Precise heat supply scheduling method and system based on one source and one day

Abstract

The invention discloses a heat supply accurate scheduling method and system based on one source and one day, and belongs to the technical field of heat supply scheduling. Heat exchange stations are classified according to factors such as energy-saving standards executed in building construction years and building types, and existing heat indexes are calculated in combination with actual heat consumption in a heating season and outdoor average temperature; comprehensively determining the heat index of the heat exchange station unit; secondly, on the basis of the heat index, the actual supply area, the indoor design temperature, the outdoor forecast temperature and the heating outdoor calculation temperature, the next day heat load is calculated; then, according to the heat load and the hydraulic working condition of the primary pipe network, a heat source plant strictly executes heat load scheduling according to a plan, and the actual heat consumption of the day is recorded; and finally, if the deviation between the actual heat consumption of the day and the planned heat load exceeds + / -10%, an assessment and early warning mechanism is triggered, deviation analysis and management optimization are carried out, the heat dynamic matching of the heat source end and the user end is realized, and the operation efficiency and the management precision of the heat supply system are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of heat supply scheduling, and in particular to a method and system for accurately scheduling heat supply based on one source per day. Background Art

[0002] Precise heating scheduling based on a single source per day approach involves scientifically calculating heat indicators for each heat source plant based on multiple dimensions, including building type, historical heat consumption data, and weather forecasts. This generates a detailed scheduling plan for each heating day (i.e., a "one source, one day, one plan"). The heat source plant strictly adjusts its heat load according to this daily plan, achieving a dynamic balance between heat supply at the heat source and heat demand at the network end. This ensures neither a shortage nor an excess of heat, improves heat supply quality and stability, and effectively reduces energy consumption. This approach, through a heat load calculation formula and a strict implementation and assessment mechanism, ensures precise and controllable daily heating scheduling, maintains user room temperatures within a comfortable range, and significantly reduces energy waste.

[0003] The prior art has the following deficiencies: In view of the problems that the existing heating scheduling method is difficult to achieve on-demand heating at the heat source end, and lacks the integration of multi-dimensional information such as building type, historical heat consumption and meteorological factors into the daily scheduling system, resulting in the difficulty in effectively controlling the deviation between heat supply and heat demand, high energy consumption, and insufficient heating quality and stability, a precise heating scheduling method based on "one source, one day, one plan" is proposed. By scientifically determining the thermal indicators of the heat exchange station units, accurately predicting the heat load in combination with meteorological forecasts, and generating a strictly implemented daily scheduling plan, precise on-demand heating at the heat source end is achieved, thereby effectively balancing the heat demand at the pipeline network end and the heat supply at the heat source end, improving the heating quality and promoting energy conservation and consumption reduction. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for accurately scheduling heat supply based on one source per day to address the shortcomings of the background technology.

[0005] To achieve the above objectives, the present invention provides the following technical solutions: a method for accurately scheduling heat supply based on one source per day, comprising: Each heat exchange station is categorized based on the energy-saving standards implemented in the building's construction era and building type. The existing thermal index is calculated by investigating the building's energy-saving type, heat consumption during the standard heating season, and the average outdoor temperature. The thermal index of the heat exchange station unit is then comprehensively determined. Calculate the heat load for the next day based on the heat index, the actual supply area, the indoor design temperature, the outdoor forecast temperature and the heating outdoor calculated temperature; Based on the next day's heat load and the primary pipe network hydraulic conditions, the production technology department will guide the preparation of a one-source-one-day plan for the next day, which will be issued to the heat source plant after review; The heat source plant receives and strictly follows the one-source-one-day schedule to schedule heat loads and records the actual heat consumption for the day; When the deviation between the actual heat consumption and the planned heat consumption on the day exceeds ±10%, points will be deducted according to the deviation, and the production management department will inspect, guide and evaluate the implementation of each subsidiary.

[0006] Preferably, the categorization of the heat exchange stations includes: Establish a database of building archives within the service area of ​​the heat exchange station, and enter the energy-saving design indicators and structural types of each building into the database according to the national or industry energy-saving standards corresponding to the building's construction year; Based on the energy-saving types of buildings in the archive database, the heat consumption per unit area of ​​each type of building is counted during the standard heating season, and the average outdoor temperature during the period is calculated; The ratio of the heat consumption per unit area to the average outdoor temperature is combined with the indoor design temperature of the building and the supply and return water temperature difference of the heat exchange station to convert it into an existing thermal index to form a benchmark thermal index for different types of heat exchange stations.

[0007] Preferably, the average outdoor temperature is calculated by weighting the daily maximum, minimum and average temperatures to improve the accuracy of thermal index estimation.

[0008] Preferably, the benchmark thermal index is optimized in two stages: In the first stage, the influence of abnormal operating conditions was eliminated through multivariate regression analysis based on the historical operating data of the heat exchange station; In the second stage, based on the optimized benchmark thermal index and the rated power ratio of the heat exchange station units, the units are divided into different grades according to the size of the service area to determine the final thermal index of the units used for the heat exchange station.

[0009] Preferably, calculating the next day's heat load further includes: The difference between the indoor design temperature and the outdoor temperature forecast for the next day is calculated as the initial temperature difference, and the difference between the heating outdoor calculated temperature and the forecast temperature is calculated as the corrected temperature difference; Multiply the heat index by the actual supply area, then multiply the result by the initial temperature difference, and perform a division operation using the corrected temperature difference as a divisor to obtain the nominal heat load for the day's scheduling; Based on the analysis of historical operational deviations, dynamic correction coefficients of enclosure structure performance, wind speed, and geographical orientation are introduced to perform weighted correction on the nominal heat load to improve prediction accuracy.

[0010] Preferably, the dynamic correction coefficient is automatically updated through an adaptive feedback algorithm according to the deviation between the actual heat load and the predicted heat load of the previous day, so as to achieve continuous optimization of the future prediction model.

[0011] Preferably, the outdoor temperature forecast is fused with multiple meteorological models, and a weighted average method is used to obtain the average temperature of the next day, which is used as the basis for temperature difference calculation.

[0012] Preferably, a sub-item coefficient of the actual supply area according to the building function is introduced, and the areas of residential areas, commercial areas and public building areas are weighted separately to reflect the differences in heat consumption of different building types.

[0013] Preferably, after the daily operation is completed, the difference between the actual heat consumption of the heat source plant on that day and the planned heat load in the one-source-one-day plan table is calculated to obtain the deviation percentage; when the absolute value of the deviation exceeds 10% of the planned heat load, it is determined to be an over-limit deviation; If the heat source plant's deviation exceeds the limit, one point will be deducted for each exceeding limit, accumulated to ten points, and recorded in the dispatch assessment ledger; if the limit is exceeded for three consecutive days, the plant will be placed on the red alert list, triggering a special operation review; For deviation days, the system automatically generates a deviation analysis report, providing preliminary explanations based on weather anomalies, equipment failures, and operational deviations. A dispatch specialist then fills in a categorized explanation of the causes and uploads it to the group management platform for filing. The production management department conducts a horizontal comparison of the deviations between the execution plans and actual operations of all subsidiaries every week, identifies areas with poor scheduling stability, and organizes scheduling technology seminars to review experiences and optimize operating strategies.

[0014] The present invention also provides a precise heat supply scheduling system based on one source per day, comprising: The thermal index assessment module categorizes each heat exchange station based on the energy-saving standards implemented in the building's construction era and building type factors. It then estimates the existing thermal index by investigating the building's energy-saving type, heat consumption during the standard heating season, and the average outdoor temperature, and comprehensively determines the thermal index of the heat exchange station units. A heat load prediction module calculates the heat load for the next day based on the heat index, the actual supply area, the indoor design temperature, the outdoor forecast temperature and the heating outdoor calculated temperature; The daily scheduling plan generation module, based on the next day's heat load and the primary pipe network hydraulic conditions, is guided by the production technology department to prepare a daily schedule for each source for the next day, which is then issued to the heat source plant after review; The plan execution and operation record module receives and strictly schedules the heat load according to the one-source-one-day plan, and records the actual heat consumption of the day; Deviation assessment and management module: When the deviation between the actual heat consumption and the planned heat consumption on the day exceeds ±10%, points will be deducted according to the deviation, and the production management department will inspect, guide and assess the implementation of each subsidiary.

[0015] In the above technical solution, the technical effects and advantages provided by the present invention are: 1. This invention, for the first time, deeply integrates multi-dimensional data, including building energy-saving standards, building types, historical energy consumption, weather forecasts, and hydraulic conditions, systematically establishing a comprehensive process from thermal index determination, load forecasting, and planning to strict implementation and deviation assessment. This solution significantly improves the operational accuracy and scheduling rigidity of the heating system, efficiently matching on-demand heating at the heat source with actual user needs, and addressing the problems of heat waste, large room temperature fluctuations, and lack of refined management in traditional heating models.

[0016] 2. Through the coordinated application of automated forecasting and a closed-loop feedback mechanism, this invention can identify plan execution deviations in real time. Combined with an adaptive algorithm to optimize the heat load forecasting model, it effectively promotes the upgrade of operational scheduling towards digitalization and intelligence. Furthermore, through an assessment system, a quantitative evaluation is implemented for each heat source plant, promoting standardized operational behavior and experience sharing across enterprises. This overall technical system not only improves energy efficiency and reduces operating costs, but also ensures heating comfort and stability for users. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0018] Figure 1 Flow chart of the method of the present invention.

[0019] Figure 2 It is a flow chart of the system modules of the present invention. DETAILED DESCRIPTION

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0021] Example 1, please refer to Figure 1 As shown, the precise scheduling method for heat supply based on one source per day described in this embodiment includes: Each heat exchange station is categorized based on the energy-saving standards implemented in the building's construction era and building type. The existing thermal index is calculated by investigating the building's energy-saving type, heat consumption during the standard heating season, and the average outdoor temperature. The thermal index of the heat exchange station unit is then comprehensively determined. Calculate the heat load for the next day based on the heat index, the actual supply area, the indoor design temperature, the outdoor forecast temperature and the heating outdoor calculated temperature; Based on the predicted heat load and the hydraulic conditions of the primary pipe network, the production technology department will guide the preparation of a one-source-one-day plan for the next day, which will be issued to the heat source plant after review; The heat source plant receives and strictly follows the one-source-one-day schedule to schedule heat loads and records the actual heat consumption for the day; When the deviation between the actual heat consumption and the planned heat consumption on the day exceeds ±10%, points will be deducted according to the deviation, and the production management department will inspect, guide and evaluate the implementation of each subsidiary.

[0022] The following, in conjunction with an embodiment of the present invention, provides a detailed explanation of the technical solution of "classifying each heat exchange station according to factors such as the energy-saving standards implemented in the year of building construction and the building type, estimating the existing thermal index by investigating the building energy-saving type and the heat consumption and average outdoor temperature during the standard heating season, and comprehensively determining the thermal index of the heat exchange station unit."

[0023] This step aims to scientifically and systematically classify heat exchange stations, and on this basis, to infer existing thermal indices through empirical data. Finally, the thermal indices of each heat exchange station unit are comprehensively determined, laying the foundation for accurate heat load prediction in the next step. This step includes the following four sub-steps: Establish and classify a building information database; compile statistics on energy consumption and meteorological data during the heating season; calculate existing thermal indicators; and comprehensively determine thermal indicators.

[0024] First, for each heat exchange station’s service area, basic information of all heated buildings within the area is collected, mainly including: Construction year and applicable energy-saving standards: such as "65 version energy-saving standards", "11 version energy-saving standards", "17 version energy-saving standards", etc.; Building types: residential buildings, multi-story residential buildings, high-rise residential buildings, public buildings (offices, schools, hospitals), commercial buildings, etc. Building structure and thermal insulation performance: types of exterior wall insulation materials, thermal performance of window frames and window glass, roof insulation methods, etc.; Indoor design temperature: generally 18℃ or 20℃ according to energy-saving standards.

[0025] This information is collected through on-site surveys, property registration forms, design drawings, and energy-saving design acceptance reports, and then entered into a database. The system then categorizes each building according to the energy-saving standard level and building type corresponding to its construction year, dividing all buildings within the heat exchange station's service area into several categories (e.g., "65-version multi-story residential building," "17-version public building," etc.). This categorization takes into account both differences in energy-saving standards and functional types, providing a stratified basis for subsequent energy consumption statistics.

[0026] After completing the building classification, for each building category, the heat consumption per unit area and the average outdoor temperature during the previous standard heating season (in this embodiment, 180 days of continuous heating is used as the benchmark) are calculated, mainly including: Energy consumption data collection: Obtain the total heat consumption of each type of building under each heat exchange station from the energy consumption metering system of each station; divide the total heat consumption by the actual heating area of ​​the corresponding type of building to obtain the heat consumption per unit area of ​​that type (unit: GJ / ㎡·180 days).

[0027] Meteorological Data Acquisition: Authoritative meteorological authorities or local meteorological observatories collect the average daily temperature for the heating season. The 180-day average temperature is summed and taken the arithmetic mean to obtain the average outdoor temperature for the heating season in the region (unit: °C). To improve statistical accuracy, the meteorological database can be reprocessed using methods such as weighting the maximum and minimum temperatures and adjusting for the number of sunny and rainy days, resulting in a more accurate average temperature indicator.

[0028] After obtaining the heat consumption per unit area of ​​each building type and the average outdoor temperature during the heating season, the current thermal index can be calculated. The so-called "current thermal index" refers to the nominal thermal index value required per square meter of heating area when the indoor and outdoor temperature difference is the reference design difference under historical operating conditions. The calculation method is as follows: The difference between the building's indoor design temperature and the average outdoor temperature during the heating season is used as the temperature difference benchmark. The proportional relationship between this temperature difference and the heat consumption per unit area is considered the existing thermal index. First, calculate the difference between the design indoor temperature and the historical average outdoor temperature, then divide this temperature difference by the heat consumption per unit area. The resulting quotient is the existing thermal index.

[0029] For example, if the heat consumption per unit area of ​​a certain type of building is x GJ / ㎡·180 days, the indoor design temperature is tn℃, and the historical average outdoor temperature is tw0℃, then its existing thermal index is "heat consumption per square meter per degree Celsius temperature difference", which is the result obtained by dividing x by (the difference between tn and tw0), and the unit is GJ / ㎡·°C·180 days.

[0030] For example, for a "65 version multi-story residential building" category, the heat consumption per unit area is 0.8 GJ / ㎡·180 days, the indoor design temperature is 18°C, and the historical average outdoor temperature is 2°C; the existing thermal index = 0.8 ÷ (18 − 2) ≈ 0.05 GJ / ㎡·°C.

[0031] Through the above method, the existing thermal index value corresponding to each building category can be obtained, providing a quantitative basis for the comprehensive determination of the subsequent unit thermal index.

[0032] Finally, the existing thermal indicators of each type of building are further integrated to determine the operating thermal indicators of the heat exchange station units. This process includes: According to the proportion of actual heating area occupied by each building type served by the heat exchange station, the existing heat index of each type is weighted averaged; If there are n types of buildings in the service area of ​​the heat exchange station, the service area of ​​type i accounts for , the existing thermal index is , then the weighted heat index = .

[0033] The historical operating data of the heat exchange station is introduced into the weighted results, and the influence of abnormal days is eliminated through multiple regression or least squares method to correct the weighted heat index; the corrected results can improve the applicability and prediction accuracy of the index.

[0034] If the heat exchange station has multiple units with different capacities, the thermal indicators can be further divided into different grades and subdivided according to the rated power and coverage area of ​​each unit; Small units, standby units and main units are matched with corresponding grade indicators to ensure operation economy and adjustment flexibility.

[0035] Enter the finalized unit thermal index into the dispatch management system and generate a unique version number; When the building type or climate conditions change significantly, the thermal index can be regenerated and upgraded according to this step to ensure the timeliness of the scheduling plan.

[0036] Through this comprehensive determination process, accurate thermal index input can be provided for the subsequent "heat load forecast - daily scheduling plan generation - strict implementation" links, realizing true on-demand and precise heating.

[0037] This step aims to accurately calculate the next day's grid-wide heat supply based on the previously determined thermal indicators, guiding the "one source, one day, one plan" daily scheduling. This step includes three sub-steps: temperature difference data preprocessing; heat load quantification calculation; and dynamic correction coefficient application.

[0038] Through the above-mentioned step-by-step processing, we can not only make full use of meteorological forecast information and historical operating data, but also integrate on-site dynamic parameters to achieve high-precision prediction and real-time correction of the next day's heat load, ensuring accurate matching of heat supply at the heat source end and heat demand at the pipeline end.

[0039] To obtain the most reliable next-day outdoor temperature forecast, the system first extracts the next day's 24-hour average forecast temperature data from the National Meteorological Administration, municipal meteorological observatories, and regional microclimate models. A weighted average is used, with the National Meteorological Administration's forecast having the highest weight (e.g., 50%), followed by municipal meteorological observatories (30%), and the microclimate model participating in the calibration (20%), to reduce the impact of errors in a single forecast model on the overall forecast.

[0040] On the basis of obtaining the daily average outdoor forecast temperature, the forecast temperature is further fine-tuned using empirical correction coefficients based on factors such as the local building envelope structure characteristics (such as the insulation performance of exterior walls and roofs), topography (plains, hills, river valleys), and typical wind speed and direction to form the "next day corrected outdoor temperature."

[0041] The difference between the indoor design temperature and the corrected outdoor temperature the next day is defined as the "initial temperature difference"; The difference between the calculated outdoor temperature for heating (usually the design value of extreme low temperatures over many years in history) and the outdoor temperature the next day after correction is defined as the "corrected temperature difference".

[0042] The above preprocessing ensures that the temperature difference data not only reflects the latest meteorological conditions but also takes into account the design safety margin, laying a solid foundation for subsequent heat load quantification.

[0043] Based on the "initial temperature difference" and "corrected temperature difference" obtained in the previous sub-steps, combined with the heat index and actual supply area of ​​the heat exchange station, the nominal heat load is calculated.

[0044] First, multiply the heat index by the actual supply area to obtain the maximum heat demand under unit temperature difference; Then multiply the result by the "initial temperature difference" to get the theoretical heat required for the indoor temperature; Finally, using the "corrected temperature difference" as the adjustment basis, the above heat value is divided by the corrected temperature difference to form the "nominal heat load" for daily scheduling.

[0045] If the heat exchange station service area has different functional zones (residential, commercial, public buildings, etc.), the actual area provided shall be weighted in the above calculation: The area of ​​each zone is multiplied by the corresponding functional coefficient (e.g., residential area coefficient 1.0, commercial area coefficient 1.2, public building coefficient 1.1) to reflect the energy consumption characteristics of different building types; The weighted zone areas are summed and used instead of the total available area for nominal heating load calculations.

[0046] The nominal heat load formed in this process is the benchmark value of daily heat supply under standard design conditions, providing initial data for subsequent dynamic corrections.

[0047] The system performs statistical analysis on the deviation between the actual heat load and the predicted nominal heat load in the previous few days (such as the last 7 days) to identify regular errors (such as continuous underestimation or overestimation).

[0048] Adopting an adaptive feedback algorithm, the "dynamic correction coefficient" is automatically adjusted according to the size of historical deviations. The adjustment amplitude is proportional to the deviation, ensuring that the feedback process is both rapid and effective while avoiding violent oscillations.

[0049] Incorporate the thermal insulation performance parameters of the building's exterior walls, doors, and windows, as well as environmental factors such as wind speed, wind direction, and sunshine duration, into the correction model, and calculate the correction coefficient using multivariate linear or machine learning methods; The nominal heat load is corrected by multiplication or addition to obtain the final "next day predicted heat load".

[0050] After the actual operation is completed every day, the new deviation data is fed back to the system, and the adaptive algorithm updates the correction logic in real time to continuously optimize the prediction accuracy.

[0051] The above-mentioned dynamic correction mechanism can effectively offset weather forecast deviations, differences in building envelope performance and nonlinear effects of the pipe network system, significantly improving the stability and accuracy of the prediction.

[0052] After determining thermal indicators and forecasting heat load, this step aims to translate the forecast results into an executable daily scheduling plan. By analyzing the hydraulic operating conditions of the primary network and combining them with the forecasted heat load, the group company's production and technology department will organize and guide each heat source plant in compiling a "One Source, One Day Plan." After review, this plan will be officially issued as a rigid guide for the next day's production operations at the heat source.

[0053] The plan is formulated based on the principle of "heat load forecast as the main line, hydraulic balance as the core, and equipment capacity as the boundary", ensuring that the scheduling plan not only meets user needs but also conforms to the actual operating capacity of the system: Based on predicted heat load: The planned heat load value is derived from the load forecasting process completed the previous day, which has been combined with factors such as building structure, weather forecast, historical energy consumption and correction factors to ensure the accuracy of load demand; Primary pipe network hydraulic condition analysis: including the following parameter analysis: Design value of supply and return water temperature of the pipe network; Pressure difference distribution under actual operating conditions; The flow regulation capacity of each heat exchange station and the hydraulic control response of key nodes; The transmission capacity limitation from the heat source plant to the pipeline network (such as whether the flow pressure loss at the water supply end is acceptable).

[0054] This analysis uses hydraulic simulation software or real-time monitoring data retrospective comparison to ensure the transportability of the predicted heat load and the stability of the pipe network pressure; Heat source capacity verification: Before formulating a plan, it is necessary to compare the adjustable power, start-stop flexibility, spare capacity and historical operating efficiency of the existing units in the heat source plant to avoid scheduling targets exceeding equipment limits or frequent start-stops causing energy losses.

[0055] The "One Source, One Day Plan" is filled out by the heat source plant dispatch specialist under the guidance of the unified template of the group's production and technology department, and is finalized after review by technical personnel. Its contents include but are not limited to the following: The heat source plant name and date; the planned total heating supply for the next day (in megajoules or megawatt-hours); the planned hourly heating supply or time-based heating load curve; the recommended corresponding supply and return water temperatures; the recommended corresponding flow rate (in tons per hour); a description of peak and off-peak periods and the peak-shaving strategy; special operating requirements (such as wind chill warning response and standby unit start-up and shutdown plans); the preparer, reviewer, and issuance date. This schedule serves as a "rigid instruction" for the next day's operation and must be strictly implemented by the heat source plant dispatch center. Records of actual heating operations should be maintained for subsequent plan deviation assessments.

[0056] To ensure the scientific nature and execution of the plan, the Group's Production and Technology Department has established a three-tiered review mechanism. After the heat source plant completes the plan, the regional operations and dispatching center conducts an initial review to verify data integrity. The regional dispatching center then summarizes the data and submits it to the Production and Technology Department for a technical review, covering factors such as the matching of heat load and heat source capacity, the rationality of the primary and secondary network linkage, and the stability of the heating curve. The Technical Director or an authorized reviewer provides final approval and signs the order. This order is issued through a platform-based system with automatic push notification and manual confirmation to ensure timeliness and uniqueness.

[0057] After the "One Source, One Day, One Plan" was officially issued, the heat source plant entered a strict implementation phase. This step required heat source plant dispatchers to precisely adjust heat load output, guided by the established scheduling plan and combined with real-time monitoring data. They also recorded operating status and actual heat consumption at each time period throughout the process. This closed-loop management of planning and execution, ensuring rigid scheduling constraints and transparent heat supply, is the core step in ensuring the implementation of precise heat supply.

[0058] The heat source plant dispatch center receives the "One Source, One Day, One Plan" through the heat supply dispatch platform before the specified time each day (e.g., before 18:00 the previous day). After receiving the plan, the system automatically performs the following preparations: Importing system preset values: importing the planned time-slot heating, water supply temperature, return water temperature and flow rate data into the heat source control system as target operating parameters for each time period; Equipment start-stop configuration matching: The dispatching system presets strategies such as host unit start-stop logic, load distribution, and standby unit activation timing; Hydraulic joint commissioning preparation: Contact the heat exchange station to confirm the water supply terminal preparation status, ensure that the hydraulic loop is fully connected and there are no abnormal working conditions; Safety verification: The system automatically detects whether the target parameters exceed the unit's operating capacity, safe temperature difference and system pressure difference range. If exceeded, it prompts manual verification.

[0059] On the operation day, the heat source plant dispatchers monitor core parameters such as the main unit output, supply water temperature, return water temperature, and instantaneous flow rate of the primary network in real time based on the target values ​​imported by the system, and implement the following refined scheduling strategies: Time-based adjustment: strictly follow the heat load curve of the planned time period and fine-tune the burner opening, water pump speed and mixing valve angle in real time; Peak-valley control: During peak hours in the morning and evening, the main unit will be started 30 minutes in advance to increase the temperature and flow according to the peak heating demand instructions in the dispatch table; Abnormal response: If a large area of ​​heat deviation occurs at the user end due to sudden weather changes or unexpected failures, it is necessary to report to the regional dispatch center to apply for temporary dispatch deviation permission. The dispatch system will retain the adjustment record for assessment; Automatic / manual dual control operation: The system presets automatic execution of scheduling parameters, while the dispatcher can make fine adjustments to ensure operational safety and accurate heat output.

[0060] Each operational decision in this process is bound to a timestamp and operator identification to ensure that the scheduling process is traceable and responsibilities can be defined.

[0061] During the execution of the plan, the heat source plant needs to record the following data in real time to form the actual operating performance of the day: hourly heat output of the main unit (MWh); primary network return water temperature and flow (collection frequency is not less than 5 minutes); heat exchange station return water pressure and inlet water temperature; total heat consumption (accumulated throughout the day, in MJ or MWh); a brief description of various abnormalities and handling situations during the operating period.

[0062] The above data is automatically uploaded to the group scheduling system for cloud archiving and serves as an important basis for plan execution assessment, thermal efficiency statistics and subsequent optimization.

[0063] After the daily operation is completed, the system automatically compares the actual heat consumption uploaded by the heat source plant with the planned heat load listed in the "One Source, One Day, One Plan" for that day and calculates the deviation percentage. The deviation calculation method is as follows: Deviation value = actual heat consumption − planned heat load; Deviation percentage = deviation value ÷ planned heat load × 100%.

[0064] For example, if the planned heat load for a day is 1000 MJ and the actual heat consumption is 1120 MJ, the deviation is 120 MJ, and the deviation percentage is 12%. This deviation is greater than 10% and is therefore considered an "excessive deviation."

[0065] The system uses the absolute value deviation percentage as the judgment standard: If the deviation is within ±10%, it is considered as “normal fluctuation”; If the deviation exceeds ±10%, it will be marked as "excessive deviation" and will enter the subsequent assessment mechanism.

[0066] The judgment process is fully automatic and requires no human intervention, ensuring timeliness and objectivity.

[0067] In order to encourage heat source plants to strictly implement the scheduling plan, the present invention establishes quantitative assessment rules. The specific contents are as follows: Daily deduction system: When a heat source plant has an "exceeding limit deviation" on a certain day, the dispatch assessment score for that day will be deducted by 1 point and recorded in the dispatch assessment ledger; Maximum cumulative deduction point limit: Each heat source plant is capped at 10 points per month. If the limit is exceeded, the plant will be placed on the "dispatch stability warning" list and will be required to submit a corrective measures report. Continuous deviation warning: If there are excessive deviations (either positive or negative) for three consecutive operating days, the system will automatically put the heat source plant on the "red warning list" and trigger a special operation review process; Audit mechanism linkage: The red alert status will be reported to the group's production management platform at the same time, and the person in charge of the regional dispatch center will take the lead in arranging offline technical inspections or special consultations.

[0068] This mechanism creates pressure feedback for rigid execution of scheduling through layered punishment and cumulative constraints, prompting operating units to actively improve execution accuracy.

[0069] To make the assessment results explainable and avoid misjudgment of occasional anomalies, the system automatically analyzes all deviation daily operating data and supplements it with manual review. The analysis mechanism includes: Meteorological anomaly identification: The system compares the actual temperature of the day with the weather forecast temperature. If the deviation exceeds a set threshold (such as 3 degrees Celsius), it is determined to be "forecast deviation impact"; Equipment failure record comparison: The system links the daily equipment operation logs of the heat source plant. If there are events such as boiler tripping, main pump failure, and communication interruption, they will be recorded as "equipment failure impact"; Determination of abnormal operation: By analyzing parameters such as the time interval between the issuance and execution of scheduling instructions and the frequency of temperature and flow adjustment, we can identify whether there are human factors such as operation delays and untimely adjustments; Dispatcher responsibility mark: The dispatcher needs to fill in the "Deviation Reason Classification Description" on the platform, select the options provided by the system or customize the reasons, and submit them to the system for archiving after confirmation.

[0070] This composite analysis model combines quantitative analysis with qualitative judgment to ensure scientific and accurate deviation classification, facilitating responsibility tracing and management improvement.

[0071] To further improve the overall system operation efficiency, the Group's production management department regularly conducts a weekly horizontal comparative analysis of the scheduling execution of each subsidiary's heat source plant. The specific process is as follows: Data summary: The system automatically generates a statistical table of the deviation between the weekly planned and actual heat consumption of each heat source plant, including daily deviation percentage, number of deductions, and deviation type distribution; Stability scoring: Based on the deviation frequency, average deviation amplitude and continuous deviation records, a heat source plant operation stability scoring model is formed to automatically rank each subsidiary; Abnormal area identification: Heat source plants with low scores are automatically marked and presented in graphical form on the group's scheduling large screen system.

[0072] Through this mechanism, on the one hand, cross-regional supervision and benchmarking of scheduling deviations can be achieved, and on the other hand, technical exchanges and level improvement among enterprises can be promoted, forming a virtuous closed loop of "problem exposure - mechanism constraints - strategy optimization".

[0073] Example 2, please refer to Figure 2 As shown, the heat supply precision scheduling system based on one source per day described in this embodiment includes: The thermal index assessment module categorizes each heat exchange station based on the energy-saving standards implemented in the building's construction era and building type factors. It then estimates the existing thermal index by investigating the building's energy-saving type, heat consumption during the standard heating season, and the average outdoor temperature, and comprehensively determines the thermal index of the heat exchange station units. A heat load prediction module calculates the heat load for the next day based on the heat index, the actual supply area, the indoor design temperature, the outdoor forecast temperature and the heating outdoor calculated temperature; The daily scheduling plan generation module, based on the next day's heat load and the primary pipe network hydraulic conditions, is guided by the production technology department to prepare a daily schedule for each source for the next day, which is then issued to the heat source plant after review; The plan execution and operation record module receives and strictly schedules the heat load according to the one-source-one-day plan, and records the actual heat consumption of the day; Deviation assessment and management module: When the deviation between the actual heat consumption and the planned heat consumption on the day exceeds ±10%, points will be deducted according to the deviation, and the production management department will inspect, guide and assess the implementation of each subsidiary.

[0074] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. A precise scheduling method for heat supply based on one source per day, characterized by: include: Each heat exchange station is categorized based on the energy-saving standards implemented in the building's construction era and building type. The existing thermal index is calculated by investigating the building's energy-saving type, heat consumption during the standard heating season, and the average outdoor temperature. The thermal index of the heat exchange station unit is then comprehensively determined. Calculate the heat load for the next day based on the heat index, the actual supply area, the indoor design temperature, the outdoor forecast temperature and the heating outdoor calculated temperature; Based on the next day's heat load and the primary pipe network hydraulic conditions, the production technology department will guide the preparation of a one-source-one-day plan for the next day, which will be issued to the heat source plant after review; The heat source plant receives and strictly follows the one-source-one-day schedule to schedule heat loads and records the actual heat consumption for the day; When the deviation between the actual heat consumption and the planned heat consumption on the day exceeds ±10%, points will be deducted according to the deviation, and the production management department will inspect, guide and evaluate the implementation of each subsidiary.

2. The method for accurately scheduling heat supply based on one source per day according to claim 1, characterized in that: The classification of each heat exchange station includes: Establish a database of building archives within the service area of ​​the heat exchange station, and enter the energy-saving design indicators and structural types of each building into the database according to the national or industry energy-saving standards corresponding to the building's construction year; Based on the energy-saving types of buildings in the archive database, the heat consumption per unit area of ​​each type of building is counted during the standard heating season, and the average outdoor temperature during the period is calculated; The ratio of the heat consumption per unit area to the average outdoor temperature is combined with the indoor design temperature of the building and the supply and return water temperature difference of the heat exchange station to convert it into an existing thermal index to form a benchmark thermal index for different types of heat exchange stations.

3. The method for accurately scheduling heat supply based on one source per day according to claim 2, characterized in that: The average outdoor temperature is calculated by weighting the daily maximum, minimum and average temperatures to improve the accuracy of thermal index estimation.

4. The method for accurately scheduling heat supply based on one source per day according to claim 3, characterized in that: Two-stage optimization of the baseline thermal index: In the first stage, the influence of abnormal operating conditions was eliminated through multivariate regression analysis based on the historical operating data of the heat exchange station; In the second stage, based on the optimized benchmark thermal index and the rated power ratio of the heat exchange station units, the units are divided into different grades according to the size of the service area to determine the final thermal index of the units used for the heat exchange station.

5. The method for accurately scheduling heat supply based on one source per day according to claim 1, characterized in that: Calculation of the next day's heat load further includes: The difference between the indoor design temperature and the outdoor temperature forecast for the next day is calculated as the initial temperature difference, and the difference between the heating outdoor calculated temperature and the forecast temperature is calculated as the corrected temperature difference; Multiply the heat index by the actual supply area, then multiply the result by the initial temperature difference, and perform a division operation using the corrected temperature difference as a divisor to obtain the nominal heat load for the day's scheduling; Based on the analysis of historical operational deviations, dynamic correction coefficients of enclosure structure performance, wind speed, and geographical orientation are introduced to perform weighted correction on the nominal heat load to improve prediction accuracy.

6. The method for accurately scheduling heat supply based on one source per day according to claim 5, characterized in that: The dynamic correction coefficient is automatically updated through an adaptive feedback algorithm according to the deviation between the actual heat load and the predicted heat load of the previous day, so as to achieve continuous optimization of the future prediction model.

7. The method for accurately scheduling heat supply based on one source per day according to claim 6, characterized in that: The outdoor temperature forecast is integrated with multiple meteorological models, and the average temperature of the next day is obtained by weighted averaging, which is used as the basis for temperature difference calculation.

8. The method for accurately scheduling heat supply based on one source per day according to claim 7, characterized in that: A sub-item coefficient for the actual supply area divided by building function is introduced, and the areas of residential areas, commercial areas and public building areas are weighted separately to reflect the differences in heat consumption of different building types.

9. The method for accurately scheduling heat supply based on one source per day according to claim 1, characterized in that: After the daily operation is completed, the difference between the actual heat consumption of the heat source plant and the planned heat load in the one-source-one-day plan table is calculated to determine the deviation percentage. When the absolute value of the deviation exceeds 10% of the planned heat load, it is determined to be an over-limit deviation. If the heat source plant deviation is an over-limit deviation, one point will be deducted for each over-limit deviation, accumulated to ten points, and recorded in the dispatch assessment ledger; If the limit is exceeded for three consecutive days, the vehicle will be placed on the red alert list, triggering a special operation review; For deviation days, the system automatically generates a deviation analysis report, providing preliminary explanations based on weather anomalies, equipment failures, and operational deviations. A dispatch specialist then fills in a categorized explanation of the causes and uploads it to the group management platform for filing. The production management department conducts a horizontal comparison of the deviations between the execution plans and actual operations of all subsidiaries every week, identifies areas with poor scheduling stability, and organizes scheduling technology seminars to review experiences and optimize operating strategies.

10. A precise heat supply scheduling system based on one source per day, for implementing the precise heat supply scheduling method based on one source per day according to any one of claims 1 to 9, characterized in that: include: The thermal index assessment module categorizes each heat exchange station based on the energy-saving standards implemented in the building's construction era and building type factors. It then estimates the existing thermal index by investigating the building's energy-saving type, heat consumption during the standard heating season, and the average outdoor temperature, and comprehensively determines the thermal index of the heat exchange station units. A heat load prediction module calculates the heat load for the next day based on the heat index, the actual supply area, the indoor design temperature, the outdoor forecast temperature and the heating outdoor calculated temperature; The daily scheduling plan generation module, based on the next day's heat load and the primary pipe network hydraulic conditions, is guided by the production technology department to prepare a daily schedule for each source for the next day, which is then issued to the heat source plant after review; The plan execution and operation record module receives and strictly schedules the heat load according to the one-source-one-day plan, and records the actual heat consumption of the day; Deviation assessment and management module: When the deviation between the actual heat consumption and the planned heat consumption on the day exceeds ±10%, points will be deducted according to the deviation, and the production management department will inspect, guide and assess the implementation of each subsidiary.

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