CN110486793B - Intelligent analysis scheduling method and system based on heat supply network five-level monitoring - Google Patents
Intelligent analysis scheduling method and system based on heat supply network five-level monitoring Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F22—STEAM GENERATION
- F22B—METHODS OF STEAM GENERATION; STEAM BOILERS
- F22B35/00—Control systems for steam boilers
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- F24D19/1006—Arrangement or mounting of control or safety devices for water heating systems
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Abstract
The invention discloses an intelligent analysis scheduling method and system based on heat supply network five-level monitoring, which utilizes an index correction method based on historical load to obtain an operation configuration plan of a heat supply station and a heat exchange station, and predicts the number of opened boilers, the number of opened circulating pumps, the frequency and the total flow of a network in the heat supply station; predicting the configuration of distribution pumps or regulating valves in the heat exchange station and the number and frequency of the opening of circulating pumps, and calculating the predicted temperature supply of the second network and the predicted temperature return of the second network; the operation configuration plans of the heat supply station and the heat exchange station are sent to a bottom layer control system for differential batch control; the load prediction is more accurate; time correction is added, so that the prediction of the heat supply station and the prediction of the heat exchange station have difference, the scale difference of a thermodynamic system is fully considered, the intelligent scheduling can realize heat supply as required more accurately, and energy waste caused by untimely temperature rise or too much temperature rise in advance is avoided.
Description
Technical Field
The disclosure relates to the field of heat supply network intelligent analysis scheduling, in particular to an intelligent analysis scheduling method and system based on heat supply network five-level monitoring.
Background
With the development of the automatic control technology, the metering temperature control technology, the internet of things communication technology and the internet technology, the informatization reformation of the central heating field is rapidly developed, and each heating power company basically completes the informatization reformation of the monitoring of the heating network, so that a solid foundation is laid for further realizing intelligent heating.
In the field of domestic intelligent heat supply, the relatively advanced energy management platform system only realizes five-level monitoring of a heat supply system and is far away from the intelligent five-level linkage[1]. The realization of intelligent heat supply needs to go through three stages, namely control automation, comprehensive informatization and management intellectualization[2]The three stages have strict sequence, most of the intelligent heating platform systems on the market are between the second stage and the third stage at present, the distance from the third stage to the realization of the intellectualization is far, and some large-scale heating companies take the intellectualization as a subject to perform trial study. The third stage of intelligent heat supply is intelligentizationThe realization of the method needs to be solved, firstly, the production process is fully informationized, enough sensors need to be arranged at each key part of a thermodynamic system, and data acquisition needs to be realized by wireless communication in places without wired communication. Each thermodynamic system basically realizes remote data acquisition and monitoring from a heat source, a primary pipe network, a heat exchange station, a secondary pipe network and user metering and temperature control, and basically realizes five-stage monitoring of the heat supply network. However, the intellectualization of the heating production, transmission and distribution and heat redistribution process of the large central heating system is not realized based on the five-level linkage of the five-level monitoring of the heating network. Data analysis system and method based on heat exchange station[3]The method only acquires data of a single heat exchange station, analyzes the acquired data, finds problems of operating equipment and adjusts the equipment accordingly. In addition, there is related heat supply network intelligent scheduling system[4]In the aspect of an intelligent scheduling method, the main idea is to calculate the energy consumption data of a heat source and a heat exchange station according to the load prediction calculated by the outdoor temperature, and guide the operation according to the energy consumption data analysis. The method does not comprehensively consider the delay of heating of a heat supply network and the increase of actual heat load caused by special weather (rain, snow, strong wind, cold tide and the like), is a ratio method based on the current actual heat supply quantity, the actual indoor temperature and the actual outdoor temperature, the actual indoor temperature in the calculation method is not the attribute of a certain thermodynamic system, is the temperature of each room at the tail end, belongs to scattered point-type data, and is difficult to represent as the indoor temperature by a plurality of indoor temperatures, so the accuracy of the formula is subject to examination. In the aspect of operation guidance, energy consumption prediction and load prediction of a heat source and a heat exchange station are given, and detailed operation plans such as equipment investment plans in the heat source and the heat exchange station, operation parameter guidance and the like are not given.
In the aspect of operation guidance of a centralized heating system, the existing method is to give operation guidance according to load prediction, and an equipment operation configuration plan in a heating station or a heat exchange station is not further predicted; in the aspect of intelligent scheduling, energy consumption analysis and cost analysis are considered, factors such as different energy consumption building energy consumption classifications and weather load rates are analyzed and compared without refinement, comparison is not carried out on the basis of the same energy consumption standard, and the basis of intelligent scheduling and control is not sufficient.
Reference to the literature
[1] Research and development directions of 'intelligent heat supply' in centralized heat supply in Song Yunpeng discuss [ J ] heat supply and refrigeration, 2017(11):36+38.
[2] Liu lan bin, Wang Rong Xin, Liu Yao Yong based on the intelligent transparent heating mode [ J ] of the industrial Internet of things, 2018(04):30-35+96.
[3] Yellow loyalty, malan, popone a heat exchange station based data analysis system and method [ P ]. shandong: CN108870529A,2018-11-23.
[4] Honor, grand bin, grand san bin an intelligent scheduling system for a heat network [ P ]. beijing: CN104791903A,2015-07-22.
Disclosure of Invention
In order to solve the problems, the technical scheme of the intelligent analysis scheduling method and system based on the heat supply network five-level monitoring is provided, in view of the problems in the operation guidance aspect, temperature correction, time correction and special weather correction according to historical loads are added on the basis of considering outdoor temperature, so that load prediction is more accurate and meets the heat utilization characteristics of each thermodynamic system, an operation configuration table of a heat supply station and a heat exchange station is given, the current situation that heat supply technicians manually make heat supply plans can be changed, the workload of operation scheduling is reduced, the intelligence of operation scheduling is improved, and the working efficiency is improved.
The heat supply network five-level monitoring is a software system and a hardware facility for acquiring, monitoring, adjusting and controlling main parameters of a heat supply station, a primary pipe network, a heat exchange station, a secondary pipe network and an indoor room temperature/metering temperature control five-level thermodynamic system of a heat supply system and the running state of equipment, and specification CJJT 241-2016 town heat supply monitoring and adjusting system technical regulation is explained in detail; the invention aims at carrying out summary analysis on key information such as water, electricity, heat, temperature, pressure, flow, frequency, opening degree and the like of each thermodynamic system collected by a heat supply network five-level monitoring system, and provides a data source for the application of an intelligent analysis scheduling system.
In order to achieve the above object, according to an aspect of the present disclosure, there is provided an intelligent analysis scheduling method based on five-level monitoring of a heat supply network, the method including the steps of:
carrying out data acquisition on a thermodynamic system in the heat supply network five-level monitoring system;
forecasting the heat loads of the heat supply station and the heat exchange station by utilizing an index correction method based on historical loads, integrating outdoor weather and charging area data, considering time correction and temperature correction;
obtaining an operation configuration plan of the heat supply station according to the corrected heat load prediction of the heat supply station, wherein the operation configuration plan of the heat supply station comprises the number of opened boilers in the heat supply station, the number and frequency of opened circulating pumps and the total flow of a network;
obtaining an operation configuration plan of the heat exchange station according to the corrected heat load prediction of the heat exchange station, and calculating the number and frequency of the started circulating pumps to be added into the operation configuration plan of the heat supply station, wherein the operation configuration plan of the heat exchange station comprises the total flow of a network in the heat exchange station, the configuration of a distribution pump or the configuration of a regulating valve;
calculating according to the heat load of each system partition of the heat exchange station to obtain a two-network predicted temperature supply and a two-network predicted temperature return, and adding the two-network predicted temperature supply and the two-network predicted temperature return into an operation configuration plan of the heat exchange station;
and issuing the operation configuration plan of the heat supply station and the operation configuration plan of the heat exchange station to a bottom layer control system for differentiated batch control, wherein the operation configuration plan of the heat supply station and the operation configuration of the heat exchange station comprise the number of opened boilers, the configuration of a circulating pump, the configuration of an adjusting valve, the predicted temperature supply of the two networks and the predicted temperature return of the two networks.
Further, the data for acquiring the data of the thermodynamic system in the heat supply network five-level monitoring system comprises: the heat supply network five-level monitoring system monitors water, electricity, heat, temperature, pressure, flow, frequency and opening degree of each thermodynamic system in the system.
The heat supply network five-level monitoring system is a software system and a hardware facility for acquiring, monitoring, adjusting and controlling main parameters of a heat supply station, a primary pipe network, a heat exchange station, a secondary pipe network (building heat power inlet), and five-level heat system main parameters of a household device (indoor room temperature/metering temperature control) and the running state of the device of the heat supply system, and the specification CJJT 241-plus 2016 Town heating monitoring and adjusting system technical regulation is explained in detail;
the thermodynamic system comprises a heat supply station and complete systems of a primary pipe network, all heat exchange stations, all secondary network systems and the like which are governed by the heat supply station, can also refer to a certain heat exchange station-secondary pipe network-indoor system, and can also refer to a certain system partitioning unit of the heat exchange station-the system-secondary pipe network-indoor system.
Furthermore, the method for predicting the heat load of the heat supply station and the heat exchange station by utilizing the index correction method based on the historical load, integrating the outdoor weather and the charging area data, considering time correction and temperature correction and obtaining the corrected heat load of the heat supply station comprises the following steps:
each thermodynamic system and the end buildings and the transmission and distribution pipe network served by the thermodynamic system have characteristics, even if the end buildings with the same energy consumption classification are adopted, because the pipe network construction and maintenance conditions are different, the pipe network design is different and other factors are different, and the final energy consumption indexes are different, therefore, the load prediction method adopts a heat index correction method based on actual historical loads, integrates the outdoor temperature correction and time correction factors, and is as shown in the formula (1):
wherein: q is the instantaneous heat power of the prediction thermodynamic system, namely the corrected prediction heat load (heat load prediction value), and the unit is GJ/h; q18-20For predicting a thermodynamic system, when the indoor average temperature of the thermodynamic system is 18-20 ℃, the corresponding instantaneous thermal power is GJ/h; t'nThe required indoor temperature is expressed in units of ℃; t is tnTaking 18 ℃ for designing indoor temperature; t'w-iFor i hours after the current prediction timeThe outdoor temperature is forecasted in i hours, the preheating is carried out in advance in i hours by considering the actual conditions of the heating speed of a thermodynamic system, the transmission and distribution distance of a pipe network system and the like, and the value range of i is selected and set from 0.5h to 72 h; t is twDesigning the outdoor temperature; delta t is temperature correction, and the correction value of outdoor temperature under special meteorological conditions such as rain, snow, strong wind, cold tide and the like can be selected and set within the range of-2 ℃ to 2 ℃ according to experience; a' is the actual supply area of each thermodynamic system; q' is the heat load index of the thermal system under the outdoor temperature, and the unit is W/m2Meanwhile, the average indoor temperature at the tail end of the thermal system is predicted to meet the requirement of the designed indoor temperature, the average room temperature is generally 18-20 ℃, and the corrected index of the thermal load of the heating plant already comprises various heat losses of the thermal system.
Further, an operation configuration plan of the heating plant is obtained according to the corrected heat load prediction of the heating plant, and the operation configuration plan of the heating plant comprises a calculation method for the number of opened boilers in the heating plant, and the calculation method comprises the following steps:
the predicted load rate refers to the ratio of the predicted heat load Q of a certain heat supply station or heat exchange station to the total installed capacity C:
the calculation formula of the predicted load rate is as follows:
wherein R is the predicted load rate of the heat supply station or the heat exchange station, is dimensionless and is percentage; q is the predicted heat load of a certain heat supply station or heat exchange station, and the unit is GJ/h; and C is the total installed capacity of a certain heat supply station or heat exchange station, and the unit is MW.
Determining boiler opening (number of boilers) according to the predicted load rate: and according to the predicted load rate, comparing the predicted load rate with the percentage of the single boiler in the total installed capacity of the heating station, and optimizing to obtain a recommended starting plan. If a certain heating station has 2 boilers with equal capacity, the predicted load rate is 34.49 percent and is less than the capacity of a single unit, the boiler 1 is recommended to be opened, optimal judgment needs to be carried out, and an optimal opening plan is given; one method for determining the number of boilers to be started according to the predicted load rate is to start 1 when the predicted load rate is smaller than a load threshold, and start 2 when the predicted load rate is greater than or equal to the load threshold, wherein the load threshold is a manually set percentage, and the load threshold is defaulted to 30%.
Predicting the total flow of the network according to the formula (3):
in equation (3): g is one-network predicted flow, and the unit is t/h; q is the predicted heat load, and the unit is GJ/h;
Tgdesigning the water supply temperature for the boiler, wherein the unit is; t ishDesigning the return water temperature for the boiler, wherein the unit is;
the operation configuration plan comprises the number of the opened boilers, the configuration of circulating pumps, the configuration of regulating valves, the predicted temperature supply of the two networks and the predicted temperature return of the two networks.
Further, the method for obtaining the operation configuration plan of the heat exchange station according to the corrected heat load prediction of the heat exchange station and calculating the number and frequency of the circulating pumps to be started to be added into the operation configuration plan of the heat supply station comprises the following steps:
the distribution pump configuration comprises the number and frequency of starting distribution pumps;
the distribution pump is a first water pump, and the circulating pump is a second water pump; the method comprises the following steps of comparing a one-network predicted flow of a predicted thermodynamic system with a rated flow of a water pump, calculating the water pump frequencies of a first water pump and a second water pump under the predicted flow according to the relation between the speed-regulating water pump frequency and the flow and the direct proportion between the flow and the frequency, wherein the water pump frequencies are calculated under two conditions of A and B:
A. when the predicted flow rate is less than the single rated flow rate,
B. when the rated flow of a single unit is less than the predicted flow and less than 2 rated total flows:
in the formulas (4) and (5), the unit is t/h; g is the rated flow of the water pump, and the unit is t/h; wherein: the calculation methods of the number of the started first water pump and the second water pump and the frequency are both formulas (4) and (5); the flow rate G 'of the distributed pump input formulas (4) and (5) is predicted total flow rate of the network, namely G' ═ G; the flow G' of the circulating pump input formulas (4) and (5) is the predicted flow of each system subarea of the two-network calculated by the predicted heat load of each system subarea of the two-network,
namely, the predicted heat load of each system partition of the two networks passes through a formula
The predicted flow of each system partition of the two networks is obtained by calculation, namely
Calculating the predicted flow of each system partition of the two-network system, and calculating the circulating pump configuration of each system partition according to the predicted flow; the distribution pump is a first water pump, the circulating pump is a second water pump, the first water pump is a pump 1, the second water pump is a pump 2, G1Is the rated power, G, of the pump 12Is the rated power of the pump 2.
And (3) configuring the regulating valve, namely predicting the opening percentage of the regulating valve, and carrying out ratio on the predicted flow of the first network and the predicted rated flow of the first network of the heat exchange station, wherein the obtained percentage is the opening degree of the regulating valve, and the minimum opening degree of the regulating valve is not lower than 5% in consideration of the safety of the pipe network.
In the formulas (6) and (7), eta is the opening percentage of the prediction regulating valve and has the unit of percent; ghThe unit is the rated flow of the heat exchange station and is t/h, A is the predicted net inlet area of the heat exchange station and is m2(ii) a q is a design heat index of a predicted heat exchange station and has the unit of W/m2(ii) a G' is a predicted traffic of a network, Tg、ThAnd designing a network water supply temperature and a return water temperature respectively for the predicted heat exchange station, wherein the unit is ℃.
Further, step 5, the method for obtaining the two-network predicted temperature supply and the two-network predicted temperature return according to the heat load calculation of each system partition of the heat exchange station and adding the two-network predicted temperature return into the operation configuration plan of the heat exchange station comprises the following steps:
phi in the formulas (8) and (9) is a relative heating heat load ratio,
t′nto predict the required indoor design temperature of the end building of the thermodynamic system, the default is calculated as 18 ℃. t is tnTaking 18 ℃ for designing indoor temperature;
tgpredicting the temperature of the water supplied to the second network; t is thPredicting the temperature of the return water of the second net; t'wIs the current outdoor temperature; t is twDesigning the outdoor temperature; q is the design area heat index, with the unit of W/m2；TgDesigning the temperature of the supplied water for the boiler; t ishDesigning a return water temperature for the boiler; all temperatures mentioned above are in degrees celsius.
Further, the method for performing differentiated batch control comprises the following steps of:
the bottom control system controls the start of the circulating pump: according to the predicted total flow of the network, compared with the rated flow of the water pumps, when the predicted value is smaller than the rated flow of a single water pump, the first water pump is the pump 1, the second water pump is the pump 2, the first water pump and the second water pump are different water pumps, the pump 1 is recommended to be started, and when the predicted flow is larger than the rated flow of the pump 1 and smaller than the sum of the flows of the pump 1 and the pump 2, the pump 1 and the pump 2 are started.
The bottom layer control system controls the boiler to be started, the predicted load value is obtained by combining an algorithm for carrying out optimal matching on the rated heat supply capacity of boiler equipment, the first boiler is a boiler 1, the second boiler is a boiler 2, and the first boiler and the second boiler are different boilers. For example, when the predicted load is lower than the rated heating capacity of the pot 1, the pot 1 is recommended to be opened, and when the predicted load is larger than the rated heating capacity of the pot 1 and is smaller than the sum of the rated heating capacities of the pot 1 and the pot 2, the pot 1 and the pot 2 are recommended to be opened.
And (3) issuing the two-network predicted temperature supply and the two-network predicted temperature return to a bottom layer control system for differentiated batch control:
the bottom layer control system controls the starting of the circulating pump, the frequency configuration of the circulating pump, the reference two-network prediction temperature supply and the two-network prediction temperature return are controlled, and the prediction flow and the rated flow are the prediction two-network flow and the rated flow of the prediction thermodynamic system respectively. The bottom layer control system is a software system and a hardware facility which are used for acquiring, monitoring, adjusting and controlling main parameters of a heat supply station, a primary pipe network, a heat exchange station, a secondary pipe network (building heat inlet) and five-level thermal system of a household device (indoor room temperature/metering temperature control) and the running state of the device in a heat supply network five-level monitoring system, and the specification CJJT 241-plus 2016 Town heating monitoring and adjusting and controlling system technical specification is explained in detail.
The invention also provides an intelligent analysis scheduling system based on the heat supply network five-level monitoring, which comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the computer program to run in the units of the following system:
the data acquisition unit is used for acquiring data of a thermodynamic system in the heat supply network five-level monitoring system;
the load prediction unit is used for synthesizing outdoor weather and charging area data by using an index correction method based on historical load, considering time correction and temperature correction and predicting the heat load of the heat supply station and the heat exchange station;
the heat supply station operation configuration unit is used for obtaining an operation configuration plan of the heat supply station according to the corrected heat load prediction of the heat supply station, and the operation configuration plan of the heat supply station comprises the number of opened boilers, the number and frequency of opened circulating pumps in the heat supply station and the total flow of a network;
the heat exchange station configuration updating unit is used for calculating according to the heat load of each system partition of the heat exchange station to obtain a two-network predicted temperature supply and a two-network predicted temperature return, and adding the two-network predicted temperature supply and the two-network predicted temperature return into an operation configuration plan of the heat exchange station;
the heat exchange station configuration updating unit is used for calculating according to the heat load of each system partition of the heat exchange station to obtain a two-network predicted temperature supply and a two-network predicted temperature return and adding an operation configuration plan of the heat exchange station;
and the batch control unit is used for issuing an operation configuration plan of the heat supply station and an operation configuration plan of the heat exchange station to the bottom control system for differentiated batch control, wherein the operation configuration plan of the heat supply station and the operation configuration of the heat exchange station comprise the number of opened boilers, the configuration of a circulating pump, the configuration of an adjusting valve, the predicted temperature supply of the two networks and the predicted temperature return of the two networks.
The beneficial effect of this disclosure does: the invention provides an intelligent analysis scheduling method and system based on heat supply network five-level monitoring, which adopts a heat index correction method based on actual historical load to predict load, increases temperature correction for special weather and ensures that the load prediction is more accurate; time correction is added, so that the prediction of the heat supply station and the prediction of the heat exchange station have difference, the scale difference of a thermodynamic system is fully considered, the intelligent scheduling can realize heat supply as required more accurately, and energy waste caused by untimely temperature rise or too much temperature rise in advance is avoided. According to the predicted load and the perfect basic information of the heat supply network, the operation configuration plan of the equipment in the heat supply station or the heat exchange station is further predicted, and differentiated batch control on different heat exchange stations can be realized. The control strategy can be automatically corrected through comprehensive analysis consisting of operation analysis, resource consumption analysis, heat supply quality analysis and customer service repair analysis of real-time data acquired by the heat supply network five-level monitoring system. The energy consumption analysis and the cost analysis are compared on the basis of the same building energy consumption classification and the same weather load rate range on the basis of the same energy consumption standard and the same outdoor air temperature condition, and objective evaluation can be given to the operation of the thermodynamic system. And further, through multi-dimensional data analysis and comparison with a prediction configuration plan, strategy modification is automatically realized, automation of a control process is realized, and uncertainty and randomness of manually issued control strategies are reduced. The invention deeply combines the heating and ventilation mechanism with the intelligent heat supply management platform and establishes a perfect heat supply network basic database in an intelligent dispatching system. In the aspect of operation guidance, on the basis of considering outdoor temperature, temperature correction and time correction according to historical load are added, so that load prediction is more accurate and meets the heat utilization characteristics of each thermodynamic system, an operation plan is further given, an operation configuration table of a heat supply station and a heat exchange station is further given, the current situation that heat supply technicians manually make a heat supply plan can be changed, the workload of operation scheduling is reduced, the intelligence of operation scheduling is improved, and the working efficiency is improved.
Drawings
The foregoing and other features of the present disclosure will become more apparent from the detailed description of the embodiments shown in conjunction with the drawings in which like reference characters designate the same or similar elements throughout the several views, and it is apparent that the drawings in the following description are merely some examples of the present disclosure and that other drawings may be derived therefrom by those skilled in the art without the benefit of any inventive faculty, and in which:
FIG. 1 is a flow chart of an intelligent analysis scheduling method based on five-level monitoring of a heat supply network;
FIG. 2 is a framework diagram of an intelligent analysis scheduling architecture based on five-level monitoring of a heat supply network;
fig. 3 is a structural diagram of an intelligent analysis scheduling system based on five-level monitoring of a heat supply network.
Detailed Description
The conception, specific structure and technical effects of the present disclosure will be clearly and completely described below in conjunction with the embodiments and the accompanying drawings to fully understand the objects, aspects and effects of the present disclosure. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
Fig. 1 is a flowchart illustrating an intelligent analysis scheduling method based on five-level monitoring of a heat supply network according to the present disclosure, fig. 2 is a framework diagram illustrating an intelligent analysis scheduling structure based on five-level monitoring of a heat supply network, and an intelligent analysis scheduling method based on five-level monitoring of a heat supply network according to an embodiment of the present disclosure is described below with reference to fig. 1 and fig. 2.
The utility model provides an intelligent analysis scheduling method based on heat supply network five-level monitoring, specifically includes the following steps:
carrying out data acquisition on a thermodynamic system in the heat supply network five-level monitoring system;
forecasting the heat loads of the heat supply station and the heat exchange station by utilizing an index correction method based on historical loads, integrating outdoor weather and charging area data, considering time correction and temperature correction;
obtaining an operation configuration plan of the heat supply station according to the corrected heat load prediction of the heat supply station, wherein the operation configuration plan of the heat supply station comprises the number of opened boilers in the heat supply station, the number and frequency of opened circulating pumps and the total flow of a network;
obtaining an operation configuration plan of the heat exchange station according to the corrected heat load prediction of the heat exchange station, and calculating the number and frequency of the started circulating pumps to be added into the operation configuration plan of the heat supply station, wherein the operation configuration plan of the heat exchange station comprises the total flow of a network in the heat exchange station, the configuration of a distribution pump or the configuration of a regulating valve;
calculating according to the heat load of each system partition of the heat exchange station to obtain a two-network predicted temperature supply and a two-network predicted temperature return, and adding the two-network predicted temperature supply and the two-network predicted temperature return into an operation configuration plan of the heat exchange station;
and issuing the operation configuration plan of the heat supply station and the operation configuration plan of the heat exchange station to a bottom layer control system for differentiated batch control, wherein the operation configuration plan of the heat supply station and the operation configuration of the heat exchange station comprise the number of opened boilers, the configuration of a circulating pump, the configuration of an adjusting valve, the predicted temperature supply of the two networks and the predicted temperature return of the two networks.
Furthermore, the intelligent analysis scheduling method based on the heat supply network five-level monitoring realizes the intelligent analysis scheduling function by perfecting the basic information subsystem on the basis of the existing heat supply intelligent monitoring platform.
The basic information subsystem comprises a foundation of functions of data acquisition, data analysis, intelligent control and the like, and is a foundation of the whole intelligent heat supply monitoring platform, and the basic information subsystem comprises but is not limited to a heat consumer information module and a heat supply network information module.
In the hot user information module, information templates such as a district, a community, a building, a hot user and the like are established by taking a heat source as a unit, and a complete hot user information attribution information base is established. And defining each building according to different building energy consumption classifications in the hot house information. Different energy consumption classifications mean the energy consumption level, and the objectivity and the rationality of analysis can be guaranteed only by comparing thermodynamic systems of the same energy consumption classification in the analysis processes of operation analysis, energy consumption analysis, cost analysis and the like.
And a heat source, a primary pipe network, a heat exchange station, a secondary pipe network (building heat power inlet), a user end device (room temperature acquisition/measurement temperature control), cost information, design parameters, time definition and other complete operation related information templates are established in the heat supply network information module, wherein the cost information comprises the unit price and the heat value of water, electricity, heat, gas and raw coal at the location of a heating power system. The design parameters include design heat index, historical heat index, design outdoor temperature and design indoor temperature of each thermodynamic system. The perfect cost information and design information are the data structure requirements of the analysis and scheduling system for multidimensional analysis, and are the basis of load prediction and the establishment of an operation configuration plan.
A five-level monitoring system of a heat supply network is a software system and hardware facilities for acquiring, monitoring, regulating and controlling main parameters and operation states of five-level thermal systems of a heat supply station, a primary pipe network, a heat exchange station, a secondary pipe network (building thermal inlet) and a household device (indoor room temperature/metering temperature control), and specifications CJJT 241-plus 2016 Town heating monitoring and regulating system technical regulation are explained in detail. The system provided by the invention is used for summarizing and analyzing key information such as water, electricity, heat, temperature, pressure, flow, frequency, opening degree and the like of each thermodynamic system acquired by the heat supply network five-level monitoring system, and providing a data source for the application of an intelligent analysis and scheduling system.
The intelligent analysis scheduling subsystem is a subsystem based on a heat supply network five-level monitoring system. The intelligent analysis scheduling subsystem comprises a load prediction module, a comprehensive analysis module and a control strategy module, and is a core system of the intelligent heat supply management platform. The load prediction module predicts a thermal load of each thermodynamic system,
and generating an operation configuration plan of each thermodynamic system, and issuing the operation configuration plan to a bottom control system to realize a differentiated batch control function.
The load prediction module weather interface acquires real-time weather data, and the weather forecast interface comprises any one of a national weather forecast interface, an Aliyun weather forecast interface and a weather forecast interface of a weather bureau, but is not limited to the national weather forecast interface;
the load prediction module obtains information such as the actual supply area and the charge rate of each thermodynamic system, synthesizes outdoor weather, charge data and historical parameter correction, predicts the heat load of each thermodynamic system and obtains the energy prediction and operation configuration plan of each thermodynamic system.
The thermodynamic system comprises a heat supply station and complete systems of a primary pipe network, all heat exchange stations, all secondary network systems and the like which are governed by the heat supply station, can also refer to a certain heat exchange station-secondary pipe network-indoor system, and can also refer to a certain system partitioning unit of the heat exchange station-the system-secondary pipe network-indoor system.
Correcting the heat index of the thermodynamic system: the thermal index is used for predicting instantaneous thermal power of the thermodynamic system;
the method for forecasting the heat load of the thermodynamic system adopts an index correction method, each thermodynamic system and the end buildings and the transmission and distribution pipe network served by the thermodynamic system have characteristics, and even if the thermodynamic system and the end buildings with the same energy consumption classification have different final energy consumption indexes due to different pipe network construction and maintenance conditions, different pipe network design and other factors, so that the load forecasting method adopts a heat index correction method based on actual historical load, and the heat load forecasting method based on the historical load is as the following formula (1):
wherein: q is the instantaneous heat power of the prediction thermodynamic system, namely the corrected prediction heat load, and the unit is GJ/h; q18-20For predicting a thermodynamic system, when the indoor average temperature of the thermodynamic system is 18-20 ℃, the corresponding instantaneous thermal power is GJ/h; t'nThe required indoor temperature is expressed in units of ℃; t is tnTaking 18 ℃ for designing indoor temperature; t'w-iPreheating the outdoor temperature for the forecast outdoor temperature i hours after the current forecast time, wherein the i hours are the actual conditions such as the heating speed of a thermodynamic system, the transmission and distribution distance of a pipe network system and the like, the preheating is carried out in advance for i hours, the value range of i is selected and set from 0.5h to 72h, and h is hour; t is twDesigning the outdoor temperature; delta t is temperature correction, and the correction value of outdoor temperature under special meteorological conditions such as rain, snow, strong wind, cold tide and the like can be selected and set within the range of-2 ℃ to 2 ℃ according to experience; a' is the actual supply area of each thermodynamic system; and q' is a heat load index at the historical design outdoor temperature of the thermodynamic system, and the unit is W/m 2. The heat supply station load prediction and operation configuration table is as follows:
according to the predicted heat load, the operation configuration table of the predicted thermodynamic system can be obtained according to the design parameters of the predicted thermodynamic system, the capacity, the number and other information of the main equipment, and is divided into a heat supply station operation configuration table and a heat exchange station operation configuration table, wherein as shown in table 1, the area load and the operation configuration plan table of each heat supply station in the heating period of 201X-201X years are shown.
TABLE 1 plan table for area load and operation configuration of each heating plant in heating period of 201X-201X years
(1) The real supply area refers to the actual heat supply area of the predicted heat supply station, the occupancy rate is equal to the real supply area divided by the network access area, and the data is from a charging management system of the heat supply network five-level monitoring system;
(2) the total installed capacity refers to the total heat supply capacity of a boiler in a predicted heat supply station, and the unit is MW;
(3) the predicted load rate is equal to the predicted load divided by the total installed capacity, and the predicted load unit GJ/h needs to be converted into MW: the calculation formula of the predicted load rate is as follows:
r is the predicted load rate of the heat supply station or the heat exchange station, is dimensionless and is percentage; q is the predicted heat load of a certain heat supply station or heat exchange station, and the unit is GJ/h; and C is the total installed capacity of a certain heat supply station or heat exchange station, and the unit is MW.
Determining boiler opening (number of boilers) according to the predicted load rate: and according to the predicted load rate, comparing the predicted load rate with the percentage of the single boiler in the total installed capacity of the heating station, and optimizing to obtain a recommended starting plan. If a certain heating station has 2 boilers with equal capacity, the predicted load rate is 34.49 percent and is less than the capacity of a single unit, the boiler 1 is recommended to be opened, optimal judgment needs to be carried out, and an optimal opening plan is given; one method for determining the number of boilers to be started according to the predicted load rate is to start 1 when the predicted load rate is smaller than a load threshold, and start 2 when the predicted load rate is greater than or equal to the load threshold, wherein the load threshold is a manually set percentage, and the load threshold is defaulted to 30%.
Predicting the total flow of the network through the heat index:
in equation (3): g is one-network predicted flow, and the unit is t/h; q is the predicted heat load, and the unit is GJ/h;
Tgdesigning the water supply temperature for the boiler, wherein the unit is; t ishThe return water temperature is designed for the boiler and has the unit of ℃.
The heat exchange station load prediction and operation configuration table is as follows:
for the operation guidance of the heat exchange station, according to the predicted heat load, and according to the predicted thermal load, the design parameters of the thermodynamic system, the capacity, the number of the main equipment and other information, the operation guidance is compared with the rated capacity of the heat exchange unit in the heat exchange station, and a heat exchange station operation configuration table is given, as shown in table 2:
TABLE 2 Heat exchange station load prediction and operation configuration table
As shown in table 2, each system partition of the heat exchange station is an independent heat transfer pipeline system of the heat exchange station, and one heat exchange station may have three or two high zones, middle zones and low zones;
obtaining distribution pump configuration according to the predicted total flow of the network;
the distribution pump configuration comprises the number and frequency of starting distribution pumps;
the distribution pump comprises a first water pump and a second water pump; the method comprises the following steps of comparing a one-network predicted flow of a predicted thermodynamic system with a rated flow of a water pump, calculating the water pump frequency under the predicted flow according to the relation between the speed-regulating water pump frequency and the flow and the direct proportion between the flow and the frequency, wherein the water pump frequency is divided into a calculation method under two conditions of A and B:
A. when the predicted flow rate is less than the single rated flow rate,
B. when the rated flow of a single unit is less than the predicted flow and less than 2 rated total flows:
in the formulas (4) and (5), the unit is t/h; g is the rated flow of the water pump, and the unit is t/h; wherein: the calculation methods of the number of the started first water pump and the second water pump and the frequency are both formulas (4) and (5); the flow rate G 'of the distributed pump input formulas (4) and (5) is predicted total flow rate of the network, namely G' ═ G; the flow G' of the circulating pump input formulas (4) and (5) is the predicted flow of each system subarea of the two-network calculated by the predicted heat load of each system subarea of the two-network,
namely, the predicted heat load of each system partition of the two networks passes through a formula
The predicted flow of each system partition of the two networks is obtained by calculation, namely
Calculating the predicted flow of each system partition of the two-network system, and calculating the circulating pump configuration of each system partition according to the predicted flow; the distribution pump is a first water pump, the circulating pump is a second water pump, the first water pump is a pump 1, the second water pump is a pump 2, G1Is the rated power, G, of the pump 12Is the rated power of the pump 2.
Obtaining a regulating valve configuration according to the predicted total flow of the network
And (3) configuring the regulating valve, namely predicting the opening percentage of the regulating valve, and carrying out ratio on the predicted flow of the first network and the predicted rated flow of the first network of the heat exchange station, wherein the obtained percentage is the opening degree of the regulating valve, and the minimum opening degree of the regulating valve is not lower than 5% in consideration of the safety of the pipe network.
In the formulas (6) and (7), eta is the opening percentage of the prediction regulating valve and has the unit of percent; ghThe unit is the rated flow of the heat exchange station and is t/h, A is the predicted net inlet area of the heat exchange station and is m2(ii) a q is a design heat index of a predicted heat exchange station and has the unit of W/m2(ii) a G' is a predicted traffic of a network, Tg、ThAnd designing a network water supply temperature and a return water temperature respectively for the predicted heat exchange station, wherein the unit is ℃.
Calculating the predicted temperature supply of the second network and the predicted temperature return of the second network:
phi in the formulas (8) and (9) is a relative heating heat load ratio,
t′nto predict the required indoor design temperature of the end building of the thermodynamic system, the default is calculated as 18 ℃. t is tnTaking 18 ℃ for designing indoor temperature;
tgfor predicting water supply to two networks(ii) temperature; t is thPredicting the temperature of the return water of the second net; t'wIs the current outdoor temperature; t is twDesigning the outdoor temperature; q is the design area heat index, with the unit of W/m2；TgDesigning the temperature of the supplied water for the boiler; t ishDesigning a return water temperature for the boiler; the units are degrees celsius.
The method for distributing the regulating valve configuration to a bottom layer control system and carrying out differentiated batch control comprises the following steps:
starting a circulating pump: according to the predicted total flow of the network, comparing with the rated flow of the water pump, when the predicted value is smaller than the rated flow of a single water pump, the first water pump in the table 1 is a pump 1, the second water pump is a pump 2, and the circulating pump comprises the first water pump and the second water pump; the first water pump and the second water pump are different water pumps, the pump 1 is recommended to be started, and when the predicted flow is larger than the rated flow of the pump 1 and smaller than the sum of the flows of the pump 1 and the pump 2, the pump 1 and the pump 2 are started.
And (3) starting the boiler, and obtaining the optimal matching algorithm by combining the predicted load value and the rated heat supply capacity of the boiler equipment, wherein the first boiler is a boiler 1, the second boiler is a boiler 2, and the first boiler and the second boiler are different boilers. For example, when the predicted load is lower than the rated heating capacity of the pot 1, the pot 1 is recommended to be opened, and when the predicted load is larger than the rated heating capacity of the pot 1 and is smaller than the sum of the rated heating capacities of the pot 1 and the pot 2, the pot 1 and the pot 2 are recommended to be opened.
And (3) issuing the two-network predicted temperature supply and the two-network predicted temperature return to a bottom layer control system for differentiated batch control:
and starting a circulating pump, calculating the frequency of the circulating pump, referring to the predicted temperature supply of the second network and the predicted temperature return of the second network for control, wherein the predicted flow and the rated flow are the predicted second network flow and the rated flow of the predicted thermodynamic system respectively.
An intelligent analysis scheduling system based on heat supply network five-level monitoring provided by the embodiment of the present disclosure is, as shown in fig. 3, a structure diagram of the intelligent analysis scheduling system based on heat supply network five-level monitoring of the present disclosure, and an intelligent analysis scheduling system based on heat supply network five-level monitoring of the embodiment includes: the intelligent analysis scheduling system comprises a processor, a memory and a computer program which is stored in the memory and can run on the processor, wherein the processor executes the computer program to realize the steps in the embodiment of the intelligent analysis scheduling system based on the five-level monitoring of the heat supply network.
The system comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the computer program to run in the units of the following system:
the data acquisition unit is used for acquiring data of a thermodynamic system in the heat supply network five-level monitoring system;
the load prediction unit is used for synthesizing outdoor weather and charging area data by using an index correction method based on historical load, considering time correction and temperature correction and predicting the heat load of the heat supply station and the heat exchange station;
the heat supply station operation configuration unit is used for obtaining an operation configuration plan of the heat supply station according to the corrected heat load prediction of the heat supply station, and the operation configuration plan of the heat supply station comprises the number of opened boilers, the number and frequency of opened circulating pumps in the heat supply station and the total flow of a network;
the heat exchange station configuration updating unit is used for calculating according to the heat load of each system partition of the heat exchange station to obtain a two-network predicted temperature supply and a two-network predicted temperature return, and adding the two-network predicted temperature supply and the two-network predicted temperature return into an operation configuration plan of the heat exchange station;
the heat exchange station configuration updating unit is used for calculating according to the heat load of each system partition of the heat exchange station to obtain a two-network predicted temperature supply and a two-network predicted temperature return and adding an operation configuration plan of the heat exchange station;
and the batch control unit is used for issuing an operation configuration plan of the heat supply station and an operation configuration plan of the heat exchange station to the bottom control system for differentiated batch control, wherein the operation configuration plan of the heat supply station and the operation configuration of the heat exchange station comprise the number of opened boilers, the configuration of a circulating pump, the configuration of an adjusting valve, the predicted temperature supply of the two networks and the predicted temperature return of the two networks.
The intelligent analysis scheduling system based on the heat supply network five-level monitoring can be operated in computing equipment such as desktop computers, notebooks, palm computers and cloud servers. The intelligent analysis scheduling system based on the five-level monitoring of the heat supply network can be operated by a system comprising, but not limited to, a processor and a memory. Those skilled in the art will appreciate that the example is only an example of an intelligent analysis scheduling system based on the five-level monitoring of the heat supply network, and does not constitute a limitation of the intelligent analysis scheduling system based on the five-level monitoring of the heat supply network, and may include more or less components than the other, or combine some components, or different components, for example, the intelligent analysis scheduling system based on the five-level monitoring of the heat supply network may further include an input-output device, a network access device, a bus, and the like.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general processor can be a microprocessor or the processor can be any conventional processor and the like, the processor is a control center of the intelligent analysis scheduling system operation system based on the heat supply network five-level monitoring, and various interfaces and lines are used for connecting various parts of the whole intelligent analysis scheduling system operation system based on the heat supply network five-level monitoring.
The memory can be used for storing the computer programs and/or modules, and the processor can realize various functions of the intelligent analysis scheduling system based on the heat supply network five-level monitoring by running or executing the computer programs and/or modules stored in the memory and calling the data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
While the present disclosure has been described in considerable detail and with particular reference to a few illustrative embodiments thereof, it is not intended to be limited to any such details or embodiments or any particular embodiments, but it is to be construed as effectively covering the intended scope of the disclosure by providing a broad, potential interpretation of such claims in view of the prior art with reference to the appended claims. Furthermore, the foregoing describes the disclosure in terms of embodiments foreseen by the inventor for which an enabling description was available, notwithstanding that insubstantial modifications of the disclosure, not presently foreseen, may nonetheless represent equivalent modifications thereto.
Claims (8)
1. An intelligent analysis scheduling method based on heat supply network five-level monitoring is characterized by comprising the following steps:
carrying out data acquisition on a thermodynamic system in the heat supply network five-level monitoring system;
forecasting heat loads of a heat supply station and a heat exchange station by using an index correction method based on historical loads;
the method for predicting the heat loads of the heat supply station and the heat exchange station by using the index correction method based on the historical loads comprises the following steps: the heat load prediction method based on the historical load comprises the following steps:
wherein: q is the instantaneous heat power of the predictive thermodynamic systemRate, i.e. corrected predicted thermal load; q18-20For predicting the thermodynamic system, when the indoor average temperature is 18-20 ℃, the corresponding instantaneous thermal power; t'nTo demand the indoor temperature, tnDesigning indoor temperature; t'w-iSetting the value range of i between 0.5h and 72h for the forecast outdoor temperature i hours after the current forecast time; t is twDesigning the outdoor temperature; Δ t is temperature correction; a' is the actual supply area of each thermodynamic system; q' is the heat load index of the thermal system under the outdoor temperature in the unit of W/m2；
Obtaining an operation configuration plan of the heat supply station according to the corrected heat load prediction of the heat supply station;
obtaining an operation configuration plan of the heat exchange station according to the corrected heat load prediction of the heat exchange station, and calculating the number and frequency of the started circulating pumps to be added into the operation configuration plan of the heat supply station;
and calculating according to the heat load of each system partition of the heat exchange station to obtain a two-network predicted temperature supply and a two-network predicted temperature return, and adding the two-network predicted temperature return into an operation configuration plan of the heat exchange station.
2. The intelligent analysis and scheduling method based on the heat supply network five-level monitoring as claimed in claim 1, wherein the data for acquiring the data of the thermodynamic system in the heat supply network five-level monitoring system comprises: the heat supply network five-level monitoring system is used for monitoring water, electricity, heat, temperature, pressure, flow, frequency and opening degree of each thermodynamic system in the system; the heat supply network five-level monitoring system is a software system and hardware facilities for collecting, monitoring, adjusting and controlling the main parameters of the heat supply station of the heat supply system, the primary pipe network, the heat exchange station, the secondary pipe network and the five-level thermodynamic system of the user-side equipment and the running state of the equipment.
3. The intelligent analysis scheduling method based on the heat supply network five-level monitoring as claimed in claim 1, wherein the operation configuration plan of the heat supply station is obtained according to the corrected heat load prediction of the heat supply station, and the operation configuration plan of the heat supply station comprises a calculation method for the number of opened boilers in the heat supply station, and the calculation method comprises the following steps:
the predicted load rate refers to the ratio of the predicted heat load Q of a certain heat supply station or heat exchange station to the total installed capacity C:
the calculation formula of the predicted load rate is as follows:
wherein R is the predicted load rate of the heat supply station or the heat exchange station, is dimensionless and is percentage; q is the predicted heat load of the heat supply station or the heat exchange station, and the unit is GJ/h; c is the total installed capacity of a certain heat supply station or heat exchange station, the unit is MW, and the number of the opened boilers is determined according to the predicted load rate.
4. The intelligent analysis scheduling method based on the five-level monitoring of the heat supply network as claimed in claim 2, wherein the operation configuration plan of the heat supply station includes a total network flow, and the total network flow calculation method includes:
the total flow of the network is predicted according to the following formula:
wherein: g is one-network predicted flow, and the unit is t/h; q is the predicted heat load, and the unit is GJ/h; t isgDesigning the water supply temperature for the boiler, wherein the unit is; t ishThe return water temperature is designed for the boiler and has the unit of ℃.
5. The intelligent analysis scheduling method based on the five-level monitoring of the heat supply network as claimed in claim 3, wherein an operation configuration plan of the heat exchange station is obtained according to the corrected heat load prediction of the heat exchange station, and the operation configuration plan of adding the number and frequency of the started circulating pumps to the heat supply station is calculated, the operation configuration plan of the heat exchange station includes the configuration of distribution pumps, the configuration of the distribution pumps includes the number and frequency of the started distribution pumps, and the method for the number and frequency of the started distribution pumps and the started circulating pumps includes:
the distribution pump is a first water pump, and the circulating pump is a second water pump; the one-network predicted flow of the thermodynamic system is compared with the rated flow of the water pump, and according to the relationship between the frequency of the speed-regulating water pump and the flow, the water pump frequencies of the first water pump and the second water pump under the predicted flow are calculated according to the direct proportion between the flow and the frequency:
A. when the predicted flow rate is less than the single rated flow rate,
B. when the rated flow of a single unit is less than the predicted flow and less than 2 rated total flows:
wherein the unit is t/h; g is the rated flow of the water pump, and the unit is t/h; the flow rate G 'input by the distribution pump is a predicted total flow rate of the network, that is, G' ═ G; the flow G' input by the circulating pump is the predicted flow of each system subarea of the two-network calculated by the predicted heat load of each system subarea of the two-network,
namely, the predicted heat load of each system partition of the two networks passes through a formula
The predicted flow of each system partition of the two networks is obtained by calculation, namely
Calculating the predicted flow of each system partition of the two-network system, and calculating the circulating pump configuration of each system partition according to the predicted flow; the distribution pump is a first water pump, the circulating pump is a second water pump, the first water pump is a pump 1, the second water pump is a pump 2, G1Is the rated power, G, of the pump 12Is the rated power of the pump 2.
6. The intelligent analysis scheduling method based on the five-level monitoring of the heat supply network as claimed in claim 5, wherein the operation configuration plan of the heat exchange station includes a regulating valve configuration, and the calculating method of the regulating valve configuration is as follows:
the method comprises the steps that the configuration of an adjusting valve means that the opening percentage of the adjusting valve is predicted, the ratio of the one-network predicted flow to the one-network rated flow of a predicted heat exchange station is carried out, and the obtained percentage is the opening degree of the adjusting valve;
wherein eta is the opening percentage of the prediction regulating valve, and the unit is percent; ghThe unit is the rated flow of the heat exchange station and is t/h, A is the predicted net inlet area of the heat exchange station and is m2(ii) a q is a design heat index of a predicted heat exchange station and has the unit of W/m2(ii) a G' is a predicted traffic of a network, Tg、ThAnd designing a network water supply temperature and a return water temperature respectively for the predicted heat exchange station, wherein the unit is ℃.
7. The intelligent analysis scheduling method based on heat supply network five-level monitoring of claim 6, wherein the method for predicting the temperature supply and return according to the calculated two-network prediction comprises the following steps:
wherein phi is the relative heating heat load ratio,
t′nfor predicting the required indoor design temperature, t, of the building at the end of the thermodynamic systemnTaking 18 ℃ for designing indoor temperature; t is tgPredicting the temperature of the water supplied to the second network; t is thPredicting the temperature of the return water of the second net; t'wIs the current outdoor temperature; t is twDesigning the outdoor temperature; q is the design area heat index, with the unit of W/m2；TgDesigning the temperature of the supplied water for the boiler; t ishThe return water temperature is designed for the boiler.
8. An intelligent analysis scheduling system based on five-level monitoring of a heat supply network, the system comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the computer program to run in the units of the following system:
the data acquisition unit is used for acquiring data of a thermodynamic system in the heat supply network five-level monitoring system;
the load prediction unit is used for predicting the heat loads of the heat supply station and the heat exchange station by using an index correction method based on historical loads;
the method for predicting the heat loads of the heat supply station and the heat exchange station by using the index correction method based on the historical loads comprises the following steps: the heat load prediction method based on the historical load comprises the following steps:
wherein: q is the instantaneous heat power of the prediction thermodynamic system, namely the corrected prediction heat load; q18-20For predicting the thermodynamic system, when the indoor average temperature is 18-20 ℃, the corresponding instantaneous thermal power; t'nFor the required indoor temperatureDegree, tnDesigning indoor temperature; t'w-iSetting the value range of i between 0.5h and 72h for the forecast outdoor temperature i hours after the current forecast time; t is twDesigning the outdoor temperature; Δ t is temperature correction; a' is the actual supply area of each thermodynamic system; q' is the heat load index of the thermal system under the outdoor temperature in the unit of W/m2；
The heat supply station operation configuration unit is used for obtaining an operation configuration plan of the heat supply station according to the corrected heat load prediction of the heat supply station;
the heat exchange station operation configuration unit is used for obtaining an operation configuration plan of the heat exchange station according to the corrected heat load prediction of the heat exchange station and calculating the number and frequency of the started circulating pumps to be added into the operation configuration plan of the heat supply station;
the heat exchange station configuration updating unit is used for calculating according to the heat load of each system partition of the heat exchange station to obtain a two-network predicted temperature supply and a two-network predicted temperature return, and adding the two-network predicted temperature supply and the two-network predicted temperature return into an operation configuration plan of the heat exchange station;
and the batch control unit is used for issuing the operation configuration plan of the heat supply station and the operation configuration plan of the heat exchange station to the bottom layer control system for batch control.
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