJ. ℃) is determined for the average saturated air; h is a s,w,i ,h s,w,o Respectively the saturation enthalpy values of inlet air and outlet air; t is t w,i ,t w,o The temperature of the inlet air and the outlet air dry ball are respectively;
wherein ma is the mass air quantity of the fan; c pw The constant pressure specific heat capacity of water; m is the heat capacity rate; m is m w,i For the mass flow of water into the cooling tower, the unit is kg/s;
wherein ε a The heat exchange efficiency is achieved; h is a a,o ,h a,i Respectively the enthalpy values of the inlet air and the outlet air; h is a s,w,i Is the saturation enthalpy of the inlet air;
NTU is the number of heat transfer units; m is the heat capacity ratio;
the relation between the circulating water quantity and the fan air quantity is as follows:
wherein, the range of c is 0.5 to 5; n ranges from-1.1 to 0.35; m is m cw Is the flow of cooling water; NTU is the number of heat transfer units;
cooling tower wind energy consumption model: p (P) fun =b 0 +b 1 m a +b 2 m 2 a ,
Wherein P is fun The power consumption of the fan is kW; m is m a The mass air quantity of the fan is kg/s; b 0 ~b 2 Fitting coefficients;
according to the air quantity m of the fan da The relation with the frequency f or the rotation speed n is converted into:
wherein m is a0 The rated working condition air quantity of the fan is kg/s; m is m a1 The unit is kg/s of the air quantity of the running working condition of the fan; n is n fun0 The unit is r/min which is the rated working condition rotating speed of the fan; n is n fun1 The unit is r/min which is the rotation speed of the running working condition of the fan; f (f) fun0 The unit is HZ which is the rated working condition frequency of the fan; f (f) fun1 The unit is HZ which is the operating condition frequency of the fan;
wherein P is fun0 The power consumption is the rated working condition of the fan, and the unit is kW; p (P) fun1 And the unit is kW for the power consumption of the fan under the operation condition.
7. The system and the optimal control method based on the dynamic prediction of the central air conditioner load according to claim 6 are characterized in that the chilled water pump energy consumption model: p (P) chwp =c 0 +c 1 m chwp +c 2 m chwp 2 Wherein, c 0 ~c 2 Fitting coefficients;
wherein m is chwp0 The unit is kg/s for rated working condition water flow of the chilled water pump; m is m chwp1 The unit is kg/s for the running condition water flow of the chilled water pump; n is n chwp0 The unit is r/min which is the rated working condition rotating speed of the chilled water pump; n is n chwp1 The unit is r/min which is the running working condition rotating speed of the chilled water pump; f (f) chwp0 The unit is HZ which is the rated working condition frequency of the chilled water pump; f (f) fun1 The unit is HZ which is the operating condition frequency of the chilled water pump;
wherein P is chwp0 The power consumption is the rated working condition power consumption of the chilled water pump, and the unit is kW; p (P) chwp1 And the unit is kW for the power consumption of the running working condition of the chilled water pump.
8. The system and the optimal control method based on the dynamic prediction of the central air conditioner load according to claim 6 are characterized in that the cooling water pump energy consumption model: p (P) cwp =d 0 +d 1 m cwp +d 2 m cwp 2 Wherein d is 0 ~d 2 To fit coefficients, P cwp The unit is kW for the power consumption of the cooling water pump; m is m cwp The unit is kg/s for cooling water mass flow;
wherein m is cwp0 The unit is kg/s for rated working condition water flow of the chilled water pump; m is m cwp1 The unit is kg/s for the running condition water flow of the chilled water pump; n is n cwp0 For the refrigerating water pumpThe rotation speed under a fixed working condition is expressed as r/min; n is n cwp1 The unit is r/min which is the running working condition rotating speed of the chilled water pump; f (f) cwp0 The unit is HZ which is the rated working condition frequency of the chilled water pump; f (f) cwp0 The unit is HZ which is the operating condition frequency of the chilled water pump;
wherein P is cwp0 The power consumption is the rated working condition of the cooling water pump, and the unit is kW; p (P) cwp1 And the unit of the power consumption is kW for the operation condition of the cooling water pump.
9. The system and the optimization control method based on the central air conditioner load dynamic prediction according to claim 1, wherein the total energy consumption model is as follows:
wherein P is tot The total energy consumption of the refrigerating machine room system is kW; p (P) ch The unit is kW for the power consumption of the refrigerating unit; p (P) fun The power consumption of the cooling tower fan is kW; p (P) chwp The unit of the power consumption of the chilled water pump is kW; p (P) cwp The power consumption of the cooling water pump is kW; n (N) 1 ~N 4 The number of the refrigerating units, the cooling towers, the chilled water pumps and the cooling water pumps is respectively set; z is Z i Z is the device on state i =0 or 1,0 is unopened, 1 is on;
the comprehensive energy efficiency model of the system is as follows: COP of ss =Q e0 /P tot In the formula, COP ss The comprehensive energy efficiency of the system is realized; q (Q) e0 The unit is kW which is the predicted load of the central air conditioner; p (P) tot The total energy consumption of the refrigeration machine room system is in kW.
10. The system and the optimization control method based on the dynamic prediction of the central air conditioner load according to claim 9, wherein the optimization target setting of the control optimization model of the central air conditioner refrigerating system is:
the mathematical model is as follows:
wherein P is tot The total energy consumption of the refrigerating machine room system is kW; p (P) ch The unit is kW for the power consumption of the refrigerating unit; p (P) fun The power consumption of the cooling tower fan is kW; z is Z i Z is the device on state i =0 or 1,0 is unopened, 1 is on; p (P) chwp The unit of the power consumption of the chilled water pump is kW; p (P) cwp The power consumption of the cooling water pump is kW;
maxCOP ss =max(Q e0 /P tot );
in the formula, COP ss For the comprehensive energy efficiency of the system, Q e0 The predicted load of the central air conditioner is kW; p (P) tot The total energy consumption of the refrigeration machine room system is kW;
constraint condition setting:
constraint of refrigerating capacity of central air conditioning system: the refrigeration capacity needs to meet the constraint of the cold load demand:
in which Q e_chw The refrigerating capacity of an evaporator of a single refrigerating unit is kW; z is Z i Z is the device on state i =0 or 1,0 is unopened, 1 is on; q (Q) e0 The predicted load of the central air conditioner is kW;
the frequency modulation range corresponding to the variable frequency water pump and the fan of the central air conditioning system is required to be within the specified range of equipment operation, and the constraint is as follows:
wherein f fun For fan frequency f chwp For the frequency of the chilled water pump, f cwp The frequency of the cooling water pump;
inlet and outlet water temperature constraint of central air conditioning system: the temperature of the chilled water is required to be within the set range of the controller, if the temperature of the chilled water is too high, the energy efficiency of the refrigerating unit can be reduced, and because the cold and hot towers exchange heat with the ambient air, the temperature of the chilled water is higher than the wet bulb temperature of the environment, and is generally considered according to the approximation degree of not less than 3 ℃, the energy efficiency is restricted to:
wherein T is chw_s Supply water temperature for refrigerating unit chilled water, T cw_s For the inlet temperature of cooling water of the refrigerating unit, T wb For the ambient wet bulb temperature around the cooling tower, min is the minimum value of the water temperature setting and max is the maximum value of the water temperature setting.
Constraint among devices of the central air conditioning system: the cooling load is generated by the end user, the chilled water exchanges heat with indoor air at the end equipment to generate a refrigerating effect, the temperature of the chilled water is increased, the chilled water is circulated to the side of an evaporator of the refrigerating unit for heat exchange through a water pump, the temperature of the chilled water is reduced, the cooling water is circulated to take away the heat dissipation of the condenser, and the heat is dissipated to the outdoor air through a fan of the cooling tower.
The refrigerating unit evaporator generates refrigerating capacity to meet the terminal cold load demand:in which Q e_chw The refrigerating capacity of an evaporator of a single refrigerating unit is kW, Z i Z is the device on state i =0 or 1,0 is unopened, 1 is on, Q e0 The predicted load of the central air conditioner is kW;
the evaporator absorbs heat in the chilled water: q (Q) e_chw =C P ×m chw ×(T chw_r -T chw_s ),
In which Q e_chw The refrigerating capacity of an evaporator of a single refrigerating unit is kW; c (C) P For the specific heat capacity of the chilled water, 4.18kJ/kg. ℃; t (T) chw_s The water supply temperature for the evaporator is given in units of ℃; t (T) cw_r The return water temperature of the condenser is given in the unit of DEG C;
cooling water carries the heat dissipation capacity of the condenser: q (Q) e_chw +P ch =C P ×m cw ×(T cw_r -T cw_s ) In which Q e_chw The refrigerating capacity of the evaporator of a single refrigerating unit is kW; c (C) P Specific heat capacity for chilled water; m is m cw The unit is kg/s for cooling water mass flow; t (T) cw_s 、T cw_r The temperature of the water for cooling water is given in the unit of DEG C;
relationship between cooling water pump and cooling tower: q (Q) e_chw +P ch =ε a m a (h s,w,i -h a,i )=m a (h a,o -h a,i ) In which Q e_chw The refrigerating capacity of the evaporator of a single refrigerating unit is kW; p (P) ch The power consumption of a compressor of a single refrigerating unit is kW; epsilon a The heat exchange efficiency is achieved; m is m a The mass air quantity of the fan is kg/s; h is a a,o ,h a,i Respectively the enthalpy values of the inlet air and the outlet air; h is a s,w,i Is the saturation enthalpy of the inlet air;
and (3) establishing an overall optimization model: combining the optimization target and the constraint condition to obtain an overall optimization model
maxCOP ss =max(Q e0 /P tot ),
P in the formula tot The total energy consumption of the refrigerating machine room system is kW; p (P) ch The unit is kW for the power consumption of the refrigerating unit; p (P) fun The power consumption of the cooling tower fan is kW; p (P) chwp The unit of the power consumption of the chilled water pump is kW; p (P) cwp The power consumption of the cooling water pump is kW; n (N) 1 ~N 4 Respectively a refrigerating unit, a cooling tower and a cooling deviceThe number of the frozen water pumps and the cooling water pumps is configured; z is Z i Z is the device on state i =0 or 1,0 is unopened, on, 1 is on;
in which Q e_chw The refrigerating capacity of an evaporator of a single refrigerating unit is kW; z is Z i Z is the device on state i =0 or 1,0 is unopened, 1 is on; q (Q) e0 The unit is kW which is the predicted load of the central air conditioner; c (C) P Specific heat capacity for chilled water; m is m chw The unit is kg/s for the mass flow of chilled water; t (T) chw_s 、T chw_r The temperature of the return water for the chilled water is given in the unit of DEG C; t (T) cw_s 、T cw_r The temperature of the water for cooling water is given in the unit of DEG C; p (P) ch The power consumption of a compressor of a single refrigerating unit is kW; m is m cw The unit is kg/s for cooling water mass flow; h is a a,o ,h a,i Respectively the enthalpy values of the inlet air and the outlet air; f (f) fun The unit is HZ for the fan frequency of the cooling tower; f (f) chwp The unit is HZ for the frequency of the chilled water pump; f (f) cwp The unit is HZ for cooling water pump frequency.
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