Thermal loss-based downstream steam demand prediction method and device, and storage medium

Abstract

The present application relates to the technical field of demand prediction, and specifically discloses a downstream steam demand prediction method and device based on heat loss and a storage medium. The method comprises the following steps: obtaining downstream steam demand, determining theoretical heat loss corresponding to the downstream steam demand; generating initial demand prediction information based on the theoretical heat loss and the downstream steam demand; performing virtual flow analysis based on the initial demand prediction information and the theoretical heat loss, and generating virtual steam flow; obtaining flow sensing data, determining actual steam flow based on the flow sensing data; determining flow deviation based on the actual steam flow and the virtual flow data; and processing the initial demand prediction information based on the flow deviation, and generating processed prediction information. By analyzing and optimizing the downstream demand based on the actual heat loss, the accuracy of demand prediction is improved, and the economic benefits of enterprises are improved.

Description

Technical Field

[0001] This invention relates to the field of demand forecasting technology, specifically to a method, apparatus, and storage medium for forecasting downstream steam demand based on heat loss. Background Technology

[0002] Steam is widely used in many industries such as chemical reactions, food processing, textile printing and dyeing, and heating. In the actual steam pipeline transmission process, heat loss is a common problem that cannot be completely avoided. However, the degree of heat loss has a direct and significant impact on the interests of both the source and user enterprises, and has become one of the key factors restricting the improvement of economic benefits for related enterprises.

[0003] To produce high-temperature, high-pressure steam that meets transportation requirements, upstream enterprises need to consume large amounts of energy resources such as coal and natural gas, and their production input is directly linked to the thermal energy content of the steam. When steam is transported through pipelines, various heat losses occur, such as changes in ambient temperature, failure or damage to the pipeline insulation layer, passive steam release due to pressure accumulation, pipeline rupture, and active steam release, all of which lead to heat loss.

[0004] However, in practical applications, upstream enterprises often produce and transmit steam according to the demand of downstream enterprises. Various unforeseen factors and random events make accurate calculation of heat loss impossible. Therefore, upstream enterprises often need to provide more steam than actually required to ensure the actual needs of downstream enterprises. However, existing technologies have at least the following technical shortcomings:

[0005] On the one hand, for steam source enterprises, significant heat loss during transmission means that some heat energy is lost into the environment without being effectively utilized. Source enterprises have to increase their energy input to make up for the heat energy gap caused by heat loss, which will significantly increase their production and operating costs. At the same time, if heat loss exceeds the expected range, some steam may be ineffectively transmitted due to temperature and pressure dropping below the standard, further exacerbating the resource waste and economic losses of source enterprises.

[0006] On the other hand, for steam-using enterprises, receiving far less steam heat energy than expected will directly affect the normal operation of production activities, resulting in losses. The production processes of these enterprises often have strict requirements on parameters such as steam temperature and pressure. Insufficient steam heat energy can lead to problems such as decreased operating efficiency of production equipment, deviation of production process parameters from standards, and fluctuations in product quality, and in severe cases, even production interruption.

[0007] In summary, how to accurately assess heat loss during steam pipeline transmission in real time and accurately predict actual downstream steam demand has become a key bottleneck affecting the interests of both source and user enterprises. This not only wastes energy resources but also seriously restricts the improvement of economic efficiency and sustainable development of related industries. Summary of the Invention

[0008] To overcome the aforementioned technical problems in the prior art, embodiments of the present invention provide a method, apparatus, and storage medium for predicting downstream steam demand based on heat loss. By analyzing and proactively optimizing downstream demand based on actual heat loss conditions, the accuracy of demand forecasting is improved, thereby enhancing the economic benefits for enterprises.

[0009] To achieve the above objectives, embodiments of the present invention provide a downstream steam demand forecasting method based on heat loss. The method includes: acquiring downstream steam demand and determining the theoretical heat loss corresponding to the downstream steam demand; generating initial demand forecasting information based on the theoretical heat loss and the downstream steam demand; performing virtual flow analysis based on the initial demand forecasting information and the theoretical heat loss to generate virtual steam flow; acquiring flow sensing data and determining the actual steam flow based on the flow sensing data; determining a flow deviation based on the actual steam flow and the virtual flow data; and processing the initial demand forecasting information based on the flow deviation to generate processed forecasting information.

[0010] Preferably, determining the theoretical heat loss corresponding to the downstream steam demand includes: obtaining the demand entity corresponding to the downstream steam demand; determining the connecting pipeline between the demand entity and the demand entity; obtaining the pipeline geometric parameters, steam physical parameters, property data, and steam release compensation amount of the connecting pipeline; determining the natural heat loss based on the pipeline geometric parameters, the steam physical parameters, the property data, and the real-time ambient temperature of the connecting pipeline; and determining the theoretical heat loss based on the natural heat loss and the steam release compensation amount.

[0011] Preferably, generating initial demand forecast information based on the theoretical heat loss and the downstream steam demand includes: determining the downstream real-time steam demand value based on the downstream steam demand; determining the upstream real-time steam supply value based on the theoretical heat loss and the downstream real-time steam demand value; determining the transmission lag factor based on the pipeline length and the steam transmission speed; and generating initial demand forecast information based on the upstream real-time steam supply value and the transmission lag factor.

[0012] Preferably, the step of processing the initial demand forecast information based on the flow deviation to generate processed forecast information includes: when the flow deviation is greater than a preset deviation threshold, determining a flow deviation segment based on the flow sensing data; acquiring real-time pressure sensing data of the flow deviation segment; determining the flow deviation type of the flow deviation segment based on the real-time pressure sensing data, wherein the flow deviation type includes artificial pressure relief and non-artificial pressure relief; determining the demand adjustment amount based on the flow deviation type; and optimizing the initial demand forecast information based on the demand adjustment amount to generate processed forecast information.

[0013] Preferably, determining the flow deviation type of the flow deviation segment based on the real-time pressure sensing data includes: generating a real-time pressure curve corresponding to the real-time pressure sensing data; determining whether the real-time pressure curve has a pressure inflection point; if the pressure inflection point exists, determining whether a passive pressure relief valve exists in the flow deviation segment; if the passive pressure relief valve exists, obtaining the pressure relief pressure of the passive pressure relief valve, determining whether the pressure relief pressure is consistent with the pressure inflection point; if the pressure relief pressure is consistent with the pressure inflection point, determining that the flow deviation type is non-human-caused pressure relief; if the pressure relief pressure is inconsistent with the pressure inflection point, determining that the flow deviation type is human-caused pressure relief; if the passive pressure relief valve does not exist, determining that the flow deviation type is human-caused pressure relief; if the pressure inflection point does not exist, determining that the flow deviation type is non-human-caused pressure relief.

[0014] Preferably, determining the demand adjustment amount based on the flow deviation type includes: if the flow deviation type is artificial pressure relief, or if the flow deviation type is non-artificial pressure relief and the pressure inflection point exists: determining an initial adjustment amount based on the real-time pressure sensing data and the pressure inflection point; optimizing the initial adjustment amount based on the transmission lag factor to generate the demand adjustment amount.

[0015] Preferably, the method further includes: if the flow deviation type is non-human-induced pressure relief and there is no pressure inflection point, determining the insulation layer failure pressure difference based on the insulation layer parameters; determining whether the insulation layer has failed based on the pressure inflection point and the insulation layer failure pressure difference; if so, generating a first alarm message corresponding to the insulation layer failure; otherwise, determining that the pipeline is damaged and leaking, and generating a second alarm message corresponding to the pipeline is damaged and leaking.

[0016] Preferably, the method further includes: acquiring downstream demand big data and corresponding historical forecast data; generating a prediction reliability curve based on the pipeline length, the downstream demand big data, and the historical forecast data; generating a real-time compensation amount corresponding to the processed prediction information based on the prediction reliability curve; and optimizing the processed prediction information based on the real-time compensation amount to generate optimized prediction information.

[0017] Accordingly, the present invention also provides a downstream steam demand forecasting device based on heat loss. The device includes: a heat loss calculation unit for acquiring downstream steam demand and determining the theoretical heat loss corresponding to the downstream steam demand; an initial forecasting unit for generating initial demand forecasting information based on the theoretical heat loss and the downstream steam demand; a flow simulation unit for performing virtual flow analysis based on the initial demand forecasting information and the theoretical heat loss to generate virtual steam flow; a flow acquisition unit for acquiring flow sensing data and determining the actual steam flow based on the flow sensing data; a deviation determination unit for determining the flow deviation based on the actual steam flow and the virtual flow data; and a demand forecasting unit for processing the initial demand forecasting information based on the flow deviation to generate processed forecasting information.

[0018] On the other hand, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method provided in the embodiments of the present invention.

[0019] The present invention has at least the following technical effects through the technical solution provided by the present invention:

[0020] By comprehensively analyzing the actual physical phenomena and heat loss influencing factors during steam transmission through pipelines, accurate calculations of heat loss and precise predictions of downstream steam demand can be achieved. This significantly reduces the amount of steam wasted by upstream enterprises to meet the actual operational needs of downstream enterprises, improves enterprise operating efficiency, effectively guarantees the actual economic needs of downstream enterprises, promotes reliable verification of upstream and downstream steam transmission data, reduces enterprise disputes, and enhances the user experience for downstream enterprises.

[0021] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0022] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0023] Figure 1 This is a flowchart illustrating the specific implementation of the downstream steam demand forecasting method based on heat loss provided in this embodiment of the invention.

[0024] Figure 2 This is a schematic diagram of the downstream steam demand forecasting device based on heat loss provided in an embodiment of the present invention. Detailed Implementation

[0025] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0026] In this invention, the terms "system" and "network" are used interchangeably. "Multiple" refers to two or more; therefore, in this invention, "multiple" can also be understood as "at least two." "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / ", unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship. Furthermore, it should be understood that in the description of this invention, terms such as "first" and "second" are used only for descriptive purposes and should not be construed as indicating or implying relative importance or order.

[0027] The background technology of this application will be introduced first below.

[0028] In existing technologies, upstream steam suppliers cannot accurately predict downstream steam demand and adjust their steam output accordingly. Even after understanding downstream demand, while heat loss needs to be calculated and steam supplied based on that loss, traditional calculation methods rely on fixed, theoretical calculations, often resulting in significant deviations. To avoid impacting actual operations, suppliers often supply an excess amount to meet actual demand. However, this approach suffers from significant inefficiencies, leading to low operating efficiency for upstream steam suppliers. Furthermore, it prevents accurate settlement between upstream and downstream companies, resulting in substantial supply-use discrepancies that fail to meet actual needs, causing considerable problems for both.

[0029] Please see Figure 1 This invention provides a method for predicting downstream steam demand based on heat loss, the method comprising:

[0030] S10, Obtain downstream steam demand and determine the theoretical heat loss corresponding to the downstream steam demand;

[0031] S20, generate initial demand forecast information based on the theoretical heat loss and the downstream steam demand;

[0032] S30, based on the initial demand forecast information and the theoretical heat loss, perform virtual flow analysis to generate virtual steam flow;

[0033] S40, acquire flow sensor data, and determine the actual steam flow rate based on the flow sensor data;

[0034] S50, determine the flow deviation based on the actual steam flow rate and the virtual flow rate data;

[0035] S60, the initial demand forecast information is processed based on the flow deviation to generate processed forecast information.

[0036] In one possible implementation, in order to make more accurate predictions of downstream steam demand, the downstream steam demand is first obtained. This downstream steam demand is the demand data declared or provided by downstream enterprises based on their actual needs, which represents the amount of steam that upstream steam supply enterprises need to provide under normal circumstances. At this time, the corresponding theoretical heat loss is determined in order to prepare for accurate steam supply.

[0037] As is readily apparent to those skilled in the art, there are many factors affecting heat loss, including human factors (such as active depressurization) and non-human factors (such as passive depressurization). These can also be categorized as incidental factors (such as pipe rupture or insulation layer damage) and non-incidental factors (insulation layer aging). For human and non-incidental factors, their expected effects can be predicted. However, traditional technical solutions cannot predict non-human and incidental factors, resulting in significant deviations in existing heat loss calculation methods, which fail to meet actual needs.

[0038] To address this technical problem, in this embodiment of the invention, determining the theoretical heat loss corresponding to the downstream steam demand includes: obtaining the demand entity corresponding to the downstream steam demand; determining the connecting pipeline between the demand entity and the demand entity; obtaining the pipeline geometric parameters, steam physical parameters, property data, and steam release compensation amount of the connecting pipeline; determining the natural heat loss based on the pipeline geometric parameters, the steam physical parameters, the property data, and the real-time ambient temperature of the connecting pipeline; and determining the theoretical heat loss based on the natural heat loss and the steam release compensation amount.

[0039] In one possible implementation, this application is applied to a steam supply scenario in a chemical industrial park. The steam source company in the park is Company A, and the downstream chemical production company is Company B. Companies A and B are connected by a 2km-long steam transmission pipeline with polyurethane insulation. The steam transmission speed is 0.5km / min, and the preset flow deviation threshold is 5%. Company B's daily real-time steam demand is 10t / h. To accurately calculate the theoretical heat loss corresponding to the downstream company, the corresponding demand entity is first identified, for example, Company B. This allows determination of the connecting pipeline required to transport steam from Company A to Company B.

[0040] Further, the corresponding pipeline geometric parameters (including but not limited to pipeline length, diameter, wall thickness, diameter variation, and elevation changes), steam physical parameters (including but not limited to steam transmission speed, temperature, pressure, molar flow rate, superheat, saturation, enthalpy, entropy, and pressure drop), physical property data (including water content and impurity content in the steam, including but not limited to air, carbon dioxide, and methane), and steam release compensation can be determined. This steam release compensation is a constant (e.g., 0.2 t / h) determined based on Company B's historical steam compensation experience. This value ensures Company B's normal steam usage needs. It should be noted that insulation layer parameters (e.g., insulation layer thickness 5 cm / thermal conductivity 0.02 W / (m·K)) can be further combined to comprehensively consider heat loss-related factors and improve the accuracy of subsequent theoretical heat loss calculations. Based on the pipeline geometric parameters, steam physical parameters, physical property data, and the real-time ambient temperature of the connected pipeline, the natural heat loss in the connected pipeline can be determined. Furthermore, the theoretical heat loss is determined based on the natural heat loss and the steam release compensation.

[0041] In this embodiment of the invention, by analyzing and theoretically calculating all physical factors affecting heat loss, accurate theoretical heat loss calculation is achieved, providing a data foundation for further accuracy analysis.

[0042] After determining the theoretical heat loss, the initial demand forecast information for downstream steam-consuming enterprises is further determined. Traditional calculation methods often involve directly adding the downstream steam demand to the theoretical heat loss to obtain the corresponding demand forecast. However, in practical applications, on the one hand, steam transmission in pipelines is also a form of flow transmission; the greater the transmission distance, the higher the transmission lag. How to accurately and in real-time respond to changes in downstream enterprise demand causes significant challenges for upstream enterprises. On the other hand, since many factors affect heat loss, the shorter the transmission distance, the smaller the impact of the transmission process, resulting in higher transmission consistency; while the longer the transmission distance, the greater the impact of the transmission process. In this case, the actual output steam volume deviates more from the actual steam volume received by downstream enterprises, leading to a larger forecast deviation.

[0043] To address the aforementioned technical problems, in this embodiment of the invention, generating initial demand forecast information based on the theoretical heat loss and the downstream steam demand includes: determining the downstream real-time steam demand value based on the downstream steam demand; determining the upstream real-time steam supply value based on the theoretical heat loss and the downstream real-time steam demand value; determining the transmission lag factor based on the pipeline length and the steam transmission speed; and generating initial demand forecast information based on the upstream real-time steam supply value and the transmission lag factor.

[0044] In one possible implementation, the upstream real-time steam supply value is first determined based on downstream steam demand and theoretical heat loss; that is, how much steam the upstream enterprise should theoretically supply in real time to meet the downstream enterprise's real-time demand. Then, a transmission lag factor is determined based on pipeline length and steam transmission speed. For example, the lag time is first calculated based on pipeline length and steam transmission speed, and then the prediction accuracy is determined based on this lag time. This prediction accuracy is normalized to generate the transmission lag factor. The upstream real-time steam supply value is then processed based on this transmission lag factor (e.g., the upstream real-time steam supply value is divided by the transmission lag factor) to obtain the initial demand forecast information. In subsequent steam supply processes, the upstream enterprise can supply steam based on this initial demand forecast information to achieve better steam supply accuracy while ensuring the enterprise's normal steam usage needs.

[0045] In this embodiment of the invention, by combining the theoretical heat loss with the lag in pipeline transmission and the predictive bias of fluid during long-distance transportation, the steam supply demand of upstream enterprises is predicted, thereby greatly improving the accuracy of prediction, making subsequent steam output more precise, greatly reducing steam supply waste, and improving the operating efficiency of enterprises.

[0046] At this point, Company A supplies steam based on the initial demand forecast. To accurately monitor the steam supply and respond promptly to changes in Company B's steam demand, a physical simulation combined with a virtual pipeline model is used to fully recreate the on-site pipeline transport conditions. Specifically, sensors can be placed along the pipeline to collect measured data and observe the supply and demand relationship. The simulation data is then input into the control system to dynamically adjust the supply and demand balance and pipeline balance. In the actual simulation process, the pipeline is divided into several segments, each with input and output parameters, such as core parameters like pressure, temperature, and flow rate. The simulation system generates a virtual steam flow rate for each segment, and the difference between the virtual steam flow rate and the actual pipeline monitoring value is used to determine whether there are significant energy losses, pipeline leaks, or regional temperature losses in the pipeline. Based on the above analysis, the required steam output of the boiler is accurately determined.

[0047] In this embodiment of the invention, processing the initial demand forecast information based on the flow deviation to generate processed forecast information includes: determining a flow deviation segment based on the flow sensing data when the flow deviation is greater than a preset deviation threshold; acquiring real-time pressure sensing data of the flow deviation segment; determining the flow deviation type of the flow deviation segment based on the real-time pressure sensing data, wherein the flow deviation type includes artificial pressure relief and non-artificial pressure relief; determining the demand adjustment amount based on the flow deviation type; and optimizing the initial demand forecast information based on the demand adjustment amount to generate processed forecast information.

[0048] In one possible implementation, at a certain moment during steam pipeline transmission, if the flow deviation between the virtual steam flow rate and the actual pipeline monitoring value is found to be greater than a preset deviation threshold, indicating a prediction inaccuracy, immediate adjustment or response is required. First, the flow deviation segment is determined based on the flow sensing data. Then, real-time pressure sensing data for that segment is acquired, and further, the corresponding flow deviation type is determined based on this real-time pressure sensing data.

[0049] It is easy for those skilled in the art to know that during steam transmission, the factors affecting the accuracy of forecasts are not changes in the actual steam demand of enterprises (which are often communicated in advance and have a low frequency and magnitude of change) and ambient temperature, but rather occasional factors, such as accidental depressurization or pipeline rupture. Therefore, these factors need to be thoroughly analyzed to improve forecast accuracy.

[0050] In this embodiment of the invention, determining the flow deviation type of the flow deviation segment based on the real-time pressure sensing data includes: generating a real-time pressure curve corresponding to the real-time pressure sensing data; determining whether the real-time pressure curve has a pressure inflection point; if the pressure inflection point exists, determining whether a passive pressure relief valve exists in the flow deviation segment; if the passive pressure relief valve exists, obtaining the pressure relief pressure of the passive pressure relief valve, determining whether the pressure relief pressure is consistent with the pressure inflection point; if the pressure relief pressure is consistent with the pressure inflection point, determining that the flow deviation type is non-human-caused pressure relief; if the pressure relief pressure is inconsistent with the pressure inflection point, determining that the flow deviation type is human-caused pressure relief; if the passive pressure relief valve does not exist, determining that the flow deviation type is human-caused pressure relief; if the pressure inflection point does not exist, determining that the flow deviation type is non-human-caused pressure relief.

[0051] In one possible implementation, in order to accurately determine the type of flow deviation, a corresponding real-time pressure curve is first generated based on real-time pressure sensing data, which enables a more accurate and intuitive analysis of the physical characteristics of different deviation factors. At this point, it is determined whether there is a pressure inflection point in the real-time pressure curve.

[0052] During their research, technicians discovered that when pipeline ruptures, insulation aging, or damage occurs, steam transmission losses exhibit a non-linear increasing curve. This leads to a non-linear decreasing pressure change within the pipeline. As the pressure / temperature balances with external changes, steam is transmitted at a new transmission pressure. This type of pressure curve lacks a pressure inflection point. In contrast, passive and active pressure relief involve rapid and targeted adjustments to steam transmission. The pressure curve in these cases decreases to a certain inflection point and then remains stable, or even increases further. Therefore, precise analysis can be performed based on the characteristics of the pressure curves under different conditions.

[0053] Specifically, if no pressure inflection point is found on the real-time pressure curve, the flow deviation can be determined to be caused by pipe damage or aging / damage to the insulation layer, i.e., its type is non-human-induced pressure relief. If a pressure inflection point is found, it is necessary to further determine whether a passive pressure relief valve exists in this flow deviation range. For example, the presence of a passive pressure relief valve can be determined by obtaining the pipe design data. If no passive pressure relief valve exists, the flow deviation can be determined to be caused by human intervention, i.e., its type is human-induced pressure relief. If a passive pressure relief valve exists, the pressure relief of the passive pressure relief valve needs to be obtained. For a passive pressure relief valve, if the flow deviation is only caused by the passive pressure relief action of the valve, the pressure inflection point should be consistent with the pressure relief pressure; otherwise, there may also be active human-induced pressure relief. Therefore, based on the consistency between the pressure relief pressure and the pressure inflection point, the actual cause of the flow deviation can be determined, i.e., the type of flow deviation can be determined.

[0054] In this embodiment of the invention, the type of flow deviation is accurately determined based on the changes in the physical characteristics of steam during pipeline transmission under the influence of different pressure relief factors, thus providing reliable data support for the subsequent accurate determination of flow prediction adjustment amounts. After determining the type of flow deviation, the demand adjustment amount is further determined.

[0055] In this embodiment of the invention, determining the demand adjustment amount based on the flow deviation type includes: if the flow deviation type is artificial pressure relief, or if the flow deviation type is non-artificial pressure relief and the pressure inflection point exists: determining an initial adjustment amount based on the real-time pressure sensing data and the pressure inflection point; optimizing the initial adjustment amount based on the transmission hysteresis factor to generate the demand adjustment amount.

[0056] In one possible implementation, demand analysis needs to be performed based on different types of flow deviation to determine accurate and reliable demand adjustment amounts. Specifically, if the flow deviation type is due to artificial pressure relief, or if it is due to non-artificial pressure relief and a pressure inflection point exists, it can be determined that the current pressure deviation is influenced by human operation. In this case, the subjective demand intention of the human operation can be determined based on the pressure inflection point, i.e., the human operator hopes to control the steam transmission pressure near the pressure inflection point. Therefore, based on the corresponding real-time pressure sensing data and the pressure inflection point, the corresponding initial adjustment amount can be determined. Then, based on the aforementioned transmission lag factor, the real-time adjustment amount at the upstream steam supply enterprise can be further determined, i.e., the demand adjustment amount is generated.

[0057] In this embodiment of the invention, by analyzing human subjective intent, a precise overall transmission adjustment amount is determined. Combined with transmission lag, this enables real-time and accurate prediction of steam transmission volume, greatly reducing steam transmission waste and improving enterprise operating efficiency.

[0058] In practical applications, additional heat loss may be caused by damage to transmission pipelines or failure / damage to the insulation layer. If left unaddressed, the fault may persist, heat loss may continue to increase, and this will consequently affect the accuracy of steam demand forecasting and may even lead to pipeline safety issues. Furthermore, different types of heat loss require different maintenance measures, and their economic impact on enterprises also varies.

[0059] In this embodiment of the invention, the method further includes: if the flow deviation type is non-human-induced pressure relief and there is no pressure inflection point, determining the insulation layer failure pressure difference based on the insulation layer parameters; determining whether the insulation layer has failed based on the pressure inflection point and the insulation layer failure pressure difference; if so, generating a first alarm message corresponding to the insulation layer failure; otherwise, determining that the pipeline is damaged and leaking, and generating a second alarm message corresponding to the pipeline is damaged and leaking.

[0060] In one possible implementation, after determining that the flow deviation is due to non-human-induced pressure relief and that there is no pressure inflection point, the insulation layer failure pressure difference is further determined based on the insulation layer parameters. That is, the maximum deviation between the expected pressure and the actual pressure of steam transmission in the pipeline caused by the complete failure of the insulation layer is determined. At this time, the insulation layer failure is judged based on the pressure inflection point and the insulation layer failure pressure difference. If the current flow deviation is within the influence range of the complete failure of the insulation layer or a certain section of the insulation layer, it can be determined that the insulation layer has at least partially failed, and a corresponding first alarm message is immediately generated to prompt technicians to go to the site for maintenance in a timely manner according to the best economic considerations. If the current flow deviation is found to be outside the influence range of the complete failure of the insulation layer, it can be determined that the complete failure of the insulation layer or pipeline rupture and leakage has occurred, and immediate action is required. Therefore, a corresponding second alarm message is generated.

[0061] In this embodiment of the invention, by further precise analysis of non-human-caused pressure relief factors, the actual factors causing flow deviations are determined, and the best suggestions for corresponding handling are provided to technicians. This provides a data basis for technicians to adopt the most economical maintenance plan, thereby further improving the company's operating efficiency.

[0062] After calculating and determining the precise demand adjustment amount, the initial demand forecast information is optimized to generate processed forecast information in real time. Upstream steam supply companies can then perform corresponding steam supply operations based on this processed forecast information, thereby effectively reducing heat loss and improving business efficiency while meeting the real-time steam demand of downstream companies.

[0063] However, in practical applications, the reliability of steam transmission in pipelines decreases as the transmission distance increases. Therefore, in order to ensure the core indicator of normal steam demand of downstream enterprises, a certain control margin needs to be adopted based on the actual predicted reliability.

[0064] In this embodiment of the invention, the method further includes: acquiring downstream demand big data and corresponding historical forecast data; generating a prediction reliability curve based on the pipeline length, the downstream demand big data, and the historical forecast data; generating a real-time compensation amount corresponding to the processed prediction information based on the prediction reliability curve; and optimizing the processed prediction information based on the real-time compensation amount to generate optimized prediction information.

[0065] In one possible implementation, after generating the processed prediction information, downstream demand big data and corresponding historical prediction data are further acquired. Based on the accuracy of the prediction results for different pipeline lengths, a corresponding prediction reliability curve is plotted. Based on the prediction reliability curve, a real-time compensation amount corresponding to the processed prediction information is generated. For example, it is initially determined that the steam output needs to be increased from 30 tons to 40 tons in 10 minutes, but the deviation margin is 20%. Therefore, the actual controlled output is 48 tons, thereby reducing waste and avoiding impact on the actual operation of the enterprise, thus meeting the actual needs.

[0066] In this embodiment of the invention, the prediction results are optimized by introducing big data and historical data. The dynamic calculation of real-time compensation is realized through the prediction reliability curve, which effectively offsets the influence of accidental factors such as single operating conditions and sensor errors. This makes the prediction results not only fit the real-time operating conditions, but also have good long-term stability. At the same time, the compensation margin is controlled within a precise and small range, which further improves the accuracy of steam demand prediction and improves the business efficiency of enterprises.

[0067] Please see Figure 2 Based on the same inventive concept, embodiments of the present invention provide a downstream steam demand forecasting device based on heat loss. The device includes: a heat loss calculation unit for acquiring downstream steam demand and determining the theoretical heat loss corresponding to the downstream steam demand; an initial forecasting unit for generating initial demand forecasting information based on the theoretical heat loss and the downstream steam demand; a flow simulation unit for performing virtual flow analysis based on the initial demand forecasting information and the theoretical heat loss to generate virtual steam flow; a flow acquisition unit for acquiring flow sensing data and determining the actual steam flow based on the flow sensing data; a deviation determination unit for determining the flow deviation based on the actual steam flow and the virtual flow data; and a demand forecasting unit for processing the initial demand forecasting information based on the flow deviation to generate processed forecasting information.

[0068] Furthermore, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the methods described in the embodiments of the present invention.

[0069] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above embodiments. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention.

[0070] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not describe the various possible combinations separately.

[0071] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a microcontroller, chip, or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0072] Furthermore, various different implementations of the present invention can be combined arbitrarily, as long as they do not violate the spirit of the present invention, they should also be regarded as the content disclosed in the present invention.

Claims

1. A method for predicting downstream steam demand based on heat loss, characterized in that, The method includes: Obtain downstream steam demand and determine the theoretical heat loss corresponding to the downstream steam demand; Initial demand forecast information is generated based on the theoretical heat loss and the downstream steam demand. Based on the initial demand forecast information and the theoretical heat loss, a virtual flow analysis is performed to generate a virtual steam flow rate; Acquire flow sensor data and determine the actual steam flow rate based on the flow sensor data; The flow deviation is determined based on the actual steam flow rate and the virtual flow rate data; The initial demand forecast information is processed based on the flow deviation to generate processed forecast information.

2. The method according to claim 1, characterized in that, Determining the theoretical heat loss corresponding to the downstream steam demand includes: Obtain the demand entity corresponding to the downstream steam demand; Determine the connection channels between the entity and the demand subject; Obtain the pipe geometry parameters, steam physical parameters, physical property data, and steam release compensation amount of the connecting pipe; The natural heat loss is determined based on the pipeline geometry parameters, the steam physical parameters, the physical property data, and the real-time ambient temperature of the connecting pipeline. The theoretical heat loss is determined based on the natural heat loss and the steam release compensation.

3. The method according to claim 2, characterized in that, The generation of initial demand forecast information based on the theoretical heat loss and the downstream steam demand includes: The downstream real-time steam demand value is determined based on the downstream steam demand. The upstream real-time steam supply value is determined based on the theoretical heat loss and the downstream real-time steam demand value. The transmission lag factor is determined based on the pipeline length and steam transmission speed. Initial demand forecast information is generated based on the upstream real-time steam supply value and the transmission lag factor.

4. The method according to claim 2, characterized in that, The process of processing the initial demand forecast information based on the flow deviation to generate processed forecast information includes: If the flow deviation is greater than a preset deviation threshold, a flow deviation segment is determined based on the flow sensing data; Acquire real-time pressure sensing data for the flow deviation segment; The flow deviation type of the flow deviation segment is determined based on the real-time pressure sensing data, and the flow deviation type includes artificial pressure relief and non-artificial pressure relief; Determine the demand adjustment amount based on the aforementioned flow deviation type; The initial demand forecast information is optimized based on the demand adjustment amount to generate processed forecast information.

5. The method according to claim 4, characterized in that, Determining the type of flow deviation in the flow deviation segment based on the real-time pressure sensing data includes: Generate a real-time pressure curve corresponding to the real-time pressure sensing data; Determine whether the real-time pressure curve has a pressure inflection point; If the pressure inflection point exists, determine whether a passive pressure relief valve exists in the flow deviation range; If the passive pressure relief valve exists, obtain the pressure relief pressure of the passive pressure relief valve, and determine whether the pressure relief pressure is consistent with the pressure inflection point. If the pressure relief pressure is consistent with the pressure inflection point, determine that the flow deviation type is non-human pressure relief. If the pressure relief pressure is inconsistent with the pressure inflection point, determine that the flow deviation type is human pressure relief. If the passive pressure relief valve does not exist, the flow deviation type is determined to be artificial pressure relief; If the pressure inflection point does not exist, the flow deviation type is determined to be non-human-induced pressure relief.

6. The method according to claim 5, characterized in that, The determination of demand adjustment based on the type of flow deviation includes: If the flow deviation type is artificial pressure relief, or if the flow deviation type is non-artificial pressure relief and the pressure inflection point exists: The initial adjustment amount is determined based on the real-time pressure sensing data and the pressure inflection point. The initial adjustment amount is optimized based on the transmission lag factor to generate the demand adjustment amount.

7. The method according to claim 5, characterized in that, The method further includes: If the flow deviation type is non-human-induced pressure relief and there is no pressure inflection point, the insulation layer failure pressure difference is determined based on the insulation layer parameters; Determine whether the insulation layer has failed based on the pressure inflection point and the pressure difference at which the insulation layer fails. If so, generate the first alarm message corresponding to the failure of the insulation layer; Otherwise, if a pipe rupture and leakage is confirmed, a second alarm message corresponding to the pipe rupture and leakage is generated.

8. The method according to any one of claims 1-7, characterized in that, The method further includes: Acquire big data on downstream demand and corresponding historical forecast data; A prediction reliability curve is generated based on the pipeline length, the downstream demand big data, and the historical forecast data. Based on the predicted reliability curve, a real-time compensation amount corresponding to the processed predicted information is generated. The processed prediction information is optimized based on the real-time compensation amount to generate optimized prediction information.

9. A downstream steam demand forecasting device based on heat loss, characterized in that, The device includes: A heat loss calculation unit is used to obtain downstream steam demand and determine the theoretical heat loss corresponding to the downstream steam demand. An initial prediction unit is used to generate initial demand prediction information based on the theoretical heat loss and the downstream steam demand. The flow simulation unit is used to perform virtual flow analysis based on the initial demand forecast information and the theoretical heat loss to generate virtual steam flow. A flow acquisition unit is used to acquire flow sensing data and determine the actual steam flow rate based on the flow sensing data; A deviation determination unit is used to determine the flow deviation based on the actual steam flow rate and the virtual flow rate data; The demand forecasting unit is used to process the initial demand forecasting information based on the traffic deviation to generate processed forecasting information.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the method described in any one of claims 1-8.

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