Layered heat supply regulation and control method and system based on intelligent optimization

Abstract

The invention relates to the technical field of intelligent control, in particular to a layered heat supply regulation and control method and system based on intelligent optimization. Building a heat supply regulation and control structure of a region level and a building level; calculating a floor heat supply demand time period, and determining a floor heat supply strategy through priority ranking; according to the demand boundary and the power boundary of the heat supply unit, generating and optimizing a building level heat supply guidance curve; and by coordinating the floor heat supply demand time periods, a region-level heat supply guidance curve is generated, and heat supply distribution is optimized. Through the design of the layered regulation and control structure, accurate management of the heat supply system from the area level to the building level is achieved, distribution of heat supply resources is more reasonable, and the phenomena of resource waste and insufficient heat supply in the heat supply process are effectively reduced. The heat supply system can be dynamically adjusted according to the real-time data to adapt to the actual requirements of different areas and floors, the response speed and flexibility of the heat supply system are improved, and the overall efficiency of the heat supply system and the comfort level of a user are improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to a stratified heating control method and system based on intelligent optimization. Background Art

[0002] With the acceleration of urbanization and the continuous expansion of building scale, the demand for heating systems is becoming increasingly complex. Traditional heating control methods usually adopt fixed modes, lack flexibility, and are difficult to cope with the diverse needs of different areas and floors. This method not only leads to a waste of heating resources, but may also lead to insufficient heating in some areas, thus affecting the comfort of users and the overall efficiency of the system. Existing heating systems often lack coordination mechanisms and effective optimization methods when managing regional and floor-level heating, and are unable to achieve dynamic balance and precise control of heating. With the development of intelligent control technology, people have put forward higher requirements for heating systems, which not only need to meet the heating needs of different areas and floors, but also take into account the goals of energy conservation and emission reduction.

[0003] The present invention aims to provide a hierarchical heating control method and system based on intelligent optimization, which realizes the rational allocation and efficient utilization of heating resources and meets the heating needs at different levels by establishing regional and floor-level heating control structures and combining advanced optimization algorithms. Summary of the invention

[0004] In view of the above problems existing in the prior art, the present invention is proposed.

[0005] Therefore, the present invention provides a stratified heating control method based on intelligent optimization, which can solve the problems of resource waste, insufficient heating and inability to dynamically respond to diversified demands in traditional technical solutions. Through intelligent optimization and stratified control, efficient resource allocation and real-time control of the heating system are achieved.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a hierarchical heating control method based on intelligent optimization, comprising: establishing a heating control structure at the regional level and the floor level; calculating the floor heating demand time period, and determining the floor heating strategy by priority sorting; generating and optimizing the floor-level heating guidance curve according to the demand boundary and power boundary of the heating unit; generating a regional-level heating guidance curve by coordinating the floor heating demand time period to optimize the heating distribution.

[0007] As a preferred solution of the layered heating control method based on intelligent optimization described in the present invention, the heating control structure includes an upper-level regional heating monitoring area, which predicts the overall heating demand in the entire area and coordinates and optimizes the heating behavior of each floor. The floor-level heating monitoring area controls the heating equipment in the floor downward to achieve the control objectives of the regional-level monitoring area.

[0008] As a preferred solution of the stratified heating control method based on intelligent optimization described in the present invention, the regional heating monitoring area includes regional heating with a main heating pipeline and a heat exchange station as operating units, which coordinates and manages the connected floor-level heating units.

[0009] As a preferred solution of the stratified heating control method based on intelligent optimization described in the present invention, wherein: the floor heating demand time period includes calculating the heating demand time period number I of each floor ij , the formula is expressed as,

[0010]

[0011] Among them, n i represents the number of heating units on the ith floor, P ij represents the heating power of the jth heating unit on the ith floor, B ij represents the heat capacity of the jth heating unit on the ith floor, T target,ij represents the desired target temperature of the jth heating unit on the ith floor, T current,ij represents the current actual temperature of the jth heating unit on the ith floor, and Δt represents the time interval of heating regulation.

[0012] As a preferred solution of the stratified heating control method based on intelligent optimization described in the present invention, the floor heating strategy includes constructing a floor heating demand priority table n i ×5, each row corresponds to a unit. The heating demand priority table includes: the first column is the heating unit number, which uniquely identifies each heating unit; the second column is the current temperature T of the heating unit current,ij With the target temperature T target,ij The difference ΔT ij , the third column is the heat capacity B of the heating unit ij , the fourth column is the current heating demand level Q of the heating unit demand,ij ,The fifth column is the heating priority ρ, the higher the value, the higher the priority;

[0013] The heating demand level is expressed as,

[0014]

[0015] The heating priority formula is expressed as:

[0016]

[0017] Among them, P j represents the heating power of heating unit j;

[0018] Sort all heating units according to heating priority from high to low;

[0019] Construct the start and stop control matrix of each heating unit on the floor represents the control decision of the jth heating unit on the ith floor at time t, Indicates that the heating unit is turned on at time t. Indicates that the heating unit is turned off at time t, and the heating unit j is selected in the future T i The heating margin α of each time period j ;

[0020] Select the unit with the highest priority from the heating demand priority table to start arranging heating, set the number of the currently scheduled heating unit to j, and select the first I with the largest heating demand. ij time period, perform heating operation, and calculate the start and stop control strategy matrix of the heating unit Control the start and stop of each heating unit to achieve orderly heating.

[0021] As a preferred solution of the stratified heating control method based on intelligent optimization described in the present invention, wherein: the generation and optimization of the floor-level heating guidance curve includes calculating the future T of each heating unit i The heating demand boundary within a time period is set as T max,i is the maximum value of all accumulated heating periods of heating unit j from the current moment;

[0022] Set the target heating time t of each heating unit j on floor i ij Converted into the number of time periods T for heating regulation ij , the formula is expressed as,

[0023]

[0024] in, Indicates rounding up operation;

[0025] The longest time length for calculating the orderly heating strategy is one day, and the number of time periods T for the coordinated heating control of floor i is obtained. i , the formula is expressed as,

[0026]

[0027] Where y is the total number of time periods, min(·) is the minimum function;

[0028] Summarize the demand of all heating units in floor i and calculate the demand of each heating unit j in the future T i The upper and lower bounds of the cumulative heat supply in each time period, E min,ij represents the lower bound of the cumulative heat supply of heating unit j, Emax,ij represents the upper bound of the cumulative heat supply of heating unit j, and obtains the cumulative heat supply of each heating unit in the floor in the future T i The heating power boundary of each time period is set as P min.ij is the lower limit of the heating power of heating unit j, P max,ij is the upper limit of the heating power of heating unit j;

[0029] Considering the synergy between heating units and the demand balance of floors in different time periods, the floor-level heating demand boundary curve is constructed. The formula is expressed as:

[0030]

[0031] Among them, max(·) represents the maximum value function, E max,i 、E min,i Respectively represent the upper and lower limits of the heat supply of floor i, P max,i , P min,i They represent the upper and lower bounds of the heating power for floor i respectively;

[0032] Combine the floor-level heating demand boundary curve and the real-time heating demand to generate the floor-level heating guidance curve Q ref,i , the formula is expressed as,

[0033] min(E min,i ,P min,i )≤Q ref,i (t)≤max(E max,i ,P max,i )

[0034] Ensure that the actual heating supply of the heating unit is not lower than the cumulative heating supply and the lower limit of the heating power in each time period, and does not exceed the upper limit of the heating supply and the upper limit of the heating power, so as to achieve a balanced heat distribution.

[0035] As a preferred solution of the stratified heating control method based on intelligent optimization described in the present invention, wherein: the generating of the regional heating guidance curve includes the time period number T of the regional heating coordinated control according to the current time floor level heating i Determine the number of heating control periods T required for the heating units in the area in the future from the current moment rg , the formula is expressed as,

[0036] T rg =max(T1,T2,…,T i )

[0037] Determine the regional heating guidance curve Q according to the current time and the number of heating control periods ref , set the decision variable Q ref,rg(t), represents the guidance heating power of the regional heating system in each time period t in the future. By optimizing the heating scheduling, the heating is evenly distributed in each time period to ensure the stable operation of the heating system. The formula of the regional heating guidance curve is expressed as,

[0038]

[0039] The guiding heating power constraint in the region is expressed as:

[0040] P min,i (t)≤Q ref,rg (t)≤P max,i (t)

[0041] Outside the heating planning period, the heating power is guided to be 0 to ensure that no additional heat is output during the non-heating period. The upper and lower limits of the cumulative heating capacity of each heating unit should meet the overall heating demand in the area. The formula is:

[0042]

[0043] The linear programming algorithm is used to solve the optimization problem and obtain the regional heating guidance curve. The solved guidance curve is applied to the regional heating control to achieve orderly heating of each heating unit in the region, ensure the maximization of heating efficiency and meet the regional heating control objectives.

[0044] Another object of the present invention is to provide a hierarchical heating control system based on intelligent optimization to solve the problems of low resource utilization efficiency, inflexible control and inability to meet diversified needs in traditional heating systems. The present invention establishes a hierarchical heating control structure at the regional and floor levels, and uses an intelligent optimization algorithm to dynamically predict and adjust the heating demand in real time, thereby achieving precise control of the heating system and reasonable allocation of resources. The method can adjust the heating strategy according to real-time data to ensure that the heating demand of each area and floor is effectively met in different time periods, thereby optimizing the overall heating effect. The present invention can significantly improve the operating efficiency of the heating system, reduce energy waste, and improve user comfort and satisfaction. The present invention can also adapt to buildings of different sizes and types, has strong flexibility and scalability, and can provide an efficient and intelligent solution for the heating system of modern urban buildings.

[0045] As a preferred solution of the hierarchical heating control system based on intelligent optimization described in the present invention, it includes: a heating control structure module, a floor heating strategy module, a floor heating optimization module and a regional heating optimization module;

[0046] The heating control structure module establishes the heating control structure at the regional level and the floor level to ensure that the heating behavior of each floor is consistent with the regional level control target;

[0047] The floor heating strategy module obtains heating optimization parameters according to the heating guidance curve of the future period, calculates the number of heating demand time periods, constructs a priority table of heating units in the floor, determines the start and stop sequence of the heating units according to the sorting results of the priority table, and realizes orderly heating operation through the start and stop control matrix to ensure that key units get heating first;

[0048] The floor heating optimization module calculates the demand boundary and time period number of each heating unit, generates a floor-level heating demand boundary curve, and ensures a reasonable distribution of heat supply and power;

[0049] The regional heating optimization module determines the number of heating coordination control time periods for each floor, calculates the overall heating demand of the heating units in the region, and generates a regional heating guidance curve to optimize the heating distribution and ensure the stable operation of the heating system in the region.

[0050] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and wherein when the processor executes the computer program, the steps of any one of the methods of stratified heating control based on intelligent optimization are implemented.

[0051] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of any one of the methods of stratified heating control methods based on intelligent optimization are implemented.

[0052] Beneficial effects of the present invention: Through the design of a hierarchical control structure, accurate management of the heating system from the regional level to the floor level is achieved, making the allocation of heating resources more reasonable and effectively reducing the waste of resources and insufficient heating in the heating process. The heating system can be dynamically adjusted according to real-time data to adapt to the actual needs of different areas and floors, thereby improving the response speed and flexibility of the heating system. By prioritizing and real-time control of heating demands, it is ensured that the heating demands of key areas and floors are met first, thereby improving the overall efficiency of the heating system and the comfort of users. The present invention can significantly reduce energy consumption and achieve the goal of energy conservation and emission reduction. At the same time, while improving the operational stability and reliability of the heating system, it also improves the user experience, with significant social and economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0054] Figure 1 A schematic flow chart of a stratified heating control method based on intelligent optimization is provided for one embodiment of the present invention.

[0055] Figure 2 A module diagram of a stratified heating control system based on intelligent optimization is provided for one embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0057] Example 1, reference Figure 1 and Figure 2 , which is the first embodiment of the present invention, and provides a stratified heating control method based on intelligent optimization, comprising:

[0058] S1: Establish a heating control structure at the regional and floor levels.

[0059] It should be noted that the heating control structure includes the upper regional heating monitoring area, which predicts and monitors the heating demand in the entire area, and coordinates and optimizes the heating behavior of each floor. The regional control can issue instructions in real time to adjust the heating distribution of each floor to ensure that the heating of the entire area is optimized while meeting user needs. The floor-level heating monitoring area controls the heating equipment on the floor downward to achieve the control objectives of the regional monitoring area.

[0060] It should be noted that the regional heating monitoring area includes a regional heating system with a main heating pipeline and a heat exchange station as operating units, which coordinates and manages the connected floor-level heating units. The main heating pipeline can efficiently transfer heat from the heat source to the heat exchange station, which is then distributed to each floor by the heat exchange station. This transmission method reduces the loss of heat during the transmission process and improves the overall efficiency of the heating system.

[0061] S2: Calculate the floor heating demand time period and determine the floor heating strategy by priority sorting.

[0062] It should be noted that the floor heating demand time period includes calculating the heating demand time period number I of each floor. ij , the formula is expressed as,

[0063]

[0064] Among them, n i represents the number of heating units on the ith floor, P ij represents the heating power of the jth heating unit on the ith floor, B ij represents the heat capacity of the jth heating unit on the ith floor, T target,ij represents the desired target temperature of the jth heating unit on the ith floor, T current,ij represents the current actual temperature of the jth heating unit on the ith floor, and Δt represents the time interval of heating regulation.

[0065] By calculating the heating demand time period for each floor and based on comprehensive consideration of multiple parameters, the heating demand for each floor in the future period can be determined.

[0066] It should be noted that the floor heating strategy includes constructing a floor heating demand priority table n i ×5, each row corresponds to a unit. The heating demand priority table includes: the first column is the heating unit number, which uniquely identifies each heating unit; the second column is the current temperature T of the heating unit current,ij With the target temperature T target,ij The difference ΔT ij , the third column is the heat capacity B of the heating unit ij , the fourth column is the current heating demand level Q of the heating unit demand,ij ,The fifth column is the heating priority ρ, the higher the value, the higher the priority;

[0067] The formula for the heating demand level is expressed as,

[0068]

[0069] The heating priority formula is expressed as:

[0070]

[0071] Among them, P j represents the heating power of heating unit j;

[0072] All heating units are sorted in descending order according to the heating priority ρ. The higher the priority value, the more urgent the heating demand of the heating unit is, and it should be given priority in the heating operation.

[0073] Construct the start and stop control matrix of each heating unit on the floor represents the control decision of the jth heating unit on the ith floor at time t, Indicates that the heating unit is turned on at time t. Indicates that the heating unit is turned off at time t, and selects the heating unit from time t to the future T i The heating margin α of each time periodj ;

[0074] The heating margin reflects the heating unit's ability to meet the basic heating demand Q demand,ij After that, the remaining heating capacity of the system is expressed as:

[0075]

[0076] Heating margin plays a vital role in heating systems, ensuring that the system still has enough capacity to meet additional heating needs during increased demand or emergencies. It is also used to optimize scheduling strategies to avoid system overload during high demand periods or energy waste during low demand periods.

[0077] Select the unit with the highest priority from the heating demand priority table to start arranging heating, set the number of the currently scheduled heating unit to j, and select the first I with the largest heating demand. ij time period, perform heating operation, and calculate the start and stop control strategy matrix of the heating unit Control the start and stop of each heating unit to achieve orderly heating.

[0078] S3: Generate and optimize the floor-level heating guidance curve according to the demand boundary and power boundary of the heating unit.

[0079] It should be noted that the generation and optimization of the floor-level heating guidance curve includes calculating the future T i The heating demand boundary within a time period is set as T max,i is the maximum value of all accumulated heating periods of heating unit j from the current moment;

[0080] Set the target heating time t of each heating unit j on floor i ij Converted into the number of time periods T for heating regulation ij , the formula is expressed as,

[0081]

[0082] in, Indicates rounding up operation;

[0083] The longest time length for calculating the orderly heating strategy is one day, and the number of time periods T for the coordinated heating control of floor i is obtained. i , the formula is expressed as,

[0084]

[0085] Where y is the total number of time periods, min(·) is the minimum function;

[0086] Summarize the demand of all heating units in floor i and calculate the demand of each heating unit j in the future Ti The upper and lower bounds of the cumulative heat supply in each time period, E min,ij represents the lower bound of the cumulative heat supply of heating unit j, E max,ij represents the upper bound of the cumulative heat supply of heating unit j, and obtains the cumulative heat supply of each heating unit in the floor in the future T i The heating power boundary of each time period is set as P min.ij is the lower limit of the heating power of heating unit j, P max,ij is the upper limit of the heating power of heating unit j;

[0087] Considering the synergy between heating units and the demand balance of floors in different time periods, the floor-level heating demand boundary curve is constructed. The formula is expressed as:

[0088]

[0089]

[0090] Among them, max(·) represents the maximum value function, E max,i 、E min,i Respectively represent the upper and lower limits of the heat supply of floor i, P max,i , P min,i They represent the upper and lower bounds of the heating power for floor i respectively;

[0091] Combine the floor-level heating demand boundary curve and the real-time heating demand to generate the floor-level heating guidance curve Q ref,i , the formula is expressed as,

[0092] min(E min,i ,P min,i )≤Q ref,i (t)≤max(E max,i ,P max,i )

[0093] Ensure that the actual heating supply of the heating unit is not lower than the cumulative heating supply and the lower limit of the heating power in each time period, and does not exceed the upper limit of the heating supply and the upper limit of the heating power, so as to achieve a balanced heat distribution.

[0094] S4: Generate regional heating guidance curves by coordinating the heating demand time periods on each floor to optimize heating distribution.

[0095] It should be noted that the generating of the regional heating guidance curve includes the time period number T of the regional heating according to the current time floor level heating coordination control. i Determine the number of heating control periods T required for the heating units in the area in the future from the current moment rg , the formula is expressed as,

[0096] T rg =max(T1,T2,…,Ti )

[0097] Determine the regional heating guidance curve Q according to the current time and the number of heating control periods ref , set the decision variable Q ref,rg (t), represents the guidance heating power of the regional heating system in each time period t in the future. By optimizing the heating scheduling, the heating is evenly distributed in each time period to ensure the stable operation of the heating system. The formula of the regional heating guidance curve is expressed as,

[0098]

[0099] The guiding heating power constraint in the region is expressed as:

[0100] P min,i ≤Q ref,rg (t)≤P max,i

[0101] Outside the heating planning period, the heating power is guided to be 0 to ensure that no additional heat is output during the non-heating period. The upper and lower limits of the cumulative heating capacity of each heating unit should meet the overall heating demand in the area. The formula is:

[0102]

[0103] The objective function and constraints are input into a linear programming solver (e.g., using Python's scipy.optimize.linprog function or other linear programming tools). The solver uses an optimization algorithm to find a heating power allocation solution that minimizes the objective function while satisfying all constraints. The obtained guiding heating power curve Q ref,rg It will be applied to district-level heating control to control the actual heating power in each time period. Through this optimization process, the overall efficiency of the heating system is maximized while meeting the district-level heating control goals.

[0104] The above is a schematic scheme of a stratified heating control method based on intelligent optimization in this embodiment. It should be noted that the technical scheme of the stratified heating control system based on intelligent optimization and the technical scheme of the stratified heating control method based on intelligent optimization belong to the same concept. The details of the technical scheme of the stratified heating control system based on intelligent optimization in this embodiment that are not described in detail can all be referred to the description of the technical scheme of the stratified heating control method based on intelligent optimization.

[0105] like Figure 2 As shown, the hierarchical heating control system based on intelligent optimization in this embodiment includes: a heating control structure module, a floor heating strategy module, a floor heating optimization module and a regional heating optimization module;

[0106] The heating control structure module establishes the heating control structure at the regional level and the floor level to ensure that the heating behavior of each floor is consistent with the regional level control target;

[0107] The floor heating strategy module obtains heating optimization parameters according to the heating guidance curve of the future period, calculates the number of heating demand time periods, constructs a priority table of heating units in the floor, determines the start and stop sequence of the heating units according to the sorting results of the priority table, and realizes orderly heating operation through the start and stop control matrix to ensure that key units get heating first;

[0108] The floor heating optimization module calculates the demand boundary and time period number of each heating unit, generates a floor-level heating demand boundary curve, and ensures a reasonable distribution of heat supply and power;

[0109] The regional heating optimization module determines the number of heating coordination control time periods for each floor, calculates the overall heating demand of the heating units in the region, and generates a regional heating guidance curve to optimize the heating distribution and ensure the stable operation of the heating system in the region.

[0110] This embodiment further provides a computing device, which is applicable to the case of a stratified heating control method based on intelligent optimization, including:

[0111] If the functions are implemented in the form of software functional areas and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0112] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0113] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0114] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0115] Example 2 is the second embodiment of the present invention, which provides a stratified heating control method based on intelligent optimization. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through experiments.

[0116] The experimental scenario was selected as a heating system of an office building, which includes 5 floors, each floor is equipped with a number of heating units. The experimental group adopted the method of the present invention for heating management, while the control group used the traditional fixed heating mode.

[0117] During the specific implementation process, the initial temperature of each floor was recorded at the beginning of the experiment, and the target temperature was adjusted according to the weather forecast, floor usage and other environmental variables. The experiment lasted for 7 days, during which the actual heating supply, temperature changes and energy consumption of each floor were monitored and recorded every day. The heating system updated data and adjusted the heating strategy every hour to ensure that it could respond to the actual needs of each floor in real time.

[0118] After the experiment, the data were collected and organized into a table, as shown in Figure 1. This experiment focused on key indicators such as heating efficiency, energy consumption, and temperature balance. By comparing the experimental data of the experimental group and the control group, the superiority of the method of the present invention was evaluated.

[0119] Table 1. Data comparison table

[0120] Parameter name Floor 1 heating unit Floor 2 heating unit Floor 3 heating unit Floor 4 heating unit Floor 5 Heating Unit Control group heating unit Initial temperature(℃) 18 17 16 19 18 18 Target temperature (℃) 22 21 22 23 22 22 Actual temperature (℃) 21.5 21 21.8 22.5 21.7 21 Heating power (kW) 4.5 4 4.3 5 4.7 5.2 Heat capacity (kJ / ℃) 200 180 190 210 200 200 Energy consumption (kWh) 40 38 39 42 40 45 Temperature fluctuation(℃) ±0.5 ±0.4 ±0.3 ±0.6 ±0.4 ±1.0

[0121] It can be clearly seen from the experimental data table that the experimental group using the method of the present invention is superior to the control group in terms of heating effect, energy consumption and temperature stability. The heating units on each floor of the experimental group performed better in terms of the closeness between the actual temperature and the target temperature, with an average temperature difference of only 0.3°C, while the average temperature difference of the control group was 1°C. This shows that the present invention can control the heating more accurately, make the temperature of each floor more stable, and avoid excessive or insufficient heating.

[0122] In terms of energy consumption, the total energy consumption of the experimental group was about 10% lower than that of the control group. This is because the experimental group adopted an intelligent control strategy to dynamically adjust the heating supply according to real-time demand, avoiding the common energy waste problem in the traditional fixed heating mode. The temperature fluctuation range of the experimental group was significantly smaller than that of the control group, which reflects the efficiency and accuracy of the present invention in temperature control and improves the user comfort of the heating system.

[0123] By comparison, it can be concluded that the application of the present invention in the heating system has obvious innovation and advantages, which not only improves the heating efficiency, but also significantly reduces energy consumption. Compared with the traditional technical solution, the present invention achieves more efficient resource utilization and more stable temperature control through intelligent optimization and hierarchical regulation, showing excellent technical effects and application prospects.

[0124] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A stratified heating control method based on intelligent optimization, characterized in that: include, Establish a heating control structure at the regional and floor levels; Calculate the floor heating demand time period and determine the floor heating strategy by priority sorting; Generate and optimize floor-level heating guidance curves based on the demand boundary and power boundary of the heating unit; By coordinating the time periods of floor heating demand, a regional heating guidance curve is generated to optimize heating distribution.

2. The stratified heating control method based on intelligent optimization according to claim 1, characterized in that: The heat supply control structure includes a regional-level heat supply monitoring area at the upper level, which makes an overall heat supply demand forecast for the entire area and coordinates and optimizes the heat supply behavior of each floor. The floor-level heat supply monitoring area controls the heating equipment on the floor downward to achieve the control objectives of the regional-level monitoring area.

3. A stratified heating control method based on intelligent optimization as claimed in claim 2, characterized in that: The regional heating monitoring area includes a regional heating system with a main heating pipeline and a heat exchange station as operating units, which coordinates and manages the connected floor-level heating units.

4. The stratified heating control method based on intelligent optimization according to claim 3 is characterized in that: The floor heating demand time period includes calculating the heating demand time period number I of each floor ij , the formula is expressed as, Among them, n i represents the number of heating units on the ith floor, P ij represents the heating power of the jth heating unit on the ith floor, B ij represents the heat capacity of the jth heating unit on the ith floor, T target,ij represents the desired target temperature of the jth heating unit on the ith floor, T current,ij represents the current actual temperature of the jth heating unit on the ith floor, and Δt represents the time interval of heating regulation.

5. A stratified heating control method based on intelligent optimization as claimed in claim 4, characterized in that: The floor heating strategy includes constructing a floor heating demand priority table n i ×5, each row corresponds to a unit. The heating demand priority table includes: the first column is the heating unit number, which uniquely identifies each heating unit; the second column is the current temperature T of the heating unit current,ij With the target temperature T target,ij The difference ΔT ij , the third column is the heat capacity B of the heating unit ij , the fourth column is the current heating demand level Q of the heating unit demand,ij ,The fifth column is the heating priority ρ, the higher the value, the higher the priority; The heating demand level is expressed as, The heating priority formula is expressed as: Among them, P j represents the heating power of heating unit j; Sort all heating units according to heating priority from high to low; Construct the start and stop control matrix of each heating unit on the floor represents the control decision of the jth heating unit on the ith floor at time t, Indicates that the heating unit is turned on at time t. Indicates that the heating unit is turned off at time t, and the heating unit j is selected in the future T i The heating margin α of each time period j ; Select the unit with the highest priority from the heating demand priority table to start arranging heating, set the number of the currently scheduled heating unit to j, and select the first I with the largest heating demand. ij time period, perform heating operation, and calculate the start and stop control strategy matrix of the heating unit Control the start and stop of each heating unit to achieve orderly heating.

6. A stratified heating control method based on intelligent optimization as claimed in claim 5, characterized in that: The generating and optimizing of the floor-level heating guidance curve includes calculating each heating unit in the future T i The heating demand boundary within a time period is set as T max,i is the maximum value of all accumulated heating periods of heating unit j from the current moment; Set the target heating time t of each heating unit j on floor i ij Converted into the number of time periods T for heating regulation ij , the formula is expressed as, in, Indicates rounding up operation; The longest time length for calculating the orderly heating strategy is one day, and the number of time periods T for the coordinated heating control of floor i is obtained. i , the formula is expressed as, Where y is the total number of time periods, min(·) is the minimum function; Summarize the demand of all heating units in floor i and calculate the demand of each heating unit j in the future T i The upper and lower bounds of the cumulative heat supply in each time period, E min,ij represents the lower bound of the cumulative heat supply of heating unit j, E max,ij represents the upper bound of the cumulative heat supply of heating unit j, and obtains the cumulative heat supply of each heating unit in the floor in the future T i The heating power boundary of each time period is set as P min.ij is the lower limit of the heating power of heating unit j, P max,ij is the upper limit of the heating power of heating unit j; Considering the synergy between heating units and the demand balance of floors in different time periods, the floor-level heating demand boundary curve is constructed. The formula is expressed as: Among them, max(·) represents the maximum value function, E max,i 、E min,i Respectively represent the upper and lower limits of the heat supply of floor i, P max,i , P min,i They represent the upper and lower bounds of the heating power for floor i respectively; Combine the floor-level heating demand boundary curve and the real-time heating demand to generate the floor-level heating guidance curve Q ref,i , the formula is expressed as, my(E min,i ,P min,i )≤Q ref,i (t)≤max(E max,i ,P max,i ) Ensure that the actual heating supply of the heating unit is not lower than the cumulative heating supply and the lower limit of the heating power in each time period, and does not exceed the upper limit of the heating supply and the upper limit of the heating power, so as to achieve a balanced heat distribution.

7. A stratified heating control method based on intelligent optimization as claimed in claim 6, characterized in that: The generating of the regional heating guidance curve includes the time period number T of the regional heating coordinated control according to the current time floor level heating i Determine the number of heating control periods T required for the heating units in the area in the future from the current moment rg , the formula is expressed as, T rg =max(T1,T2,…,T i ) Determine the regional heating guidance curve Q according to the current time and the number of heating control periods ref , set the decision variable Q ref,rg (t), represents the guidance heating power of the regional heating system in each time period t in the future. By optimizing the heating scheduling, the heating is evenly distributed in each time period to ensure the stable operation of the heating system. The formula of the regional heating guidance curve is expressed as, The guiding heating power constraint in the region is expressed as: P min,i ≤Q ref,rg (t)≤P max,i Outside the heating planning period, the heating power is guided to be 0 to ensure that no additional heat is output during the non-heating period. The upper and lower limits of the cumulative heating capacity of each heating unit should meet the overall heating demand in the area. The formula is: The linear programming algorithm is used to solve the optimization problem and obtain the regional heating guidance curve. The solved guidance curve is applied to the regional heating control to achieve orderly heating of each heating unit in the region, ensure the maximization of heating efficiency and meet the regional heating control objectives.

8. A system based on the intelligent optimization-based stratified heating control method according to any one of claims 1 to 7, characterized in that: It includes heating control structure module, floor heating strategy module, floor heating optimization module and regional heating optimization module; The heating control structure module establishes the heating control structure at the regional level and the floor level to ensure that the heating behavior of each floor is consistent with the regional level control target; The floor heating strategy module obtains heating optimization parameters according to the heating guidance curve of the future period, calculates the number of heating demand time periods, constructs a priority table of heating units in the floor, determines the start and stop sequence of the heating units according to the sorting results of the priority table, and realizes orderly heating operation through the start and stop control matrix to ensure that key units get heating first; The floor heating optimization module calculates the demand boundary and time period number of each heating unit, generates a floor-level heating demand boundary curve, and ensures a reasonable distribution of heat supply and power; The regional heating optimization module determines the number of heating coordination control time periods for each floor, calculates the overall heating demand of the heating units in the region, and generates a regional heating guidance curve to optimize the heating distribution and ensure the stable operation of the heating system in the region.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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