CN106440853A - Cooling tower outlet air anti-fogging energy consumption optimization method based on firefly algorithm - Google Patents

Abstract

The invention discloses a cooling tower outlet air anti-fogging method of energy consumption optimization based on a firefly algorithm. The cooling tower outlet air anti-fogging method comprises the steps that the temperature, the relative humidity and the wind speed of cooling tower outlet air and the dry-bulb temperature, the relative humidity and the wind speed of the surrounding environment of an air outlet are collected, and the temperature and the absolute humidity of mixed gas are calculated; if the saturation humidity after mixing is lower than the absolute humidity, an air supply device is started to increase the cold air supply quantity; and a cold air supply quantity value is obtained for optimizing energy consumption, a temperature saturation difference value and a dew point temperature difference value through the firefly algorithm in a multi-objective mode, and cooling tower outlet air anti-fogging at low energy consumption is finally achieved. By adoption of the method, a mathematic model is established according to a cooling tower outlet air fogging mechanism, only the dry-bulb temperatures, the relative humidities and the wind speeds of the cooling tower outlet air and the surrounding environment of the cooling tower outlet air need to be collected, the cold air supply quantity is automatically optimized, cooling tower outlet air anti-fogging at lower energy consumption can be achieved, and the thermal performance of a cooling tower is ensured.

Description

A kind of antifog energy consumption optimization method of the cooling tower air-out based on glowworm swarm algorithm

Technical field

The present invention relates to cooling tower air-out anti-fog method, the more particularly to antifog side of the cooling tower air-out based on intelligent algorithm Method.

Background technology

Cooling tower is taken away industry or air conditioning system used heat, is become air conditioning system using air and heat transfer water mass transport process Important component part.Thermal water utilization coil pipe is referred to as dry type with cold air by the cooling tower that heat transfer radiates；Directly hot water is sprayed Drench on filler, the cooling tower for allowing air to radiate with water droplet directly contact is referred to as wet cooling tower.Dry cooling tower can be eliminated and be followed The loss of ring water, but cooling effectiveness is low, and the cooling limit is air dry-bulb temperature；Wet cooling tower cooling effectiveness height, cools down the limit For air's wet bulb temperature, good cooling results, therefore find broad application.

Cold dry air becomes the saturated air of high enthalpy in wet cooling tower with shower water after heat exchange.Excessively Season is interim, is air-dried, and dew point temperature is low, and cooling tower leaving air temp reaches dew point, enters fog-zone, forms white haze, form As the white cigarette for causing on fire, Residents do not know about and are mistaken for fire, and had even reports to the police, and causes unnecessary fear and fiber crops Tired.

Content of the invention

For solving above-mentioned technical problem, it is an object of the invention to provide a kind of cooling based on glowworm swarm algorithm energy optimization Tower air-out anti-fog method.

The purpose of the present invention is realized by following technical scheme：

A kind of cooling tower air-out anti-fog method based on glowworm swarm algorithm energy optimization, the method be based on cooling tower air-out Mist formation mechanism mathematical model, cooling tower air-out and surrounding enviroment parameter measurement and multi-target glowworm swarm optimized algorithm are realized, specifically Comprise the steps：

A collection cooling tower leaving air temp, relative humidity and wind speed and air outlet surrounding enviroment dry-bulb temperature, relative humidity And wind speed；

B calculates mixed gas temperature and absolute humidity；If the saturated humidity of mixed gas is higher than absolute humidity, do not carry out Antifog process；If mixed saturated humidity is less than absolute humidity, start air compensation device to improve cold wind wind supply quantity；

C obtains cold wind air feed value using glowworm swarm algorithm multiple-objection optimization, and the cooling tower air-out for realizing low energy consumption is antifog.

Compared with prior art, one or more embodiments of the invention can have the advantage that：

According to cooling tower air-out mist formation mechanism founding mathematical models, the dry of cooling tower air-out and its surrounding enviroment need to be only gathered Ball temperature, relative humidity, wind speed, Automatic Optimal cold wind wind supply quantity, you can the cooling tower air-out for realizing low energy consumption is antifog, it is ensured that The thermal performance of cooling tower.

Description of the drawings

Fig. 1 is the cooling tower air-out anti-fog method flow chart based on glowworm swarm algorithm energy optimization；

Fig. 2 is cooling tower air-out mist formation and antifog mechanism；

Fig. 3 is the cooling tower air-out anti-fog method program frame figure based on glowworm swarm algorithm energy optimization.

Specific embodiment

For making the object, technical solutions and advantages of the present invention clearer, below in conjunction with embodiment and accompanying drawing to this Bright it is described in further detail.

As shown in figure 1, being the cooling tower air-out anti-fog method based on glowworm swarm algorithm energy optimization, the method includes as follows Step：

Step 1 collection cooling tower leaving air temp, relative humidity, wind speed are monitoring air outlet surrounding enviroment dry-bulb temperature, relative Humidity, wind speed；

Step 2 calculates mixing air temperature, absolute humidity, if the saturated humidity of mixing air is higher than absolute humidity, no Carry out antifog process；If mixed saturated humidity is less than absolute humidity, starts air compensation device and improve cold wind wind supply quantity；

Step 3 obtains cold wind air feed value using glowworm swarm algorithm multiple-objection optimization, and the cooling tower air-out for realizing low energy consumption is prevented Mist.

Fig. 2 is cooling tower air-out mist formation and antifog mechanism.

Such as Fig. 3, above-mentioned steps 1 are specifically included：Survey in the internal mounting temperature sensor of air outlet of cooling tower, humidity sensor Measure temperature T of wind_o, relative humidityObtain air-out blower fan air quantity Q_o；In cooling tower weather mounting temperature sensor, wet Degree sensor, anemobiagraph obtain ambient temperature T respectively_e, relative humidityWind speed v_e.

Mixing air temperature T of above-mentioned steps 2_m, absolute humidity ρ_mComputational methods are:

If air outlet of cooling tower sectional area is A_t, the absolute humidity ρ of mixing air_wFor：

If the latent heat of water is i_w, according to air outlet temperature T_oObtain highest humidity ρ of air-out_omax, air specific heat at constant pressure C_pao, vapor specific heat at constant pressure C_pwo；Then air-out enthalpy I_oFor：

According to ambient temperature T_eObtain highest humidity ρ of air_emax, air specific heat at constant pressure C_pae, vapor level pressure Specific heat capacity C_pwe；Then cold wind enthalpy I_eFor：

The specific heat at constant pressure C of mixing air_pam, vapor specific heat at constant pressure C_pwm, then temperature T of mixing air_mFor：

According to T_mObtain highest humidity ρ of mixing air_mmax, then：

Above-mentioned steps 3 are specifically included：

When cold wind fan delivery is Q_nWhen, the absolute humidity ρ ' of mixing air_wFor：

Then start the cold wind enthalpy I after blower fan_e' be：

Then start the mixing air specific heat at constant pressure C ' after blower fan_pam, vapor specific heat at constant pressure C '_pwm, then mix empty Temperature T of gas_m' be：

According to T_m′、ρ′_mObtain the highest humidity ρ ' of mixing air_mmax, dew point temperature T '_md, then moisture-saturated difference DELTA ρ ′_m, dew point temperature difference DELTA T_m′：

Δρ′_m=ρ '_mmax-ρ′_m

ΔT_m'=T '_md-T_m′

If fan pressure is h_n, efficiency eta_n, then fan shaft power P_nFor

By Q_nAs the control variable of glowworm swarm algorithm, vector [Δ ρ '_m,ΔT_m′,P_n] for glowworm swarm algorithm optimization mesh Mark, weight vectors A=[a_ρ,a_T,a_P]^T, score R of optimum results is：

Searched out by algorithm so that the Q of R maximum_n.

Although disclosed herein embodiment as above, described content is only to facilitate understanding the present invention and adopting Embodiment, is not limited to the present invention.Technical staff in any the technical field of the invention, without departing from this On the premise of the disclosed spirit and scope of invention, any modification and change can be made in the formal and details that implements, But the scope of patent protection of the present invention, still must be defined by the scope of which is defined in the appended claims.

Claims (4)

1. a kind of cooling tower air-out anti-fog method based on glowworm swarm algorithm energy optimization, it is characterised in that methods described is base Calculate in cooling tower air-out mist formation mechanism mathematical model, cooling tower air-out and surrounding enviroment parameter measurement and multi-target glowworm swarm optimization Method is realized, and specifically includes following steps：

A collection cooling tower leaving air temp, relative humidity and wind speed and air outlet surrounding enviroment dry-bulb temperature, relative humidity and wind Speed；

B calculates mixed gas temperature and absolute humidity；If the saturated humidity of mixed gas is higher than absolute humidity, do not carry out antifog Process；If mixed saturated humidity is less than absolute humidity, start air compensation device to improve cold wind wind supply quantity；

C obtains cold wind air feed value using glowworm swarm algorithm multiple-objection optimization, and the cooling tower air-out for realizing low energy consumption is antifog.

2. the cooling tower air-out anti-fog method based on glowworm swarm algorithm energy optimization as claimed in claim 1, it is characterised in that Step A is specifically included：

In the internal mounting temperature sensor of air outlet of cooling tower and humidity sensor, for measuring temperature T of air-out_oWith respect to wet DegreeObtain air-out blower fan air quantity Q_o；

In cooling tower weather mounting temperature sensor, humidity sensor and anemobiagraph, ambient temperature T is obtained respectively_e, relatively wet DegreeWith wind speed v_e.

3. the cooling tower air-out anti-fog method based on glowworm swarm algorithm energy optimization as claimed in claim 1 or 2, its feature exists In mixing air temperature T of step B_m, absolute humidity ρ_mComputational methods are:

If air outlet of cooling tower sectional area is A_t, the absolute humidity ρ of mixing air_wFor：

If the latent heat of water is i_w, according to air outlet temperature T_oObtain highest humidity ρ of air-out_omax, air specific heat at constant pressure C_pao、 The specific heat at constant pressure C of vapor_pwo；Then air-out enthalpy I_oFor：

According to ambient temperature T_eObtain highest humidity ρ of air_emax, air specific heat at constant pressure C_pae, vapor specific heat at constant pressure Hold C_pwe；Then cold wind enthalpy I_eFor：

The specific heat at constant pressure C of mixing air_pam, vapor specific heat at constant pressure C_pwm, then temperature T of mixing air_mFor：

$T_m=\frac{I_o+I_e-{\mathrm{\ρ}}_w{i}_w}{(Q_o+v_{e}A)(C_{pam}+{\mathrm{\ρ}}_w{C}_{pwm})}$

According to T_mObtain highest humidity ρ of mixing air_mmax, then：

4. the cooling tower air-out anti-fog method based on glowworm swarm algorithm energy optimization as claimed in claim 1, it is characterised in that Step C is specifically included：

When cold wind fan delivery is Q_nWhen, the absolute humidity ρ ' of mixing air_wFor：

Then start the cold wind enthalpy I ' after blower fan_eFor：

Then start the mixing air specific heat at constant pressure C ' after blower fan_pam, vapor specific heat at constant pressure C '_pwm, then mixing air Temperature T '_mFor：

$T_m^{\′}=\frac{I_o+I_e^{\′}-{\mathrm{\ρ}}_w^{\′}{i}_w}{(Q_o+v_{e}A+Q_n)(C_{pam}^{\′}+{\mathrm{\ρ}}_w^{\′}{C}_{pwm}^{\′})}$

According to T '_m、ρ′_mObtain the highest humidity ρ ' of mixing air_mmax, dew point temperature T '_md, then moisture-saturated difference DELTA ρ '_m, dew Point temperature gap Δ T '_m：

Δρ′_m=ρ '_mmax-ρ′_m

ΔT′_m=T '_md-T′_m

If fan pressure is h_n, efficiency eta_n, then fan shaft power P_nFor

$P_n=\frac{Q_n{h}_n}{3600\×1000{\mathrm{\η}}_n}$

By Q_nAs the control variable of glowworm swarm algorithm, vector [Δ ρ '_m,ΔT′_m,P_n] for glowworm swarm algorithm optimization aim, power Weight vector A=[a_ρ,a_T,a_P]^T, optimisation strategy is：

$\left\{\begin{array}{c}\mathrm{\Δ}{\mathrm{\ρ}}_m^{\′}>0\\ \mathrm{\Δ}{T}_m^{\′}>0\\ R=\[\mathrm{\Δ}{\mathrm{\ρ}}_m^{\′},\mathrm{\Δ}{T}_m^{\′},P_n\]\·A\end{array}\right.$

Searched out by algorithm so that R meets the Q of condition_n.