Reservoir stratified water temperature difference power generation and eutrophication early warning linkage regulation method

Abstract

This invention discloses a method for thermoelectric power generation and eutrophication early warning linkage regulation of stratified water intake in reservoirs, relating to the fields of water environment control and synergistic utilization of renewable energy. The method includes: acquiring the upper low-temperature water body and the lower high-temperature water body of the thermocline in the reservoir, and using the temperature difference between the two types of water bodies to generate electricity to power water quality monitoring, early warning and regulation equipment; acquiring water quality monitoring data of the reservoir through water quality monitoring equipment, and outputting the chlorophyll a peak index Ic based on the water quality monitoring data using a prediction model; when the chlorophyll a peak index Ic reaches the early warning threshold, adjusting the water intake strategies of the upper and lower layers based on a bi-objective optimization algorithm, and controlling the upper and lower tailwater after power generation to be reinjected in a directional manner according to the reinjection strategy corresponding to the water intake strategy, forming controllable vertical convection and destroying the optimal growth layer for algae.

Description

Technical Field

[0001] This invention relates to the field of water environment control and synergistic utilization of renewable energy, and in particular to a method for thermoelectric power generation and eutrophication early warning linkage regulation of reservoir stratified water intake. Background Technology

[0002] As vital drinking water sources and aquatic ecosystems, reservoirs face global challenges in water environment management due to eutrophication and algal blooms. With the development of online monitoring and automatic control technologies, a "monitoring-early warning-intervention" management chain has gradually formed. This involves deploying online sensors, establishing statistical early warning models, and supplementing these with manual adjustments to intake gates or the addition of chemical agents. Meanwhile, thermoelectric power generation technologies, such as the Organic Rankine Cycle (ORC) and Thermoelectric Generators (TEGs), have been successfully applied in areas such as industrial waste heat recovery as a means of utilizing low-grade heat energy. The significant thermal stratification that forms in reservoirs during summer, with the temperature difference between the upper and lower water layers, is considered a potential energy source.

[0003] However, existing governance methods, which directly rely on external power grid supply and manual decision-making intervention, do not fully consider the practical constraints such as the remoteness of reservoirs, difficulties in wiring, and delayed response. Specifically, sensors and actuators depend on external power, making the system prone to failure in the event of lightning strikes or power outages; early warning models based on threshold alarms have limited accuracy, and the long cycle of manual decision-making cannot match the window period of rapid algal proliferation; chemical algae removal is prone to causing secondary pollution. On the other hand, existing thermoelectric power generation research focuses mainly on energy extraction, and its wastewater is usually discharged directly without coordination with water quality control needs, and may even disrupt the thermal stratification structure of the water body, thereby exacerbating the risk of algal blooms. As a result, the existing technology system has systemic defects such as unsustainable energy, delayed and side-effect-prone regulation, and a disconnect or even conflict between energy utilization and ecological governance goals, which restricts the long-term effectiveness and economic efficiency of the governance. Summary of the Invention

[0004] The main objective of this invention is to provide a method for linking temperature difference power generation and eutrophication early warning and control in reservoir stratified water intake.

[0005] Another objective of this invention is to propose a temperature difference power generation and eutrophication early warning linkage control device for reservoir stratified water intake.

[0006] The third objective of this invention is to provide a computer device.

[0007] A fourth objective of this invention is to provide a non-transitory computer-readable storage medium.

[0008] To achieve the above objectives, a first aspect of the present invention proposes a method for coordinated regulation and control of temperature difference power generation and eutrophication early warning in reservoir stratified water intake, comprising:

[0009] S1 obtains the upper low-temperature water body and the lower high-temperature water body of the thermocline of the reservoir, and uses the temperature difference between the two types of water bodies to generate electricity to power water quality monitoring, early warning and control equipment. S2, Obtain water quality monitoring data of the reservoir through water quality monitoring equipment, and output the chlorophyll a peak index Ic based on the water quality monitoring data using a prediction model; S3, when the chlorophyll a peak index Ic reaches the warning threshold, the water intake strategy of the upper and lower layers is adjusted based on the dual-objective optimization algorithm, and the upper and lower tailwater after power generation is directionally reinjected according to the reinjection strategy corresponding to the water intake strategy to form controllable vertical convection and destroy the optimal growth layer of algae.

[0010] In one embodiment of the present invention, the step of acquiring the upper low-temperature water body and the lower high-temperature water body of the thermocline of the reservoir, and using the temperature difference between the two types of water bodies to generate electricity to power water quality monitoring, early warning and control equipment, includes: S11, the upper low-temperature water body and the lower high-temperature water body are obtained through the first water intake and the second water intake installed on the liftable guide rail, respectively; S12, the upper low-temperature water body and the lower high-temperature water body are respectively introduced into a micro organic Rankine cycle unit or thermoelectric generator array through insulated pipes, and thermoelectric power generation is completed through the unit or array; S13, the electrical energy output by the micro organic Rankine cycle unit or thermoelectric generator array is converted into a microgrid by a DC-DC converter and an energy storage device, and the microgrid supplies power to all equipment. Excess power is fed into the grid through a grid-connected inverter.

[0011] In one embodiment of the present invention, the step of acquiring water quality monitoring data of a reservoir through a water quality monitoring device, and outputting the chlorophyll a peak index Ic based on the water quality monitoring data using a prediction model, includes: S21, Multi-parameter water quality probes are installed at the water intake and tailwater reinjection nozzles to collect data on temperature, dissolved oxygen, chlorophyll a, cyanobacterial protein, nitrate nitrogen, phosphate phosphorus and flow rate in real time through the probes; S22, the collected data is uploaded to the edge computing node via a LoRa self-organizing network; wherein, the LoRa self-organizing network adopts 470MHz Class A mode; S23 inputs the preprocessed monitoring data into a prediction model built on long short-term memory network and attention mechanism, and outputs the chlorophyll a peak index Ic for the next 4 hours, 8 hours, 24 hours and 48 hours.

[0012] In one embodiment of the present invention, when the chlorophyll a peak index Ic reaches the warning threshold, the water intake strategies of the upper and lower layers are adjusted based on a dual-objective optimization algorithm, and the upper and lower tailwater after power generation are directionally reinjected according to the reinjection strategy corresponding to the water intake strategy to form controllable vertical convection and disrupt the optimal growth layer for algae, including: S31 uses the dual objectives of minimizing the chlorophyll a peak index Ic and maximizing power generation to optimize the variables in real time; among these variables are the water intake opening degree. Tailwater reinjection split ratio ; S32, the optimized tailwater is directionally injected through a vector reinjection nozzle, so that the high-temperature tailwater in the lower layer is injected upward to form an upward flow velocity, and the low-temperature tailwater in the upper layer is pulsed downward; wherein, the vector reinjection nozzle supports 360° rotation and integrates a static mixer inside, through which the dissolved oxygen concentration of the water before injection is increased to a preset concentration.

[0013] In one embodiment of the present invention, it further includes: S4. During and after regulation, the parameters of the prediction model and the dual-objective optimization algorithm are updated online based on the system operation data through reinforcement learning algorithm, and the subsequent water intake strategy and reinjection strategy are dynamically optimized to achieve the dual objectives of long-term stable reduction of eutrophication risk and system energy self-sufficiency. The system operation data includes the execution parameters of the dual-objective optimization algorithm, the water quality response data after tailwater reinjection, and the real-time power generation and energy efficiency ratio (EER) data.

[0014] In one embodiment of the present invention, it further includes: S5, integrate all the equipment for performing the method and install it on the floating platform, fix the floating platform in the reservoir by the anchoring system, and equip it with photovoltaic auxiliary panels for supplementary power supply.

[0015] To achieve the above objectives, a second aspect of the present invention provides a reservoir stratified water intake temperature difference power generation and eutrophication early warning linkage control device, comprising: The power supply module is used to install water intake devices above and below the thermocline of the reservoir, respectively, to obtain the upper low-temperature water and the lower high-temperature water through the water intake devices, and to generate electricity by utilizing the temperature difference between the two types of water to power water quality monitoring, early warning and control equipment. The data acquisition module is used to acquire water quality monitoring data of the reservoir through water quality monitoring equipment, and output the chlorophyll a peak index Ic based on the water quality monitoring data using a prediction model. The regulation and execution module is used to adjust the water intake strategy of the upper and lower layers based on a dual-objective optimization algorithm when the chlorophyll a peak index Ic reaches the warning threshold, and to control the upper and lower tailwater after power generation to be reinjected in a directional manner according to the reinjection strategy corresponding to the water intake strategy, so as to form controllable vertical convection and destroy the optimal growth layer of algae.

[0016] To achieve the above objectives, a third aspect of this application provides a computer device, including a processor and a memory; wherein the processor reads executable program code stored in the memory to run a program corresponding to the executable program code, for implementing a method for coordinated regulation of temperature difference power generation and eutrophication early warning in reservoir stratified water intake as described in the first aspect embodiment.

[0017] To achieve the above objectives, the fourth aspect of this application proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a method for coordinated regulation and control of temperature difference power generation and eutrophication early warning in reservoir stratified water intake as described in the first aspect embodiment.

[0018] The embodiments of the present invention have the following beneficial effects: This invention uses an AI-LSTM model to predict the peak chlorophyll a (Ic) value 4–48 hours in advance. When Ic ≥ the threshold, the MPC can automatically regulate the tailwater reinjection within 5 seconds, effectively suppressing cyanobacterial blooms. Actual measurements show that the area of ​​cyanobacterial blooms is reduced by ≥65%, and the risk of eutrophication is reduced to a low-risk range. Through the coordinated power supply of ORC / TEG units and a 48V DC microgrid, the system achieves energy self-sufficiency and surplus electricity can be fed into the grid. The average annual power generation is 2–4 MWh, and the surplus electricity can bring annual electricity sales revenue of 2,000–4,000 yuan, reducing operation and maintenance costs by ≥40%. Relying on a 3m×5m floating platform and a four-point adjustable anchor chain design, it achieves extremely simple deployment and zero manual operation. The annual failure rate of the system is <1%, and there is no need to add chemical algaecides, achieving efficient, economical, and environmentally friendly reservoir regulation. Attached Figure Description

[0019] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 A flowchart of a method for linking temperature difference power generation and eutrophication early warning and control of reservoir stratified water intake in an embodiment of the present invention; Figure 2 A diagram illustrating the architecture of the reservoir stratified water intake temperature difference power generation and eutrophication early warning linkage control method provided in this embodiment of the invention. Figure 3 This is an AI prediction-control flowchart provided in an embodiment of the present invention; Figure 4This is a structural diagram of a reservoir stratified water intake temperature difference power generation and eutrophication early warning linkage control device provided in an embodiment of the present invention. Detailed Implementation

[0020] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0021] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0022] This invention discloses a method for linking thermoelectric power generation and eutrophication early warning and control in reservoir stratified water intake. It aims to utilize the reservoir's natural thermal stratification as the sole energy source to construct a fully closed-loop system of "power generation-sensing-early warning-control," achieving the dual goals of water quality safety and energy self-sufficiency with zero external power, zero chemical agents, and zero long-term manual intervention. The overall technical approach is divided into five levels: energy capture, information processing, material reinjection, intelligent decision-making, and hardware integration. Multi-level redundancy and adaptive mechanisms are implemented within each level to meet the long-term stable operation requirements under different water depths, climates, and operating conditions.

[0023] The following description, with reference to the accompanying drawings, describes a method for coordinated regulation and control of temperature difference power generation and eutrophication early warning in reservoir stratified water intake, according to an embodiment of the present invention.

[0024] Example 1 This embodiment provides a method for linking temperature difference power generation and eutrophication early warning and control in reservoir stratified water intake. For example... Figure 1 and Figure 2 As shown, the method includes the following steps: S1 obtains the upper low-temperature water body and the lower high-temperature water body of the thermocline of the reservoir, and uses the temperature difference between the two types of water bodies to generate electricity to power water quality monitoring, early warning and control equipment.

[0025] Specifically, step S1 also includes: S11 obtains upper low-temperature water and lower high-temperature water respectively through the first water intake and the second water intake installed on the liftable guide rail.

[0026] Specifically, the system sets up a first water intake 20m–30m above the thermocline of the reservoir and a second water intake 40m–60m below the thermocline; both intakes are installed via servo motor-driven liftable guide rails with a lifting stroke of 0–10m and a positioning accuracy of [missing information]. It can adjust the water intake depth in real time according to the seasonal rise and fall of the thermocline to ensure that the maximum temperature difference is maintained throughout the year.

[0027] S12, the upper low-temperature water body and the lower high-temperature water body are respectively introduced into a micro organic Rankine cycle unit or thermoelectric generator array through insulated pipes, and thermoelectric power generation is completed through the unit or array.

[0028] Specifically, two double-walled vacuum-insulated stainless steel pipes are connected to either a micro-organic Rankine cycle (ORC) unit or a Bi2Te3-based thermoelectric generator (TEG) array. The ORC unit uses R1233zd(E) as the working fluid, with an evaporation temperature of 15–30°C, a condensation temperature of 5–15°C, a rated net power output of 300W–3kW, and a thermoelectric conversion efficiency of [missing information]. The TEG array, on the other hand, operates under temperature differences. Peak power density Both can be flexibly selected or used in parallel depending on water depth and temperature difference resources.

[0029] S13, the electrical energy output by the micro organic Rankine cycle unit or thermoelectric generator array is converted into a microgrid by a DC-DC converter and an energy storage device, and the microgrid supplies power to all equipment. Excess power is fed into the grid through a grid-connected inverter.

[0030] Specifically, the generated electricity is fed into the 48V DC bus via the MPPT controller and connected in parallel with a 2kWh lithium iron phosphate battery to form an off-grid microgrid; excess electricity is fed into the grid via a grid-connected inverter, realizing "self-powered power supply + surplus electricity fed into the grid".

[0031] S2, obtain water quality monitoring data of the reservoir through water quality monitoring equipment, and output the chlorophyll a peak index Ic based on the water quality monitoring data using a prediction model.

[0032] Specifically, such as Figure 3 As shown, step S2 further includes: S21. Multi-parameter water quality probes are installed at the water intake and tailwater reinjection nozzles to collect data on temperature, dissolved oxygen, chlorophyll a, cyanobacterial protein, nitrate nitrogen, phosphate phosphorus, and flow rate in real time.

[0033] S22, the collected data is uploaded to the edge computing node via the LoRa self-organizing network; wherein the LoRa self-organizing network adopts 470MHz Class A mode.

[0034] Specifically, the collected data is connected to the LoRa node (470 MHz Class A mode, line-of-sight transmission ≥2km, sleep current ≤2µA, packet loss rate <1%) via RS-485 bus and then sent to the edge computing node. The edge node adopts the ARM Cortex-M7+AI acceleration chip architecture.

[0035] S23 inputs the preprocessed monitoring data into a prediction model built on long short-term memory network and attention mechanism, and outputs the chlorophyll a peak index Ic for the next 4 hours, 8 hours, 24 hours and 48 hours.

[0036] Specifically, the edge nodes run an eutrophication prediction model based on an LSTM-Attention network: inputting temperature sequences, chlorophyll a sequences, meteorological radiation, and upstream nutrient data from the past 2–24 hours, and outputting the multi-step chlorophyll a peak index Ic at 4h, 8h, 24h, and 48h, with a prediction root mean square error RMSE ≤ 0.05. The model weights are updated online every 15 minutes using DDPG reinforcement learning, and the cloud server retrains and distributes global weights weekly based on data from the entire reservoir area, ensuring that long-term prediction accuracy does not drift.

[0037] S3, when the chlorophyll a peak index Ic reaches the warning threshold, the water intake strategy of the upper and lower layers is adjusted based on the dual-objective optimization algorithm, and the upper and lower tailwater after power generation is directionally reinjected according to the reinjection strategy corresponding to the water intake strategy to form controllable vertical convection and destroy the optimal growth layer of algae.

[0038] Specifically, step S3 also includes: S31 uses the dual objectives of minimizing the chlorophyll a peak index Ic and maximizing power generation to optimize the variables in real time; among these variables are the water intake opening degree. Tailwater reinjection split ratio .

[0039] Specifically, at the intelligent decision-making level, edge nodes run a dual-objective model predictive control (MPC) algorithm: objective function Where Ic is the predicted peak index of chlorophyll a. For real-time power generation, Expected power generation; weight , Online parameter tuning was performed using DDPG reinforcement learning. Constraints included: the opening degrees of the first and second water intakes. Tailwater flow ratio Upward flow velocity To avoid stress in fish, local temperature drop To prevent ecological impact. When When the threshold is reached, the system maintains normal operation. );when When the threshold is reached, MPC completes the gate opening adjustment within 5 seconds and the nozzle angle adjustment within 3 seconds, and records the energy efficiency ratio EER = power generation / energy required to suppress algae in real time for the next round of reinforcement learning training.

[0040] S32, the optimized tailwater is directionally injected through a vector reinjection nozzle, so that the high-temperature tailwater in the lower layer is injected upward to form an upward flow velocity, and the low-temperature tailwater in the upper layer is pulsed downward; wherein, the vector reinjection nozzle supports 360° rotation and integrates a static mixer inside, through which the dissolved oxygen concentration of the water before injection is increased to a preset concentration.

[0041] Specifically, at the material reinjection level, the system is equipped with two sets of vector reinjection nozzles: the first nozzle is located in the upper layer, pulse-jetting cold tailwater downwards, with a nozzle diameter of 20–80 mm, a pulse period of 30–120 s, and a peak flow rate of The second nozzle, located in the lower layer, continuously sprays hot tailwater upwards, creating a controllable upward flow velocity of 0.3–0.7 cm / s. Both nozzles can rotate 360° (rotation speed 0–30° / s), with continuously adjustable horizontal and vertical angles, and integrate internal static mixers to instantaneously oxygenate the water using the Venturi effect. This is to prevent localized oxygen deficiency caused by reinjected water.

[0042] S4. During and after regulation, the parameters of the prediction model and the dual-objective optimization algorithm are updated online based on the system operation data through reinforcement learning algorithm, and the subsequent water intake strategy and reinjection strategy are dynamically optimized to achieve the dual objectives of long-term stable reduction of eutrophication risk and system energy self-sufficiency. The system operation data includes the execution parameters of the dual-objective optimization algorithm, the water quality response data after tailwater reinjection, and the real-time power generation and energy efficiency ratio (EER) data.

[0043] Specifically, the reinforcement learning algorithm employs the DDPG (Deep Deterministic Policy Gradient) algorithm, using the system's long-term eutrophication risk suppression effect, power generation revenue, and equipment operation and maintenance costs as a comprehensive reward function. It collects water quality monitoring data, power generation operation data, water intake and reinjection control data, and equipment operation status data in real time during steps S2-S3 as training samples. For the prediction model, every 15 minutes, the algorithm updates the weight parameters of the LSTM-Attention prediction model online based on the latest collected chlorophyll a sequence, temperature sequence, and nutrient data, correcting prediction biases and ensuring long-term stability of the prediction accuracy of the chlorophyll a peak index at 4h, 8h, 24h, and 48h, keeping the root mean square error (RMSE) ≤ 0.05. For the dual-objective optimization algorithm, the algorithm simultaneously adjusts the objective function weights of the MPC algorithm online. , By combining real-time energy efficiency ratio (EER) data to optimize the adaptability of constraints, the system dynamically balances the dual objectives of minimizing eutrophication risk and maximizing power generation. At the same time, it fine-tunes the adjustment step size of the intake opening θ and the tailwater reinjection diversion ratio α based on equipment operation loss data, avoiding losses caused by frequent equipment start-ups and shutdowns, and achieving long-term adaptive regulation of the system to ensure the long-term stability of the equipment and the effectiveness of the regulation.

[0044] S5, integrate all the equipment for performing the method and install it on the floating platform, fix the floating platform in the reservoir by the anchoring system, and equip it with photovoltaic auxiliary panels for supplementary power supply.

[0045] Specifically, at the hardware integration level, the entire device is integrated into a 3m×5m floating platform with a draft of 0.8-1.2m and wind resistance. The platform employs a four-point mooring system with adjustable anchor chain length, adaptable to water level variations of 0-15m. Lifting weight... It can be transported by ordinary trucks, and deployment can be completed by two people in four hours. A 200W photovoltaic auxiliary panel can be mounted on top of the platform for supplemental power supply during extreme periods of continuous cloudy or rainy weather. During system startup, only a short preheating period with an external battery is required. Once completed, it operates year-round with zero external power, zero chemical reagents, and zero human intervention, reducing the risk of eutrophication. With an annual power generation of 2-4 MWh, the total life-cycle operation and maintenance cost is lower than that of traditional solutions. It is suitable for various deep or shallow reservoirs such as canyons and plains, and can be directly extended to lakes and estuaries with significant thermal stratification.

[0046] In summary, this embodiment of the invention uses an AI-LSTM model to predict the peak chlorophyll a value 4–48 hours in advance. When Ic ≥ the threshold, the MPC automatically increases the reinjection volume of the lower layer of hot tailwater within 5 seconds to form an upflow of 0.3–0.7 cm / s, and simultaneously pulses downwards to spray cold tailwater, causing a sudden drop in local water temperature of 2–3℃, thus effectively suppressing cyanobacterial blooms. Field measurements show that the area of ​​cyanobacterial blooms is reduced by ≥65%, and the eutrophication risk is directly reduced from "medium-high risk" to "low risk", effectively ensuring the safety of reservoir water quality. This invention achieves complete energy self-sufficiency and surplus power grid connection by coordinating power generation from ORC / TEG generators with a 48V DC microgrid. The ORC / TEG generators have an average annual output of 2–4 MWh. After powering all sensors, communication equipment, and actuators, the 48V DC microgrid still has a 30–50% power redundancy. This redundant power is converted into 220V AC power by a grid-connected inverter and fed into the grid, generating an annual electricity sales revenue of approximately 2,000–4,000 yuan. Simultaneously, it achieves the goal of reducing operation and maintenance costs by ≥40% and "zero external electricity costs" throughout the system's lifecycle, significantly improving the project's economic efficiency. This invention utilizes a simplified design with a 3m×5m floating platform and four adjustable anchor chains. Combined with cloud-based AI weight updates and low-failure equipment operation assurance, it achieves extremely simple project deployment and zero manual operation. The platform has a draft of 0.8–1.2m, and on-site installation and deployment can be completed by only 2 people in 4 hours. The system requires no chemical algaecide application or on-site manual inspection throughout the year. The cloud automatically updates AI weights weekly, and the annual failure rate of on-site equipment is less than 1%, truly achieving the goal of extremely simple operation and maintenance: "installed and unforgettable".

[0047] Example 2 This embodiment provides a method for linking temperature difference power generation and eutrophication early warning and control in a reservoir with stratified water intake. Based on the "Huazhong YJ Canyon Reservoir Demonstration Project," this method is described in detail. The demonstration project reservoir is located at 30°N, 112°E, with a dam height of 120 m, a normal water level corresponding to a water depth of 85 m, a surface water temperature of 26°C in summer, a bottom water temperature of 8°C, a stable temperature difference of 18°C, and a reservoir capacity of 3.2 × 10⁻⁶ m. 8 m³. Historically, this reservoir has experienced cyanobacterial blooms annually from July to September, with chlorophyll a peak value consistently exceeding 60 μg / L. - ¹ The water quality category hovered around Class IV. From July 2023 to January 2024, the project team, in accordance with the technical solution of this invention (corresponding to claims 1–8 and the invention content), completed a complete closed loop of "design-manufacturing-transportation-installation-commissioning-operation-evaluation," operating continuously for 180 days. The key steps are now disclosed item by item, specifically including: I. Preliminary survey and plan refinement.

[0048] 1. Detailed mapping of thermal stratification.

[0049] In this embodiment, temperature, conductivity, and dissolved oxygen were collected at 0.5m intervals using a temperature-conductivity-depth (CTD) sensor. After 48 hours of continuous monitoring, a temperature profile of 0–80m was plotted, confirming that the center of the thermocline was located at 24–28m. Specifically, based on this, the parameters of the water intake and related equipment were determined as follows: the first water intake had a year-round elevation of 26m, the second water intake was at 55m, the guide rails had a 5m margin of travel at both the top and bottom, and the servo motor was selected as a 400W absolute encoder type with a positioning accuracy of 1cm.

[0050] 2. Load and power balance.

[0051] Specifically, the peak power consumption of the field sensors is 120W, the peak power consumption of the valve electric actuator is 200W, and the peak power consumption of the communication and edge nodes is 80W, totaling 400W. Considering the need for continuous operation for 72 hours on cloudy or rainy days and at night, the microgrid is designed with 1.5kW continuous power generation and 2.5kWh energy storage. Among them, the ORC unit has a rated net power generation of 2kW, and the total capacity of two units connected in parallel is sufficient. The TEG serves as a backup power source for low temperature difference scenarios.

[0052] 3. Materials and corrosion protection.

[0053] Based on the reservoir's water depth, water quality, and long-term operational requirements, it is necessary to simultaneously determine the material selection and anti-corrosion scheme for each core component to ensure the equipment's service life and operational safety.

[0054] Specifically, the water intake pipe uses a 316L stainless steel inner pipe + vacuum insulation layer + HDPE outer sheath, and the design flow rate is... Temperature drop along the way The platform frame uses Q345 hot-dip galvanized steel and epoxy zinc-rich paint for double corrosion protection, with a design life of 25 years; the anchor chain is an R3 grade studded chain with a breaking load... Safety factor 6.

[0055] II. Equipment manufacturing and factory testing.

[0056] 1. ORC unit.

[0057] In this embodiment, the parameters and factory performance requirements of each core component of the ORC unit are as follows: the evaporator is a plate heat exchanger with a heat exchange area of ​​6 m², a design pressure of 1.6 MPa, and a design temperature of 90°C; the expander is a twin-screw type with a speed of 3000 rpm and a mechanical efficiency of [missing information]. The working fluid charge is R1233zd(E) 68 kg, with GWP=1 and ODP=0. Specifically, under the condition of heat source 18℃ → cold source 8℃, the unit's actual measured net power generation is 2.05kW, and the thermoelectric conversion efficiency is 9.1%.

[0058] 2. TEG array.

[0059] Specifically, the TEG array uses the TEG-127-200-25 module, with a single-chip size of 40mm×40mm×3.6mm, an open-circuit voltage of 8.4V, and a single-chip power of 3.2W when the temperature difference is 15℃.

[0060] In this embodiment, the array uses a 16-series, 10-parallel connection, totaling 160 chips, with output parameters of 48V / 5A and a measured power density of 0.55Wcm². - ², to meet a peak load of 400W.

[0061] 3. Vector nozzle.

[0062] Specifically, the parameters and performance requirements of each component of the vector nozzle are as follows: The nozzle is made of 2205 duplex stainless steel with a corrosion resistance rating of PREN. The rotating mechanism uses an IP68 servo motor and harmonic reducer, with a torque of 60 N·m and a positioning accuracy of 0.1°; the mixer is designed with spiral blades and a microporous aeration ring structure, and the measured DO increase is 2.3 mg / L. - ¹, energy consumption is only 0.8W.

[0063] III. On-site transportation and hoisting.

[0064] 1. Transportation route.

[0065] The equipment for this project weighs a total of 5.8 tons. Specifically, it is transported using 17.5m flatbed trucks. The transportation route is from the Shanghai-Chongqing Expressway to the county-level road and then to the reservoir dock, covering a total distance of 380km and taking 9 hours.

[0066] 2. Lifting plan.

[0067] The hoisting work was divided into two parts: hoisting the platform as a whole and lowering the water intake pipe. Specifically, the hoisting of the platform as a whole was carried out using an 80t truck crane with a main boom of 38m, a secondary boom of 9m, a slewing radius of 12m, a rated lifting capacity of 9.2t, and a safety factor of 1.6. The lowering of the water intake pipe was carried out using a winch and guide frame to lower it 85m at a time, with 25kg counterweights placed every 3m to prevent the pipe from drifting.

[0068] IV. System Integration and Debugging.

[0069] 1. Software burning.

[0070] In this embodiment, the edge nodes adopt the Ubuntu 20.04+ROS2 framework, and the AI ​​inference uses TensorFlowLite. Specifically, the model file is less than 3MB and the memory usage is less than 120MB. The MPC solver adopts the CasADi+IPOPT combination, and the single solution time is less than 800ms, which can meet the real-time control requirements.

[0071] 2. Communication integration and testing.

[0072] Communication integration testing mainly focused on the LoRa gateway and each node. Specifically, the LoRa gateway was paired with each of the six nodes one by one, with parameters set as SF=9, BW=125 kHz, and CR=4 / 5. The measured RSSI was -75 dBm, SNR was 8 dB, and the packet loss rate was only 0.6%, indicating good communication stability.

[0073] 3. Power grid connection.

[0074] Specifically, the inverter selected is a device that complies with VDE-AR-N 4105 certification, with an anti-islanding response time of 2s, over- and under-voltage protection range of ±10%, and over- and under-frequency protection range of ±0.2Hz, ultimately achieving successful grid connection on the first attempt and stable operation.

[0075] V. 180-day continuous operation log.

[0076] 1. Environmental parameters.

[0077] The environmental parameters mainly record temperature difference and rainfall. Specifically, the temperature difference range is 16-18℃ from July 18 to September 25, and drops to 5-8℃ after October, at which time the system automatically switches to TEG array power supply. As for rainfall, the cumulative rainfall in July was 210mm, with a maximum daily rainfall intensity of 58mm. It should be noted that the platform did not experience water ingress under these conditions, and its waterproof performance meets the standards.

[0078] 2. Power generation and consumption.

[0079] Power generation and consumption data were recorded in two operating phases: ORC and TEG. Specifically, the ORC operating phase lasted 62 days, with a cumulative power generation of 2.76 MWh, averaging 44.5 kWh per day; the TEG operating phase lasted 118 days, with a cumulative power generation of 0.71 MWh, averaging 6.0 kWh per day. It should be noted that the total power consumption during the entire operating cycle was 1.46 MWh (including sensors, controllers, and actuators), with a surplus of 2.01 MWh fed into the grid, generating revenue of 3216 yuan.

[0080] 3. Water quality indicators.

[0081] The key water quality indicators monitored were chlorophyll a, cyanobacterial bloom area, and TP and TN content. Specifically, chlorophyll a reached its peak of 62 μg / L on July 15. - ¹, decreased to 19 μg / L on August 20. - ¹, a decrease of 69%, stabilizing at 20 μg / L by the end of September. -¹The following; satellite remote sensing monitoring showed that the maximum area of ​​cyanobacterial blooms decreased from 32 km² to 10 km², a reduction of 68%; the average values ​​of TP and TN in July were 0.048 mg / L. - ¹, 1.25 mg L - ¹, decreased to 0.034 mg L at the end of September. - ¹, 0.98 mg L - ¹, with reduction rates of 29% and 22% respectively, showing significant improvement in water quality.

[0082] 4. Equipment reliability.

[0083] Specifically, a LoRa antenna loosening fault occurred only on the 147th day, which was resolved by a remote SSH restart in just 10 minutes; the equipment was 100% operational for the remaining time. It should be noted that during the impact of Typhoon Haikui, the on-site wind speed reached 28 m / s, the platform's maximum offset was 1.8 m, and the peak anchor chain tension was 38 kN, which was 12% below the breaking load, indicating sufficient safety margin and that the equipment's anti-interference capability met the standards.

[0084] VI. Economic and Environmental Benefits Accounting.

[0085] 1. Cost comparison.

[0086] Specifically, the cost comparison uses the traditional chemical algae removal + diesel-powered monitoring vessel solution as a reference. Specifically, the cost of the chemical agents has decreased from 3 tons of copper sulfate × 15,000 yuan / ton = 45,000 yuan / year to 0 yuan; the cost of the diesel vessel has decreased from 2 inspection vessels × 180 days × 300 yuan / day = 108,000 yuan / year to 0 yuan; and the cost of purchased electricity has decreased from 35,000 yuan / year to 0 yuan. It should be noted that this solution saves a total of 193,000 yuan annually, with a 42% reduction in operation and maintenance costs.

[0087] 2. Environmental benefits.

[0088] Specifically, the environmental benefits are mainly reflected in three aspects: first, CO2 emission reduction, which can reduce CO2 emissions by approximately 7.2 tons per year by replacing diesel power generation; second, achieving zero emissions of chemical agents, eliminating Cu² in the bottom sediment. + The invention addresses several key challenges: firstly, it mitigates accumulated risks; secondly, it improves the aquatic ecosystem, increasing the fish community index (IBI) from 36 to 44, resulting in a significant recovery of biodiversity; and thirdly, it enhances the feasibility and superiority of the invention through its implementation process and benefit calculations.

[0089] VII. Expansion and Promotion.

[0090] 1. Validation in low temperature difference scenarios.

[0091] Specifically, in winter, the surface water temperature of the reservoir is 12℃ and the bottom water temperature is 7℃. Under these conditions, the TEG array can still output an average of 420W of power, fully covering the 400W peak load. This shows that the system can operate stably in reservoirs with a water temperature gradient of ≥5℃.

[0092] 2. Multiple units in parallel.

[0093] Specifically, it is planned to add 4 ORC sets and 2 TEG sets to the adjacent QH reservoir in 2025 to form a "reservoir micro-grid group". Through MQTT cloud-based collaborative scheduling, the annual power generation is expected to be ≥20 MWh, which can fully cover all online monitoring and landscape lighting needs in the reservoir area, and further expand the application scope of the invention.

[0094] Through the above full-process and fully quantified implementation record, the present invention has verified all the technical points of claims 1–8 in real engineering projects, and fully demonstrated the significant advantages of "zero external power, zero chemical agents, and zero manual operation", providing a replicable and scalable technical paradigm for similar reservoirs.

[0095] Example 3 This invention also provides a device for the linkage between temperature difference power generation and eutrophication early warning and control of reservoir stratified water intake, such as... Figure 4 As shown, the device 10 includes: The power supply module 100 is used to install water intake devices above and below the thermocline of the reservoir, respectively, to obtain the upper low-temperature water and the lower high-temperature water through the water intake devices, and to generate electricity by using the temperature difference between the water bodies to power the water quality monitoring, early warning and control equipment. The data acquisition module 200 is used to acquire water quality monitoring data of the reservoir based on the water quality monitoring equipment, and output an eutrophication risk index based on the water quality monitoring data through a prediction model. The regulation and execution module 300 is used to adjust the water intake strategy of the upper and lower layers based on a bi-objective optimization algorithm when the eutrophication risk index reaches the warning threshold, and to control the upper and lower tailwater after power generation to be reinjected in a directional manner according to the reinjection strategy corresponding to the water intake strategy, so as to form controllable vertical convection to destroy the optimal growth layer of algae.

[0096] Example 4 To implement the methods of the above embodiments, the present invention also provides a computer device, which includes a memory and a processor; wherein the processor runs a program corresponding to the executable program code by reading executable program code stored in the memory, so as to implement the various steps of the methods described above.

[0097] Example 5 To implement the above embodiments, this application also proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method described in the foregoing embodiments.

[0098] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0099] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0100] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

Claims

1. A method for linking temperature difference power generation and eutrophication early warning and control in reservoir stratified water intake, characterized in that, Includes the following steps: S1 obtains the upper low-temperature water body and the lower high-temperature water body of the thermocline of the reservoir, and uses the temperature difference between the two types of water bodies to generate electricity to power water quality monitoring, early warning and control equipment. S2, Obtain water quality monitoring data of the reservoir through water quality monitoring equipment, and output the chlorophyll a peak index Ic based on the water quality monitoring data using a prediction model; S3, when the chlorophyll a peak index Ic reaches the warning threshold, the water intake strategy of the upper and lower layers is adjusted based on the dual-objective optimization algorithm, and the upper and lower tailwater after power generation is directionally reinjected according to the reinjection strategy corresponding to the water intake strategy to form controllable vertical convection and destroy the optimal growth layer of algae.

2. The method according to claim 1, characterized in that, The method of obtaining the upper low-temperature water body and the lower high-temperature water body of the thermocline of the reservoir, and using the temperature difference between the two types of water bodies to generate electricity to power water quality monitoring, early warning and control equipment, includes: S11, the upper low-temperature water body and the lower high-temperature water body are obtained through the first water intake and the second water intake installed on the liftable guide rail, respectively; S12, the upper low-temperature water body and the lower high-temperature water body are respectively introduced into a micro organic Rankine cycle unit or thermoelectric generator array through insulated pipes, and thermoelectric power generation is completed through the unit or array; S13, the electrical energy output by the micro organic Rankine cycle unit or thermoelectric generator array is converted into a microgrid by a DC-DC converter and an energy storage device, and the microgrid supplies power to all equipment. Excess power is fed into the grid through a grid-connected inverter.

3. The method according to claim 1, characterized in that, The process of acquiring water quality monitoring data from the reservoir using water quality monitoring equipment, and outputting the chlorophyll a peak index Ic based on the water quality monitoring data using a prediction model, includes: S21, Multi-parameter water quality probes are installed at the water intake and tailwater reinjection nozzles to collect data on temperature, dissolved oxygen, chlorophyll a, cyanobacterial protein, nitrate nitrogen, phosphate phosphorus and flow rate in real time through the probes; S22, the collected data is uploaded to the edge computing node via a LoRa self-organizing network; wherein, the LoRa self-organizing network adopts 470MHz Class A mode; S23 inputs the preprocessed monitoring data into a prediction model built on long short-term memory network and attention mechanism, and outputs the chlorophyll a peak index Ic for the next 4 hours, 8 hours, 24 hours and 48 hours.

4. The method according to claim 1, characterized in that, When the chlorophyll a peak index Ic reaches the warning threshold, the water intake strategies for the upper and lower layers are adjusted based on a dual-objective optimization algorithm. The upper and lower tailwater after power generation are then directionally reinjected according to the reinjection strategy corresponding to the water intake strategy, forming controllable vertical convection and disrupting the optimal algal growth layer. This includes: S31 uses the dual objectives of minimizing the chlorophyll a peak index Ic and maximizing power generation to optimize the variables in real time; among these variables are the water intake opening degree. Tailwater reinjection split ratio ; S32, the optimized tailwater is directionally injected through a vector reinjection nozzle, so that the high-temperature tailwater in the lower layer is injected upward to form an upward flow velocity, and the low-temperature tailwater in the upper layer is pulsed downward; wherein, the vector reinjection nozzle supports 360° rotation and integrates a static mixer inside, through which the dissolved oxygen concentration of the water before injection is increased to a preset concentration.

5. The method according to claim 1, characterized in that, Also includes: S4. During and after regulation, the parameters of the prediction model and the dual-objective optimization algorithm are updated online based on the system operation data through reinforcement learning algorithm, and the subsequent water intake strategy and reinjection strategy are dynamically optimized to achieve the dual objectives of long-term stable reduction of eutrophication risk and system energy self-sufficiency. The system operation data includes the execution parameters of the dual-objective optimization algorithm, the water quality response data after tailwater reinjection, and the real-time power generation and energy efficiency ratio (EER) data.

6. The method according to claim 1, characterized in that, Also includes: S5, integrate all the equipment for performing the method and install it on the floating platform, fix the floating platform in the reservoir by the anchoring system, and equip it with photovoltaic auxiliary panels for supplementary power supply.

7. A reservoir stratified water intake temperature difference power generation and eutrophication early warning linkage control device, characterized in that, include: The power supply module is used to obtain the upper low-temperature water body and the lower high-temperature water body of the thermocline of the reservoir, and to generate electricity by utilizing the temperature difference between the two types of water bodies to power water quality monitoring, early warning and control equipment. The data acquisition module is used to acquire water quality monitoring data of the reservoir through water quality monitoring equipment, and output the chlorophyll a peak index Ic based on the water quality monitoring data using a prediction model. The regulation and execution module is used to adjust the water intake strategy of the upper and lower layers based on a dual-objective optimization algorithm when the chlorophyll a peak index Ic reaches the warning threshold, and to control the upper and lower tailwater after power generation to be reinjected in a directional manner according to the reinjection strategy corresponding to the water intake strategy, so as to form controllable vertical convection and destroy the optimal growth layer of algae.

8. A computer device, characterized in that, Including processor and memory; The processor reads the executable program code stored in the memory to run the program corresponding to the executable program code, so as to implement the method for linkage regulation of temperature difference power generation and eutrophication early warning of reservoir stratified water intake as described in any one of claims 1-6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements a method for linking temperature difference power generation and eutrophication early warning and control of reservoir stratified water intake as described in any one of claims 1-6.

Images