CN111125938B

CN111125938B - Optimal design method of large-scale central air-conditioning chilled water pipe network based on suboptimal algorithm

Info

Publication number: CN111125938B
Application number: CN202010042823.6A
Authority: CN
Inventors: 刘雪峰; 蒋航航; 路坦; 王家绪; 郑宇蓝; 刘金平
Original assignee: South China University of Technology SCUT
Current assignee: South China University of Technology SCUT
Priority date: 2020-01-15
Filing date: 2020-01-15
Publication date: 2021-07-16
Anticipated expiration: 2040-01-15
Also published as: CN111125938A

Abstract

The invention discloses an optimal design method for a large-scale central air-conditioning chilled water pipe network based on a suboptimal algorithm. By constructing a thermodynamic model of a large-scale central air-conditioning chilled water pipe network, the present invention integrates existing traditional pipe network design methods such as the recommended flow rate method and the most unfavorable loop economic specific friction method and traditional optimization design methods such as simulated annealing algorithm, Genetic algorithm and neural network algorithm are used to optimize the design effect of central air-conditioning pipe network, and the sub-optimal calculation method of random walking is proposed to discard the optimal solution to obtain the sub-optimal solution of the pipe diameter design scheme suitable for various load distribution changes. , the initial investment and annual operating cost of the pipe network are used as the objective function for the optimization calculation. Through the forward optimization calculation and the reverse verification calculation, the results of the optimization calculation of the pipe diameter of the pipe network by different load distribution forms and load ratio distribution adaptive effects. In order to achieve the purpose of saving energy consumption, it is conducive to the sustainable development of modernization.

Description

Suboptimal algorithm-based optimization design method for large central air-conditioning chilled water pipe network

Technical Field

The invention relates to the field of optimization design of a large central air-conditioning chilled water pipe network, in particular to a suboptimal algorithm-based optimization design method of the large central air-conditioning chilled water pipe network.

Background

The city in China in the 21 st century has developed towards the direction of internationalization, ecology, modernization and intellectualization, the rapid expansion of the scale of the city aggravates the intensity of city buildings, and a central air conditioning system is taken as an indispensable part of a city public building, so that the high energy consumption of the central air conditioning system is always concerned. Irrational early-stage design and unscientific later-stage operation management of the air conditioning system are main reasons for ineffective energy consumption. The actual energy-saving operation of the large-scale central air-conditioning system generally has the problems of poor stability, poor adjustability, poor energy-saving effect and the like. Generally, the building energy consumption can reach more than 20% of the total social energy consumption, the energy consumption of the air conditioning system in the building energy consumption can reach 60%, and the energy consumption level of the centralized air conditioning system depends on the simultaneous utilization rate of the tail ends, the topological structure form of the pipe network, the operation management mode of equipment and the like. Generally, the annual energy consumption of an air conditioning system with the building air conditioner using area exceeding 2 million square meters can reach 400 million kWh, 60 million kWh can be saved every year according to the average energy saving rate of 15%, if the number of buildings exceeding 2 million square meters in a certain town reaches 1000, the energy saving amount of the air conditioning system in the town can reach 6 hundred million kWh/year, the electric charge of the town can be saved by 53998 ten thousand yuan every year, large public buildings in China can be greatly increased along with the urbanization development, and the energy saving potential of the optimized operation of a large central air conditioning chilled water system is very large.

The optimized design research of the pipe diameter and the topological structure of the central air-conditioning pipe network is always the key point of the research of the students, a neural network method is applied by using a slow wave and the like to establish a prediction model of the water conveying energy efficiency ratio of the regional cooling pipe network, a fluid mechanics calculation formula is adopted to calculate the conveying energy efficiency ratio, and a definite conveying energy efficiency ratio range is determined to provide reference for the reasonable design of the regional cooling system (the slow wave, the Gong-Fu-wind, the regional cooling pipe network conveying energy efficiency ratio calculation model research [ J ]. the heat energy ventilation air conditioner for the building [ 2012(05):25-27 ]. Reem Khir et al have studied the optimization design and operation of DCS, have established models including equipment capacity, storage capacity, piping network scale and layout and quantity, hydraulic characteristics and thermal characteristics models, have optimized design to minimize the total investment and operating cost (Khir R, Haouari M. optimization models for a single-plant discharge engineering System [ J ]. European Journal of Operational research.2015,247(2):648 658.). The method is characterized in that a von Xiaoping student adopts a genetic algorithm to optimally design a pipe network of a centralized air-conditioning water system, a pipe network mathematical model is established, the analysis is carried out by utilizing the basic principle, the coding technology, the evaluation function and the cross and variation methods of the genetic algorithm, and experiments prove that the GA algorithm is effectively applied to the problem of optimal selection of the pipe diameter of the air-conditioning pipe network (von Xiaoping, Longdan-Guo, the optimization design of the pipe network of the centralized air-conditioning water system based on the genetic algorithm [ J ] fluid machinery 2007(03): 80-84.). ALS Chan et al adopt genetic algorithm and local search technology, in the situation that the pipe network node has already been confirmed, optimize and calculate the topological structure and pipe diameter of the pipe network, make the initial investment add the operating cost minimum (Chan A L S, Hanby V I, Chow T. optimization of distribution piping network in distributing the systematic using genetic algorithm [ J ]. Energy Conversion & management.2007,48(10): 2622). Earlier-stage scientific researchers work shows that the traditional optimization algorithm has a certain optimization effect on the optimization design of the pipe network pipe diameter and the topological structure, but the traditional optimization algorithm also has the defects of easiness in falling into local optimization, large difference of optimization results, long time for single optimization calculation and the like. By adopting the random walking suboptimal calculation method, the optimization process of each control variable in the optimization calculation process is random and independent, the probability that the optimization calculation is trapped in local optimization or even is not converged can be greatly reduced, the optimization calculation result is basically not influenced by the change of the optimization initial value, and the adaptability of the optimization design can be improved.

Disclosure of Invention

The invention aims to provide a suboptimal algorithm-based optimization design method for a large central air-conditioning chilled water pipe network aiming at the problems in the background technology, and integrates the traditional pipe network design methods such as: the recommended flow rate method and the most unfavorable economic friction method of the loop are compared with the traditional optimization design method, such as: the optimization design effect of a simulated annealing algorithm, a genetic algorithm, a neural network algorithm and the like on a central air-conditioning pipe network is achieved, a random walking suboptimal calculation method is provided, an optimal solution is abandoned to obtain a pipe diameter design scheme suitable for various load distribution changes, the suboptimal solution is obtained, optimization calculation is carried out by taking the initial investment and the annual operating cost of the pipe network as a target function, and finally the influence of different load distribution forms and load rate distribution on the pipe diameter optimization calculation result and the adaptability of the pipe network is analyzed through forward optimization calculation and reverse verification calculation. Thereby achieving the purpose of saving energy consumption and being beneficial to the sustainable development of modernization.

The purpose of the invention is realized by at least one of the following technical solutions.

The optimization design method of the large central air-conditioning chilled water pipe network based on the suboptimal algorithm comprises the following steps:

s1, establishing a thermal performance calculation model of the terminal equipment: establishing a surface cooler physical model, taking 8 input parameters of outdoor environment dry bulb temperature, outdoor environment wet bulb temperature, indoor control point dry bulb temperature, surface cooler chilled water inlet temperature, total air quantity, fresh air ratio, cold load and wet load into consideration, establishing a heat-humidity balance equation, dividing the heat-humidity balance equation into two layers to perform iterative circulation to obtain 7 output parameters of surface cooler chilled water flow, surface cooler chilled water return water temperature, air supply temperature difference, indoor control point wet bulb temperature, indoor control point temperature, air dry bulb temperature at an inlet of the surface cooler and air wet bulb temperature at an inlet of the surface cooler, and establishing a thermal performance calculation model of the end equipment;

s2, establishing a chilled water pipe network hydraulic calculation model: obtaining a chilled water pipe network hydraulic calculation model according to the pressure balance of each branch of the pipe network, the flow conservation principle of each node and the flow rule of series-parallel pipelines by taking the tail end impedance, the required flow of each branch, namely the output parameters in the thermal performance calculation model of the tail end equipment in the step S1, namely the chilled water flow of the surface cooler, the pipe lengths of the pipe network water supply and return pipe and the branch pipe, the pipe diameters of the pipe network water supply and return pipe and the branch pipe, the local resistance coefficient, the pipe inner wall roughness of the pipe network water supply and return pipe and the branch pipe, the valve body impedance corresponding to the maximum opening of the valve and the tail end;

s3, selecting an objective function for pipe network optimization: under the premise of comprehensively considering the initial investment cost, the annual operation cost and the depreciation cost of the pipe network of the chilled water pipe network of the central air conditioner, the annual reduced cost of the pipe network is provided as a target function for optimizing the pipe network;

s4, analyzing the change rule of the objective function of the pipe network by adopting a suboptimal calculation method: considering different functional building types, inputting boundary calculation parameters; calculating an optimal solution in each pre-defined calculation area by adopting a random walking and optimization area division suboptimal calculation method, taking the minimum value of the optimal solution in each area as a new optimization calculation starting point, performing variable-step-length cyclic iterative optimization calculation again, avoiding the calculation from falling into local optimization to the maximum extent, calculating the optimization results of the pipe network under different working conditions, and analyzing the target function change rule of the pipe network in the optimization design results of the pipe network under different working conditions compared with the traditional design method;

s5, performing optimal calculation suboptimal solution group statistical analysis: calculating and analyzing frequency distribution statistics of pipe diameters of various pipe sections in suboptimal solution groups output in the whole calculation process under different working conditions, and obtaining pipe network pipe diameter distribution forms universally adapted to various loads and pipe network pipe diameter distribution obtained by a traditional design method under uniform load distribution;

and S6, analyzing statistical rules and random behaviors according to the obtained solution group, obtaining reference ranges of pipe diameters of all pipe sections under different load distribution forms and load rates, and providing guidance opinions and scientific bases for early-stage design and later-stage optimization and transformation of the large-scale central air-conditioning chilled water pipe network.

Further, in step S1, firstly, performing off-line calculation on the thermal performance calculation model of the single terminal device, forming a uniform calculation grid by using 6 variables of the air inlet temperature, the air inlet relative humidity, the air outlet temperature, the air outlet relative humidity, the air volume and the AHU water flow, wherein each variable takes 10 horizontal calculation values, and the calculation is completed by off-line calculation; and screening bad values of all data, eliminating the bad values, creating a terminal equipment operation characteristic database, and directly performing interpolation calculation according to an inverse distance weighted interpolation method to reduce the times of optimization calculation.

Further, in step S1, under a certain structural parameter of the surface cooler, for a certain model of surface cooler, any one of the operating condition parameters thereof satisfies the following three relationships: heat exchange efficiency coefficient epsilon in air treatment process_r1Equal to the heat exchange efficiency coefficient epsilon of the surface cooler structure during operation _j1② contact coefficient ε in air treatment process_r2Equal to the contact coefficient epsilon of the surface cooler structure during operation_j2The quantity of heat exchange of the air in the air treatment process is equal to the quantity of heat exchange Q of the chilled water; the following relations exist among parameters in the surface cooler:

heat exchange coefficient epsilon in process of constraining surface cooler treating air_r1Contact coefficient ε_r2Amount of heat exchange with air Q_airHeat exchange coefficient epsilon determined by surface cooler self structure parameter and empirical coefficient_j1Contact coefficient ε_j2Amount of heat exchange with chilled water Q_waterEqual to the dry bulb temperature t at the air side inlet of the surface cooler₁Surface cooler inlet air enthalpy value i₁Air flow G at air side inlet of surface cooler and cold water temperature t at cold water side inlet of surface cooler_w1For calculating input variables, the temperature t of the dry bulb at the air side outlet of the surface cooler is output through modeling calculation₂Surface cooler outlet air enthalpy value i₂And the temperature t of cold water at cold water side outlet of surface cooler_w2：

In the formula: beta is the number of heat transfer units; ge. me, ne are empirical systems for solving contact coefficientsNumber, derived from experiments; k is the heat exchange coefficient of the surface cooler in the air treatment process; gamma is the water equivalence ratio of air to chilled water; v_yThe frontal area of the surface cooler is shown; xi is the moisture analysis coefficient in the treatment process; k_sThe heat transfer coefficient under the wet working condition; t is t₁The temperature of the dry bulb at the air side inlet of the surface cooler; i.e. i₁The enthalpy value of the inlet air of the surface cooler is obtained; t is t_w1The temperature of cold water at the cold water side inlet of the surface cooler is set; t is t₂The temperature of the dry bulb at the air side outlet of the surface cooler; i.e. i₂The enthalpy value of the air at the outlet of the surface cooler; t is t_w2The temperature of cold water at the cold water side outlet of the surface cooler is set; f is the heat exchange area of the surface cooler; c. C_pThe average specific heat capacity of air in the treatment process; g is the air flow in the air treatment process of the surface air cooler; w is the flow of the chilled water in the treatment process; omega is the flow rate of the chilled water in the treatment process; c is the average specific heat capacity of the frozen water in the treatment process; t is t₃The temperature of the air outlet dry bulb is the ideal state of the surface cooler in the air treatment process; A. b is a coefficient obtained by an experiment; and m and n are indexes obtained by experiments.

Further, in step S1, a heat-humidity balance equation is established according to the input parameters, and 7 output parameters are obtained by two-layer iterative loop, which is specifically as follows:

W＝(d_N-d_L)G；

in the formula: g is the air flow in the air treatment process of the surface cooler, and the unit is kg/h; q is the heat exchange quantity in the air treatment process, and the unit is kw; i.e. i_cThe unit is kj/kg for the air enthalpy value at the mixing point; d_cThe air moisture content at the mixing point is given in g/kg; t is t_LThe temperature of air at the outlet of the surface cooler is measured in units of ℃;

relative humidity of air at the outlet of the surface cooler; i.e. i_wIs the enthalpy value of outdoor air, and the unit is kj/kg; m is_newThe fresh air ratio is adopted; i.e. i_NIs the enthalpy value of indoor air, and the unit is kj/kg; d_wThe moisture content of outdoor air is g/kg; d_NThe indoor air moisture content is g/kg; the type is the type of the surface cooler; t is t_cIs the air temperature at the mixing point in units;

the mixing point air relative humidity; t is t₂The temperature of a dry bulb at the air side outlet of the surface cooler is unit ℃;

the relative humidity of the air at the air side outlet of the surface air cooler; i.e. i_LThe enthalpy value of the air at the outlet of the surface cooler is kj/kg; d_LThe moisture content of the air at the outlet of the surface cooler is given in g/kg.

Further, step S1 includes the steps of:

s1.1, inputting the dry bulb temperature of a tail end indoor control point under a simulation working condition, the dry bulb temperature and the wet bulb temperature of an outdoor environment, the total air quantity, the fresh air ratio, the cold load, the wet load and the inlet water temperature of chilled water of a surface cooler;

s1.2, setting indoor moisture content, and determining indoor state point parameters;

s1.3, calculating a mixed point air state and an air supply point air state, wherein the air supply point air state comprises an air supply point air temperature and an air supply point air moisture content;

s1.4, setting an initial value of the flow of chilled water of a fan bypass pipe;

s1.5, solving a surface cooler outlet air state by using a surface cooler physical model, wherein the surface cooler outlet air state comprises a surface cooler outlet air temperature and a surface cooler outlet air moisture content;

s1.6, judging whether the air temperature at the outlet of the surface air cooler is equal to the air temperature at the air supply point, if so, executing the step S1.7; if not, executing the step S1.4;

s1.7, judging whether the moisture content of air at the outlet of the surface air cooler is equal to that of air at an air supply point, if so, executing a step S1.8, and if not, executing a step S1.2;

s1.8, outputting data output parameters: the system comprises a cooler freezing water flow, a surface cooler freezing water return water temperature, an air supply temperature difference, an indoor control point wet bulb temperature, an indoor control point temperature, a surface cooler inlet air dry bulb temperature and a surface cooler inlet air wet bulb temperature.

Further, in step S2, the on-way resistance coefficient λ of the pipeline has the following relationship with the impedance:

calculation of λ: the relative roughness is epsilon 2 delta/D, Reynolds number Re v D/gamma, A59.7/epsilon^8/7And B ═ 665-: λ ═ 0; when 0 is present<Re<3000, the on-way drag coefficient of the pipe is: λ 64/Re; when Re>3000, and Re<The on-way resistance coefficient of the pipeline is as follows: lambda is 0.3164/Re^0.25(ii) a When A is<Re, and Re<When B is obtained, the on-way resistance coefficient of the pipeline is as follows: λ ═ 1/(-1.8 × Log ((Δ/3.7 × D))^1.11+6.8/Re)/Log(10))²(ii) a When B is present<At Re, the on-way drag coefficient of the pipeline is: λ 1/(2 Log (3.7D/Δ))²；

Therefore, the branch pipelines and the water supply and return main pipelines have the following impedances:

the end device impedances are as follows:

in the hydraulic calculation model of the freezing water pipe network, the pipe lengths, pipe diameters, inner wall roughness, local resistance coefficients, valve impedances, terminal equipment impedances, and the flow of each terminal and the pressure drop of each branch of the pipe network water supply main pipe, the water return main pipe and the terminal branch have the following relations:

the constraint conditions of the cold water pipe network water conservancy calculation model are as follows:

G_{branch_1}≤G_{branch_ini_1},…,G_{branch_n}≤G_{branch_ini_n}

S_{valve_temp_1}≥S_{valve_temp_min_1},…,S_{valve_temp_n}≥S_{valve_temp_min_n}

Δp_{branch_1}≥0,…,Δp_{branch_n}≥0,Δp_AB≥0

in the formula: delta P_{branch_b_n}Represents the equilibrium pressure drop of the branch line in Pa; s_{AHU_n}Represents the impedance of the terminal equipment AHU and has the unit of Pa/(kg)²/s²)；S_{branch_n}Represents the branch line impedance with the unit of Pa/(kg)²/s²)；S_{main_in-n}Represents the impedance of the water main between two nodes and has the unit of Pa/(kg)²/s²)；S_{main_out_n}Representing the impedance of the backwater main pipe between two nodes and the unit is Pa/(kg)²/s²)；ΔP_ABThe minimum water supply and return pressure difference of the pipe network is expressed in Pa; g_{branch_n}Represents the terminal flow rate in kg/s; delta P_{valve_n}Represents the valve differential pressure in Pa; gamma represents the average kinetic viscosity of the chilled water; i represents the water on-off area; a1 denotes the fan coil coefficient; n1 represents the fan coil coefficient; ζ represents the local drag coefficient; Δ represents the surface roughness; d_{branch_n}The pipe diameter of the branch pipe is expressed in m; l is_{branch_n}Represents the length of the branch pipe, and the unit is m; d_{main_in_n}The pipe diameter of the water supply main pipe is shown, and the unit is m; l is_{main_in_n}The length of the water supply main pipe is expressed in m; d_{main_out_n}The pipe diameter of the backwater main pipe is expressed in m; l is_{main_out_n}The length of the backwater main pipe is expressed in m.

Further, in step S3, the economic evaluation criteria of the chilled water system includes initial investment cost and operating cost of the chilled water system, and the scrap disposal cost is the remaining value, the source of the chilled water system refers to "practical heating air-conditioning design manual (second edition)", for the chilled water system pipe network, the equivalent uniform annual cost includes the operating electricity cost of the chilled water pump, the depreciation cost of the pipeline, the average annual depreciation cost, and the average annual maintenance cost, the chilled water delivery adopts a variable-frequency speed-regulating water pump, and under different load rate conditions, the flow rate delivered by the chilled water pump is regulated, and the chilled water is delivered under the condition of ensuring the constant temperature of the delivered water, so the operating electricity cost calculation formula of the chilled water pump is as follows:

in the formula, Q_waterCalculating the flow of the circulating water pump according to the flow required by the cold source side; p is the working pressure of the circulating water pump; eta_pThe value range is 0.5-0.7 for the electromechanical efficiency of the water pump; tau is_iThe service time under the ith load rate; c. C_eIs the electricity price;

the objective function of the pipe network optimization design is as follows:

in the formula: c_hRepresents capital (investment) recovery; c_chRepresenting the initial investment cost of the pipe network, including planning cost, design cost and construction cost;

representing the price conversion rate of the current year;

expressing j-year price conversion rate; c_yjAn annual operating fee (in terms of base years) representing the j years; i.e. i_jExpressing the inflation of the currency in j years, namely the interest rate increasing rate which is j year rate/(j-1) year rate; c_WjRepresenting the maintenance cost of the jth year converted from the basic year; s represents the scrap disposal cost or the remaining value; i represents interest; n represents the year of operation.

Further, in step S4, the boundary calculation parameters include an indoor control point dry-bulb temperature, an outdoor control point dry-wet-bulb temperature, a total air volume, a fresh air ratio, a cold load, a wet load, a terminal impedance, a required flow of each branch, a pipe network water supply and return pipe and branch pipe lengths, pipe network water supply and return pipe and branch pipe diameters, a local resistance coefficient, pipe network water supply and return pipe and branch pipe inner wall roughness, a valve body impedance corresponding to a maximum valve opening, and a terminal device impedance; the selection of the calculation parameters of each boundary is as follows:

according to the regulations in the design Standard for energy conservation of public buildings (GB 50189-2005) and the design Specification for heating Ventilation and air Conditioning (GB 50019-2003), when the height of an air supply opening is less than or equal to 5m, the temperature difference of the supplied air is between 5 degrees and 10 degrees, and when the height of the air supply opening is greater than 5m, the temperature difference of the supplied air is greater than 10 degrees and less than 15 degrees.

According to the regulations in the design specifications of heating ventilation and air conditioning and the air conditioning, the indoor and outdoor calculation parameters of the comfort air conditioner are as follows:

the indoor dry bulb temperature is 24 ℃, the indoor relative humidity is maintained between 40% and 65%, the outdoor dry bulb temperature is 33.5 ℃, the outdoor wet bulb temperature is 27.7 ℃, the fresh air ratio is 0.1, and the chilled water inlet temperature is 7 ℃;

on the premise of determining the parameters such as the number of indoor personnel, the working time, the working state of the personnel and the like, the calculation formulas of the cold load, the wet load and the air volume are as follows:

in the formula: q_τCalculating the moment cold load W formed by sensible heat radiation of a human body; q. q.s_m,W,minIs the fresh air quantity, and the unit is m³H; d _ tau is the human body moisture content at the moment of calculation, and the unit is kg/s; q _ tau is latent heat cold load formed by calculating the human body moisture content at the moment, and the unit is W; n is the total number of people in the air-conditioning area at the moment of calculation;

is the cluster coefficient; q. q.s₁Is the heat dissipation capacity of the adult male in hour, W; tau is the calculation time and the unit is h; t is the time when the person enters the air conditioning area, and the unit is h; tau-T is the duration time from the time when the personnel enter the air conditioning area to the time when the personnel calculate, and the unit is h;X_τ-Ta cold load coefficient for sensible heat dissipation of a human body at the time of tau-T; q. q.s_m,W,pThe minimum fresh air quantity required by each person per hour is expressed in the unit of (m)³V (humans x h)); q. q.s_m,W,bIs the minimum fresh air quantity required per hour per unit building area and has the unit of (m)³/(m²H)); f is the building area of the ventilated room, and the unit is m²。

Further, the step S4 includes the following steps:

s4.1, setting the pipe network water supply and return of each section and the pipe diameter X of the tail end branch as (X)₁,x₂,…,x_n) N is the serial number of the pipe section of the pipe network, N is 1-N, x_nOptimizing calculation variables for a pipe network, and setting the number N of total variables, the random walking step length A and the terminal control modulus M;

s4.2, inputting pipe network tail end impedance, chilled water flow of each branch surface cooler, pipe network water supply and return pipes and branch pipe lengths, pipe network water supply and return pipes and branch pipe diameters, local resistance coefficients, pipe network water supply and return pipes and branch pipe inner wall roughness, valve body impedance corresponding to the maximum opening degree of a valve, and tail end equipment impedance calculation parameter information;

s4.3, setting an optimization objective function F (x) as the annual reduced cost of the pipe network;

s4.4, setting the maximum and minimum flow rates in the pipe corresponding to the pipe diameters of the water supply and return main pipe and the tail end branch of each section of the pipe network, taking the maximum pipe diameter corresponding to the minimum flow rate in the pipe as the initial starting point of optimization calculation of each section, and X₀＝(x₁₀,x₂₀,…,x_n0)；

S4.5, calculating starting point X by optimizing₀＝(x₁₀,x₂₀,…,x_n0) Taking the upper limit value and the lower limit value of each independent variable as a constraint, calculating an optimization area division control modulus, carrying out equidistant area division on a multi-dimensional optimization independent variable grid, dividing the multi-dimensional optimization independent variable grid into N optimization calculation area, and calculating the minimum value of an objective function in each optimization area;

s4.6, randomly generating a random number r in a certain range_nTo obtain a random walking unit direction vector R,

determining a new optimization starting point X₁，X₁＝(x₁₁,x₂₁,…,x_n1) Wherein: x is the number of_1o＝(x_max+x_min)/2+A·M·r₁/R，x_no＝(x_max+x_min)/2+A·M·r_n/R；

S4.7, calculating a tentative objective function value F (X)_temp(ii) a If F (X) ≦ F (X)_tempThen F (X) ═ F (X)_temp；x₁₀＝x₁，x₂₀＝x₂，x_n0＝x_n(ii) a Reducing the step length A to 0.8A, and circularly calculating; if F (X)>F(X)_tempContinuing to step S4.5 until the number of times of the calculation step reaches a set value;

s4.8, arranging the calculation results of each area in the order from small to large, and taking the independent variable value corresponding to the minimum objective function in each area as a new optimization starting point to perform optimization calculation again;

s4.9, if A>A₀Continuing to step S5, if A is<A₀And (5) finishing the calculation to obtain an optimal solution:

X_k＝(x₁,x₂,…,x_n)，i≤x_n≤j，k＝1,2…

the search range of the variable is (x)_n0-A,x_n0+ A), along with the reduction of the value A, the calculation search range is gradually reduced, the more the number of the circulating calculation times is, the closer the random solution vector is to the theoretical optimal solution, the more the distribution is concentrated, the statistical optimal solution is obtained according to the distribution characteristics, and the analysis of the target function change rule of the pipe network compared with the traditional design method under different working conditions of the pipe network optimization design result is completed.

In step S5, in the actual operation of the air conditioning system, because the variation of the load at each end is large along with the time and space distribution, and the variation of the load has a certain randomness, and detailed data of the load variation cannot be obtained at the initial stage of the pipe network design, in the conventional engineering design, engineers design the chilled water pipe network of the central air conditioning according to the designed maximum load, so that the air conditioning system operates in the designed partial load state most of the time, the pipe network transmission efficiency is low, the pipe network utilization rate is low, and the initial investment of the pipe network is relatively large.

The step S5 includes the steps of:

s5.1, respectively carrying out optimization design calculation on five pipe networks with different load distribution forms by utilizing a random walking suboptimal algorithm to obtain optimal solutions of pipe network pipe diameter distribution optimization designs of various types, comparing the optimal solutions with pipe diameter distribution obtained by adopting traditional design calculation under the condition of the same load parameters, and analyzing the difference between the initial investment and the annual operating cost of the optimally designed pipe network pipe diameter in the operating year compared with the traditional design method;

s5.2, outputting parameter suboptimal calculation solution groups of pipe network optimization calculation under each working condition, outputting optimization step length, valve opening of each branch, objective function, pressure drop of each branch, valve pressure drop, pressure drop of a water supply and return main pipe, pipe diameter of a water supply main pipe, pipe diameter of a water return main pipe and pipe diameter of a tail end branch in the optimization calculation process, and counting the pipe diameter value probability distribution trend of the water supply main pipe and the water return main pipe in the single-time pipe network suboptimal optimization design calculation process under different load distribution;

s5.3, performing statistical analysis on regions with highest probability coincidence degree of pipe diameters of the water supply and return main pipe and the tail end branch in solution groups with five different load distribution forms to serve as suboptimal solutions of pipe diameter values;

and S5.4, outputting the pipe diameter value suboptimal solution of each type of pipe section obtained in the step S5.3, substituting the pipe diameter value suboptimal solution into five different load distribution working conditions, comparing the pipe diameter value suboptimal solution with a target function value of pipe diameter distribution obtained by adopting a traditional design method under each working condition in different operation years, and analyzing the load adaptability of the pipe diameter distribution obtained by the suboptimal solution.

Compared with the prior art, the invention has the following beneficial effects:

1. on the premise of fully considering hydraulic characteristics and different distribution types of terminal loads of a central air-conditioning chilled water system pipe network, a chilled water system optimization design scheme based on a suboptimal theory and taking annual reduced cost of the chilled water pipe network as a target function is provided. The optimization calculation initial value is changed to carry out 30 times of optimization calculation, the final optimization result is maximum, the minimum value difference is less than 0.1%, the obtained optimization result accords with the hydraulic characteristics of a pipe network, the problems of discrete variables, nonlinear programming and multiple constraints can be solved by the random walk and variable step suboptimal algorithm, the calculation process is simple, multi-path optimization can be realized, and the calculation result is reliable.

2. The pipe diameter distribution obtained by suboptimal calculation under each load distribution type is subjected to statistical analysis, the annual reduced cost of optimal design in 15 years under different load distributions is compared with the annual reduced cost of traditional design, and the annual reduced cost of a pipe network based on suboptimal optimal design aiming at certain determined load distribution can be greatly reduced compared with the traditional design scheme, and the proportion of cost saving is increased along with the increase of the operation years.

3. Through statistical analysis of the solution group obtained by the optimal calculation of the pipe diameter of the same-path pipe network, a pipe diameter value range suitable for different load distribution forms can be obtained. Compared with the change rule of 15-year reduced cost under different load distributions of the suboptimal calculation result and the pipe diameter value obtained by the traditional design method under uniform load distribution, the suboptimal optimization design result is greatly improved in adaptability to load compared with the traditional design.

Drawings

FIG. 1 is a flow chart of a suboptimal algorithm-based optimization design method for a large-scale central air-conditioning chilled water pipe network in the embodiment of the invention;

FIG. 2 is a flow chart of a sub-optimal computation method in an embodiment of the invention;

FIG. 3 is a diagram of an approximation process of a pipe network optimization result in an embodiment of the present invention;

FIG. 4 is a value probability distribution diagram of pipe diameters of pipe sections of the water main pipe according to the embodiment of the present invention;

FIG. 5 is a value probability distribution diagram of pipe diameters of pipe sections of a backwater main pipe in the embodiment of the invention;

FIG. 6 is a value probability distribution diagram of pipe diameters of pipe sections of a terminal branch in an embodiment of the present invention;

FIG. 7 is a diagram illustrating a distribution of pipe diameters of various types distributed uniformly in an embodiment of the present invention;

FIG. 8 is a diagram illustrating a distribution of pipe diameters of various types in an increasing distribution in an embodiment of the present invention;

FIG. 9 is a diagram illustrating various pipe diameters distributed in a concave shape according to an embodiment of the present invention;

FIG. 10 is a diagram illustrating a distribution of decreasing pipe diameters of different types according to an embodiment of the present invention;

FIG. 11 is a diagram illustrating various pipe diameters distributed in a convex shape according to an embodiment of the present invention;

FIG. 12 is a diagram of a suboptimal tube diameter profile in an embodiment of the present invention;

FIG. 13 is a graph illustrating the ratio of the saved cost to the total cost of the optimal design under different loads in an embodiment of the present invention;

FIG. 14 is a diagram of a ratio of the saving cost to the total cost of the optimal design of the sub-optimal pipe diameter distribution under different loads according to an embodiment of the present invention;

FIG. 15 is a ratio of the cost saving to the total cost of the design of pipe diameter under different load distributions according to the conventional design method under uniform load distribution in the embodiment of the present invention.

Detailed Description

Specific embodiments of the present invention will be described in further detail below with reference to examples and drawings, but the present invention is not limited thereto.

Example 1:

a suboptimal algorithm-based optimization design method for a large central air-conditioning chilled water pipe network is shown in figure 1 and comprises the following steps:

firstly, performing off-line calculation on a thermal performance calculation model of single terminal equipment, forming a uniform calculation grid by 6 variables of inlet air temperature, inlet air relative humidity, outlet air temperature, outlet air relative humidity, air quantity and AHU water flow, and finishing off-line calculation by taking 10 horizontal calculation values of each variable; and screening bad values of all data, eliminating the bad values, creating a terminal equipment operation characteristic database, and directly performing interpolation calculation according to an inverse distance weighted interpolation method to reduce the times of optimization calculation.

Under certain structural parameters of the surface air cooler, for a certain type of surface air cooler, any operating condition parameter of the surface air cooler meets the following three relations: heat exchange efficiency coefficient epsilon in air treatment process_r1Equal to the heat exchange efficiency coefficient epsilon of the surface cooler structure during operation _j1② contact coefficient ε in air treatment process_r2Equal to the contact coefficient epsilon of the surface cooler structure during operation_j2The quantity of heat exchange of the air in the air treatment process is equal to the quantity of heat exchange Q of the chilled water; the following relations exist among parameters in the surface cooler:

In the formula: beta is the number of heat transfer units; ge. me and ne are empirical coefficients for solving the contact coefficient and are obtained through experiments; k is the heat exchange coefficient of the surface cooler in the air treatment process;gamma is the water equivalence ratio of air to chilled water; v_yThe frontal area of the surface cooler is shown; xi is the moisture analysis coefficient in the treatment process; k_sThe heat transfer coefficient under the wet working condition; t is t₁The temperature of the dry bulb at the air side inlet of the surface cooler; i.e. i₁The enthalpy value of the inlet air of the surface cooler is obtained; t is t_w1The temperature of cold water at the cold water side inlet of the surface cooler is set; t is t₂The temperature of the dry bulb at the air side outlet of the surface cooler; i.e. i₂The enthalpy value of the air at the outlet of the surface cooler; t is t_w2The temperature of cold water at the cold water side outlet of the surface cooler is set; f is the heat exchange area of the surface cooler; c. C_pThe average specific heat capacity of air in the treatment process; g is the air flow in the air treatment process of the surface air cooler; w is the flow of the chilled water in the treatment process; omega is the flow rate of the chilled water in the treatment process; c is the average specific heat capacity of the frozen water in the treatment process; t is t₃The temperature of the air outlet dry bulb is the ideal state of the surface cooler in the air treatment process; A. b is a coefficient obtained by an experiment; and m and n are indexes obtained by experiments.

Establishing a heat-humidity balance equation according to the input parameters, and obtaining 7 output parameters by two-layer iterative cycle, wherein the method specifically comprises the following steps:

relative humidity of air at the outlet of the surface cooler; i.e. i_wIs the enthalpy value of outdoor air, and the unit is kj/kg; m is_newThe fresh air ratio is adopted; i.e. i_NIs the enthalpy value of indoor air, and the unit is kj/kg; d_wThe moisture content of outdoor air is g/kg; d_NThe indoor air moisture content is g/kg; the type is the type of the surface cooler; t is t_cIs the air temperature at the mixing point in degrees C；

Step S1 includes the following steps:

S2 and S2, establishing a hydraulic calculation model of the freezing water pipe network: obtaining a chilled water pipe network hydraulic calculation model according to the pressure balance of each branch of the pipe network, the flow conservation principle of each node and the flow rule of series-parallel pipelines by taking the tail end impedance, the required flow of each branch, namely the output parameters in the thermal performance calculation model of the tail end equipment in the step S1, namely the chilled water flow of the surface cooler, the pipe lengths of the pipe network water supply and return pipe and the branch pipe, the pipe diameters of the pipe network water supply and return pipe and the branch pipe, the local resistance coefficient, the pipe inner wall roughness of the pipe network water supply and return pipe and the branch pipe, the valve body impedance corresponding to the maximum opening of the valve and the tail end;

in step S2, the on-way resistance coefficient λ of the pipeline has the following relationship with the impedance:

the end device impedances are as follows:

G_{branch_1}≤G_{branch_ini_1},…,G_{branch_n}≤G_{branch_ini_n}

Δp_{branch_1}≥0,…,Δp_{branch_n}≥0,Δp_AB≥0

in the formula: delta P_{branch_b_n}Represents the equilibrium pressure drop of the branch line in Pa; s_{AHU_n}Represents the impedance of the terminal equipment AHU and has the unit of Pa/(kg)²/s²)；S_{branch_n}Represents the branch line impedance with the unit of Pa/(kg)²/s²)；S_{main_in-n}Represents the impedance of the water main between two nodes and has the unit of Pa/(kg)²/s²)；S_{main_out_n}Representing the impedance of the backwater main pipe between two nodes and the unit is Pa/(kg)²/s²)；ΔP_ABThe minimum water supply and return pressure difference of the pipe network is expressed in Pa; g_{branch_n}Represents the terminal flow rate in kg/s; delta P_{valve_n}Represents the valve differential pressure in Pa; gamma represents the average dynamic viscosity of the chilled water and is 0.000001308; i represents the water on-off area, and the value is 0.0013; a1 represents the fan coil coefficient, and the value is 27.8889; n1 represents the fan coil coefficient, and the value is 1.8897; ζ represents the local drag coefficient; Δ represents the surface roughness, and the value is 0.0002; d_{branch_n}The pipe diameter of the branch pipe is expressed in m; l is_{branch_n}Represents the length of the branch pipe, and the unit is m; d_{main_in_n}The pipe diameter of the water supply main pipe is shown, and the unit is m; l is_{main_in_n}The length of the water supply main pipe is expressed in m; d_{main_out_n}The pipe diameter of the backwater main pipe is expressed in m; l is_{main_out_n}The length of the backwater main pipe is expressed in m.

in step S3, the economic evaluation criteria of the chilled water system includes initial investment cost and operating cost of the chilled water system, and scrap disposal cost, i.e. residual value, the source of the chilled water system refers to "practical heating air-conditioning design manual (second edition)", for a chilled water system pipe network, equivalent uniform annual cost includes chilled water pump operating electricity cost, pipeline depreciation cost, annual average maintenance cost, the chilled water delivery adopts a variable frequency speed control water pump, and under different load factor conditions, by adjusting the flow rate delivered by the chilled water pump, and delivering the chilled water under the condition of guaranteeing the constant temperature of the delivered water, the operating electricity cost calculation formula of the chilled water pump is as follows:

in the formula, Q_waterCalculating the flow of the circulating water pump according to the flow required by the cold source side; p is the working pressure of the circulating water pump; eta_pEta in the present embodiment, which is the electromechanical efficiency of the water pump_pTaking 0.7; tau is_iThe service time under the ith load rate; c. C_eIs the electricity price;

the objective function of the pipe network optimization design is as follows:

representing the price conversion rate of the current year;

S4, as shown in FIG. 2, analyzing the change rule of the objective function of the pipe network by adopting a suboptimal calculation method: considering different functional building types, inputting boundary calculation parameters; calculating an optimal solution in each pre-defined calculation area by adopting a random walking and optimization area division suboptimal calculation method, taking the minimum value of the optimal solution in each area as a new optimization calculation starting point, performing variable-step-length cyclic iterative optimization calculation again, avoiding the calculation from falling into local optimization to the maximum extent, calculating the optimization results of the pipe network under different working conditions, and analyzing the target function change rule of the pipe network in the optimization design results of the pipe network under different working conditions compared with the traditional design method;

in step S4, the boundary calculation parameters include an indoor control point dry-bulb temperature, an outdoor control point dry-wet-bulb temperature, a total air volume, a fresh air ratio, a cold load, a wet load, a terminal impedance, a required flow of each branch, lengths of a pipe network water supply and return pipe and a branch pipe, pipe diameters of the pipe network water supply and return pipe and the branch pipe, a local resistance coefficient, pipe inner wall roughness of the pipe network water supply and return pipe and the branch pipe, a valve body impedance corresponding to a maximum opening degree of a valve, and a terminal device impedance; the selection of the calculation parameters of each boundary is as follows:

according to the regulations in the public building energy saving design Standard (GB 50189-2005) and the heating Ventilation and air Conditioning design Specification (GB 50019-2003), when the height of the air supply opening is 5m or less, the temperature difference of the supplied air is between 5 degrees and 10 degrees, and when the height of the air supply opening is more than 5m, the temperature difference of the supplied air is more than 10 degrees and less than 15 degrees, as shown in the following table:

table 1 air supply temperature difference and ventilation frequency table of technical air conditioner

TABLE 2 initial calculation parameters Table

is the cluster coefficient; q. q.s₁Is the heat dissipation capacity of the adult male in hour, W; tau is the calculation time and the unit is h; t is the time when the person enters the air conditioning area, and the unit is h; tau-T is the duration time from the time when the personnel enter the air conditioning area to the time when the personnel calculate, and the unit is h; x_τ-TA cold load coefficient for sensible heat dissipation of a human body at the time of tau-T; q. q.s_m,W,pThe minimum fresh air quantity required by each person per hour is expressed in the unit of (m)³V (humans x h)); q. q.s_m,W,bIs the minimum fresh air quantity required per hour per unit building area and has the unit of (m)³/(m²H)); f is the building area of the ventilated room, and the unit is m²。

The step S4 includes:

s4.9.1, if A>A₀Continuing to step S5, if A is<A₀And (5) finishing the calculation to obtain an optimal solution:

X_k＝(x₁,x₂,…,x_n)，i≤x_n≤j，k＝1,2…

S4.9.2, in the embodiment, under the same working condition, a recommended flow velocity method is adopted to design and calculate the pipe diameter distribution form of the pipe network;

the recommended flow rate method is to determine the pipe diameter according to the flow according to the following table:

TABLE 3 flow and caliber corresponding table

S4.9.3, performing optimization calculation and design calculation on the pipe network under the uniform load distribution by respectively using a suboptimal algorithm and a recommended flow velocity algorithm. Through calculation, the annual running cost of the pipe network designed by the recommended flow rate method is 25168.8 yuan, and the initial investment cost is 55238.2 yuan. The annual operation cost of the pipe network designed by the suboptimal algorithm is 1930.9 yuan, the initial investment cost is 100849.1 yuan, and the cost can be saved by 302956.9 yuan after 15 years of operation.

in this embodiment, S5 includes the following steps:

s5.1, substituting the pipe diameter distribution values of various types obtained by design and calculation of the traditional method under uniform load distribution into the working conditions of various loads, calculating annual reduced cost under different operation years, and comparing the result with the traditional design result of various types of load distribution, wherein the traditional design method (such as a recommended flow rate method) has extremely poor adaptability when the load distribution is changed aiming at a certain load distribution type design, and the proportion of the cost saved by comparing the 15-year reduced cost sum with the traditional recommended flow rate method is-0.64 and-1.1 respectively. The ratio of cost saving is-4.6 for the worst adaptability of the ascending load distribution and the descending load distribution.

S5.2, calculating and analyzing frequency distribution statistics of pipe diameters of various pipe sections in the suboptimal solution group output in the whole calculation process under different working conditions;

s5.3, giving up the highest pipe diameter value probability, finding out an area with the highest coincidence degree of the pipe diameter value probabilities of the pipe network under the load distribution, and using the area as a suboptimal solution of the pipe diameter value;

and S5.4, substituting the calculated pipe diameter distribution values of various types into the load working conditions, calculating the annual conversion cost under different operation years, and comparing the result with the traditional design result. It can be known that the adaptability of the pipe network obtained by suboptimal design to different load distributions is different, wherein the adaptability to convex load distribution and uniform load distribution is stronger, and the proportion of the cost saved by comparing the sum of 15-year reduced cost with the traditional recommended flow rate method is 0.49 and 0.54 respectively. The concave load distribution and the incremental load distribution have small adaptability change, and the cost saving ratio is respectively 0.12 and-0.04. The cost saving ratio for the poor adaptability of the decreasing load distribution is-0.88.

Example 2:

taking an office building oriented to east and west of Guangdong as a research object, wherein the office building comprises functional spaces such as public office areas (with high personnel mobility), offices, conference rooms, staff canteens, reporting halls and the like, and the air-conditioning area of the first building is 270m²370m area of air-conditioning area of second floor²370m area of air-conditioning area of third floor²270m area of air-conditioning area of four-floor²Total air conditioning area 1240m²Two air cabinets are arranged on the first floor, three air cabinets are arranged on the second floor, three air cabinets are arranged on the third floor, two air cabinets are arranged on the fourth floor to supply air to an air conditioning area of each floor, and an area of 36m is arranged between the first floor and the fourth floor²The atrium (1).

Because the business particularity of the office building and the use function particularity of each area have large personnel flow on the whole, the number of people entering and leaving the office building in a whole day is continuously changed and unpredictable, the moment-by-moment load of the office building cannot be directly obtained, the random walking method is adopted to carry out random assignment calculation on the load at present, and the working time of the office building in a whole day is 8: and 00-18: 00, calculating a simulation assignment (cold load and wet load) time by time. And calculating the used outdoor temperature and humidity by adopting real-time monitored weather data.

According to field data acquisition, later-stage energy-saving reconstruction calculation and energy-saving potential evaluation are performed on the freezing water pipe network of the central air-conditioning of the building. Firstly, a thermodynamic model of a central air-conditioning chilled water pipe network is constructed according to the actual pipe network topological structure on site and the specific air handling unit condition of the terminal equipment. The method comprises the steps of collecting 8 tail end environment calculation input parameters of environment dry bulb temperature, outdoor environment wet bulb temperature, indoor control point dry bulb temperature, surface cooler chilled water inlet temperature, total air quantity, fresh air ratio, cold load and wet load, tail end impedance, local resistance coefficient of each part of a pipeline, pipe length, pipe inner wall roughness and other pipe network modeling calculation input parameters, and performing optimization calculation by adopting a suboptimal calculation method of random walking and optimization area division.

Fig. 3 reflects a 30-time calculation sub-optimal solution approximation process, and the optimization process is the calculation times in the optimization process. The optimal solution difference of 30 times of calculation is not more than 0.1%, the maximum value of annual conversion cost of the chilled water pipe network is 10.1276 ten thousand yuan, the minimum value is 10.1262 ten thousand yuan, the calculation result is slightly influenced by the initial value of the solution vector, and the method has good convergence and reproducibility.

The distribution of the optimized design pipe network obtained by each load distribution is shown in fig. 7, fig. 8, fig. 9, fig. 10 and fig. 11, the proportion of the cost saved by the traditional design method and the optimized design of each load distribution type to the total cost changes with the operation years is shown in fig. 13, and the specific data is shown in the following table:

proportion table for saving cost in total cost

From the above table, for each load distribution type, the initial investment of the pipe network is large due to the large selection value of the optimized pipe diameter compared with the traditional design method, but the annual operation cost of the pipe network is low, and the proportion of the cost saving of the optimally designed pipe network is increased increasingly along with the increase of the operation years.

And counting the occurrence frequency distribution of the pipe diameters of various pipe sections in the suboptimal solution group output in the whole calculation process of suboptimal calculation, wherein the value probability of the pipe diameters of various pipe sections is shown in fig. 4, fig. 5 and fig. 6. Statistical analysis is performed on pipe network pipe diameter values under different load distributions, the highest pipe diameter value probability is given up, and the area with the highest pipe diameter value probability coincidence degree under each load distribution is found out and used as the suboptimal solution of the pipe diameter value, as shown in fig. 12. Substituting the calculated pipe diameter distribution values of various types into the working conditions of various loads, calculating the annual conversion cost under different operation years, and comparing the result with the traditional design result, wherein the result is shown in fig. 14 and 15. It can be known that the adaptability of the pipe network obtained by suboptimal design to different load distributions is different, wherein the adaptability to convex load distribution and uniform load distribution is stronger, and the proportion of the cost saved by comparing the sum of 15-year reduced cost with the traditional recommended flow rate method is 0.49 and 0.54 respectively. The concave load distribution and the incremental load distribution have small adaptability change, and the cost saving ratio is respectively 0.12 and-0.04. The cost saving ratio for the poor adaptability of the decreasing load distribution is-0.88. It can be known that the adaptability of the pipe network designed by the suboptimal algorithm to different load distributions is greatly increased.

The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and all such changes, modifications, substitutions, combinations, and simplifications are intended to be included in the scope of the present invention.

Claims

1. the large-scale central air-conditioning chilled water pipe network optimization design method based on suboptimal algorithm, is characterized in that, comprises the following steps:

S1. Establish a thermal performance calculation model of the terminal equipment: establish a physical model of the surface cooler, considering the outdoor ambient dry bulb temperature, the outdoor ambient wet bulb temperature, the dry bulb temperature of the indoor control point, the chilled water inlet temperature of the surface cooler, the total air volume, and the fresh air. Ratio, cooling load, and humidity load 8 input parameters, establish a heat-humidity balance equation and divide it into a two-layer iterative cycle to obtain the chilled water flow of the surface cooler, the return temperature of the chilled water of the surface cooler, the temperature difference of the supply air, the wet bulb temperature of the indoor control point, The indoor control point temperature, the air dry bulb temperature at the inlet of the surface cooler, and the air wet bulb temperature at the inlet of the surface cooler are 7 output parameters, and the thermal performance calculation model of the terminal equipment is established;

S2. Establish a hydraulic calculation model of the chilled water pipe network: the output parameters of the terminal impedance and the demand flow of each branch, that is, the output parameters in the thermal performance calculation model of the terminal equipment in step S1, indicate the chilled water flow of the chiller, the supply and return pipes of the pipe network, and the pipe length of the branch pipes. , pipe network supply and return pipe and branch pipe diameter, local resistance coefficient, inner wall roughness of pipe network supply and return pipe and branch pipe, valve body impedance corresponding to the maximum opening of the valve, and impedance of terminal equipment as input parameters. The hydraulic calculation model of the chilled water pipe network is obtained based on the pressure balance of each branch of the network, the principle of flow conservation at each node and the flow law of the series and parallel pipelines;

S3. Select the objective function of pipe network optimization: Under the premise of comprehensively considering the initial investment cost of the central air-conditioning chilled water pipe network, the annual operating cost of the pipe network and the depreciation cost of the pipe network, the annual conversion cost of the pipe network is proposed as the objective function of the pipe network optimization;

S4. Use the sub-optimal calculation method to analyze the change rule of the objective function of the pipe network: consider different functional building types, input the boundary calculation parameters; Calculate the optimal solution in the area, take the minimum value of the optimal solution in each area as the starting point of the new optimization calculation, and re-execute the iterative optimization calculation with variable step size to avoid the calculation falling into the local optimum to the greatest extent, and calculate different working conditions. Based on the optimization results of the pipeline network, the objective function variation rule of the pipeline network optimization design results compared with the traditional design method under different working conditions is analyzed; it includes the following steps:

S4.1. Set the supply and return water and end branch pipe diameters of each section of the pipe network X = (x ₁ , x ₂ ,..., x _n ), n is the number of the pipe network section, n = 1 ~ N, x _n is Pipe network optimization calculation variables, set the total number of variables N, the random walking step length A, and the end control modulus M;

S4.2. Input the impedance of the end of the pipe network, the chilled water flow of each branch surface cooler, the pipe network supply and return pipes and the pipe lengths of the branch pipes, the pipe network supply and return pipes and the branch pipe diameters, the local resistance coefficient, the pipe network The inner wall roughness of the water supply and return pipes and the branch pipes, the valve body impedance corresponding to the maximum opening of the valve, and the calculation parameter information of the impedance of the terminal equipment;

S4.3. Set the optimization objective function F(x) as the annual conversion cost of the pipe network;

S4.4. Set the maximum and minimum flow rates in the pipes corresponding to the pipe diameters of the supply and return water main pipes and the end branch pipes of each section of the pipe network, and take the maximum pipe diameter corresponding to the minimum flow rate in the pipes as the initial starting point for the optimization calculation of each pipe section, X ₀ = (x ₁₀ , x ₂₀ ,...,x _n0 );

S4.5. Taking the optimization calculation starting point X ₀ =(x ₁₀ ,x ₂₀ ,…,x _n0 ) as the center, and with the upper and lower limits of each independent variable as constraints, calculate the optimization area division control modulus, and set the The multi-dimensional optimization independent variable grid is divided into equidistant areas, divided into N optimization calculation areas, and the minimum value of the objective function is calculated in each optimization area;

_S4.6 . Randomly generate a random number rn within a certain range, and obtain a random walking unit direction vector R,

Determine a new optimization starting point X ₁ , X ₁ =(x ₁₁ ,x ₂₁ ,...,x _n1 ), where:

x _1o =(x _max +x _min )/2+A·M·r ₁ /R, x _no =(x _max +x _min )/2+A·M·r _n /R;

S4.7, calculate the tentative objective function value F(X) _temp ; if F(X)≤F(X) _temp then F(X)=F(X) _temp ; x ₁₀ =x ₁ , x ₂₀ =x ₂ , x _n0 = x _n ; the step A is reduced to 0.8A, and the cycle is calculated; if F(X)>F(X) _temp , then continue to step S4.5 until the number of calculation steps reaches the set value;

S4.8. Arrange the calculation results of each area in the order from small to large, take the value of the independent variable corresponding to the minimum objective function in each area as a new optimization starting point, and perform the optimization calculation again;

S4.9. If A>A ₀ , continue to step S5, if A<A ₀ , the calculation ends, and the optimal solution is obtained:

X _k =(x ₁ ,x ₂ ,...,x _n ), i≤x _n ≤j, k=1,2...

The search range of the variable is (x _n0 -A, x _n0 +A). As the value of A decreases, the range of the calculation search is gradually reduced. The more the number of loop calculations, the closer the random solution vector is to the theoretical optimal solution. , the distribution is more concentrated, according to its distribution characteristics, the statistical optimal solution is obtained, and the analysis of the change law of the objective function of the pipe network under different working conditions compared with the traditional design method is completed;

S5. Statistical analysis of the sub-optimal solution group of the optimization calculation: Calculate and analyze the frequency distribution statistics of the pipe diameters of various pipe sections in the sub-optimal solution group output by different working conditions in the whole calculation process, and obtain the pipe network pipe diameter that is generally suitable for each load. The distribution form is compared with the pipe diameter distribution obtained by the traditional design method under the uniform load distribution to observe the adaptability of the optimized design and the traditional design to different load changes;

S6. According to the statistical law and random behavior of the obtained solution group analysis, the reference range of the pipe diameter of each pipe section under different load distribution forms and load rates is obtained. Guidance and scientific basis.

2. the large-scale central air-conditioning refrigerated water pipe network optimization design method based on suboptimal algorithm according to claim 1, is characterized in that, in step S1, first off-line calculation is carried out to single terminal equipment thermal performance calculation model, with inlet air temperature, The 6 variables of inlet relative humidity, outlet temperature, outlet relative humidity, air volume, and AHU water flow constitute a uniform calculation grid. Each variable has 10 horizontal calculation values, which are completed through offline calculation; all data are evaluated for bad values. Screen, remove bad values, create a database of terminal equipment operating characteristics, and directly perform interpolation calculations according to the inverse distance weight method interpolation method to reduce the number of optimization calculations.

3. the large-scale central air-conditioning chilled water pipe network optimization design method based on suboptimal algorithm according to claim 1, is characterized in that, in step S1, under certain surface cooler structural parameters, for a certain type of surface cooler As far as the air cooler is concerned, any operating condition parameter satisfies the following three relationships: ① the heat exchange efficiency coefficient ε _r1 in the air treatment process is equal to the heat exchange efficiency coefficient ε _j1 that the surface cooler structure can achieve during operation, ② air The contact coefficient ε _r2 in the treatment process is equal to the contact coefficient ε _j2 that the surface cooler structure can achieve during operation. ③ The heat exchange of air during the air treatment process is equal in quantity to the heat exchange of chilled water Q; the surface cooler The internal parameters have the following relationships:

The heat exchange coefficient _ε _r1 , the contact coefficient _ε _r2 and the air exchange heat Q _air in the process of constraining the surface cooler to process air The heat exchange Q _water is equal, and the dry bulb temperature t ₁ at the air side inlet of the surface cooler, the enthalpy value i ₁ of the surface cooler inlet air, the air flow G at the air side inlet of the surface cooler, and the inlet cold water temperature t _w1 at the cold water side of the surface cooler In order to calculate the input variables, the output dry bulb temperature t ₂ at the air side outlet of the surface cooler, the air enthalpy value i ₂ at the outlet of the surface cooler, and the cold water temperature t _w2 at the outlet of the cold water side of the surface cooler are calculated by modeling:

In the formula: β is the number of heat transfer units; Ge, me, and ne are the empirical coefficients for solving the contact coefficient, which are obtained from experiments; K is the heat transfer coefficient of the surface cooler in the air treatment process; γ is the water equivalent of air and chilled water V _y is the windward area of the surface cooler; ξ is the moisture separation coefficient of the treatment process; K _s is the heat transfer coefficient under wet conditions; t ₁ is the dry bulb temperature of the air side inlet of the surface cooler; i ₁ is the inlet of the surface cooler Air enthalpy; t _w1 is the inlet cold water temperature of the cold water side of the surface cooler; t ₂ is the dry bulb temperature of the air side outlet of the surface cooler; i ₂ is the air enthalpy value of the surface cooler outlet; t _w2 is the cold water outlet of the surface cooler temperature; F is the heat exchange area of the surface cooler; c _p is the average specific heat capacity of the air during the treatment process; G is the air flow rate during the air cooler treatment process; W is the chilled water flow rate during the treatment process; ω is the air flow rate during the treatment process. The flow rate of chilled water; c is the average specific heat capacity of the chilled water during the treatment process; t ₃ is the ideal state air outlet dry bulb temperature of the surface cooler in the air treatment process; A, B are the coefficients obtained from the experiment; m, n are obtained from the experiment index.

4. the large-scale central air-conditioning chilled water pipe network optimization design method based on suboptimal algorithm according to claim 1, is characterized in that, in step S1, according to input parameter, establish heat and humidity balance equation and divide into two layers of iterative cycle to obtain 7 output parameters ,details as follows:

In the formula: G is the air flow in the process of air treatment by the surface cooler; Q is the heat exchange in the air treatment process; ic is the air enthalpy value at the mixing point; _dc is the air moisture content at the mixing point; _t _L is the surface cooling outlet air temperature;

is the relative humidity of the air at the outlet of the surface cooler; i _w is the enthalpy value of the outdoor air, m _new is the fresh air ratio; i _N is the enthalpy value of the indoor air, d _w is the moisture content of the outdoor air; d _N is the moisture content of the indoor air; type is the table Type of cooler; t _c is the air temperature at the mixing point;

is the air relative humidity at the mixing point; t ₂ is the dry bulb temperature at the air side outlet of the surface cooler;

is the relative humidity of the air at the air side outlet of the surface cooler; i _L is the enthalpy value of the air at the outlet of the surface cooler; d _L is the moisture content of the air at the outlet of the surface cooler.

5. the large-scale central air-conditioning chilled water pipe network optimization design method based on suboptimal algorithm according to claim 1, is characterized in that, step S1 comprises the following steps:

S1.1. Input the dry bulb temperature of the terminal indoor control point under the simulated working conditions, the dry and wet bulb temperature of the outdoor environment, the total air volume, the fresh air ratio, the cooling load, the wet load and the chilled water inlet temperature of the surface cooler;

S1.2. Set the indoor moisture content and determine the indoor state point parameters;

S1.3. Calculate the air state at the mixing point and the air state at the air supply point. The air state at the air supply point includes the air temperature at the air supply point and the air moisture content at the air supply point;

S1.4. Set the initial value of the chilled water flow in the fan bypass pipe;

S1.5. Use the physical model of the surface cooler to solve the state of the air at the outlet of the surface cooler, including the temperature of the air at the outlet of the surface cooler and the moisture content of the air at the outlet of the surface cooler;

S1.6, determine whether the air temperature at the outlet of the surface cooler is equal to the air temperature at the air supply point, if so, go to step S1.7; if not, go to step S1.4;

S1.7, determine whether the moisture content of the air at the outlet of the surface cooler is equal to the moisture content of the air at the air supply point, if yes, go to step S1.8, if no, go to step S1.2;

S1.8. Output data output parameters: chiller chilled water flow, surface chiller chilled water return temperature, supply air temperature difference, indoor control point wet bulb temperature, indoor control point temperature, air dry bulb temperature at the inlet of the surface cooler, The air wet bulb temperature at the inlet of the surface cooler.

6. the large-scale central air-conditioning chilled water pipe network optimization design method based on suboptimal algorithm according to claim 1, is characterized in that, in step S2, pipeline resistance coefficient λ and impedance have following relationship:

Calculation of λ: relative roughness is ε=2*Δ/D, Reynolds number Re=v*D/γ, A=59.7/ε ^8/7 , B=(665-765*Log(ε))/ε, When Re=0, the resistance coefficient along the pipeline is: λ=0; when 0<Re<=3000, the resistance coefficient along the pipeline is: λ=64/Re; when Re>3000, and Re<=A , the resistance coefficient along the pipeline is: λ=0.3164/Re ^0.25 ; when A<Re, and Re<=B, the resistance coefficient along the pipeline is: λ=1/(-1.8*Log((Δ/3.7 *D)) ^1.11 +6.8/Re)/Log(10)) ² ; when B<Re, the resistance coefficient along the pipeline is: λ=1/(2*Log(3.7*D/Δ)) ² ;

Therefore, the impedance of the branch pipeline and the main water supply and return pipeline is as follows:

The end device impedance is as follows:

In the hydraulic calculation model of the chilled water pipe network, the pipe length, pipe diameter, inner wall roughness, local resistance coefficient, valve impedance, terminal equipment impedance, flow rate of each terminal and each branch of the water supply main pipe, return water main pipe and terminal branch of the pipe network The pressure drop is related as follows:

The constraints of the hydraulic calculation model of the cold water pipe network are as follows:

G _{branch_1} ≤G _{branch_ini_1} ,…,G _{branch_n} ≤G _{branch_ini_n}

S _{valve-temp_1 ≥S} _{valve-temp-min_1} ,…,S _{valve_temp_n} _{≥S valve_temp_min_n}

Δp _{branch_1} ≥0,…,Δp _{branch_n} ≥0,Δp _AB ≥0

where:

Represents the equilibrium pressure drop of the branch line;

Indicates the impedance of the end device AHU;

represents the branch line impedance;

represents the water supply mains impedance between two nodes;

represents the return mains impedance between two nodes;

Indicates the terminal flow;

ΔP _{valve_n} represents the valve pressure difference; γ represents the average dynamic viscosity of chilled water; I represents the water on-off area; n1 represents the fan coil coefficient; ζ represents the local resistance coefficient; Δ represents the surface roughness.

7. the large-scale central air-conditioning chilled water pipe network optimization design method based on suboptimal algorithm according to claim 1, is characterized in that, in step S3, the economical evaluation standard of chilled water system comprises the initial investment cost and the operation of chilled water system Expenses and disposal fees are the residual value. For the chilled water system pipeline network, the equivalent and average annual costs include the electricity cost for the operation of the chilled water pump, the depreciation cost of the pipeline, the average annual depreciation cost, and the average annual maintenance cost. The chilled water transmission adopts frequency conversion speed regulation The water pump, under the condition of different load rates, adjusts the flow rate delivered by the chilled water pump, and at the same time delivers chilled water under the condition that the water delivery temperature remains unchanged, the calculation formula of the operating electricity fee of the chilled water pump is as follows:

In the formula, Q _water is the flow rate of the circulating water pump, which is calculated according to the demand flow of the cold source side; P is the working pressure of the circulating water pump; η _p is the electromechanical efficiency of the water pump, and its value ranges from 0.5 to 0.7; τ _i is the i-th load rate the usage time under the following conditions; c _e is the electricity price;

The objective function of pipeline network optimization design is:

In the formula: C _h is the capital recovery rate; C _ch is the initial investment cost of the pipeline network, including planning cost, design cost and construction cost;

Indicates the price conversion rate of the current year;

Represents the price conversion rate in year j; C _yj represents the annual operating cost in year _j ; ij represents the inflation in year j, that is, the rate of interest rate increase, the rate of interest rate increase = j annual rate/(j-1) annual interest rate; C _Wj represents the The annual maintenance fee of the jth year converted from the base year; S represents the disposal fee or residual value; I represents the interest; n represents the operating year.

8. The optimal design method for large-scale central air-conditioning chilled water pipe network based on suboptimal algorithm according to claim 1, wherein in step S4, the boundary calculation parameters include indoor control point dry bulb temperature, outdoor control point dry and wet Bulb temperature, total air volume, fresh air ratio, cooling load, wet load, end impedance, demand flow of each branch, pipe network supply and return pipes and branch pipe lengths, pipe network supply and return pipes and branch pipe diameters, local resistance coefficient, the inner wall roughness of the water supply and return pipes of the pipe network and the branch pipes, the valve body impedance corresponding to the maximum opening of the valve, and the impedance of the terminal equipment; the selection of the calculation parameters of each boundary is as follows:

When the height of the air outlet is less than or equal to 5m, the temperature difference of the air supply is between 5 degrees and 10 degrees. When the height of the air outlet is greater than 5m, the temperature difference of the air supply is greater than 10 degrees and less than 15 degrees;

The indoor and outdoor calculation parameters of the comfort air conditioner are as follows:

The indoor dry bulb temperature is 24°C, the indoor relative humidity should be maintained between 40% and 65%, the outdoor dry bulb temperature is 33.5°C, the outdoor wet bulb temperature is 27.7°C, the fresh air ratio is 0.1, and the chilled water inlet temperature is 7 ℃; among them, under the premise of determining the number of indoor personnel, working hours, personnel working status and other parameters, the calculation formulas of cooling load, humidity load and air volume are as follows:

In the formula: Q _τ is the cooling load at the calculation time formed by the sensible heat dissipation of the human body, W; q _{m, W, min} is the fresh air volume; D_τ is the human body moisture dissipation at the calculation time; Q_τ is the latent heat formed by the human body moisture dissipation at the calculation time Cooling load; n is the total number of people in the air-conditioning area at the time of calculation;

is the cluster coefficient; q ₁ is the hourly sensible heat dissipation of an adult man, W; τ is the calculation time; T is the time when the person enters the air-conditioning area; τ-T is the time from the moment when the person enters the air-conditioning area to the calculation time Duration; X _τ-T is the cooling load coefficient of the sensible heat dissipation of the human body at the time of τ-T; q _{m, W, p} is the minimum fresh air volume per person per hour; q _{m, W, b} is the unit building area per hour The minimum required fresh air volume; F is the building area of the ventilation room.

9. the large-scale central air-conditioning chilled water pipe network optimization design method based on suboptimal algorithm according to claim 1, is characterized in that, in step S5, for suboptimal calculation gained solution group probability analysis statistical method steps are as follows:

S5.1. Use the sub-optimal algorithm of random walking to carry out the optimal design calculation for the five different load distribution forms of the pipe network respectively, and obtain the optimal solution of the optimal design of the pipe diameter distribution of each type of the pipe network, and compare it with the same load parameter conditions. The pipe diameter distribution calculated by the traditional design is used for comparison, and the difference between the initial investment and the annual operating cost of the optimized design pipe network pipe diameter within the operating life compared with the traditional design method is analyzed;

S5.2. Output the suboptimal calculation solution group of each parameter in the optimization calculation of the pipeline network under each working condition, and output the optimization step size, the valve opening of each branch, the objective function, the pressure drop of each branch, and the valve during the optimization calculation process. Pressure drop, pressure drop of supply and return water main pipes, water supply main pipe diameter, return water main pipe diameter, end branch pipe diameter, statistics Probability distribution trend of pipe diameter value of water main pipe section;

S5.3. Statistically analyze the area with the highest probability of coincidence of the value of the supply and return water main pipe and the end branch pipe diameter in the solution group of five different load distribution forms, as the sub-optimal solution of the pipe diameter value;

S5.4. Output the suboptimal solution of the pipe diameter of each type of pipe section obtained in step S5.3, and re-substitute it into five different load distribution conditions, respectively, and the pipe diameter distribution obtained by using the traditional design method for each condition under different operating years The objective function value of the suboptimal solution is compared, and the load adaptability of the pipe diameter distribution obtained by the suboptimal solution is analyzed.