Terrestrial heat and solar energy coupling heat supply control method and system

Abstract

The invention relates to the field of heat supply control, in particular to a terrestrial heat and solar energy coupling heat supply control method and system. The method comprises the following steps: acquiring heat supply load prediction data and solar radiation prediction data of a target area, dynamically formulating and executing pre-preparation operation of a cascade flash evaporation reactor based on the data, and generating a reactor dynamic preheating scheme set; on this basis, geothermal fluid is introduced into a fluid self-flashing chamber, geothermal fluid self-flashing triggered based on pressure drop is executed, and a primary basic flashing information set is generated; on this basis, the remaining liquid fluid is guided to an enhanced boiling flash chamber, contact type enhanced boiling flash operation triggered based on the significant temperature difference is executed, and a secondary enhanced flash information set is generated; on the basis, multi-parameter dynamic feedback of geothermal fluid flow, chamber pressure and heat storage release rate is collected, and a collaborative optimization heat supply control set is generated. In the multi-energy coupling heat supply process, the heat supply quality can be guaranteed.

Description

Technical Field

[0001] This application relates to the field of heating control, and in particular to a method and system for controlling geothermal and solar coupled heating. Background Technology

[0002] In the field of renewable energy heating, geothermal energy is stable and reliable, while solar energy is clean and readily available. The coupling and complementarity of the two is a key path to improve the energy efficiency and low carbon level of district heating systems, which is of great strategic significance for building a new energy system and realizing the green transformation of the building sector.

[0003] However, existing coupled heating technologies lack intelligent control mechanisms to collaboratively predict multi-source parameters and dynamically optimize system operation when facing dynamically changing heating demands and intermittent solar energy input. This often leads to low energy utilization efficiency and delayed system response, making it difficult to minimize energy consumption and operating costs while ensuring heating quality. Summary of the Invention

[0004] This application provides a geothermal and solar coupled heating control method and system to solve the above-mentioned technical problems.

[0005] In a first aspect, this application provides a geothermal and solar coupled heating control method, the method comprising: acquiring target area heating load prediction data and solar irradiance prediction data; dynamically formulating and executing pre-preparation operations for a cascaded flash reactor based on the target area heating load prediction data and the solar irradiance prediction data, generating a set of dynamic preheating schemes for the reactor; introducing geothermal fluid into a fluid self-flash chamber based on the set of dynamic preheating schemes for the reactor, executing geothermal fluid self-flash based on pressure drop triggering, generating a primary basic flash information set; guiding the remaining liquid fluid to an enhanced boiling flash chamber based on the primary basic flash information set, executing a contact-type enhanced boiling flash operation based on significant temperature difference triggering, generating a secondary enhanced flash information set; and collecting multi-parameter dynamic feedback of geothermal fluid flow rate, chamber pressure, and heat storage release rate based on the primary basic flash information set and the secondary enhanced flash information set, generating a collaboratively optimized heating control set.

[0006] Through the above technical solutions, based on the intelligent coupling and cascade flash evaporation process of solar and geothermal energy, the comprehensive utilization rate of geothermal fluid quality is significantly improved, achieving higher total steam production and heating energy efficiency. At the same time, it has the ability to predict and dynamically optimize, and can flexibly adapt to fluctuations on both the source and load sides, ensuring heating stability while maximizing the contribution of solar energy, reducing auxiliary energy consumption, and improving overall economic efficiency.

[0007] Optionally, the generation of the reactor dynamic preheating scheme set includes: predicting the target values ​​of key thermodynamic parameters required by the cascade flash reactor to trigger the subsequent two-stage flash reactions based on the target area heating load prediction data and the solar irradiance prediction data; generating a reactor heating dynamic formulation strategy based on the target values ​​of key thermodynamic parameters, with the optimization objective of minimizing pre-preparation energy consumption and maximizing peak heating matching degree; driving the cascade flash reactor to perform preheating and pre-vacuuming operations based on the reactor heating dynamic formulation strategy, and monitoring the actual temperature value of the cascade flash reactor in real time until the temperature target value is reached; and integrating the target values ​​of key thermodynamic parameters and the reactor heating dynamic formulation strategy to generate the reactor dynamic preheating scheme set as the subsequent control benchmark.

[0008] Optionally, the cascade flash reactor includes: the cascade flash reactor is powered by solar photovoltaic panels to provide the electricity required for its preheating and operation, and includes a fluid self-flash chamber for performing the geothermal fluid self-flash triggered by a pressure drop, and an enhanced boiling flash chamber for performing the contact-type enhanced boiling flash operation triggered by a significant temperature difference; the geothermal fluid self-flash process is as follows: high-temperature geothermal fluid is introduced into a preset low-pressure environment in the chamber, causing it to undergo adiabatic expansion, thereby causing a portion of the fluid to vaporize instantaneously, forming a first stream of saturated steam and the remaining liquid fluid after the first flash; the contact-type enhanced boiling flash operation process is as follows: the remaining liquid fluid is directly sprayed or guided to a preheated high-temperature heat exchange wall, and the huge temperature difference between the fluid and the wall drives the fluid to undergo violent nucleation boiling and secondary vaporization on the wall, forming a second stream of saturated steam and the final waste liquid.

[0009] Optionally, the reactor heating dynamic formulation strategy includes: analyzing the type characteristics and day-night load variation patterns of the target area based on the target area heating load forecast data, and analyzing the intensity and effective duration of solar energy during the predicted day based on the solar irradiance forecast data; when the target area needs continuous and stable heating, or when the predicted day's solar energy is insufficient, generating a continuous preheating strategy to maintain a constant wall temperature of the enhanced boiling flash evaporation chamber; when the target area needs intermittent heating, and the predicted day's solar energy is sufficient, generating a timed enhanced preheating strategy with peak heating demand as the optimization target, wherein the enhanced preheating delays heat storage during periods of abundant solar energy and is concentratedly executed before the heating load climbs.

[0010] Optionally, generating the initial basic flash evaporation information set includes: based on the reactor dynamic preheating scheme set, confirming that the fluid self-flash evaporation chamber has reached the preset initial low-pressure environment and chamber wall temperature, and generating a first-level flash evaporation ready signal; responding to the first-level flash evaporation ready signal, dynamically adjusting the introduction flow rate and introduction pressure of the geothermal fluid according to the real-time heating load demand, and injecting the high-temperature geothermal fluid into the fluid self-flash evaporation chamber in the form of a controllable jet; in the fluid self-flash evaporation chamber, based on the pressure drop between the preset low pressure and the injected fluid, triggering the adiabatic self-flash evaporation process of the geothermal fluid, forming the first stream of saturated steam and the remaining liquid fluid after one flash evaporation; and synchronously monitoring and collecting the pressure and flow rate of the first stream of saturated steam, the temperature and flow rate of the remaining liquid fluid, and the real-time pressure of the fluid self-flash evaporation chamber in real time to generate the initial basic flash evaporation information set.

[0011] Optionally, the dynamic adjustment of the introduced flow rate and pressure of the geothermal fluid includes: analyzing the optimal geothermal fluid demand benchmark under the current target heating power based on the previous cycle heating efficiency fed back by the collaboratively optimized heating control set and the real-time solar-assisted heating potential indicated by the solar irradiance prediction data; using the optimal geothermal fluid demand benchmark as a set value and coupling the real-time pressure feedback of the fluid from the flash chamber, dynamically adjusting the variable frequency pump and pressure regulating valve on the geothermal fluid supply pipeline through a proportional-integral-derivative control algorithm; and synchronously updating the adjusted actual introduced flow rate, introduced pressure, and their deviation from the demand benchmark as key parameters to the initial basic flash information set.

[0012] Optionally, generating the secondary enhanced flash evaporation information set includes: based on the initial basic flash evaporation information set, analyzing the current temperature and flow rate of the remaining liquid fluid in real time, and combining it with a preset target wall temperature value to analyze the critical heat transfer temperature difference required to trigger effective secondary flash evaporation; determining whether the difference between the temperature of the remaining liquid fluid and the target wall temperature value is greater than or equal to the critical heat transfer temperature difference, and if so, generating a second-level flash evaporation trigger command; responding to the second-level flash evaporation trigger command, dynamically controlling the remaining liquid fluid to be uniformly distributed in atomized or thin-film form on the preheated high-temperature heat exchange wall surface according to the real-time heat storage state of the enhanced boiling flash evaporation chamber; triggering intense nucleation boiling and contact flash evaporation on the high-temperature heat exchange wall surface based on the huge solid-liquid temperature difference to form the second stream of saturated steam and the final waste liquid; synchronously monitoring and collecting the flow rate and temperature of the second stream of saturated steam, the temperature of the final waste liquid, and the temperature distribution of the high-temperature heat exchange wall surface in real time to generate the secondary enhanced flash evaporation information set.

[0013] Optionally, the dynamic control of the remaining liquid fluid includes: identifying local overheated and underheated areas on the wall surface based on the temperature distribution data of the high-temperature heat exchange wall surface in the secondary enhanced flash evaporation information set; for the identified local overheated areas, controlling the corresponding allocated nozzles to increase the jet flow rate or switch to a jet mode with finer atomization particle size to enhance the penetration and disturbance of the thermal boundary layer; for the identified local underheated areas, controlling the corresponding allocated nozzles to decrease the jet flow rate or switch to a flow mode that forms a stable and extended liquid film to improve the uniformity of fluid coverage and residence time.

[0014] Optionally, the generation of the collaboratively optimized heating control set includes: analyzing the instantaneous system energy efficiency ratio based on the total steam output and total geothermal fluid consumption of the two stages in real time according to the initial basic flash evaporation information set and the secondary enhanced flash evaporation information set; superimposing the instantaneous system energy efficiency ratio with the predicted solar-assisted potential to generate a dynamic heating capacity curve; tracking the heating load of the target area in real time with the dynamic heating capacity curve, and using a model predictive control algorithm to continuously optimize the reactor dynamic preheating scheme set, geothermal fluid introduction parameters, and secondary flash evaporation trigger threshold to generate the collaboratively optimized heating control set.

[0015] Secondly, this application provides a geothermal and solar coupled heating control system, the system comprising: a preheating scheme generation module, used to acquire target area heating load prediction data and solar irradiance prediction data, and based on the target area heating load prediction data and the solar irradiance prediction data, dynamically formulate and execute pre-preparation operations for a cascaded flash reactor, generating a set of dynamic preheating schemes for the reactor; a first flash evaporation module, used to introduce geothermal fluid into a fluid self-flash evaporation chamber based on the set of dynamic preheating schemes for the reactor, and execute geothermal fluid self-flash evaporation triggered by a pressure drop, generating a set of initial basic flash evaporation information; a second flash evaporation module, used to guide the remaining liquid fluid to an enhanced boiling flash evaporation chamber based on the set of initial basic flash evaporation information, and execute a contact-type enhanced boiling flash evaporation operation triggered by a significant temperature difference, generating a set of secondary enhanced flash evaporation information; and a coupled optimization control module, used to collect multi-parameter dynamic feedback of geothermal fluid flow rate, chamber pressure, and heat storage release rate based on the set of initial basic flash evaporation information and the set of secondary enhanced flash evaporation information, generating a set of synergistically optimized heating control. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram illustrating an application scenario provided in one embodiment of this application; Figure 2 A flowchart of a geothermal and solar coupled heating control method provided in one embodiment of this application; Figure 3 This is a schematic diagram of a geothermal and solar coupled heating control system provided in one embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0019] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0020] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0021] Existing coupled heating technologies lack intelligent control mechanisms to collaboratively predict multi-source parameters and dynamically optimize system operation when facing dynamically changing heating demands and intermittent solar energy input. This often leads to low energy utilization efficiency and delayed system response, making it difficult to minimize energy consumption and operating costs while ensuring heating quality.

[0022] Based on this, this application provides a geothermal and solar coupled heating control method and system. First, heating load and solar irradiance data are predicted to dynamically generate a preheating scheme for a cascaded flash reactor. During operation, high-temperature geothermal fluid is introduced into a pre-set low-pressure fluid flash chamber, where a sudden pressure drop triggers flash evaporation, generating the first stream of steam and yielding residual liquid fluid. Subsequently, this residual fluid is guided to a high-temperature wall surface preheated by solar energy (enhanced boiling flash chamber), where a large temperature difference triggers intense contact boiling flash evaporation, generating the second stream of steam. Finally, the system collects multi-parameter dynamic feedback from the two-stage flash evaporation process in real time, generating a collaboratively optimized heating control set, which is then output to the control personnel. Through the intelligent coupling and cascaded flash evaporation process of solar and geothermal energy, the comprehensive utilization rate of geothermal fluid quality is significantly improved, achieving higher total steam production and heating efficiency. Simultaneously, it possesses forward-looking prediction and dynamic feedback optimization capabilities, flexibly adapting to fluctuations on both the source and load sides, ensuring heating stability while maximizing solar energy contribution, reducing auxiliary energy consumption, and improving overall economic efficiency.

[0023] Figure 1 This is a schematic diagram illustrating an application scenario provided by this application. In multi-energy coupled heating processes, the method provided in this application can minimize energy consumption and operating costs while ensuring heating quality.

[0024] Specifically, the method of this application is applied to any server that communicates with a regional energy management system and a photovoltaic monitoring system. The server obtains target area heating load forecast data from the regional energy management system and solar irradiance forecast data from the photovoltaic monitoring system. First, it forecasts the heating load and solar irradiance data, dynamically generating a preheating scheme for a cascaded flash reactor. During operation, high-temperature geothermal fluid is introduced into a pre-set low-pressure fluid flash chamber, triggering self-flash evaporation using a sudden pressure drop, generating the first stream of steam and obtaining residual liquid fluid. Subsequently, this residual fluid is guided to a high-temperature wall surface preheated by solar energy (enhanced boiling flash chamber), where a large temperature difference triggers intense contact boiling flash evaporation, generating the second stream of steam. Finally, the system collects multi-parameter dynamic feedback from the two-stage flash evaporation process in real time, generating a collaboratively optimized heating control set, and outputting it to the control personnel.

[0025] For specific implementation details, please refer to the following examples.

[0026] Figure 2 This is a flowchart illustrating a geothermal and solar coupled heating control method according to an embodiment of this application. The method of this embodiment can be applied to servers in the above-described scenarios. Figure 2 As shown, the method includes: S201. Obtain the target area's heating load forecast data and solar irradiance forecast data. Based on the target area's heating load forecast data and solar irradiance forecast data, dynamically formulate and execute the pre-preparation operation of the cascade flash reactor, and generate a set of dynamic preheating schemes for the reactor.

[0027] The target area heating load forecast data can be the heating load demand curve for a future period predicted by machine learning models or physical models based on information such as building characteristics, historical energy consumption, weather forecasts, and human activity patterns of the target area (such as residential communities, commercial complexes, or industrial parks). The data comes from the regional energy management system. Solar irradiance forecast data can refer to the time-series data of solar irradiance intensity, sunshine duration, and cloud cover changes for a target area over a future period, predicted by meteorological forecast models, satellite remote sensing data, or ground monitoring stations. The data comes from the photovoltaic monitoring system. A cascade flash reactor is a specialized device that efficiently converts the thermal energy of geothermal fluids into steam for heating through two consecutive stages of different physical processes (the first stage is self-flash evaporation driven by a pressure drop, and the second stage is enhanced boiling flash evaporation driven by temperature difference and surface contact). A dynamic preheating scheme set for reactors can be a complete set of preheating strategies dynamically generated based on a comprehensive consideration of heating demand and the volatility of solar energy supply. This set includes preheating target parameters, execution timing, energy consumption budget, and expected effect assessment.

[0028] Specifically, coupling geothermal and solar energy for district heating is an important way to improve the utilization rate of clean energy and reduce dependence on fossil fuels. Geothermal fluids contain stable but limited-grade (temperature) heat energy, while solar energy is characterized by strong fluctuations but can provide high-grade heat energy. Traditional geothermal flash heating systems often have low utilization rates of geothermal fluid quality and are difficult to flexibly adapt to diurnal and seasonal load changes. This scheme introduces solar energy as an auxiliary and regulating energy source to drive a specially designed "cascade flash reactor" to achieve tiered, deep extraction and flexible output of geothermal energy. However, the efficient operation of this reactor is heavily dependent on its initial thermodynamic state before startup. Insufficient preheating will prevent the effective triggering of the subsequent enhanced flash process; excessive preheating or improper preheating timing will result in waste of solar energy and its own energy consumption, making it impossible to accurately match dynamic heating loads. Therefore, the necessity of this step lies in the fact that it constitutes the decision-making starting point for the intelligent coupling and dynamic adaptation of the entire method. By acquiring and integrating forward-looking information from the heating side (load forecasting) and the energy side (solar energy forecasting), this step aims to address the critical questions of when to preheat, to what extent to preheat, and how to preheat at minimal cost. It sets optimal initial conditions for subsequent physical energy conversion processes, ensuring that the cascade flash system can quickly reach high-efficiency operation when load demand arrives, while maximizing the use of free solar energy and minimizing system auxiliary energy consumption.

[0029] S202. Based on the reactor dynamic preheating scheme set, geothermal fluid is introduced into the fluid self-flash chamber, and geothermal fluid self-flash is performed based on pressure drop triggering, generating the initial basic flash information set.

[0030] Geothermal fluid can refer to high-temperature hot water or a steam-water mixture extracted from a geothermal well. The fluid flash chamber can be a specially designed first-stage processing unit in a cascaded flash reactor, maintaining a low-pressure environment below the geothermal fluid saturation pressure, pre-set by the pre-preparation process. The initial basic flash information set can be a set of parameters monitored and recorded in real time during the first flash, including key information such as the flow rate, temperature / pressure (enthalpy) of the first stream of saturated steam generated, and the temperature, flow rate, and enthalpy of the remaining liquid fluid after the first flash.

[0031] Specifically, geothermal fluid flash evaporation is one of the most direct and fastest traditional methods for utilizing geothermal energy. In this cascaded system, its use as the first stage is of significant strategic importance. First, it fulfills the fundamental function of "initial energy release and stable supply." As long as the geothermal fluid temperature is sufficient, a considerable amount of steam can be generated instantaneously under a preset low pressure, rapidly responding to basic or sudden increases in heating demand, ensuring the system's immediacy and basic reliability in heating. Second, this process occurs within a dedicated chamber, making the physical process relatively independent and rapid, facilitating control and monitoring. More importantly, it provides the necessary "raw material" for the second-stage deep energy extraction—the residual liquid fluid after the first flash evaporation. Although the pressure and saturation temperature of this fluid have decreased, it still contains a large amount of sensible and latent heat. The generation of the initial basic flash evaporation information set is crucial; it not only serves as the basis for evaluating the efficiency of the first-stage flash evaporation and monitoring the current operating status of the system, but also acts as a key intermediate variable and feedback signal, providing real-time data input for the operation settings of the second-stage flash evaporation (such as the required temperature difference) and subsequent system co-optimization.

[0032] S203. Based on the initial basic flash evaporation information set, the remaining liquid fluid is guided to the enhanced boiling flash evaporation chamber, and a contact-type enhanced boiling flash evaporation operation triggered by a significant temperature difference is performed to generate a secondary enhanced flash evaporation information set.

[0033] Enhanced boiling flash evaporation chambers can be the second-stage core processing unit in a cascaded flash reactor. They contain metal heat exchange walls or other highly efficient heat exchange structures that have been preheated to high temperatures through pre-preparation operations (typically by solar or electrical heating). The secondary enhanced flash evaporation information set can be a collection of parameters monitored and recorded during the second flash evaporation process. This primarily includes the flow rate and quality of the generated second stream of saturated steam, the temperature and flow rate of the final discharged waste liquid, and process parameters reflecting boiling intensity such as the wall temperature gradient and heat transfer coefficient.

[0034] Specifically, the residual liquid fluid after the first-stage self-flash evaporation still carries some of the initial heat energy. Direct discharge would result in significant energy waste and thermal pollution. The contact-enhanced boiling flash evaporation operation defined in this step is the key innovation of this scheme to achieve "deep extraction" and "efficiency breakthrough" of geothermal energy. It is essentially complementary and reinforcing to the first-stage self-flash evaporation in terms of mechanism and function: the first stage relies on volumetric flash evaporation occurring within the fluid due to a sudden drop in overall pressure, while the second stage relies on contact boiling heat transfer triggered by a large local temperature difference on the solid surface. This difference allows the second stage to overcome the limitation of weakened fluid driving potential (temperature difference, pressure difference) after the first stage, using externally input high-grade thermal energy (solar energy) as a "lever" to actively and forcibly "extract" the latent heat of vaporization from the low-temperature fluid, achieving deep recovery of low-grade waste heat. Its necessity lies in greatly improving the overall thermal efficiency and energy grade utilization rate of the system.

[0035] S204. Based on the initial basic flash evaporation information set and the secondary enhanced flash evaporation information set, collect multi-parameter dynamic feedback of geothermal fluid flow rate, chamber pressure and heat storage release rate to generate a collaboratively optimized heating control set.

[0036] Multi-parameter dynamic feedback can be a set of key physical quantities that reflect the real-time operating status of the system, collected in real time by a sensor network throughout the two-stage flash evaporation process. The collaborative optimization heating control set can be a set of instructions calculated using optimization algorithms (such as PID control) based on real-time feedback data and initial heating load prediction, used to coordinate the control of multiple actuators throughout the system.

[0037] Specifically, the cascaded flash evaporation system coupling geothermal and solar energy is a complex thermal system characterized by multiple variables, strong coupling, and dynamic changes on both the source (geothermal and solar energy) and load (heating load). Relying solely on feedforward pre-preparation and open-loop two-stage flash evaporation is insufficient to maintain the system under optimal operating conditions in the long term, nor can it cope with various disturbances encountered during actual operation (such as fluctuations in geothermal fluid parameters, sudden changes in solar energy input, and instantaneous load variations). Therefore, the multi-parameter dynamic feedback and closed-loop collaborative optimization introduced in this step are crucial for ensuring the adaptive, robust, and continuously efficient operation of the entire method. It solves the problem of transitioning from "static design optimization" to "dynamic operation optimization."

[0038] The method provided in this embodiment first predicts heating load and solar irradiance data to dynamically generate a preheating scheme for a cascaded flash reactor. During operation, high-temperature geothermal fluid is introduced into a pre-set low-pressure fluid flash chamber, where a sudden pressure drop triggers flash evaporation, generating the first stream of steam and yielding residual liquid fluid. Subsequently, this residual fluid is guided to a high-temperature wall surface preheated by solar energy (enhanced boiling flash chamber), where a large temperature difference triggers intense contact boiling flash evaporation, generating the second stream of steam. Finally, the system collects multi-parameter dynamic feedback from the two-stage flash evaporation process in real time, generating a collaboratively optimized heating control set and outputting it to the control personnel. Through the intelligent coupling of solar and geothermal energy and the cascaded flash evaporation process, the comprehensive utilization rate of geothermal fluid quality is significantly improved, achieving higher total steam production and heating efficiency. Simultaneously, it possesses forward-looking prediction and dynamic feedback optimization capabilities, flexibly adapting to fluctuations on both the source and load sides, ensuring heating stability while maximizing solar energy contribution, reducing auxiliary energy consumption, and improving overall economic efficiency.

[0039] In some embodiments, based on the target area heating load forecast data and solar irradiance forecast data, the target values ​​of key thermodynamic parameters required to trigger the subsequent two-stage flash reactions in the cascade flash reactor are predicted. Based on the target values ​​of key thermodynamic parameters, a dynamic reactor heating strategy is generated with the optimization objective of minimizing pre-preparation energy consumption and maximizing peak heating matching degree. Based on the dynamic reactor heating strategy, the cascade flash reactor is driven to perform preheating and pre-vacuuming operations, and the actual temperature value of the cascade flash reactor is monitored in real time until the temperature target value is reached. The target values ​​of key thermodynamic parameters and the dynamic reactor heating strategy are integrated to generate a set of dynamic preheating schemes for the reactor as a reference for subsequent control.

[0040] The target values ​​for key thermodynamic parameters can be the standard values ​​of the core thermodynamic parameters required for the cascade flash reactor to trigger the subsequent two-stage reactions of "pressure drop-type geothermal fluid self-flash evaporation" and "significant temperature difference-type contact-enhanced boiling flash evaporation". The dynamic formulation strategy for reactor heating can be a systematic strategy based on the target values ​​of key thermodynamic parameters, combined with the predicted characteristics of heating load and solar irradiance, with the dual optimization objectives of "minimizing pre-preparation energy consumption" and "maximizing peak heating matching degree". This involves dynamically adjusting the reactor's preheating timing, preheating intensity, preheating duration, and pre-vacuuming rhythm. Minimizing pre-preparation energy consumption refers to the total energy consumed by the cascade flash reactor during preheating and pre-vacuuming operations, mainly including the electrical energy consumed by the solar photovoltaic panels and the equivalent energy consumption corresponding to heat loss during preheating. This is a core indicator for measuring the economic efficiency of the reactor's pre-preparation stage. Maximizing peak heating matching degree refers to the degree of fit between the flash steam energy output by the reactor after pre-preparation (generated through the subsequent two-stage flash reaction) and the load demand of the target area during peak heating periods. The higher the matching degree, the more energy shortage or waste can be avoided during peak heating periods. Preheating and pre-vacuuming operations are two core pre-preparation operations performed on the cascaded flash reactor to meet the thermodynamic conditions of the two-stage flash reaction.

[0041] Specifically, traditional geothermal and solar coupled heating systems often employ fixed preheating schemes for their reactors. These schemes fail to consider the dynamic changes in the target area's heating load or the uncertainties of solar irradiance, leading to a significant mismatch between high preheating energy consumption and peak heating demand. For example, residential communities typically experience low daytime heating loads (e.g., only needing to meet a small amount of domestic hot water demand) and high nighttime heating loads (e.g., maintaining room temperature at 22°C). Traditional schemes, if preheating is performed at a fixed power level, result in daytime energy waste. Conversely, on cloudy or rainy days with insufficient solar irradiance (e.g., only 2 hours of effective irradiance), the fixed preheating strategy may fail to meet preheating standards due to insufficient photovoltaic power, preventing the subsequent flash evaporation reaction and impacting peak nighttime heating. Furthermore, key thermodynamic parameters in traditional technologies rely on empirical settings and are not dynamically adjusted according to load and irradiance. For instance, a fixed chamber preheating temperature of 75°C results in insufficient steam production when the heating load increases and energy waste when the load decreases. To address the above issues, this step first obtains predicted heating load data for the target area using a combination of regional heating network monitoring terminals, user metering equipment, and an LSTM model (e.g., predicting peak load for residential areas between 6 PM and 10 PM, with a peak demand of 500kW). Then, it obtains irradiance prediction data using a solar irradiance monitoring station and a meteorological prediction model (e.g., predicting a sunny day with irradiance reaching 800W / m² between 10 AM and 3 PM, effective for 5 hours). Based on these two types of data, and combined with parameters such as the chamber volume of the cascade flash reactor and the boiling point of the geothermal fluid (e.g., 95℃), it predicts target values ​​for key thermodynamic parameters (e.g., chamber preheating temperature). (80℃, pre-vacuum pressure 0.05MPa); aiming to minimize energy consumption and maximize peak matching degree, a heating strategy is generated (e.g., if the residential area requires intermittent heating and has sufficient solar energy, a time-selective enhanced preheating strategy is formulated, using photovoltaic power-powered heat storage to delay preheating from 10:00 to 15:00, and concentrating on increasing heating power at 17:00); the reactor is driven to perform preheating and pre-vacuuming operations through photovoltaic-powered heating components, and the chamber temperature is monitored in real time through a PT100 temperature sensor until it stabilizes at 80℃; finally, the key parameter target values ​​and heating strategies are integrated to generate a set of dynamic preheating schemes for the reactor, including temperature curves, pre-vacuuming rhythm, etc.

[0042] The method provided in this embodiment breaks through the limitations of traditional fixed preheating schemes by formulating a dynamic preheating strategy, enabling the preheating operation of the reactor to adapt to load fluctuations and solar energy changes in real time. That is, it ensures preheating intensity during peak load, reduces ineffective energy consumption during off-peak load, makes full use of clean energy when solar energy is abundant, and stabilizes the preheating state when solar energy is insufficient, significantly improving the flexibility and adaptability of the preheating scheme.

[0043] In some embodiments, the cascade flash reactor is powered by solar photovoltaic panels to provide the electricity required for its preheating and operation, and includes a fluid flash chamber for performing geothermal fluid flashing triggered by a pressure drop, and an enhanced boiling flash chamber for performing contact-based enhanced boiling flashing operation triggered by a significant temperature difference. The geothermal fluid flashing process is as follows: high-temperature geothermal fluid is introduced into a preset low-pressure environment in the chamber, causing it to undergo adiabatic expansion, thereby causing a portion of the fluid to vaporize instantaneously, forming a first stream of saturated steam and the remaining liquid fluid after the first flash. The contact-based enhanced boiling flashing operation is as follows: the remaining liquid fluid is directly sprayed or guided to a preheated high-temperature heat exchange wall, and the huge temperature difference between the fluid and the wall drives the fluid to undergo violent nucleation boiling and secondary vaporization on the wall, forming a second stream of saturated steam and the final waste liquid.

[0044] Pressure drop triggering can be a flash evaporation process where a significant pressure difference is created between a preset low-pressure environment and the geothermal fluid's own pressure within the fluid flash evaporation chamber, triggering adiabatic expansion of the geothermal fluid and resulting in the instantaneous vaporization of a portion of the fluid. This is the primary energy extraction process of geothermal fluids. Geothermal fluid flash evaporation can be a complete process where, after high-temperature geothermal fluid enters the preset low-pressure environment of the fluid flash evaporation chamber, it undergoes adiabatic expansion triggered by a pressure drop without external heating, causing the fluid temperature to rapidly decrease to the saturation temperature at the corresponding pressure, and a portion of the fluid instantly transforms into a gaseous state. The fluid flash evaporation chamber can be the primary flash evaporation module of a cascaded flash evaporation reactor, specifically designed to perform "geothermal fluid flash evaporation based on pressure drop triggering," and the chamber is sealed and pressure-adjustable. Adiabatic expansion can be a physical process where high-temperature geothermal fluid enters the preset low-pressure fluid flash evaporation chamber and rapidly expands in a sealed environment with almost no heat exchange with the outside environment. Instantaneous vaporization of a fluid can refer to the phenomenon where, during the adiabatic expansion of a geothermal fluid, its temperature drops to the saturation temperature at the corresponding pressure, causing a portion of the liquid geothermal fluid to transform into gaseous saturated steam within a very short time. The first stream of saturated steam can be a gaseous product generated during the self-flash evaporation process of the geothermal fluid in the flash evaporation chamber, with its temperature and pressure matching the preset low-pressure environment of the chamber. The remaining liquid fluid can be the portion of the geothermal fluid that remains liquid after the first-stage flash evaporation in the flash evaporation chamber without vaporization. Contact-type enhanced boiling flash evaporation involves directly spraying or guiding the remaining liquid fluid after the first flash evaporation into contact with the preheated high-temperature heat exchange wall surface within the enhanced boiling flash evaporation chamber. Utilizing the significant temperature difference between the wall surface and the fluid, a complete process is initiated, stimulating vigorous nucleus boiling and completing secondary vaporization. The high-temperature heat exchange wall surface can be the surface of a heat exchange structure within the enhanced boiling flash evaporation chamber, preheated to a set high temperature by a heating component powered by solar photovoltaic panels. Vigorous nucleo-boiling refers to a boiling state in which a large number of bubbles are rapidly generated and violently grow and detach from the fluid after the remaining liquid fluid comes into contact with a high-temperature heat exchange wall under the influence of a huge temperature difference. In this state, the heat transfer coefficient is extremely high, and the fluid's thermal energy can be converted into latent heat of vaporization in a short time. The second stream of saturated steam can be a gaseous product generated in the enhanced boiling flash evaporation chamber through contact-type enhanced boiling flash evaporation. Its temperature matches the temperature of the high-temperature heat exchange wall and the saturation temperature after the fluid's secondary vaporization, and together with the first stream of saturated steam, it constitutes the heat energy output carrier of the heating system. The final waste liquid can be the liquid waste from the geothermal fluid that has completely lost its usability after two stages of flash evaporation.

[0045] Specifically, traditional geothermal heating technologies mostly employ single-stage flash evaporation or direct heat exchange, which suffer from significant drawbacks such as low thermal energy utilization, poor equipment adaptability, and reliance on external energy sources. Single-stage flash evaporation can only extract a portion of the easily vaporizable heat energy from the geothermal fluid, with the remaining liquid fluid (e.g., at a temperature still reaching 60°C) carrying a large amount of heat energy being directly discharged, resulting in severe energy waste. Direct heat exchange easily leads to scaling on the heat exchange surface, causing a continuous decline in heat transfer efficiency. Furthermore, traditional equipment relies on external power grid supply, increasing operating costs, contradicting the initial goal of clean energy utilization, and being unable to adapt to geothermal fluids with different pressures and viscosities (e.g., low-pressure fluids are difficult to fully vaporize with single-stage flash evaporation). To address the above issues, this cascaded flash reactor consists of solar photovoltaic panels (powering preheating components, vacuum equipment, etc.), a fluid self-flash chamber, and an enhanced boiling flash chamber. First, the fluid is pre-evacuated from the flash chamber to a preset low-pressure environment (e.g., 0.03 MPa) using vacuum equipment. High-temperature geothermal fluid (e.g., 120℃, 1.0 MPa) is then introduced, causing it to expand adiabatically within the chamber, reducing its temperature to the corresponding saturation temperature (e.g., 69℃). Part of the fluid instantly vaporizes to generate the first stream of saturated steam (e.g., 69℃, 0.03 MPa). The remaining liquid fluid (e.g., 69℃) is transported to the enhanced boiling flash chamber via a guide pipe and directly sprayed into fine droplets through atomizing nozzles. These droplets contact the high-temperature heat exchange wall, heated to 150℃ by the photovoltaic panels. A significant temperature difference of 81℃ drives vigorous nucleo-boiling, achieving secondary vaporization to generate the second stream of saturated steam (e.g., 100℃, 0.1 MPa). Finally, the waste liquid (e.g., 50℃) is treated to meet discharge standards or reinjected into the underground reservoir.

[0046] The method provided in this embodiment, based on a two-stage differentiated flash chamber design and combined with solar photovoltaic power supply, first extracts easily vaporizable heat energy through self-flash evaporation by a sudden pressure drop, and then further extracts the remaining heat energy through enhanced boiling flash evaporation by temperature difference. At the same time, it optimizes the contact mode between the fluid and the heat exchange surface, accurately solving the problems of waste, poor adaptability and reliance on non-clean energy in traditional technologies. It is the core of improving the energy efficiency and environmental protection of coupled heating systems.

[0047] In some embodiments, based on the target area heating load forecast data, the type characteristics and day-night load variation patterns of the target area are analyzed, and based on the solar irradiance forecast data, the intensity and effective duration of solar energy during the predicted day are analyzed; when the target area needs continuous and stable heating, or when the predicted solar energy is insufficient during the day, a continuous preheating strategy to maintain a constant wall temperature of the enhanced boiling flash evaporation chamber is generated; when the target area needs intermittent heating, and the predicted solar energy is sufficient during the day, a timed enhanced preheating strategy with peak heating demand as the optimization target is generated, wherein the enhanced preheating is delayed during the period of abundant solar energy and is concentratedly executed before the heating load climbs.

[0048] The target area's type characteristics can be defined by its inherent heating demand attributes due to its purpose and user group composition, categorized into "requiring continuous and stable heating" and "requiring intermittent heating." For example, hospitals and industrial production areas belong to the former, while residential communities and commercial complexes belong to the latter. The diurnal load variation pattern can be defined as the fluctuation pattern of the heating load in the target area over a 24-hour period (day and night), reflecting the rhythm of load changes over time, such as a "stable mode" for areas with continuous heating and a "low daytime, high nighttime mode" for areas with intermittent heating. Continuous preheating strategies can be designed for scenarios with continuous and stable heating demand or insufficient solar energy. The core is to maintain the enhanced boiling flash chamber wall temperature at a constant target value by dynamically adjusting the power supply, ensuring the reactor always has stable flashing conditions. Time-selective enhanced preheating strategies can be designed for scenarios with intermittent heating demand and sufficient solar energy. The core is "peak-shifting heat storage + peak-hour enhancement," delaying heat storage during periods of abundant solar energy and concentrating on increasing preheating intensity before the heating load rises. Delayed heat storage can be achieved by controlling the heating components to operate at medium power during periods of abundant solar energy but low heating load, storing the heat energy converted from solar energy in the chamber walls and insulation layer, without immediately performing full-load preheating, thus avoiding energy waste. Heating load ramp-up can refer to the preparatory period when the heating load in the target area is about to transition from off-peak to peak hours, such as 5:00 PM to 6:00 PM in residential areas; this period is a critical window for centralized preheating.

[0049] Specifically, the reactor preheating strategy of traditional geothermal and solar coupled heating systems has a serious flaw: it applies a one-size-fits-all approach without distinguishing between the target area's heating type and the dynamic changes in solar irradiance. This leads to both energy waste and unstable heating. For example, in hospitals requiring 24-hour continuous heating, the traditional fixed-power preheating strategy cannot maintain stable wall temperatures during cloudy or rainy days when solar energy is insufficient (e.g., effective duration only 2 hours, intensity 300W / ㎡). The fluctuation range exceeds ±10℃, resulting in a sharp drop in flash steam production and affecting medical heating. In contrast, in residential areas with intermittent heating, the traditional continuous preheating strategy heats at full power even when solar energy is abundant during the day (e.g., intensity 800W / ㎡, effective duration 5 hours) but the load is only 100kW (only 40% of the nighttime peak), resulting in energy waste. Furthermore, without heat storage before the nighttime load rises, the wall temperature is insufficient to quickly meet the heating demand. To address the above issues, this step involves collecting historical data through heating network monitoring terminals and user heat metering devices. This data is then combined with an LSTM model to generate predicted heating load data for the target area (e.g., a hospital with a constant 300kW load over 24 hours, and residential areas with a 100kW load during the day (10:00-16:00) and a 400kW load at night (18:00-22:00). Irradiance data is obtained through solar irradiance monitoring stations and weather forecast models (e.g., for the hospital area, a cloudy / rainy day with an intensity of 300W / ㎡ and an effective duration of 2 hours; for the residential area, a sunny day with an intensity of 800W / ㎡ and an effective duration of 5 hours). After analyzing the area type (hospitals provide continuous and stable heating, while residential areas provide intermittent heating) and solar energy conditions, the hospital generates a continuous preheating strategy, which uses photovoltaic panels and energy storage devices to dynamically adjust the heating power and maintain a constant wall temperature of 150℃ (fluctuation ±5℃) in the enhanced boiling flash evaporation chamber. The residential area generates a timed enhanced preheating strategy, which uses 60% of the rated power to store heat during the solar energy abundant period from 10:00 to 15:00 (maintaining the wall temperature at 100℃), and then heats at full power before the heating load climbs up at 17:00, raising the wall temperature to 150℃ within 1 hour to meet the peak demand at night.

[0050] By differentiating between areas with continuous and stable heating and areas with intermittent heating, this embodiment generates differentiated preheating strategies, avoiding the mismatch between demand and strategy caused by the traditional one-size-fits-all approach. This ensures the heating stability of different types of areas—areas with continuous heating can maintain constant wall temperature and steam output, while areas with intermittent heating can accurately meet heating needs during peak hours.

[0051] In some embodiments, based on the reactor dynamic preheating scheme set, it is confirmed that the fluid self-flash chamber has reached the preset initial low-pressure environment and chamber wall temperature, and a first-stage flash ready signal is generated; in response to the first-stage flash ready signal, the introduction flow rate and introduction pressure of the geothermal fluid are dynamically adjusted according to the real-time heating load demand, and the high-temperature geothermal fluid is injected into the fluid self-flash chamber in the form of a controllable jet; in the fluid self-flash chamber, based on the pressure drop between the preset low pressure and the injected fluid, the adiabatic self-flash process of the geothermal fluid is triggered, forming a first stream of saturated steam and the remaining liquid fluid after one flash; the pressure and flow rate of the first stream of saturated steam, the temperature and flow rate of the remaining liquid fluid, and the real-time pressure of the fluid self-flash chamber are monitored and collected in real time to generate an initial basic flash information set.

[0052] The first-stage flash evaporation readiness signal can be an automatic trigger signal generated by the system when the pressure of the fluid in the flash chamber reaches the preset initial low-pressure environment and the chamber wall temperature reaches the target value. This signal indicates that the first-stage flash evaporation can be started and is a prerequisite for the subsequent introduction of geothermal fluid. The controllable jet form can be achieved by using a flow regulating device and a jet structure to inject geothermal fluid into the chamber in a jet state with precise control over the flow rate and direction, ensuring uniform distribution of the fluid within the chamber and guaranteeing the stability of the flash evaporation process.

[0053] Specifically, traditional geothermal flash steam technology suffers from several drawbacks, including a lack of pre-condition verification, rigid parameter control, and incomplete data acquisition. Geothermal fluid is often introduced blindly without confirming whether the chamber has reached the preset low pressure or wall temperature. For example, if the preset initial low pressure is 0.05 MPa but the pressure only reaches 0.08 MPa before startup, the geothermal fluid vaporization rate drops from the designed 30% to 18%, resulting in significant heat energy waste. Furthermore, the fixed flow rate and pressure cannot adapt to real-time heating load fluctuations. For instance, during peak evening heating periods in residential areas, steam production is insufficient, while during off-peak hours, excessive fluid injection leads to steam venting and waste. Additionally, monitoring only a single parameter results in insufficient data support. To address the above issues, this step, based on the reactor's dynamic preheating scheme set, uses pressure and temperature sensors within the chamber to confirm that the fluid has reached the preset initial low-pressure environment (e.g., 0.04 MPa) and target chamber wall temperature (e.g., 80°C) in the flash evaporation chamber. The system automatically generates a first-stage flash evaporation ready signal. Upon receiving this signal, real-time heating load demand (e.g., 450 kW of heat energy required during peak evening heating in residential areas) is obtained through flow and temperature sensors in the heating network. Combined with the physical parameters of the high-temperature geothermal fluid (e.g., extraction temperature 110°C), the optimal inlet flow rate (e.g., 5 m³ / h) and inlet pressure (e.g., 0.8 MPa) are determined. This is then achieved through the geothermal fluid supply pipe. The variable frequency pump and pressure regulating valve on the road inject geothermal fluid into the chamber in a controllable jet form. Utilizing the sudden drop effect of the injection pressure and the preset low pressure in the chamber, adiabatic self-flash evaporation is triggered, forming the first stream of saturated steam (e.g., temperature 75℃, pressure 0.04MPa, flow rate 1.5m³ / h) and residual liquid fluid (e.g., temperature 75℃, flow rate 3.5m³ / h). Simultaneously, multi-dimensional parameters are collected through pressure and flow sensors in the steam output pipeline, temperature and flow sensors in the residual fluid outlet pipeline, and real-time pressure sensors in the chamber. After integrating and formatting these data, a complete initial basic flash evaporation information set is generated, providing core data support for subsequent processes.

[0054] The method provided in this embodiment, through rigorous confirmation of flash evaporation readiness conditions, dynamic adaptation of load adjustment parameters, controllable jet injection, and all-dimensional monitoring, precisely solves the problems of extensive control, poor load matching, and incomplete data in traditional technologies, ensuring that the first-stage flash evaporation is fully stable and providing reliable data support for subsequent second-stage flash evaporation and synergistic optimization. This is the key to improving system energy efficiency and heating stability.

[0055] In some embodiments, based on the previous cycle heating efficiency fed back by the collaboratively optimized heating control set and the real-time solar-assisted heating potential indicated by solar irradiance prediction data, the optimal geothermal fluid demand benchmark under the current target heating power is analyzed; using the optimal geothermal fluid demand benchmark as the setpoint, and coupled with the real-time pressure feedback of the fluid from the flash chamber, the variable frequency pump and pressure regulating valve on the geothermal fluid supply pipeline are dynamically adjusted through a proportional-integral-derivative control algorithm; the adjusted actual inlet flow rate, inlet pressure, and their deviation from the demand benchmark are synchronously updated to the initial basic flash information set as key parameters.

[0056] The heating efficiency of the previous cycle can be the ratio of the total heat energy output by the system to the sum of the total heat energy consumed by the geothermal fluid and the equivalent energy of the solar-assisted electricity within the previous complete heating cycle (e.g., 1 hour). This reflects the energy-saving and efficient operation of the system in the previous cycle. The real-time solar-assisted heating potential is calculated based on solar irradiance prediction data, combined with the power generation efficiency of solar photovoltaic panels and the electricity demand for reactor preheating and operation. It represents the maximum capacity of solar energy to replace or supplement geothermal heating in the current period and is a key indicator for measuring the value of solar energy utilization. The optimal geothermal fluid demand benchmark can be the most economical and efficient combination of geothermal fluid inlet flow rate and inlet pressure, calculated under the current target heating power, by integrating the heating efficiency feedback from the previous cycle and the real-time solar-assisted heating potential. This is the core basis for regulation and operation. The proportional-integral-derivative (PI-D) control algorithm is a commonly used closed-loop control algorithm in industry. Through the coordinated operation of the proportional (P), integral (I), and derivative (D) components, it dynamically outputs a control signal based on the deviation between the setpoint and the actual value, achieving precise and rapid adjustment of the controlled object. It features fast response and strong stability. A variable frequency pump, installed on a geothermal fluid transport pipeline, adjusts its speed by changing the power supply frequency, thereby precisely controlling the fluid flow rate. It is the core actuator for achieving dynamic flow regulation. A pressure regulating valve, also installed on a geothermal fluid transport pipeline, adjusts the fluid pressure within the pipeline by changing the valve core opening, achieving dynamic pressure regulation. It works in conjunction with the variable frequency pump to complete parameter adjustment.

[0057] Specifically, traditional geothermal fluid introduction parameter regulation suffers from drawbacks such as lack of feedback optimization, lack of coordination with clean energy, and low regulation accuracy: it often uses fixed parameters or manual fine-tuning without considering the heating efficiency of the previous cycle. For example, if the heating efficiency of the previous cycle is only 65% ​​(lower than the design value of 80%), it may still inject geothermal fluid at the original flow rate of 5 m³ / h and pressure of 0.9 MPa, resulting in wasted geothermal fluid. Furthermore, it ignores the potential of solar energy assistance, and when solar energy is abundant (such as an immediate auxiliary heating potential of 100 kW), it still injects excessive amounts of geothermal fluid, violating the concept of coupled heating. At the same time, it lacks precise algorithm support, and its response is lagging when the chamber pressure changes suddenly, which can easily lead to flash evaporation instability. To address the above issues, this step extracts the heating efficiency of the previous cycle (e.g., 72%) from the collaboratively optimized heating control set, analyzes the real-time solar-assisted heating potential (e.g., 120kW) based on solar irradiance prediction data, determines the current target heating power (e.g., 380kW) based on the real-time heating load, and comprehensively calculates the optimal geothermal fluid demand baseline (introduced flow rate 4.2m³ / h, introduced pressure 0.75MPa). This baseline is used as the setpoint for the PID control algorithm, coupled with real-time pressure feedback from the fluid flash chamber (e.g., 0.042MPa). The PID algorithm then... The proportional element quickly responds to deviations, the integral element eliminates steady-state errors, and the derivative element predicts changing trends, generating control signals that are transmitted to the variable frequency pump and pressure regulating valve on the geothermal fluid supply pipeline. The variable frequency pump reduces the power supply frequency from 50Hz to 42Hz, and the pressure regulating valve adjusts the valve core opening from 60% to 52%, accurately adjusting the actual introduced flow rate and pressure to the target values. Finally, the actual parameters (4.2m³ / h, 0.75MPa) and deviation values ​​(both 0) after adjustment are collected and synchronously updated to the initial basic flash evaporation information set, providing accurate data support for subsequent processes.

[0058] The method provided in this embodiment optimizes the demand benchmark through efficiency feedback from the previous cycle, coordinates solar energy potential, and precisely adjusts the system using a PID algorithm. It also records deviation values ​​to improve the data, accurately solving the problems of inefficiency, waste, and slow response of traditional technologies. This achieves dynamic matching of parameters with load and energy supply, which is the core of ensuring system energy efficiency and stability.

[0059] In some embodiments, based on the initial basic flash evaporation information set, the current temperature and flow rate of the remaining liquid fluid are analyzed in real time, and combined with the preset target wall temperature value, the critical heat transfer temperature difference required to trigger effective secondary flash evaporation is analyzed; it is determined whether the difference between the temperature of the remaining liquid fluid and the target wall temperature value is greater than or equal to the critical heat transfer temperature difference. If it is satisfied, a second-level flash evaporation trigger command is generated; in response to the second-level flash evaporation trigger command, according to the real-time heat storage state of the enhanced boiling flash evaporation chamber, the remaining liquid fluid is dynamically controlled to be uniformly distributed on the preheated high-temperature heat exchange wall in the form of atomization or film; on the high-temperature heat exchange wall, based on the huge solid-liquid temperature difference, intense nucleation boiling and contact flash evaporation are triggered to form a second stream of saturated steam and final waste liquid; the flow rate and temperature of the second stream of saturated steam, the temperature of the final waste liquid, and the temperature distribution of the high-temperature heat exchange wall are monitored and collected in real time to generate a secondary enhanced flash evaporation information set.

[0060] The critical heat transfer temperature difference can be the minimum temperature difference required to trigger effective secondary flash evaporation of the remaining liquid fluid, i.e., the lower limit of the difference between the temperature of the remaining liquid fluid and the preset target wall temperature. Below this difference, secondary flash evaporation cannot proceed sufficiently. The second-stage flash evaporation trigger command can be a control signal automatically generated by the system to start the second-stage flash evaporation operation when the difference between the temperature of the remaining liquid fluid and the preset target wall temperature reaches or exceeds the critical heat transfer temperature difference. It is a key triggering mechanism connecting all stages of the second-stage flash evaporation. The real-time heat storage status can be the total amount of heat energy stored and released in real time in the enhanced boiling flash evaporation chamber (including the high-temperature heat exchange wall). It is comprehensively characterized by parameters such as wall temperature distribution and chamber ambient temperature, and is an important reference for dynamically controlling the state of the remaining liquid fluid. Atomization or film formation can be two distribution forms of residual liquid fluid on high-temperature heat exchanger walls. Atomization is when the fluid is atomized into fine droplets (with a particle size of 10-100μm) through a nozzle, while film formation is when the fluid forms a uniform and continuous liquid film along the wall (with a thickness of 0.1-1mm). Both forms are designed to improve the heat transfer efficiency between the fluid and the wall.

[0061] Specifically, the two-stage flash evaporation technology may still have defects such as blind triggering, fixed form, and one-sided monitoring: the critical heat transfer temperature difference is not clearly defined, and flash evaporation is often started when the temperature difference is insufficient. For example, it is started when the remaining liquid fluid temperature is 70°C and the wall temperature is 120°C (temperature difference of 50°C, not reaching the critical 60°C), resulting in a secondary vaporization rate of only 15% and a waste liquid temperature of 65°C, which is a serious waste of heat energy; moreover, the fluid form is fixed, and the atomization form is still used when the heat storage is insufficient, and the droplets vaporize before sufficient heat transfer, resulting in a 30% decrease in steam production; only a single parameter is monitored, and the data support is insufficient. To address the above issues, this step analyzes the current temperature (e.g., 75℃) and flow rate (e.g., 3.5 m³ / h) of the remaining liquid fluid from the initial basic flash evaporation information set. It extracts the preset target wall temperature (e.g., 150℃) from the reactor dynamic preheating scheme set and calculates the critical heat transfer temperature difference (e.g., 55℃) based on fluid physical properties (e.g., boiling point 95℃). If the fluid temperature and wall temperature difference is 75℃ ≥ 55℃, a second-stage flash evaporation trigger command is generated. The real-time heat storage status of the enhanced boiling flash evaporation chamber (e.g., average wall temperature 152℃, heat storage...) is collected using a temperature sensor array and a heat flow sensor. With sufficient heat, the control nozzles switch the fluid to an atomized form (droplet diameter 30μm) and spray it evenly on the high-temperature heat exchange wall. The solid-liquid temperature difference of 77℃ triggers intense nucleation boiling and contact flash evaporation, generating a second stream of saturated steam (e.g., 120℃, 2.8m³ / h) and final waste liquid (e.g., 45℃). Through the flow and temperature sensors of the steam pipeline, the temperature sensor of the waste liquid pipeline, and the temperature sensor array embedded in the wall, multi-dimensional parameters are collected simultaneously and integrated into a complete set of secondary enhanced flash evaporation information, providing core data support for subsequent collaborative optimization of the heating control set.

[0062] The method provided in this embodiment scientifically determines the triggering conditions based on the calculated critical heat transfer temperature difference, dynamically controls the fluid morphology according to the real-time heat storage state of the chamber, and monitors parameters in all dimensions. This accurately solves the problems of inefficiency, poor adaptability, and incomplete data in traditional technologies, ensuring sufficient and stable secondary flash evaporation and providing complete data for collaborative optimization of heating. This is the key to improving the system's thermal energy utilization rate.

[0063] In some embodiments, based on the temperature distribution data of the high-temperature heat exchange wall surface collected by the secondary enhanced flash evaporation information, local overheated areas and local underheated areas of the wall surface are identified; for the identified local overheated areas, the corresponding allocated nozzles are controlled to increase the jet flow rate or switch to a spray mode with finer atomization particle size to enhance the penetration and disturbance of the thermal boundary layer; for the identified local underheated areas, the corresponding allocated nozzles are controlled to decrease the jet flow rate or switch to a flow mode that forms a stable and extended liquid film to improve the uniformity of fluid coverage and residence time.

[0064] Localized overheating zones can be localized areas on high-temperature heat exchanger walls where the temperature is significantly higher than the preset target wall temperature (e.g., exceeding 5°C). In these areas, heat cannot be carried away by the fluid in time, leading to scaling, corrosion, and low heat transfer efficiency. Localized underheating zones can be localized areas on high-temperature heat exchanger walls where the temperature is significantly lower than the preset target wall temperature (e.g., below 5°C). In these areas, insufficient fluid coverage or short residence time results in inadequate heat transfer, and the remaining heat energy of the liquid fluid is not effectively extracted.

[0065] Specifically, the two-stage flash evaporation technology suffers from a core flaw: a fixed spray pattern that ignores localized differences in wall thermal state. This leads to low heat transfer efficiency and severe equipment wear. Due to factors such as fluctuations in geothermal fluid flow and changes in solar irradiance, uneven temperature distribution is inevitable on high-temperature heat exchange walls. Traditional technologies, employing a one-size-fits-all fixed spray pattern (such as single atomization or liquid film), cannot be adapted to these variations. For example, in a system with a preset target wall temperature of 150°C, the actual operating temperature in some areas reaches 160°C (localized overheating zone). Because the fluid cannot effectively penetrate the thermal boundary layer, heat accumulation leads to scaling on the wall, reducing the heat transfer coefficient by 30%. In another area, the temperature is only 140°C (localized underheating zone). Due to the extremely short fluid residence time (only 0.5 seconds), the vaporization rate is only 12%, and the waste liquid temperature still reaches 55°C, resulting in significant residual heat. To address the above issues, this step extracts temperature distribution data of the high-temperature heat exchanger wall from the secondary enhanced flash evaporation information. This data is collected by a 3×6 array PT100 temperature sensor embedded in the wall (e.g., if the preset target wall temperature is 150℃, the monitoring display shows 158-162℃ in the upper left corner and 143-145℃ in the upper right corner). The monitored temperatures are compared with the target values, defining areas exceeding the target value by more than 5℃ as locally overheated areas and areas below by more than 5℃ as locally underheated areas. Based on this, the upper left corner is determined to be an overheated area and the upper right corner an underheated area. For the overheated areas, the corresponding nozzles are controlled to increase the jet velocity from 2m / s to 3m / s, switching... The atomization particle size was reduced to a finer setting (droplet size reduced from 30μm to 15μm) to enhance penetration and disturbance of the thermal boundary layer (0.1mm thickness). For underheated areas, the jet velocity was reduced from 2m / s to 1.2m / s by controlling the corresponding distribution nozzles, switching to a stable extended liquid film mode (liquid film thickness 0.4mm) to improve fluid coverage uniformity (from 85% to 98%) and residence time (from 0.5 seconds to 1.2 seconds). After adjustment, the temperature was monitored in real time by a temperature sensor array. If temperature deviation still existed, further fine-tuning was performed until the temperature of each area of ​​the wall stabilized at 150℃±2℃ to ensure optimal heat transfer efficiency.

[0066] The method provided in this embodiment accurately identifies local overheated / underheated areas based on extracted wall temperature distribution data, and adjusts the spray pattern accordingly. Overheated areas are enhanced with turbulent heat transfer, while underheated areas have optimized coverage and residence time. This fundamentally solves the problems of heat transfer imbalance, energy waste, and equipment scaling associated with traditional technologies, achieving refined control of two-stage flash evaporation. This is key to improving heat transfer efficiency and protecting equipment.

[0067] In some embodiments, the instantaneous system energy efficiency ratio is analyzed in real time based on the initial basic flash evaporation information set and the secondary enhanced flash evaporation information set, according to the total steam output of the two stages and the total geothermal fluid consumption. The instantaneous system energy efficiency ratio is superimposed with the predicted solar-assisted potential to generate a dynamic heating capacity curve. The heating load of the target area is tracked in real time using the dynamic heating capacity curve. Through model predictive control algorithms, the dynamic preheating scheme set of the reactor, the geothermal fluid introduction parameters, and the secondary flash evaporation trigger threshold are continuously optimized to generate a collaboratively optimized heating control set.

[0068] The real-time system energy efficiency ratio (ERR) can be the ratio of the total steam heat energy produced by the system through two-stage flash evaporation to the sum of the total heat energy consumed by geothermal fluids and the equivalent energy of solar-assisted electricity within a specific real-time point (or a short period, such as 15 minutes). It directly reflects the current energy utilization efficiency of the system. Solar-assisted potential can be calculated based on solar irradiance prediction data (such as irradiance intensity and effective duration), combined with the power generation efficiency of solar photovoltaic panels and the preheating and operating power requirements of the reactor. It represents the maximum capacity of solar energy to replace or supplement geothermal heating in the current and future periods. The dynamic heating capacity curve can be a curve that integrates the real-time system EERR and solar-assisted potential, with time as the horizontal axis and heating power as the vertical axis. It reflects the changes in the system's output heating capacity in real-time and over a future period, directly demonstrating the correlation between the system's heating potential and time. The target area heating load can be the curve of the target area's heating demand changes in real-time and over a future period. It is generated by combining real-time data collected by the heating network monitoring terminal with the load prediction model and is the core target that the system's heating needs to track. Model predictive control (MMC) is an advanced model-based control algorithm that predicts the deviation between system output and load over a future period by establishing a dynamic model of the system. It optimizes control parameters in advance to achieve precise and forward-looking regulation of complex systems, and features strong anti-interference and excellent dynamic response.

[0069] Specifically, traditional geothermal heating systems suffer from core defects such as rigid control, lack of closed-loop optimization, and isolated parameters, resulting in low energy efficiency and poor heating stability. Parameters like preheating temperature and geothermal fluid flow rate are often initially fixed values. Even if the two-stage flash evaporation efficiency ratio is found to be only 60% (far below the designed 80%), dynamic adjustments are impossible. Furthermore, the potential for solar-assisted heating is ignored; when the instantaneous solar-assisted heating potential reaches 150kW, geothermal fluid is still injected at full load, resulting in resource waste. Simultaneously, traditional systems only passively respond to the current load, lacking predictive capabilities. For example, if the load in a residential area suddenly increases from 300kW to 450kW in the evening, the steam production cannot keep up due to the lack of prior parameter optimization, causing the room temperature to remain below the set value for up to one hour. Isolated parameter adjustments, such as adjusting only the flow rate without changing the preheating temperature, lead to mismatched flash evaporation conditions. To address the above issues, this step extracts data from the initial basic flash evaporation information set (e.g., first stream of steam 2.0 m³ / h, 75℃) and the secondary enhanced flash evaporation information set (e.g., second stream of steam 3.2 m³ / h, 120℃). Combined with the total geothermal fluid consumption (e.g., 8 m³ / h, 110℃) and solar-assisted electricity (e.g., 50 kWh), the instantaneous system energy efficiency ratio is calculated to be approximately 77%. The predicted solar-assisted potential (e.g., 800 W / m², 140 kW) is overlaid to generate a dynamic heating capacity curve. Using a model predictive control algorithm with a 15-minute optimization cycle, the target area heating load curve is tracked (e.g., from 380 kW to 450 kW). The reactor preheating scheme is continuously optimized (wall temperature adjusted from 150℃ to 155℃), geothermal fluid introduction parameters (flow rate adjusted from 4.2 m³ / h to 4.5 m³ / h), and the secondary flash evaporation trigger threshold (reduced from 55℃ to 52℃). All optimization instructions are integrated to generate a collaboratively optimized heating control set, guiding real-time adjustments at each stage and entering the next cycle.

[0070] The method provided in this embodiment, based on real-time energy efficiency analysis, dynamic capacity modeling, and MPC algorithm rolling optimization, enables coordinated linkage of various parameters, accurately solves the problems of inefficiency, waste, and lag in response of traditional technologies, and forms a closed-loop control throughout the entire process. This is the key to ensuring that the system adapts to dynamic loads and solar energy and operates stably and efficiently in the long term.

[0071] Figure 3 A schematic diagram of a geothermal and solar coupled heating control system provided in one embodiment of this application is shown below. Figure 3 As shown, a geothermal and solar coupled heating control system 300 of this embodiment includes: a preheating scheme generation module 301, a first flash evaporation module 302, a second flash evaporation module 303, and a coupling optimization control module 304.

[0072] The preheating scheme generation module 301 is used to acquire target area heating load prediction data and solar irradiance prediction data, and dynamically formulate and execute the pre-preparation operation of the cascade flash reactor based on the target area heating load prediction data and the solar irradiance prediction data to generate a set of dynamic preheating schemes for the reactor; the first flash evaporation module 302 is used to introduce geothermal fluid into the fluid self-flash evaporation chamber based on the set of dynamic preheating schemes for the reactor, and execute geothermal fluid self-flash evaporation triggered by a pressure drop to generate a set of initial basic flash evaporation information; the second flash evaporation module 303 is used to guide the remaining liquid fluid to the enhanced boiling flash evaporation chamber based on the set of initial basic flash evaporation information, and execute contact enhanced boiling flash evaporation operation triggered by a significant temperature difference to generate a set of secondary enhanced flash evaporation information; the coupled optimization control module 304 is used to collect multi-parameter dynamic feedback of geothermal fluid flow rate, chamber pressure and heat storage release rate based on the set of initial basic flash evaporation information and the set of secondary enhanced flash evaporation information to generate a set of collaboratively optimized heating control.

[0073] Optionally, the preheating scheme generation module 301, when generating the reactor dynamic preheating scheme set, specifically performs the following: based on the target area heating load prediction data and the solar irradiance prediction data, predicts the target values ​​of key thermodynamic parameters required by the cascade flash reactor to trigger the subsequent two-stage flash reactions; based on the target values ​​of the key thermodynamic parameters, with the optimization objective of minimizing pre-preparation energy consumption and maximizing peak heating matching degree, generates a reactor heating dynamic formulation strategy; based on the reactor heating dynamic formulation strategy, drives the cascade flash reactor to perform preheating and pre-vacuuming operations, and monitors the actual temperature value of the cascade flash reactor in real time until the temperature target value is reached; integrates the target values ​​of the key thermodynamic parameters and the reactor heating dynamic formulation strategy to generate the reactor dynamic preheating scheme set as the subsequent control benchmark.

[0074] Optionally, when the preheating scheme generation module 301 is based on the cascade flash reactor, it is specifically used for: the cascade flash reactor is provided with the electrical energy required for its preheating and operation by solar photovoltaic panels, and includes a fluid self-flash chamber for performing the geothermal fluid self-flash triggered by a pressure drop, and an enhanced boiling flash chamber for performing the contact-type enhanced boiling flash operation triggered by a significant temperature difference; the process of geothermal fluid self-flash is as follows: high-temperature geothermal fluid is introduced into a preset low-pressure environment in the chamber, causing it to undergo adiabatic expansion, thereby causing a portion of the fluid to vaporize instantaneously, forming a first stream of saturated steam and the remaining liquid fluid after the first flash; the process of contact-type enhanced boiling flash operation is as follows: the remaining liquid fluid is directly sprayed or guided to a preheated high-temperature heat exchange wall, and the huge temperature difference between the fluid and the wall is used to drive the fluid to undergo violent nucleation boiling and secondary vaporization on the wall, forming a second stream of saturated steam and the final waste liquid.

[0075] Optionally, the preheating scheme generation module 301, when based on the cascade flash reactor, is specifically used for: analyzing the type characteristics and day-night load change patterns of the target area based on the target area heating load prediction data, and analyzing the intensity and effective duration of solar energy during the predicted day based on the solar irradiance prediction data; when the target area needs continuous and stable heating, or when the predicted day's solar energy is insufficient, generating a continuous preheating strategy to maintain a constant wall temperature of the enhanced boiling flash chamber; when the target area needs intermittent heating, and the predicted day's solar energy is sufficient, generating a timed enhanced preheating strategy with peak heating demand as the optimization target, wherein the enhanced preheating delays heat storage during periods of abundant solar energy and is concentratedly executed before the heating load climbs.

[0076] Optionally, the first flash evaporation module 302, when generating the initial basic flash evaporation information set, is specifically used for: confirming, based on the reactor dynamic preheating scheme set, that the fluid self-flash evaporation chamber has reached the preset initial low-pressure environment and chamber wall temperature, and generating a first-level flash evaporation ready signal; responding to the first-level flash evaporation ready signal, dynamically adjusting the introduction flow rate and introduction pressure of the geothermal fluid according to the real-time heating load demand, and injecting the high-temperature geothermal fluid into the fluid self-flash evaporation chamber in the form of a controllable jet; in the fluid self-flash evaporation chamber, based on the pressure drop between the preset low pressure and the injected fluid, triggering the adiabatic self-flash evaporation process of the geothermal fluid, forming the first stream of saturated steam and the remaining liquid fluid after one flash evaporation; and synchronously monitoring and collecting the pressure and flow rate of the first stream of saturated steam, the temperature and flow rate of the remaining liquid fluid, and the real-time pressure of the fluid self-flash evaporation chamber in real time, to generate the initial basic flash evaporation information set.

[0077] Optionally, when the first flash evaporation module 302 dynamically adjusts the introduced flow rate and pressure of the geothermal fluid, it is specifically used to: analyze the optimal geothermal fluid demand benchmark under the current target heating power based on the heating efficiency of the previous cycle fed back by the collaborative optimization heating control set and the instantaneous solar-assisted heating potential indicated by the solar irradiance prediction data; using the optimal geothermal fluid demand benchmark as a set value and coupling the real-time pressure feedback of the fluid from the flash evaporation chamber, dynamically adjust the variable frequency pump and pressure regulating valve on the geothermal fluid supply pipeline through a proportional-integral-derivative control algorithm; and synchronously update the adjusted actual introduced flow rate, introduced pressure, and their deviation from the demand benchmark as key parameters to the initial basic flash evaporation information set.

[0078] Optionally, the second flash evaporation module 303, when generating the secondary enhanced flash evaporation information set, is specifically used for: analyzing the current temperature and flow rate of the remaining liquid fluid in real time based on the initial basic flash evaporation information set, and combining it with a preset wall temperature target value to analyze the critical heat transfer temperature difference required to trigger effective secondary flash evaporation; determining whether the difference between the temperature of the remaining liquid fluid and the wall temperature target value is greater than or equal to the critical heat transfer temperature difference, and if so, generating a second-level flash evaporation trigger command; responding to the second-level flash evaporation trigger command, dynamically controlling the remaining liquid fluid to be uniformly distributed in atomized or thin-film form on the preheated high-temperature heat exchange wall surface according to the real-time heat storage state of the enhanced boiling flash evaporation chamber; triggering intense nucleation boiling and contact flash evaporation on the high-temperature heat exchange wall surface based on the huge solid-liquid temperature difference, forming the second stream of saturated steam and the final waste liquid; synchronously monitoring and collecting the flow rate and temperature of the second stream of saturated steam, the temperature of the final waste liquid, and the temperature distribution of the high-temperature heat exchange wall surface in real time to generate the secondary enhanced flash evaporation information set.

[0079] Optionally, the second flash evaporation module 303, when dynamically controlling the remaining liquid fluid, is specifically used to: identify local overheated areas and local underheated areas on the wall surface based on the temperature distribution data of the high-temperature heat exchange wall surface in the secondary enhanced flash evaporation information set; for the identified local overheated areas, control the corresponding allocated nozzles to increase the jet flow rate or switch to a spray mode with finer atomization particle size to enhance the penetration and disturbance of the thermal boundary layer; for the identified local underheated areas, control the corresponding allocated nozzles to decrease the jet flow rate or switch to a flow mode that forms a stable and extended liquid film to improve the uniformity of fluid coverage and residence time.

[0080] Optionally, the coupled optimization control module 304 is specifically used to: analyze the instantaneous system energy efficiency ratio based on the total steam output and total geothermal fluid consumption of the two stages in real time according to the initial basic flash evaporation information set and the secondary enhanced flash evaporation information set; superimpose the instantaneous system energy efficiency ratio with the predicted solar-assisted potential to generate a dynamic heating capacity curve; track the heating load of the target area in real time with the dynamic heating capacity curve, and continuously optimize the reactor dynamic preheating scheme set, geothermal fluid introduction parameters and secondary flash evaporation trigger threshold through a model predictive control algorithm to generate the collaboratively optimized heating control set.

[0081] The system in this embodiment can be used to execute the methods of any of the above embodiments, and its implementation principle and technical effect are similar, so they will not be described again here.

Claims

1. A method for controlling geothermal and solar coupled heating, characterized in that, include: Acquire target area heating load forecast data and solar irradiance forecast data, and based on the target area heating load forecast data and solar irradiance forecast data, dynamically formulate and execute the pre-preparation operation of the cascade flash reactor, and generate a set of dynamic preheating schemes for the reactor; Based on the reactor dynamic preheating scheme set, geothermal fluid is introduced into the fluid self-flash chamber, and geothermal fluid self-flash is performed based on pressure drop triggering, generating an initial basic flash information set; Based on the initial basic flash evaporation information set, the remaining liquid fluid is guided to the enhanced boiling flash evaporation chamber to perform a contact-type enhanced boiling flash evaporation operation triggered by a significant temperature difference, thereby generating a secondary enhanced flash evaporation information set. Based on the initial basic flash evaporation information set and the secondary enhanced flash evaporation information set, multi-parameter dynamic feedback of geothermal fluid flow rate, chamber pressure and heat storage release rate is collected to generate a collaboratively optimized heating control set.

2. The method according to claim 1, characterized in that, The set of dynamic preheating schemes for the generating reactor includes: Based on the target area heating load prediction data and the solar irradiance prediction data, predict the target values ​​of the key thermodynamic parameters required by the cascade flash reactor to trigger the subsequent two-stage flash reactions; Based on the target values ​​of the key thermodynamic parameters, with the optimization objective of minimizing pre-preparation energy consumption and maximizing the matching degree of peak heating, a dynamic formulation strategy for reactor heating is generated. Based on the dynamic heating strategy of the reactor, the cascade flash reactor is driven to perform preheating and pre-vacuuming operations, and the actual temperature value of the cascade flash reactor is monitored in real time until the target temperature value is reached. By integrating the target values ​​of the key thermodynamic parameters with the dynamic heating strategy of the reactor, a set of dynamic preheating schemes for the reactor is generated as the benchmark for subsequent control.

3. The method according to claim 2, characterized in that, The cascade flash reactor includes: The cascade flash reactor is powered by solar photovoltaic panels to provide the electricity required for its preheating and operation, and includes a fluid flash chamber for performing the geothermal fluid flash based on pressure drop triggering, and an enhanced boiling flash chamber for performing the contact-type enhanced boiling flash operation based on significant temperature difference triggering. The process of the geothermal fluid flash evaporation is as follows: high-temperature geothermal fluid is introduced into a pre-set low-pressure environment in the chamber, causing it to undergo adiabatic expansion, thereby causing some of the fluid to vaporize instantaneously, forming the first stream of saturated steam and the remaining liquid fluid after one flash evaporation. The process of the contact-enhanced boiling flash evaporation operation is as follows: the remaining liquid fluid is directly sprayed or guided to the preheated high-temperature heat exchange wall. The huge temperature difference between the fluid and the wall drives the fluid to undergo violent nucleation boiling and secondary vaporization on the wall to form a second stream of saturated steam and the final waste liquid.

4. The method according to claim 2, characterized in that, The reactor heating dynamic formulation strategy includes: Based on the heating load forecast data of the target area, the type characteristics and day-night load change patterns of the target area are analyzed, and based on the solar irradiance forecast data, the intensity and effective duration of solar energy during the day are analyzed and predicted. When the target area requires continuous and stable heating, or when the predicted solar energy is insufficient during the day, a continuous preheating strategy is generated to maintain a constant wall temperature in the enhanced boiling flash chamber. When the target area requires intermittent heating and the predicted intraday solar energy is sufficient, a timed enhanced preheating strategy is generated with the peak heating demand period as the optimization target. The enhanced preheating delays heat storage during the period of abundant solar energy and is concentratedly executed before the heating load climbs.

5. The method according to claim 3, characterized in that, The generation of the initial basic flash evaporation information set includes: Based on the reactor dynamic preheating scheme set, it is confirmed that the fluid in the flash chamber has reached the preset initial low pressure environment and chamber wall temperature, and a first-stage flash ready signal is generated. In response to the first-stage flash evaporation ready signal, the inlet flow rate and inlet pressure of the geothermal fluid are dynamically adjusted according to the real-time heating load demand, and the high-temperature geothermal fluid is injected into the fluid from the flash evaporation chamber in the form of a controllable jet. In the fluid flash evaporation chamber, based on the pressure drop between the preset low pressure and the injected fluid, the geothermal fluid is triggered to undergo an adiabatic flash evaporation process, forming the first stream of saturated steam and the remaining liquid fluid after one flash evaporation. The pressure and flow rate of the first saturated steam, the temperature and flow rate of the remaining liquid fluid, and the real-time pressure of the fluid from the flash chamber are monitored and collected in real time to generate an initial basic flash information set.

6. The method according to claim 5, characterized in that, The dynamic adjustment of the introduced flow rate and introduced pressure of the geothermal fluid includes: Based on the previous cycle heating efficiency fed back by the collaborative optimization heating control set, and the real-time solar-assisted heating potential indicated by the solar irradiance prediction data, the optimal geothermal fluid demand benchmark under the current target heating power is analyzed. Using the optimal geothermal fluid demand benchmark as the set value, and coupled with the real-time pressure feedback of the fluid from the flash chamber, the variable frequency pump and pressure regulating valve on the geothermal fluid supply pipeline are dynamically adjusted through a proportional-integral-derivative control algorithm. The adjusted actual inlet flow rate, inlet pressure, and their deviation from the demand baseline are synchronously updated to the initial basic flash evaporation information set as key parameters.

7. The method according to claim 6, characterized in that, The generation of the secondary enhanced flash evaporation information set includes: Based on the initial flash evaporation information set, the current temperature and flow rate of the remaining liquid fluid are analyzed in real time, and combined with the preset wall temperature target value, the critical heat transfer temperature difference required to trigger effective secondary flash evaporation is analyzed. Determine whether the difference between the temperature of the remaining liquid fluid and the target value of the wall temperature is greater than or equal to the critical heat transfer temperature difference. If the condition is met, generate a second-level flash evaporation trigger command. In response to the second-stage flash evaporation trigger command, the remaining liquid fluid is dynamically controlled to be evenly distributed in the form of atomization or film on the preheated high-temperature heat exchange wall surface according to the real-time heat storage state of the enhanced boiling flash evaporation chamber. On the high-temperature heat exchange wall, a violent nucleation boiling and contact flash evaporation are triggered by the huge solid-liquid temperature difference, forming the second stream of saturated steam and the final waste liquid; The flow rate and temperature of the second saturated steam, the temperature of the final waste liquid, and the temperature distribution of the high-temperature heat exchange wall are monitored and collected in real time to generate the secondary enhanced flash evaporation information set.

8. The method according to claim 7, characterized in that, The dynamic control of the remaining liquid fluid includes: Based on the temperature distribution data of the high-temperature heat exchange wall surface in the secondary enhanced flash evaporation information set, local overheated areas and local underheated areas of the wall surface are identified. For the identified local overheated areas, control the corresponding allocated nozzles to increase the jet flow or switch to a spray mode with finer atomization particle size to enhance the penetration and disturbance of the thermal boundary layer. For the identified local underheated areas, the corresponding nozzles are controlled to reduce the jet flow rate or switch to a flow mode that forms a stable and extended liquid film, so as to improve the uniformity of fluid coverage and residence time.

9. The method according to claim 8, characterized in that, The generation of the collaboratively optimized heating control set includes: Based on the initial basic flash steam information set and the secondary enhanced flash steam information set, the real-time system energy efficiency ratio is analyzed based on the total steam output of the two stages and the total geothermal fluid consumption. The instantaneous system energy efficiency ratio is superimposed with the predicted solar-assisted potential to generate a dynamic heating capacity curve; The target area's heating load is tracked in real time using the dynamic heating capacity curve. The reactor's dynamic preheating scheme set, geothermal fluid introduction parameters, and secondary flash evaporation trigger threshold are continuously optimized using a model predictive control algorithm to generate the collaboratively optimized heating control set.

10. A geothermal and solar coupled heating control system, characterized in that, The method applied to any one of claims 1-9 includes: The preheating scheme generation module is used to acquire target area heating load prediction data and solar irradiance prediction data, and based on the target area heating load prediction data and solar irradiance prediction data, dynamically formulate and execute the pre-preparation operation of the cascade flash reactor, and generate a set of dynamic preheating schemes for the reactor. The first flash evaporation module is used to introduce geothermal fluid into the fluid self-flash evaporation chamber based on the reactor dynamic preheating scheme set, perform geothermal fluid self-flash evaporation triggered by pressure drop, and generate the initial basic flash evaporation information set; The second flash evaporation module is used to guide the remaining liquid fluid to the enhanced boiling flash evaporation chamber based on the initial basic flash evaporation information set, perform a contact-type enhanced boiling flash evaporation operation triggered by a significant temperature difference, and generate a second enhanced flash evaporation information set. The coupled optimization control module is used to collect multi-parameter dynamic feedback of geothermal fluid flow rate, chamber pressure and heat storage release rate based on the initial basic flash evaporation information set and the secondary enhanced flash evaporation information set, and generate a collaboratively optimized heating control set.

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