A method and apparatus for regulating a heating network

Abstract

The application provides a heat supply network adjusting method and device, which comprises the following steps: determining the proportion of resident users in a heat supply area; when the proportion of resident users is less than a proportion threshold, predicting the heat supply load of the heat supply area to obtain the predicted heat supply load of the heat supply area; when the proportion of resident users is greater than or equal to the proportion threshold, determining the area type of the heat supply area; determining the heat supply satisfaction degree based on the area type of the heat supply area; predicting the load of resident users and industrial users to obtain the predicted resident load and the predicted industrial load; correcting the predicted resident load by the heat supply satisfaction degree, and determining the predicted heat supply load of the heat supply area by the predicted industrial load and the corrected predicted resident load; comparing the predicted heat supply load with the actual heat supply load of the heat supply network, and controlling the distributed energy storage system to adjust the heat supply network according to the comparison result, so that the time lag of the heat supply network regulation is shortened, and the response capacity of the heat supply network is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of coal-fired heating technology, and particularly relates to a heat network regulation method and device. BACKGROUND

[0002] Currently, the city heat network usually realizes the balance regulation of water power and heat by adjusting the temperature, flow, pressure and other parameters of the heat network fluid medium. The adjusted parameters can be multiple or one.

[0003] However, whether adjusting multiple parameters or a single parameter will have a lag, that is, from the heat source to make a strategy to change the fluid operating parameters, there is a certain delay for the heat network fluid of the new working condition to reach the heat exchange station. For the heat exchange station close to the heat source, the adjustment effect may be produced after half an hour, while for the heat exchange station at the end of the heat network, the adjustment effect may be produced after several hours, and the existing adjustment mode for the heat network has high lag. SUMMARY

[0004] Therefore, the embodiments of the present application provide a heat network regulation method and device to solve the problem of high lag of the existing adjustment mode for the heat network.

[0005] To achieve the above object, the embodiments of the present application provide the following technical scheme:

[0006] The first aspect of the embodiments of the present application discloses a heat network regulation method, which comprises:

[0007] Based on the load type of the heat supply area of the heat network regulation system, the proportion of the residential user in the heat supply area is determined;

[0008] When the proportion of the residential user is less than the proportion threshold, the heat supply load of the heat supply area is predicted to obtain the predicted heat supply load of the heat supply area;

[0009] When the proportion of the residential user is greater than or equal to the proportion threshold, the area type of the heat supply area is determined based on the complaint rate of the residential user and the heat supply parameter of the heat supply area;

[0010] The heat supply satisfaction degree is determined based on the area type of the heat supply area;

[0011] The load of the residential user is predicted to obtain the predicted residential load, and the load of the industrial user in the heat supply area is predicted to obtain the predicted industrial load;

[0012] The predicted residential load is corrected by the heat supply satisfaction degree, and the predicted heat supply load of the heat supply area is determined by using the predicted industrial load and the corrected predicted residential load;

[0013] comparing the predicted heat supply load of the heat supply area and the actual heat supply load of the heat supply network of the heat network regulation system, and controlling the preset distributed energy storage system to regulate the heat supply network according to the comparison result, the distributed energy storage system being constructed based on a boiler room.

[0014] Preferably, the comparison of the predicted heat supply load of the heat supply area and the actual heat supply load of the heat supply network of the heat network regulation system comprises:

[0015] calculating an absolute value of a difference between the predicted heat supply load of the heat supply area and the actual heat supply load of the heat supply network of the heat network regulation system to obtain a load error;

[0016] if the load error is less than a first threshold value, the heat storage function and the heat release function of the distributed energy storage system are not started;

[0017] if the load error is greater than or equal to a second threshold value, when the predicted heat supply load is greater than the actual heat supply load, the heat release function of the distributed energy storage system is started to provide heat to the heat supply network, and when the predicted heat supply load is less than the actual heat supply load, the heat storage function of the distributed energy storage system is started to store heat using the heat of the heat supply network;

[0018] if the load error is greater than a third threshold value and less than the second threshold value, a timer is started; when the timer time is greater than a time threshold value and the predicted heat supply load is greater than the actual heat supply load, the heat release function of the distributed energy storage system is started to provide heat to the heat supply network, and when the timer time is greater than the time threshold value and the predicted heat supply load is less than the actual heat supply load, the heat storage function of the distributed energy storage system is started to store heat using the heat of the heat supply network;

[0019] wherein the third threshold value is greater than the first threshold value, and the third threshold value is less than the second threshold value.

[0020] Preferably, when the proportion of the residential users is greater than or equal to the proportion threshold value, the area type of the heat supply area is determined based on the complaint rate of the residential users and the heat supply parameters of the heat supply area, comprising:

[0021] when the proportion of the residential users is greater than or equal to the proportion threshold value, if the complaint rate of the residential users is less than a complaint rate threshold value, the area type of the heat supply area is determined to be a general heat supply area;

[0022] If the complaint rate of the resident user is greater than or equal to the complaint rate threshold, an evaluation result of the complaint rate is constructed according to the heating parameters of the heating area, and the area type of the heating area is determined as a problem heating area or another heating area.

[0023] Preferably, if the complaint rate of the resident user is greater than or equal to the complaint rate threshold, an evaluation result of the complaint rate is constructed according to the heating parameters of the heating area, and the area type of the heating area is determined as a problem heating area or another heating area, comprising:

[0024] If the complaint rate of the resident user is greater than or equal to the complaint rate threshold, the heating parameters of the heating area are input into a first model trained in advance to make the first model output a heating evaluation value;

[0025] When the heating evaluation value is less than a first set evaluation value, it is determined that the complaint rate is true and the area type of the heating area is determined as a problem heating area, and an evaluation result of the complaint rate is constructed according to the heating evaluation value;

[0026] When the heating evaluation value is greater than or equal to the first set evaluation value, the user parameters of the heating area are input into a second model trained in advance to make the second model output a user evaluation value;

[0027] When the user evaluation value is less than a second set evaluation value, it is determined that the complaint rate is true and the area type of the heating area is determined as a problem heating area, and an evaluation result of the complaint rate is constructed according to the heating evaluation value and the user evaluation value;

[0028] When the user evaluation value is greater than or equal to the second set evaluation value, a comprehensive evaluation value is determined based on the heating evaluation value and the user evaluation value;

[0029] A similar heating area similar to the heating area is determined through the comprehensive evaluation value, if it is determined that the complaint rate is true based on an actual complaint rate in the similar heating area, it is determined that the complaint rate is true and the area type of the heating area is determined as a problem heating area, and an evaluation result of the complaint rate is constructed according to the comprehensive evaluation value;

[0030] If it is determined that the complaint rate is false based on the actual complaint rate in the similar heating area, historical failure rates and running times of heating equipment and temperature collection equipment of the heating area are input into a third model trained in advance to make the third model output an equipment evaluation value;

[0031] determining that the complaint rate is true and determining that the area type of the heating area is a problem heating area, and constructing an evaluation result of the complaint rate according to the equipment evaluation value, the heating evaluation value and the user evaluation value when the equipment evaluation value is less than a third set evaluation value;

[0032] determining that the complaint rate is false and determining that the area type of the heating area is other heating area, and constructing an evaluation result of the complaint rate according to the equipment evaluation value, the heating evaluation value and the user evaluation value when the equipment evaluation value is greater than or equal to the third set evaluation value.

[0033] Preferably, the heating satisfaction degree is determined based on the area type of the heating area, comprising:

[0034] determining the heating satisfaction degree based on the evaluation result, the heating area and the complaint rate in combination with a preset evaluation model when the area type of the heating area is the problem heating area;

[0035] calculating a product of the evaluation result and the complaint rate, and calculating a difference between 1 and the product to obtain the heating satisfaction degree when the area type of the heating area is the other heating area;

[0036] setting the heating satisfaction degree as a preset value when the area type of the heating area is the general heating area.

[0037] Preferably, the load amount of the resident user is predicted to obtain a predicted resident load amount, and the load amount of the industrial user in the heating area is predicted to obtain a predicted industrial load amount, comprising:

[0038] obtaining an input set and an industrial data set, the input set at least containing temperature, humidity, hours and dates corresponding to a predicted time point, and the industrial data set at least containing hours and dates corresponding to the predicted time point;

[0039] inputting the input set into a resident load prediction model which is obtained by pre-training, and obtaining a prediction result related to the area type of the heating area output by the resident load prediction model as the predicted resident load amount;

[0040] inputting the industrial data set into an industrial load prediction model which is obtained by pre-training, and enabling the industrial load prediction model to output the predicted industrial load amount.

[0041] The second aspect of the embodiment of the present application discloses a heat network adjusting device, comprising:

[0042] a first determining unit configured to determine a proportion of resident users in a heating area of a heat network adjusting system based on a load type of the heating area;

[0043] a first prediction unit configured to predict a heating load of the heating area to obtain a predicted heating load of the heating area when the proportion of the resident users is less than a proportion threshold;

[0044] a second determination unit configured to determine a region type of the heating area based on a complaint rate of the resident users and a heating parameter of the heating area when the proportion of the resident users is greater than or equal to the proportion threshold;

[0045] a third determination unit configured to determine a heating satisfaction degree based on the region type of the heating area;

[0046] a second prediction unit configured to predict a load of the resident users to obtain a predicted resident load and predict a load of industrial users in the heating area to obtain a predicted industrial load;

[0047] a processing unit configured to correct the predicted resident load by using the heating satisfaction degree and determine the predicted heating load of the heating area by using the predicted industrial load and the corrected predicted resident load;

[0048] an adjusting unit configured to compare the predicted heating load of the heating area with an actual heating load of a heat distribution network of a heat network adjusting system, and control a pre-set distributed energy storage system to adjust the heat distribution network according to a comparison result, the distributed energy storage system being constructed based on a boiler room.

[0049] Preferably, the adjusting unit comprises:

[0050] a calculation module configured to calculate an absolute value of a difference between the predicted heating load of the heating area and the actual heating load of the heat distribution network of the heat network adjusting system to obtain a load error;

[0051] a first control module configured to start neither a heat storage function nor a heat release function of the distributed energy storage system if the load error is less than a first threshold;

[0052] a second control module configured to start the heat release function of the distributed energy storage system to provide heat to the heat distribution network if the predicted heating load is greater than the actual heating load and start the heat storage function of the distributed energy storage system to store heat by using heat of the heat distribution network if the predicted heating load is less than the actual heating load when the load error is greater than or equal to a second threshold;

[0053] a third control module, configured to start timing if the load error is greater than a third threshold value and less than the second threshold value, start a heat release function of the distributed energy storage system to provide heat to the heat supply network when the timing time is greater than a time threshold value and the predicted heat supply load is greater than the actual heat supply load, and start a heat storage function of the distributed energy storage system to store heat using heat of the heat supply network when the timing time is greater than the time threshold value and the predicted heat supply load is less than the actual heat supply load.

[0054] Preferably, the third threshold value is greater than the first threshold value and less than the second threshold value.

[0055] Preferably, the second determination unit comprises:

[0056] a first determination module, configured to determine that the region type of the heat supply region is a general heat supply region if the complaint rate of the residential user is less than a complaint rate threshold value when the proportion of the residential user is greater than or equal to the proportion threshold value.

[0057] a second determination module, configured to construct an evaluation result of the complaint rate according to the heat supply parameter of the heat supply region and determine that the region type of the heat supply region is a problem heat supply region or another heat supply region if the complaint rate of the residential user is greater than or equal to the complaint rate threshold value.

[0058] Preferably, the second determination module is specifically configured to:

[0059] input the heat supply parameter of the heat supply region into a first model trained in advance to make the first model output a heat supply evaluation value if the complaint rate of the residential user is greater than or equal to the complaint rate threshold value.

[0060] determine that the complaint rate is true and determine that the region type of the heat supply region is a problem heat supply region when the heat supply evaluation value is less than a first set evaluation value, and construct an evaluation result of the complaint rate according to the heat supply evaluation value.

[0061] input a user parameter of the heat supply region into a second model trained in advance to make the second model output a user evaluation value if the heat supply evaluation value is greater than or equal to the first set evaluation value.

[0062] determine that the complaint rate is true and determine that the region type of the heat supply region is a problem heat supply region when the user evaluation value is less than a second set evaluation value, and construct an evaluation result of the complaint rate according to the heat supply evaluation value and the user evaluation value.

[0063] determine a comprehensive evaluation value based on the heat supply evaluation value and the user evaluation value when the user evaluation value is greater than or equal to the second set evaluation value.

[0064] determining a similar heating area similar to the heating area according to the comprehensive evaluation value, determining the complaint rate as true based on an actual complaint rate in the similar heating area, determining the complaint rate as true and determining the area type of the heating area as a problem heating area, and constructing an evaluation result of the complaint rate according to the comprehensive evaluation value;

[0065] if the complaint rate is determined as false based on the actual complaint rate in the similar heating area, inputting a historical failure rate and an operation time of a heating device and a temperature collection device of the heating area into a third model pre-trained to make the third model output a device evaluation value;

[0066] when the device evaluation value is less than a third set evaluation value, determining the complaint rate as true and determining the area type of the heating area as a problem heating area, and constructing an evaluation result of the complaint rate according to the device evaluation value, the heating evaluation value and the user evaluation value;

[0067] when the device evaluation value is greater than or equal to the third set evaluation value, determining the complaint rate as false and determining the area type of the heating area as another heating area, and constructing an evaluation result of the complaint rate according to the device evaluation value, the heating evaluation value and the user evaluation value.

[0068] Based on the above-mentioned heating network regulation method and device provided by the embodiment of the present application, the method is: based on the load type of the heating area of the heating network regulation system, determining the proportion of the residential user in the heating area; when the proportion of the residential user is less than the proportion threshold, predicting the heating load of the heating area to obtain the predicted heating load of the heating area; when the proportion of the residential user is greater than or equal to the proportion threshold, determining the area type of the heating area based on the complaint rate of the residential user and the heating parameter of the heating area; determining the heating satisfaction degree based on the area type of the heating area; predicting the load of the residential user to obtain the predicted residential load, and predicting the load of the industrial user in the heating area to obtain the predicted industrial load; correcting the predicted residential load by the heating satisfaction degree, and determining the predicted heating load of the heating area by using the predicted industrial load and the corrected predicted residential load; comparing the predicted heating load of the heating area and the actual heating load of the heat distribution network of the heating network regulation system, and controlling the pre-set distributed energy storage system to regulate the heat distribution network according to the comparison result. In the present scheme, the predicted heating load of the heating area is predicted, the predicted heating load and the actual heating load are compared, and the distributed energy storage system is controlled to regulate the heat distribution network according to the comparison result, which can shorten the time lag of the heat distribution network regulation, thereby improving the response capability of the heat distribution network. BRIEF DESCRIPTION OF DRAWINGS

[0069] In order 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 needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only represent some embodiments of the present application, and for those skilled in the art, other drawings can be obtained based on the provided drawings without any creative effort.

[0070] Figure 1 A flow chart of a heat network regulation method provided for the embodiments of the present application;

[0071] Figure 2 A flow chart of regulating a heat network provided for the embodiments of the present application;

[0072] Figure 3 A flow chart of determining a region type of a heat supply region provided for the embodiments of the present application;

[0073] Figure 4 A principle example diagram of a heat network regulation method provided for the embodiments of the present application;

[0074] Figure 5 A structure block diagram of a heat network regulation device provided for the embodiments of the present application. DETAILED DESCRIPTION

[0075] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only represent some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort fall within the protection scope of the present application.

[0076] In the present application, the term “comprising”, “containing” or any other variant thereof is intended to cover the non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or includes the elements inherent to such process, method, article or equipment. Without more limitations, the element defined by the sentence “including a…” does not exclude the presence of other identical elements in the process, method, article or equipment including the element.

[0077] The inventors have found through research that in order to vigorously promote low-carbon economy and adjust energy structure, a large number of boiler houses in cities are demolished or transformed in various regions, and the heating of many regions relies on the boiler houses distributed in the urban areas. With the demolition or transformation of the boiler houses, the city heat supply network is gradually expanded, and cogeneration and clean energy gradually replace the boiler houses, and the boiler houses in various regions are also closed, but many regions have not demolished the abandoned boiler houses, and have not reasonably utilized the abandoned boiler houses. At the same time, with the expansion of the city heat supply network, the time lag of the heat supply network regulation and control is greater (which can reach hours).

[0078] At present, the city heat supply network usually realizes the balance regulation of water power and heat by adjusting the temperature, flow, pressure and other parameters of the heat supply network fluid medium, and the adjusted parameters can be multiple or one. However, whether multiple parameters or a single parameter is adjusted, there will be a lag, that is, from the heat source, the strategy is made to change the fluid operating parameters, and there is a certain delay for the heat supply network fluid in the new working condition to reach the heat exchange station. For the heat exchange station close to the heat source, the adjustment effect may be produced after half an hour, while for the heat exchange station at the end of the heat supply network, the adjustment effect may be produced after several hours, and the lag is very obvious.

[0079] Therefore, the present scheme proposes to establish a distributed energy storage system by using the abandoned boiler house (establish an energy storage system in the abandoned boiler house), compare the predicted heating load and the actual heating load after the predicted heating load of the heating area is predicted, and control the distributed energy storage system to regulate the heat supply network according to the comparison result, so as to shorten the time lag of the heat supply network regulation and control, thereby improving the response capability of the heat supply network.

[0080] Referring to Figure 1 , a flow chart of a heat network regulation method provided by an embodiment of the present application is shown, and the heat network regulation method comprises the following steps:

[0081] Step S101: determining the proportion of residential users in the heating area of the heat network regulation system based on the load type of the heating area.

[0082] In the process of specifically implementing step S101, the load type of the heating area of the heat network regulation system is obtained, and the proportion of industrial users and the proportion of residential users in the heating area are determined based on the load type.

[0083] The proportion of residential users and the proportion threshold are compared. When the proportion of residential users is less than the proportion threshold, it is indicated that the heating satisfaction degree does not need to be considered, and steps S102 and S107 are executed.

[0084] When the proportion of residential users is greater than or equal to the proportion threshold, it is indicated that the heating satisfaction degree needs to be considered, and steps S103 to S107 are executed.

[0085] It should be noted that the above-mentioned proportion threshold can be determined according to the historical heating load of the heating area and the complaint rate of the resident user; specifically, the proportion threshold can be determined by constructing a mathematical model.

[0086] Step S102: When the proportion of the resident user is less than the proportion threshold, the heating load of the heating area is predicted to obtain the predicted heating load of the heating area; step S107 is performed.

[0087] In the process of specifically implementing step S102, when the proportion of the resident user is less than the proportion threshold, it is represented that the heating satisfaction degree does not need to be considered, at this time, the heating load of the heating area is dynamically predicted based on the heat network regulation system, thereby obtaining the predicted heating load of the heating area, and step S107 is performed.

[0088] Specifically, the heating load of the heating area can be dynamically predicted by the pre-trained load prediction model to obtain the predicted heating load.

[0089] Step S103: When the proportion of the resident user is greater than or equal to the proportion threshold, the area type of the heating area is determined based on the complaint rate of the resident user and the heating parameter of the heating area.

[0090] It should be noted that the area type of the heating area can be divided into a screening heating area and a general heating area; further, the screening heating area is divided into a problem heating area and other heating areas. That is, the area type of the heating area can be a general heating area, a problem heating area or other heating areas.

[0091] More specifically, the screening heating area has a higher complaint rate of the resident user, and the general heating area has a lower complaint rate of the resident user; since the "complaint rate is high" may be false, the screening heating area can be further divided into a problem heating area and other heating areas without problems by the heating parameter, wherein if the heating parameter is normal, it can be determined that the "complaint rate is high" is false.

[0092] In the process of specifically implementing step S103, when the proportion of the resident user is greater than or equal to the proportion threshold, the complaint rate of the resident user is compared with the complaint rate threshold.

[0093] If the complaint rate of the resident user is less than the complaint rate threshold, the area type of the heating area is determined as a general heating area.

[0094] If the complaint rate of the resident user is greater than or equal to the complaint rate threshold, the heating area is represented as a screening heating area, at this time, the complaint rate is evaluated according to the heating parameter of the heating area to obtain an evaluation result (that is, the evaluation result is constructed), and the area type of the heating area is determined to be a problem heating area or other heating area based on the heating parameter.

[0095] Specifically, how to determine the area type of the heating area and how to construct the evaluation result will be described in detail in the following embodiment of the present application. Figure 3

[0096] Step S104: determining the heating satisfaction degree based on the area type of the heating area.

[0097] It should be noted that when determining the heating satisfaction degree, different satisfaction evaluation methods are used for the problem heating area, the other heating area and the general heating area to determine the heating satisfaction degree.

[0098] In the process of implementing step S104, the satisfaction evaluation method corresponding to the area type of the heating area is used to determine the heating satisfaction degree.

[0099] Specifically, when the area type of the heating area is a problem heating area, the heating satisfaction degree is determined based on the evaluation result, the heating area and the complaint rate, combined with a preset evaluation model; wherein the preset evaluation model can be an evaluation model using PSO-lstm algorithm. The larger the evaluation result, the smaller the heating area and the smaller the complaint rate, the greater the heating satisfaction degree.

[0100] It should be noted that the larger the heating area and the smaller the evaluation result, the worse the accuracy of the complaint rate. When the heating area becomes larger, some resident users may feel troublesome and do not make complaints, so the heating satisfaction degree is smaller.

[0101] When the area type of the heating area is other heating area, the product of the evaluation result and the complaint rate (the complaint rate of the resident user) is calculated, and the difference between 1 and the product is calculated to obtain the heating satisfaction degree; that is, the heating satisfaction degree = 1 - evaluation result * complaint rate.

[0102] When the area type of the heating area is a general heating area, the heating satisfaction degree is set to a preset value; for example: when the area type of the heating area is a general heating area, the heating satisfaction degree is set to 1.

[0103] Step S105: predicting the load of the resident user to obtain a predicted resident load, and predicting the load of the industrial user in the heating area to obtain a predicted industrial load.

[0104] ​In the implementation of step S105, an input set and an industrial data set are obtained, the input set at least including temperature, humidity, hours and date (date type) corresponding to the prediction time point, and the industrial data set at least including hours and date corresponding to the prediction time point.

[0105] It should be noted that the prediction time point is a time point at which the load needs to be predicted (equivalent to which time point the load needs to be predicted).

[0106] The input set is input into the pre-trained resident load prediction model, and the prediction result related to the region type of the heating region output by the resident load prediction model is obtained as the predicted resident load.

[0107] It should be noted that the resident load prediction model can be a prediction model using the PSO-lstm algorithm; after the input set is input into the resident load prediction model, the resident load prediction model will output the prediction result (load prediction result) corresponding to each region type; at this time, the prediction result related to the region type of the heating region is selected as the predicted resident load.

[0108] For example: after the input set is input into the resident load prediction model, the resident load prediction model will output the prediction result of the problem heating region, the prediction result of other heating regions, and the prediction result of the general heating region; if the region type of the heating region is a general heating region, the prediction result of the general heating region is determined as the predicted resident load.

[0109] The industrial data set is input into the pre-trained industrial load prediction model, so that the industrial load prediction model outputs the predicted industrial load.

[0110] It should be noted that the industrial load prediction model can be a prediction model using the PSO-lstm algorithm.

[0111] Step S106: correcting the predicted resident load by the heating satisfaction, and determining the predicted heating load of the heating region by the predicted industrial load and the corrected predicted resident load.

[0112] In the implementation of step S106, after the predicted resident load and the predicted industrial load are predicted, the predicted resident load is corrected by the heating satisfaction determined in step S104.

[0113] Specifically, the heating satisfaction and the predicted resident load are multiplied to obtain the corrected predicted resident load.

[0114] The predicted industrial load and the corrected predicted resident load are added to obtain the predicted heating load of the heating region.

[0115] Step S107: Comparing the predicted heat supply load of the heat supply area and the actual heat supply load of the heat supply network of the heat network regulation system, and controlling the preset distributed energy storage system to regulate the heat supply network according to the comparison result.

[0116] It should be noted that the distributed energy storage system is constructed based on the boiler room, that is, the distributed energy storage system is constructed in advance by using the boiler room; the constructed distributed energy storage system is connected to the heat supply network; the distributed energy storage system can provide heat to the heat supply network, and can also store heat by using the heat of the heat supply network.

[0117] In the process of specifically implementing step S107, after the predicted heat supply load of the heat supply area is determined through step S102 or through steps S103 to S107, the predicted heat supply load of the heat supply area is compared with the actual heat supply load of the heat supply network of the heat network regulation system, and the distributed energy storage system is controlled to regulate the heat supply network according to the comparison result.

[0118] Specifically, according to the comparison result of the predicted heat supply load and the actual heat supply load, the start and stop of the heat storage function and the heat release function of the distributed energy storage system are controlled, so as to realize the regulation of the heat supply network.

[0119] It should be noted that the actual heat supply load refers to the heat actually provided by the heat station to the heat supply network, and the heat supply network in the present scheme can be a long heat supply network (long-distance heat supply network).

[0120] In the embodiment of the present application, the predicted heat supply load of the heat supply area is predicted, the predicted heat supply load is compared with the actual heat supply load, and the distributed energy storage system is controlled to regulate the heat supply network according to the comparison result, so as to shorten the time lag of the regulation of the heat supply network, thereby improving the response capability of the heat supply network. In addition, the predicted resident load is corrected by using the heat supply satisfaction, which not only improves the regulation effect but also considers the demand of users, thereby improving the satisfaction of users to the heating.

[0121] The above embodiment of the present application Figure 1 The process of regulating the heat supply network in step S107 is described in detail below with reference to Figure 2 , which shows a flowchart of regulating the heat supply network according to an embodiment of the present application, Figure 2 including the following steps:

[0122] Step S201: Calculating the absolute value of the difference between the predicted heat supply load of the heat supply area and the actual heat supply load of the heat supply network of the heat network regulation system to obtain a load error.

[0123] In the process of implementing step S201, the absolute value of the difference between the predicted heat supply load of the heat supply area and the actual heat supply load of the heat supply network of the heat network regulation system is calculated, and the absolute value is taken as a load error; the load error can be used to represent the error between the predicted heat supply load and the actual heat supply load, that is, the error between the predicted heat supply load and the actual heat provided by the heating station to the heat supply network.

[0124] The load error is compared with the first threshold value, the second threshold value and the third threshold value respectively. The third threshold value is greater than the first threshold value, and the third threshold value is less than the second threshold value.

[0125] If the load error is less than the first threshold value, step S202 is executed; if the load error is greater than or equal to the second threshold value, step S203 is executed; if the load error is greater than the third threshold value and less than the second threshold value, step S204 is executed.

[0126] Step S202: If the load error is less than the first threshold value, the heat storage function and the heat release function of the distributed energy storage system are not started.

[0127] In the process of implementing step S202, if the load error is less than the first threshold value, the heat storage function and the heat release function of the distributed energy storage system are not started, that is, the distributed energy storage system does not establish a heat storage process and does not establish a heat release process.

[0128] Specifically, if the load error is less than the first threshold value, it indicates that the predicted heat supply load and the actual heat supply load are not much different, and are within the allowable range, so that the heat supply network does not need to be adjusted.

[0129] Step S203: If the load error is greater than or equal to the second threshold value, when the predicted heat supply load is greater than the actual heat supply load, the heat release function of the distributed energy storage system is started to provide heat to the heat supply network, and when the predicted heat supply load is less than the actual heat supply load, the heat storage function of the distributed energy storage system is started to store heat using the heat of the heat supply network.

[0130] In the process of implementing step S203, if the load error is greater than or equal to the second threshold value, the heat storage function or the heat release function of the distributed energy storage system is started, that is, the distributed energy storage system establishes a heat storage process or a heat release process.

[0131] Specifically, if the load error is greater than or equal to the second threshold value, when the predicted heat supply load is greater than the actual heat supply load, the heat release function of the distributed energy storage system is started to provide heat to the heat supply network (the distributed energy storage system establishes a heat release process).

[0132] When the predicted heat supply load is less than the actual heat supply load, the heat storage function of the distributed energy storage system is started to store heat using the heat of the heat supply network (the distributed energy storage system establishes a heat storage process).

[0133] In general, if the load quantity error is greater than or equal to the second threshold value, it indicates that the difference between the predicted heat supply load quantity and the actual heat supply load quantity is large, and it is not within the allowable range, at which time the heat supply network needs to be adjusted.

[0134] In some embodiments, the distributed energy storage system can also be selected to be equipped with an electric heating device or a heat pump to utilize valley electricity or abandoned electricity for secondary heat supply at night.

[0135] Step S204: If the load quantity error is greater than the third threshold value and less than the second threshold value, start timing; when the timing time is greater than the time threshold value and the predicted heat supply load quantity is greater than the actual heat supply load quantity, start the heat release function of the distributed energy storage system to provide heat to the heat supply network, and when the timing time is greater than the time threshold value and the predicted heat supply load quantity is less than the actual heat supply load quantity, start the heat storage function of the distributed energy storage system to utilize the heat of the heat supply network for heat storage.

[0136] In the process of implementing step S204, if the load quantity error is greater than the third threshold value and less than the second threshold value, the heat network adjustment system starts timing; when the timing time is greater than the time threshold value; start the heat storage function or the heat release function of the distributed energy storage system, that is, the distributed energy storage system establishes a heat storage process or a heat release process.

[0137] Specifically, when the timing time is greater than the time threshold value and the predicted heat supply load quantity is greater than the actual heat supply load quantity, the heat release function of the distributed energy storage system is started to provide heat to the heat supply network (the distributed energy storage system establishes a heat release process).

[0138] When the timing time is greater than the time threshold value and the predicted heat supply load quantity is less than the actual heat supply load quantity, the heat storage function of the distributed energy storage system is started to utilize the heat of the heat supply network for heat storage (the distributed energy storage system establishes a heat storage process).

[0139] In general, if the load quantity error is greater than the third threshold value and less than the second threshold value (equivalent to being between the second threshold value and the first threshold value and greater than the third threshold value), although the load quantity error is not large at this time, a long time will cause a certain waste, so the timing needs to be done first, and after the timing time is greater than the time threshold value, the distributed energy storage system establishes a heat storage process or a heat release process.

[0140] It should be noted that the first threshold value mentioned above can be set to 1% of the rated heat supply quantity, the second threshold value can be set to 3% of the rated heat supply quantity, the third threshold value can be set to 2% of the rated heat supply quantity, and the time threshold value can be set to 10 minutes.

[0141] It should be further explained that the setting of the first threshold value, the second threshold value, the third threshold value and the time threshold value is related to environmental factors, and the first threshold value, the second threshold value, the third threshold value and the time threshold value can be corrected according to environmental conditions and heat supply conditions.

[0142] For example, as the cold weather intensifies, when it is monitored that the predicted heat supply load of the heat supply area is less than the actual heat supply load, the first threshold value, the second threshold value and the third threshold value at this time will increase with the decrease of the outdoor temperature, and the time threshold value will decrease with the decrease of the outdoor temperature, thereby increasing the heat supply while reducing unnecessary waste, thereby ensuring the heating demand of the residents.

[0143] In addition, the first threshold value, the second threshold value, the third threshold value and the time threshold value can also be corrected again according to the building model of the high-cold region.

[0144] For example, the distribution ratio of new and old communities is used to further control, A = old community area / new community area; as A increases, the heat to be provided is higher, because the heat preservation effect of the old community is relatively poor, and the heat output needs to be further improved to ensure the heating of the residents; the predicted heat supply load of the heat supply area is generally greater than the actual heat supply load. Therefore, as A increases, the first threshold value, the second threshold value and the third threshold value will increase, and the time threshold value will decrease; by increasing the first threshold value, the second threshold value and the third threshold value, the heat output of the heat supply network is increased (equivalent to increasing the heat supply).

[0145] Through the above content, by using the comprehensive factors in connection with the actual situation, the heating demand can be ensured, and the energy waste can be reduced. By using the wide distribution of the distributed energy storage system, the precise control of the heating can be further realized.

[0146] It should be noted that the distributed energy storage system is widely arranged in each area of the city heat network, has the advantage of being close to the residents, can precisely control the heat supply network, and can shorten the time lag of the heat supply network control, so that the effect of the control is advanced; in addition, since the distributed energy storage system is widely distributed, the region can be finely adjusted according to the conditions of the region, which can affect the overall output of the heat supply network and meet the demand of the region, thereby realizing the precise control of the heat supply network.

[0147] The above embodiment of the present application Figure 1 The content of step S103 of determining the area type of the heat supply area is described with reference to Figure 3 , which shows the flowchart of determining the area type of the heat supply area provided by the embodiment of the present application, Figure 3 including the following steps:

[0148] Step S301: When the proportion of resident users is greater than or equal to the proportion threshold, it is determined whether the complaint rate of the resident users is less than the complaint rate threshold. If the complaint rate of the resident users is less than the complaint rate threshold, step S302 is executed; if the complaint rate of the resident users is greater than or equal to the complaint rate threshold, step S303 is executed.

[0149] In the implementation of step S301, when the proportion of resident users is greater than or equal to the proportion threshold, the complaint rate of the resident users is compared with the complaint rate threshold to determine whether the complaint rate of the resident users is less than the complaint rate threshold.

[0150] If the complaint rate of the resident users is less than the complaint rate threshold, step S302 is executed to determine that the region type of the heating region is a general heating region.

[0151] If the complaint rate of the resident users is greater than or equal to the complaint rate threshold, it is first determined that the heating region is a screening heating region, and step S303 is executed to construct an evaluation result of the complaint rate and further determine that the region type of the heating region is a problem heating region or another heating region.

[0152] In some embodiments, the complaint rate threshold can be selected as a value of 10% or less. The screening heating region can be a single resident community or a resident community using the same heating pipeline.

[0153] Step S302: Determine that the region type of the heating region is a general heating region.

[0154] In the implementation of step S302, if the complaint rate of the resident users is less than the complaint rate threshold, it is determined that the region type of the heating region is a general heating region.

[0155] Step S303: Construct an evaluation result of the complaint rate according to the heating parameters of the heating region, and determine that the region type of the heating region is a problem heating region or another heating region.

[0156] In the implementation of step S303, if the complaint rate of the resident users is greater than or equal to the complaint rate threshold, an evaluation result of the complaint rate is constructed according to the heating parameters of the heating region, and it is determined that the region type of the heating region is a problem heating region or another heating region; the specific construction of the evaluation result and the determination of the region type of the heating region are shown in the following processes A1 to A9.

[0157] A1, if the complaint rate of the resident users is greater than or equal to the complaint rate threshold, the heating parameters of the heating region are obtained; the heating parameters include heating capacity, water supply temperature, return water temperature, water supply flow, return water flow, etc. The heating parameters of the heating region are input into a first model trained in advance to make the first model output a heating evaluation value of the heating region.

[0158] It should be noted that the first model can be a model using the PSO-lstm algorithm; how to build the first model is explained through the following processes B1 to B6.

[0159] B1, divide the original data to obtain a training set and a test set, and standardize the training set and the test set.

[0160] B2, set the PSO algorithm parameters, specifically, determine the particle swarm dimension, population size, iteration number, learning factor, and inertia weight value interval.

[0161] B3, introduce an improved Tent chaotic mapping to initialize the position and speed of the PSO particle, and take the average of the root mean squared error (RMSE) and the mean absolute error (MAE) between the predicted value and the true value of the test set in the long short-term memory (LSTM) model as the fitness function value.

[0162] B4, mark the current position of each particle and calculate the corresponding fitness function value to determine the individual extreme value and the population optimal value.

[0163] B5, introduce an adaptive inertia weight factor in the main loop iteration of the basic PSO algorithm, constantly update the particle inertia weight value, particle speed and position, and calculate the new fitness function value to determine the individual extreme value and the population optimal value of the updated particle.

[0164] The calculation formula of the adaptive inertia weight factor is as formula (1)

[0165]

[0166] In formula (1), is the fitness value of the mth iteration of the population particle x i , is the average fitness value of all particles at the mth iteration, f min m is the minimum fitness value of all particles at the mth iteration, ω max and ω min are the preset maximum inertia weight value and the minimum inertia weight value, ω max and ω min may be 0.85 and 0.35 respectively.

[0167] B6, after meeting the set maximum iteration number, input the optimal hyperparameter combination into the LSTM model to build the first model.

[0168] The above processes B1 to B6 are the construction process of the first model.

[0169] A2, when the heating evaluation value is less than the first set evaluation value, determining that the complaint rate is true and determining that the area type of the heating area is a problem heating area, and constructing an evaluation result of the complaint rate according to the heating evaluation value.

[0170] Specifically, whether the complaint rate of the resident user is true is judged based on the heating evaluation value. If the heating evaluation value is less than the first set evaluation value, it is determined that the complaint rate is true and that the area type of the heating area is a problem heating area, and an evaluation result of the complaint rate is constructed according to the heating evaluation value. Otherwise, if the heating evaluation value is greater than or equal to the first set evaluation value, A3 is entered.

[0171] A3, when the heating evaluation value is greater than or equal to the first set evaluation value, obtaining a user parameter of the heating area, the user parameter including occupancy rate, floor height, number of heating users, building age, etc. The user parameter of the heating area is input into the second model trained in advance to make the second model output a user evaluation value.

[0172] It should be noted that the second model can be constructed based on a neural network, and the construction method of the second model can refer to the construction process of the first model described above, which will not be repeated here.

[0173] A4, when the user evaluation value is less than the second set evaluation value, determining that the complaint rate is true and determining that the area type of the heating area is a problem heating area, and constructing an evaluation result of the complaint rate according to the heating evaluation value and the user evaluation value.

[0174] Specifically, whether the complaint rate of the resident user is true is judged based on the user evaluation value. If the user evaluation value is less than the second set evaluation value, it is determined that the complaint rate is true and that the area type of the heating area is a problem heating area, and an evaluation result of the complaint rate is constructed according to the heating evaluation value and the user evaluation value. Otherwise, if the user evaluation value is greater than or equal to the second set evaluation value, A5 is entered.

[0175] A5, when the user evaluation value is greater than or equal to the second set evaluation value, determining a comprehensive evaluation value based on the heating evaluation value and the user evaluation value.

[0176] Specifically, based on the heating evaluation value and the user evaluation value, the comprehensive evaluation value is determined by combining the analytic hierarchy process or the neural network.

[0177] A6, determining a similar heating area similar to the heating area through the comprehensive evaluation value, and if it is determined that the complaint rate is true based on the actual complaint rate in the similar heating area, it is determined that the complaint rate is true and that the area type of the heating area is a problem heating area, and an evaluation result of the complaint rate is constructed according to the comprehensive evaluation value.

[0178] Specifically, a region with a comprehensive evaluation value close to that of the heating region is determined as a similar heating region similar to the heating region, i.e., the difference between the comprehensive evaluation values of the heating region and the similar heating region is within a preset range.

[0179] According to the actual complaint rate in the similar heating region, it is determined whether the complaint rate of the resident user is true. Specifically, if the complaint rate of the resident user of the heating region is high, but the actual complaint rate in the similar heating region similar to the heating region is low, it indicates that the complaint rate of the resident user is false. If the complaint rate of the resident user of the heating region is high, and the actual complaint rate in the similar heating region similar to the heating region is also high, it indicates that the complaint rate of the resident user is true.

[0180] If it is determined that the complaint rate of the resident user of the heating region is true based on the actual complaint rate in the similar heating region, it is determined that the complaint rate is true, and it is determined that the region type of the heating region is a problem heating region, and the evaluation result of the complaint rate is constructed according to the comprehensive evaluation value.

[0181] If it is determined that the complaint rate of the resident user of the heating region is false based on the actual complaint rate in the similar heating region, A7 is entered.

[0182] A7, if it is determined that the complaint rate is false based on the actual complaint rate in the similar heating region, the historical failure rate and the running time of the heating equipment and the temperature collection equipment of the heating region are input into the third model pre-trained to make the third model output an equipment evaluation value.

[0183] It should be noted that the third model can be constructed based on a neural network, and the construction method of the third model can refer to the construction process of the first model described above, which will not be described here.

[0184] A8, when the equipment evaluation value is less than a third set evaluation value, it is determined that the complaint rate is true, and it is determined that the region type of the heating region is a problem heating region, and the evaluation result of the complaint rate is constructed according to the equipment evaluation value, the heating evaluation value and the user evaluation value.

[0185] A9, when the equipment evaluation value is greater than or equal to the third set evaluation value, it is determined that the complaint rate is false (finally determined that the complaint rate is false), and it is determined that the region type of the heating region is other heating region, and the evaluation result of the complaint rate is constructed according to the equipment evaluation value, the heating evaluation value and the user evaluation value.

[0186] It should be noted that the evaluation result also includes the heating parameter.

[0187] As can be seen from the above A1 to A9, when it is determined that the complaint rate of the heating region is true, it is determined that the region type of the heating region is a problem heating region. When it is still determined that the complaint rate of the heating region is false after A1-A9, it is determined that the region type of the heating region is other heating region.

[0188] The above various embodiments are detailed descriptions of the present scheme, and through the content of the above various embodiments, it can be seen that the present scheme can transform the abandoned boiler room to establish a distributed energy storage system, realizing reuse and reducing unnecessary waste. The distributed energy storage system can utilize the heat of the heat distribution network for heat storage, and the distributed energy storage system can also select to add electric heating equipment or a heat pump to utilize valley electricity or abandoned electricity for secondary heat supplement at night. When the heat distribution network needs to be regulated, the heat network regulation system can directly control the distributed energy storage system to regulate the heat distribution network, and the heat network regulation system can utilize the distributed energy storage system to accurately regulate the heat distribution network according to the heating satisfaction degree and other comprehensive factors, to ensure that the heating effect meets the actual situation, further ensuring the heating quality and more meeting the user demand. The distributed energy storage system is widely arranged in each region of the city heat network, can shorten the time lag of heat distribution network regulation, advance the time of regulation effect, and thus improve the heating stability and rapid response capability of the heat distribution network.

[0189] In practical application, the principle of the heat network regulation method provided by the present scheme is as follows Figure 4 The principle example diagram of the heat network regulation method provided by the embodiment of the present application is shown in the figure; Figure 4 The heat source side and the heat user side are contained in the above-mentioned embodiment of the present application Figures 1 to 3 The principle of the heat network regulation method provided by the present scheme is as follows

[0190] Corresponding to the heat network regulation method provided by the above-mentioned embodiment of the present application, referring to Figure 5 The embodiment of the present application also provides a structure block diagram of a heat network regulation device, which comprises: a first determination unit 501, a first prediction unit 502, a second determination unit 503, a third determination unit 504, a second prediction unit 505, a processing unit 506, and a regulation unit 507.

[0191] The first determination unit 501 is configured to determine the proportion of the resident user in the heating area based on the load type of the heat network regulation system in the heating area.

[0192] The first prediction unit 502 is configured to predict the heating load of the heating area when the proportion of the resident user is less than the proportion threshold, to obtain the predicted heating load of the heating area.

[0193] The second determination unit 503 is configured to determine the area type of the heating area based on the complaint rate of the resident user and the heating parameter of the heating area when the proportion of the resident user is greater than or equal to the proportion threshold.

[0194] The third determination unit 504 is configured to determine the heating satisfaction degree based on the area type of the heating area.

[0195] In specific implementation, the third determination unit 504 is specifically configured to: when the area type of the heating area is the problem heating area, determine the heating satisfaction degree based on the evaluation result, the heating area and the complaint rate, and in combination with a preset evaluation model; when the area type of the heating area is the other heating area, calculate the product of the evaluation result and the complaint rate, and calculate the difference between 1 and the product to obtain the heating satisfaction degree; and when the area type of the heating area is the general heating area, set the heating satisfaction degree as a preset value.

[0196] The second prediction unit 505 is configured to predict the load of the residential user to obtain a predicted residential load, and predict the load of the industrial user in the heating area to obtain a predicted industrial load.

[0197] In specific implementation, the second prediction unit 505 is specifically configured to: obtain an input set and an industrial data set, the input set at least containing temperature, humidity, hours and date corresponding to a prediction time point, and the industrial data set at least containing hours and date corresponding to the prediction time point; input the input set into a residential load prediction model that is pre-trained to obtain a prediction result related to the area type of the heating area output by the residential load prediction model as the predicted residential load; and input the industrial data set into an industrial load prediction model that is pre-trained to make the industrial load prediction model output the predicted industrial load.

[0198] The processing unit 506 is configured to correct the predicted residential load by the heating satisfaction degree, and determine the predicted heating load of the heating area by using the predicted industrial load and the corrected predicted residential load.

[0199] The adjusting unit 507 is configured to compare the predicted heating load of the heating area with an actual heating load of a heat supply network of a heat network adjusting system, and control a preset distributed energy storage system to adjust the heat supply network according to the comparison result, the distributed energy storage system being constructed based on a boiler room.

[0200] In the embodiment of the present application, the predicted heating load of the heating area is predicted, the predicted heating load is compared with the actual heating load, and the distributed energy storage system is controlled to adjust the heat supply network according to the comparison result, so that the time lag of the heat supply network regulation can be shortened, and the response capability of the heat supply network can be improved.

[0201] Preferably, in combination with Figure 5 As shown, the adjusting unit 507 includes a calculation module, a first control module, a second control module and a third control module, and the execution principles of the modules are as follows.

[0202] The computing module is configured to calculate an absolute value of a difference between the predicted heating load of the heating area and an actual heating load of the heat supply network of the heat network regulation system, to obtain a load error.

[0203] The first control module is configured to, if the load error is less than a first threshold value, not start the heat storage function and the heat release function of the distributed energy storage system.

[0204] The second control module is configured to, if the load error is greater than or equal to a second threshold value, start the heat release function of the distributed energy storage system to provide heat to the heat supply network when the predicted heating load is greater than the actual heating load, and start the heat storage function of the distributed energy storage system to store heat using heat of the heat supply network when the predicted heating load is less than the actual heating load.

[0205] The third control module is configured to, if the load error is greater than a third threshold value and less than the second threshold value, start timing; start the heat release function of the distributed energy storage system to provide heat to the heat supply network when the timing time is greater than a time threshold value and the predicted heating load is greater than the actual heating load, and start the heat storage function of the distributed energy storage system to store heat using heat of the heat supply network when the timing time is greater than the time threshold value and the predicted heating load is less than the actual heating load.

[0206] The third threshold value is greater than the first threshold value and less than the second threshold value.

[0207] Preferably, in combination with Figure 5 As shown, the second determining unit 503 includes a first determining module and a second determining module, and the execution principles of the modules are as follows:

[0208] The first determining module is configured to, when the proportion of the residential user is greater than or equal to a proportion threshold value, determine the area type of the heating area as a general heating area if the complaint rate of the residential user is less than a complaint rate threshold value.

[0209] The second determining module is configured to, if the complaint rate of the residential user is greater than or equal to the complaint rate threshold value, construct an evaluation result of the complaint rate according to the heating parameter of the heating area, and determine the area type of the heating area as a problem heating area or another heating area.

[0210] In a specific implementation, the second determining module is specifically configured to:

[0211] If the complaint rate of the residential user is greater than or equal to the complaint rate threshold value, input the heating parameter of the heating area into a first model trained in advance to make the first model output a heating evaluation value;

[0212] When the heating evaluation value is less than a first set evaluation value, determine that the complaint rate is true and determine that the area type of the heating area is a problem heating area, and construct an evaluation result of the complaint rate according to the heating evaluation value.

[0213] when the heat supply evaluation value is greater than or equal to a first set evaluation value, inputting a user parameter of the heat supply area into a second model obtained by pre-training to make the second model output a user evaluation value;

[0214] when the user evaluation value is less than a second set evaluation value, determining that the complaint rate is true and determining that the area type of the heat supply area is a problem heat supply area, and constructing an evaluation result of the complaint rate according to the heat supply evaluation value and the user evaluation value;

[0215] when the user evaluation value is greater than or equal to the second set evaluation value, determining a comprehensive evaluation value based on the heat supply evaluation value and the user evaluation value;

[0216] determining a similar heat supply area similar to the heat supply area through the comprehensive evaluation value, and if it is determined that the complaint rate is true based on an actual complaint rate in the similar heat supply area, determining that the complaint rate is true and determining that the area type of the heat supply area is a problem heat supply area, and constructing the evaluation result of the complaint rate according to the comprehensive evaluation value;

[0217] if it is determined that the complaint rate is false based on the actual complaint rate in the similar heat supply area, inputting a historical failure rate and an operation time of a heat supply equipment and a temperature collection equipment of the heat supply area into a third model obtained by pre-training to make the third model output an equipment evaluation value;

[0218] when the equipment evaluation value is less than a third set evaluation value, determining that the complaint rate is true and determining that the area type of the heat supply area is a problem heat supply area, and constructing the evaluation result of the complaint rate according to the equipment evaluation value, the heat supply evaluation value and the user evaluation value;

[0219] when the equipment evaluation value is greater than or equal to the third set evaluation value, determining that the complaint rate is false and determining that the area type of the heat supply area is another heat supply area, and constructing the evaluation result of the complaint rate according to the equipment evaluation value, the heat supply evaluation value and the user evaluation value.

[0220] In summary, the embodiment of the present application provides a heat network regulation method and device, a predicted heat supply load of a heat supply area is predicted, the predicted heat supply load and an actual heat supply load are compared, and the distributed energy storage system is controlled to regulate the heat supply network according to the comparison result, so that the time lag of the heat supply network regulation is shortened, and the response capability of the heat supply network is improved.

[0221] The various embodiments described in this specification are described in progressive order, with each embodiment building on the previous one. The same or similar elements in each embodiment are denoted by the same or similar reference signs. For each embodiment, the differences between that embodiment and the preceding ones are described in more detail. In particular, the system or system embodiments are described more briefly than the method embodiments, since they are substantially similar to the method embodiments. The system and system embodiments described above are merely illustrative, and the units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e. can be located at one place or distributed over multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the embodiments. Those skilled in the art can understand and implement without creative labor.

[0222] The person skilled in the art will further appreciate that the units and algorithm steps of the examples described in connection with the embodiments disclosed herein can be realized in electronic hardware, computer software, or a combination of both. The disclosure has been presented in the form of functional generalizations so as to clearly illustrate the interchangeability of hardware and software. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. The person skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0223] The above description of the disclosed embodiments enables a person skilled in the art to implement or use the application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the scope of the application. Therefore, the present application is not to be limited to the embodiments shown herein, but is to be consistent with the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method of heat network regulation, characterized in that, The method comprises: determining a proportion of resident users in a heating area of a heat network regulation system based on a load type of the heating area; when the proportion of resident users is less than a proportion threshold, predicting a heating load of the heating area to obtain a predicted heating load of the heating area; when the proportion of resident users is greater than or equal to the proportion threshold, determining a region type of the heating area based on a complaint rate of the resident users and a heating parameter of the heating area; determining a heating satisfaction degree based on the region type of the heating area; predicting a load of the resident users to obtain a predicted resident load and predicting a load of industrial users in the heating area to obtain a predicted industrial load; correcting the predicted resident load by the heating satisfaction degree and determining the predicted heating load of the heating area by using the predicted industrial load and the corrected predicted resident load; comparing the predicted heating load of the heating area and an actual heating load of a heat distribution network of the heat network regulation system, and controlling a preset distributed energy storage system to regulate the heat distribution network according to a comparison result, the distributed energy storage system being constructed based on a boiler room; when the proportion of resident users is greater than or equal to the proportion threshold, determining the region type of the heating area based on the complaint rate of the resident users and the heating parameter of the heating area, comprises: when the proportion of resident users is greater than or equal to the proportion threshold, if the complaint rate of the resident users is less than a complaint rate threshold, determining that the region type of the heating area is a general heating area; if the complaint rate of the resident users is greater than or equal to the complaint rate threshold, constructing an evaluation result of the complaint rate according to the heating parameter of the heating area and determining that the region type of the heating area is a problem heating area or another heating area; determining the heating satisfaction degree based on the region type of the heating area, comprises: when the region type of the heating area is the problem heating area, determining the heating satisfaction degree based on the evaluation result, a heating area and the complaint rate in combination with a preset evaluation model; when the region type of the heating area is the another heating area, calculating a product of the evaluation result and the complaint rate and calculating a difference between 1 and the product to obtain the heating satisfaction degree; when the region type of the heating area is the general heating area, setting the heating satisfaction degree as a preset value.

2. The method of claim 1, wherein, comparing the predicted heating load of the heating area and the actual heating load of the heat distribution network of the heat network regulation system, and controlling the preset distributed energy storage system to regulate the heat distribution network according to the comparison result, comprises: calculating an absolute value of a difference between the predicted heating load of the heating area and the actual heating load of the heat distribution network of the heat network regulation system to obtain a load error; if the load error is less than a first threshold, not starting a heat storage function and a heat release function of the distributed energy storage system; if the load error is greater than or equal to a second threshold value, when the predicted heat supply load is greater than the actual heat supply load, starting the heat release function of the distributed energy storage system to provide heat to the heat supply network, and when the predicted heat supply load is less than the actual heat supply load, starting the heat storage function of the distributed energy storage system to store heat using the heat of the heat supply network; if the load error is greater than a third threshold value and less than the second threshold value, starting timing; when the timing time is greater than a time threshold value and the predicted heat supply load is greater than the actual heat supply load, starting the heat release function of the distributed energy storage system to provide heat to the heat supply network, and when the timing time is greater than the time threshold value and the predicted heat supply load is less than the actual heat supply load, starting the heat storage function of the distributed energy storage system to store heat using the heat of the heat supply network; wherein the third threshold value is greater than the first threshold value, and the third threshold value is less than the second threshold value.

3. The method of claim 1, wherein, if the complaint rate of the residential user is greater than or equal to the complaint rate threshold value, constructing an evaluation result of the complaint rate according to the heat supply parameters of the heat supply area, and determining the area type of the heat supply area as a problem heat supply area or another heat supply area, comprising: if the complaint rate of the residential user is greater than or equal to the complaint rate threshold value, inputting the heat supply parameters of the heat supply area into a first model trained in advance to make the first model output a heat supply evaluation value; when the heat supply evaluation value is less than a first set evaluation value, determining that the complaint rate is true and determining that the area type of the heat supply area is a problem heat supply area, and constructing an evaluation result of the complaint rate according to the heat supply evaluation value; when the heat supply evaluation value is greater than or equal to the first set evaluation value, inputting the user parameters of the heat supply area into a second model trained in advance to make the second model output a user evaluation value; when the user evaluation value is less than a second set evaluation value, determining that the complaint rate is true and determining that the area type of the heat supply area is a problem heat supply area, and constructing an evaluation result of the complaint rate according to the heat supply evaluation value and the user evaluation value; when the user evaluation value is greater than or equal to the second set evaluation value, determining a comprehensive evaluation value based on the heat supply evaluation value and the user evaluation value; determining a similar heat supply area similar to the heat supply area through the comprehensive evaluation value, if it is determined that the complaint rate is true based on the actual complaint rate in the similar heat supply area, determining that the complaint rate is true and determining that the area type of the heat supply area is a problem heat supply area, and constructing an evaluation result of the complaint rate according to the comprehensive evaluation value; if it is determined that the complaint rate is false based on the actual complaint rate in the similar heat supply area, inputting the historical failure rate and operation time of the heat supply equipment and temperature collection equipment of the heat supply area into a third model trained in advance to make the third model output an equipment evaluation value; when the equipment evaluation value is less than a third set evaluation value, determining that the complaint rate is true and determining that the area type of the heating area is a problem heating area, and constructing an evaluation result of the complaint rate according to the equipment evaluation value, the heating evaluation value and the user evaluation value; when the equipment evaluation value is greater than or equal to the third set evaluation value, determining that the complaint rate is false and determining that the area type of the heating area is another heating area, and constructing an evaluation result of the complaint rate according to the equipment evaluation value, the heating evaluation value and the user evaluation value.

4. The method of claim 1, wherein, predicting a load of the resident user to obtain a predicted resident load and predicting a load of an industrial user in the heating area to obtain a predicted industrial load, comprising: obtaining an input set and an industrial data set, the input set at least containing temperature, humidity, hours and dates corresponding to a prediction time point, and the industrial data set at least containing hours and dates corresponding to the prediction time point; inputting the input set into a resident load prediction model pre-trained to obtain a prediction result related to the area type of the heating area output by the resident load prediction model as the predicted resident load; inputting the industrial data set into an industrial load prediction model pre-trained to make the industrial load prediction model output the predicted industrial load.

5. A heat network regulating device, characterized in that The device comprises: a first determination unit configured to determine a proportion of resident users in the heating area of the heat network regulation system based on a load type of the heating area; a first prediction unit configured to predict a heating load of the heating area to obtain a predicted heating load of the heating area when the proportion of the resident users is less than a proportion threshold; a second determination unit configured to determine an area type of the heating area based on a complaint rate of the resident users and a heating parameter of the heating area when the proportion of the resident users is greater than or equal to the proportion threshold; a third determination unit configured to determine a heating satisfaction degree based on the area type of the heating area; a second prediction unit configured to predict a load of the resident users to obtain a predicted resident load and predict a load of an industrial user in the heating area to obtain a predicted industrial load; a processing unit configured to correct the predicted resident load by using the heating satisfaction degree and determine a predicted heating load of the heating area by using the predicted industrial load and the corrected predicted resident load; a regulation unit configured to compare the predicted heating load of the heating area with an actual heating load of a heat distribution network of the heat network regulation system, and control a pre-set distributed energy storage system to regulate the heat distribution network according to a comparison result, the distributed energy storage system being constructed based on a boiler room; The second determination unit comprises: a first determination module configured to determine that the area type of the heating area is a general heating area if the complaint rate of the resident users is less than a complaint rate threshold when the proportion of the resident users is greater than or equal to the proportion threshold. The second determining module is configured to, if the complaint rate of the resident user is greater than or equal to the complaint rate threshold, construct an evaluation result of the complaint rate according to the heating parameters of the heating area, and determine the area type of the heating area as a problem heating area or another heating area. The third determining unit is specifically configured to: when the area type of the heating area is the problem heating area, determine a heating satisfaction degree based on the evaluation result, the heating area, and the complaint rate, and in combination with a preset evaluation model. When the area type of the heating area is the other heating area, a product of the evaluation result and the complaint rate is calculated, and a difference between 1 and the product is calculated to obtain the heating satisfaction degree. When the area type of the heating area is the general heating area, the heating satisfaction degree is set as a preset value.

6. The apparatus of claim 5, wherein, The adjusting unit comprises: The calculating module is configured to calculate an absolute value of a difference between a predicted heating load of the heating area and an actual heating load of a heat distribution network of the heat network adjusting system, to obtain a load error. The first control module is configured to, if the load error is less than a first threshold, not start a heat storage function and a heat release function of the distributed energy storage system. The second control module is configured to, if the load error is greater than or equal to a second threshold, when the predicted heating load is greater than the actual heating load, start the heat release function of the distributed energy storage system to provide heat to the heat distribution network, and when the predicted heating load is less than the actual heating load, start the heat storage function of the distributed energy storage system to store heat by using heat of the heat distribution network. The third control module is configured to, if the load error is greater than a third threshold and less than the second threshold, start timing, when a timing time is greater than a time threshold and the predicted heating load is greater than the actual heating load, start the heat release function of the distributed energy storage system to provide heat to the heat distribution network, and when the timing time is greater than the time threshold and the predicted heating load is less than the actual heating load, start the heat storage function of the distributed energy storage system to store heat by using heat of the heat distribution network. The third threshold is greater than the first threshold and less than the second threshold.

7. The apparatus of claim 5, wherein, The second determining module is specifically configured to: If the complaint rate of the resident user is greater than or equal to the complaint rate threshold, input the heating parameters of the heating area into a first model trained in advance to make the first model output a heating evaluation value. When the heating evaluation value is less than a first set evaluation value, determine that the complaint rate is true and that the area type of the heating area is the problem heating area, and construct an evaluation result of the complaint rate according to the heating evaluation value. When the heating evaluation value is greater than or equal to the first set evaluation value, input user parameters of the heating area into a second model trained in advance to make the second model output a user evaluation value. When the user evaluation value is less than a second set evaluation value, determine that the complaint rate is true and that the area type of the heating area is the problem heating area, and construct an evaluation result of the complaint rate according to the heating evaluation value and the user evaluation value. determining a comprehensive evaluation value based on the heat supply evaluation value and the user evaluation value when the user evaluation value is greater than or equal to the second set evaluation value; determining a similar heat supply region similar to the heat supply region through the comprehensive evaluation value, determining that the complaint rate is true and determining that the region type of the heat supply region is a problem heat supply region if it is determined that the complaint rate is true based on the actual complaint rate in the similar heat supply region, and constructing an evaluation result of the complaint rate according to the comprehensive evaluation value; if it is determined that the complaint rate is false based on the actual complaint rate in the similar heat supply region, inputting the historical failure rate and the operation time of the heat supply equipment and the temperature collection equipment of the heat supply region into a third model trained in advance to make the third model output an equipment evaluation value; determining that the complaint rate is true and determining that the region type of the heat supply region is a problem heat supply region when the equipment evaluation value is less than a third set evaluation value, and constructing an evaluation result of the complaint rate according to the equipment evaluation value, the heat supply evaluation value and the user evaluation value; determining that the complaint rate is false and determining that the region type of the heat supply region is another heat supply region when the equipment evaluation value is greater than or equal to the third set evaluation value, and constructing an evaluation result of the complaint rate according to the equipment evaluation value, the heat supply evaluation value and the user evaluation value.

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