Method and system for analyzing time-delay effect of central air conditioner participating in demand response

Abstract

The invention provides a central air-conditioning participation demand response time-lag effect analysis method, which comprises the following steps of: constructing a simplified time-lag effect calculation model according to a building body shape and an air-conditioning system design specification; an actual building case is selected, and the time-delay effect calculation model is further verified; on the basis of the verified case, an air conditioning system simulation platform is built, external data and built-in data are read, and the external data and the built-in data are sorted and stored in a working area; and a demand response operation scene is simulated on the air conditioning system simulation platform, and the influence of the time-lag effect on the cooling capacity and the thermal comfort of the tail end of the air conditioning system is evaluated by comparing simulation data with external data and built-in data. According to the method, through deep analysis of the time-lag effect, the operation strategy of the air conditioning system can be optimized, and the regulation and control effect and precision of the air conditioning system in demand response are improved.

Description

Technical Field

[0001] The present invention relates to the fields of heating, gas supply, ventilation and air conditioning engineering, and in particular to a method and system for analyzing the time lag effect of central air conditioning participating in demand response. Background Art

[0002] In recent years, with the rapid development of my country's economy, the demand for electricity has continued to increase. The "Guiding Opinions on Energy Work in 2021" issued by the National Energy Administration pointed out that in order to ensure the security of energy supply, optimize the energy structure, and promote energy consumption reform, the proportion of electricity in terminal energy consumption should strive to reach about 28%. To this end, my country has proposed the "dual carbon" goal, requiring various industries to implement further emission reduction policies, especially to optimize and regulate the power industry, in order to achieve efficient use of energy and low-carbon transformation.

[0003] Building energy consumption accounts for an important proportion of electricity demand, among which air conditioning load accounts for the largest proportion. Especially during the peak period of electricity consumption in summer, the pressure caused by air conditioning load on the power grid is particularly prominent. Statistics show that during the peak period of summer, air conditioning load accounts for 30% to 40% of the peak load of the power grid, and even reaches 50% in some cities. Therefore, by regulating the air conditioning system to participate in demand response, the peak load of the power grid can be effectively reduced and the pressure on the power grid can be relieved.

[0004] Grid demand response refers to balancing the supply and demand of electricity by incentivizing and guiding users to adjust their electricity consumption behavior and participate in power dispatch when the supply and demand of electricity is tight. Demand response is characterized by randomness, suddenness, and short duration. As a typical large time-delay system, the air-conditioning system will experience delays in regulation and attenuation of regulation when participating in grid demand response. The time-delay effect refers to the delay in the system transmitting materials or information to the controlled object, which causes the air-conditioning system to experience a decrease in cooling capacity and room temperature fluctuations during the demand response period, affecting the regulation effect.

[0005] At present, many studies have explored the participation of air conditioning systems in demand response. For example, some scholars have proposed a control strategy for building air conditioning systems in demand response, which achieves load peak shaving and valley filling by optimizing the start and stop sequence and adjustment parameters of air conditioning equipment. However, existing studies mostly focus on the optimization of control strategies, lacking in-depth analysis and research on time lag effects. How to accurately describe and quantify the impact of time lag effects on the participation of air conditioning systems in demand response is an important topic of current research. Summary of the invention

[0006] In order to overcome the above-mentioned deficiencies of the prior art, the present invention discloses a method for analyzing the time lag effect of central air conditioning participating in demand response.

[0007] The technical solution provided by the present invention is: a method for analyzing the time lag effect of central air conditioning participating in demand response, comprising the following steps:

[0008] According to the building shape and air conditioning system design specifications, a simplified time lag effect calculation model is constructed;

[0009] Select actual building cases to further verify the time-lag effect calculation model;

[0010] Based on the verified cases, build an air conditioning system simulation platform, read external data and built-in data, organize and save the external data and built-in data in the workspace;

[0011] The demand response operation scenario is simulated on the air-conditioning system simulation platform, and the impact of the time lag effect on the cooling capacity and thermal comfort of the air-conditioning system terminal is evaluated by comparing the simulated data with the external data and the built-in data.

[0012] Preferably, the construction of a simplified time-lag effect calculation model specifically involves a simplified calculation of the piping layout of the chilled water system, taking into account factors such as the layout of terminal equipment, the proportion of building air-conditioning area, and the location of the refrigeration room.

[0013] Further preferably, the case verification not only includes the accuracy verification of the time-lag model, but also covers the quantitative comparison of the pipeline temperature rise and the terminal cooling attenuation in actual operation, ensuring that the model prediction is highly consistent with the field data, and combines the calculation results of the time-lag effect calculation model to analyze the composition and characteristics of the delay and temperature rise in the time-lag effect, and discuss the accuracy of the calculation.

[0014] Further preferably, the air-conditioning system platform is built, a platform is built that can describe the changes in parameters of various parts of the air-conditioning system during actual operation, and modules that consider time-lag effects are added to the platform in a targeted manner for comparative research, and the influence of time-lag effects on the air-conditioning system is explored by comparing the changes in parameters of various parts of the air-conditioning system platform after considering the time-lag effects.

[0015] Further preferably, the air conditioning system platform construction includes: a cold station model construction unit, a water pump model construction unit, a water valve control model construction unit, a terminal model construction unit, a room model construction unit, a water network model construction unit and a real lag model construction unit;

[0016] Among them, the chiller in the cold station model construction unit cools the refrigerant through the refrigeration system, and then the water pump sends the low-temperature refrigerant to the equipment or terminal. After heat exchange, the heat is taken away, the temperature of the refrigerant rises, and finally flows back to the water tank; the energy utilization efficiency of the above process can be evaluated by COP. The algorithm of the chiller COP is shown in formula (1). The cold station model uses the relevant conclusions of Gordon JM and is applicable to centrifugal chillers and screw chillers. The model is shown in formulas (2)-(7):

[0017]

[0018] Where:

[0019] COP——Coefficient of refrigeration performance of refrigeration machine; Q e ——Refrigeration capacity of refrigeration machine, kW; W chiller ——Energy consumption of cooling machine, kW; Q c ——heat rejection on the condenser side, kW; T c ——Condensation temperature of condenser, K; T e ——Evaporation temperature of evaporator, K; C c ——Heat transfer coefficient of condenser, kJ / K; C e ——Heat transfer coefficient of evaporator, kJ / K; T ew,out ——chilled water supply temperature, K;

[0020]

[0021] T cw,in ——Condensate return temperature, K;

[0022] q e =a 0 +a 1 ×R q +a 2 ×R q 2 +a 3 ×R q 3 (4)

[0023] q c =a 4 +a 5 ×R q +a 6 ×R q 2 +a 7 ×R q 3 (5)

[0024] Where:

[0025] q e ——Irreversible loss on the evaporator side; q c ——Irreversible loss on the condenser side; R q is the load factor, %;

[0026] where a 1 , a 2 , a 3 , a 4 , a 5 , a6 , a 7 The coefficients of different chillers are different. The coefficient algorithm of the screw chiller selected in this model is shown in the following formula (6):

[0027]

[0028]

[0029] Where:

[0030] G w ——Chilled water flow, m 3 / h; G ew ——Chilled water flow, m 3 / h;

[0031] The water pump model in the water pump model construction unit has two modes: fixed frequency and variable frequency. When simulating fixed frequency operation, the water pump model is shown in equations (7)-(8):

[0032] H=k 1 ×G pump 2 +k 2 ×G pump +k 3 (7)

[0033] Where:

[0034] H——water pump head, kPa; G pump ——Water pump flow, m 3 / h;k 1 ——quadratic coefficient of pump head characteristic curve; k 2 ——primary coefficient of pump head characteristic curve; k 3 ——Zero-order coefficient of pump head characteristic curve;

[0035]

[0036] Where:

[0037] η 0 ——Efficiency of water pump, %; k 4 ——quadratic coefficient of pump efficiency characteristic curve; k 5 ——primary coefficient of water pump efficiency characteristic curve; k 6 ——Zero-order coefficient of water pump efficiency characteristic curve;

[0038] The water valve at the end of the model has the function of following the room temperature adjustment, and the corresponding water pump also needs to operate with variable frequency. When simulating variable frequency operation, the water pump model is shown in equations (9) to (10):

[0039]

[0040]

[0041] Where:

[0042] N 0 ——Design speed of water pump, r / min; N 1 ——Speed ​​of the water pump when running with variable frequency, r / min;

[0043] In the water valve control model construction unit, the regulating valve is an on-off regulating valve, that is, it can only control the branch flow to 100% or 0% of the full load state. The indoor set temperature ± temperature control value is the temperature interval. When the room temperature is higher than the maximum value of the temperature interval, the terminal valve is fully open. When the room temperature is lower than the minimum value of the temperature interval, the valve is closed. When the room temperature is within the set temperature range, the valve state is consistent with the previous moment.

[0044] The resistance coefficient calculation method of the water valve is shown in the following formula (11):

[0045]

[0046] Where:

[0047] ζ——Resistance coefficient when the valve is fully open, kPa / (L / s) 2 ; ΔP——Design pressure drop of the branch when the valve is fully open, kPa; G branch ——branch design flow, L / s;

[0048] When the valve is closed, the end flow is close to 0, and the valve resistance can be regarded as infinite;

[0049] The valve opening judgment model is shown in formula (12):

[0050]

[0051] Where:

[0052] v i ——valve opening at time i, %; v i-1 ——valve opening at the previous moment before moment i, %; t ri ——Room temperature at time i, °C; t set_up ——Upper limit of room temperature range, ℃; t set_down ——Lower limit of room temperature range, ℃;

[0053] The above formula is the default judgment logic of the water valve. When performing demand response in the future, the judgment logic of the water valve status will be modified according to different scenario requirements;

[0054] The equipment selected in the terminal model construction unit is a fan coil unit, which is composed of a fan, a motor, and a coil unit. The fluid passing through the coil unit exchanges heat with the air, causing the temperature and humidity of the air to change, thereby achieving the purpose of air conditioning.

[0055] The surface cooler of the fan coil unit cools and dehumidifies the air through cold water. The heat exchange model of the water side and the air side of the fan coil unit is shown in formula (13):

[0056] G a ×(h a1 -h a2 )=G W ×C W (t w2 -t w1 ) (13)

[0057] Where:

[0058] G a ——Terminal air supply volume, m 3 / s;h a1 ——Enthalpy of air at the fan coil inlet, kJ / kg; h a2 ——Enthalpy of air at fan coil outlet, kJ / kg; t w1 ——Fan coil water supply temperature, °C; t w2 ——Fan coil unit return water temperature, °C;

[0059] The contact coefficient that can be achieved by the surface cooler should meet the contact coefficient required by the air treatment process, see formula (14) ~ (15):

[0060]

[0061] Where:

[0062] E th ——Total heat exchange efficiency, %; x, y——coefficients measured for fan coil units; t al ——Dry bulb temperature of air at the inlet of fan coil unit, °C; t a2 ——Dry bulb temperature of air at the fan coil outlet, °C;

[0063]

[0064] Where:

[0065] E g ——General heat exchange efficiency, %; λ 1 ——Heat exchange coefficient of coil outer surface, kW / (m 2 ·℃); γ——rib pass coefficient; n 3 ——row number; v y ——Face wind speed of coil, m / s; Cp ——Specific heat capacity of air at constant pressure, J / kg·℃; ρ a ——Air density, kg / m 3 ;t s1 ——Wet bulb temperature at the fan coil outlet, °C; t s2 ——Wet bulb temperature at the inlet of the fan coil unit, °C;

[0066] The room model construction unit uses the state space method. During the solution process, the object with uneven internal temperature field is divided into multiple temperature nodes, and the object with uniform temperature space is converted into one node. The node temperature changes continuously over time. The room model takes into account the coupling between the air conditioning terminal and the building room. The building thermal characteristic parameters exported by the DeST software and the basic room temperature of each room are used as the data basis for the room enclosure structure model. The hourly temperature of the room is calculated in combination with the air supply volume and air supply temperature at the terminal.

[0067]

[0068] q=C p ×ρ a ×G a ×(t a -t r ) (17)

[0069]

[0070] Where:

[0071] t r ——Room temperature, °C; t bt ——Basic room temperature, °C; basic room temperature is the temperature in the room without using air conditioning, reflecting the room temperature state in a natural ventilation environment; ——Thermal characteristic coefficient of a room, which is the thermal reaction coefficient of the outdoor temperature on the room; q——Cooling capacity of a room, W; C p ——Specific heat capacity of air at constant pressure, J / kg·℃; ρ a ——Air density, kg / m 3 ; G a ——Terminal air supply volume, m 3 / s;t a ——Terminal supply air temperature, ℃.

[0072] Further preferably, the calculation process of the air conditioning system platform in step S3 is mainly divided into four steps: external data reading, program internal data reading, program calculation, and finally outputting the calculation results. Before calculation, it is necessary to set meteorological parameters and establish a room model on DeST, and then export data from DeST;

[0073] The external data are the building environment information read from DeST, including building envelope parameters, basic room temperature of each room in the building, outdoor temperature and humidity, and the resistance coefficient of each section of the simplified water network calculated according to the air conditioning water system;

[0074] Internal data refers to the data directly input into the Matlab editor, which mainly includes the information of each unit and pipeline of the air conditioning system;

[0075] The program calculation process is calculated in the order of cooling transfer. The calculation within the program is based on the initial state of the air-conditioning system and the room. A calculation is performed at each moment (the time interval is set by yourself). The calculation content includes the parameters of the chiller, water pump, water valve, terminal, room, and cooling tower. Then, according to the time interval, the outdoor meteorological parameters within the time interval are combined with the calculation results of the previous moment to calculate the parameters of each part at this moment. Finally, the parameter information of each device in each iteration process is recorded. After the iteration is completed, the data is sorted and saved in the workspace.

[0076] Further preferably, in step S4, a time lag effect is introduced during the demand response period, and delay and temperature rise parameters are introduced, that is, a temperature rise and delay module is added to the program to simulate the influence of the time lag effect on the performance of the air-conditioning terminal, and the water pump continues to work to maintain water circulation, so that the terminal can use the remaining cold capacity in the pipeline to maintain cooling. After the demand response is over, the refrigeration equipment quickly resumes operation, and in the process from the restart of the equipment to the re-supply of cooling at the terminal;

[0077] When the temperature rise of the water pump remains unchanged, the change of the terminal temperature rise value is determined by the chilled water pipe. The longer the chilled water pipe, the greater the terminal temperature rise value. The chilled water temperature rise at the same terminal is the same at any time. The algorithm of chilled water temperature rise in the time-lag model is shown in formula (19):

[0078]

[0079] Where:

[0080] ——water inlet temperature at the nth terminal, °C; t chiller,out ——Chiller outlet water temperature, °C; Δt n ——Total temperature rise at the nth end, °C;

[0081] The change of the terminal delay value is determined by the chilled water pipe. The longer the chilled water pipe, the larger the terminal delay value. The transmission delay caused by the time lag effect will make the terminal water temperature change later than the chiller action time. The delay from the chiller to the terminal is u. If the chiller stops at time i, the chiller temperature change it generates will be transmitted to the terminal after a time of u, as shown in formula (20):

[0082] terminal(i)=chiller(iu) (20)

[0083] Where:

[0084] terminal(i)——the state of the terminal at time i; chiller(iu)——the state of the chiller at time iu;

[0085] After considering the temperature rise and delay, the water temperature at a specific time at the end is calculated as shown in formula (21):

[0086]

[0087] Where:

[0088] t terminal(i),wl,n ——the inlet water temperature at the nth end time i, °C;

[0089] t chiller(i-u),out ——Water outlet temperature of the refrigeration machine at time iu, ℃.

[0090] It is further preferred that the influence of residual cooling is considered in the time lag model during the demand response period. When using chilled water residual cooling for cooling, the cooling capacity of residual cooling is limited due to the closure of the chiller. The water temperature will gradually rise when the chilled water circulates in the pipeline. In order to explore the limit of residual cooling, the measured data of the terminal fan coil sample is required as a basis. According to the thermal performance data of the traditional fan coil unit, the mathematical method of multiple regression is used to obtain the calculation formula of the total heat cooling capacity and sensible heat cooling capacity of the fan coil unit. The total heat cooling capacity algorithm is shown in formula (22), and the sensible heat cooling capacity algorithm is shown in formula (23):

[0091]

[0092] Where:

[0093] Q t ——Total heating and cooling capacity of the coil in actual state, kW; Q t,0 ——Coil design total heating and cooling capacity, kW;

[0094] Q s ——Sensible heat and cooling capacity of the coil in actual state, kW; Q s,0 ——Design sensible heat and cooling capacity of coil, kW; ——Air inlet dry bulb temperature of fan coil under actual working conditions, °C; t a,s1 ——Air inlet wet bulb temperature of fan coil under actual working conditions, °C; t w1 ——Cold water inlet temperature of fan coil under actual working conditions, °C; G w ——Water volume of fan coil under actual working conditions, m 3 / s; G w0——Water volume of fan coil under design conditions, m 3 / s; G a ——Air volume of fan coil unit under actual working conditions, m 3 / s; G a0 ——Air volume of fan coil under design conditions, m 3 / s;

[0095] From equations (22) and (23), it can be seen that when the water volume and air volume remain unchanged, the difference between the indoor temperature and the chilled water inlet temperature is proportional to the coil cooling capacity. As the coil inlet temperature rises, the terminal cooling capacity will gradually decrease. When the water temperature is close to the room wet bulb temperature, the coil sensible cooling capacity approaches 0; when the water temperature is close to the room dry bulb temperature, the coil total cooling capacity approaches 0. When the chiller is shut down and the residual cold in the pipeline is used for cooling, the cooling capacity of the terminal coil gradually decreases as the water temperature rises. When the chilled water temperature is equal to the indoor temperature, the coil cannot output cooling capacity, and the residual cold in the chilled water system has been used up.

[0096] According to another aspect of the present invention, there is also provided a system for analyzing time lag effects of central air conditioning participating in demand response, comprising:

[0097] Simplified time-lag effect calculation model construction unit, used to analyze the time-lag effect of air-conditioning system and provide core theoretical support for subsequent analysis;

[0098] The time-lag effect calculation model verification unit is used to further verify the time-lag effect calculation model by selecting actual building cases;

[0099] The air conditioning system simulation platform construction unit builds the simulation platform based on the verified cases, reads external data and built-in data, and organizes and saves the data in the workspace;

[0100] The time-lag effect module building unit of the simulation platform simulates the demand response operation scenario on the simulation platform, simulates the operation status of the air-conditioning system in the demand response, and evaluates the impact of the time-lag effect on the terminal cooling capacity and thermal comfort of the air-conditioning system by comparing the simulation data with external data and built-in data.

[0101] Preferably, the air conditioning system simulation platform construction unit is established on Matlab.

[0102] The beneficial effects of the present invention are:

[0103] The present invention plays a very important role in the field of electricity. It can not only greatly improve the work efficiency of electric workers, but also ensure the safety and reliability of their work. In order to improve the control effect and accuracy of the air-conditioning system in demand response, firstly, a time-lag effect calculation model is established based on the building shape and the design specifications of the air-conditioning system, so as to accurately analyze the time-lag effect of the air-conditioning system. By simplifying the calculation model, the time-lag value of the chilled water system can be quickly determined, thereby providing reliable data support for demand response; secondly, the model is verified by using actual building cases to ensure the accuracy of the calculation results. The verification process combines actual engineering experience to ensure the reliability and operability of the model, laying a solid foundation for subsequent demand response analysis; then, an air-conditioning system simulation platform is built in the Matlab environment, integrating demand response and time-lag effect simulation functions. Through this platform, the operation of the air-conditioning system in different demand response scenarios can be simulated, and the influence of the time-lag effect on the cooling capacity and indoor thermal environment can be analyzed in detail; finally, the influence of the time-lag effect on the participation of the air-conditioning system in demand response is evaluated according to the test results, and optimization measures and suggestions are proposed. Through the in-depth analysis of the time-lag effect, it can help optimize the operation strategy of the air-conditioning system and improve its control effect and accuracy in demand response. BRIEF DESCRIPTION OF THE DRAWINGS

[0104] Figure 1 is a flow chart of the present invention;

[0105] Figure 2 It is a composition diagram of the air conditioning system simulation platform of the present invention;

[0106] Figure 3 The calculation flow chart of the air conditioning system simulation platform of the present invention;

[0107] Figure 4 This is a flow chart of the air conditioning system participating in demand response of the present invention. DETAILED DESCRIPTION

[0108] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0109] The present invention provides a method for responding to low-carbon demand of a power system based on carbon emission flow, referring to Figure 1 As shown, the following steps are included:

[0110] S1: Construct a simplified time-lag effect calculation model based on the building shape and air-conditioning system design specifications;

[0111] In step S1, the time lag value of the air conditioning system can usually be deduced by the air conditioning operation management personnel based on engineering experience and historical operation data of the air conditioning system. However, in actual situations, not all air conditioning systems have corresponding historical operation data and not all professionals have sufficient engineering experience. Therefore, a model that can accurately reflect the time lag phenomenon in the central air conditioning system is established, and the causes and influencing factors of the time lag effect are analyzed by establishing a theoretical model, which is helpful for the actual operation management of the air conditioning system.

[0112] The most intuitive way to distinguish different buildings is to distinguish them based on their shapes. Buildings with the same functions and similar shapes will have similar air conditioning pipeline layouts, so their time lag values ​​will not be too different. Simplified calculations of the scale of air conditioning chilled water system pipelines based on building shapes can quickly calculate the time lag effect of the air conditioning system in a specific building. The building shape limits the scale of the air conditioning water system pipelines. The larger the scale of the air conditioning water system pipelines, the stronger the time lag effect. A stronger time lag effect will affect the air conditioning terminal, causing the delay time of cooling to become longer and the temperature rise to become larger.

[0113] Select actual building cases to further verify the time-lag effect calculation model;

[0114] The influence of the time lag effect is mainly manifested in the time delay and temperature rise at the end, and both the time delay and temperature rise are based on the pipe calculation, so the accuracy of the pipe calculation is very important. This paper will use several sets of actual architectural drawings to verify the accuracy of the time lag model, and analyze the composition and characteristics of the time delay and temperature rise in the time lag effect in combination with the model calculation results, and discuss the accuracy of the calculation;

[0115] The cooling machine pipe in the total pipe is measured by the design plan of the machine room. The riser pipe is directly related to the building height. There is no deviation when the data is accurate. However, the plane pipe calculation of the model is somewhat simplified compared with the actual situation. To ensure the accuracy of the model, two examples are used for verification:

[0116] Example 1 is the exhibition area of ​​a certain exhibition hall. The terminal equipment is a fan coil unit. The pipe well is represented by a solid circle, the nearest and farthest terminals are represented by solid triangles, and the pipelines corresponding to the nearest and farthest terminals are represented by thick straight lines.

[0117] Example 2 is a guest room layer of a hotel building. The terminal equipment is a fan coil unit. The plane outline of the hotel guest room layer is similar to a fan. Facing a building with a non-rectangular plane outline, the plane outline needs to be processed into a rectangle before the formula can be used for calculation;

[0118] The present invention verifies the plane pipe calculation. Only parameters related to the plane pipe calculation are input into the model. The input parameters of the example are shown in Table 1, and the calculation results are shown in Table 2:

[0119] Table 1 Example input parameters

[0120]

[0121] Table 2 Calculation results of the example

[0122]

[0123] There is no deviation between the chiller pipe and the riser pipe in the total pipe when the data is accurate, so the total pipe deviation rate calculated by the model should be smaller than the plane deviation rate; the plane pipe calculation deviation rates of Example 2 and Example 1 in Table 2 are similar, and the deviation rates are small, which proves the correctness of the contour regularization method; the pipe calculation deviation values ​​of the two examples are both less than 10m, indicating that the plane pipe calculation results of the model are accurate; the delay value deviation caused by the pipe deviation is within 10s, while the duration of the demand response event is mostly more than 15min, and this deviation has little impact on the final result;

[0124] Based on the verified cases, build an air conditioning system simulation platform, read external data and built-in data, organize and save the external data and built-in data in the workspace;

[0125] The actual air-conditioning system has time lag effect, and the time lag effect exists in each part of the air-conditioning water system, wind system and control system. The time lag effect of each part affects each other, which brings inconvenience to the targeted exploration of the influence of the time lag effect of a certain part of the air-conditioning system. Therefore, to explore the influence of the time lag effect on the air-conditioning system, we must first build a platform that can describe the parameter changes of each part of the air-conditioning system during actual operation, and add modules that consider the time lag effect on the platform for comparative exploration. By comparing the changes in the parameters of each part of the air-conditioning system platform after considering the time lag effect, we can explore the influence of the time lag effect on the air-conditioning system.

[0126] The time lag effect calculation model constructed by the present invention is a simplified model that does not consider the detailed water network topology of the air conditioning chilled water system. Figure 2 The terminal no water network on-off regulation model does not consider the topological structure of the detailed water network of the air conditioning system in the building. The chilled water distribution network is regarded as a whole for calculation. The calculation process is relatively simple, which is conducive to the subsequent research combined with the calculation results of the time-lag effect model.

[0127] After inputting hourly load, enclosure parameters, outdoor temperature and humidity, air conditioning system equipment parameters, and air conditioning system design parameters, the model performs calculations at a set time step and finally outputs the state parameters and indoor temperature changes in each time step during the operation of the air conditioning system.

[0128] The chiller in the cold station model construction unit is the key equipment for achieving temperature control, constant temperature, cooling and cooling functions in the building air conditioning. The chiller cools the refrigerant through the refrigeration system, and then the low-temperature refrigerant is sent to the equipment or terminal by the water pump. After heat exchange, the heat is taken away, the refrigerant temperature rises, and finally flows back to the water tank to achieve the effect of air conditioning. The energy utilization efficiency of the above process can be evaluated by COP. The algorithm of the chiller COP is shown in formula (1). The cold station model uses the relevant conclusions of Gordon JM and is applicable to centrifugal chillers and screw chillers. The model is shown in formulas (2)-(7):

[0129]

[0130]

[0131] Where:

[0132] COP——Coefficient of refrigeration performance of refrigeration machine; Q e ——Refrigeration capacity of refrigeration machine, kW; W chiller ——Energy consumption of cooling machine, kW; Q c ——heat rejection on the condenser side, kW; T c ——Condensation temperature of condenser, K; T e ——Evaporation temperature of evaporator, K; C c ——Heat transfer coefficient of condenser, kJ / K; C e ——Heat transfer coefficient of evaporator, kJ / K; T ew,out ——chilled water supply temperature, K;

[0133]

[0134] T cw,in ——Condensate return temperature, K;

[0135] q e =a 0 +a 1 ×R q +a 2 ×R q 2 +a 3 ×R q 3 (4)

[0136] q c =a 4 +a 5 ×R q +a 6 ×R q 2 +a 7 ×R q3 (5)

[0137] Where:

[0138] q e ——Irreversible loss on the evaporator side; q c ——Irreversible loss on the condenser side; R q is the load factor, %;

[0139] where a 1 , a 2 , a 3 , a 4 , a 5 , a 6 , a 7 The coefficients of different chillers are different. The coefficient algorithm of the screw chiller selected in this model is shown in the following formula (6):

[0140]

[0141]

[0142] Where:

[0143] G w ——Chilled water flow, m 3 / h; G ew ——Chilled water flow, m 3 / h;

[0144] The function of the circulating water pump in the water pump model construction unit is to provide power for the water supply cycle and ensure that the circulating water can flow in the system according to the set flow rate and flow velocity; the water pump model has two modes: fixed frequency and variable frequency. When simulating fixed frequency operation, the water pump model is shown in equations (7)-(8):

[0145] H=k 1 ×G pump 2 +k 2 ×G pump +k 3 (7)

[0146] Where:

[0147] H——water pump head, kPa; G pump ——Water pump flow, m 3 / h;k 1 ——quadratic coefficient of pump head characteristic curve; k 2 ——primary coefficient of pump head characteristic curve; k 3 ——Zero-order coefficient of pump head characteristic curve;

[0148]

[0149] Where:

[0150] η 0 ——Efficiency of water pump, %; k 4 ——quadratic coefficient of pump efficiency characteristic curve; k 5 ——primary coefficient of water pump efficiency characteristic curve; k 6 ——Zero-order coefficient of the water pump efficiency characteristic curve; the water valve at the end of the model has the function of following the room temperature adjustment, and the corresponding water pump also needs variable frequency operation. When simulating variable frequency operation, the water pump model is shown in equations (9) to (10):

[0151]

[0152] Where:

[0153] N 0 ——Design speed of water pump, r / min; N 1 ——Speed ​​of the water pump when running with variable frequency, r / min;

[0154] The pipeline regulating valve in the water valve control model building unit is a flow diversion and confluence or flow direction switching device, which can control the branch flow by adjusting the valve opening to meet the flow change requirements of different room load changes; the regulating valve is an on-off regulating valve, that is, it can only control the branch flow to 100% or 0% of the full load state; the indoor set temperature ± temperature control value is the temperature range, when the room temperature is higher than the maximum value of the temperature range, the end valve is fully open, when the room temperature is lower than the minimum value of the temperature range, the valve is closed, when the room temperature is within the set temperature range, the valve state is consistent with the previous moment;

[0155] The resistance coefficient calculation method of the water valve is shown in the following formula (11):

[0156]

[0157] Where:

[0158] ζ——Resistance coefficient when the valve is fully open, kPa / (L / s) 2 ; ΔP——Design pressure drop of the branch when the valve is fully open, kPa; G branch ——Branch design flow, L / s; when the valve is closed, the terminal flow is close to 0, and the valve resistance can be regarded as infinite; the valve opening judgment model is shown in formula (12):

[0159]

[0160] Where:

[0161] ν i ——valve opening at time i, %; ν i-1——valve opening at the previous moment before moment i, %; t ri ——Room temperature at time i, °C; t set_up ——Upper limit of room temperature range, ℃; t set_down ——Lower limit of room temperature range, ℃;

[0162] The above formula is the default judgment logic of the water valve. When performing demand response in the future, the judgment logic of the water valve status will be modified according to different scenario requirements;

[0163] The equipment selected in the terminal model construction unit is the fan coil unit, which is composed of a fan, a motor, and a coil unit. It is a commonly used cooling and heating terminal equipment. The fluid in the coil unit exchanges heat with the air, causing the temperature and humidity of the air to change, thereby achieving the purpose of air conditioning.

[0164] The surface cooler of the fan coil unit cools and dehumidifies the air through cold water. The heat exchange model of the water side and the air side of the fan coil unit is shown in formula (13):

[0165] G a ×(h a1 -h a2 )=G W ×C W (t w2 -t w1 ) (13)

[0166] Where:

[0167] G a ——Terminal air supply volume, m 3 / s;h a1 ——Enthalpy of air at the fan coil inlet, kJ / kg; h a2 ——Enthalpy of air at fan coil outlet, kJ / kg; t w1 ——Fan coil water supply temperature, °C; t w2 ——Fan coil unit return water temperature, °C;

[0168] The contact coefficient that can be achieved by the surface cooler should meet the contact coefficient required by the air treatment process, see formula (14) ~ (15):

[0169]

[0170] Where:

[0171] E th ——Total heat exchange efficiency, %; x, y——coefficients measured for fan coil units; t al ——Dry bulb temperature of air at the inlet of fan coil unit, °C; t a2 ——Dry bulb temperature of air at the fan coil outlet, °C;

[0172]

[0173] Where:

[0174] E g ——General heat exchange efficiency, %; λ 1 ——Heat exchange coefficient of coil outer surface, kW / (m 2 ·℃); γ——rib pass coefficient; n 3 ——row number; v y ——Face wind speed of coil, m / s; C p ——Specific heat capacity of air at constant pressure, J / kg·℃; ρ a ——Air density, kg / m 3 ;

[0175] t s1 ——Wet bulb temperature at the fan coil outlet, °C; t s2 ——Wet bulb temperature at the inlet of the fan coil unit, °C;

[0176] The room model construction unit uses the state space method, which is characterized by spatial differentiation and time continuity. In the solution process, objects with uneven internal temperature fields can be divided into multiple temperature nodes, and objects with uniform temperature space can be transformed into one node. The node temperature changes continuously over time. The room model takes into account the coupling between the air conditioning terminal and the building room. The building thermal characteristic parameters exported by the DeST software and the basic room temperature of each room are used as the data basis for the room envelope structure model, and the hourly temperature of the room is calculated in combination with the air supply volume and air supply temperature at the terminal.

[0177]

[0178] q=C p ×ρ a ×G a ×(t a -t r ) (17)

[0179]

[0180] Where:

[0181] t r ——Room temperature, °C; t bt ——Basic room temperature, °C; basic room temperature is the temperature in the room without using air conditioning, reflecting the room temperature state in a natural ventilation environment; ——Thermal characteristic coefficient of a room, which is the thermal reaction coefficient of the outdoor temperature on the room; q——Cooling capacity of a room, W; C p——Specific heat capacity of air at constant pressure, J / kg·℃; ρ a ——Air density, kg / m 3 ; G a ——Terminal air supply volume, m 3 / s;t a ——Terminal air supply temperature, °C;

[0182] The data integration calculation process is as follows Figure 3 , mainly divided into 4 links: external data reading, program internal data reading, program calculation, and finally outputting the calculation results;

[0183] Before calculation, it is necessary to set meteorological parameters and build a room model on DeST, and then export data from DeST. The external data are the building environment information read from DeST, including building envelope parameters, basic room temperature of each room in the building, outdoor temperature and humidity, and the simplified water network resistance coefficient calculated according to the air conditioning water system.

[0184] Internal data refers to the data directly input into the Matlab editor, which mainly includes the information of each device and pipeline of the air conditioning system;

[0185] The program calculation process is calculated in the order of cooling transfer. The calculation in the program is based on the initial state of the air-conditioning system and the room. A calculation is performed at each moment (the time interval is set by yourself). The calculation content includes the parameters of the chiller, water pump, water valve, terminal, room, and cooling tower. Then, according to the time interval, the outdoor meteorological parameters within the time interval and the calculation results of the previous moment are combined to calculate the parameters of each part at this moment. Finally, the parameter information of each device in each iteration process is recorded. After the iteration is completed, the data is sorted and saved in the workspace.

[0186] The demand response operation scenario is simulated on the air conditioning system simulation platform. By comparing the simulated data with external data and built-in data, the impact of the time lag effect on the cooling capacity and thermal comfort of the air conditioning system terminal is evaluated.

[0187] Delay and temperature rise parameters are introduced into the traditional model to simulate the impact of time lag effect on the performance of air conditioning terminals. During the demand response period, although the refrigeration equipment is suspended, the water pump continues to work to maintain water circulation, so that the terminal can use the remaining cooling capacity in the pipeline to maintain cooling. After the demand response ends, the refrigeration equipment quickly resumes operation. In the process from the restart of the equipment to the re-supply of cooling at the terminal, the time lag model takes into account the time lag effect and more accurately calculates the system response during the demand response period. The specific demand response calculation process can be referred to Figure 4 The time-lag model in

[0188] In order to enable the model to simulate the above scenarios, the traditional model needs to be modified, that is, adding temperature rise and delay modules to the program;

[0189] When the temperature rise of the water pump remains unchanged, the change of the terminal temperature rise value is determined by the chilled water pipe. The longer the chilled water pipe, the greater the terminal temperature rise value. The chilled water temperature rise at the same terminal is the same at any time. The algorithm of chilled water temperature rise in the time-lag model is shown in formula (19);

[0190]

[0191] Where:

[0192] ——water inlet temperature at the nth terminal, °C; t chiller,out ——Chiller outlet water temperature, °C; Δt n ——Total temperature rise at the nth end, °C;

[0193] The change of the terminal delay value is determined by the chilled water pipe. The longer the chilled water pipe, the larger the terminal delay value. The transmission delay caused by the time lag effect will make the terminal water temperature change later than the chiller action time. The delay from the chiller to the terminal is u. If the chiller stops at time i, the chiller temperature change it generates will be transmitted to the terminal after a time of u, as shown in formula (20):

[0194] terminal(i)=chiller(iu) (20)

[0195] Where:

[0196] terminal(i)——the state of the terminal at time i; chiller(iu)——the state of the chiller at time iu;

[0197] After considering the temperature rise and delay, the water temperature at a specific time at the end is calculated as shown in formula (21);

[0198]

[0199] Where:

[0200] t terminal(i),wl,n ——water inlet temperature at the nth end time i, °C; t chiller(i-u),out ——Water outlet temperature of the refrigeration machine at time iu, °C;

[0201] During the demand response period, the residual cooling in the chilled water pipe can be used for cooling to extend the downtime of the chiller and fully tap the peak-shaving potential of the air-conditioning system. When using residual cooling for cooling, the chilled water circulates in the pipeline. The larger the circulating water volume in the pipeline, the more residual cooling there is. The amount of circulating water is proportional to the scale of the pipeline. Therefore, the influence of the pipe process must be considered to qualitatively characterize the cooling process of residual cooling. In the traditional model, the chiller and the terminal act synchronously. The chiller and the terminal can be considered to be in a state of "no direct connection with the pipeline network". If the scale of the pipeline is not determined by calculating the time lag effect, it is impossible to simulate the residual cooling. Therefore The present invention only considers the influence of residual cooling in the time-lag model. When using chilled water for residual cooling, the cooling capacity of residual cooling is limited due to the closure of the chiller. The water temperature will gradually rise when the chilled water circulates in the pipeline. In order to explore the limit of residual cooling, the measured data of the terminal fan coil sample is needed as a basis. According to the thermal performance data of a fan coil unit in a factory, including more than 2,000 data under 5 types, 6 water temperatures, 5 flow rates and 11 temperature and humidity conditions, the mathematical method of multiple regression is used to obtain the total heat cooling capacity and sensible heat cooling capacity calculation formula of the fan coil unit. The total heat cooling capacity algorithm is shown in formula (22), and the sensible heat cooling capacity algorithm is shown in formula (23):

[0202]

[0203]

[0204] Where:

[0205] Q t ——Total heating and cooling capacity of the coil in actual state, kW; Q t,0 ——Coil design total heating and cooling capacity, kW; Q s ——Sensible heat and cooling capacity of the coil in actual state, kW; Q s,0 ——Designed sensible heat and cooling capacity of coil, kW; t a1 ——Air inlet dry bulb temperature of fan coil under actual working conditions, °C; t a,s1 ——Air inlet wet bulb temperature of fan coil under actual working conditions, °C; t w1 ——Cold water inlet temperature of fan coil under actual working conditions, °C; G w ——Water volume of fan coil under actual working conditions, m 3 / s; G w0 ——Water volume of fan coil under design conditions, m 3 / s; G a ——Air volume of fan coil unit under actual working conditions, m 3 / s; G a0 ——Air volume of fan coil under design conditions, m 3 / s;

[0206] From equations (22) and (23), it can be seen that when the water volume and air volume are unchanged, the difference between the indoor temperature and the chilled water inlet temperature is proportional to the coil cooling capacity. As the coil inlet temperature rises, the terminal cooling capacity will gradually decrease. When the water temperature is close to the room wet bulb temperature, the coil sensible heat cooling capacity approaches 0; when the water temperature is close to the room dry bulb temperature, the coil total heat cooling capacity approaches 0. At this time, when the chiller is shut down and the residual cold in the pipeline is used for cooling, the cooling capacity of the terminal coil gradually decreases as the water temperature rises. When the chilled water temperature is equal to the indoor temperature, the coil cannot output cooling capacity, and it can be considered that the residual cold in the chilled water system has been used up.

[0207] Among them, the demand response plan settings:

[0208] Scenario setting: Build an air conditioning system platform in the Matlab environment and set up two demand response scenarios: emergency demand response (EDR) and long-term demand response (LDR);

[0209] Parameter configuration: According to the time-of-use electricity price and summer outdoor temperature data provided by the power company, set the specific parameters of the simulation scenario. The specific setting scheme is shown in Table 3:

[0210] Table 3 Demand response setting scheme

[0211] Demand response scenarios Time period Cold machine start-stop strategy Load regulation strategy EDR 15 minutes Fast shutdown 30% reduction in load LDR 2 hours Phased shutdown 50% reduction in load

[0212] Data analysis and result evaluation:

[0213] Comparative analysis: By comparing simulation data with actual measurement data, the impact of time lag effect on the cooling capacity and thermal comfort of the air-conditioning system terminal is evaluated;

[0214] Analysis results: It is found that the time lag effect will lead to cooling transfer delay and temperature rise, especially in the long-term demand response scenario.

[0215] The specific analysis results are shown in Table 4:

[0216] Table 4 Analysis results

[0217] Scenario The cooling capacity at the end decreases Room temperature rise EDR 10％ 1℃ LDR 25％ 3℃

[0218] EDR scenario: In the emergency demand response scenario, the response speed and cooling capacity of the air conditioning system are tested through the rapid shutdown strategy. The results show that the time lag effect causes the terminal cooling capacity to drop by 10% and the room temperature to rise by 1°C;

[0219] LDR scenario: In the long-term demand response scenario, the performance of the air conditioning system in long-term demand response was tested through a phased shutdown strategy. The results showed that the time lag effect caused the terminal cooling capacity to drop by 25% and the room temperature to rise by 3°C.

[0220] This paper evaluates the impact of time lag effect on system operation through actual testing and analysis of the central air-conditioning system in the process of participating in demand response, and proposes corresponding optimization measures and suggestions. The following is an evaluation of the test results and the proposed optimization suggestions:

[0221] Evaluate the impact of time lag effects on air conditioning systems participating in demand response;

[0222] The test results show that the air conditioning system has a delay in adjusting its action and a certain attenuation in cooling capacity during the demand response period due to the existence of the time lag effect, which is mainly reflected in the following aspects:

[0223] Adjustment delay: After the air conditioning system receives the demand response signal, the shutdown operation of the chiller cannot be immediately reflected at the air conditioning terminal. There is a certain delay time, which is mainly determined by the transmission time of the chilled water in the pipeline;

[0224] Cooling attenuation: Since the temperature of chilled water rises during transmission, the actual cooling capacity obtained by the terminal is lower than the expected value. The temperature rise is mainly caused by heat transfer in the pipeline and work done by the water pump.

[0225] Based on the above evaluation results, in order to participate in demand response more effectively, the following optimization measures and suggestions are proposed:

[0226] Optimize pipeline design: During the design phase of the air conditioning system, the transmission distance of chilled water should be shortened as much as possible, and materials with better thermal insulation performance should be used to reduce the temperature rise of chilled water, thereby reducing the impact of time lag effect on cooling capacity;

[0227] Improve control accuracy: Adopt more accurate control algorithms to monitor and predict the temperature and flow of chilled water in real time, adjust the operating status of chillers and water pumps in time, and reduce adjustment delays and cooling attenuation;

[0228] Use cold storage technology: During the demand response period, the cold stored in the cold storage equipment is used for cooling, reducing the reliance on the chiller, thereby reducing the impact of the time lag effect on the air conditioning system. At the same time, the downtime of the chiller can be extended, improving the flexibility of demand response;

[0229] Zoning control: For large buildings, zoning control strategies can be adopted to divide the building into multiple independent air-conditioning zones. Each zone independently transmits and regulates chilled water, reducing the time lag effect of a single zone and improving the response speed and cooling effect of the overall system.

[0230] Intelligent scheduling: Introduce an intelligent scheduling system to dynamically adjust the operation strategy of the air-conditioning system according to the real-time electricity price, outdoor temperature and the cooling load demand of the building, so as to maximize the economic benefits of demand response and cooling effect.

[0231] According to another aspect of the present invention, there is also provided a system for analyzing time lag effects of central air conditioning participating in demand response, comprising:

[0232] Simplified time-lag effect calculation model construction unit, used to analyze the time-lag effect of air-conditioning system and provide core theoretical support for subsequent analysis;

[0233] A time-lag effect calculation model verification unit is used to further verify the time-lag effect calculation model and verify the accuracy and applicability of the time-lag calculation model;

[0234] The air conditioning system simulation platform construction unit takes the verified theory as the core, builds the simulation platform in the Matlab environment, reads external data and built-in data, integrates and calculates the data, and saves it in the workspace;

[0235] The time-lag effect module building unit of the simulation platform designs demand response operation scenarios on the simulation platform, simulates the operation status of the air-conditioning system in demand response, and analyzes the impact of time-lag effect on cooling capacity and response characteristics;

[0236] The evaluation and optimization suggestion unit evaluates the impact of time lag effect on the air-conditioning system's participation in demand response based on the test results, and proposes optimization measures and suggestions.

[0237] It should be understood that, inspired by the technical concept of the present invention, those skilled in the art can make various improvements and changes based on the above description without departing from the content of the present invention, which still fall within the protection scope of the present invention.

[0238] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. The specification and examples are to be considered exemplary only, and the true scope and spirit of the present invention are indicated by the claims.

[0239] It should be understood that the present invention is not limited to the precise construction shown in the above description and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for analyzing the time lag effect of central air conditioning participating in demand response, characterized in that: The steps include: According to the building shape and air conditioning system design specifications, a simplified time lag effect calculation model is constructed; Select actual building cases to further verify the time-lag effect calculation model; Based on the verified cases, build an air conditioning system simulation platform, read external data and built-in data, organize and save the external data and built-in data in the workspace; The demand response operation scenario is simulated and designed on the air-conditioning system simulation platform. By comparing the simulated data with external data and built-in data, the impact of the time lag effect on the cooling capacity and thermal comfort of the air-conditioning system terminal is evaluated.

2. A method for analyzing the time lag effect of central air conditioning participating in demand response according to claim 1, characterized in that: The construction of the simplified time-lag effect calculation model specifically involves a simplified calculation of the piping layout of the chilled water system, taking into account factors such as the layout of terminal equipment, the proportion of building air conditioning area, and the location of the refrigeration room.

3. The method for analyzing the time lag effect of central air conditioning participating in demand response according to claim 1 is characterized in that: The case verification not only includes the accuracy verification of the time-lag model, but also covers the quantitative comparison of pipeline temperature rise and terminal cooling attenuation in actual operation.

4. The method for analyzing the time lag effect of central air conditioning participating in demand response according to claim 1 is characterized in that: The air-conditioning system platform is constructed, and a platform is constructed that can describe the changes in parameters of various parts of the air-conditioning system during actual operation. Modules that consider time-lag effects are added to the platform in a targeted manner for comparative research. The influence of time-lag effects on the air-conditioning system is explored by comparing the changes in parameters of various parts of the air-conditioning system platform after considering the time-lag effects.

5. The method for analyzing the time lag effect of central air conditioning participating in demand response according to claim 1 is characterized in that: The air conditioning system platform construction includes: a cold station model construction unit, a water pump model construction unit, a water valve control model construction unit, a terminal model construction unit, a room model construction unit, a water network model construction unit and a real lag model construction unit; Among them, the chiller in the cold station model construction unit cools the refrigerant through the refrigeration system, and then the water pump sends the low-temperature refrigerant to the equipment or terminal. After heat exchange, the heat is taken away, the temperature of the refrigerant rises, and finally flows back to the water tank; the energy utilization efficiency of the above process can be evaluated by COP. The algorithm of the chiller COP is shown in formula (1). The cold station model uses the relevant conclusions of Gordon JM and is applicable to centrifugal chillers and screw chillers. The model is shown in formulas (2)-(7): Where: COP——Coefficient of refrigeration performance of refrigeration machine; Q e ——Refrigeration capacity of refrigeration machine, kW; W chiller ——Energy consumption of cooling machine, kW; Q c ——heat rejection on the condenser side, kW; T c ——Condensation temperature of condenser, K; T e ——Evaporation temperature of evaporator, K; C c ——Heat transfer coefficient of condenser, kJ / K; C e ——Heat transfer coefficient of evaporator, kJ / K; T ew,out ——chilled water supply temperature, K; T cw,in ——Condensate return temperature, K; what e =a0+a1×R q +a2×R q 2 +a3×R q 3 (4) q c =a4+a5×R q +a6×R q 2 +a7×R q 3 (5) Where: q e ——Irreversible loss on the evaporator side; q c ——Irreversible loss on the condenser side; R q is the load factor, %; Among them, a1, a2, a3, a4, a5, a6, and a7 are coefficients. The coefficients of different chillers are different. The coefficient algorithm of the screw chiller selected in this model is shown in the following formula (6): Where: G w ——Chilled water flow, m 3 / h; G ew ——Chilled water flow, m 3 / h; The water pump model in the water pump model construction unit has two modes: fixed frequency and variable frequency. When simulating fixed frequency operation, the water pump model is shown in equations (7)-(8): H=k1×G pump 2 +k2×G pump +k3 (7) Where: H——water pump head, kPa; G pump ——Water pump flow, m 3 / h; k1——quadratic coefficient of water pump head characteristic curve; k2——primary coefficient of water pump head characteristic curve; k3——zero-order coefficient of water pump head characteristic curve; Where: η0——water pump efficiency, %; k4——quadratic coefficient of water pump efficiency characteristic curve; k5——primary coefficient of water pump efficiency characteristic curve; k6——zero-order coefficient of water pump efficiency characteristic curve; The water valve at the end of the model has the function of following the room temperature adjustment, and the corresponding water pump also needs variable frequency operation. When simulating variable frequency operation, the water pump model is shown in equations (9) to (10); Where: N0——designed speed of the water pump, r / min; N1——speed of the water pump during variable frequency operation, r / min; In the water valve control model construction unit, the regulating valve is an on-off regulating valve, that is, it can only control the branch flow to 100% or 0% of the full load state. The indoor set temperature ± temperature control value is the temperature interval. When the room temperature is higher than the maximum value of the temperature interval, the terminal valve is fully open. When the room temperature is lower than the minimum value of the temperature interval, the valve is closed. When the room temperature is within the set temperature range, the valve state is consistent with the previous moment. The resistance coefficient calculation method of the water valve is shown in the following formula (11): Where: ζ——Resistance coefficient when the valve is fully open, kPa / (L / s) 2 ; ΔP——Design pressure drop of the branch when the valve is fully open, kPa; G branc h——branch design flow, L / s; When the valve is closed, the end flow is close to 0, and the valve resistance can be regarded as infinite; The valve opening judgment model is shown in formula (12): Where: v i ——valve opening at time i, %; v i-1 ——valve opening at the previous moment before moment i, %; t ri ——Room temperature at time i, °C; t set_up ——Upper limit of room temperature range, ℃; t set_down ——Lower limit of room temperature range, ℃; The above formula is the default judgment logic of the water valve. When performing demand response in the future, the judgment logic of the water valve status will be modified according to different scenario requirements; The equipment selected in the terminal model construction unit is a fan coil unit, which is composed of a fan, a motor, and a coil unit. The fluid passing through the coil unit exchanges heat with the air. The surface cooler of the fan coil unit cools and dehumidifies the air through cold water. The heat exchange model of the water side and the air side of the fan coil unit is shown in formula (13): G a ×(h a1 -h a2 )=G W ×C W (t w2 -t w1 ) (13) Where: G a ——Terminal air supply volume, m 3 / s;h a1 ——Enthalpy of air at the fan coil inlet, kJ / kg; h a2 ——Enthalpy of air at fan coil outlet, kJ / kg; t w1 ——Fan coil water supply temperature, °C; t w2 ——Fan coil unit return water temperature, °C; The contact coefficient that can be achieved by the surface cooler is shown in equations (14) to (15): Where: E th ——Total heat exchange efficiency, %; x, y——coefficients measured for fan coil units; t al ——Dry bulb temperature of air at the inlet of fan coil unit, °C; t a2 ——Dry bulb temperature of air at the fan coil outlet, °C; Where: E g ——General heat exchange efficiency, %; λ1——Heat exchange coefficient of outer surface of coil, kW / (m 2 ·℃); γ——rib pass coefficient; n3——row number; v y ——Face wind speed of coil, m / s; C p ——Specific heat capacity of air at constant pressure, J / kg·℃; ρ a ——Air density, kg / m 3 ;t s1 ——Wet bulb temperature at the fan coil outlet, °C; t s2 ——Wet bulb temperature at the inlet of fan coil unit, °C; The room model construction unit uses the state space method. During the solution process, the object with uneven internal temperature field is divided into multiple temperature nodes, and the object with uniform temperature space is converted into one node. The node temperature changes continuously over time. The room model takes into account the coupling between the air conditioning terminal and the building room. The building thermal characteristic parameters exported by the DeST software and the basic room temperature of each room are used as the data basis for the room enclosure structure model. The hourly temperature of the room is calculated in combination with the air supply volume and air supply temperature at the terminal. q=C p ×ρ a ×G a ×(t a -t r ) (17) Where: t r ——Room temperature, °C; t bt ——Basic room temperature, °C; basic room temperature is the temperature in the room without using air conditioning, reflecting the room temperature state in a natural ventilation environment; ——Thermal characteristic coefficient of a room, which is the thermal reaction coefficient of the outdoor temperature on the room; q——Cooling capacity of a room, W; C p ——Specific heat capacity of air at constant pressure, J / kg·℃; ρ a ——Air density, kg / m 3 ; G a ——Terminal air supply volume, m 3 / s;t a ——Terminal supply air temperature, ℃.

6. The method for analyzing the time lag effect of central air conditioning participating in demand response according to claim 1 is characterized in that: The calculation process of the air conditioning system platform is mainly divided into four links: external data reading, program internal data reading, program calculation, and finally output of calculation results. Before calculation, meteorological parameters need to be set and room model needs to be established, and then data is exported; The external data are the building environment information read, including the building envelope parameters, the basic room temperature of each room in the building, the outdoor temperature and humidity, and the simplified water network resistance coefficients calculated based on the air conditioning water system. Internal data refers to data that is directly input, mainly including information about each unit and pipeline of the air conditioning system; The program calculation process is calculated in the order of cold transfer.

7. The method for analyzing the time lag effect of central air conditioning participating in demand response according to claim 1 is characterized in that: A time lag effect is introduced during the demand response, and delay and temperature rise parameters are introduced; The algorithm for chilled water temperature rise in the time-lag model is shown in equation (19): Where: ——water inlet temperature at the nth terminal, °C; t chiller,out ——Chiller outlet water temperature, °C; Δt n ——Total temperature rise at the nth end, °C; The terminal delay value is shown in formula (20): terminal(i)=chiller(iu) (20) Where: terminal(i)——the state of the terminal at time i; chiller(iu)——the state of the chiller at time iu; After considering the temperature rise and delay, the water temperature at a specific time at the end is calculated as shown in formula (21): Where: t terminal(i),wl,n ——water inlet temperature at the nth end time i, °C; t chiller(i-u),out ——Water outlet temperature of the refrigeration machine at iu, ℃.

8. The method for analyzing the time lag effect of central air conditioning participating in demand response according to claim 1 is characterized in that: The total heat and cooling capacity algorithm of the time-lag model during the demand response period is shown in formula (22), and the sensible heat and cooling capacity algorithm is shown in formula (23): Where: Q t ——Total heating and cooling capacity of the coil in actual state, kW; Q t,0 ——Coil design total heating and cooling capacity, kW; Q s ——Sensible heat and cooling capacity of the coil in actual state, kW; Q s,0 ——Design sensible heat and cooling capacity of coil, kW; ——Air inlet dry bulb temperature of fan coil under actual working conditions, °C; t a,s1 ——Air inlet wet bulb temperature of fan coil under actual working conditions, °C; t w1 ——Cold water inlet temperature of fan coil under actual working conditions, °C; G w ——Water volume of fan coil under actual working conditions, m 3 / s; G w0 ——Water volume of fan coil under design conditions, m 3 / s; G a ——Air volume of fan coil unit under actual working conditions, m 3 / s; G a0 ——Air volume of fan coil under design conditions, m 3 / s.

9. A time lag effect analysis system for central air conditioning participating in demand response, characterized in that: include: Simplified time-lag effect calculation model construction unit, used to analyze the time-lag effect of air-conditioning system and provide core theoretical support for subsequent analysis; The time-lag effect calculation model verification unit is used to further verify the time-lag effect calculation model by selecting actual building cases; The air conditioning system simulation platform construction unit builds the simulation platform based on the verified cases, reads external data and built-in data, and organizes and saves the data in the workspace; The time-lag effect module building unit of the simulation platform simulates the demand response operation scenario on the simulation platform, simulates the operation status of the air-conditioning system in the demand response, and evaluates the impact of the time-lag effect on the terminal cooling capacity and thermal comfort of the air-conditioning system by comparing the simulation data with external data and built-in data.

10. The central air-conditioning demand response time lag effect analysis system according to claim 9, characterized in that: The air conditioning system simulation platform construction unit is established on Matlab.

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