A method and system for temperature control of circulating water in power plant heating

Abstract

This invention discloses a method and system for regulating the temperature of circulating water in a power plant's heating system, relating to the field of data acquisition and monitoring control technology. The method includes: acquiring the first inlet and first outlet temperatures of the internal circulating water in the heater of a power plant's heating system, and the second inlet and second outlet temperatures of the primary piping network within the heater; determining the target waste heat fluctuation rate of the internal circulating water in the heater based on the first inlet and first outlet temperatures; determining the supply-demand matching deviation of the power plant's heating system based on the first inlet temperature, first outlet temperature, second inlet temperature, and second outlet temperature; determining a first adjustment weight for the power plant's heating system based on the target waste heat fluctuation rate and the supply-demand matching deviation; and dynamically adjusting the heating temperature of the power plant's heating system based on the first adjustment weight. This invention can improve the reliability of heating system temperature regulation.

Description

Technical Field

[0001] This invention relates to the field of data acquisition and monitoring control technology, specifically to a method and system for regulating the temperature of circulating water in a power plant heating system. Background Technology

[0002] Power plant heating, as an important form of combined heat and power (CHP), uses circulating heating water to deliver waste heat generated by power plant electricity to users, achieving waste heat recovery and utilization, and improving energy efficiency. However, power plant waste heat is affected by grid dispatch instructions, exhibiting drastic fluctuations on a second or minute basis, while user heat load is affected by meteorological and behavioral factors, exhibiting inertial changes on an hourly basis. This time-varying characteristic of both the heat source and the heat load makes it difficult to accurately match waste heat with user heat load demand on a time scale, resulting in discrepancies.

[0003] Existing methods for controlling the temperature of circulating water in power plant heating systems primarily balance power generation and user heating demands by allocating a fixed threshold ratio to ensure that the needs of all parties are met. This method is based on a static allocation strategy with rigid boundaries, distributing waste heat through preset thresholds to maintain relative stability between power generation and heating.

[0004] However, this may result in sacrificing heating temperature to maintain power generation vacuum during sudden drops in waste heat, or causing heat waste due to adjustment lag when waste heat is redundant, thereby affecting power generation efficiency and heating efficiency, leading to poor reliability of heating circulating water temperature control. Summary of the Invention

[0005] This invention provides a method and system for regulating the temperature of circulating water in a power plant heating system, which can improve the reliability of circulating water temperature regulation.

[0006] A first aspect of the present invention provides a method for regulating the temperature of circulating water in a power plant heating system, comprising: The first inlet temperature and the first outlet temperature of the internal circulating water in the heater of the power plant heating circulating water system, as well as the second inlet temperature and the second outlet temperature of the primary pipeline in the heater, are obtained. Based on the first inlet temperature and the first outlet temperature, the target waste heat fluctuation rate of the internal circulating water in the heater is determined; the target waste heat fluctuation rate is used to characterize the severity of the impact of power grid dispatch on heating supply. Based on the first inlet temperature, the first outlet temperature, the second inlet temperature, and the second outlet temperature, the supply and demand matching deviation of the power plant's heating circulating water system is determined. Based on the target waste heat volatility and the supply-demand mismatch, the first adjustment weight of the power plant heating circulating water system is determined. Based on the first adjustment weight, the heating temperature of the power plant's heating circulating water system is dynamically adjusted.

[0007] Furthermore, this application also proposes determining the target waste heat fluctuation rate of the internal circulating water in the heater based on the first inlet temperature and the first outlet temperature, including: The theoretical lag time of the internal circulating water is determined based on the flow rate of the internal circulating water and the effective heat exchange length of the heater. Based on the first temperature difference between the first outlet temperature at time t and the first inlet temperature at time tn, a first temperature difference sequence is constructed; where t is a positive integer and n is the theoretical lag time. Based on the first temperature difference values ​​within the first sliding window corresponding to the first temperature difference sequence at the current moment, the target waste heat fluctuation rate of the internal circulating water in the heater at the current moment is determined.

[0008] Furthermore, this application also proposes determining the target waste heat fluctuation rate of the internal circulating water in the heater at the current moment based on each first temperature difference value within the first sliding window corresponding to the first temperature difference sequence at the current moment, including: The average value of each temperature difference in the first temperature difference sequence within the first sliding window is obtained by averaging the temperature difference values. The absolute values ​​of the differences between each temperature difference value and the mean temperature difference in the first temperature difference sequence within the first sliding window are averaged to obtain the target waste heat fluctuation rate of the internal circulating water in the heater at the current moment.

[0009] Furthermore, this application also proposes determining the supply-demand mismatch of a power plant heating circulating water system based on the first inlet temperature, the first outlet temperature, the second inlet temperature, and the second outlet temperature, including: A first temperature difference sequence is constructed based on the first temperature difference between the first outlet temperature at time t and the first inlet temperature at time tn, and a second temperature difference sequence is constructed based on the second temperature difference between the second outlet temperature at time t and the second inlet temperature at time tn; where t is a positive integer and n is the theoretical lag time. The average exothermic temperature difference is determined based on the first temperature difference values ​​within the second sliding window corresponding to the first temperature difference sequence at the current time, and the average endothermic temperature difference is determined based on the second temperature difference values ​​within the second sliding window corresponding to the second temperature difference sequence at the current time. The supply-demand mismatch of the power plant's heating circulating water system is determined based on the average heat release temperature difference and the average heat absorption temperature difference.

[0010] Furthermore, this application also proposes determining the supply-demand matching deviation of a power plant's heating circulating water system based on the average heat release temperature difference and the average heat absorption temperature difference, including: The heat transfer ratio of the power plant's heating circulating water system is determined by dividing the average heat absorption temperature difference by the average heat release temperature difference. The flow rate of the internal circulating water in the second sliding window is divided by the second flow rate of the primary pipeline in the second sliding window to obtain the flow rate ratio of the power plant heating circulating water system. Based on the heat transfer ratio and flow ratio, the supply and demand matching deviation of the power plant's heating circulating water system is determined.

[0011] Furthermore, this application also proposes determining the supply-demand mismatch of a power plant's heating circulating water system based on heat transfer ratio and flow rate ratio, including: Multiply the heat transfer ratio by the reciprocal of the flow rate ratio to obtain the deviation evaluation value; The deviation evaluation values ​​are normalized to obtain the supply and demand matching deviation of the power plant heating circulating water system.

[0012] Furthermore, this application proposes determining the first adjustment weight of the power plant's heating circulating water system based on the target waste heat volatility and the supply-demand mismatch, including: Multiply the supply-demand matching deviation by the first adjustment coefficient to obtain the first weight value; The second weight value is obtained by multiplying the ratio of the target waste heat volatility to the maximum historical waste heat volatility by the second adjustment coefficient; the sum of the first adjustment coefficient and the second adjustment coefficient is one. The first weight value is added to the second weight value to obtain the first adjustment weight of the power plant heating circulating water system.

[0013] Furthermore, this application also proposes to dynamically adjust the heating temperature of the power plant's heating circulating water system based on a first adjustment weight, including: Based on the first adjustment weight, the corrected opening value of the regulating valve in the power plant heating circulating water system is determined; Based on the corrected opening value, the opening of the regulating valve in the power plant's heating circulating water system is dynamically adjusted.

[0014] Furthermore, this application also proposes determining the corrected opening value of the regulating valve in the power plant heating circulating water system based on a first adjustment weight, including: Map the first adjustment weight to the target interval to obtain the second adjustment weight; Based on the adjustment intensity coefficient, the second adjustment weight is corrected to obtain the third adjustment weight; Based on the third adjustment weight, the basic opening value of the regulating valve in the power plant heating circulating water system is corrected to obtain the corrected opening value of the regulating valve in the power plant heating circulating water system.

[0015] A second aspect of the present invention provides a power plant heating circulating water temperature control system, comprising: The temperature acquisition module is used to acquire the first inlet temperature and the first outlet temperature of the internal circulating water in the heater of the power plant heating circulating water system, as well as the second inlet temperature and the second outlet temperature of the primary pipeline in the heater. The volatility assessment module is used to determine the target waste heat volatility of the internal circulating water in the heater based on the first inlet temperature and the first outlet temperature; the target waste heat volatility is used to characterize the severity of the impact of power grid dispatch on heating supply. The deviation assessment module is used to determine the supply and demand matching deviation of the power plant heating circulating water system based on the first inlet temperature, the first outlet temperature, the second inlet temperature, and the second outlet temperature. The weighting evaluation module is used to determine the first adjustment weight of the power plant's heating circulating water system based on the target waste heat volatility and the supply-demand matching deviation. The system adjustment module is used to dynamically adjust the heating temperature of the power plant's heating circulating water system based on a first adjustment weight.

[0016] The present invention has the following beneficial effects: The power plant heating circulating water temperature control method provided in this invention first acquires temperature data of the internal circulating water and primary pipeline in the heater of the power plant heating circulating water system. Based on the inlet and outlet temperatures of the internal circulating water, a target waste heat fluctuation rate is determined to characterize the severity of the impact of grid dispatch on heating. Then, the supply-demand matching deviation is determined by combining the temperature data between the internal circulating water and the primary pipeline. Subsequently, a first adjustment weight is determined based on the target waste heat fluctuation rate and the supply-demand matching deviation. Finally, the heating temperature is dynamically adjusted based on this first adjustment weight. Thus, this method comprehensively considers waste heat fluctuations and supply-demand matching, enabling flexible adjustment of the heating temperature according to actual conditions. This avoids the unreasonable adjustment problems caused by fixed threshold allocation in existing methods, thereby improving the reliability of heating circulating water temperature control. Attached Figure Description

[0017] To more clearly illustrate the technical solutions and advantages in the embodiments of the present 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 only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic flowchart of a method for regulating the temperature of circulating water in a power plant heating system, provided in one embodiment of the present invention. Figure 2 This is a schematic diagram of heat exchange inside a heater according to an embodiment of the present invention; Figure 3This is a schematic diagram of a power plant heating circulating water temperature control system according to an embodiment of the present invention. Detailed Implementation

[0019] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a power plant heating circulating water temperature control method and system proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0021] In traditional power plant heating circulating water systems, waste heat from power plants fluctuates dramatically on a second- or minute-by-minute basis due to grid dispatch commands, while user heat load exhibits hourly inertial changes influenced by meteorological and behavioral factors. This makes it difficult to accurately match waste heat with user heat load demand on a time scale. Existing technologies employ static allocation strategies with fixed threshold allocation ratios, which cannot dynamically adapt to the time-varying characteristics of both the heat source and the heat load. This results in lowering heating temperatures to ensure power generation during sudden drops in waste heat, or wasting heat due to adjustment lags when waste heat is redundant, thus affecting power generation efficiency and heating efficiency, and reducing the reliability of heating circulating water temperature control. In particular, this static allocation strategy allocates waste heat based on preset thresholds with rigid boundaries, failing to characterize the severity of grid dispatch impacts on heating supply, and also failing to quantify supply-demand mismatches, resulting in insufficient dynamic response capability of the system.

[0022] If the above problems are not resolved, the heating circulating water system of the power plant will frequently experience unstable heating temperatures, resulting in reduced thermal comfort for users. At the same time, the power generation side will exacerbate heating fluctuations due to prioritizing power generation. Over the long term, the system's reliability will continue to deteriorate, affecting the overall efficiency of combined heat and power.

[0023] Based on this, this application provides a specific embodiment of a method and system for regulating the temperature of circulating water in a power plant heating system. For example... Figure 1 As shown, this application provides a flowchart of a method for controlling the temperature of circulating water in a power plant's heating system. This method can be applied to electronic equipment and includes the following steps S110 to S150: S110, obtain the first inlet temperature and the first outlet temperature of the internal circulating water in the heater of the power plant heating circulating water system, and the second inlet temperature and the second outlet temperature of the primary pipeline in the heater. S120, based on the first inlet temperature and the first outlet temperature, determine the target waste heat fluctuation rate of the internal circulating water in the heater; the target waste heat fluctuation rate is used to characterize the severity of the impact of power grid dispatch on heating supply. S130, based on the first inlet temperature, the first outlet temperature, the second inlet temperature, and the second outlet temperature, determine the supply and demand matching deviation of the power plant heating circulating water system; S140, based on the target waste heat volatility and supply-demand matching deviation, determine the first adjustment weight of the power plant heating circulating water system; S150 dynamically adjusts the heating temperature of the power plant's heating circulating water system based on the first adjustment weight.

[0024] For ease of understanding, the following explains some key terms in this embodiment: A power plant heating circulating water system refers to a system in which a power plant uses waste heat generated during power generation to provide heat energy to external users through a circulating water medium. This system typically includes heaters, circulating water pumps, piping networks, and various sensors and control equipment. Its purpose is to achieve effective recovery and utilization of waste heat while meeting the heating needs of users.

[0025] The heater is the core equipment in the power plant's heating circulating water system. Its function is to transfer the waste heat generated by the power plant to the low-temperature heating circulating water in the primary pipeline network, thereby raising the temperature of the low-temperature heating circulating water in the primary pipeline network so that it can carry heat to the user end.

[0026] Internal circulating water refers to the process where some of the steam that has already done work in the turbine is introduced into the heater. The latent heat of vaporization released by the condensation of the steam transfers waste heat to the low-temperature heating circulating water in the primary pipeline, transforming it into high-temperature heating circulating water. The steam, after heat exchange, condenses into liquid water and is recycled to the boiler feedwater system for reuse in the power generation cycle. This water flow transfers heat to the low-temperature heating circulating water in the primary pipeline within the heater, releases heat, and then returns to the turbine, forming a closed loop.

[0027] The primary pipeline network refers to the pipeline system that exchanges heat with the waste heat medium in the heater. Typically, the low-temperature heating circulating water in the primary pipeline network is pumped into the heater to exchange heat with the internal circulating water, and then transported by the circulating pump to each heat exchange station for heating.

[0028] The first inlet temperature and the first outlet temperature refer to the temperatures of the internal circulating water when it enters the heater and when it leaves the heater, respectively. These two temperature values ​​reflect the ability and effectiveness of the internal circulating water in releasing heat within the heater.

[0029] The second inlet temperature and the second outlet temperature refer to the temperatures of the low-temperature heating circulating water medium in the primary pipeline network when it enters the heater and when it leaves the heater, respectively. These two temperature values ​​reflect the capacity and effectiveness of the primary pipeline network in absorbing heat in the heater.

[0030] The target waste heat volatility is an indicator used to characterize the severity of the impact of grid dispatch on heating supply. Changes in grid dispatch instructions may lead to rapid adjustments in power plant generation load, which in turn affects the amount and temperature of waste heat generated. This volatility quantifies the intensity and frequency of such impacts.

[0031] Supply-demand mismatch is an indicator used to characterize the difference between the heating capacity of a power plant's heating circulating water system and the heat load demand of users. When heating capacity and demand do not match, insufficient heating or heat waste may occur.

[0032] The first adjustment weight is a parameter determined based on the target waste heat fluctuation rate and the supply-demand mismatch, used to guide the dynamic adjustment of the heating temperature in the power plant's heating circulating water system. This weight reflects how the system should balance waste heat fluctuations with the supply-demand matching requirements under current operating conditions.

[0033] Heating temperature refers to the temperature of the high-temperature circulating water supplied by the power plant's heating system to users. This temperature is a key parameter affecting the heating effect on users and needs to be precisely controlled according to actual conditions.

[0034] Dynamic regulation refers to the continuous and real-time adjustment of the heating temperature of the power plant's heating circulating water system based on real-time changes in operating parameters and system status, in order to adapt to changes in power grid dispatch and user heat load, and to achieve optimized operation of the heating system.

[0035] like Figure 2 The diagram illustrates heat exchange within a heater. Internal circulating water enters the heater from the left at a first inlet temperature W_G,in, releases heat, and exits at a first outlet temperature W_G,out. Simultaneously, low-temperature heating circulating water from the primary network enters the heater from the right at a second inlet temperature W_H,in, absorbs heat, and exits at a second outlet temperature W_H,out. This diagram demonstrates the process of heat exchange between the internal circulating water and the low-temperature heating circulating water from the primary network within the heater through opposite flow directions, clearly illustrating the mechanism by which heat is transferred from the internal circulating water to the low-temperature heating circulating water from the primary network.

[0036] This embodiment provides a method for regulating the temperature of circulating water in a power plant's heating system, and its main technical features include the following aspects: First, the first inlet and first outlet temperatures of the circulating water inside the heater of the power plant's heating circulating water system, as well as the second inlet and second outlet temperatures of the primary piping network within the heater, are obtained. This temperature data forms the basis for subsequent analysis and control. For example, these temperature values ​​can be obtained by installing temperature sensors at the heater inlet and outlet and periodically reading the sensor data.

[0037] Secondly, based on the first inlet temperature and the first outlet temperature, a target waste heat fluctuation rate for the internal circulating water in the heater is determined. This target waste heat fluctuation rate is used to characterize the severity of the impact of grid dispatch on heating supply. For example, the difference between the first inlet temperature and the first outlet temperature of the internal circulating water at the current moment can be simply calculated, and a preliminary indication of waste heat fluctuation can be determined based on this difference. Alternatively, the average value of the difference between the first inlet temperature and the first outlet temperature over a fixed time period can be calculated to reflect the average fluctuation of waste heat.

[0038] Next, based on the first inlet temperature, the first outlet temperature, the second inlet temperature, and the second outlet temperature, the supply and demand matching deviation of the power plant's heating circulating water system is determined. For example, the temperature drop of the internal circulating water in the heater (first outlet temperature minus first inlet temperature) and the temperature rise of the primary pipeline medium in the heater (second inlet temperature minus second outlet temperature) can be calculated, and then the supply and demand matching status can be preliminarily judged by comparing the ratio of these two temperature differences.

[0039] Furthermore, based on the target waste heat fluctuation rate and the supply-demand mismatch, a first adjustment weight is determined for the power plant's heating circulating water system. This first adjustment weight is a key parameter guiding the dynamic adjustment of the heating temperature. For example, a simple lookup table can be pre-set to directly find the corresponding first adjustment weight based on the values ​​of the target waste heat fluctuation rate and the supply-demand mismatch.

[0040] Finally, based on this first adjustment weight, the heating temperature of the power plant's heating circulating water system is dynamically adjusted. For example, the first adjustment weight can be directly applied to the current heating temperature setpoint, and the heating temperature can be adjusted through simple addition and subtraction operations. Alternatively, based on the magnitude of the first adjustment weight, a suitable level can be selected from several preset heating temperature levels for switching, thereby achieving heating temperature regulation.

[0041] The following example will provide a more detailed explanation of the above technical solution: Suppose that during a cold winter, a power plant is providing heating services to urban area A. The power plant's heating circulating water system needs to maintain a stable heating temperature to meet the heating needs of users in area A. However, due to a sudden change in grid dispatch instructions, the power plant's generating load is required to be reduced in a short period of time. This directly leads to a sharp decrease in waste heat production, thus impacting the temperature stability of the heating circulating water system.

[0042] In this scenario, the control method of this embodiment first uses sensors installed on the heater to acquire the first inlet and first outlet temperatures of the internal circulating water, as well as the second inlet and second outlet temperatures of the primary piping network in real time. For example, at a certain time T, the system monitors that the first inlet temperature of the internal circulating water is 120 degrees Celsius and the first outlet temperature is 90 degrees Celsius; the second inlet temperature of the primary piping network is 60 degrees Celsius and the second outlet temperature is 85 degrees Celsius. These data are continuously collected and recorded.

[0043] Next, the system determines the target waste heat fluctuation rate of the internal circulating water in the heater based on the first inlet temperature and the first outlet temperature. For example, by calculating the variation range of the difference between the first inlet temperature and the first outlet temperature over a past period, the system assesses that the current waste heat fluctuation rate is high, indicating that the impact of grid dispatch on heating supply is relatively severe. This fluctuation rate calculation reflects the dynamic characteristics of the waste heat supply side.

[0044] Simultaneously, based on the first inlet temperature, first outlet temperature, second inlet temperature, and second outlet temperature, the system determines the supply-demand mismatch of the power plant's heating circulating water system. For example, by comparing the actual temperature drop of the internal circulating water in the heater with the temperature rise of the primary network medium, and combining this with historical operating data, the system finds that the current temperature rise of the primary network is lower than expected, while the temperature drop of the internal circulating water is correspondingly reduced. This indicates that there is a certain negative deviation between the waste heat supply capacity and the user's heat load demand, meaning that the heating capacity may not be sufficient to fully meet the demand.

[0045] Subsequently, the system uses the aforementioned target waste heat volatility and supply-demand mismatch as input to comprehensively calculate the first adjustment weight of the power plant's heating circulating water system. For example, when the waste heat volatility is high and the supply-demand mismatch indicates insufficient heating, the system will assign a larger first adjustment weight to indicate the need for more aggressive temperature regulation. The determination of this first adjustment weight reflects a comprehensive consideration of the volatility of waste heat supply and the matching degree of user demand.

[0046] Finally, based on this first adjustment weight, the system dynamically adjusts the heating temperature of the power plant's circulating water system. For example, if the calculated first adjustment weight indicates a need to increase the heating temperature, the system sends a command to the regulating valve to increase its opening, thereby increasing the internal circulating water flow through the heater or improving the heater's heat exchange efficiency, ultimately achieving an increase in the heating temperature. Through this dynamic adjustment, the system can respond promptly to waste heat fluctuations caused by grid dispatch and flexibly adjust the heating temperature according to the actual supply and demand matching, avoiding sacrifices in heating quality due to sudden drops in waste heat or heat waste due to adjustment lags. This process ensures that the heating system can maintain high reliability and operating efficiency even in complex and variable environments.

[0047] Based on the above examples, the technical solution of this embodiment demonstrates significant technical contributions. Existing methods for regulating the temperature of circulating water in power plant heating systems typically employ fixed thresholds or static allocation strategies to balance power generation and heating demands. For example, when waste heat supply changes, existing methods may only adjust based on a preset fixed ratio, which can easily lead to lag or inaccuracy in regulation when waste heat fluctuates drastically or when supply and demand are mismatched.

[0048] In contrast, the method in this embodiment introduces two dynamic indicators—target waste heat fluctuation rate and supply-demand matching deviation—and determines a first adjustment weight based on these indicators, achieving refined and dynamic adjustment of heating temperature. In the example above, when grid dispatch causes a sudden drop in waste heat, this method not only detects the waste heat fluctuation but also simultaneously assesses the actual deviation in supply-demand matching. Therefore, the system can generate a comprehensive adjustment weight that simultaneously reflects the drastic changes on the waste heat supply side and the actual matching situation on the user demand side.

[0049] This weighting mechanism based on dual dynamic indicators allows for real-time and flexible adjustment of heating temperature, moving beyond simple static allocation to adapt to real-time and flexible changes in grid dispatch impacts and user heat load. For example, when a sudden drop in waste heat leads to insufficient heating capacity, this method can promptly and accurately increase the heating temperature, avoiding the situation in existing technologies where heating temperature is sacrificed to maintain power generation efficiency. Furthermore, when waste heat is redundant, this method also avoids heat waste caused by adjustment lag. Therefore, the technical solution in this embodiment effectively improves the reliability of power plant heating circulating water temperature control, optimizes power generation efficiency and heating efficiency, and solves the technical problems of inaccurate supply-demand matching and poor adjustment reliability in existing technologies.

[0050] This embodiment first acquires temperature data of the internal circulating water and primary pipeline in the heater of the power plant's heating circulating water system. Based on the inlet and outlet temperatures of the internal circulating water, a target waste heat fluctuation rate is determined to characterize the severity of the impact of grid dispatch on heating. Then, the supply-demand matching deviation is determined by combining the temperature data between the internal circulating water and the primary pipeline. Subsequently, a first adjustment weight is determined based on the target waste heat fluctuation rate and the supply-demand matching deviation. Finally, the heating temperature is dynamically adjusted based on this first adjustment weight. Thus, this method comprehensively considers waste heat fluctuations and supply-demand matching, enabling flexible adjustment of the heating temperature according to actual conditions. This avoids the unreasonable adjustment problems caused by fixed threshold allocation in existing methods, thereby improving the reliability of circulating water temperature control.

[0051] In some of the embodiments described above in this application, when determining the target waste heat fluctuation rate of the internal circulating water in the heater based on the first inlet temperature and the first outlet temperature, if only the instantaneous temperature difference is relied upon, it may not be possible to accurately capture the physical characteristics of heat transfer in the fluid, resulting in an inaccurate assessment of the waste heat fluctuation rate, which in turn affects the effectiveness of subsequent heating temperature regulation.

[0052] In this regard, this application further proposes that S120 includes: The theoretical lag time of the internal circulating water is determined based on the flow rate of the internal circulating water and the effective heat exchange length of the heater. Based on the first temperature difference between the first outlet temperature at time t and the first inlet temperature at time tn, a first temperature difference sequence is constructed; where t is a positive integer and n is the theoretical lag time. Based on the first temperature difference values ​​within the first sliding window corresponding to the first temperature difference sequence at the current moment, the target waste heat fluctuation rate of the internal circulating water in the heater at the current moment is determined.

[0053] In this embodiment, the external user heat load is affected by meteorological conditions (air temperature, wind speed) and user heating behavior (start time, set temperature), exhibiting hourly inertial changes; while the available waste heat on the heating side is affected by grid dispatch instructions, exhibiting drastic fluctuations on the order of seconds / minutes. Given this time scale difference, simply relying on the heater outlet temperature cannot determine the matching degree between the current heating supply and the user's actual heating demand. For example, when the user heat load decreases, if the circulating pump continues to operate at high speed, it will lead to increased power consumption of the circulating pump, but the actual heat exchange efficiency will not improve, and may even cause hydraulic imbalance in the pipe network, i.e., some areas are overheated and some areas are undercooled. When there is waste heat redundancy, if the adjustment is not timely, it will lead to heat waste.

[0054] Therefore, dynamic analysis of the adjustment of heating circulating water for power plant waste heat requires consideration of the stability and efficiency of heating during the heat exchange process. By constructing the supply-demand matching deviation through the temperature change relationship between the heating side and the user side at adjacent moments within the effective temperature difference sequence, the nonlinear coupling relationship between the heating side's temperature rise capacity and the user side's temperature drop feedback can be demonstrated. This allows for the determination of the matching degree between the heat supply and actual heat consumption during the heat exchange process, providing a basis for the calculation of the first adjustment weight.

[0055] The internal circulating water velocity refers to the speed at which the internal circulating water flows within the pipes or heat exchangers of the heater in a power plant's heating circulating water system. It can be directly measured by a flow meter installed on the circulating water pipeline. The effective heat exchange length of the heater refers to the length of the actual heat exchange zone within the heater. This is typically determined based on the heater's design parameters or through experimental calibration. The theoretical lag time refers to the time required for the internal circulating water to travel from the heater's first inlet through the effective heat exchange length to the first outlet. This theoretical lag time is a function of the internal circulating water velocity and the heater's effective heat exchange length, reflecting the inherent delay in the heat transfer process.

[0056] The first temperature difference value refers to the difference between the first outlet temperature of the internal circulating water at a specific time t and the first inlet temperature before the theoretical lag time n (i.e., time tn). This difference value can more accurately reflect the actual heat loss of the internal circulating water in the heater after considering the fluid lag effect. The first temperature difference sequence is a series of multiple first temperature difference values ​​collected continuously or periodically, arranged in chronological order. This sequence records the dynamic history of heat changes of the internal circulating water in the heater. The first sliding window refers to a fixed-length time interval defined on the first temperature difference sequence. This window slides forward over time to capture data points from the most recent period in the sequence for local statistical analysis, thereby reflecting the dynamic characteristics at the current moment. It should be noted that the time length corresponding to the first sliding window can be 50 time intervals. The first sliding window is mainly used to capture the dynamic changes of waste heat fluctuations. Setting a relatively short time length can ensure the real-time nature of the fluctuation characteristics to a certain extent. It should be understood that implementers can set it according to the actual situation in other specific implementation scenarios. The target waste heat fluctuation rate is used to characterize the severity of the impact of grid dispatch on heating supply. In this embodiment, it is calculated based on the first temperature difference value within the first sliding window, which can quantify the intensity and frequency of heat changes in the internal circulating water in the heater.

[0057] In the process of temperature control of circulating water in power plant heating systems, in order to accurately assess the severity of the impact of grid dispatch on heating, it is necessary to precisely determine the target waste heat fluctuation rate of the internal circulating water in the heater. The proposed solution first calculates the theoretical lag time of the internal circulating water in the heater by obtaining the flow velocity of the internal circulating water and the effective heat exchange length of the heater. Specifically, the theoretical lag time of the internal circulating water in the heater can be obtained by directly dividing the effective heat exchange length by the flow velocity of the internal circulating water. This step is crucial because it considers the physical delay of heat transfer in the fluid, ensuring that subsequent temperature difference calculations reflect the actual temperature difference of the same batch of water entering and leaving the heater. Next, based on the first outlet temperature at the current moment and the first inlet temperature before the theoretical lag time (i.e., time tn), a first temperature difference sequence is constructed. This method of constructing difference values ​​avoids errors that may be caused by instantaneous temperature differences and more accurately captures the actual heat exchange situation of the internal circulating water in the heater. Subsequently, by setting a first sliding window on the first temperature difference sequence, statistical analysis is performed on each first temperature difference value within the window to determine the target waste heat fluctuation rate at the current moment. This sliding window-based analysis method can reflect the trend and intensity of waste heat fluctuations in real time and dynamically, effectively filtering out short-term noise and making the assessment of the target waste heat fluctuation rate more stable and reliable. Through the above steps, this solution can provide a more accurate and real-time target waste heat fluctuation rate, providing a reliable basis for subsequent dynamic adjustment of heating temperature, thereby effectively coping with the heating shock caused by power grid dispatch.

[0058] The above technical solution fully considers the physical lag effect of heat transfer in the heater of the power plant's heating circulating water system when determining the target waste heat fluctuation rate of the internal circulating water. The theoretical lag time is determined by introducing the flow rate of the internal circulating water and the effective heat exchange length of the heater, and a first temperature difference sequence is constructed based on this. This allows the calculated temperature difference value to more accurately reflect the actual temperature rise or fall of the same batch of water in the heater. Furthermore, dynamic analysis of the first temperature difference sequence using a first sliding window effectively captures the real-time nature and intensity of waste heat fluctuations, avoiding the impact of instantaneous measurement errors on the fluctuation rate assessment. This makes the assessment of the target waste heat fluctuation rate more accurate and stable, providing a more reliable basis for the dynamic adjustment of the heating temperature of the power plant's heating circulating water system. This helps the system more effectively cope with the heating impact brought by grid dispatch, improving the stability and response speed of the heating system.

[0059] In some embodiments described above in this application, a method is proposed to determine the target waste heat fluctuation rate of the internal circulating water in the heater at the current moment based on the first temperature difference values ​​within a first sliding window corresponding to the first temperature difference sequence at the current moment. However, simply processing these temperature difference values ​​may not accurately capture the severity of the impact of grid dispatch on heating, especially when the data contains noise or irregular fluctuations, making it difficult to effectively quantify its fluctuation characteristics.

[0060] In this regard, this application further proposes to determine the target waste heat fluctuation rate of the internal circulating water in the heater at the current moment based on the first temperature difference values ​​within the first sliding window corresponding to the first temperature difference sequence at the current moment, including: The average value of each temperature difference in the first temperature difference sequence within the first sliding window is obtained by averaging the temperature difference values. The absolute values ​​of the differences between each temperature difference value and the mean temperature difference in the first temperature difference sequence within the first sliding window are averaged to obtain the target waste heat fluctuation rate of the internal circulating water in the heater at the current moment.

[0061] In this embodiment, the first temperature difference values ​​within the first sliding window of the first temperature difference sequence are averaged to obtain the average temperature difference. This averaging process is a statistical method used to calculate the central tendency of a set of values. Its purpose is to eliminate random noise, smooth the data, and provide a typical value representing the data set. When determining the average temperature difference, methods such as arithmetic mean can be used. For example, the arithmetic mean can be obtained by simply summing all the first temperature difference values ​​within the first sliding window and then dividing by the number of values.

[0062] The absolute values ​​of the differences between each first temperature difference value and the mean temperature difference within the first sliding window of the first temperature difference sequence are averaged to obtain the target waste heat fluctuation rate of the internal circulating water in the heater at the current moment. This step aims to quantify the degree of deviation of the temperature difference value from its average level, i.e., the volatility. By calculating the difference between each first temperature difference value and the obtained mean temperature difference, a series of values ​​reflecting the degree of deviation can be obtained. Subsequently, averaging these differences yields a comprehensive volatility index.

[0063] The proposed solution employs a two-stage averaging process on the first temperature difference values ​​within a first sliding window to accurately quantify the target waste heat fluctuation rate of the internal circulating water in the heater. First, all first temperature difference values ​​within the first sliding window are averaged to obtain a benchmark value representing the temperature difference within that time window, i.e., the average temperature difference. This benchmark value effectively smooths out instantaneous noise and provides an average state of waste heat transfer during that time period. Second, to capture the volatility of waste heat transfer, this application further calculates the deviation of each first temperature difference value from the average temperature difference and averages these deviations again. This method effectively filters out the influence of unidirectional deviations, focusing instead on quantifying the magnitude of temperature difference value fluctuations around its average level, thereby accurately characterizing the severity of the impact of grid dispatch on heating supply.

[0064] As an example, the target waste heat fluctuation rate can be determined using the following formula 1: Formula 1 In formula 1, The variable N is used to characterize the target waste heat fluctuation rate at time t, and N is used to characterize the length of the first sliding window. This is used to characterize the first temperature difference value at the i-th time within the first sliding window. Used to characterize the average temperature difference within the first sliding window.

[0065] in, It is the average of the absolute values ​​of the differences between the first temperature difference value and the mean temperature difference value within the first sliding window. It is used to reflect the severity of waste heat fluctuations. The larger the value, the greater the impact of power grid dispatch on heating, and the greater the possibility of needing to adjust the heat exchange ratio.

[0066] Through the above technical solution, this application effectively overcomes the problem that a single data point or simple average value cannot accurately reflect the severity of waste heat fluctuations by performing two-stage averaging processing on the first temperature difference value within the first sliding window. First, the average temperature difference is calculated, providing a stable benchmark for fluctuation analysis. Then, the average difference between each temperature difference value and this average temperature difference is calculated, which accurately quantifies the average deviation of waste heat transfer, thus more accurately and robustly characterizing the severity of the impact of grid dispatch on heating supply. This processing method effectively filters out random noise and transient interference, making the determined target waste heat fluctuation rate more stable and reliable, providing a more precise input for the subsequent dynamic adjustment of the power plant's heating circulating water system, thereby improving the response speed and stability of the heating system.

[0067] In some embodiments described above in this application, the supply-demand matching deviation of a power plant heating circulating water system is determined based on a first inlet temperature, a first outlet temperature, a second inlet temperature, and a second outlet temperature. However, in actual operation, due to the lag in heat transfer within the circulating water system, directly calculating the supply-demand matching deviation based on instantaneous temperature data may not accurately reflect the true thermodynamic balance of the system, leading to inaccurate deviation assessment and consequently affecting the timeliness and effectiveness of heating temperature regulation.

[0068] In this regard, this application further proposes that S130 includes: A first temperature difference sequence is constructed based on the first temperature difference between the first outlet temperature at time t and the first inlet temperature at time tn, and a second temperature difference sequence is constructed based on the second temperature difference between the second outlet temperature at time t and the second inlet temperature at time tn; where t is a positive integer and n is the theoretical lag time. The average exothermic temperature difference is determined based on the first temperature difference values ​​within the second sliding window corresponding to the first temperature difference sequence at the current time, and the average endothermic temperature difference is determined based on the second temperature difference values ​​within the second sliding window corresponding to the second temperature difference sequence at the current time. The supply-demand mismatch of the power plant's heating circulating water system is determined based on the average heat release temperature difference and the average heat absorption temperature difference.

[0069] In this embodiment, constructing a first temperature difference sequence and a second temperature difference sequence aims to more accurately capture temperature changes during heat exchange by considering the heat transfer lag of the internal circulating water and primary piping network. The first temperature difference value represents the difference between the outlet temperature of the internal circulating water after passing through the heater and its inlet temperature before the theoretical lag time, reflecting the actual heat release capacity of the internal circulating water in the heater. Similarly, the second temperature difference value represents the difference between the outlet temperature of the primary piping network after passing through the heater and its inlet temperature before the theoretical lag time, reflecting the actual heat absorption capacity of the primary piping network in the heater. By constructing these sequences, the impact of system lag on instantaneous temperature data evaluation can be effectively eliminated or reduced, providing a more representative data basis for subsequent supply and demand matching deviation calculations.

[0070] The purpose of determining the average exothermic and average endothermic temperature differences is to obtain more stable and representative heat exchange temperature difference indices by statistically processing temperature difference values ​​over a period of time. The average exothermic temperature difference is obtained by processing the values ​​within a second sliding window of a first temperature difference sequence; it represents the average heat release level of the internal circulating water over a recent period. The average endothermic temperature difference is obtained by processing the values ​​within a second sliding window of a second temperature difference sequence; it represents the average heat absorption level of the primary piping network over a recent period. By introducing a second sliding window and performing averaging, the influence of instantaneous noise and short-term fluctuations on the temperature difference assessment can be effectively filtered out, making the determined temperature difference values ​​more robust and better reflecting the thermodynamic characteristics of the system over a certain time scale.

[0071] It should be noted that the second sliding window refers to a time window consisting of a period of time preceding the current moment. The length of the time window can be 300 moments. The second sliding window is mainly used to calculate the average level of data in two different sequences. Setting a relatively long time window makes it easier to capture the average level of the data. It should be understood that in other specific implementation scenarios, implementers can set it according to the actual situation.

[0072] Determining the supply-demand matching deviation based on the average exothermic and endothermic temperature differences aims to comprehensively analyze the processed and averaged exothermic and endothermic temperature differences, thereby quantifying the degree of matching between the heating capacity and actual demand of the power plant's heating circulating water system. The supply-demand matching deviation is a key indicator for measuring system operating efficiency and stability, directly reflecting whether there is over- or under-supply of heat. By reasonably combining the average exothermic and endothermic temperature differences, a mathematical model or index that accurately characterizes the system's thermal balance can be constructed. For example, intelligent algorithms such as fuzzy logic and neural networks can be used to train the model based on historical data, using the average exothermic and endothermic temperature differences as inputs to output the supply-demand matching deviation.

[0073] This application's solution addresses the lag and instability issues inherent in traditional instantaneous temperature data when assessing supply-demand mismatch by introducing time lag and sliding window averaging mechanisms. First, a first temperature difference sequence is constructed based on the first temperature difference between the first outlet temperature at time t and the first inlet temperature at time tn. A second temperature difference sequence is then constructed based on the second temperature difference between the second outlet temperature at time t and the second inlet temperature at time tn. This effectively compensates for the inherent lag effect of the circulating water and primary piping within the heater during heat transfer. This approach ensures that the calculated temperature difference values ​​accurately reflect the state changes of the same batch of water or heat before and after passing through the heater, thus providing more accurate raw data for subsequent deviation assessment.

[0074] Based on this, the average exothermic temperature difference is determined by the first temperature difference values ​​within the second sliding window corresponding to the current time, and the average endothermic temperature difference is determined by the second temperature difference values ​​within the second sliding window corresponding to the current time, further enhancing the robustness of the deviation assessment. The sliding window averaging process effectively filters out instantaneous measurement noise and short-term fluctuations, making the obtained average exothermic and average endothermic temperature differences more stable and representative, reflecting the system's average heat exchange performance over a certain period. Finally, based on the average exothermic and average endothermic temperature differences, the supply-demand matching deviation of the power plant's heating circulating water system is determined. This method integrates key thermodynamic parameters after time lag compensation and noise smoothing, thereby accurately and dynamically quantifying the degree of matching between the power plant's heating circulating water system's heating capacity and actual demand.

[0075] Through the above technical solution, this application overcomes the inaccuracy caused by system lag and instantaneous fluctuations in traditional methods when assessing the supply-demand matching deviation of power plant heating circulating water systems. By introducing a theoretical lag time *n* to construct a temperature difference sequence, it ensures that the temperature comparison before and after heat transfer is performed on the same batch of water, thus enabling the first and second temperature difference values ​​to more accurately reflect the actual heat release and absorption inside the heater. Furthermore, by averaging these temperature difference values ​​within a second sliding window, measurement noise and short-term fluctuations are effectively filtered out, making the obtained average heat release temperature difference and average heat absorption temperature difference more stable and representative.

[0076] In some embodiments described above in this application, the supply-demand matching deviation of a power plant heating circulating water system is determined based on a first inlet temperature, a first outlet temperature, a second inlet temperature, and a second outlet temperature. However, in actual operation, relying solely on the average heat release temperature difference and the average heat absorption temperature difference to assess the supply-demand matching deviation may not fully reflect the actual heat transfer efficiency and fluid exchange status between the internal circulating water in the heater and the primary piping network. This results in an inaccurate judgment of the system's thermal balance state, affecting the accuracy and timeliness of subsequent heating temperature adjustments.

[0077] In this regard, this application further proposes to determine the supply-demand matching deviation of the power plant's heating circulating water system based on the average heat release temperature difference and the average heat absorption temperature difference, including: The heat transfer ratio of the power plant's heating circulating water system is determined by dividing the average heat absorption temperature difference by the average heat release temperature difference. The flow rate of the internal circulating water in the second sliding window is divided by the second flow rate of the primary pipeline in the second sliding window to obtain the flow rate ratio of the power plant heating circulating water system. Based on the heat transfer ratio and flow ratio, the supply and demand matching deviation of the power plant's heating circulating water system is determined.

[0078] In this embodiment, the heat transfer ratio is a key indicator for measuring the heat exchange efficiency in the heater. It is obtained by comparing the average heat absorption temperature difference on the primary pipe network side with the average heat release temperature difference on the internal circulating water side, and intuitively reflects the effectiveness of heat transfer from the high-temperature side to the low-temperature side.

[0079] The flow ratio characterizes the relative relationship between the mass or volumetric flow of fluid between the internal circulating water in the heater and the primary piping network. It is determined by comparing the first flow rate of the internal circulating water with the second flow rate of the primary piping network, directly affecting the heat transfer capacity and the dynamic response of heat exchange. The first and second flow rates can be obtained through real-time measurement using high-precision flow meters installed on the corresponding pipelines. Alternatively, in some cases, they can be estimated based on pump operating parameters, valve openings, and pipeline characteristics, combined with principles of fluid dynamics.

[0080] The determination of supply-demand mismatch no longer relies solely on temperature differences, but comprehensively considers both heat transfer efficiency and fluid transport capacity. This comprehensive assessment can more accurately depict the actual thermal balance state within the heating system. In practice, a mathematical model can be constructed, using the heat transfer ratio and flow rate ratio as input variables, to calculate the supply-demand mismatch through a pre-defined functional relationship. Alternatively, advanced data analysis techniques, such as machine learning algorithms, can be utilized to learn from historical operating data and establish a model capable of intelligently predicting supply-demand mismatch based on the heat transfer ratio and flow rate ratio.

[0081] This application proposes a more refined assessment of the supply-demand mismatch in power plant heating circulating water systems by introducing heat transfer ratio and flow rate ratio. Specifically, firstly, the heat transfer efficiency within the heater, i.e., the heat transfer ratio, is quantified by dividing the average heat absorption temperature difference by the average heat release temperature difference. Secondly, the flow rate ratio is obtained by dividing the first flow rate of the internal circulating water by the second flow rate of the primary pipeline. Finally, these two key ratios—the heat transfer ratio and the flow rate ratio—are used as comprehensive consideration factors to determine the supply-demand mismatch in the power plant heating circulating water system. This method goes beyond simple temperature difference assessment, organically combining thermodynamic efficiency and fluid dynamics characteristics, resulting in a more comprehensive and accurate judgment of the system's thermal balance. In this way, the system can more accurately identify the actual degree of mismatch between heating supply and demand, providing a more reliable basis for subsequent dynamic adjustment of the heating temperature.

[0082] The above technical solution, when determining the supply-demand matching deviation of the power plant's heating circulating water system, not only considers the average heat release temperature difference and the average heat absorption temperature difference, but also further introduces the heat transfer ratio and flow ratio. This comprehensive evaluation method makes the judgment of the system's thermal balance state more accurate and comprehensive. The introduction of the heat transfer ratio can effectively reflect the actual heat exchange efficiency inside the heater, avoiding misjudgments that may be caused by relying solely on temperature differences; while the consideration of the flow ratio ensures an accurate assessment of the heat carrier's transport capacity, compensating for the shortcomings of temperature indicators alone. Therefore, the determined supply-demand matching deviation can more realistically reflect the actual degree of matching between heating supply and demand, providing a more reliable and refined basis for subsequent dynamic adjustment of the heating temperature based on the first adjustment weight.

[0083] In some of the embodiments described above in this application, it is proposed to evaluate the supply and demand matching deviation of the power plant heating circulating water system by calculating the heat transfer ratio and flow ratio. However, in actual implementation, simply judging the degree of supply and demand matching based on these two ratios may not be intuitive or accurate enough, especially when the system operating state is complex and changeable. It is difficult to directly reflect the actual degree of supply and demand imbalance of the heating system, thereby affecting the accuracy and response speed of subsequent temperature control.

[0084] In this regard, this application further proposes to determine the supply-demand matching deviation of the power plant heating circulating water system based on the heat transfer ratio and flow ratio, including: Multiply the heat transfer ratio by the reciprocal of the flow rate ratio to obtain the deviation evaluation value; The deviation evaluation values ​​are normalized to obtain the supply and demand matching deviation of the power plant heating circulating water system.

[0085] In this embodiment, the deviation evaluation value is an intermediate indicator used to quantify the supply-demand matching degree of the power plant's heating circulating water system. It integrates heat transfer efficiency and flow distribution into a single value, comprehensively reflecting the system's operating status. This evaluation value can be obtained by multiplying the heat transfer ratio by the reciprocal of the flow ratio. Normalization is a data preprocessing technique designed to transform data with different dimensions or numerical ranges into a unified, pre-defined interval. Its function is to eliminate the influence of data dimensions, making different indicators comparable and preventing certain indicators with large numerical ranges from dominating subsequent calculations. Normalization can employ nonlinear normalization methods such as the Sigmoid function and the Tanh function to map the deviation evaluation value to a specific interval to adapt to the input data range requirements of subsequent algorithms.

[0086] The proposed solution obtains the heat transfer ratio by dividing the average heat absorption temperature difference by the average heat release temperature difference, which reflects the efficiency of heat exchange. Simultaneously, it obtains the flow rate ratio by dividing the first flow rate of the internal circulating water within the second sliding window by the second flow rate of the primary pipeline within the second sliding window, which reflects the distribution of the heating medium. To integrate these two key indicators into a single quantitative value that comprehensively reflects the degree of supply-demand imbalance, this application further proposes multiplying the heat transfer ratio by the reciprocal of the flow rate ratio to obtain a deviation evaluation value. After obtaining the deviation evaluation value, to ensure its stable and comparable significance in subsequent weight determination and system adjustment, this application performs normalization. Through normalization, the deviation evaluation value can be mapped to a preset, unified numerical range. This not only eliminates the potential problems of dimensional differences and excessively large numerical ranges in the original evaluation values, making the deviation evaluation values ​​at different time points or under different operating conditions comparable, but also provides a standardized input for the subsequent calculation of the first adjustment weight based on the deviation evaluation value, thereby avoiding the problems of calculation deviation or insensitive adjustment caused by excessively large differences in numerical ranges.

[0087] As an example, the supply-demand mismatch in a power plant's heating circulating water system can be determined using the following formula 2: Formula 2 In formula 2, Used to characterize the supply-demand mismatch in the power plant's heating circulating water system at time t. This is used to characterize the average heat absorption temperature difference within the second sliding window corresponding to time t. This is used to characterize the average exothermic temperature difference within the second sliding window corresponding to time t. s is used to characterize the flow rate ratio of the power plant's heating circulating water system at time t. The function is used for normalization.

[0088] in, The ratio between the user-side temperature adjustment parameter and the temperature change of the internal circulating water on the heating side within the second sliding window represents the heat transfer ratio. The larger the value, the better the heat transfer efficiency. The inverse proportionality coefficient between the total internal circulating water flow rate and the total flow rate in the primary pipe network is used as a factor influencing the effect of water flow hysteresis on heat transfer. The activation function normalizes the result. Multiplying the two results reflects the matching ratio between user-side flow and heating-side flow; the core logic of this multiplication embodies the dual constraint quantification of supply-demand imbalance. It should be noted that, to ensure the calculation results are meaningful, in this embodiment of the invention, when performing fractional operations, if the denominator is 0, a parameter adjustment factor ε greater than 0 needs to be added to the denominator before summing to prevent the denominator from being zero. The value of the parameter adjustment factor can be 0.01, or it can be set by the implementer according to the actual situation; this invention does not impose any special restrictions.

[0089] By multiplying the heat transfer ratio by the reciprocal of the flow rate ratio, the two key factors of heat exchange efficiency and heating medium flow distribution can be effectively coupled to form a comprehensive deviation evaluation value. This coupling method makes the assessment of supply-demand matching deviation more comprehensive and accurate, and can more sensitively capture the imbalance state of the system in heat transfer and flow distribution, avoiding misjudgments that may be caused by a single indicator. Subsequently, the deviation evaluation value is normalized to ensure that the deviation value is comparable and stable under different operating conditions, eliminating the influence of dimensions and numerical range, thus providing standardized input for the subsequent calculation of the first adjustment weight. This significantly improves the accuracy and reliability of the supply-demand matching deviation assessment, thereby enabling the dynamic adjustment of heating temperature based on this deviation to more accurately respond to the actual supply and demand changes of the system, effectively avoiding over-adjustment or under-adjustment caused by inaccurate assessment, and improving the operating efficiency and stability of the power plant's heating circulating water system.

[0090] In some of the embodiments described above in this application, the heating temperature regulation of the power plant's heating circulating water system needs to comprehensively consider the severity of the impact of grid dispatch on heating (characterized by the target waste heat fluctuation rate) and the supply-demand matching status within the system (characterized by the supply-demand matching deviation). However, in practical applications, how to effectively quantify and integrate these two factors with different dimensions and units to generate a unified and guiding adjustment weight is a key challenge in achieving precise dynamic temperature control.

[0091] In this regard, this application further proposes that S140 includes: Multiply the supply-demand matching deviation by the first adjustment coefficient to obtain the first weight value; The second weight value is obtained by multiplying the ratio of the target waste heat volatility to the maximum historical waste heat volatility by the second adjustment coefficient; the sum of the first adjustment coefficient and the second adjustment coefficient is one. The first weight value is added to the second weight value to obtain the first adjustment weight of the power plant heating circulating water system.

[0092] In this embodiment, the supply-demand matching deviation quantifies the degree of imbalance between the current heat supply and user heat demand in the power plant's heating circulating water system. Its magnitude reflects whether the system's heat load is surplus or insufficient. The first adjustment coefficient is a numerical factor used to adjust the influence of the supply-demand matching deviation. It can be a preset fixed value, for example, determined through historical operating data analysis, expert experience, or system simulation optimization; or its value can be dynamically adjusted according to the system's current operating mode, seasonal changes, or load characteristics to adapt to different operating conditions. The first weight value is the result of weighting the supply-demand matching deviation by the first adjustment coefficient; it specifically characterizes the degree to which the current supply-demand imbalance contributes to the final temperature regulation decision.

[0093] The target waste heat volatility characterizes the severity of the heat shock to the power plant's heating system caused by changes in grid dispatching, and its value reflects the potential impact of external disturbances on system stability. The historical maximum waste heat volatility is the highest recorded target waste heat volatility over a past period, serving as a reference benchmark for the current target waste heat volatility and measuring its severity relative to historical extremes. This maximum value can be stored in the system database and updated periodically, or obtained through sliding window statistics. The ratio of the target waste heat volatility to the historical maximum waste heat volatility normalizes the current target waste heat volatility, making it a dimensionless relative indicator. By comparing it with the historical maximum, the relative intensity of the current waste heat volatility within a historical context can be assessed more intuitively. The second adjustment coefficient is a numerical factor used to adjust the influence of the normalized target waste heat volatility. It can be a preset fixed value, for example, set according to the frequency and amplitude of grid dispatching shocks and the system's response characteristics to the shocks; or it can be adaptively adjusted based on actual operating conditions. The second weight value is the result of normalizing the target waste heat fluctuation rate and weighting it by the second adjustment coefficient. It specifically represents the degree of contribution of grid dispatch shocks to the final temperature regulation decision.

[0094] The sum of the first adjustment coefficient and the second adjustment coefficient is one. This constraint ensures the proportional relationship between the first adjustment coefficient and the second adjustment coefficient in the total weight allocation. By limiting the sum of the two to one, it can be ensured that the supply and demand matching deviation and the target waste heat fluctuation rate occupy a reasonable and complementary proportion in the final first adjustment weight, avoiding the weight being too high or too low due to improper coefficient settings.

[0095] The first adjustment weight is the final result of adding the first weight value and the second weight value. It comprehensively reflects the current supply and demand matching status of the power plant's heating circulating water system and the severity of the impact of power grid dispatch. This weight value will serve as the direct basis for subsequent dynamic adjustment of heating temperature.

[0096] This application's solution effectively addresses the challenge of quantifying and applying factors from different dimensions to temperature regulation by weighting and fusing two key indicators: supply-demand matching deviation and target waste heat volatility. Specifically, the supply-demand matching deviation is first multiplied by a first adjustment coefficient to quantify its impact on temperature regulation, yielding a first weight value. Simultaneously, the target waste heat volatility is compared to the historical maximum waste heat volatility to achieve a normalized assessment of the severity of external shocks. This is then multiplied by a second adjustment coefficient to quantify its impact on temperature regulation, resulting in a second weight value. Crucially, the sum of the first and second adjustment coefficients is set to one, ensuring that the two factors occupy a reasonable and complementary proportion in the final first adjustment weight, avoiding the over-dominance or under-dominance of a single factor. Finally, the sum of these two weighted values ​​yields the first adjustment weight, comprehensively reflecting both the internal supply-demand situation and external grid dispatch shocks. This weighted fusion mechanism enables the first adjustment weight to comprehensively and balancedly reflect the internal and external challenges currently facing the system, providing a more accurate and robust basis for subsequent dynamic adjustment of heating temperature.

[0097] As an example, the first adjustment weight of the power plant heating circulating water system can be determined using the following formula 3: Formula 3 In formula 3, The first adjustment weight is used to characterize the power plant's heating circulating water system at time t. Used to characterize the target waste heat fluctuation rate at time t. Used to characterize the supply-demand mismatch in the power plant's heating circulating water system at time t. Used to characterize the maximum historical waste heat fluctuation rate. Used to characterize the first adjustment coefficient The second adjustment coefficient is used to characterize the first adjustment coefficient. For example, if the first adjustment coefficient can be 0.4, then the second adjustment coefficient can be 0.6.

[0098] In some of the embodiments described above in this application, the heating temperature of the power plant heating circulating water system is dynamically adjusted based on a first adjustment weight. However, how to effectively convert this adjustment weight into specific physical control commands to achieve precise and real-time control of the heating temperature is a problem that needs to be solved in practical applications.

[0099] In this regard, this application further proposes S150 including: Based on the first adjustment weight, the corrected opening value of the regulating valve in the power plant heating circulating water system is determined; Based on the corrected opening value, the opening of the regulating valve in the power plant's heating circulating water system is dynamically adjusted.

[0100] In this embodiment, the first adjustment weight is a quantitative indicator calculated based on the target waste heat fluctuation rate and the supply-demand matching deviation. It reflects the degree to which the current power plant heating circulating water system needs temperature regulation and serves as the decision-making basis for dynamic temperature regulation of the system. The regulating valve in the power plant heating circulating water system is a key actuator installed in the system to control fluid flow, pressure, or temperature. By changing the valve opening, the fluid throughput can be precisely controlled, thereby affecting the heat exchanger efficiency and the temperature of the heating circulating water. The regulating valve can be an electric, pneumatic, or hydraulic regulating valve, etc., and its opening can be continuously or progressively adjusted by an external control signal. The corrected opening value is calculated based on the first adjustment weight and is a specific value used to guide the actual opening setting of the regulating valve. It transforms the abstract "first adjustment weight" into a physical quantity that the regulating valve can recognize and execute, ensuring that the regulating valve can accurately adjust its opening according to the actual needs of the system.

[0101] This application's solution transforms the abstract first adjustment weight into a concrete physical control quantity by introducing a corrected opening value for the regulating valve, thereby achieving dynamic adjustment of the heating temperature in the power plant's heating circulating water system. Specifically, the system first calculates the first adjustment weight based on the target waste heat fluctuation rate and the supply-demand matching deviation. This first adjustment weight quantifies the degree of temperature adjustment required by the current system. To implement this quantification, this solution further calculates the corrected opening value of the regulating valve in the power plant's heating circulating water system based on this first adjustment weight. This corrected opening value serves as a control command for the regulating valve, guiding it to adjust its opening accordingly. For example, when the first adjustment weight indicates a need to lower the heating temperature, the corrected opening value may indicate a decrease in the regulating valve opening, thereby reducing the heat source flow into the heater; conversely, when a need to raise the heating temperature, the corrected opening value may indicate an increase in the regulating valve opening. In this way, the opening of the regulating valve can be dynamically adjusted in real-time, continuously, or discretely according to the corrected opening value, directly affecting the heat exchange of the heater and thus precisely controlling the temperature of the heating circulating water. This mechanism, which directly applies the comprehensive evaluation results (first adjustment weight) to the physical actuator (regulating valve) by adjusting the opening value, enables the entire heating circulating water system to respond quickly and effectively to heating shocks caused by power grid dispatch and supply-demand mismatches, ensuring the stability of heating temperature and the operating efficiency of the system.

[0102] The above technical solution directly converts the primary adjustment weight of the power plant's heating circulating water system into the corrected opening value of the regulating valve, and dynamically adjusts the valve opening accordingly, thus solving the problem of how to translate abstract system regulation requirements into concrete physical control actions. This enables the heating circulating water system to achieve precise, real-time, and automated control of heating temperature based on the severity of the impact of power grid dispatch on heating and the supply-demand mismatch.

[0103] In some of the embodiments described above in this application, directly applying the first adjustment weight to the opening correction of the control valve may not fully take into account the fine adjustment requirements and the stability of system operation, resulting in poor adjustment effect or excessive system response.

[0104] In this regard, this application further proposes, based on a first adjustment weight, determining the corrected opening value of the regulating valve in the power plant heating circulating water system, including: Map the first adjustment weight to the target interval to obtain the second adjustment weight; Based on the adjustment intensity coefficient, the second adjustment weight is corrected to obtain the third adjustment weight; Based on the third adjustment weight, the basic opening value of the regulating valve in the power plant heating circulating water system is corrected to obtain the corrected opening value of the regulating valve in the power plant heating circulating water system.

[0105] In this embodiment, the corrected opening value of the regulating valve in the power plant heating circulating water system can be determined by the following formula 4: Formula 4 In formula 4, Used to characterize the corrected opening value of the regulating valve in the power plant's heating circulating water system at time t. Used to characterize the basic opening value of the regulating valve in the power plant's heating circulating water system at time t. The first adjustment weight is used to characterize the power plant's heating circulating water system at time t. Used to characterize the adjustment intensity coefficient, its value range is: This is to prevent system oscillations caused by excessively large single adjustments (based on experience).

[0106] in, Weight Mapped to The interval is where the second adjustment weight is obtained. When... When this value is positive, the system tends to increase the opening degree (to cope with insufficient demand or drastic fluctuations); when... When this term is negative, the system tends to reduce the opening degree (to cope with oversupply or system stability).

[0107] This embodiment maps the first adjustment weight to the target range, transforming the abstract weight value into a more operational value that matches the regulating valve opening adjustment logic, thus laying the foundation for subsequent refined adjustment. Furthermore, the second adjustment weight is modified based on the adjustment intensity coefficient, providing the system with flexible adjustment capabilities. It can dynamically adjust the aggressiveness or conservatism of the adjustment according to actual operational needs or experience, effectively avoiding overly drastic adjustments or slow responses. Finally, the third adjustment weight modifies the basic opening value of the regulating valve, ensuring that dynamic adjustment is carried out on a stable and reasonable basis, avoiding large and unstable fluctuations. This significantly improves the accuracy, stability, and response speed of the heating temperature regulation in the power plant's heating circulating water system, thereby better coping with the impact of grid dispatch on heating and optimizing supply and demand matching.

[0108] Based on the specific embodiments of the power plant heating circulating water temperature control method provided in this application, correspondingly, this application further provides a specific embodiment of a power plant heating circulating water temperature control system.

[0109] like Figure 3 The diagram shows a structural schematic of a power plant heating circulating water temperature control system. The power plant heating circulating water temperature control system 300 includes: Temperature acquisition module 310 is used to acquire the first inlet temperature and the first outlet temperature of the internal circulating water in the heater of the power plant heating circulating water system, as well as the second inlet temperature and the second outlet temperature of the primary pipeline in the heater. The volatility assessment module 320 is used to determine the target waste heat volatility of the internal circulating water in the heater based on the first inlet temperature and the first outlet temperature; the target waste heat volatility is used to characterize the severity of the impact of power grid dispatch on heating supply. Deviation assessment module 330 is used to determine the supply and demand matching deviation of the power plant heating circulating water system based on the first inlet temperature, the first outlet temperature, the second inlet temperature, and the second outlet temperature. The weight assessment module 340 is used to determine the first adjustment weight of the power plant heating circulating water system based on the target waste heat volatility and the supply and demand matching deviation. The system adjustment module 350 is used to dynamically adjust the heating temperature of the power plant heating circulating water system based on the first adjustment weight.

[0110] The power plant heating circulating water temperature control system provided in this embodiment of the invention first acquires the temperature data of the internal circulating water and primary pipeline in the heater of the power plant heating circulating water system. Based on the inlet and outlet temperatures of the internal circulating water, a target waste heat fluctuation rate is determined to characterize the severity of the impact of grid dispatch on heating. Then, the supply-demand matching deviation is determined by combining the temperature data between the internal circulating water and the primary pipeline. Subsequently, a first adjustment weight is determined based on the target waste heat fluctuation rate and the supply-demand matching deviation. Finally, the heating temperature is dynamically adjusted based on this first adjustment weight. Thus, this method comprehensively considers waste heat fluctuations and supply-demand matching, enabling flexible adjustment of the heating temperature according to actual conditions. This avoids the unreasonable adjustment problems caused by fixed threshold allocation in existing methods, thereby improving the reliability of heating circulating water temperature control.

[0111] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0112] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for regulating the temperature of circulating heating water in a power plant, characterized in that, The method includes: The first inlet temperature and the first outlet temperature of the internal circulating water in the heater of the power plant heating circulating water system, as well as the second inlet temperature and the second outlet temperature of the primary pipeline in the heater, are obtained. Based on the first inlet temperature and the first outlet temperature, the target waste heat fluctuation rate of the internal circulating water in the heater is determined; the target waste heat fluctuation rate is used to characterize the severity of the impact of power grid dispatch on heating supply. Based on the first inlet temperature, the first outlet temperature, the second inlet temperature, and the second outlet temperature, the supply and demand matching deviation of the power plant heating circulating water system is determined. Based on the target waste heat fluctuation rate and the supply-demand matching deviation, the first adjustment weight of the power plant heating circulating water system is determined; Based on the first adjustment weight, the heating temperature of the power plant's heating circulating water system is dynamically adjusted.

2. The method for regulating the temperature of circulating water in a power plant heating system according to claim 1, characterized in that, The step of determining the target waste heat fluctuation rate of the internal circulating water in the heater based on the first inlet temperature and the first outlet temperature includes: Based on the flow rate of the internal circulating water and the effective heat exchange length of the heater, the theoretical lag time of the internal circulating water is determined. A first temperature difference sequence is constructed based on the first temperature difference between the first outlet temperature at time t and the first inlet temperature at time tn; where t is a positive integer and n is the theoretical lag time. Based on the first temperature difference values ​​within the first sliding window corresponding to the first temperature difference sequence at the current time, the target waste heat fluctuation rate of the internal circulating water in the heater at the current time is determined.

3. The method for regulating the temperature of circulating water in a power plant heating system according to claim 2, characterized in that, The step of determining the target waste heat fluctuation rate of the internal circulating water in the heater at the current moment based on each of the first temperature difference values ​​within the first sliding window corresponding to the first temperature difference sequence at the current moment includes: The average value of each temperature difference in the first temperature difference sequence within the first sliding window is obtained by averaging the temperature difference values. The absolute values ​​of the differences between each of the first temperature difference values ​​in the first temperature difference sequence within the first sliding window and the mean value of the temperature difference are averaged to obtain the target waste heat fluctuation rate of the internal circulating water in the heater at the current moment.

4. The method for regulating the temperature of circulating water in a power plant heating system according to claim 1, characterized in that, The determination of the supply-demand mismatch of the power plant's heating circulating water system based on the first inlet temperature, the first outlet temperature, the second inlet temperature, and the second outlet temperature includes: A first temperature difference sequence is constructed based on the first temperature difference between the first outlet temperature at time t and the first inlet temperature at time tn, and a second temperature difference sequence is constructed based on the second temperature difference between the second outlet temperature at time t and the second inlet temperature at time tn; where t is a positive integer and n is the theoretical lag time. The average exothermic temperature difference is determined based on each of the first temperature difference values ​​in the second sliding window corresponding to the first temperature difference sequence at the current time, and the average endothermic temperature difference is determined based on each of the second temperature difference values ​​in the second sliding window corresponding to the second temperature difference sequence at the current time. Based on the average heat release temperature difference and the average heat absorption temperature difference, the supply and demand matching deviation of the power plant heating circulating water system is determined.

5. The method for regulating the temperature of circulating water in a power plant heating system according to claim 4, characterized in that, The determination of the supply-demand mismatch of the power plant's heating circulating water system based on the average exothermic temperature difference and the average endothermic temperature difference includes: The heat transfer ratio of the power plant heating circulating water system is determined by dividing the average heat absorption temperature difference by the average heat release temperature difference. The flow rate of the power plant heating circulating water system is obtained by dividing the first flow rate of the internal circulating water in the second sliding window by the second flow rate of the primary pipeline in the second sliding window. Based on the heat transfer ratio and the flow rate ratio, the supply and demand matching deviation of the power plant heating circulating water system is determined.

6. The method for regulating the temperature of circulating water in a power plant heating system according to claim 5, characterized in that, The determination of the supply-demand matching deviation of the power plant's heating circulating water system based on the heat transfer ratio and the flow rate ratio includes: Multiply the heat transfer ratio by the reciprocal of the flow rate ratio to obtain the deviation evaluation value; The deviation evaluation value is normalized to obtain the supply and demand matching deviation of the power plant heating circulating water system.

7. The method for regulating the temperature of circulating heating water in a power plant according to claim 1, characterized in that, The determination of the first adjustment weight of the power plant's heating circulating water system based on the target waste heat fluctuation rate and the supply-demand matching deviation includes: The supply-demand matching deviation is multiplied by the first adjustment coefficient to obtain the first weight value; The ratio of the target waste heat volatility to the maximum historical waste heat volatility is multiplied by a second adjustment coefficient to obtain a second weight value; the sum of the first adjustment coefficient and the second adjustment coefficient is one. The first weight value is added to the second weight value to obtain the first adjustment weight of the power plant heating circulating water system.

8. The method for regulating the temperature of circulating water in a power plant heating system according to claim 1, characterized in that, The dynamic adjustment of the heating temperature of the power plant's heating circulating water system based on the first adjustment weight includes: Based on the first adjustment weight, the corrected opening value of the regulating valve in the power plant heating circulating water system is determined; Based on the corrected opening value, the opening of the regulating valve in the power plant's heating circulating water system is dynamically adjusted.

9. The method for regulating the temperature of circulating water in a power plant heating system according to claim 8, characterized in that, The step of determining the corrected opening value of the regulating valve in the power plant heating circulating water system based on the first adjustment weight includes: The first adjustment weight is mapped to the target interval to obtain the second adjustment weight; Based on the adjustment intensity coefficient, the second adjustment weight is corrected to obtain the third adjustment weight; Based on the third adjustment weight, the basic opening value of the regulating valve in the power plant heating circulating water system is corrected to obtain the corrected opening value of the regulating valve in the power plant heating circulating water system.

10. A power plant heating circulating water temperature control system, characterized in that, The system includes: The temperature acquisition module is used to acquire the first inlet temperature and the first outlet temperature of the internal circulating water in the heater of the power plant heating circulating water system, as well as the second inlet temperature and the second outlet temperature of the primary pipeline in the heater. The volatility assessment module is used to determine the target waste heat volatility of the internal circulating water in the heater based on the first inlet temperature and the first outlet temperature; the target waste heat volatility is used to characterize the severity of the impact of power grid dispatch on heating supply. The deviation assessment module is used to determine the supply and demand matching deviation of the power plant heating circulating water system based on the first inlet temperature, the first outlet temperature, the second inlet temperature, and the second outlet temperature. The weight evaluation module is used to determine the first adjustment weight of the power plant heating circulating water system based on the target waste heat fluctuation rate and the supply and demand matching deviation. The system adjustment module is used to dynamically adjust the heating temperature of the power plant heating circulating water system based on the first adjustment weight.

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