Multi-heat-source heat supply cooperative scheduling method, device, equipment and medium

Abstract

The invention provides a multi-heat-source heat supply cooperative scheduling method, device and equipment and a medium, and the method comprises the steps: obtaining a heat source scheduling combination corresponding to each historical moment in a historical heat supply period according to heat source ratio information in the historical heat supply period; wherein the heat source ratio information is obtained according to historical energy supply information, obtained in advance, of each heat source, the effective heat supply amount of each heat source is determined by utilizing a conversion model, and the unit energy purchase cost and the carbon emission factor, obtained in advance, of each heat source are combined by utilizing an optimal stopping criterion of a greedy algorithm; the conversion model is constructed according to historical heating data obtained in advance and the energy conversion coefficient of each heat source; and selecting the heat source scheduling combination at the current target moment according to the heat source scheduling combination corresponding to each historical moment in the historical heat supply cycle, and cooperatively scheduling the corresponding heat source according to the selected heat source scheduling combination. The system can effectively cope with the peak load of a municipal heat source and reduce the energy consumption while giving consideration to economy and environmental protection.

Description

Technical Field

[0001] This invention relates to the field of smart heating technology, and in particular to a method, device, equipment and medium for coordinated scheduling of multi-heat source heating. Background Technology

[0002] With the increasing severity of global climate change and the scarcity of energy resources, low-carbon and energy-saving heating technologies have been widely researched and applied. Municipal heat sources, as an important component of traditional heating systems, have long been a source of concern for energy management departments due to issues such as load fluctuations, fuel consumption, and heating efficiency during peak periods. During the cold season, the sharp increase in heat demand often causes municipal heat sources to exceed their optimal operating range, leading to overload operation, significant energy waste, and even unstable heating or system failures.

[0003] Current heating dispatching methods largely rely on traditional timed preset scheduling or simple real-time adjustment strategies, and depend on the scale of traditional heat sources and energy storage equipment for regulation. However, this dispatching approach lacks accurate prediction of demand fluctuations, weather changes, and load variations, failing to achieve intelligent and optimized dispatching. This results in problems such as energy waste, environmental pollution, and uneven equipment load during the operation of the heating dispatching system. Summary of the Invention

[0004] This invention provides a method, apparatus, equipment, and medium for coordinated scheduling of multi-heat source heating systems, which addresses the shortcomings of existing heating systems such as inflexible scheduling, high carbon emissions, and insufficient energy utilization, thereby achieving intelligent scheduling and ensuring low-carbon and efficient energy utilization.

[0005] This invention provides a multi-heat-source heating coordinated scheduling method, comprising: obtaining heat source scheduling combinations corresponding to each historical moment within a historical heating cycle based on heat source allocation information within the historical heating cycle; wherein, the heat source allocation information is obtained by using a conversion model to determine the effective heat supply of each heat source based on previously acquired historical energy supply information of each heat source, and by combining the previously acquired unit energy purchase cost and carbon emission factor of each heat source with the optimal stopping criterion of a greedy algorithm; the conversion model is constructed based on previously acquired historical heating data and the energy conversion coefficient of each heat source; selecting the heat source scheduling combination for the current target moment based on the heat source scheduling combinations corresponding to each historical moment within the historical heating cycle, and coordinating the scheduling of the corresponding heat sources according to the selected heat source scheduling combination.

[0006] According to the multi-heat source heating coordinated scheduling method provided by the present invention, before obtaining the heat source scheduling combination corresponding to each historical moment in the historical heating cycle based on the heat source allocation information in the historical heating cycle, the method includes: acquiring the historical energy supply information of each heat source; wherein, the historical energy supply information includes the energy supply information of the corresponding heat source at each historical moment; inputting the historical energy supply information of each heat source into a conversion model to convert the historical energy supply information of the corresponding heat source based on the energy conversion coefficient of each heat source to obtain the effective heat supply of each heat source; and based on the effective heat supply of each heat source, combined with the previously acquired unit energy purchase cost and carbon emission factor of each heat source. The process involves determining the unit heating cost and unit heating carbon emissions for each heat source at each historical time. For each historical time, based on the unit heating cost and unit heating carbon emissions, an economic benefit score is determined for each heat source. Based on the economic benefit score, the heat sources are ranked to obtain the heat source ranking results for each historical time. For each historical time, based on historical heating data and the heat source ranking results for that historical time, the optimal stopping criterion of a greedy algorithm is used to determine the allocated load for each heat source. Combined with the historical heating data for that historical time, the allocation ratio of each heat source for that historical time is determined to obtain the heat source allocation information.

[0007] According to the multi-heat source heating coordinated scheduling method provided by the present invention, the unit heating cost and unit heating carbon emission of each heat source at each historical time are determined based on the effective heat supply of each heat source and the previously acquired unit energy purchase cost and carbon emission factor of each heat source. The method includes: inputting the effective heat supply of each heat source into a heating cost assessment model to assess the heating cost for each historical time, based on the unit energy purchase cost of each heat source, to obtain the system operating cost for each historical time; wherein the heating cost assessment model is constructed based on the previously acquired unit energy purchase cost of each heat source; inputting the effective heat supply of each heat source into a carbon emission assessment model to assess the carbon emission for each historical time, based on the corresponding carbon emission factor of each heat source, to obtain the total carbon emission for each historical time; wherein the carbon emission assessment model is constructed based on the previously acquired carbon emission factor of each heat source; and determining the unit heating cost and unit heating carbon emission of each heat source at each historical time based on the system operating cost and the total carbon emission for each historical time.

[0008] According to the multi-heat source heating coordinated scheduling method provided by the present invention, before determining the economic benefit score of each heat source based on the unit heating cost and unit heating carbon emission of each heat source for each historical time, the method includes: obtaining the unit heating cost and unit heating carbon emission of a single heat source reference system constructed under the same operating conditions for each historical time; normalizing the unit heating cost of each historical time using the unit heating cost corresponding to the single heat source reference system, and normalizing the unit heating carbon emission of each historical time using the unit heating carbon emission of the single heat source reference system.

[0009] According to the multi-heat source heating coordinated scheduling method provided by the present invention, before inputting the historical energy supply information of each heat source into the conversion model, the method includes: obtaining the energy conversion coefficient of each heat source, and constructing a conversion model based on the energy conversion coefficient of each heat source; After constructing a conversion model based on the energy conversion coefficients of each heat source, the process includes: determining if a heat source matches the target type, and acquiring historical heating data; wherein, the historical heating data includes the indoor heating demand temperature and outdoor heating temperature at each historical time; obtaining the heating load at each historical time based on the historical heating data; obtaining the relative heating load ratio at each historical time based on the heating load of the target heat source at each historical time and the preset heating load at the corresponding historical time; determining the supply water temperature at each historical time based on the relative heating load ratio and the indoor heating demand temperature at each historical time, combined with the preset supply water temperature and preset return water temperature at the corresponding historical time; and correcting the energy conversion coefficient of the target heat source according to the corresponding historical time based on the supply water temperature and outdoor heating temperature at each historical time.

[0010] According to the multi-heat source heating coordinated scheduling method provided by the present invention, for each historical time point, based on historical heating data and the heat source ranking results for the corresponding historical time point, the optimal stopping criterion of a greedy algorithm is used to determine the allocated load for each corresponding heat source, including: for each historical time point, obtaining the heating load for the corresponding historical time point based on the indoor heating demand temperature and outdoor heating temperature for the corresponding historical time point in the historical heating data; according to the heat source ranking results for the corresponding historical time point, selecting the corresponding heat sources in descending order of economic benefit scores, comparing the effective heat supply of the selected heat sources with the heating load for the corresponding time point, and allocating the minimum value obtained from the comparison to the corresponding selected heat source to obtain the allocated load for the selected heat source; wherein, if it is determined that the effective heat supply of the selected heat source is less than the heating load for the corresponding historical time point, the heating load is updated based on the effective heat supply of the selected heat source, and the next heat source is selected; otherwise, the allocation of load to the remaining unselected load is stopped.

[0011] According to the present invention, a multi-heat source heating coordinated scheduling method includes the following steps before generating control commands and sending them to the corresponding heat sources based on the heat source scheduling combination: obtaining the current operating status of each heat source's equipment; determining, based on the operating status of each heat source's equipment, that at least one of the following occurs in the heat source scheduling combination: heat source equipment failure, deviation of actual effective heat supply, cumulative running time reaching a limit, and equipment continuous start-stop count reaching an upper limit; adjusting the heat source allocation ratio in the corresponding heat source allocation information to 0; updating the allocated load of the remaining heat sources based on the heat source sorting results of the other heat sources at the corresponding time and the current heating load using the optimal stopping criterion of a greedy algorithm; determining the allocation ratio of the remaining heat sources at the corresponding time based on the current heating load; and updating the heat source scheduling combination based on the allocation ratio of the remaining heat sources at the corresponding time.

[0012] This invention also provides a multi-heat source heating coordinated scheduling device, comprising: a combination acquisition module, which obtains the heat source scheduling combination corresponding to each historical moment in the historical heating cycle based on the heat source allocation information in the historical heating cycle; wherein, the heat source allocation information is obtained by using a conversion model to determine the effective heat supply of each heat source based on the historical energy supply information of each heat source obtained in advance, and by combining the unit energy purchase cost and carbon emission factor of each heat source obtained in advance, using the optimal stopping criterion of a greedy algorithm; the conversion model is constructed based on the historical heating data obtained in advance and the energy conversion coefficient of each heat source; and a coordinated scheduling module, which selects the heat source scheduling combination for the current target moment based on the heat source scheduling combination corresponding to each historical moment in the historical heating cycle, and coordinates the corresponding heat source according to the selected heat source scheduling combination.

[0013] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the multi-heat source heating coordinated scheduling method as described above.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the multi-heat source heating coordinated scheduling method as described above.

[0015] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the multi-heat source heating coordinated scheduling method as described above.

[0016] The multi-heat-source heating coordinated scheduling method, device, equipment, and medium provided by this invention transforms the original energy input of each heat source into standardized effective heat supply through a conversion model, enabling all heat sources to be compared on a unified scale. Combined with previously acquired unit energy purchase costs and carbon emission factors of each heat source, the invention fully considers the possibility of low-carbon and efficient use of renewable energy, explores the optimization potential of the system, and utilizes the optimal stopping criterion of a greedy algorithm to quickly find a sufficiently good solution for each historical moment, obtaining heat source allocation information. This ensures that the resulting scheduling strategy balances economy and environmental protection while flexibly and effectively responding to peak loads of municipal heat sources, reducing energy consumption, achieving intelligent scheduling, and guaranteeing low-carbon and efficient energy utilization. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the multi-heat source heating coordinated scheduling method provided by the present invention; Figure 2 This is a schematic diagram of the process for obtaining heat source ratio information provided by the present invention; Figure 3 This is a schematic diagram of the multi-heat source heating coordinated scheduling device provided by the present invention; Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0020] Figure 1 This is a flowchart illustrating the multi-heat source heating coordinated scheduling method provided by the present invention, as shown below. Figure 1 As shown, the method includes: S11. Based on the heat source allocation information within the historical heating cycle, obtain the heat source scheduling combination corresponding to each historical moment within the historical heating cycle. The heat source allocation information is obtained by using a conversion model to determine the effective heat supply of each heat source based on the historical energy supply information of each heat source obtained in advance, and by combining the unit energy purchase cost and carbon emission factor of each heat source obtained in advance, using the optimal stopping criterion of a greedy algorithm. The conversion model is constructed based on the historical heating data obtained in advance and the energy conversion coefficient of each heat source. S12: Select the heat source scheduling combination for the current target time according to the heat source scheduling combination corresponding to each historical moment in the historical heating cycle, and coordinate the scheduling of the corresponding heat source according to the selected heat source scheduling combination.

[0021] It should be noted that the step number "S1N" in this manual does not represent the order of steps in the multi-heat source heating coordinated scheduling method. The following details will explain this in conjunction with... Figure 2 The present invention describes a multi-heat source heating coordinated scheduling method.

[0022] Step S11: Based on the heat source allocation information within the historical heating cycle, obtain the heat source scheduling combination corresponding to each historical moment within the historical heating cycle; wherein, the heat source allocation information is obtained by using a conversion model to determine the effective heat supply of each heat source based on the historical energy supply information of each heat source obtained in advance, and by combining the unit energy purchase cost and carbon emission factor of each heat source obtained in advance, using the optimal stopping criterion of a greedy algorithm; the conversion model is constructed based on the historical heating data obtained in advance and the energy conversion coefficient of each heat source.

[0023] In this embodiment, the heat source allocation information includes the allocation ratio of each heat source at each historical moment within the historical heating cycle. The heat source allocation ratio indicates the proportion of contribution undertaken by the heat source to meet the heating load at the corresponding historical moment. The types of heat sources include traditional energy sources such as municipal heat source gas boilers and low-carbon distributed energy sources such as solar energy and geothermal energy. The specific selection can be made according to the actual design, and no further limitation is made here.

[0024] Accordingly, based on the heat source allocation information within the historical heating cycle, the heat source scheduling combination corresponding to each historical moment within the historical heating cycle is obtained, including: for each historical moment, according to the allocation of each corresponding heat source, selecting heat sources with a non-zero allocation ratio, and combining the allocation ratio of the selected heat sources to obtain the heat source scheduling combination for the corresponding historical moment. The heat source scheduling combination includes the corresponding heat source and the allocation ratio of each heat source.

[0025] In one alternative embodiment, reference Figure 2 Before obtaining the heat source scheduling combination corresponding to each historical moment in the historical heating cycle based on the heat source allocation information in the historical heating cycle, the following steps are included: Step S21: Obtain historical energy supply information for each heat source; wherein, the historical energy supply information includes the energy supply information of the corresponding heat source at each historical moment.

[0026] It should be added that historical energy supply information is used to characterize the original input of the corresponding heat source. The specific historical energy supply information can be determined according to the type of the corresponding heat source. For example, if the heat source is an air source heat pump (ASHP), the corresponding historical energy supply information is the system input electrical power. If the heat source is a municipal gas-fired boiler (GFB) or other traditional energy source, the corresponding historical energy supply information is the resource input energy. The specific energy supply information needs to be determined in conjunction with the actual type of heat source involved, and no further restrictions are made here.

[0027] Step S22: Input the historical energy supply information of each heat source into the conversion model, and convert the historical energy supply information of the corresponding heat source based on the energy conversion coefficient of each heat source to obtain the effective heat supply of each heat source; wherein, the effective heat supply of each heat source includes the effective heat supply at each historical moment.

[0028] It is worth noting that when the heat source is an air-source heat pump, for any given historical moment, its energy conversion process follows thermodynamic principles, that is... ,in, This represents the effective heat supply of the heat source at historical time t. This represents the system input electrical power of the heat source at historical time t. The Coefficient of Performance (COP) represents the device performance of the heat source at historical time t, which is the energy conversion coefficient.

[0029] When the heat source is a traditional energy source such as a municipal gas-fired boiler, the energy utilization process follows the energy quality conversion law at any given historical moment, that is... ,in, This represents the available heat from the heat source at time t in history. This represents the energy input to the heat source at time t in history. express This represents the energy conversion efficiency of the heat source at historical time t, i.e., the energy conversion coefficient.

[0030] Therefore, in order to achieve unified modeling of multiple types of heat sources, such as renewable energy and gas boilers, before inputting the historical energy supply information of each heat source into the conversion model, the following steps are taken: obtaining the energy conversion coefficient of each heat source, and constructing a conversion model based on the energy conversion coefficient of each heat source. The conversion model is used to describe the energy conversion relationship of various heat sources in a multi-heat source system per unit time.

[0031] Accordingly, the transformation model is represented as: in, This represents the effective heat supply of each heat source as output by the conversion model at historical time t. , This represents the effective heat supply of heat source i at time t, in units of Kw, where i = 1, 2, ..., n; This represents the energy conversion coefficient of each heat source at historical time t. Where n represents the total number of heat sources, This represents the energy conversion coefficient of heat source i at time t, such as the device performance coefficient and energy conversion efficiency mentioned above, which are specifically determined based on the corresponding heat source. This represents the historical energy supply information of the heat source input to the conversion model at historical time t. ,in, This indicates the energy supply information of heat source i at time t, such as system input electrical power, resource input energy, etc., which is determined according to the corresponding heat source, and the unit is kW.

[0032] Furthermore, when the heat source is the target heat source, such as an air-source heat pump, the outdoor heating temperature easily affects the compressor compression ratio, and the water supply temperature affects the evaporator absorption capacity. Therefore, the COP coefficient is easily affected by the outdoor heating temperature and the water supply temperature. Accordingly, after constructing a conversion model based on the energy conversion coefficients of each heat source, the following steps are taken: when a heat source that meets the target type is determined, historical heating data is obtained; the historical heating data includes the indoor heating demand temperature and the outdoor heating temperature at each historical time; based on the historical heating data, the heating load at each historical time is obtained; based on the heating load of the target heat source at each historical time and the preset heating load at the corresponding historical time, the relative heating load ratio at each historical time is obtained; based on the relative heating load ratio at each historical time and the indoor heating demand temperature at each historical time, combined with the preset water supply temperature and preset return water temperature at the corresponding historical time, the water supply temperature at each historical time is determined; based on the water supply temperature and the outdoor heating temperature at each historical time, the energy conversion coefficient of the target heat source is corrected according to the corresponding historical time.

[0033] It should be added that the target type can be set according to the actual heat source affected by the outdoor heating temperature and water supply temperature, so that when the target heat source is determined after the conversion model is built, the corresponding energy conversion coefficient can be corrected one by one according to each historical time. No further restrictions are made here.

[0034] Furthermore, taking the COP coefficient as an example, the corrected energy conversion coefficient is expressed as: in, This represents the correction factor for the heat source at historical time t. This represents the water supply temperature at historical time t; This represents the outdoor heating temperature at historical time t.

[0035] Furthermore, before determining the water supply temperature for each historical time based on the relative heating load ratio and the indoor heating demand temperature at each historical time, combined with the preset water supply temperature and preset return water temperature at the corresponding historical time, a water supply temperature prediction model is constructed.

[0036] It should be noted that this assumes the user-side heat load regulation is primarily qualitative, adjusting the supply and return water temperatures to match fluctuating indoor heat load demands, aiming for low-carbon and high-efficiency operation. Without considering heat loss along the heating path, the heat supply of the hot water heating system should satisfy the following heat balance relationship: in, This indicates the preset heating load, which is the building's design heating load, expressed in W. This indicates the outdoor design calculation temperature for heating. Below, the heat released by the radiator is measured in W. This indicates the outdoor design calculation temperature for heating. Below is the heat delivered by the hot water network to heating users, expressed in W. This indicates the heating design index per square meter of building area, i.e., the heating capacity per square meter of building area. 2 The heat consumption of the heating area when the indoor and outdoor temperature difference is 1℃ is expressed in W / (m²). 2 ·℃); This indicates the heating area of ​​a building, in square meters (m²). 2 ; This indicates the calculated indoor temperature for heating, in °C. This indicates the outdoor design calculation temperature for heating, in °C. This represents the heat transfer coefficient of the radiator under design conditions, expressed in W / (m²). 2 ·℃); This indicates the heat dissipation area of ​​the radiator, in meters (m²). 2 ; This indicates the average design temperature of the heat transfer medium inside the radiator, in °C. This indicates the design circulating water volume for heating users, expressed in kg / h. This indicates the design temperature of the water supply entering the heating user's system, i.e., the preset supply temperature, in °C. If the user is directly connected to the heating network without a mixing device, then the heating network supply temperature is... If the user connects directly to the heating network using a mixing device, then ; This indicates the design temperature of the return water for heating users, in degrees Celsius (°C). It is the preset return water temperature. If the user is directly connected to the heating network, the return water temperature of the heating network is equal to the return water temperature of the heating system. .

[0037] In addition, the heat dissipation method of the radiator is natural convection, and its heat transfer coefficient has... The form is: where 'a' represents a comprehensive coefficient, influenced by various factors including radiator material and structural characteristics, and fluid physical properties; 'b' represents the temperature difference index, reflecting the degree of change in the heat transfer coefficient K with temperature difference. For example, for the entire heating system, it can be approximated as: Accordingly, .

[0038] When the actual outdoor temperature for heating is At this time, the heat balance equation can be expressed as: It should be noted that the meaning of each parameter in the heat balance equation can be found in the meaning of the design parameters corresponding to the heat balance relationship above, and will not be repeated here.

[0039] Accordingly, assuming that during the adjustment process, the corresponding The ratio of the heating load provided to the preset heating load is called the relative heating load ratio. ,but: For direct-connection hot water heating systems without a mixing device, Substituting into the above formula, we obtain the water supply temperature prediction model. This facilitates the input of the corresponding indoor heating demand temperature at each historical time into the final stage of the water supply temperature prediction model when determining the water supply temperature at each historical time, thus obtaining the return water temperature at each historical time. Specifically, the water supply temperature prediction model is expressed as: Similarly, based on the above method, a return water temperature prediction model can also be obtained, expressed as: Step S23: Based on the effective heat supply of each heat source, and combined with the previously obtained unit energy purchase cost and carbon emission factor of each heat source, determine the unit heating cost and unit heating carbon emission of each heat source at each historical moment.

[0040] In this embodiment, based on the effective heat supply of each heat source and combined with the previously obtained unit energy purchase cost and carbon emission factor of each heat source, the unit heating cost and unit heating carbon emission of each heat source at each historical time are determined. This includes: inputting the effective heat supply of each heat source into a heating cost assessment model to assess the heating cost for each historical time, combined with the unit energy purchase cost of each heat source, to obtain the system operating cost for each historical time; wherein, the heating cost assessment model is constructed based on the previously obtained unit energy purchase cost of each heat source; inputting the effective heat supply of each heat source into a carbon emission assessment model to assess the carbon emission for each historical time, combined with the carbon emission factor of each heat source, to obtain the total carbon emission for each historical time; wherein, the carbon emission assessment model is constructed based on the previously obtained carbon emission factor of each heat source; and determining the unit heating cost and unit heating carbon emission of each heat source at each historical time based on the system operating cost and the total carbon emission for each historical time. It should be added that, for each heat source, the unit energy purchase cost includes the cost for each historical moment.

[0041] Furthermore, operating cost (OC) refers to all energy procurement expenditures incurred by the system to maintain heating throughout the entire scheduling cycle. Accordingly, the heating cost assessment model is expressed as: in, This represents the system operating cost at historical time t; This represents the unit energy purchase price of heat source i at historical time t, in yuan / kWh; This represents the energy supply information of heat source i at time t, in kW; This represents the effective heat supply of heat source i at historical time t, expressed in kW.

[0042] Furthermore, the Levelized Cost of Heat (LCOH) measures the average economic cost of supplying one unit of heat energy within a system's scheduling cycle. Accordingly, based on the system operating cost at historical time t, the corresponding unit cost of heat energy for each energy source at historical time t is determined, expressed as: In addition, Total Carbon Emission (TCE) is used to assess the environmental impact during system operation. Accordingly, the carbon emission assessment model is expressed as follows: in, This represents the total carbon emissions at historical time t; The carbon emission factor of heat source i is expressed in kgCO2 / kWh.

[0043] Furthermore, Specific Carbon Emission of Heat Supply (CEOH) measures the carbon emission intensity corresponding to various heat sources in providing a unit of heat energy. Accordingly, based on the total carbon emissions at historical time t, the corresponding unit heating cost for each energy source at historical time t is determined, expressed as: It should be noted that by fully considering the possibility of low-carbon and efficient use of renewable energy, exploring the optimization potential of the system, flexibly and effectively responding to extreme load fluctuations, reducing the peak load of municipal heat sources, reducing energy consumption, and introducing low-carbon distributed energy (such as solar energy, geothermal energy, etc.), the dependence on fossil fuels can be further reduced, thereby reducing the carbon emissions of the system.

[0044] In one optional embodiment, before determining the economic benefit score of each heat source based on the unit heating cost and unit heating carbon emission for each historical moment, the method includes: obtaining the unit heating cost and unit heating carbon emission of a single heat source reference system constructed under the same operating conditions for each historical moment; normalizing the unit heating cost for each historical moment using the unit heating cost corresponding to the single heat source reference system, and normalizing the unit heating carbon emission for each historical moment using the unit heating carbon emission of the single heat source reference system.

[0045] It should be added that the normalized unit heating cost for each historical moment is expressed as: in, This represents the unit heating cost of heat source i after normalization at historical time t. This represents the unit heating cost corresponding to historical time t of a single heat source reference system. This represents the unit energy purchase price of the heat source in a single heat source reference system at historical time t. This represents the energy conversion coefficient of the heat source in a single heat source reference system at historical time t.

[0046] The normalized carbon emissions per unit of heating at each historical moment are expressed as follows: in, This represents the unit heating carbon emission of historical time t after normalization of heat source i; This represents the carbon emissions per unit of heating corresponding to historical time t of a single heat source reference system. This represents the carbon emission factor of the heat source in a single heat source reference system at historical time t.

[0047] In addition, a single heat source reference system can use a municipal gas boiler or other single heat source, and operate under the same conditions. The specific heat source can be selected according to actual design requirements, and no further restrictions are made here.

[0048] Assuming a reference system using a municipal gas-fired boiler as the heat source, under the same operating conditions... Below, by establishing a system energy balance model and conversion efficiency calculation system, key parameters reflecting the performance characteristics of the reference system are derived item by item: First, the rated input power of the system is determined. This parameter represents the minimum energy input baseline required for the reference system to maintain stable thermodynamic cycle operation under the aforementioned operating conditions; subsequently, based on the comprehensive energy conversion characteristics under standard operating conditions, the system energy conversion coefficient is quantified. Simultaneously, taking into account the characteristics of the regional energy market, the unit energy purchase price for the energy consumed in the system operation should be clearly defined. , which serves as the basic price parameter for economic analysis.

[0049] The rated input power of the above system System energy conversion coefficient Purchase price per unit of energy The unit heating cost is determined through a heating cost assessment model. And introduce carbon emission factors The carbon footprint of the system operation process is quantified, and the carbon emissions per unit of heating are determined through a carbon emission assessment model. This results in a dual evaluation index system that includes both economic and environmental factors.

[0050] Step S24: For each historical moment, determine the economic benefit score of each heat source based on the unit heating cost and unit heating carbon emission of each heat source, and sort the corresponding heat sources based on the economic benefit score to obtain the heat source sorting results for each historical moment.

[0051] In this embodiment, the economic benefit score of each heat source is determined based on the unit heating cost and unit heating carbon emission of each heat source. This includes: for each historical moment, the unit heating cost and unit heating carbon emission of each heat source are weighted and summed according to preset cost weights and preset carbon emission weights to obtain the economic benefit score of each heat source.

[0052] It should be added that the preset cost weights This indicates the cost-benefit ratio of heat source operation, encompassing economic indicators such as energy conversion efficiency, return on investment, and operation and maintenance costs. Quantify; preset carbon emission weights Reflecting the environmental friendliness of heat sources, this study focuses on low-carbon indicators such as fossil energy consumption intensity, carbon footprint intensity, and the proportion of renewable energy consumption. Make indicators explicit; preset cost weights and preset carbon emission weights The sum is 1, that is .

[0053] It should be noted that different policy orientations apply to different regions, and different pre-set cost weights apply. and preset carbon emission weights Establish a differentiated weighting mechanism, specifically: for key carbon-neutral regions (such as carbon neutrality pilot cities), strengthen the weighting of carbon emission benefits, i.e. >0.5, to align with the rigid constraints of regional carbon emission reduction; for regions with high-quality economic development (such as national-level new areas), the emphasis is on the weight of economic benefits, i.e. >0.5, to balance the needs of low-carbon transformation and industrial investment returns. Preset cost weight. and preset carbon emission weights The specific values ​​can be set according to the differentiated weight allocation mechanism and prior experience, and are not further limited here.

[0054] In addition, the economic benefit scores for each heat source at each historical moment are expressed as follows: in, This represents the economic benefit score of heat source i at historical time t.

[0055] It should be noted that the economic benefit score uses a linear weighting method to couple and quantify economic benefits and carbon emission benefits, forming a single decision variable. This resolves the issue of conflicting indicators in multi-objective optimization. The higher the value, the better the overall performance of the heat source's corresponding operation plan in terms of economy and environmental protection.

[0056] Furthermore, by using the above method, the economic benefit score of each heat source at each historical moment is determined, which facilitates the ranking of heat sources at the corresponding historical moments based on the economic benefit score, thus obtaining the heat source ranking results for each historical moment. ,in, This represents the number of the k-th heat source in the heat source sorting result, where k = 1, 2, ..., n. In actual design, a descending order can be chosen, while an ascending order can be chosen in other embodiments; no further limitation is made here.

[0057] Step S25: For each historical moment, based on the historical heating data and the heat source sorting results of the corresponding historical moment, the optimal stopping criterion of the greedy algorithm is used to determine the distribution load of each heat source, and combined with the historical heating data of the corresponding historical moment, the ratio of each heat source for the corresponding historical moment is determined to obtain the heat source ratio information.

[0058] In this embodiment, for each historical moment, based on historical heating data and the heat source ranking results for that historical moment, the optimal stopping criterion of a greedy algorithm is used to determine the allocated load for each heat source. This includes: for each historical moment, obtaining the heating load for that historical moment based on the indoor heating demand temperature and outdoor heating temperature in the historical heating data; selecting corresponding heat sources in descending order of economic benefit score according to the heat source ranking results for that historical moment, comparing the effective heat supply of the selected heat source with the heating load for that historical moment, and allocating the minimum value obtained from the comparison to the selected heat source to obtain the allocated load for the selected heat source; wherein, if it is determined that the effective heat supply of the selected heat source is less than the heating load for that historical moment, the heating load is updated based on the effective heat supply of the selected heat source, and the next heat source is selected; otherwise, the allocation of load to the remaining unselected load is stopped.

[0059] It should be added that the optimal stopping criterion using the greedy algorithm is expressed as: in, This indicates that time t is the first heat source. Distribute its effective heat supply and the heating load at the corresponding historical time t The minimum value in; This indicates that the k-th heat source is at historical time t. Distribute its effective heat supply and the heating load at the corresponding historical time t The minimum value in the range. It should be noted that when the effective heat supply of the corresponding heat source is greater than or equal to the corresponding heat load demand (heating load)... or When the load is not allocated to the remaining heat source, stop allocating load to the remaining heat source.

[0060] For example, assuming there are 3 heat sources, and the heat source ranking is a descending order based on economic benefit scores, then the heat source ranking at historical time t is expressed as follows: Accordingly, based on the heat source sorting results, the first heat source is selected first. heat source Effective heating Heating load at the corresponding time The minimum value in the range is assigned to the heat source. As a heat source The load distribution, if the heat source When the effective heat supply is greater than or equal to the heating load, it shall cease to be a residual heat source. Distribute the load; otherwise, update the heating load to... And select a second heat source heat source Effective heating Corresponding updated heating load The minimum value in the range is assigned to the heat source. And based on a second heat source effective utilization rate Greater than or equal to the updated heating load Stop being a residual heat source Distribute the load; otherwise, update the heating load to... And select a third heat source heat source Effective heating Corresponding updated heating load The minimum value in the range is assigned to the heat source. .

[0061] In addition, the heat source allocation information is obtained, including: according to the allocated load of each heat source at the corresponding historical time, setting the corresponding allocation ratio to 0 for heat sources without allocated load; for heat sources with allocated load, determining the allocation ratio of the corresponding heat source according to the allocated load and heating load; and constructing an allocation matrix based on the allocation ratio of all heat sources at each historical time to obtain the heat source allocation information.

[0062] Specifically, the ratio of each heat source to each historical moment is expressed as follows: in, This represents the ratio of each heat source at historical time t.

[0063] In addition, the proportion matrix , is represented as: Step S12: Select the heat source scheduling combination for the current target time according to the heat source scheduling combination corresponding to each historical moment in the historical heating cycle, and coordinate the scheduling of the corresponding heat source according to the selected heat source scheduling combination.

[0064] It should be noted that the coordinated scheduling of the corresponding heat sources according to the selected heat source scheduling combination includes: generating scheduling instructions for the corresponding heat sources according to the selected heat source scheduling combination, and sending the scheduling instructions to the corresponding heat sources to realize the coordinated scheduling of multiple heat sources. This enables the determination of scheduling strategies through accurate demand forecasting, reduces energy waste, and achieves low-carbon and energy-saving heating services.

[0065] In an optional embodiment, before generating control commands and sending them to the corresponding heat sources according to the heat source scheduling combination, the process includes: obtaining the current operating status of each heat source's equipment; determining, based on the operating status of each heat source's equipment, that at least one of the following occurs in the heat source scheduling combination: a heat source meets the equipment fault criteria, the actual effective heat supply deviates from the limit, the cumulative running time reaches the limit, or the number of consecutive start-stop cycles of the equipment reaches the upper limit; adjusting the heat source allocation ratio in the corresponding heat source allocation information to 0; updating the allocated load of the remaining heat sources according to the heat source sorting results of the other heat sources at the corresponding time and the current heating load using the optimal stopping criterion of a greedy algorithm; determining the allocation ratio of the remaining heat sources at the corresponding time based on the current heating load; and updating the heat source scheduling combination according to the allocation ratio of the remaining heat sources at the corresponding time.

[0066] It should be added that by flexibly adjusting the scheduling strategy according to the equipment's operating status, the system's adaptability and resilience can be enhanced. In the event of sudden changes in demand or system failures, the system can provide stable heating and ensure users' heating needs are met. This improves the stability and resilience of the heating system, thereby significantly reducing energy consumption and carbon emissions while ensuring heating quality and stability, and enhancing the system's flexibility and emergency response capabilities.

[0067] In addition, before updating the allocated load of each of the remaining heat sources based on the heat source ranking results at the corresponding time and the current heating load using the optimal stopping criterion of the greedy algorithm, the process includes: inputting the operating status data of each of the remaining heat sources into the error prediction model to predict the load error of each heat source based on its operating status, thus obtaining the load error of each heat source; wherein, the error prediction model is first trained based on the historical operating status and error labels of each heat source device; and based on the load error of each heat source, the effective heat supply of each heat source at the corresponding historical time is compensated, so that the corresponding allocation ratio is updated according to the updated effective heat supply of each heat source in the manner described above, which will not be repeated here.

[0068] In summary, this invention transforms the raw energy input of each heat source into a standardized effective heat supply through a conversion model, enabling all heat sources to be compared on a unified scale. Combined with previously acquired unit energy purchase costs and carbon emission factors for each heat source, the invention fully considers the possibility of low-carbon and efficient use of renewable energy, explores the system's optimization potential, and utilizes the optimal stopping criterion of a greedy algorithm to quickly find a sufficiently good solution for each historical moment, obtaining heat source allocation information. This ensures that the resulting scheduling strategy balances economics and environmental protection while flexibly and effectively responding to peak loads of municipal heat sources, reducing energy consumption, achieving intelligent scheduling, and guaranteeing low-carbon and efficient energy utilization.

[0069] The multi-heat source heating coordinated scheduling device provided by the present invention is described below. The multi-heat source heating coordinated scheduling device described below can be referred to in correspondence with the multi-heat source heating coordinated scheduling method described above.

[0070] Figure 3 A schematic diagram of a multi-heat source heating coordinated scheduling device is shown. The device includes: The combined acquisition module 31 obtains the heat source scheduling combination corresponding to each historical moment in the historical heating cycle based on the heat source allocation information in the historical heating cycle. The heat source allocation information is obtained by using a conversion model to determine the effective heat supply of each heat source based on the historical energy supply information of each heat source obtained in advance, and by using the optimal stopping criterion of a greedy algorithm in combination with the unit energy purchase cost and carbon emission factor of each heat source obtained in advance. The conversion model is constructed based on the historical heating data obtained in advance and the energy conversion coefficient of each heat source. The collaborative scheduling module 32 selects the heat source scheduling combination for the current target time based on the heat source scheduling combination corresponding to each historical moment within the historical heating cycle, and coordinates the scheduling of the corresponding heat source according to the selected heat source scheduling combination.

[0071] It should be noted that the specific principles of the embodiments of the present invention are the same as those of the method embodiments described above. For details, please refer to the method embodiments above. More detailed explanations will not be repeated here.

[0072] Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4As shown, the electronic device may include: a processor 410, a communications interface 420, a memory 430, and a communications bus 440, wherein the processor 410, the communications interface 420, and the memory 430 communicate with each other through the communications bus 440. The processor 410 can call logic instructions in the memory 430 to execute a multi-heat source heating coordinated scheduling method. This method includes: obtaining heat source scheduling combinations corresponding to each historical moment within a historical heating cycle based on heat source allocation information within that cycle; wherein the heat source allocation information is obtained by using a conversion model to determine the effective heat supply of each heat source based on previously acquired historical energy supply information, and by combining previously acquired unit energy purchase costs and carbon emission factors of each heat source with the optimal stopping criterion of a greedy algorithm; the conversion model is constructed based on previously acquired historical heating data and the energy conversion coefficients of each heat source; selecting the heat source scheduling combination for the current target moment based on the heat source scheduling combinations corresponding to each historical moment within the historical heating cycle, and coordinating the scheduling of the corresponding heat sources according to the selected heat source scheduling combination.

[0073] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, 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 a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0074] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the multi-heat source heating coordinated scheduling method provided by the above methods. The method includes: obtaining the heat source scheduling combination corresponding to each historical moment in the historical heating cycle based on the heat source allocation information in the historical heating cycle; wherein, the heat source allocation information is obtained by using a conversion model to determine the effective heat supply of each heat source based on the historical energy supply information of each heat source obtained in advance, and by combining the unit energy purchase cost and carbon emission factor of each heat source obtained in advance, using the optimal stopping criterion of a greedy algorithm; the conversion model is constructed based on the historical heating data obtained in advance and the energy conversion coefficient of each heat source; selecting the heat source scheduling combination for the current target moment according to the heat source scheduling combination corresponding to each historical moment in the historical heating cycle, and coordinating the corresponding heat source according to the selected heat source scheduling combination.

[0075] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the multi-heat source heating coordinated scheduling method provided by the above methods. This method includes: obtaining heat source scheduling combinations corresponding to each historical moment within a historical heating cycle based on heat source allocation information within the historical heating cycle; wherein the heat source allocation information is obtained by using a conversion model to determine the effective heat supply of each heat source based on previously acquired historical energy supply information of each heat source, and by combining the previously acquired unit energy purchase cost and carbon emission factor of each heat source with the optimal stopping criterion of a greedy algorithm; the conversion model is constructed based on previously acquired historical heating data and the energy conversion coefficient of each heat source; selecting the heat source scheduling combination for the current target moment based on the heat source scheduling combinations corresponding to each historical moment within the historical heating cycle, and coordinating the corresponding heat sources according to the selected heat source scheduling combination.

[0076] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0077] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0078] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for coordinated scheduling of multi-heat source heating, characterized in that, include: Based on the heat source allocation information within the historical heating cycle, the heat source scheduling combination corresponding to each historical moment within the historical heating cycle is obtained; wherein, the heat source allocation information is obtained by using a conversion model to determine the effective heat supply of each heat source based on the historical energy supply information of each heat source obtained in advance, and by combining the unit energy purchase cost and carbon emission factor of each heat source obtained in advance, using the optimal stopping criterion of a greedy algorithm; the conversion model is constructed based on the historical heating data obtained in advance and the energy conversion coefficient of each heat source. Based on the heat source scheduling combinations corresponding to each historical moment within the historical heating cycle, select the heat source scheduling combination for the current target moment, and coordinate the scheduling of the corresponding heat source according to the selected heat source scheduling combination.

2. The multi-heat source heating coordinated scheduling method according to claim 1, characterized in that, Before obtaining the heat source scheduling combination corresponding to each historical moment within the historical heating cycle based on the heat source allocation information within the historical heating cycle, the process includes: Obtain historical energy supply information for each heat source; wherein, the historical energy supply information includes the energy supply information of the corresponding heat source at each historical moment; The historical energy supply information of each heat source is input into the conversion model, and the historical energy supply information of the corresponding heat source is converted based on the energy conversion coefficient of each heat source to obtain the effective heat supply of each heat source. Based on the effective heat supply of each heat source, and combined with the previously obtained unit energy purchase cost and carbon emission factor of each heat source, determine the unit heating cost and unit heating carbon emission of each heat source at each historical moment. For each historical moment, the economic benefit score of each heat source is determined based on the unit heating cost and unit heating carbon emission of each heat source. Based on the economic benefit score, the corresponding heat sources are sorted to obtain the heat source sorting results for each historical moment. For each historical moment, based on the historical heating data and the heat source sorting results for the corresponding historical moment, the optimal stopping criterion of the greedy algorithm is used to determine the load distribution for each heat source, and combined with the historical heating data for the corresponding historical moment, the ratio of each heat source for the corresponding historical moment is determined to obtain the heat source ratio information.

3. The multi-heat source heating coordinated scheduling method according to claim 2, characterized in that, Based on the effective heat supply of each heat source, and combined with the previously obtained unit energy purchase cost and carbon emission factor of each heat source, determine the unit heating cost and unit heating carbon emission of each heat source at each historical moment, including: The effective heat supply of each heat source is input into the heating cost assessment model to assess the heating cost for each historical time point, in conjunction with the unit energy purchase cost of each heat source, and to obtain the system operating cost for each historical time point; wherein, the heating cost assessment model is constructed based on the previously obtained unit energy purchase cost of each heat source; The effective heat supply of each heat source is input into the carbon emission assessment model to assess the carbon emissions for each historical time point, in combination with the carbon emission factors of each heat source, so as to obtain the total carbon emissions for each historical time point; wherein, the carbon emission assessment model is constructed based on the carbon emission factors of each heat source obtained in advance; Based on the system operating costs and total carbon emissions at each historical moment, determine the unit heating cost and unit heating carbon emissions for each heat source at each historical moment.

4. The multi-heat source heating coordinated scheduling method according to claim 2, characterized in that, Before determining the economic benefit score of each heat source based on its unit heating cost and unit heating carbon emissions for each historical moment, the following steps are included: Obtain the unit heating cost and unit heating carbon emissions for each historical moment corresponding to a single heat source reference system constructed under the same operating conditions; For each historical moment, the unit heating cost corresponding to the single heat source reference system is normalized, and the unit heating carbon emission corresponding to the single heat source reference system is normalized.

5. The multi-heat source heating coordinated scheduling method according to claim 2, characterized in that, Before inputting the historical energy supply information of each heat source into the conversion model, the following steps are included: Obtain the energy conversion coefficient of each heat source, and construct a conversion model based on the energy conversion coefficient of each heat source; After constructing the conversion model based on the energy conversion coefficients of each heat source, the following is included: When it is determined that a heat source matches the target type, historical heating data is obtained; wherein, the historical heating data includes the indoor heating demand temperature and the outdoor heating temperature at each of the historical times; Based on the historical heating data, the heating load at each of the historical moments is obtained; Based on the heating load of the target heat source corresponding to each historical moment and the preset heating load of the corresponding historical moment, the relative heating load ratio of each historical moment is obtained. Based on the relative heating load ratio and the indoor heating demand temperature at each of the historical times, and in conjunction with the preset supply water temperature and preset return water temperature at the corresponding historical times, the supply water temperature at each of the historical times is determined. The energy conversion coefficient of the target heat source is corrected according to the water supply temperature and outdoor heating temperature at each historical moment.

6. The multi-heat source heating coordinated scheduling method according to claim 2, characterized in that, For each historical moment, based on the historical heating data and the heat source ranking results for the corresponding historical moment, the optimal stopping criterion of the greedy algorithm is used to determine the allocated load for each heat source, including: For each historical moment, the heating load for that historical moment is obtained based on the indoor heating demand temperature and outdoor heating temperature for that historical moment in the historical heating data. Based on the heat source ranking results at the corresponding historical moment, the corresponding heat sources are selected in descending order of economic benefit scores. The effective heat supply of the selected heat sources is compared with the heating load at the corresponding moment. The minimum value obtained from the comparison is allocated to the corresponding selected heat source to obtain the allocated load of the selected heat source. Specifically, if the effective heat supply of the selected heat source is less than the heating load at the corresponding historical time, the heating load is updated based on the effective heat supply of the selected heat source, and the next heat source is selected; otherwise, the allocation of load to the remaining unselected load is stopped.

7. The multi-heat source heating coordinated scheduling method according to claim 2, characterized in that, Before generating control commands and sending them to the corresponding heat sources based on the heat source scheduling combination, the process includes: Obtain the current operating status of each heat source; Based on the operating status of each heat source, if at least one of the following conditions is met in the heat source scheduling combination: heat source meets equipment failure, actual effective heat supply deviates, cumulative running time reaches the limit, and the number of consecutive equipment start-stops reaches the upper limit, the heat source allocation ratio in the heat source allocation ratio information at the corresponding time is adjusted to 0. Based on the heat source sorting results of the other heat sources at the corresponding time and the heating load at the current time, the optimal stopping criterion of the greedy algorithm is used to update the allocated load of the other heat sources. Combined with the heating load at the current time, the allocation ratio of the other heat sources at the corresponding time is determined. The heat source scheduling combination is updated based on the ratio of the other heat sources at the corresponding time.

8. A multi-heat source heating coordinated scheduling device, characterized in that, include: The combined acquisition module obtains the heat source scheduling combination corresponding to each historical moment within the historical heating cycle based on the heat source allocation information within the historical heating cycle. The heat source allocation information is obtained by using a conversion model to determine the effective heat supply of each heat source based on previously acquired historical energy supply information, and by combining this with the previously acquired unit energy purchase cost and carbon emission factor of each heat source, using the optimal stopping criterion of a greedy algorithm. The conversion model is constructed based on previously acquired historical heating data and the energy conversion coefficient of each heat source. The collaborative scheduling module selects the heat source scheduling combination for the current target time based on the heat source scheduling combination corresponding to each historical moment within the historical heating cycle, and collaboratively schedules the corresponding heat source according to the selected heat source scheduling combination.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the multi-heat source heating coordinated scheduling method as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the multi-heat source heating coordinated scheduling method as described in any one of claims 1 to 7.

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