Heat supply station energy-saving control method and device based on load feedback

Abstract

The invention provides a heat supply station energy-saving control method and device based on load feedback, relates to the technical field of automatic control, and solves the technical problems that in the prior art, core control parameters cannot be dynamically and cooperatively adjusted based on the actual load of a user, so that the energy consumption of a heat supply station is high, and the heat supply quality stability is insufficient. The method specifically comprises the steps that core load parameters of a heat supply station and the average indoor temperature of a user are obtained; the core load parameters and the average indoor temperature of the user are preprocessed, and correlation indexes are calculated; inputting the associated indexes into a heat supply station load feedback control model, and adjusting the boiler combustion intensity and the circulating water pump frequency; and based on the heat supply station load feedback control model, continuously feeding back and adjusting the core load parameter and the average indoor temperature of the user according to a period, and then performing closed-loop control on the heat supply station based on the continuously adjusted core load parameter and the average indoor temperature of the user. The method is used for energy-saving control of the heat supply station.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic control, in particular to a heat supply station energy-saving control method and device based on load feedback. BACKGROUND

[0002] As the core heat supply facility for winter livelihood security and industrial production, the energy-saving control of the heat supply station is of great significance for reducing energy consumption and ensuring the stability of heat supply. At present, the existing heat supply station energy-saving control methods mostly adopt extensive control based on preset fixed parameters, or rely on single outdoor environment temperature parameter for feedback regulation, that is, simply increase or decrease the boiler combustion intensity according to the outdoor temperature. Such methods not only have the problem of over-supply or under-supply due to fixed parameter control, but also ignore the multi-parameter coordination due to single outdoor temperature feedback. Therefore, the existing technology has the technical problem of being unable to dynamically coordinate and adjust the core control parameters based on the actual load of users, resulting in high energy consumption of the heat supply station and insufficient stability of heat supply quality. SUMMARY

[0003] The present application provides a heat supply station energy-saving control method and device based on load feedback, which solves the technical problem of the existing technology that cannot dynamically coordinate and adjust the core control parameters based on the actual load of users, resulting in high energy consumption of the heat supply station and insufficient stability of heat supply quality.

[0004] To achieve the above purpose, the present application adopts the following technical scheme: In a first aspect, a heat supply station energy-saving control method based on load feedback is provided, comprising: obtaining core load parameters of the heat supply station and indoor average temperature of users; the core load parameters include water supply temperature, return water temperature and circulation flow; preprocessing the core load parameters and the indoor average temperature of users and calculating correlation indexes; the correlation indexes include actual heat supply, user temperature deviation and supply-return water temperature difference; inputting the correlation indexes into a heat supply station load feedback control model to adjust the boiler combustion intensity and the circulation water pump frequency; the heat supply station load feedback control model includes a user temperature-combustion intensity closed loop and a supply-return water temperature difference-circulation flow closed loop; the user temperature-combustion intensity closed loop is used to adjust the boiler combustion intensity based on the adaptive PID algorithm through the user temperature deviation and the supply-return water temperature difference, and the supply-return water temperature difference-circulation flow closed loop is used to control the circulation water pump frequency based on the heat correction algorithm through the supply-return water temperature difference and the actual heat supply; based on the heat supply station load feedback control model, the core load parameters and the indoor average temperature of users are continuously feedback adjusted at a period, and then the heat supply station is controlled in a closed loop based on the continuously adjusted core load parameters and the indoor average temperature of users.

[0005] In a possible implementation manner of the first aspect, the core load parameter and the user indoor average temperature are preprocessed and the correlation index is calculated, including: performing outlier elimination on the supply water temperature, the return water temperature, the circulation flow and the user indoor average temperature by using a 3σ criterion to obtain effective data; performing sliding average filtering processing on the effective data to eliminate transient fluctuations to obtain smoothed data; and calculating the correlation index based on the smoothed data; the process of calculating the correlation index is: calculating a supply-return water temperature difference based on a difference between the supply water temperature and the return water temperature; calculating a user temperature deviation by using a difference between the user indoor average temperature and a set indoor target temperature; and calculating an actual heating capacity based on the supply-return water temperature difference, the circulation flow, and the density and specific heat capacity of water.

[0006] In a possible implementation manner of the first aspect, the boiler combustion intensity is adjusted based on the user temperature deviation and the supply-return water temperature difference by using an adaptive PID algorithm, including: determining a proportional coefficient, an integral coefficient and a differential coefficient of the adaptive PID algorithm based on an absolute value of the user temperature deviation; calculating an adjustment amount of the boiler combustion intensity based on the determined PID parameters, a current user temperature deviation, a summation value of historical user temperature deviations, and a difference between the current user temperature deviation and a user temperature deviation of a previous period, in combination with a thermal efficiency correction term of the supply-return water temperature difference; and updating a current boiler combustion intensity based on a boiler combustion intensity of the previous period and the adjustment amount.

[0007] In a possible implementation manner of the first aspect, the proportional coefficient, the integral coefficient and the differential coefficient of the adaptive PID algorithm are determined based on the absolute value of the user temperature deviation, including: when the absolute value of the user temperature deviation is greater than a maximum deviation threshold, the proportional coefficient, the integral coefficient and the differential coefficient of the adaptive PID algorithm take a first PID coefficient combination; when the absolute value of the user temperature deviation is less than the maximum deviation threshold and greater than a minimum deviation threshold, the proportional coefficient, the integral coefficient and the differential coefficient of the adaptive PID algorithm take a second PID coefficient combination; and when the absolute value of the user temperature deviation is less than the minimum deviation threshold, the proportional coefficient, the integral coefficient and the differential coefficient of the adaptive PID algorithm take a third PID coefficient combination.

[0008] In a possible implementation manner of the first aspect, the adjustment amount of the boiler combustion intensity satisfies the following formula:

[0009] wherein, the adjustment amount of the boiler combustion intensity is denoted as K, the proportional coefficient is denoted as Kp, the integral coefficient is denoted as Ki, the differential coefficient is denoted as Kd, the user temperature deviation of the current period is denoted as e(k), the user temperature deviation of the previous period is denoted as e(k-1), is a heat efficiency correction coefficient, is a supply-return water temperature difference constraint function, , is a supply-return water temperature difference of the current period.

[0010] In combination with the first aspect, in a possible implementation manner, the circulating water pump frequency is controlled based on the heat correction algorithm through the supply-return water temperature difference and the actual heat supply, comprising: obtaining a reference heat supply, a reference outdoor environment temperature of a historical same period, and an outdoor environment temperature of the current period; calculating a heat supply deviation based on the reference heat supply, the reference outdoor environment temperature of the historical same period, the outdoor environment temperature of the current period, and the actual heat supply, and calculating a temperature difference deviation based on a set target supply-return water temperature difference and the supply-return water temperature difference of the current period; determining a circulating water pump target frequency of the current period in combination with a reference frequency of the circulating water pump, the heat supply deviation and a corresponding heat supply deviation weight coefficient, the temperature difference deviation and a corresponding temperature difference deviation weight coefficient; sending the circulating water pump target frequency to a variable frequency control unit of the circulating water pump, and updating the operating frequency of the circulating water pump.

[0011] In combination with the first aspect, in a possible implementation manner, the circulating water pump target frequency of the current period satisfies the following formula:

[0012] wherein, is a circulating water pump frequency of the current period, is a reference frequency of the circulating water pump, is a heat supply deviation weight coefficient, is a temperature difference deviation weight coefficient, and satisfies , is a heat supply deviation, , is a target heat supply of the current period, is a reference heat supply of the historical same period, is a temperature correction coefficient, is a reference outdoor environment temperature of the historical same period, and T is an outdoor environment temperature of the current period, is an actual heat supply of the current period, is a temperature difference deviation, , is a set target supply-return water temperature difference.

[0013] In a possible implementation manner of the first aspect, based on the heat supply station load feedback control model, the core load parameter and the average indoor temperature of the user are continuously fed back and adjusted in a period, and then closed-loop control is performed on the heat supply station based on the continuously adjusted core load parameter and the average indoor temperature of the user, including: obtaining the core load parameter and the average indoor temperature of the user adjusted by the load feedback control model in a preset period, performing outlier elimination on the collected parameters by using the 3σ criterion to obtain effective parameters for closed-loop control; inputting the effective parameters into the heat supply station load feedback control model to update the historical user temperature deviation summation value, the actual heat supply quantity record and the load state data stored in the model; based on the updated model data, it is verified through the user temperature-combustion intensity closed loop whether the current boiler combustion intensity matches the average indoor temperature demand of the user, and through the supply and return water temperature difference-circulation flow closed loop whether the current circulation water pump frequency matches the core load parameter efficiency requirement, if not, re-generate corresponding adjustment instructions to perform adjustment, and repeat the above period obtaining, data updating and adjustment checking steps.

[0014] In a possible implementation manner of the first aspect, based on the heat supply station load feedback control model, the core load parameter and the average indoor temperature of the user are continuously fed back and adjusted in a period, and then closed-loop control is performed on the heat supply station based on the continuously adjusted core load parameter and the average indoor temperature of the user, including: obtaining the core load parameter and the average indoor temperature of the user adjusted by the load feedback control model in a preset period, performing outlier elimination on the collected parameters by using the 3σ criterion to obtain effective parameters for closed-loop control; inputting the effective parameters into the heat supply station load feedback control model to update the historical user temperature deviation summation value, the actual heat supply quantity record and the load state data stored in the model; based on the updated model data, it is verified through the user temperature-combustion intensity closed loop whether the current boiler combustion intensity matches the average indoor temperature demand of the user, and through the supply and return water temperature difference-circulation flow closed loop whether the current circulation water pump frequency matches the core load parameter efficiency requirement, if not, re-generate corresponding adjustment instructions to perform adjustment, and repeat the above period obtaining, data updating and adjustment checking steps.

[0015] In a possible implementation manner of the first aspect, based on the heat supply station load feedback control model, the core load parameter and the average indoor temperature of the user are continuously fed back and adjusted in a period, and then closed-loop control is performed on the heat supply station based on the continuously adjusted core load parameter and the average indoor temperature of the user, including: obtaining the core load parameter and the average indoor temperature of the user adjusted by the load feedback control model in a preset period, performing outlier elimination on the collected parameters by using the 3σ criterion to obtain effective parameters for closed-loop control; inputting the effective parameters into the heat supply station load feedback control model to update the historical user temperature deviation summation value, the actual heat supply quantity record and the load state data stored in the model; based on the updated model data, it is verified through the user temperature-combustion intensity closed loop whether the current boiler combustion intensity matches the average indoor temperature demand of the user, and through the supply and return water temperature difference-circulation flow closed loop whether the current circulation water pump frequency matches the core load parameter efficiency requirement, if not, re-generate corresponding adjustment instructions to perform adjustment, and repeat the above period obtaining, data updating and adjustment checking steps.

[0016] In a fourth aspect, the present application provides a load feedback based energy-saving control device for a heating station, comprising: a processor and a storage medium; the storage medium comprises instructions, and the processor is configured to execute the instructions to implement the method described in the first aspect and any possible implementation manner of the first aspect. The load feedback based energy-saving control device for the heating station can be an electronic device or a chip in the electronic device.

[0017] In a fifth aspect, the present application provides a load feedback based energy-saving control system for a heating station, comprising: a temperature acquisition module, a flow rate measurement module and a load feedback based energy-saving control device for the heating station; wherein the temperature acquisition module is configured to acquire a supply water temperature, a return water temperature, an average indoor temperature of users and an outdoor environment temperature; the flow rate measurement module is configured to acquire a circulation flow rate; the load feedback based energy-saving control device for the heating station is configured to acquire a core load parameter of the heating station and the average indoor temperature of the users; to preprocess the core load parameter and the average indoor temperature of the users and calculate a correlation index; to input the correlation index into a load feedback control model for the heating station, to adjust a boiler combustion intensity and a circulation water pump frequency; and to continuously feedback adjust the core load parameter and the average indoor temperature of the users based on the load feedback control model for the heating station in a period, and to perform closed-loop control on the heating station based on the continuously adjusted core load parameter and the average indoor temperature of the users.

[0018] In a sixth aspect, the present application provides a computer program product comprising instructions which, when the computer program product is executed on a load feedback based energy-saving control device for a heating station, cause the load feedback based energy-saving control device for the heating station to perform the method described in the first aspect and any possible implementation manner of the first aspect.

[0019] The present application provides a load feedback based energy-saving control method and device for a heating station, which can dynamically adjust a core load parameter through a double closed-loop cooperation, to achieve the dual goals of reducing energy consumption of heating and stabilizing indoor temperature of users. The core lies in taking the average indoor temperature of users, a supply-return water temperature difference and other actual load parameters as feedback, to cooperatively control a boiler combustion intensity and a circulation water pump frequency through a user temperature-combustion intensity closed loop and a supply-return water temperature difference-circulation flow rate closed loop, to avoid energy waste caused by over-supply / under-supply due to fixed parameter control, and to cooperatively optimize heat exchange efficiency through multiple parameters, so as to simultaneously consider energy saving and heating stability compared with a traditional control method.

[0020] It should be understood that the description of technical features, technical solutions, advantages or similar language in the present application does not imply that all features and advantages can be realized in any single embodiment. On the contrary, it can be understood that the description of a feature or advantage means that the specific technical feature, technical solution or advantage is included in at least one embodiment. Therefore, the description of technical features, technical solutions or advantages in the specification does not necessarily refer to the same embodiment. Further, the technical features, technical solutions and advantages described in the embodiments can be combined in any appropriate manner. Those skilled in the art will understand that the embodiments can be implemented without one or more specific technical features, technical solutions or advantages of a particular embodiment. In other embodiments, additional technical features and advantages can be identified in specific embodiments that do not embody all embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 A system architecture diagram of a load feedback-based energy-saving control system of a heat supply station provided by an embodiment of the present application; Figure 2 A flowchart of a load feedback-based energy-saving control method of a heat supply station provided by an embodiment of the present application; Figure 3 A flowchart of another load feedback-based energy-saving control method of a heat supply station provided by an embodiment of the present application; Figure 4 A flowchart of another load feedback-based energy-saving control method of a heat supply station provided by an embodiment of the present application; Figure 5 A flowchart of another load feedback-based energy-saving control method of a heat supply station provided by an embodiment of the present application; Figure 6 A structural diagram of a load feedback-based energy-saving control device of a heat supply station provided by an embodiment of the present application; Figure 7 A hardware structural diagram of a load feedback-based energy-saving control device of a heat supply station provided by an embodiment of the present application. DETAILED DESCRIPTION

[0022] In the description of the present application, unless otherwise specified, " / " means "or", for example, A / B can mean A or B. "And / or" in this document is only a description of the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can mean that A exists alone, A and B exist together, and B exists alone. In addition, "at least one" means one or more, and "multiple" means two or more. "First", "second", etc. do not limit the quantity and execution order, and "first", "second", etc. do not necessarily mean different.

[0023] It should be noted that in this application, the words "exemplary" or "for example" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "for example" should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of "exemplary" or "for example" is intended to present concepts in a concrete manner.

[0024] The load feedback-based heating station energy-saving control method provided by the embodiments of the present application can be applied to a load feedback-based heating station energy-saving control system as shown in the figure. Figure 1 The system comprises a temperature acquisition module 101, a flow rate measurement module 102, and a load feedback-based heating station energy-saving control device 103.

[0025] The temperature acquisition module 101 is configured to acquire the supply water temperature, the return water temperature, the user indoor average temperature, and the outdoor environment temperature; the flow rate measurement module 102 is configured to acquire the circulating flow rate; and the load feedback-based heating station energy-saving control device 103 is configured to acquire the core load parameter of the heating station and the user indoor average temperature, to preprocess the core load parameter and the user indoor average temperature and calculate the correlation index, to input the correlation index into the heating station load feedback control model, to adjust the boiler combustion intensity and the circulating water pump frequency, to continuously feedback adjust the core load parameter and the user indoor average temperature based on the heating station load feedback control model, and to perform closed-loop control on the heating station based on the continuously adjusted core load parameter and user indoor average temperature.

[0026] To solve the technical problem that the prior art cannot dynamically and cooperatively adjust the core control parameter based on the actual load of the user, resulting in high energy consumption of the heating station and insufficient stability of the heating quality, the embodiments of the present application provide a load feedback-based heating station energy-saving control method, which comprises: acquiring the core load parameter of the heating station and the user indoor average temperature; preprocessing the core load parameter and the user indoor average temperature and calculating the correlation index; inputting the correlation index into the heating station load feedback control model, adjusting the boiler combustion intensity and the circulating water pump frequency; continuously feedback adjusting the core load parameter and the user indoor average temperature based on the heating station load feedback control model; and performing closed-loop control on the heating station based on the continuously adjusted core load parameter and user indoor average temperature. Based on this, the core load parameter is dynamically and cooperatively adjusted through the double closed-loop, the dual goals of reducing the heating energy consumption and stabilizing the user indoor temperature are achieved, and the technical problem that the prior art cannot dynamically and cooperatively adjust the core control parameter based on the actual load of the user, resulting in high energy consumption of the heating station and insufficient stability of the heating quality, is effectively solved.

[0027] Figure 2A flowchart of the energy-saving control method of the heat supply station based on load feedback provided by the embodiments of the present application is shown in FIG. 1, which comprises the following steps: Figure 2 In step 201, the energy-saving control device of the heat supply station based on load feedback acquires core load parameters of the heat supply station and average indoor temperature of users.

[0028] The core load parameters include water supply temperature, return water temperature and circulation flow rate, and the average indoor temperature of users is the statistical average of the temperature of multiple user monitoring points.

[0029] In the embodiments of the present application, the control device acquires the core load parameters through temperature sensors and flow collectors deployed in the heat supply pipe network, acquires indoor temperature data at a preset time interval through user end room temperature collection equipment, and then calculates the average temperature by statistically calculating the data of multiple users.

[0030] It should be noted that the parameter acquisition needs to ensure time synchronization to avoid affecting the accuracy of subsequent analysis due to time difference.

[0031] As an example, in the heat supply scenario of a residential community, the parameters are collected through temperature sensors and flow meters of the pipe network of each building, and the average temperature is calculated in combination with the data of room temperature collectors at a height of 1.2-1.5 m in users' homes.

[0032] Based on the above steps, the basic data of the operation state of the heat supply system and the demand of the user end are obtained, which provides data support for subsequent control.

[0033] In step 202, the energy-saving control device of the heat supply station based on load feedback preprocesses the core load parameters and the average indoor temperature of users and calculates correlation indexes.

[0034] The correlation indexes include actual heat supply, user temperature deviation and supply-return water temperature difference.

[0035] In the embodiments of the present application, the control device first performs data cleaning on the collected parameters to eliminate obvious outliers, then eliminates transient fluctuations through sliding average filtering, and finally calculates each correlation index according to a preset algorithm.

[0036] Based on the above steps, standardized indexes that can be directly used as inputs of the control model are obtained, which improves the accuracy of control decisions.

[0037] In step 203, the energy-saving control device of the heat supply station based on load feedback inputs the correlation indexes into a load feedback control model of the heat supply station to adjust the combustion intensity of the boiler and the frequency of the circulating water pump.

[0038] ​The heat supply station load feedback control model comprises a user temperature-combustion intensity closed loop and a supply and return water temperature difference-circulation flow closed loop; the user temperature-combustion intensity closed loop is used for adjusting the boiler combustion intensity based on the adaptive PID algorithm through the user temperature deviation and the supply and return water temperature difference; and the supply and return water temperature difference-circulation flow closed loop is used for controlling the circulation water pump frequency based on the heat correction algorithm through the supply and return water temperature difference and the actual heat supply.

[0039] In the embodiment of the application, the control device inputs the preprocessed correlation index into the preset double closed loop control model, the model generates the adjustment signals of the boiler combustion intensity and the circulation water pump frequency according to the index values respectively, and sends them to the corresponding execution mechanisms.

[0040] As an example, in the heat supply station of an industrial park, the model receives the actual heat supply, the user temperature deviation and other indexes, and outputs the boiler damper opening adjustment instruction and the water pump variable frequency signal.

[0041] Based on the above steps, the precise regulation and control of the key operating parameters of the heat supply system are realized, so that the system operating state matches the current load demand.

[0042] In step 204, the heat supply station energy saving control device based on load feedback continuously feeds back the adjustment of the core load parameter and the user indoor average temperature based on the heat supply station load feedback control model according to a period, and then performs closed loop control on the heat supply station based on the continuously adjusted core load parameter and the user indoor average temperature.

[0043] In the embodiment of the application, the control device repeatedly executes the processes of parameter collection, preprocessing, model calculation and execution adjustment according to a preset period, and corrects the control instruction by continuously monitoring the parameter changes after the adjustment.

[0044] It should be noted that the feedback period can be set according to the system response speed to balance the control precision and energy consumption cost.

[0045] As an example, a heat supply station of a certain community sets 30 seconds as a feedback period, and updates the user room temperature and the pipe network parameters in real time to continuously optimize the operating state of the boiler and the water pump.

[0046] Based on the above steps, a continuous and dynamic closed loop control mechanism is formed to ensure the long-term stable and efficient operation of the heat supply system.

[0047] Based on the above technical solution, through the whole-process closed loop management from data collection and processing to dynamic regulation and control, the precise matching of the heat supply system operating state and the user load demand is realized, the indoor temperature of the user is ensured to be stable, and the heat supply energy consumption is effectively reduced, so that the heat supply quality and energy saving benefits are taken into account.

[0048] In a possible implementation manner, the above Figure 2 For example, Figure 3As shown, the process of preprocessing the core load parameters and the user indoor average temperature and calculating the correlation index in step 202 can be implemented through steps 301-303 as follows: Step 301: The heating station energy-saving control device based on load feedback adopts the 3σ criterion to remove outliers of the water supply temperature, return water temperature, circulation flow rate and user indoor average temperature, and obtains effective data.

[0049] The 3σ criterion refers to a statistical method for determining outliers if the data deviates from the mean by more than 3 times the standard deviation.

[0050] In the embodiments of the present application, the control device first calculates the mean and standard deviation of each parameter, and then iterates through the data points to remove data with an absolute deviation greater than 3 times the standard deviation.

[0051] It should be noted that if the data distribution deviates from the normal distribution, the determination rule can be adjusted or other anomaly detection methods can be used.

[0052] As an example, a point of the water supply temperature of a certain heating station that is much higher than the mean and exceeds 3 times the standard deviation is determined as an outlier and removed.

[0053] Based on the above steps, the error data can be removed to ensure the reliability of subsequent calculations.

[0054] Step 302: The heating station energy-saving control device based on load feedback uses sliding average filtering to process the effective data to eliminate transient fluctuations and obtain smoothed data.

[0055] The sliding average filtering is a method of taking the average of consecutive data to weaken transient fluctuations.

[0056] In the embodiments of the present application, the control device sets the sliding window length (such as the last 5 effective data points) and calculates the average of the data in each window as smoothed data.

[0057] As an example, when the circulation flow rate data has small transient fluctuations, the average value is calculated through a sliding window of 3 data points to obtain smooth data.

[0058] Based on the above steps, transient interference is eliminated, and the data trend is more consistent with the actual operation law.

[0059] Step 303: The heating station energy-saving control device based on load feedback calculates the correlation index based on the smoothed data.

[0060] In an embodiment of the present application, the control device combines the physical properties of water, calculates the actual heating amount from the smoothed supply and return water temperatures and circulation flow, and simultaneously calculates the user temperature deviation and the supply and return water temperature difference. The process of calculating the associated indicators is as follows: the supply and return water temperature difference is calculated based on the difference between the supply water temperature and the return water temperature; the user temperature deviation is calculated by the difference between the user's indoor average temperature and the set indoor target temperature; the actual heating amount is calculated based on the supply and return water temperature difference, the circulation flow, and the density and specific heat capacity of water.

[0061] As an example, the smoothed data after sliding average filtering is: water supply temperature 55℃, return water temperature 42℃, circulation flow 80m³ / h, set indoor target temperature 20℃, user indoor average temperature 19℃, water density 1000kg / m³, specific heat capacity 4.186kJ / (kg ℃); the supply and return water temperature difference is 55℃-42℃=13℃, the user temperature deviation is 19℃-20℃=-1℃, and the actual heat supply is 4.186kJ / (kg ℃)×1000kg / m³×80m³ / h×13℃÷3600s / h≈1219kW.

[0062] Based on the above steps, an accurate correlation index reflecting the matching degree between load and demand is obtained, providing reliable input for subsequent control.

[0063] Based on the above technical solution, the data quality is improved through the progressive processing of outlier elimination, smoothing filtering and correlation index calculation, so that the control model can make decisions based on more accurate inputs, ensuring the accuracy and stability of heat supply regulation.

[0064] In a possible implementation, combining the above Figure 2 ,like Figure 4 As shown, the process of adjusting the boiler combustion intensity based on the adaptive PID algorithm by the user temperature deviation and the supply and return water temperature difference in step 203 can be specifically implemented by the following steps 401 to 403: Step 401: The heat supply station energy-saving control device based on load feedback determines the proportional coefficient, integral coefficient and differential coefficient of the adaptive PID algorithm based on the absolute value of the user temperature deviation.

[0065] Among them, the absolute value of the user temperature deviation is the absolute value of the difference between the current user's indoor average temperature and the set indoor target temperature. The proportional coefficient, integral coefficient, and differential coefficient of the adaptive PID algorithm are used to adjust the regulation response speed, eliminate steady-state errors, and suppress overshoot fluctuations, respectively.

[0066] In the embodiment of the present application, the control device first acquires the user temperature deviation calculated in the current period, compares the absolute value of the user temperature deviation with the preset deviation threshold, and then matches the corresponding PID coefficient combination according to the comparison result.

[0067] Optionally, the PID coefficient determination mode based on the absolute value of the user temperature deviation satisfies: when the absolute value of the user temperature deviation is greater than the maximum deviation threshold, the first PID coefficient combination is taken; when the absolute value is less than the maximum deviation threshold and greater than the minimum deviation threshold, the second PID coefficient combination is taken; and when the absolute value is less than the minimum deviation threshold, the third PID coefficient combination is taken.

[0068] As an example, assuming that the maximum deviation threshold is 2℃ and the minimum deviation threshold is 1℃, if the absolute value of the current user temperature deviation is 3℃, which is greater than the maximum threshold, the first PID coefficient combination is taken (Kp=0.8, Ki=0.02, Kd=0.1); if the absolute value is 1.5℃, which is between the two thresholds, the second PID coefficient combination is taken (Kp=0.5, Ki=0.01, Kd=0.05); and if the absolute value is 0.8℃, which is less than the minimum threshold, the third PID coefficient combination is taken (Kp=0.3, Ki=0.005, Kd=0.02).

[0069] Based on the above steps, the adaptive PID coefficient selection mode based on the absolute value of the user temperature deviation and the threshold can meet the energy-saving control demand based on load feedback and dynamically adapt the heating regulation strategy. When the user temperature deviation is large, the PID coefficient combination with high responsiveness is used to quickly correct the deviation, so as to avoid the under-supply leading to the non-compliance of the indoor temperature of the user; and when the deviation is small, the coefficient combination with low fluctuation is used to reduce the regulation frequency, so as to avoid the invalid energy consumption caused by over-supply. The value selection mode not only guarantees the stability of the heating quality, but also reduces unnecessary energy consumption.

[0070] In step 402, the heating station energy-saving control device based on load feedback calculates the regulation amount of the boiler combustion intensity based on the determined PID parameter, the current user temperature deviation, the sum of the historical user temperature deviations, and the difference between the current and previous user temperature deviations, and the heat efficiency correction term of the supply and return water temperature difference.

[0071] The sum of the historical user temperature deviations is the cumulative value of the user temperature deviations in the previous N periods (N≥5) before the current period, and the heat efficiency correction term of the supply and return water temperature difference is used to dynamically adjust the regulation amplitude according to the heat exchange efficiency.

[0072] ​​​​​​​​​In the embodiment of the present application, the control device first calls the PID parameters determined in step 401, then reads the stored historical user temperature deviation data to calculate the sum value, calculates the difference value of the current and last period deviation, and simultaneously calculates the thermal efficiency correction term according to the current supply and return water temperature difference, and finally substitutes each parameter into the formula to calculate the adjustment amount.

[0073] Optionally, the adjustment amount of the boiler combustion intensity satisfies the following formula:

[0074] wherein, is the adjustment amount of the boiler combustion intensity, is a proportional coefficient, is an integral coefficient, is a differential coefficient, is the user temperature deviation of the current period, is the user temperature deviation of the last period, is a thermal efficiency correction coefficient, is a supply and return water temperature difference constraint function, , is the supply and return water temperature difference of the current period.

[0075] As an example, it is assumed that =0.5, =0.01, =0.05, the current =-1℃ (the indoor temperature is lower than the target), =-3℃ (the deviation sum of the previous 5 periods), =-1-(-0.8)=-0.2℃, =0.1, =9℃, and substitution into the formula gives 0.5×(-1)+0.01×(-3)+0.05×(-0.2)+0.1×1=-0.44, the negative sign indicates that the combustion intensity needs to be increased, and the specific boiler combustion intensity can be converted according to the calculated adjustment amount according to the system calibration, for example, the adjustment amount 0.44 corresponds to an upward adjustment of 8% of the damper opening degree.

[0076] Based on the above steps, the precise calculation of the boiler combustion intensity adjustment amount is realized, the temperature deviation correction and thermal efficiency optimization are taken into account, and blind adjustment is avoided.

[0077] Step 403, the heating station energy-saving control device based on load feedback updates the current boiler combustion intensity based on the boiler combustion intensity and the adjustment amount of the last period.

[0078] Wherein, the boiler combustion intensity of the last period is the actual operation intensity of the boiler after the last round of adjustment (such as the percentage of damper opening, fuel supply amount, etc.), and the current boiler combustion intensity is the control parameter updated for the operation of this round.

[0079] In the embodiment of the present application, the control device reads the boiler combustion intensity data stored in the last period, superimposes it with the adjustment amount calculated in step 402, and if the superimposed result exceeds the preset safe operation range (such as 0-100% damper opening), the extreme value in the range is taken as the current combustion intensity.

[0080] As an example, suppose the boiler combustion intensity of the last period is 60% (damper opening), and the adjustment amount calculated in step 402 is +8%, then the current combustion intensity is updated to 60%+8%=68%, which does not exceed the safe range; if the adjustment amount is +45%, then it is updated to 100%.

[0081] Based on the above steps, the dynamic updating of the boiler combustion intensity is realized, so that the combustion state matches the current load demand, providing a basis for stabilizing the indoor temperature of the user.

[0082] In a possible implementation, in combination with the above Figure 2 As shown in Figure 4 The process of step 203 of controlling the circulating water pump frequency based on the heat correction algorithm through the supply and return water temperature difference and the actual heating amount can be implemented through the following steps 404-407: Step 404, the heating station energy-saving control device based on load feedback obtains the reference heating amount, the reference outdoor environment temperature of the historical same period, and the outdoor environment temperature of the current period.

[0083] Wherein, the historical same period refers to a historical period close to the current date and time period, the reference heating amount is the optimal heating amount of the heating system matching the user demand in the historical same period, and the reference outdoor environment temperature is the outdoor temperature corresponding to the historical same period.

[0084] In the embodiment of the present application, the control device retrieves the heating operation data of the historical same period through the data storage module, extracts the reference heating amount and the reference outdoor environment temperature, and simultaneously collects the outdoor environment temperature of the current period through the temperature sensor deployed outdoors.

[0085] It should be noted that the historical same period data needs to be selected from a period with similar heating load characteristics, such as normal operation period excluding extreme weather influence, to ensure data reference.

[0086] As an example, in the heating scene of a certain community in mid-December, the control device retrieves the reference heating amount of 8MW and the reference outdoor environment temperature of-3℃ in mid-December last year, and simultaneously collects the outdoor environment temperature of-5℃ in the current period.

[0087] Based on the above steps, the basic reference data for heating capacity correction is obtained, which provides a basis for subsequent matching of the target heating capacity under the current environment.

[0088] Step 405, the load feedback-based heating station energy-saving control device calculates the heating capacity deviation based on the historical same period reference heating capacity, the reference outdoor environment temperature, the outdoor environment temperature of the current period and the actual heating capacity, and calculates the temperature difference deviation based on the set target supply-return water temperature difference and the supply-return water temperature difference of the current period.

[0089] Among them, the heating capacity deviation is the relative difference between the current target heating capacity and the actual heating capacity, and the temperature difference deviation is the relative difference between the set target supply-return water temperature difference and the current supply-return water temperature difference, both of which are used to reflect the deviation degree of the current running state from the ideal state.

[0090] In the embodiments of the present application, the control device first calculates the current target heating capacity according to the historical reference data and the current outdoor temperature, and then calculates the heating capacity deviation using the target heating capacity and the current actual heating capacity; at the same time, the set target supply-return water temperature difference is read and the temperature difference deviation is calculated with the current supply-return water temperature difference, and the calculation process adopts the form of relative difference, that is, deviation=(target value-actual value) / target value.

[0091] As an example, assuming that the historical reference heating capacity is 8MW, the reference outdoor temperature is-3℃, and the current outdoor temperature is-5℃ (temperature correction coefficient k=0.05), then the current target heating capacity is =8×[1+0.05×(-3-(-5))]=8.8MW; the current actual heating capacity is =8.2MW, the heating capacity deviation is =(8.8-8.2) / 8.8≈0.068; the set target supply-return water temperature difference is =10℃, the current =9℃, the temperature difference deviation is =(10-9) / 10=0.1.

[0092] Based on the above steps, the deviation degree of the current heating capacity and the supply-return water temperature difference is quantified, which provides a clear basis for subsequent circulating water pump frequency adjustment.

[0093] Step 406, the load feedback-based heating station energy-saving control device determines the target frequency of the circulating water pump in the current period in combination with the reference frequency of the circulating water pump, the heating capacity deviation and the corresponding heating capacity deviation weight coefficient, the temperature difference deviation and the corresponding temperature difference deviation weight coefficient.

[0094] Among them, the reference frequency of the circulating water pump is the water pump operating frequency matched with the optimal heat exchange efficiency in the historical same period, and the weight coefficient (β, γ) is used to allocate the influence degree of the heating capacity deviation and the temperature difference deviation on the frequency adjustment, and β+γ=1.

[0095] In the embodiments of the present application, the control device first determines the weight coefficient according to the current outdoor environment temperature interval, such as β=0.8, γ=0.2 when the outdoor temperature is <-5℃, to preferentially guarantee the heating capacity; and β=0.6, γ=0.4 when the outdoor temperature is >5℃, to focus on the temperature difference optimization. Then the reference frequency of the circulating water pump is read, and each parameter is substituted into the formula to calculate the target frequency.

[0096] Alternatively, the circulating water pump target frequency of the current period satisfies the following formula:

[0097] wherein, is the circulating water pump frequency of the current period, is the reference frequency of the circulating water pump, is the heating capacity deviation weight coefficient, is the temperature difference deviation weight coefficient, and satisfies , is the heating capacity deviation, , is the target heating capacity of the current period, is the reference heating capacity of the historical same period, is the temperature correction coefficient, is the reference outdoor environment temperature of the historical same period, and T is the outdoor environment temperature of the current period, is the actual heating capacity of the current period, is the temperature difference deviation, , is the set target supply and return water temperature difference.

[0098] As an example, it is assumed that =50Hz, the current outdoor temperature is -5℃ (β=0.8, γ=0.2), =0.068, =0.1; and the formula is substituted to obtain =50×[1+0.8×0.068+0.2×0.1]=53.72Hz.

[0099] Based on the above steps, the on-demand adjustment of the circulating water pump frequency is realized, which matches the heating capacity demand and guarantees that the supply and return water temperature difference is in the high-efficiency interval.

[0100] In step 407, the heating station energy-saving control device based on load feedback sends the circulating water pump target frequency to the variable frequency control unit of the circulating water pump, and updates the operating frequency of the circulating water pump.

[0101] The variable frequency control unit of the circulating water pump is an execution module that receives frequency instructions and drives the water pump to adjust the rotating speed, and can change the operating frequency of the water pump in real time according to the instruction signal.

[0102] In an embodiment of the present application, the control device sends the target frequency determined in step 406 to the frequency conversion control unit in the form of a digital signal through the communication interface. After receiving the signal, the frequency conversion control unit drives the water pump motor speed to change by adjusting the output voltage frequency, so that the water pump operating frequency is updated to the target value.

[0103] As an example, the control device sends a target frequency instruction of 53.72Hz to the frequency converter cabinet of the community heating circulation water pump. After receiving it, the frequency converter cabinet gradually increases the operating frequency of the water pump from the current 50Hz to 53.72Hz. During the process, the water pump current, pressure and other parameters are monitored in real time to ensure stability.

[0104] Based on the above steps, the frequency adjustment instruction is converted into a change in the actual operating state of the water pump, realizing dynamic optimization of the circulation flow and improving the heat exchange efficiency.

[0105] Based on the above technical solution, adaptive PID adjustment is used to achieve precise control of boiler combustion intensity to ensure stable indoor temperature for users; dynamic optimization of circulating water pump frequency is achieved through heat correction algorithm to improve heat exchange efficiency; the two work together to form a dual closed-loop adjustment, which not only avoids energy waste caused by oversupply / undersupply, but also solves the inefficiency problem of single parameter adjustment, achieving the dual goals of reducing energy consumption of heating stations and stabilizing heating quality.

[0106] In a possible implementation, combining the above Figure 2 ,like Figure 5 As shown, the above step 204 continuously adjusts the core load parameters and the average indoor temperature of the user according to the periodic feedback based on the load feedback control model of the heating station, and then performs closed-loop control of the heating station based on the continuously adjusted core load parameters and the average indoor temperature of the user can be specifically implemented by the following steps 501 to 503: Step 501: The energy-saving control device of the heating station based on load feedback obtains the core load parameters and the average indoor temperature of the user after adjustment by the load feedback control model according to a preset period, and uses the 3σ criterion to eliminate abnormal values ​​of the collected parameters to obtain effective parameters for closed-loop control.

[0107] The preset period refers to the parameter collection interval set according to the response characteristics of the heating system.

[0108] In an embodiment of the present application, the control device obtains the adjusted core load parameters and the user's indoor average temperature according to a preset period through the pipe network sensor and the user's room temperature collection equipment, first calculates the mean and standard deviation of each parameter, and then traverses the data points to eliminate abnormal data with an absolute value of the deviation greater than 3 times the standard deviation.

[0109] It should be noted that the preset period needs to be adjusted in combination with the heat inertia of the heating system to avoid data redundancy caused by too short period and regulation lag caused by too long period.

[0110] As an example, in a certain community heating scenario, the control device sets 30 seconds as the preset period, and the collected water supply temperature data shows 65℃, the average value is 52℃, the standard deviation is 4℃, and the deviation is more than 3 times the standard deviation. It is determined as an abnormal value and is excluded.

[0111] Based on the above steps, invalid interference data is removed, ensuring that the parameters input into the closed-loop control are real and reliable, and avoiding abnormal data causing control decision deviation.

[0112] Step 502, the heating station energy-saving control device based on load feedback inputs the effective parameters into the heating station load feedback control model, updates the historical user temperature deviation summation value, actual heating capacity record and load state data stored in the model.

[0113] Among them, the load state data includes the current efficient / inefficient / adjustment state identifier of the heating system.

[0114] In the embodiment of the application, the control device inputs the effective parameters obtained in step 501 into the load feedback control model, and the model automatically calculates the latest user temperature deviation and adds it to the historical summation value. The current actual heating capacity replaces the old heating capacity record stored in the model, and the load state data is updated according to the supply and return water temperature difference and the circulating flow.

[0115] It should be noted that the model data update needs to cover the timeliness of historical data to avoid old data occupying storage or affecting decision-making. Generally, the effective period data within the last 1 hour is retained.

[0116] As an example, the control device adds the user temperature deviation-1.2℃ calculated by the effective parameters to the historical summation value, the original summation value is-3.8℃, and the updated summation value is-5℃. The current actual heating capacity 1.1MW replaces the original 0.98MW record in the model, and the load state is updated from standby adjustment to low efficiency.

[0117] Based on the above steps, the load feedback control model is always based on the latest effective data.

[0118] Step 503, the heating station energy-saving control device based on load feedback updates the model data, and checks whether the current boiler combustion intensity matches the user indoor average temperature demand through user temperature-burning intensity closed loop, and whether the current circulating water pump frequency matches the core load parameter efficiency requirement through supply and return water temperature difference-circulating flow closed loop.

[0119] Wherein, the user indoor average temperature demand is based on the set target temperature, the core load parameter efficiency requirement is based on the optimal interval of the supply and return water temperature difference, and the two closed loop verifications correspond to the adaptability judgment of the combustion intensity and the water pump frequency respectively.

[0120] In the embodiment of the application, the control device calculates the current user temperature deviation through the user temperature-combustion intensity closed loop based on the updated model data, judges whether it exceeds the allowed range of the set target temperature, and if so, the combustion intensity is not matched; reads the current supply and return water temperature difference through the supply and return water temperature difference-circulation flow closed loop, judges whether it is in the efficient interval of the supply and return water temperature difference, and if not, the water pump frequency is not matched; if not matched, the corresponding adjustment instruction is regenerated to perform adjustment, and the above-mentioned periodic acquisition, data updating and verification adjustment steps are repeated.

[0121] It should be pointed out that the two closed loop verifications need to be executed synchronously to avoid that the separate verification of a parameter leads to the imbalance of the overall system operation.

[0122] As an example, the control device finds through the verification that the current user temperature deviation is -1.5℃ (exceeds the allowed range of ±1℃), and determines that the boiler combustion intensity is not matched with the temperature demand; the supply and return water temperature difference is 7.5℃ (is lower than the efficient interval of 8-12℃), and determines that the circulation water pump frequency is not matched with the efficiency requirement.

[0123] Based on the above steps, the mismatching problem of the current control parameter and the load demand is identified in time, and the judgment basis for providing adjustment instruction and maintaining the efficient operation of the system is provided.

[0124] Based on the above technical solution, the input reliability is ensured through the abnormal data elimination, the decision timeliness is maintained through the model data updating, the adaptation problem is accurately identified through the double closed loop verification, the closed loop management links of data purification, model updating and state verification are formed, and it is ensured that the load feedback control model of the heating station can continuously adjust the operation parameter based on the real and latest data, and the long-term stable and efficient energy saving control of the heating system is realized.

[0125] The above mainly introduces the scheme of the embodiment of the application from the perspective of equipment implementation. It can be understood that each device, for example, the load feedback based heating station energy saving control device, contains at least one of the corresponding hardware structure and software module for executing each function. Those skilled in the art should easily realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in the present text can be realized in the form of hardware or the combination of hardware and computer software. Whether a certain function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraint conditions of the technical solution. The professional technicians can use different methods to realize the described functions for each specific application, but such implementation should not be considered as beyond the scope of the application.

[0126] The embodiments of the present application can divide the function units of the heat supply station energy-saving control device based on load feedback according to the above method examples. For example, each function unit can be divided according to each function, or two or more functions can be integrated in one processing unit. The integrated unit can be realized in the form of hardware or in the form of a software function unit. It should be noted that the division of the units in the embodiments of the present application is illustrative, and is only a logical function division. In actual implementation, there can be another division manner.

[0127] In the case of using integrated units, Figure 6 A possible structure diagram of the heat supply station energy-saving control device based on load feedback (denoted as heat supply station energy-saving control device 60 based on load feedback) involved in the above embodiments is shown, which includes a processing unit 601 and a communication unit 602, and can also include a storage unit 603. Figure 6 The structure diagram shown can be used to illustrate the structure of the heat supply station energy-saving control device based on load feedback involved in the above embodiments.

[0128] When Figure 6 When the structure diagram shown is used to illustrate the structure of the heat supply station energy-saving control device based on load feedback involved in the above embodiments, the processing unit 601 is used to control and manage the actions of the heat supply station energy-saving control device based on load feedback, the communication unit 602 is used for communication between the heat supply station energy-saving control device based on load feedback and other devices, and the storage unit 603 is used to store the program code and data of the heat supply station energy-saving control device based on load feedback.

[0129] For example, the communication unit 602 is used to obtain the core load parameter of the heat supply station and the average indoor temperature of the user; The processing unit 601 is used to preprocess the core load parameter and the average indoor temperature of the user and calculate the correlation index. The correlation index includes the actual heat supply, the user temperature deviation, and the supply and return water temperature difference. The correlation index is input into the heat supply station load feedback control model to adjust the boiler combustion intensity and the circulating water pump frequency. The heat supply station load feedback control model includes a user temperature-boiler combustion intensity closed loop and a supply and return water temperature difference-circulating flow closed loop. The user temperature-boiler combustion intensity closed loop is used to adjust the boiler combustion intensity based on the adaptive PID algorithm through the user temperature deviation and the supply and return water temperature difference. The supply and return water temperature difference-circulating flow closed loop is used to control the circulating water pump frequency based on the heat correction algorithm through the supply and return water temperature difference and the actual heat supply. Based on the heat supply station load feedback control model, the core load parameter and the average indoor temperature of the user are continuously fed back and adjusted periodically, and then the heat supply station is controlled in a closed loop based on the continuously adjusted core load parameter and the average indoor temperature of the user.

[0130] In a possible implementation, the processing unit 601 is further configured to preprocess the core load parameter and the user indoor average temperature and calculate the correlation index, including: performing outlier elimination on the supply water temperature, the return water temperature, the circulation flow and the user indoor average temperature by using a 3σ criterion to obtain effective data; performing sliding average filtering processing on the effective data to eliminate transient fluctuations to obtain smoothed data; and calculating the correlation index based on the smoothed data; and the calculation of the correlation index includes: calculating a supply-return water temperature difference based on a difference between the supply water temperature and the return water temperature; calculating a user temperature deviation by using a difference between the user indoor average temperature and a set indoor target temperature; and calculating an actual heating capacity based on the supply-return water temperature difference, the circulation flow, and the density and specific heat capacity of water.

[0131] In a possible implementation, the processing unit 601 is further configured to adjust the boiler combustion intensity based on the user temperature deviation and the supply-return water temperature difference by using an adaptive PID algorithm, including: determining a proportional coefficient, an integral coefficient and a differential coefficient of the adaptive PID algorithm based on an absolute value of the user temperature deviation; calculating an adjustment amount of the boiler combustion intensity based on the determined PID parameters, a current user temperature deviation, a summation value of historical user temperature deviations, and a difference between the current user temperature deviation and a user temperature deviation of a previous period, and a thermal efficiency correction term of the supply-return water temperature difference; and updating a current boiler combustion intensity based on a boiler combustion intensity of the previous period and the adjustment amount.

[0132] In a possible implementation, the processing unit 601 is further configured to determine the proportional coefficient, the integral coefficient and the differential coefficient of the adaptive PID algorithm based on the absolute value of the user temperature deviation, including: when the absolute value of the user temperature deviation is greater than a maximum deviation threshold, the proportional coefficient, the integral coefficient and the differential coefficient of the adaptive PID algorithm take a first PID coefficient combination; when the absolute value of the user temperature deviation is less than the maximum deviation threshold and greater than a minimum deviation threshold, the proportional coefficient, the integral coefficient and the differential coefficient of the adaptive PID algorithm take a second PID coefficient combination; and when the absolute value of the user temperature deviation is less than the minimum deviation threshold, the proportional coefficient, the integral coefficient and the differential coefficient of the adaptive PID algorithm take a third PID coefficient combination.

[0133] In a possible implementation, the adjustment amount of the boiler combustion intensity satisfies the following formula:

[0134] wherein, the adjustment amount of the boiler combustion intensity is ΔT, the proportional coefficient is Kp, the integral coefficient is Ki, the differential coefficient is Kd, the user temperature deviation of the current period is ΔT, the user temperature deviation of the previous period is ΔT-1, the thermal efficiency correction coefficient is Kf. is a supply-return water temperature difference of the current period, , is a supply-return water temperature difference of the current period.

[0135] In a possible implementation, the communication unit 602 is further configured to acquire a reference heat supply, a reference outdoor environment temperature of a historical same period, and an outdoor environment temperature of the current period.

[0136] In a possible implementation, the processing unit 601 is further configured to control the circulating water pump frequency based on the heat quantity correction algorithm through the supply-return water temperature difference and the actual heat supply, including: calculating a heat supply deviation based on the reference heat supply, the reference outdoor environment temperature of the historical same period, the outdoor environment temperature of the current period, and the actual heat supply, and calculating a temperature difference deviation based on the set target supply-return water temperature difference and the supply-return water temperature difference of the current period; determining the circulating water pump target frequency of the current period by combining the reference frequency of the circulating water pump, the heat supply deviation and a corresponding heat supply deviation weight coefficient, the temperature difference deviation and a corresponding temperature difference deviation weight coefficient; and sending the circulating water pump target frequency to a variable frequency control unit of the circulating water pump to update the operating frequency of the circulating water pump.

[0137] In a possible implementation, the circulating water pump target frequency of the current period satisfies the following formula:

[0138] wherein, is the circulating water pump frequency of the current period, is the reference frequency of the circulating water pump, is the heat supply deviation weight coefficient, is the temperature difference deviation weight coefficient, and satisfies , is the heat supply deviation, , is the target heat supply of the current period, is the reference heat supply of the historical same period, is the temperature correction coefficient, is the reference outdoor environment temperature of the historical same period, and T is the outdoor environment temperature of the current period, is the actual heat supply of the current period, is the temperature difference deviation, , is the set target supply-return water temperature difference.

[0139] In a possible implementation, the processing unit 601 is further configured to: continuously feed back the core load parameter and the average indoor temperature of the user based on the heat supply station load feedback control model, and perform closed-loop control on the heat supply station based on the continuously adjusted core load parameter and the average indoor temperature of the user, including: obtaining the core load parameter and the average indoor temperature of the user adjusted by the load feedback control model at a preset period, performing outlier elimination on the collected parameters by using the 3σ criterion to obtain effective parameters for closed-loop control; inputting the effective parameters into the heat supply station load feedback control model to update the historical user temperature deviation summation value, the actual heat supply amount record, and the load state data stored in the model; based on the updated model data, checking whether the current boiler combustion intensity matches the average indoor temperature requirement of the user through user temperature-burning intensity closed-loop verification, and checking whether the current circulating water pump frequency matches the core load parameter efficiency requirement through supply and return water temperature difference-circulating flow closed-loop verification, and if not, re-generating corresponding adjustment instructions to perform adjustment, and repeating the above steps of period acquisition, data updating, and adjustment checking.

[0140] The processing unit 601 can be a processor or a controller, and the communication unit 602 can be a communication interface, a transceiver, a transceiver, a transceiver circuit, a transceiver device, or the like. The communication interface is collectively referred to as an interface, which can include one or more interfaces. The storage unit 603 can be a memory. When the load feedback-based heat supply station energy-saving control device 60 is a chip, the processing unit 601 can be a processor or a controller, and the communication unit 602 can be an input interface and / or an output interface, a pin, or a circuit, etc. The storage unit 603 can be a storage unit (for example, a register, a cache, etc.) within the chip, or can be a storage unit (for example, a read-only memory (ROM), a random access memory (RAM), etc.) located outside the chip.

[0141] The communication unit can also be referred to as a transceiver unit. The antenna and control circuit with transceiver function in the load feedback-based heat supply station energy-saving control device 60 can be regarded as the communication unit 602 of the load feedback-based heat supply station energy-saving control device 60, and the processor with processing function can be regarded as the processing unit 601 of the load feedback-based heat supply station energy-saving control device 60. Optionally, the device for realizing the receiving function in the communication unit 602 can be regarded as a communication unit, which is used to execute the receiving steps in the embodiments of the present application, and the communication unit can be a receiver, a receiver, a receiving circuit, etc. The device for realizing the sending function in the communication unit 602 can be regarded as a sending unit, which is used to execute the sending steps in the embodiments of the present application, and the sending unit can be a transmitter, a sender, a sending circuit, etc.

[0142] Figure 6The integrated units in the above embodiments, if realized in the form of software function modules and sold or used as independent products, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application essentially or say the parts that make contributions to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform all or part of the steps of the methods described in the embodiments of the present application. The storage medium storing the computer software product includes a U disk, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk or an optical disk, and various media that can store program codes.

[0143] Figure 6 The units in the above embodiments can also be referred to as modules, for example, the processing unit can be referred to as a processing module.

[0144] The embodiments of the present application also provide a hardware structure schematic diagram of a load feedback based heat supply station energy saving control device (denoted as a load feedback based heat supply station energy saving control device 70), which is shown in Figure 7 The load feedback based heat supply station energy saving control device 70 includes a processor 701, and optionally, further includes a memory 702 connected with the processor 701.

[0145] In a first possible implementation, referring to Figure 7 The load feedback based heat supply station energy saving control device 70 further includes a transceiver 703. The processor 701, the memory 702 and the transceiver 703 are connected through a bus. The transceiver 703 is used for communicating with other devices or communication networks. Optionally, the transceiver 703 can include a transmitter and a receiver. The device for realizing the receiving function in the transceiver 703 can be regarded as a receiver, and the receiver is used for executing the steps of receiving in the embodiments of the present application. The device for realizing the sending function in the transceiver 703 can be regarded as a transmitter, and the transmitter is used for executing the steps of sending in the embodiments of the present application.

[0146] Based on the first possible implementation, Figure 7 The structure schematic diagram shown in the above can be used for illustrating the structure of the load feedback based heat supply station energy saving control device involved in the above embodiments.

[0147] Among them, Figure 7 The system chip in the load feedback based heat supply station energy saving control device can also be illustrated. In this case, the actions performed by the above load feedback based heat supply station energy saving control device can be realized by the system chip, and the specific actions performed can be referred to the above, which will not be described here.

[0148] During implementation, each step of the method provided in this embodiment can be completed by hardware integrated logic circuits in a processor or by software instructions. The steps of the method disclosed in the embodiments of this application can be directly implemented as execution by a hardware processor, or as a combination of hardware and software modules in a processor.

[0149] The processor in this application may include, but is not limited to, at least one of the following: a central processing unit (CPU), a microprocessor, a digital signal processor (DSP), a microcontroller unit (MCU), or an artificial intelligence processor, among other types of computing devices that run software. Each computing device may include one or more cores for executing software instructions to perform calculations or processing. The processor may be a separate semiconductor chip or integrated into a semiconductor chip with other circuits. For example, it may form an SoC (system on a chip) with other circuits (such as a codec circuit, a hardware acceleration circuit, or various bus and interface circuits). Alternatively, it may be integrated into an ASIC as a built-in processor. The ASIC with the integrated processor may be packaged separately or with other circuits. In addition to the core for executing software instructions to perform calculations or processing, the processor may further include necessary hardware accelerators, such as a field programmable gate array (FPGA), a PLD (programmable logic device), or logic circuits that implement specialized logic operations.

[0150] The memory in the embodiments of the present application may include at least one of the following types: read-only memory (ROM) or other types of static storage devices that can store static information and instructions, random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or electrically erasable programmable read-only memory (EEPROM). In some scenarios, the memory may also be a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compact disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0151] The embodiment of the present application further provides a computer readable storage medium comprising instructions which, when executed on a computer, cause the computer to perform any of the above methods.

[0152] The embodiment of the present application further provides a computer program product comprising instructions which, when executed on a computer, cause the computer to perform any of the above methods.

[0153] The embodiment of the present application further provides a chip, comprising a processor and an interface circuit, wherein the interface circuit is coupled with the processor, the processor is configured to execute a computer program or instructions to implement the above method, and the interface circuit is configured to communicate with other modules outside the chip.

[0154] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product comprises one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable devices. The computer instructions can be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through wired (for example, coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (for example, infrared, wireless, microwave, etc.) mode. The computer readable storage medium can be any available medium that can be accessed by a computer or data storage device such as one or more servers, data centers, etc. integrated with one or more media. The available media can be magnetic media (for example, floppy disk, hard disk, magnetic tape), optical media (for example, DVD), or semiconductor media (for example, solid state disk (SSD)) and the like.

[0155] Although the present application is described herein in conjunction with various embodiments, other variations of the disclosed embodiments can be understood and implemented by those skilled in the art through viewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "one" does not exclude a plurality. A single processor or other unit can implement several functions listed in the claims. Some measures described in mutually different dependent claims can be combined and produce a good result.

[0156] While the application has been described in connection with specific features thereof, it will be evident that many modifications and variations of the application are possible, and will be evident to those of ordinary skill in the art. Accordingly, it is intended that all such modifications and variations be considered as within the spirit and scope of the application. Other combinations and sub-combinations of features, functions, acts and / or functionalities described herein are also intended to fall within the scope of the application. It will be apparent to one of ordinary skill in the art that features, acts, and / or functions from different aspects of the application can be interchanged lead to still further embodiments.

Claims

1. A load feedback based energy saving control method for a heating station, characterized in that, The method comprises the following steps: obtaining core load parameters of a heating station and an average indoor temperature of users; the core load parameters comprise water supply temperature, return water temperature and circulation flow rate; preprocessing the core load parameters and the average indoor temperature of users and calculating correlation indexes; the correlation indexes comprise actual heating quantity, user temperature deviation and supply-return water temperature difference; inputting the correlation indexes into a heating station load feedback control model to adjust boiler combustion intensity and circulation water pump frequency; the heating station load feedback control model comprises a user temperature-boiler combustion intensity closed loop and a supply-return water temperature difference-circulation flow rate closed loop; the user temperature-boiler combustion intensity closed loop is used to adjust boiler combustion intensity based on an adaptive PID algorithm through the user temperature deviation and the supply-return water temperature difference, and the supply-return water temperature difference-circulation flow rate closed loop is used to control circulation water pump frequency based on a heat correction algorithm through the supply-return water temperature difference and the actual heating quantity; continuously feeding back and adjusting the core load parameters and the average indoor temperature of users based on the heating station load feedback control model in cycles, and then performing closed loop control on the heating station based on the continuously adjusted core load parameters and the average indoor temperature of users.

2. The method of claim 1, wherein, The preprocessing of the core load parameters and the average indoor temperature of users and the calculation of correlation indexes comprise the following steps: adopting a 3σ criterion to remove outliers from the water supply temperature, the return water temperature, the circulation flow rate and the average indoor temperature of users to obtain effective data; adopting a moving average filter to process the effective data to eliminate transient fluctuations to obtain smoothed data; calculating correlation indexes based on the smoothed data; the calculation of correlation indexes comprises the following steps: calculating the supply-return water temperature difference based on the difference between the water supply temperature and the return water temperature; calculating the user temperature deviation through the difference between the average indoor temperature of users and a set indoor target temperature; calculating the actual heating quantity based on the supply-return water temperature difference, the circulation flow rate, the density and specific heat capacity of water.

3. The method of claim 1, wherein, adjusting boiler combustion intensity based on an adaptive PID algorithm through the user temperature deviation and the supply-return water temperature difference comprises the following steps: determining the proportional coefficient, the integral coefficient and the differential coefficient of the adaptive PID algorithm based on the absolute value of the user temperature deviation; calculating the adjustment amount of boiler combustion intensity based on the determined PID parameters, the current user temperature deviation, the sum of historical user temperature deviations and the difference between the current and previous cycle user temperature deviations, and the heat efficiency correction term of the supply-return water temperature difference; updating the current boiler combustion intensity based on the boiler combustion intensity of the previous cycle and the adjustment amount.

4. The method of claim 3, wherein, determining the proportional coefficient, the integral coefficient and the differential coefficient of the adaptive PID algorithm based on the absolute value of the user temperature deviation comprises the following steps: when the absolute value of the user temperature deviation is greater than the maximum deviation threshold, the proportional coefficient, the integral coefficient and the differential coefficient of the adaptive PID algorithm take a first PID coefficient combination; when the absolute value of the user temperature deviation is less than the maximum deviation threshold and greater than the minimum deviation threshold, the proportional coefficient, the integral coefficient and the differential coefficient of the adaptive PID algorithm take a second PID coefficient combination. When the absolute value of the user temperature deviation is less than the minimum deviation threshold, the proportional coefficient, the integral coefficient and the differential coefficient of the adaptive PID algorithm take a third PID coefficient combination.

5. The method of claim 3, wherein, The adjustment amount of the boiler combustion intensity satisfies the following formula: wherein, is the adjustment amount of the boiler combustion intensity, is the proportionality coefficient, is the integral coefficient, is the differential coefficient, is the user temperature deviation of the current period, is the user temperature deviation of the previous period, is the thermal efficiency correction coefficient, is the supply-return water temperature difference constraint function, , is the supply-return water temperature difference of the current period.

6. The method of claim 1, wherein, The circulating water pump frequency is controlled based on the heat correction algorithm through the supply and return water temperature difference and the actual heat supply amount, including: The reference heat supply amount and the reference outdoor environment temperature of the same period in history are obtained, and the outdoor environment temperature of the current period is obtained. Based on the reference heat supply amount, the reference outdoor environment temperature of the same period in history, the outdoor environment temperature of the current period and the actual heat supply amount, the heat supply amount deviation is calculated, and based on the set target supply and return water temperature difference and the supply and return water temperature difference of the current period, the temperature difference deviation is calculated. The circulating water pump target frequency of the current period is determined in combination with the reference frequency of the circulating water pump, the heat supply amount deviation and the corresponding heat supply amount deviation weight coefficient, the temperature difference deviation and the corresponding temperature difference deviation weight coefficient. The circulating water pump target frequency is sent to the frequency conversion control unit of the circulating water pump, and the operating frequency of the circulating water pump is updated.

7. The method of claim 6, wherein, The circulating water pump target frequency of the current period satisfies the following formula: wherein, is a circulating water pump frequency of a current period, is a reference frequency of the circulating water pump, is a heating capacity deviation weight coefficient, is a temperature difference deviation weight coefficient, and satisfies , is the heating capacity deviation, , is a target heating capacity of the current period, is a reference heating capacity of the historical same period, is a temperature correction coefficient, is a reference outdoor environment temperature of the historical same period, and T is an outdoor environment temperature of the current period, is an actual heating capacity of the current period, is the temperature difference deviation, , is a set target supply and return water temperature difference.

8. The method of claim 1, wherein, The core load parameter and the user indoor average temperature are continuously fed back and adjusted based on the heat supply station load feedback control model by period, and the heat supply station is closed-loop controlled based on the continuously adjusted core load parameter and user indoor average temperature, including: The core load parameter and the user indoor average temperature adjusted by the load feedback control model are obtained according to a preset period, and the collected parameters are subjected to outlier rejection by using the 3σ criterion to obtain effective parameters for closed-loop control. The effective parameters are input into the heat supply station load feedback control model, and the historical user temperature deviation summation value, the actual heat supply amount record and the load state data stored in the model are updated. Based on the updated model data, whether the current boiler combustion intensity matches the user indoor average temperature requirement is verified through user temperature-combustion intensity closed loop, and whether the current circulating water pump frequency matches the core load parameter efficiency requirement is verified through supply and return water temperature difference-circulating flow closed loop, and if not, corresponding adjustment instructions are regenerated to perform adjustment, and the above period acquisition, data updating and verification adjustment steps are repeated.

9. A load feedback based energy saving control device for a heating station, characterized by, The device comprises a communication unit and a processing unit. The communication unit is configured to obtain the core load parameter and the user indoor average temperature of the heat supply station, and the core load parameter comprises the supply water temperature, the return water temperature and the circulating flow. The processing unit is configured to preprocess the core load parameter and the user indoor average temperature and calculate a correlation index; the correlation index includes actual heat supply, user temperature deviation, and supply-return water temperature difference; the correlation index is input into a heat supply station load feedback control model to adjust boiler combustion intensity and circulating water pump frequency; the heat supply station load feedback control model includes a user temperature-boiler combustion intensity closed loop and a supply-return water temperature difference-circulating flow closed loop; the user temperature-boiler combustion intensity closed loop is configured to adjust the boiler combustion intensity based on an adaptive PID algorithm through the user temperature deviation and the supply-return water temperature difference; the supply-return water temperature difference-circulating flow closed loop is configured to control the circulating water pump frequency based on a heat correction algorithm through the supply-return water temperature difference and the actual heat supply; the core load parameter and the user indoor average temperature are continuously fed back and adjusted based on the heat supply station load feedback control model at a period, and the heat supply station is controlled in a closed loop based on the continuously adjusted core load parameter and user indoor average temperature.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores instructions, when the instructions run on the load feedback based heat supply station energy saving control device, the load feedback based heat supply station energy saving control device executes the method as claimed in any one of claims 1-8.

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