CN108320042B - Optimization method and device for circulating water system - Google Patents
Optimization method and device for circulating water system Download PDFInfo
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Abstract
The invention provides an optimization method of a circulating water system, which belongs to the field of industrial control and comprises the following steps: selecting historical operating data of equipment from a circulating water system, and establishing a correlation model; according to the specific working condition of equipment in the circulating water system, a mechanism model corresponding to the circulating water system is constructed by combining a correlation model to obtain a theoretical calculation result, and the theoretical calculation result is corrected by combining the obtained actual operation data of the equipment; and constructing an optimization model of the circulating water system, and determining an optimization operation strategy of the circulating water system under the condition of ensuring the minimum total energy consumption of the circulating water system under the constraint condition. The method comprises the steps of constructing a circulating water system optimization model by taking the total circulating water flow and the refrigerating capacity load as constraints and the total energy consumption of a circulating water system as a target, giving an optimal circulating water scheduling scheme, a cooling tower fan operation scheme and an operation strategy of a circulating water pump and a water chilling unit through optimization calculation, and finally performing optimization operation on the circulating water system through a manual or control system to enable the comprehensive energy consumption of the circulating water system to be the lowest.
Description
Technical Field
The invention belongs to the field of industrial control, and particularly relates to a method and a device for optimizing a circulating water system.
Background
The circulating water system is one of important devices of various large industrial production enterprises, so that water can be circulated, daily production of the enterprises is guaranteed, and meanwhile, the problem of increasingly prominent high energy consumption and waste is caused. In the actual production process, the circulating water system is always at partial load for most cases, i.e. the power of the circulating water system is always at a lower power than the rated power. In contrast, due to the lack of support of theoretical calculation and refined operation management measures, production enterprises often still use a full-load standard operation mode, so that a large amount of energy is wasted, and meanwhile, the method is limited to monomer energy conservation, a single parameter is adjusted by experience, a thorough energy-saving strategy is not made from the whole system, and the condition of low system operation efficiency is not improved.
In the aspect of the optimization of a circulating water system of an industrial enterprise, the main patent technologies comprise:
(1) an optimization method of an industrial circulating water system (CN 201510049980.9);
(2) an integral optimization energy-saving method of a circulating water system (CN 201410408389.3).
The patent (1) mainly provides a circulating water pipe network optimization scheme, factors such as pressure heads required by various water utilization equipment, pressure of a circulating water pipe network in the device, actual constraint conditions of field water utilization equipment, running pressure of a circulating water main pipe network and the like are comprehensively considered, the technology can optimize the water utilization network and provide an optimal scheduling scheme of the circulating water consumption, but the technology does not relate to the characteristics of the device and cannot comprehensively consider the problem of comprehensive energy consumption of key energy utilization equipment such as a cooling tower fan, a water chiller and the like in a circulating water system.
Patent (2) mainly provides a whole optimization transformation scheme of circulating water system, through eliminating the unreasonable high energy consumption that causes, has reached energy-conserving effect, has increased the equipment transformation expense. And the analysis is carried out based on the parameters collected on the spot, the uncertainty of the real-time parameters is not considered, the historical operation data of the equipment is not fully utilized and mined, and theoretical support is not provided by establishing a mathematical model of the system.
Disclosure of Invention
In order to solve the defects and shortcomings in the prior art, the invention provides an optimization method and device for constructing an optimization objective function, solving the objective function under the constraint conditions including the energy consumption, the material cost, the device efficiency and the like, and finally determining an optimization strategy implemented on a circulating water system.
In order to achieve the above technical objects, in one aspect, the present invention provides an optimization method of a circulating water system, the optimization method comprising:
selecting historical operation data of equipment from a circulating water system, establishing a flow-current correlation model, and updating the correlation model in real time according to the acquired real-time data of the equipment;
according to the specific working condition of equipment in the circulating water system, combining the updated correlation model, constructing a mechanism model corresponding to the circulating water system to obtain theoretical calculation results about the flow and the temperature in the circulating water system, and correcting the theoretical calculation results by combining the obtained actual operation data of the equipment;
and constructing a circulating water system optimization model, determining an optimization operation strategy of the circulating water system under the condition of ensuring the total energy consumption of the circulating water system to be minimum under the constraint conditions of total circulating water flow and refrigerating capacity load, and applying the optimization operation strategy to carry out optimization treatment on the circulating water system.
Optionally, the optimization method further includes:
analyzing the operation parameters in the circulating water system, determining key adjustable parameters related to the energy consumption of the circulating water system, analyzing the sensitivity of the key adjustable parameters, and determining key parameters influencing the energy consumption in the circulating water system;
key parameters in the circulating water system are adjusted.
Optionally, the analyzing the operation parameters in the circulating water system, determining key adjustable parameters related to energy consumption of the circulating water system, analyzing the sensitivity of the key adjustable parameters, and determining the key parameters affecting energy consumption in the circulating water system includes:
according to a mathematical model of a circulating water system, performing sensitivity analysis on each key adjustable parameter influencing system energy consumption by adopting a Sobol method to obtain expressions shown in formulas (1) to (5), and searching for the most sensitive factor according to the expressions;
STj＝ΣS(i) (5)
in the formula: d represents the variance, SiExpressed as 1 degree sensitivity, S ij2 degree of sensitivity, and so on, S1,2,…,nIs n degree sensitivity, STjIs the total sensitivity of the ith parameter.
Optionally, the selecting historical operating data of the equipment from the circulating water system, and establishing a flow-current correlation model includes:
acquiring historical data of equipment in a circulating water system;
based on a least square method, establishing a flow-current correlation model I corresponding to a circulating water systemi＝Li×ai+biIn the formula Ii、LiRespectively represent the current and flow of each device, ai、biFitting coefficients of the correlation model;
constructing a sum of squares error function
yj＝Li*ai+bi (7)
The formula (7) may be substituted for the formula (6):
a is obtained by subjecting formula (8) to ai、biThe partial derivative is calculated to be equal to 0, and model fitting coefficients with the minimum of equation (6) as the "optimization criterion" are obtained.
Optionally, the constructing, according to the specific working conditions of the equipment in the circulating water system, a mechanism model corresponding to the circulating water system in combination with the updated association model to obtain theoretical calculation results about the flow and the temperature in the circulating water system, and correcting the theoretical calculation results in combination with the obtained actual operation data of the equipment, includes:
according to the specific working condition of equipment in the circulating water system, modeling is carried out on a cooling tower system in the circulating water system by combining the updated correlation model, and mathematical modeling is carried out on a water chilling unit system in the circulating water system;
based on a mechanism model of a cooling tower system and a water chilling unit system, combined with an empirical model of a circulating water pump and a cooling tower fan, a sequential module method is adopted to obtain a theoretical calculation result comprising flow and temperature, and the theoretical calculation result is subjected to accounting correction according to actual operation data of equipment.
Optionally, the modeling of the cooling tower system in the circulating water system includes:
obtaining modeling parameters including mass balance, heat balance and cooling tower efficiency in a cooling tower system;
and determining a parameter expression corresponding to each modeling parameter.
Optionally, the mathematically modeling the chiller system in the circulating water system includes:
obtaining modeling parameters of a water chilling unit system including a compressor, a condenser, an electronic throttle valve, an evaporator and a refrigerating system;
and determining a parameter expression corresponding to each modeling parameter.
Optionally, the constructing a circulating water system optimization model, and determining an optimized operation strategy of the circulating water system under the condition of ensuring the minimum total energy consumption of the circulating water system under the constraint conditions of total circulating water flow and refrigeration load includes:
constructing an objective function which minimizes the comprehensive energy consumption of the whole circulating water system under the condition of ensuring the circulating water supply quantity and the refrigerating capacity demand
Wherein, Pfan,i、Ppumpcw,i、Prefri,iThe electric power of the ith cooling tower fan, the circulating water pump and the refrigerating unit is respectively; p istotalCalculating the electric power of each device based on a system mathematical model for the comprehensive electric power of the whole circulating water system;
constructing constraint conditions including material balance, energy balance, device constraint, efficiency constraint and efficiency constraint;
and solving the objective function by adopting a nonlinear programming method based on the constraint condition to obtain an optimized operation strategy comprising a circulating water optimized scheduling scheme, a cooling tower fan optimized operation scheme and a circulating water pump and a water chilling unit.
On the other hand, this embodiment has also proposed the optimizing apparatus of circulating water system, optimizing apparatus includes:
the data acquisition module is used for selecting historical operation data of equipment from the circulating water system, establishing a flow-current correlation model and updating the correlation model in real time according to the acquired real-time data of the equipment;
the data processing module is used for constructing a mechanism model corresponding to the circulating water system by combining the updated correlation model according to the specific working condition of equipment in the circulating water system to obtain a theoretical calculation result about the flow and the temperature in the circulating water system, and correcting the theoretical calculation result by combining the obtained actual operation data of the equipment;
and the data optimization module is used for constructing a circulating water system optimization model, determining an optimization operation strategy of the circulating water system under the condition of ensuring the minimum total energy consumption of the circulating water system under the constraint conditions of total circulating water flow and refrigerating capacity load, and applying the optimization operation strategy to optimize the circulating water system.
Optionally, the data processing module is further configured to:
analyzing the operating parameters in the circulating water system, determining key adjustable parameters related to the energy consumption of the circulating water system, analyzing the sensitivity of the key adjustable parameters, and determining key parameters influencing the energy consumption in the circulating water system;
key parameters in the circulating water system are adjusted.
The technical scheme provided by the invention has the beneficial effects that:
the method comprises the steps of constructing a circulating water system optimization model by taking the total circulating water flow and the refrigerating capacity load as constraints and the total energy consumption of a circulating water system as a target, giving an optimal circulating water scheduling scheme, a cooling tower fan operation scheme and an operation strategy of a circulating water pump and a water chilling unit through optimization calculation, and finally performing optimization operation on the circulating water system through a manual or control system to enable the comprehensive energy consumption of the circulating water system to be the lowest.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
FIG. 1 is a schematic flow diagram of a method for optimizing a circulating water system according to the present invention;
FIG. 2 is a schematic structural diagram of an optimization device of a circulating water system provided by the invention;
FIG. 3 is a schematic process flow diagram of a circulating water system of a chemical industry enterprise provided by the invention;
fig. 4 is a schematic diagram of an optimization proposal scheme obtained after the optimization method proposed by the embodiment of the invention is executed.
Detailed Description
In order to make the structure and advantages of the present invention clearer, the structure of the present invention will be further described with reference to the accompanying drawings.
Example one
In order to achieve the above technical object, the present invention provides an optimization method of a circulating water system, as shown in fig. 1, the optimization method comprising:
11. selecting historical operation data of equipment from a circulating water system, establishing a flow-current correlation model, and updating the correlation model in real time according to the acquired real-time data of the equipment;
12. according to the specific working condition of equipment in the circulating water system, combining the updated correlation model, constructing a mechanism model corresponding to the circulating water system to obtain theoretical calculation results about the flow and the temperature in the circulating water system, and correcting the theoretical calculation results by combining the obtained actual operation data of the equipment;
13. and constructing a circulating water system optimization model, determining an optimization operation strategy of the circulating water system under the condition of ensuring the total energy consumption of the circulating water system to be minimum under the constraint conditions of total circulating water flow and refrigerating capacity load, and applying the optimization operation strategy to carry out optimization treatment on the circulating water system.
In the implementation, the invention provides an optimization method and device of a circulating water system, so as to solve the problem of energy waste caused by the fact that the circulating water system cannot be subjected to refined operation management due to the lack of a theoretical calculation model and an integral management system in the prior art. The method specifically comprises the following steps:
searching and analyzing each operating parameter of the circulating water system to obtain key adjustable parameters related to energy consumption; based on historical operating data of a cooling tower fan and a circulating water pump, respectively establishing corresponding flow and current correlation models by a data fitting method such as a least square method, and updating the models by means of real-time data; establishing a strict mechanism model of a circulating water system based on an empirical model of the flow and the current of each device according to the specific structure and the working condition of the device, acquiring theoretical calculation results of the flow, the temperature and the like, comparing actual operation data, and performing accounting correction on the model; constructing a circulating water system optimization model by taking the total flow of circulating water and the load of refrigerating capacity as constraints and the minimum total energy consumption of a circulating water system as a target, and providing an optimal circulating water scheduling scheme, a cooling tower fan operation scheme and an operation strategy of a circulating water pump and a water chilling unit through optimization calculation; based on historical operating data, the feasibility of the circulating water optimization scheme is judged by combining with the actual special condition of production, and individual deviation data can be corrected manually; under the condition that the circulating water optimization scheme is feasible, the circulating water system is optimized by a manual or control system through steady-state detection, so that the comprehensive energy consumption of the circulating water system is lowest.
Optionally, the optimization method further includes:
analyzing the operating parameters in the circulating water system, determining key adjustable parameters related to the energy consumption of the circulating water system, analyzing the sensitivity of the key adjustable parameters, and determining key parameters influencing the energy consumption in the circulating water system;
key parameters in the circulating water system are adjusted.
In practice, in addition to the method for optimizing in a modeling manner described above, the method further includes a step of adjusting the key parameters, so as to achieve the effect of further optimizing the circulating water system and provide a reference for daily production regulation.
The step of adjusting the key parameter comprises:
according to a mathematical model of the circulating water system, performing sensitivity analysis on each key adjustable parameter influencing system energy consumption by adopting a Sobol method to obtain expressions shown in formulas (1) to (5), and searching for the most sensitive factor according to the expressions;
STj＝∑S(i) (5)
in the formula: d represents the variance, SiExpressed as 1 degree sensitivity, S ij2 degree of sensitivity, and so on, S1,2,…,nIs n degree sensitivity, STjIs the total sensitivity of the ith parameter.
In practice, the general methods for global sensitivity analysis include multiple regression, RSA, FAST, Sobol, extended FAST, GLUE, and the like. Among them, the Sobol method has the advantages of simple form, simple and convenient calculation, etc., is the most representative global sensitivity analysis method, and has been applied to sensitivity analysis of hydrological model parameters such as topmode, SWAT, sacsa, etc. The Sobol method is the most effective method to evaluate single-parameter sensitivity and multi-parameter interaction sensitivity of lumped models.
Optionally, the selecting historical operating data of the equipment from the circulating water system, and establishing a flow-current correlation model includes:
acquiring historical data of equipment in a circulating water system;
based on a least square method, establishing a flow-current correlation model I corresponding to a circulating water systemi＝Li×ai+biIn the formula Ii、LiRespectively represent the current and flow of each device, ai、biFitting coefficients of the correlation model;
constructing a sum of squares error function
yj＝Li*ai+bi (7)
The formula (7) may be substituted for the formula (6):
a is obtained by subjecting formula (8) to ai、biThe partial derivative is calculated to be equal to 0, and model fitting coefficients with the minimum of equation (6) as the "optimization criterion" are obtained.
In the implementation, step 11 proposes the step of establishing a flow-current key model,specifically, in the step, based on historical operation data of the circulating water system, correlation models of flow and current of a cooling tower fan and a circulating water pump are respectively established through data fitting methods such as a least square method. The fitting problem is converted into a minimal point problem of solving a square sum of errors function. A is obtained by subjecting formula (8) to ai、biThe partial derivative is calculated to be equal to 0, and the model fitting coefficient with the minimum of equation (6) as the "optimization criterion" can be obtained.
Because the fluctuation range of the air quantity of the cooling tower along with the temperature and the humidity of the environment is large, the model parameters of the air quantity and the fan current are unstable, and the model needs to be updated and corrected by means of real-time operation data of the fan.
Optionally, the constructing, according to the specific working conditions of the equipment in the circulating water system, a mechanism model corresponding to the circulating water system in combination with the updated association model to obtain theoretical calculation results about the flow and the temperature in the circulating water system, and correcting the theoretical calculation results in combination with the obtained actual operation data of the equipment, includes:
according to the specific working condition of equipment in the circulating water system, modeling is carried out on a cooling tower system in the circulating water system by combining the updated correlation model, and mathematical modeling is carried out on a water chilling unit system in the circulating water system;
based on a mechanism model of a cooling tower system and a water chilling unit system, combined with an empirical model of a circulating water pump and a cooling tower fan, a sequential module method is adopted to obtain a theoretical calculation result comprising flow and temperature, and the theoretical calculation result is subjected to accounting correction according to actual operation data of equipment.
In the implementation, the step 12 proposes to construct a mechanism model corresponding to the circulating water system, and specifically includes modeling the cooling tower system and the chiller system in the circulating water system respectively.
Specifically, modeling of a cooling tower system in a circulating water system needs to be performed from three aspects of mass balance, heat balance and cooling tower efficiency,
aiming at the mass balance, the constructed expression is as follows:
mw,i-mw,o＝ma(wa,o-wa,i) (9)
in the formula: m isw,iShows the return flow of cooling water, mw,oWater flow rate for cooling water, maFor tower air flow, wa,oIs the moisture content of the outlet air, wa,iIs the moisture content of the inlet air.
For heat balance, the expression constructed is:
mw,i×Cp,w×(Tw,i-Tref)-Qcell＝mw,o×Cp,w×(Tw,o-Tref) (10)
in the formula: cp,wDenotes the specific heat of cooling water, Tw,iIs the return water temperature of the cooling water, TrefIs the reference temperature (0 ℃) of water, Tw,oThe supply water temperature of the cooling water.
Qcell＝ma(ha,o-ha,i) (11)
In the formula: h isa,oRepresents the outlet air enthalpy value, ha,iRepresenting the inlet air enthalpy.
Cooling tower efficiency:
in the formula: n denotes the number of cooling, h "2Is the enthalpy of saturated air at the temperature of the water supply, h1For the enthalpy of air entering the tower, h "mIs the saturated air enthalpy at the average water temperature, hmIs the air enthalpy at the average water temperature, h "1Is the enthalpy of saturated air at the backwater temperature, h2The enthalpy value of the air out of the tower is shown as k, and the k is a heat coefficient.
The mathematical modeling of the water chilling unit system in the circulating water system needs to be carried out from five aspects of a compressor, a condenser, an electronic throttle valve, an evaporator and a refrigeration system.
For a compressor, the expression is constructed as follows:
Pi＝qm×(H2-H1)+QC (13)
in the formula: piRepresenting the electric power of the compressor i, qmIs the mass flow of the refrigerant, H2Is the enthalpy of the refrigerant at the outlet of the compressor, H1Is the enthalpy of the refrigerant at the compressor inlet, QCIs the amount of heat given off to the outside in the compressor by the refrigerant per unit time.
For the condenser, the expression is constructed as follows:
Qk＝qm×(H2-H3) (14)
in the formula: qkRepresents the heat dissipated to the outside in the condenser per unit time of the refrigerant, H3Is the enthalpy of the refrigerant at the outlet of the condenser.
For an electronic throttle valve, the constructed expression is as follows:
0＝qm×(H1-H3) (15)
for the evaporator, the expression is constructed as follows:
Q0＝qm×(H1-H4) (16)
in the formula: q0Indicating the cooling capacity.
For a refrigeration system, the expression is constructed as follows:
Q0+Pi＝Qk+QC (17)
based on the mechanism model of the cooling tower system and the water chilling unit system, and the empirical models of the circulating water pump and the cooling tower fan, a mathematical model of the whole circulating water system is established by adopting a sequential module method according to the specific structure and the working condition of each device, theoretical calculation results of flow, temperature and the like are obtained, actual operation data are compared, and the model is subjected to accounting correction.
Optionally, the constructing a circulating water system optimization model, and determining an optimized operation strategy of the circulating water system under the condition of ensuring the minimum total energy consumption of the circulating water system under the constraint conditions of total circulating water flow and refrigeration load includes:
the optimization of the circulating water system aims to minimize the comprehensive energy consumption of the whole circulating water system under the condition of ensuring the supply quantity of circulating water and the demand of refrigerating capacity.
Therefore, on the premise that an objective function capable of characterizing the requirement is constructed, the expression is as follows:
in the formula: pfan,i、Ppumpcw,i、Prefri,iElectric power of the ith cooling tower fan, the circulating water pump and the refrigerating unit respectively; ptotalFor the comprehensive electric power of the whole circulating water system, the electric power of each device is calculated based on a system mathematical model.
After the objective function is constructed, the objective function needs to be solved under preset constraint conditions, wherein the constraint conditions comprise five aspects of material balance constraint, energy balance constraint, device constraint, efficiency constraint and demand constraint.
Specifically, the material balance constraints include:
for the whole circulating water system: sigma (F)a,in-Fa,out)＝0 (19)
For each sub-device: sigma (F)i,in-Fi,out)＝0 (20)
In the formula: fa,inIndicating the air inlet quantity of the circulating water system, Fa,outIndicating the air outlet quantity of the circulating water system, Fi,inShowing the inlet amount of material i, F, of each sub-unit of the circulating water systemi,outAnd (4) representing the material i outlet quantity of each sub-device of the circulating water system.
Energy balance constraint expression: sigma (F)i,in×Hi,in-Fi,out×Hi,out-Wi-Qi)＝0 (21)
In the formula: hi,inRepresents the enthalpy value of the material i inlet of each sub-device of the circulating water system, Hi,outExpressing the enthalpy value of a material i outlet of each sub-device of the circulating water system, W is used for doing work outwards, and Q isiIs an energy loss.
The device constraints specifically include that the medium flow rates distributed to the cooling tower, the circulating water pump and the water chilling unit must be within a normal range, otherwise the normal operation of the equipment is affected:
the expression is as follows: fi,min≤Fi≤Fi,max(22)
Ii,min≤Ii≤Ii,max (23)
In the formula, FiRepresenting the quantity of material in the plant, Fi,minIs the minimum load that the equipment can bear, Fi,maxThe maximum load that the apparatus can bear, IiRepresenting the current value of the device, Ii,minIs the minimum amount of current that the device can withstand, Ii,maxThe maximum amount of current that the device can withstand.
The meaning of the efficiency constraint is that in the actual production process, the efficiency condition of a single device is always fully considered, the device with the low efficiency value is not started normally so as to avoid load waste, and the expression is
if Ii＞0，ηi,min≤ηi≤1 (24)
In the formula: etaiThe plant efficiency is expressed and calculated from each plant model.
The requirement constraint means that the requirement of daily production on the total quantity of circulating water and the refrigerating capacity must be met for optimizing a circulating water system.
Lcw,need≤Lcw (25)
Qneed≤Qe (26)
In the formula: l iscwRepresents the total amount of circulating water, L, provided by the optimization schemecw,needFor the total demand of actual production on circulating water, a real-time value Q is adopted in calculationeRefrigerating capacity, Q, provided for optimisation of the planneedThe requirement of actual production on the refrigerating capacity of the circulating water system is calculated by acquiring the temperature and the humidity of the environment in real time.
After the objective function and numerous constraint conditions are determined, solving the models by adopting a sequential quadratic programming method (SQP) or an interior-point method (interior-point) in a nonlinear programming method to obtain a circulating water optimal scheduling scheme, a cooling tower fan optimal operation scheme and an optimal operation strategy of a circulating water pump and a water chilling unit.
It is noted that the optimization method for the circulating water system proposed in the present embodiment includes two supplementary steps of judging the feasibility of the optimization scheme and executing the optimization scheme, in addition to the foregoing.
The former is the feasibility judgment of the optimization scheme, and comprises the following steps: and judging the feasibility of the circulating water optimization scheme obtained by the optimization model based on historical operating data and by combining with the actual special condition of production, and manually correcting individual deviation data.
The latter, i.e. the execution of the optimization scheme, then includes: when the optimization scheme of the circulating water system is judged to be feasible, firstly, the advanced control personnel carry out steady state detection, and carry out an optimization result on the scheme which can be in a steady state, namely, the operating personnel carry out manual adjustment or connect an optimization calculation model with control systems such as a field DCS (distributed control system), a PLC (programmable logic controller) and the like to carry out online automatic adjustment according to the optimization calculation result, so that the running state of the circulating water system is always in the lowest energy consumption.
The invention provides an optimization method of a circulating water system, which comprises the following steps: selecting historical operation data of equipment from a circulating water system, establishing a flow-current correlation model, and updating the correlation model in real time according to the acquired real-time data of the equipment; according to the specific working condition of equipment in the circulating water system, combining the updated correlation model, constructing a mechanism model corresponding to the circulating water system to obtain theoretical calculation results about the flow and the temperature in the circulating water system, and correcting the theoretical calculation results by combining the obtained actual operation data of the equipment; and constructing a circulating water system optimization model, determining an optimization operation strategy of the circulating water system under the condition of ensuring the total energy consumption of the circulating water system to be minimum under the constraint conditions of total circulating water flow and refrigerating capacity load, and applying the optimization operation strategy to carry out optimization treatment on the circulating water system. The method comprises the steps of constructing a circulating water system optimization model by taking total circulating water flow and refrigerating capacity load as constraints and the minimum total energy consumption of a circulating water system as a target, giving an optimal circulating water scheduling scheme, a cooling tower fan operation scheme and an operation strategy of a circulating water pump and a water chilling unit through optimization calculation, and finally performing optimization operation on the circulating water system through a manual or control system to enable the comprehensive energy consumption of the circulating water system to be the lowest.
Example two
In view of the optimization method for a circulating water system proposed in the previous embodiment, the present embodiment proposes an optimization device 2 for a circulating water system using the optimization method, as shown in fig. 2, where the optimization device 2 includes:
the data acquisition module 21 is configured to select historical operation data of the equipment from the circulating water system, establish a flow-current correlation model, and update the correlation model in real time according to the acquired real-time data of the equipment;
the data processing module 22 is configured to construct a mechanism model corresponding to the circulating water system according to the specific working conditions of the equipment in the circulating water system in combination with the updated association model, obtain theoretical calculation results about the flow and the temperature in the circulating water system, and correct the theoretical calculation results in combination with the obtained actual operation data of the equipment;
and the data optimization module 23 is configured to construct a circulating water system optimization model, determine an optimized operation strategy of the circulating water system under the condition that total energy consumption of the circulating water system is minimum under the constraint conditions of total circulating water flow and refrigeration load, and apply the optimized operation strategy to perform optimization processing on the circulating water system.
In implementation, the invention provides an optimization device of a circulating water system, and aims to solve the problem of energy waste caused by the fact that a circulating water system cannot be subjected to refined operation management due to the lack of a theoretical calculation model and an integral management system in the prior art. The optimization device 2 includes three modules, namely a data obtaining module 21, a data processing module 22, and a data optimizing module 23, where each module respectively executes the contents shown in steps 11, 12, and 13 described in the previous embodiment, and this embodiment is not described in detail herein.
The optimization device 2 mainly performs operations including:
searching and analyzing each operating parameter of the circulating water system to obtain key adjustable parameters related to energy consumption; based on historical operating data of a cooling tower fan and a circulating water pump, respectively establishing corresponding flow and current correlation models by a data fitting method such as a least square method, and updating the models by means of real-time data; establishing a strict mechanism model of a circulating water system based on an empirical model of the flow and the current of each device according to the specific structure and the working condition of the device, acquiring theoretical calculation results of the flow, the temperature and the like, comparing actual operation data, and performing accounting correction on the model; constructing a circulating water system optimization model by taking the total flow of circulating water and the load of refrigerating capacity as constraints and the minimum total energy consumption of a circulating water system as a target, and giving an optimal circulating water scheduling scheme, a cooling tower fan operation scheme and an operation strategy of a circulating water pump and a water chilling unit through optimization calculation; based on historical operating data, the feasibility of the circulating water optimization scheme is judged by combining with the actual special condition of production, and individual deviation data can be corrected manually; under the condition that the circulating water optimization scheme is feasible, the circulating water system is optimized by a manual or control system through steady-state detection, so that the comprehensive energy consumption of the circulating water system is lowest.
Optionally, the data processing module 22 is further configured to:
analyzing the operating parameters in the circulating water system, determining key adjustable parameters related to the energy consumption of the circulating water system, analyzing the sensitivity of the key adjustable parameters, and determining key parameters influencing the energy consumption in the circulating water system;
key parameters in the circulating water system are adjusted.
In practice, the data processing module 22 also needs to perform a step of adjusting the key parameters, so as to achieve the effect of further optimizing the circulating water system, and provide a reference for daily production adjustment.
The steps for adjusting the key parameter include:
according to a mathematical model of the circulating water system, performing sensitivity analysis on each key adjustable parameter influencing system energy consumption by adopting a Sobol method to obtain expressions shown in formulas (1) to (5), and searching for the most sensitive factor according to the expressions;
STj＝∑S(i) (5)
in the formula: d represents the variance, SiExpressed as 1 degree sensitivity, S ij2 degree of sensitivity, and so on, S1,2,…,nIs n degree sensitivity, STjIs the total sensitivity of the ith parameter.
In practice, the general methods for global sensitivity analysis include multiple regression, RSA, FAST, Sobol, extended FAST, GLUE, and the like. Among them, the Sobol method has the advantages of simple form, simple and convenient calculation, etc., is the most representative global sensitivity analysis method, and has been applied to sensitivity analysis of hydrological model parameters such as topmode, SWAT, sacsa, etc. The Sobol method is the most effective method to evaluate single-parameter sensitivity and multi-parameter interaction sensitivity of lumped models.
In addition, the embodiment also provides a concept of establishing a result display module and an interpersonal interaction module, wherein the result display module is used for visually displaying the optimized data obtained by the data analysis module on a display platform; the latter is used for providing a user requirement input interface, and performing predictive calculation and visual presentation on the optimal circulating water operation strategy under a certain reasonable requirement condition in the future through manual input.
The invention provides an optimization device of a circulating water system, which comprises: selecting historical operation data of equipment from a circulating water system, establishing a flow-current association model, and updating the association model in real time according to the acquired real-time data of the equipment; according to the specific working condition of equipment in the circulating water system, combining the updated correlation model, constructing a mechanism model corresponding to the circulating water system to obtain theoretical calculation results about the flow and the temperature in the circulating water system, and correcting the theoretical calculation results by combining the obtained actual operation data of the equipment; and constructing a circulating water system optimization model, determining an optimization operation strategy of the circulating water system under the condition of ensuring the total energy consumption of the circulating water system to be minimum under the constraint conditions of total circulating water flow and refrigerating capacity load, and performing optimization treatment on the circulating water system by applying the optimization operation strategy. The method comprises the steps of constructing a circulating water system optimization model by taking total circulating water flow and refrigerating capacity load as constraints and the minimum total energy consumption of a circulating water system as a target, giving an optimal circulating water scheduling scheme, a cooling tower fan operation scheme and an operation strategy of a circulating water pump and a water chilling unit through optimization calculation, and finally performing optimization operation on the circulating water system through a manual or control system to enable the comprehensive energy consumption of the circulating water system to be the lowest.
Typical application cases are as follows: the process flow of the circulating water system of a chemical industry enterprise is shown in fig. 3, and the circulating water system comprises four cooling towers, four fans, nine circulating water pumps, nine refrigerators, seven chilled water pumps, a tail end air conditioner and the like.
Taking a typical summer mode of 32 ℃ and 65% RH as an example, the optimization model and the device provided by the invention are used for calculation, the obtained optimization proposal scheme is shown in fig. 4, the operation is carried out according to the optimization scheme, under the condition of meeting the total quantity demand and the refrigerating capacity demand of circulating water, the power consumption of a circulating water system is about 2500 million KWH/year, and the power consumption is expected to be saved by 2-20%.
The sequence numbers in the above embodiments are merely for description, and do not represent the sequence of the assembly or the use of the components.
The above description is only exemplary of the present invention and should not be taken as limiting the invention, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (4)
1. The optimization method of the circulating water system is characterized by comprising the following steps:
selecting historical operation data of equipment from a circulating water system, establishing a flow-current correlation model, and updating the correlation model in real time according to the acquired real-time data of the equipment;
according to the specific working condition of equipment in the circulating water system, combining the updated correlation model, constructing a mechanism model corresponding to the circulating water system to obtain theoretical calculation results about the flow and the temperature in the circulating water system, and correcting the theoretical calculation results by combining the obtained actual operation data of the equipment;
constructing a circulating water system optimization model, determining an optimization operation strategy of the circulating water system under the condition of ensuring the total energy consumption of the circulating water system to be minimum under the constraint conditions of total circulating water flow and refrigerating capacity load, and applying the optimization operation strategy to carry out optimization treatment on the circulating water system;
selecting historical operation data of equipment from a circulating water system, and establishing a flow-current association model, wherein the flow-current association model comprises the following steps:
acquiring historical data of equipment in a circulating water system;
based on least square method, establishing flow-current correlation model corresponding to circulating water system
Ii＝Li×ai+bi，
In the formula Ii、LiRespectively represent the current and flow of each device, ai、biFitting coefficients of the correlation model;
constructing a sum of squares error function
yj＝Li*ai+bi (7)
Substitution of formula (7) for formula (6) gives:
a is obtained by subjecting formula (8) toi、biCalculating a partial derivative to be equal to 0, and obtaining a model fitting coefficient taking the minimum of the formula (6) as an optimization criterion;
the method includes the steps of establishing a mechanism model corresponding to the circulating water system according to specific working conditions of equipment in the circulating water system and by combining the updated association model, obtaining theoretical calculation results about flow and temperature in the circulating water system, and correcting the theoretical calculation results by combining the obtained actual operation data of the equipment, and includes the following steps:
according to the specific working condition of equipment in the circulating water system, modeling is carried out on a cooling tower system in the circulating water system by combining the updated correlation model, and mathematical modeling is carried out on a water chilling unit system in the circulating water system;
based on a mechanism model of a cooling tower system and a water chilling unit system, combining an empirical model of a circulating water pump and a cooling tower fan, adopting a sequential module method to obtain a theoretical calculation result comprising flow and temperature, and performing accounting correction on the theoretical calculation result according to actual operation data of equipment;
the method for establishing the optimization model of the circulating water system and determining the optimization operation strategy of the circulating water system under the condition of ensuring the minimum total energy consumption of the circulating water system under the constraint conditions of total circulating water flow and refrigerating capacity load comprises the following steps of:
constructing an objective function which minimizes the comprehensive energy consumption of the whole circulating water system under the condition of ensuring the circulating water supply quantity and the refrigerating capacity demand
Wherein, Pfan,i、Ppumpcw,i、Prefri,iElectric power of the ith cooling tower fan, the circulating water pump and the refrigerating unit respectively; ptotalCalculating the electric power of each device based on a system mathematical model for the comprehensive electric power of the whole circulating water system;
constructing constraint conditions including material balance, energy balance, device constraint, efficiency constraint and efficiency constraint;
and solving the objective function by adopting a nonlinear programming method based on the constraint condition to obtain an optimized operation strategy comprising a circulating water optimized dispatching scheme, a cooling tower fan optimized operation scheme and a circulating water pump and water chilling unit.
2. The optimization method of a circulating water system according to claim 1, further comprising:
analyzing the operating parameters in the circulating water system, determining key adjustable parameters related to the energy consumption of the circulating water system, analyzing the sensitivity of the key adjustable parameters, and determining key parameters influencing the energy consumption in the circulating water system;
key parameters in the circulating water system are adjusted.
3. The method for optimizing a circulating water system according to claim 1, wherein the modeling a cooling tower system in the circulating water system comprises:
obtaining modeling parameters including mass balance, heat balance and cooling tower efficiency in a cooling tower system;
and determining a parameter expression corresponding to each modeling parameter.
4. The method of optimizing a circulating water system of claim 1, wherein the mathematically modeling a chiller system in a circulating water system comprises:
obtaining modeling parameters including a compressor, a condenser, an electronic throttle valve and an evaporator in a water chilling unit system;
and determining a parameter expression corresponding to each modeling parameter.
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| CN110631212B (en) * | 2019-08-16 | 2021-09-24 | 西安建筑科技大学 | Energy-saving control method for central air-conditioning cooling water system |
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| CN111178576B (en) * | 2019-11-19 | 2023-09-05 | 浙江中控技术股份有限公司 | Operation optimization method based on refining device operation data |
| CN114358417B (en) * | 2021-12-31 | 2023-06-20 | 山东双轮股份有限公司 | Energy-saving consumption-reducing operation control method for industrial circulating cooling water system |
| CN115265024B (en) * | 2022-06-14 | 2023-11-24 | 浙江中控技术股份有限公司 | Integrated control optimization method for circulating cooling water system |
| CN117215255B (en) * | 2023-11-09 | 2024-01-26 | 中控技术股份有限公司 | Automatic energy-saving consumption-reducing operation control system of industrial circulating water system |
| CN117234071B (en) * | 2023-11-16 | 2024-01-26 | 中控技术股份有限公司 | Circulating water system energy-saving optimization method and device based on temperature and pressure control |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104636800A (en) * | 2013-11-06 | 2015-05-20 | 上海思控电气设备有限公司 | Freezing station system neural network optimization unit based on least square weighted and method thereof |
| CN106091515A (en) * | 2016-06-20 | 2016-11-09 | 福建大唐国际宁德发电有限责任公司 | The method that fired power generating unit once-though cooling circulation on-line operation optimizes |
| CN106250617A (en) * | 2016-07-29 | 2016-12-21 | 上海交通大学 | The double back pressure cold end system variable frequency pump circulating water flow optimization method of a kind of fired power generating unit |
-
2017
- 2017-12-05 CN CN201711270570.2A patent/CN108320042B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104636800A (en) * | 2013-11-06 | 2015-05-20 | 上海思控电气设备有限公司 | Freezing station system neural network optimization unit based on least square weighted and method thereof |
| CN106091515A (en) * | 2016-06-20 | 2016-11-09 | 福建大唐国际宁德发电有限责任公司 | The method that fired power generating unit once-though cooling circulation on-line operation optimizes |
| CN106250617A (en) * | 2016-07-29 | 2016-12-21 | 上海交通大学 | The double back pressure cold end system variable frequency pump circulating water flow optimization method of a kind of fired power generating unit |
Non-Patent Citations (1)
| Title |
|---|
| "Recirculating Cooling-Water Network with an Intermediate Cooling-Water Main";Xiao feng 等;《Energy & Fuels》;20050415;全文 * |
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