Simulation model construction method applied to regional heating efficiency evaluation

Abstract

The invention discloses a simulation model construction method applied to regional heating efficiency evaluation, relates to the technical field of heating management, and improves the heating energy utilization efficiency. According to the method, a multi-heating evaluation model is established through heating thermal parameters and user energy consumption data, the current heating quarter period is divided into a plurality of heating detection time points, and when one heating detection time point starts, the real-time heating thermal parameters and the real-time user energy consumption data are collected and input into the multi-heating evaluation model; and according to the energy consumption relationship among the heat source evaluation model, the pipe network evaluation model and the user energy efficiency evaluation model, the required fuel quantity at the corresponding heating detection time point is obtained, and whether the transmission and distribution pipe network is abnormal or not is detected.

Description

Technical Field

[0001] The present invention relates to the technical field of heating management, and specifically to a method for constructing a simulation model applied to the evaluation of regional heating efficiency. Background Art

[0002] As an important part of urban infrastructure, the regional heating system plays a key role in ensuring that residents can spend the winter warmly and the normal operation of industrial production. The traditional regional heating management mode often relies on experience and extensive regulation, lacking accurate monitoring and scientific evaluation of each link of the heating system.

[0003] In terms of heat source supply, due to the lack of real-time and accurate grasp of the actual output thermal parameters of the heat source, it often leads to the mismatch between energy supply and actual demand, resulting in energy waste or insufficient supply. For example, in some cases, the heat source over-supplies heat, causing a large amount of heat energy to be wasted during transmission and use; while in other cases, it may also lead to unqualified indoor temperatures for some users due to insufficient supply.

[0004] As the channel for heat transmission, the operation status of the distribution network directly affects the heating effect. However, due to the wide distribution and complex structure of the network, it is difficult for traditional methods to detect abnormal situations such as leaks and blockages in the network in a timely manner, which will not only cause heat loss but also may affect the stability and reliability of the entire heating system.

[0005] At the user end, there are differences in the energy consumption demands of different users, but the traditional heating management mode is difficult to accurately analyze and regulate the actual energy consumption situation of users, unable to provide personalized heating services, and not conducive to improving energy utilization efficiency. Therefore, a method for constructing a simulation model applied to the evaluation of regional heating efficiency is provided. Summary of the Invention

[0006] In order to solve the above technical problems, the purpose of the present invention is to provide a method for constructing a simulation model applied to the evaluation of regional heating efficiency.

[0007] In order to achieve the above purpose, the present invention provides the following technical solutions:

[0008] A method for constructing a simulation model applied to the evaluation of regional heating efficiency, comprising the following steps:

[0009] Step S1: Deploy a variety of collection devices at the heat source supply station, distribution network, and user end in the regional heating system, and set the heating quarter cycle, and then collect the heating thermal parameters and user energy consumption data of the regional heating system in each heating quarter cycle;

[0010] Step S2: Establish a multiple heating evaluation model based on heating thermal parameters and user energy consumption data. The multiple heating evaluation model includes a heat source evaluation model, a pipe network evaluation model, a user energy efficiency evaluation model, and a regional visualization model;

[0011] Step S3: Divide the current heating quarter cycle into several heating detection time points. Whenever a heating detection time point starts, collect real-time heating thermal parameters and real-time user energy consumption data and input them into the multiple heating evaluation model. Then, obtain the required fuel quantity at the corresponding heating detection time point according to the energy consumption relationship among the heat source evaluation model, the pipe network evaluation model, and the user energy efficiency evaluation model, and detect whether there are abnormalities in the transmission and distribution pipe network.

[0012] Furthermore, the heat source supply station is used to produce heating heat sources and input the heating heat sources into the transmission and distribution pipe network;

[0013] The transmission and distribution pipe network is directly connected to each user area and is used to transport the heating heat source to each user area according to the heating demand of each user area. The user area represents the residential area;

[0014] Deploy temperature sensors, pressure sensors, flow meters, and user heat meters at the heat source supply station, the transmission and distribution pipe network, and the user area, and set the same data upload frequency for each collection device.

[0015] Furthermore, the collection process of the heating thermal parameters and user energy consumption data includes:

[0016] Set the heating quarter cycle. Then, whenever a heating quarter cycle starts, each collection device collects various heating parameter data or user energy consumption data at its location;

[0017] The heating parameter data includes the supply water temperature change curve, the return water temperature change curve, the pipeline pressure change value, and the flow curve. The user energy consumption data includes the cumulative heat consumption, the indoor temperature value, the user target heating temperature, and the supply and return water temperature difference;

[0018] Whenever a data upload cycle ends, each collection device uploads the various data it has collected, and at the same time obtains the fuel consumption of the source supply station during the data upload cycle, so as to obtain the heating thermal parameters and user energy consumption data for each heating quarter cycle.

[0019] Furthermore, the establishment process of the regional visualization model includes:

[0020] Obtain the regional heating system structure diagram, which includes the spatial location distribution of the heat source supply station, the transmission and distribution pipe network, and the user area;

[0021] Furthermore, a regional visualization model is established based on the structural diagram of the district heating system. The regional visualization model includes a heat source supply station model part, a transmission and distribution pipe network model part, and a user area model. Among them, the transmission and distribution pipe network model part is connected to both the heat source supply station model part and the user area model at the same time, and numbers a1, a2, a3, ……, a n , where n is a natural number greater than 0;

[0022] The transfer points of the transmission and distribution pipes in each transmission and distribution pipe network model part are recorded as temperature-sensitive points and pressure fluctuation points.

[0023] Furthermore, the establishment process of the heat source evaluation model includes:

[0024] According to the historical supply water temperature change curve, historical return water temperature change curve, and historical fuel consumption in the heat source supply station within the recent heating quarter cycle, obtain the dynamic equation of the heat source output power under different fuel consumptions in the heating quarter cycle.

[0025] Furthermore, the establishment process of the pipe network evaluation model includes:

[0026] According to the position distribution of each collection device in the transmission and distribution pipe network and the distribution of temperature-sensitive points and pressure fluctuation points, divide the transmission and distribution pipe network model part into several pipe section units. Then, according to the recent three supply water temperature change curves, return water temperature change curves, pipeline pressure change values, and flow curves, obtain the standard pressure-flow velocity equation and the standard flow velocity-temperature loss formula for each pipe section unit.

[0027] Furthermore, the establishment process of the user energy efficiency evaluation model includes:

[0028] Respectively retrieve the historical user energy consumption data of each user area in m heating quarter cycles. According to the thermodynamic principle, set the user area as a uniform thermal environment. At the same time, since the heating quarter for indoor heating is generally winter, as the temperature difference between indoor and outdoor continuously increases, the heating efficiency shows a fluctuating change, where m is a natural number greater than 20;

[0029] Furthermore, set multiple indoor temperature intervals, group the historical user energy consumption data of each heating quarter cycle according to the indoor temperature values included in the historical user energy consumption data. Then, according to the historical cumulative heat consumption and the difference between supply and return water temperatures in the same group of historical user energy consumption data, obtain the heating efficiency under different indoor temperature intervals;

[0030] Mark the heat source evaluation model, the user energy efficiency evaluation model, and the pipe network evaluation model at the corresponding positions of the multiple heating evaluation model.

[0031] Furthermore, the process of obtaining the required fuel quantity at the heating detection time point includes:

[0032] Each data upload cycle within the heating quarter cycle is recorded as a heating detection time point. Then, starting from the most recent heating quarter cycle, each collection device collects various real-time heating parameter data and real-time user energy consumption data at its location, and marks the real-time heating parameter data and real-time user energy consumption data on the multiple heating evaluation model.

[0033] The district heating system detects the heating demands uploaded by each user area and marks the heating demands on the corresponding user area models in the multiple heating evaluation model. The heating demands include the demand time period and the required heating temperature.

[0034] Whenever a heating detection time point starts, traverse the user area models with heating demands from the multiple heating evaluation model, and set the heating life cycle for the corresponding user area models according to the demand time period in the heating demands.

[0035] In the multiple heating evaluation model, traverse the pipe section units associated between the user area model and the heat source supply station model part, and generate the corresponding heating pipeline chain. Then, input the required heating temperature and the real-time indoor temperature into the user energy efficiency evaluation model and the corresponding pipe network evaluation model in sequence.

[0036] Overlap and merge the heating pipeline chains between the same pair of heating detection time points according to the same pipe section units.

[0037] According to the user area model and the pipe network evaluation model, hierarchically summarize the required heat between each pair of heating detection time points, and input the summary result into the heat source supply station model. Then, the heat source supply station model outputs the required fuel quantity according to the summary result.

[0038] Furthermore, the process of detecting whether there is an abnormality in the transmission and distribution pipe network includes:

[0039] According to the real-time flow curves of each pipe section unit, obtain the predicted pipeline pressure values of each pipe section unit, set the pipe pressure change detection interval, compare the predicted pipeline pressure values with the corresponding real-time pipeline pressure change values. If the difference between the real-time pipeline pressure change value and the pressure exceeding the threshold is within the pipe pressure change detection interval, no operation is performed. Otherwise, it is determined that the corresponding pipe section unit is abnormal, and then an abnormal maintenance prompt is sent to the staff according to the number of the corresponding pipe section unit.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] 1. The present invention establishes a multiple heating evaluation model based on the collected heating thermal parameters and user energy consumption data, including a heat source evaluation model, a pipe network evaluation model, a user energy efficiency evaluation model, and a regional visualization model. These models comprehensively evaluate the regional heating system from different perspectives, can deeply analyze the energy consumption and operation efficiency of the heat source, pipe network, and user side, and provide a scientific basis for optimizing the heating system.

[0042] 2. By dividing the current heating quarter cycle into several heating detection time points, whenever a heating detection time point starts, the real-time heating thermal parameters and real-time user energy consumption data are collected and input into the multiple heating evaluation model. It realizes the real-time evaluation and dynamic regulation of the heating system, accurately calculates the required fuel quantity according to the actual situation at different heating detection time points, avoids waste or insufficient supply of energy, and improves energy utilization efficiency. Description of the Drawings

[0043] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention.

[0044] Figure 1 It is a flowchart of the method of the present invention. Detailed Embodiments

[0045] To make the purpose, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be described in detail below. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other implementation manners obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0046] As Figure 1 shown, a simulation model construction method applied to regional heating efficiency evaluation includes the following steps:

[0047] Step S1: Deploy a variety of collection devices at the heat source supply station, distribution pipe network, and user side in the regional heating system, and set the heating quarter cycle, and then collect the heating thermal parameters and user energy consumption data of the regional heating system in each heating quarter cycle;

[0048] Step S2: Establish a multiple heating evaluation model according to the heating thermal parameters and user energy consumption data, and the multiple heating evaluation model includes a heat source evaluation model, a pipe network evaluation model, a user energy efficiency evaluation model, and a regional visualization model;

[0049] Step S3: Divide the current heating quarter cycle into several heating detection time points. Whenever a heating detection time point starts, collect real-time heating thermal parameters and real-time user energy consumption data and input them into the multi-heating evaluation model. Then, obtain the required fuel quantity at the corresponding heating detection time point according to the energy consumption relationship among the heat source evaluation model, the pipe network evaluation model, and the user energy efficiency evaluation model, and detect whether there are any abnormalities in the distribution and transmission pipeline network.

[0050] Further, the step S1 is implemented through the following process:

[0051] The district heating system consists of a heat source supply station, a distribution and transmission pipeline network, and user areas. The heat source supply station is used to produce heating heat sources and input the heating heat sources into the distribution and transmission pipeline network.

[0052] The distribution and transmission pipeline network is directly connected to each user area and is used to transport the heating heat sources to each user area according to the heating demands of each user area. The user area represents the residential area of residents.

[0053] Deploy temperature sensors, pressure sensors, flow meters, and user heat meters at the heat source supply station, the distribution and transmission pipeline network, and the user areas, and set the same data upload frequency for each collection device. Generally, the data upload frequency is 10 to 20 seconds.

[0054] It should be noted that due to the structure and spatial position distribution of the distribution and transmission pipeline network, the temperature sensors, pressure sensors, and flow meters in each user area are used to collect various heating parameter data of the part of the distribution and transmission pipeline network connected to them. At the same time, each collection device located in the distribution and transmission pipeline network is installed at the corner and the middle position of the distribution pipeline.

[0055] Set the heating quarter cycle. Then, whenever a heating quarter cycle starts, each collection device collects various heating parameter data or user energy consumption data at its location.

[0056] The heating parameter data includes the supply water temperature change curve, the return water temperature change curve, the pipeline pressure change value, and the flow curve. The user energy consumption data includes the cumulative heat consumption, the indoor temperature value, the user target heating temperature, and the difference between the supply and return water temperatures.

[0057] Whenever a data upload cycle ends, each collection device uploads the various data it has collected. At the same time, obtain the fuel consumption of the heat source supply station during the data upload cycle, and then obtain the heating thermal parameters and user energy consumption data for each heating quarter cycle.

[0058] Further, the step S2 is implemented through the following process:

[0059] The multiple heating evaluation model consists of a heat source evaluation model, a pipe network evaluation model, a user energy efficiency evaluation model, and a regional visualization model;

[0060] The establishment process of the regional visualization model includes:

[0061] Obtain the structural diagram of the regional heating system, which includes the spatial location distribution of the heat source supply station, the distribution network, and the user area;

[0062] Furthermore, establish a regional visualization model according to the structural diagram of the regional heating system. The regional visualization model includes a heat source supply station model part, a distribution network model part, and a user area model. Among them, the distribution network model part is connected to the heat source supply station model part and the user area model at the same time, and each user area model is set with numbers a1, a2, a3,..., a n , where n is a natural number greater than 0;

[0063] Record the transfer points of the distribution pipes in each distribution network model part as temperature-sensitive points and pressure fluctuation points.

[0064] The heat source evaluation model includes:

[0065] According to the historical supply water temperature change curve, historical return water temperature change curve, and historical fuel usage in the recent heating quarter cycle of the heat source supply station, obtain the dynamic equation of the heat source output power under different fuel usages in the heating quarter cycle:

[0066] ηxΔ 燃料 =ρ 水 C p (T out -T in )vt;

[0067] Where η is the thermal efficiency, ρ 水 respectively represent the water density, T out and T in respectively represent the supply and return water temperatures, x represents the fuel usage, C p and Δ 燃料 represent the constant pressure specific heat capacity and the calorific value of the fuel, and v and t represent the unit time flow rate and the time length.

[0068] The pipe network evaluation model includes:

[0069] According to the position distribution of each collection device in the distribution network and the distribution of temperature-sensitive points and pressure fluctuation points, divide the distribution network model part into several pipe section units. Furthermore, according to the recent three supply water temperature change curves, return water temperature change curves, pipeline pressure change values, and flow curves, obtain the standard pressure-flow velocity equation and the standard flow velocity-temperature loss formula for each pipe section unit;

[0070] Among them, the standard pressure-flow equation:

[0071] P(t) represents the pipeline pressure value of the pipeline section unit corresponding to the data upload period at time t, f is the pipeline friction coefficient, L is the length of the pipeline section unit, and D is the radius of the pipeline section unit;

[0072] Standard flow rate-temperature loss formula:

[0073] ΔQ(t) represents the heat loss value in the t-th data upload period, k is the thermal conductivity of the pipe material, and A is the surface area of the pipeline section unit;

[0074] The user energy efficiency evaluation model includes:

[0075] Retrieve the historical user energy consumption data of each user area in m heating quarter cycles respectively. According to the thermodynamic principle, set the user area as a uniform thermal environment. At the same time, since the heating quarter for indoor heating is generally winter, as the temperature difference between indoor and outdoor increases continuously, the heating efficiency shows a fluctuating change, where m is a natural number greater than 20;

[0076] Furthermore, set multiple indoor temperature intervals, group the historical user energy consumption data of each heating quarter cycle according to the indoor temperature values included in the historical user energy consumption data, and then obtain the heating efficiency μ under different indoor temperature intervals according to the historical cumulative heat consumption and the temperature difference between supply and return water in the same group of historical user energy consumption data;

[0077] The formula for obtaining the heating efficiency is:

[0078]

[0079] Where k and α are proportionality coefficients, t is the number of passed data upload cycles, T 差 represents the temperature difference between supply and return water, and Q num represents the historical cumulative heat consumption at the num-th data upload cycle, and num is a natural number greater than 0;

[0080] Iterate the formula for obtaining the heating efficiency in different heating quarter cycles but the same indoor temperature interval, and correct k and α according to the iteration result;

[0081] Mark the heat source evaluation model, user energy efficiency evaluation model, and pipe network evaluation model at the corresponding positions of the multiple heating evaluation model.

[0082] Furthermore, the step S3 is implemented through the following process:

[0083] Each data upload cycle within the heating quarter cycle is recorded as a heating detection time point. Starting from the most recent heating quarter cycle, each collection device collects various real-time heating parameter data and real-time user energy consumption data at its location, and labels the real-time heating parameter data and real-time user energy consumption data on the multiple heating evaluation model;

[0084] It should be noted that for the real-time supply temperature change curve, real-time return water temperature change curve, and real-time pipeline pressure change value of the distribution pipeline network, they are labeled at the temperature-sensitive points and pressure fluctuation points, and the real-time flow curve is labeled on the pipe segment unit;

[0085] The district heating system detects the heating demands uploaded by each user area and labels the heating demands on the corresponding user area model in the multiple heating evaluation model. The heating demands include the demand period and the required heating temperature;

[0086] Whenever a heating detection time point starts, the user area models with heating demands are traversed from the multiple heating evaluation model, and the heating life cycle is set for the corresponding user area models according to the demand period in the heating demands;

[0087] In the multiple heating evaluation model, the pipe segment units associated between the user area model and the heat source supply station model part are traversed, and the corresponding heating pipeline chain is generated. Then, the required heating temperature and the real-time indoor temperature are input into the user energy efficiency evaluation model and the corresponding pipe network evaluation model in sequence;

[0088] Since there is a situation where the same pipe segment unit manages multiple user area models, the heating pipeline chains between the same pair of heating detection time points are overlapped and merged according to the same pipe segment unit;

[0089] According to the user area model and the pipe network evaluation model, the required heat between each pair of heating detection time points is hierarchically summarized, and the summary result is input into the heat source supply station model. Then, the heat source supply station model outputs the required fuel quantity according to the summary result;

[0090] At the same time, according to the real-time flow curve of each pipe segment unit, the predicted pipeline pressure value of each pipe segment unit is obtained, a pipe pressure change detection interval is set, and the predicted pipeline pressure value is compared with the corresponding real-time pipeline pressure change value. If the difference between the real-time pipeline pressure change value and the pressure exceeding the threshold is within the pipe pressure change detection interval, no operation is performed. Otherwise, it is determined that the corresponding pipe segment unit is abnormal, and then an abnormal maintenance prompt is sent to the staff according to the number of the corresponding pipe segment unit;

[0091] Whenever a heating detection time point ends, it is judged whether the heating life cycle of the user area model ends. If not, the next heating detection time point is directly carried out;

[0092] If it exists, the corresponding user area model is ignored at the start of the next heating detection time point, and the above determination of the required fuel quantity is repeated until all heating demands are completed.

[0093] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A simulation model construction method for district heating efficiency evaluation, characterized in that: The following steps are involved: Step S1, deploying a variety of collection devices at the heat source supply station, the transmission and distribution network and the user end of the district heating system, and setting the heating quarterly cycle, and then collecting the heating thermal parameters and user energy consumption data of the district heating system in each heating quarterly cycle; Step S2: establishing a multiple heating evaluation model according to heating thermal parameters and user energy consumption data, wherein the multiple heating evaluation model includes a heat source evaluation model, a pipe network evaluation model, a user energy efficiency evaluation model and a regional visualization model; Step S3, divide the current heating quarterly cycle into several heating detection time points. When each heating detection time point starts, collect real-time heating thermal parameters and real-time user energy consumption data and input them into multiple heating evaluation models. Then, according to the energy consumption relationship among the heat source evaluation model, the pipeline network evaluation model and the user energy efficiency evaluation model, obtain the required fuel quantity at the corresponding heating detection time point, and detect whether there is any abnormality in the transmission and distribution pipeline network.

2. The method for constructing a simulation model for district heating efficiency evaluation according to claim 1, characterized in that: The heat source supply station is used to produce heating heat source and input the heating heat source into the transmission and distribution pipeline network; The transmission and distribution pipeline network is directly connected to each user area and is used to transport the heating heat source to each user area according to the heating demand of each user area; Temperature sensors, pressure sensors, flow meters and user heat meters are deployed at heat source supply stations, transmission and distribution pipelines and user areas, and the same data upload frequency is set for each collection device.

3. The method for constructing a simulation model for district heating efficiency evaluation according to claim 2, characterized in that: The process of collecting heating thermal parameters and user energy consumption data includes: A heating quarterly cycle is set, and each time a heating quarterly cycle begins, each collection device collects various heating parameter data or user energy consumption data at the location; The heating parameter data includes a supply water temperature change curve, a return water temperature change curve, a pipeline pressure change value, and a flow curve; the user energy consumption data includes cumulative heat consumption, indoor temperature value, user target heating temperature, and supply and return water temperature difference; Whenever a data upload cycle ends, each collection device uploads the data it has collected, and at the same time obtains the fuel usage of the source supply station during the data upload cycle, and then obtains the heating thermal parameters and user energy consumption data of each heating quarter cycle.

4. The method for constructing a simulation model for district heating efficiency evaluation according to claim 3, characterized in that: The process of establishing the regional visualization model includes: Obtaining a district heating system structure diagram, and establishing a regional visualization model according to the district heating system structure diagram, wherein the regional visualization model includes a heat source supply station model part, a transmission and distribution pipeline network model part, and a user area model; The transfer points of the distribution pipelines in each distribution network model part are recorded as temperature sensitive points and pressure fluctuation points.

5. The method for constructing a simulation model for district heating efficiency evaluation according to claim 3, characterized in that: The process of establishing the heat source assessment model includes: According to the historical water supply temperature change curve, historical return water temperature change curve and historical fuel usage of the heat source supply station in the most recent heating quarterly cycle, the dynamic equation of the heat source output power under different fuel usages in the heating quarterly cycle is obtained.

6. The method for constructing a simulation model for district heating efficiency evaluation according to claim 3, characterized in that: The process of establishing the pipeline network assessment model includes: According to the location distribution of each acquisition device in the transmission and distribution network and the distribution of temperature sensitive points and pressure fluctuation points, the transmission and distribution network model is divided into several pipe section units. Then, according to the latest three water supply temperature change curves, return water temperature change curves, pipeline pressure change values ​​and flow curves, the standard pressure-flow velocity equation and standard flow velocity-temperature loss formula of each pipe section unit are obtained.

7. The method for constructing a simulation model for district heating efficiency evaluation according to claim 3, characterized in that: The process of establishing the user energy efficiency evaluation model includes: Set multiple indoor temperature intervals, group the historical user energy consumption data of each heating quarterly cycle according to the indoor temperature values ​​contained in the historical user energy consumption data, and obtain the heating efficiency under different indoor temperature intervals according to the historical cumulative heat consumption and supply and return water temperature difference in the same group of historical user energy consumption data; The heat source assessment model, user energy efficiency assessment model and pipe network assessment model are marked at the corresponding positions of the multiple heating assessment model.

8. The method for constructing a simulation model for district heating efficiency evaluation according to claim 7, characterized in that: The process of obtaining the required fuel quantity at the heating detection time point includes: Each data upload period within the heating quarterly cycle is recorded as a heating detection time point, and then at the beginning of the latest heating quarterly cycle, each collection device collects various real-time heating parameter data and real-time user energy consumption data at its location, and annotates the real-time heating parameter data and real-time user energy consumption data in the multiple heating evaluation model; The regional heating system detects the heating demand uploaded by each user area and marks the heating demand on the corresponding user area model in the multiple heating assessment model, wherein the heating demand includes the demand period and the required heating temperature; Whenever a heating detection time point starts, the user area model with heating demand is traversed from the multiple heating evaluation models, and the heating life cycle is set for the corresponding user area model according to the demand period in the heating demand; In the multiple heating evaluation model, the pipe section units associated between the user area model and the heat source supply station model are traversed, and the corresponding heating pipeline chain is generated, and then the required heating temperature and the real-time indoor temperature are input into the user energy efficiency evaluation model and the corresponding pipe network evaluation model in sequence; According to the user area model and the pipeline network assessment model, the required heat between each pair of heating detection time points is hierarchically summarized, and the summary results are input into the heat source supply station model, and then the heat source supply station model outputs the required fuel quantity according to the summary results.

9. The method for constructing a simulation model for district heating efficiency evaluation according to claim 8, characterized in that: The process of detecting whether there are abnormalities in the transmission and distribution network includes: According to the real-time flow curve of each pipe section unit, the estimated pipeline pressure value of each pipe section unit is obtained, the pipe pressure change detection interval is set, and the estimated pipeline pressure value is compared with the corresponding real-time pipeline pressure change value. If the difference between the real-time pipeline pressure change value and the pressure exceeding the threshold value is within the pipe pressure change detection interval, no operation is performed, otherwise it is judged that the corresponding pipe section unit has an abnormality.

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