Adaptive adjustment double synergistic sewage treatment method and treatment system

Abstract

The present application relates to sewage treatment technical field, disclose a kind of self-adapting adjustment's double collaborative sewage treatment method and processing system, system includes MFC module, solar cell module, partial pressure regulating unit, the power storage module of electrically connecting MFC module and solar cell module and the sensing module for real-time monitoring operating parameter in sewage treatment process;Method includes: according to weather parameter, real-time adjustment solar panel angle;Real-time monitoring operating parameter of MFC module, and according to monitored parameter, determine the best bias voltage interval of MFC module;According to the bias voltage actually generated by solar cell module, the bias voltage of solar cell module supplied to MFC module is regulated to the best bias voltage interval, and additional electric energy is stored to power storage module.The present application can determine the best bias voltage interval of MFC module, the voltage provided by solar cell module is divided to provide suitable bias voltage, to improve sewage treatment efficiency.

Description

Technical Field

[0001] This invention relates to the field of wastewater treatment technology, and in particular to an adaptively adjustable dual-cooperative wastewater treatment method and an adaptively adjustable dual-cooperative wastewater treatment system. Background Technology

[0002] With the global water supply and demand imbalance intensifying and water pollution becoming a prominent issue, research on wastewater treatment processes has become particularly important.

[0003] Existing wastewater treatment systems generally employ the activated sludge process. The activated sludge process essentially utilizes activated sludge formed by aerobic microbial communities (bacteria, protozoa, and fungi, etc.) to adsorb, oxidize, and decompose dissolved organic matter in water under aerobic conditions. It can also achieve nitrification (denitrification), denitrification, and biological phosphorus removal. However, existing wastewater treatment systems often have high energy consumption, requiring energy not only but also failing to achieve energy recovery. Therefore, they are no longer suitable for the needs of green and low-carbon development.

[0004] Microbial fuel cells (MFCs) are devices that utilize microorganisms to directly convert the chemical energy of organic matter in wastewater into electrical energy. MFCs can directly convert the chemical energy of wastewater into electrical energy, purifying the wastewater while simultaneously generating electricity. A typical design of a microbial fuel cell employs a dual-chamber structure. The anode chamber, containing the microorganisms, is isolated from the cathode chamber by a proton exchange membrane. Electrons generated during the degradation of organic matter by anaerobic microorganisms in the anode chamber are transferred from the anode to the cathode chamber via an external circuit. Simultaneously, protons also pass through the proton exchange membrane from the anode chamber to the cathode chamber, forming a current loop. This loop connects to electrical components to recover or utilize electrical energy. Oxygen molecules, protons, and electrons combine in the cathode chamber to generate water. Microbial catalysis generates electrons from the anode, which are conducted through the external circuit to the cathode for reaction, producing current in the loop. This constitutes the microbial fuel cell. Typical MFCs are not only complex in construction, expensive, and have high internal resistance, but also require significant external power, limiting their energy production efficiency and widespread application.

[0005] The development of microbial fuel cells is currently constrained by their relatively low power generation performance. Besides high cost, the main reason is the low power density, with open-circuit voltage typically around 300mV to 400mV. The factors determining the power density of microbial fuel cells mainly include: the degradation rate of the substrate by the microorganisms, the electron transfer rate from the microorganisms to the anode, the internal resistance of the cell, the proton transfer rate to the cathode, the oxidant supply and the rate of reduction reaction at the cathode, and the catalytic effect of the cathode material.

[0006] The electron and proton transport rates are significantly affected by the bias voltage provided by the external circuit. Current technologies typically use an external power grid to provide a fixed bias voltage to the microbial fuel cell. This method consumes power from the external grid and is not energy-efficient. Furthermore, to ensure safety, the provided bias voltage is generally within a safe voltage range, which is not conducive to the efficient operation of the microbial fuel cell.

[0007] In order to reduce the energy consumption of microbial fuel cells that rely on external power grids, some technical solutions have proposed using solar cell modules to provide bias voltage for microbial fuel cells.

[0008] Both of the above methods only consider the bias energy source of the microbial fuel cell, but neither takes into account the matching between the microbial community conditions of the microbial fuel cell and the bias voltage.

[0009] Our team's research found that the bias provided by microbial fuel cells needs to take into account fluctuations in two factors.

[0010] The first type of fluctuation factor is the fluctuation of wastewater quality conditions. Specifically, as wastewater treatment processes progress, wastewater quality conditions fluctuate (e.g., changes in COD, pH, and water temperature), thus altering the bias voltage required by the microbial fuel cell. Under these fluctuating conditions, the existing technology, which uses an external power grid to continuously provide a fixed bias voltage to the microbial fuel cell, cannot adapt to the changing bias voltage requirements of the microbial fuel cell, resulting in poor power generation performance.

[0011] The second type of fluctuation factor is the fluctuation of microbial community activity. Specifically, the activity of microbial communities fluctuates based on changes in COD, pH, and water temperature. For example, in the high temperatures of summer, the wastewater temperature is higher than the optimal environmental temperature for microorganisms, inhibiting the activity of microorganisms in the microbial fuel cell and reducing its power generation capacity. Simultaneously, the bias voltage provided by the solar cell module to the microbial fuel cell is very high during the summer days, and directly utilizing this high bias voltage can further damage the stability of the microbial community. Furthermore, due to the instability of solar radiation intensity, not only can the intensity of light differ drastically between adjacent days (e.g., sunny days and rainy days), but even within the same day, the intensity of light can vary significantly at different times. Under the alternating effects of strong day and night light and high temperatures, microorganisms are repeatedly subjected to stress, causing repeated fluctuations in their metabolic capacity, which can have a more detrimental effect on them. Therefore, an inappropriate bias voltage provided by the solar cell module may inhibit the power generation efficiency and wastewater treatment efficiency of the microbial fuel cell.

[0012] Therefore, the technical problem with existing wastewater treatment methods is that neither using an external power grid to provide a fixed bias voltage to the microbial fuel cell nor using a solar cell module to provide bias voltage to the microbial fuel cell takes into account the impact of fluctuations in wastewater quality and microbial community activity on the bias voltage demand. As a result, an inappropriate bias voltage supply will have an adverse effect on the power generation performance of the microbial fuel cell, leading to low wastewater treatment efficiency. Summary of the Invention

[0013] The main objective of this invention is to provide an adaptive and synergistic wastewater treatment method and system, which aims to solve the technical problem that existing wastewater treatment methods using microbial fuel cells do not take into account fluctuations in wastewater quality and microbial community activity during the bias supply process, which adversely affects the power generation performance of the microbial fuel cell and leads to low wastewater treatment efficiency.

[0014] To achieve the above objectives, this invention provides an adaptively adjustable dual-cooperative wastewater treatment method. The wastewater treatment system employs an adaptively adjustable dual-cooperative wastewater treatment system, which includes an MFC module, a solar cell module, a voltage regulator unit, an energy storage module, and a sensing module. The voltage regulator unit regulates the bias voltage provided by the solar cell module to the MFC module. The energy storage module is electrically connected to both the MFC module and the solar cell module. The sensing module monitors the operating parameters during the wastewater treatment process in real time. The MFC module and the solar cell module provide dual-cooperative power for the wastewater treatment process. The operating parameters include COD, water temperature, pH, light intensity, voltage, and current. The method includes: Based on meteorological parameters, the solar cell module adjusts the angle of the solar panel to be perpendicular to the angle of solar incidence in order to enable the solar cell module to generate electricity at maximum power. The system monitors the operating parameters of the MFC module in real time, predicts the optimal operating conditions, and automatically adjusts the control parameters of the MFC module based on the predicted optimal operating conditions to ensure that the wastewater treatment system is in an optimized state of production capacity and carbon capture. Determine the optimal bias range for the MFC module based on its operating parameters; Based on the actual bias voltage generated by the solar cell module, the circuit load is adjusted through the voltage divider adjustment unit to adjust the bias voltage provided by the solar cell module to the MFC module to the preset optimal bias voltage range, and the electrical energy outside the optimal bias voltage range provided by the solar cell module is stored in the energy storage module. When the energy storage module is at or after it is fully charged, the tracking angle of the solar cell module is controlled so that the bias voltage provided by the solar cell module to the MFC module is within the corrected optimal bias voltage range.

[0015] Optionally, the step of adjusting the angle of the solar panel to be perpendicular to the angle of solar incidence based on meteorological parameters, so as to enable the solar panel module to generate electricity at maximum power, includes: Preset light intensity threshold; When the actual monitored light intensity is less than the light intensity threshold, the energy storage module or the external power grid is used to provide the MFC module with a bias voltage that meets the optimal bias voltage range. When the actual monitored light intensity reaches the light intensity threshold, based on the current date and the latitude and longitude of the location of the sewage treatment system, the sunrise and sunset times of the solar panel location and the solar incidence angle at each moment are predicted, and the solar cell module is controlled to adjust the angle of the solar panel to be perpendicular to the solar incidence angle at each moment.

[0016] Optionally, the step of real-time monitoring of the operating parameters of the MFC module, predicting optimal operating conditions, and automatically adjusting the control parameters of the MFC module based on the predicted optimal operating conditions to ensure the wastewater treatment system is in an optimized capacity and carbon capture state includes: Obtain the measured running parameters of each MFC module, and obtain the static optimal range corresponding to each running parameter. Based on the static optimal range of each running parameter, determine the optimal running conditions. Determine whether each running parameter is within its corresponding static optimal range; If not, the operating parameters that exceed the static optimal range will be determined as the target operating parameters; Optionally, the control parameters of the MFC module are automatically adjusted according to a preset adjustment strategy to bring the target operating parameters into the corresponding static optimal range. When the target operating parameters fail to be adjusted to the static optimal range, the parameter range for dynamic optimization is determined based on the actual values ​​of the target operating parameters in order to adaptively adjust the optimal operating conditions and keep the wastewater treatment system in an optimized capacity and carbon capture state.

[0017] Optionally, the step of automatically adjusting the control parameters of the MFC module according to a preset adjustment strategy to adjust the target operating parameters to the corresponding static optimal range includes: When the water temperature is higher than the optimal water temperature range, the MFC module is controlled to reduce the afternoon sewage flow and increase the proportion of nighttime water intake in order to lower the water temperature through nighttime water intake. When the water temperature is below the optimal range, the MFC module is moved closer to the anaerobic tank and placed in a sunny, south-facing position to increase the water temperature by absorbing heat from the sunlight.

[0018] Optionally, the step of automatically adjusting the control parameters of the MFC module according to a preset adjustment strategy to adjust the target operating parameters to the corresponding static optimal range further includes: When the pH is below the optimal pH range, the alkaline sludge from the aerobic or anaerobic section of the wastewater treatment system is returned to the MFC module. When the pH is greater than the optimal pH range, remove the amount of alkaline sludge from the aerobic or anaerobic section.

[0019] Optionally, the step of automatically adjusting the control parameters of the MFC module according to a preset adjustment strategy to adjust the target operating parameters to the corresponding static optimal range further includes: When the COD is greater than the optimal COD range, use influent water that is lower than the preset COD range to reduce the COD value; When the COD is below the optimal COD range, reduce the influent flow rate of the MFC module and extend the hydraulic retention time.

[0020] Optionally, after the steps of adjusting the circuit load through a voltage divider adjustment unit according to the actual bias voltage generated by the solar cell module to adjust the bias voltage provided by the solar cell module to the MFC module to a preset optimal bias voltage range, and storing the electrical energy outside the optimal bias voltage range provided by the solar cell module to the energy storage module, the method further includes: Determine if the energy storage module is fully charged; When the energy storage module is not fully charged, the solar cell module continues to charge the energy storage module. When the energy storage module is fully charged, the solar cell module disconnects from the energy storage module so that the energy storage module can supply power to the external power grid.

[0021] Optionally, the method further includes: Based on the collected pH and COD, predict whether there is membrane fouling or microbial dysbiosis; If so, trigger a warning signal.

[0022] Optionally, the step of controlling the tracking angle of the solar cell module so that the bias voltage provided by the solar cell module to the MFC module is within the corrected optimal bias voltage range when the energy storage module is at a preset critical full state or after it is fully charged further includes: The energy storage status of the energy storage module is detected. When the energy storage status of the energy storage module is at a preset critical full state or after it is full, a set of micro-perturbation pulse voltages are periodically applied to the MFC module, and the current polarization curve is reconstructed based on the current response. Identify the inflection point voltage on the reconstructed polarization curve; The optimal bias range is corrected to control the average bias voltage provided to the MFC module to be lower than the inflection point voltage, so that the MFC module operates in metastable state within the power peak range. Thus, based on the corrected optimal bias range, the tracking angle of the solar cell module is controlled to avoid voltage collapse caused by the bias voltage provided to the MFC module entering the polarization region.

[0023] To achieve the above objectives, this invention also proposes an adaptive dual-cooperative wastewater treatment system. The system employs an adaptive dual-cooperative wastewater treatment method, comprising an MFC module, a solar cell module, a voltage regulator unit, an energy storage module, and a sensing module. The voltage regulator unit regulates the bias voltage provided by the solar cell module to the MFC module. The energy storage module is electrically connected to both the MFC module and the solar cell module. The sensing module monitors the operating parameters during the wastewater treatment process in real time. The MFC module and the solar cell module provide dual-cooperative power for the wastewater treatment process, and the operating parameters include COD, water temperature, pH, light intensity, voltage, and current.

[0024] This invention addresses the problem in existing wastewater treatment methods using microbial fuel cells that fail to consider fluctuations in wastewater quality and microbial community activity during the bias supply process. This negatively impacts the power generation performance of the microbial fuel cell, leading to low wastewater treatment efficiency. The specific analysis is as follows: This invention achieves dual-coordinated power supply for wastewater treatment through an MFC module and a solar cell module, integrating the high-efficiency solar cell module with the anode and cathode of the MFC module. Based on the operating parameters of the MFC module, the optimal bias range for the MFC module is determined. The solar cell module provides bias to the MFC module within this optimal range, and excess solar energy can be stored in an energy storage module. When there is no light or poor lighting conditions, and bias is needed to power the MFC module, electrical energy can be output from the energy storage module. The high voltage generated by the solar cell module under sunlight can serve as a suitable bias for the MFC module, significantly improving the electron transfer efficiency of microorganisms and the total power output of the system. This enables an all-weather power production mode where solar energy dominates power generation on sunny days, while microorganisms provide continuous power on cloudy days and at night. Simultaneously, this invention also replaces external grid power with solar energy to provide a suitable bias for the MFC module, achieving energy savings while significantly improving the electron transfer efficiency of microorganisms and the total power output of the system through a suitable bias, thus helping to reduce energy consumption in wastewater treatment.

[0025] Furthermore, this invention tracks the solar incidence angle in real time based on meteorological parameters and automatically adjusts the angle of the solar panel to be perpendicular to the solar incidence angle to achieve maximum power generation. Simultaneously, it monitors the operating parameters of the MFC module, such as water temperature, pH, and COD, and adjusts these parameters in real time to maintain them at the predicted optimal operating conditions. This determines the optimal bias range for the MFC module, and then, through a series voltage divider adjustment unit, adjusts the circuit load to precisely adjust the bias of the MFC module to the optimal bias range, ensuring that the MFC module is always in optimal operating condition and improving the overall power generation density of the system. Moreover, the power supplied by the solar cell module to the MFC module, in addition to the bias provided by the solar cell module, is stored in an energy storage module to ensure that the MFC module maintains efficient operation in the absence of light or insufficient light conditions, thanks to the bias provided by the energy storage module. Therefore, this invention provides power to wastewater treatment in synergy with an MFC module and a solar cell module. Simultaneously, based on operating parameters and predicted optimal operating conditions, it adaptively adjusts the wastewater treatment system to achieve optimized capacity and carbon capture. The operating parameters and predicted optimal operating conditions of the MFC module reflect fluctuations in wastewater quality and microbial community activity, thus adaptively providing the MFC module with the optimal bias range and storing excess energy in the energy storage module. Furthermore, when the energy storage module is at a preset critical full state or fully charged, it can reversely adjust the tracking angle of the solar cell module to maintain the optimal bias range for the MFC module. This avoids the adverse effects of an unsuitable bias range on the power generation performance of the microbial fuel cell, thus maintaining optimized synergistic conditions for wastewater treatment and improving wastewater treatment efficiency. Attached Figure Description

[0026] Figure 1 This is a schematic flowchart of the first embodiment of the wastewater treatment method of the present invention; Figure 2 This is a flowchart illustrating the process of adjusting operating parameters in the MFC module of this invention. Figure 3 A flowchart illustrating an embodiment of the solar cell module power adjustment and energy storage module power supply of the present invention; Figure 4 This is a schematic diagram of the physical embodiment of the present invention. Detailed Implementation

[0027] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0028] In the following description, the use of suffixes such as "unit," "component," or "element" to denote elements is solely for the purpose of illustrative purposes and has no specific meaning in itself. Therefore, "unit," "component," or "element" may be used interchangeably.

[0029] Please see Figures 1 to 4 The first embodiment of the present invention provides an adaptive dual-cooperative wastewater treatment method, which uses an adaptive dual-cooperative wastewater treatment system for wastewater treatment. The wastewater treatment system includes an MFC module, a solar cell module, a voltage regulator unit, an energy storage module, and a sensing module. The voltage regulator unit is used to regulate the bias voltage provided by the solar cell module to the MFC module. The energy storage module is electrically connected to both the MFC module and the solar cell module. The sensing module is used to monitor the operating parameters during the wastewater treatment process in real time. The MFC module and the solar cell module provide dual-cooperative power for the wastewater treatment. The operating parameters include COD (Chemical Oxygen Demand), water temperature, pH, light intensity, voltage, and current. The method includes: Step S10: According to meteorological parameters, the solar cell module adjusts the angle of the solar panel to be perpendicular to the angle of solar incidence, so as to enable the solar cell module to generate electricity at maximum power. Step S20: Monitor the operating parameters of the MFC module in real time, predict the optimal operating conditions, and automatically adjust the control parameters of the MFC module according to the predicted optimal operating conditions so that the wastewater treatment system is in an optimized capacity and carbon capture state. Step S30: Determine the optimal bias range of the MFC module based on its operating parameters; Step S40: Based on the actual bias voltage generated by the solar cell module, the circuit load is adjusted through the voltage divider adjustment unit to adjust the bias voltage provided by the solar cell module to the MFC module to the preset optimal bias voltage range, and the electrical energy outside the optimal bias voltage range provided by the solar cell module is stored in the energy storage module. Step S50: When the energy storage module is at a preset critical full state or after it is fully charged, control the tracking angle of the solar cell module so that the bias voltage provided by the solar cell module to the MFC module is in the corrected optimal bias voltage range.

[0030] This invention addresses the problem in existing wastewater treatment methods using microbial fuel cells that fail to consider fluctuations in wastewater quality and microbial community activity during the bias supply process. This negatively impacts the power generation performance of the microbial fuel cell, leading to low wastewater treatment efficiency. The specific analysis is as follows: This invention achieves dual-coordinated power supply for wastewater treatment through an MFC module and a solar cell module, integrating the high-efficiency solar cell module with the anode and cathode of the MFC module. Based on the operating parameters of the MFC module, the optimal bias range for the MFC module is determined. The solar cell module provides bias to the MFC module within this optimal range, and excess solar energy can be stored in an energy storage module. When there is no light or poor lighting conditions, and bias is needed to power the MFC module, electrical energy can be output from the energy storage module. The high voltage generated by the solar cell module under sunlight can serve as a suitable bias for the MFC module, significantly improving the electron transfer efficiency of microorganisms and the total power output of the system. This enables an all-weather power production mode where solar energy dominates power generation on sunny days, while microorganisms provide continuous power on cloudy days and at night. Simultaneously, this invention also replaces external grid power with solar energy to provide a suitable bias for the MFC module, achieving energy savings while significantly improving the electron transfer efficiency of microorganisms and the total power output of the system through a suitable bias, thus helping to reduce energy consumption in wastewater treatment. Furthermore, based on the energy storage status of the energy storage module, the tracking angle of the solar cell module is adjusted in reverse to maintain the optimal bias range when the energy storage capacity is insufficient. Therefore, this invention evaluates fluctuations in wastewater quality conditions and microbial community activity by using the operating parameters of the MFC module and the predicted optimal operating conditions, providing a suitable bias range. This avoids the adverse effects of an unsuitable bias range on the power generation performance of the microbial fuel cell, thus improving wastewater treatment efficiency.

[0031] Furthermore, this invention tracks the solar incidence angle in real time based on meteorological parameters and automatically adjusts the angle of the solar panel to be perpendicular to the solar incidence angle to achieve maximum power generation. Simultaneously, it monitors the operating parameters of the MFC module, such as water temperature, pH, and COD, and adjusts these parameters in real time to maintain them at the predicted optimal operating conditions. This determines the optimal bias range for the MFC module, and then, through a series voltage divider adjustment unit, adjusts the circuit load to precisely adjust the bias of the MFC module to the optimal bias range, ensuring that the MFC module is always in optimal operating condition and improving the overall power generation density of the system. Moreover, the power supplied by the solar cell module to the MFC module, in addition to the bias provided by the solar cell module, is stored in an energy storage module to ensure that the MFC module maintains efficient operation in the absence of light or insufficient light conditions, thanks to the bias provided by the energy storage module. Therefore, this invention provides power to wastewater treatment in synergy with an MFC module and a solar cell module. Simultaneously, based on operating parameters and predicted optimal operating conditions, it adaptively adjusts the wastewater treatment system to achieve optimized capacity and carbon capture. The operating parameters and predicted optimal operating conditions of the MFC module reflect fluctuations in wastewater quality and microbial community activity, thus adaptively providing the MFC module with the optimal bias range and storing excess energy in the energy storage module. Furthermore, when the energy storage module is at a preset critical full state or fully charged, it can reversely adjust the tracking angle of the solar cell module to maintain the optimal bias range for the MFC module. This avoids the adverse effects of an unsuitable bias range on the power generation performance of the microbial fuel cell, thus maintaining optimized synergistic conditions for wastewater treatment and improving wastewater treatment efficiency.

[0032] In the current context of escalating global water supply and demand imbalances and prominent water pollution problems, traditional wastewater treatment processes, such as the activated sludge process, suffer from core drawbacks including high energy consumption, large sludge production, incomplete removal of recalcitrant pollutants (antibiotics, dyes, etc.), and inability to recover energy, making them unsuitable for the demands of green and low-carbon development. Therefore, this invention introduces an MFC-PSC wastewater treatment system that couples microbial fuel cells (MFCs) with perovskite solar cell (PSC) modules. This synergistic approach overcomes the bottlenecks of traditional processes: on the one hand, leveraging the high-efficiency degradation advantages of MFC modules, it significantly improves the removal rates of pollutants such as COD, ammonia nitrogen, and heavy metals, substantially reducing sludge production and mitigating the risk of secondary pollution; on the other hand, utilizing the energy conversion characteristics of MFC modules, it converts the chemical energy in wastewater into electrical energy to power the system operation or peripheral equipment, achieving energy self-sufficiency or even surplus, while simultaneously recovering heavy metal resources, thus achieving the dual goals of pollution control and resource recycling.

[0033] Specifically, solar cell modules (PSC), microbial fuel cells (MFC), and energy storage modules (batteries / supercapacitors) are integrated into the same wastewater treatment system. Through intelligent control, the three components can dynamically switch and coordinate to provide energy under different lighting conditions, enabling the system to operate 24 / 7 and adaptively.

[0034] Furthermore, the STM32 main control chip can be used in conjunction with a multi-sensor network to monitor system operating parameters (such as COD, water temperature, pH, light intensity, voltage and current, etc.) in real time. By dynamically adjusting the bias voltage provided by the solar cell module to the MFC module, the electron transfer efficiency can be optimized, the pollutant degradation rate can be improved, and the system's power generation performance can be enhanced.

[0035] In addition, the wastewater treatment system has the ability to monitor and adaptively adjust the operating environment of the MFC module (such as COD, water temperature, pH, hydraulic retention time, etc.) in real time, and can predict problems such as microbial community imbalance and membrane fouling through data pattern recognition, so as to achieve predictive maintenance and precise intervention.

[0036] The optimal bias range is determined by applying different bias voltages to different MFC module operating parameter ranges, and testing to find the range with the best power generation capacity. A mapping table between operating parameters and the optimal bias range is then created based on the test results.

[0037] In a first embodiment of the adaptively adjustable dual-synergistic wastewater treatment method of the present invention, and in a second embodiment of the same method, the step of adjusting the angle of the solar panel to be perpendicular to the angle of solar incidence based on meteorological parameters to achieve maximum power generation by the solar panel module includes: Step S11: Preset light intensity threshold; Step S12: When the actual monitored light intensity is less than the light intensity threshold, the energy storage module or the external power grid is used to provide the MFC module with a bias voltage that meets the optimal bias voltage range. Step S13: When the actual monitored light intensity reaches the light intensity threshold, based on the current date and the latitude and longitude of the location of the sewage treatment system, predict the sunrise and sunset times of the solar panel location and the solar incidence angle at each moment, and control the solar cell module to adjust the angle of the solar panel to be perpendicular to the solar incidence angle at each moment.

[0038] In this embodiment, the preset light intensity threshold is the light intensity threshold under sunny conditions; specifically, the solar cell module can be a novel compound thin-film solar cell module using perovskite materials as the light-absorbing layer; perovskite is a general term for a class of crystalline materials with an ABX3 structure, and there are many types of materials that can be selected; its structure mainly consists of five key parts: a transparent conductive substrate, an electron transport layer, a perovskite light-absorbing layer, a hole transport layer, and a metal electrode; the principle is as follows: Light absorption and exciton generation: When sunlight shines on the perovskite light-absorbing layer, photon energy is absorbed, causing valence band electrons to jump to the conduction band, forming electron-hole pairs (excitons). Perovskite materials have high light absorption coefficients and tunable band gaps, enabling effective utilization of the visible spectrum. Carrier separation and transport: Excitons separate into free electrons and holes within the perovskite layer; electrons are transported to the negative electrode through the electron transport layer (ETL), and holes are transported to the positive electrode through the hole transport layer (HTL); ETL and HTL (such as TiO2 or spiro-OMeTAD) can selectively extract corresponding carriers, reducing recombination losses; Charge collection and current generation: Electrons and holes are collected by electrodes (such as ITO / FTO transparent electrodes and metal electrodes), and current is generated through external circuits to realize the conversion of light energy into electrical energy; the battery structure usually includes a perovskite layer, ETL, HTL and electrode layer, and each layer works together to optimize efficiency.

[0039] In a first embodiment of the adaptively adjustable dual-cooperative wastewater treatment method of the present invention, and in a third embodiment of the same method, the step of real-time monitoring of the operating parameters of the MFC module, predicting the optimal operating conditions, and automatically adjusting the control parameters of the MFC module based on the predicted optimal operating conditions to ensure the wastewater treatment system is in an optimized capacity and carbon capture state includes: Step S21: Obtain the measured operating parameters of the MFC module and obtain the static optimal range corresponding to each operating parameter. Determine the optimal operating condition based on the static optimal range of each operating parameter. Step S22: Determine whether each running parameter is within its corresponding static optimal range; Step S23: If not, determine the operating parameters that exceed the static optimal range as the target operating parameters; Step S24: According to the preset adjustment strategy, automatically adjust the control parameters of the MFC module to adjust the target operating parameters to the corresponding static optimal range; Step S25: When the target operating parameters fail to be adjusted to the static optimal range, determine the dynamically optimized parameter range based on the actual values ​​of the target operating parameters to adaptively adjust the optimal operating conditions, so that the wastewater treatment system is in an optimized capacity and carbon capture state.

[0040] In this embodiment, the technical support for the MFC module, i.e., the microbial fuel cell, covers multiple aspects, aiming to improve its performance, stability, and application scope; the relevant technical support is summarized below from key areas: Electrode material development: By developing high-performance anode and cathode materials (such as carbon-based materials and nanostructured electrodes), electron transfer efficiency can be enhanced, thereby improving power generation capacity; Optimized operating conditions: Precisely control parameters such as water temperature, pH, and substrate concentration (e.g., COD) to maintain microbial activity and system stability, and improve energy conversion efficiency; Internal resistance reduction strategies: Utilize optimized membrane materials, electrode spacing design, or reactor structure to reduce ion and electron transport resistance and decrease energy loss; Reactor structural design: Innovative designs (such as spiral baffles and stacked structures) are used to increase the electrode surface area, improve the mass transfer process, and enhance power output; Microbial community regulation: By selectively enriching highly electroactive bacterial groups (such as Pseudomonas and anaerobic bacteria), electron transport pathways are optimized to improve the synergistic efficiency of organic matter degradation and electricity generation; These technologies collectively support the application potential of MFC modules in wastewater treatment, soil remediation, biosensors and other fields. In addition, the operating parameters of the MFC module are measurable physical quantities or process indicators of the real-time operating status of the MFC module, such as water temperature, pH, COD, BOD (Biochemical Oxygen Demand), external resistance, etc.; the static optimal range is a range of values ​​for a certain operating parameter that is pre-set based on experience, experiments or theoretical models and is considered to enable the MFC module to be in a better state of production capacity and decarbonization; the optimal operating condition refers to the overall operating state in which a group (or more) of operating parameters are controlled within their respective optimal ranges or target values; carbon capture is the effective oxidation / conversion of organic matter by microorganisms into extracellular electrons rather than CO2 emission, or the capture of carbon through subsequent gas collection.

[0041] In a third embodiment of the adaptive adjustment dual-cooperative wastewater treatment method of the present invention, and in a fourth embodiment of the adaptive adjustment dual-cooperative wastewater treatment method of the present invention, the step of automatically adjusting the control parameters of the MFC module according to a preset adjustment strategy to adjust the target operating parameters to the corresponding static optimal range includes: Step S241: When the water temperature is greater than the optimal water temperature range, control the MFC module to reduce the afternoon sewage flow and increase the nighttime water intake ratio in order to lower the water temperature through nighttime water intake. Step S242: When the water temperature is below the optimal water temperature range, control the MFC module to move closer to the anaerobic tank and place it in a sunny south-facing position to increase the water temperature by absorbing heat from the sunlight.

[0042] In this embodiment, the target operating parameter is the water temperature of the MFC module. The static optimal range refers to the fixed temperature range (e.g., 28℃–34℃) obtained through calibration under steady-state experimental conditions, which makes the power generation performance of the MFC module optimal and does not change with real-time load fluctuations.

[0043] In a third embodiment of the adaptive adjustment dual-cooperative wastewater treatment method of the present invention, and in a fifth embodiment of the adaptive adjustment dual-cooperative wastewater treatment method of the present invention, the step of automatically adjusting the control parameters of the MFC module according to a preset adjustment strategy to adjust the target operating parameters to the corresponding static optimal range further includes: Step S243: When the pH is less than the optimal pH range, the alkaline sludge from the aerobic or anaerobic section of the wastewater treatment system is returned to the MFC module. Step S244: When the pH is greater than the optimal pH range, remove the amount of alkaline sludge from the aerobic or anaerobic section.

[0044] In this embodiment, the aerobic section is a biological reaction zone where oxygen is continuously supplied to the wastewater, and aerobic microorganisms degrade pollutants and nitrify ammonia nitrogen into nitrate. The anaerobic section refers to a reaction zone where no oxygen is supplied and no nitrate is introduced, and anaerobic microorganisms (or polyphosphate-accumulating bacteria) complete phosphorus release, hydrolysis acidification (for high-concentration organic wastewater), or methane fermentation. Based on the deviation of pH from the optimal pH range, three control levels are defined: slight deviation, moderate deviation, and severe deviation. Correspondingly, three recirculation modes are set: low-flow intermittent recirculation, medium-flow continuous recirculation, and high-flow priority recirculation. At the same time, the influent flow rate of the MFC module is finely adjusted to avoid water quality fluctuations caused by a single recirculation mode and achieve precise and stable pH control.

[0045] In the third embodiment of the adaptive adjustment dual-cooperative wastewater treatment method of the present invention, and in the sixth embodiment of the adaptive adjustment dual-cooperative wastewater treatment method of the present invention, the step of automatically adjusting the control parameters of the MFC module according to a preset adjustment strategy to adjust the target operating parameters to the corresponding static optimal range further includes: Step S245: When the COD is greater than the optimal COD range, reduce the COD value by using influent water that is lower than the preset COD range. Step S246: When the COD is less than the optimal COD range, reduce the water inlet flow of the MFC module and extend the hydraulic retention time.

[0046] In this embodiment, the control parameters can be external resistance, aeration rate, influent flow rate, hydraulic retention time (HRT), electrodes, and voltage, etc.; the static optimal range refers to the optimal COD range; influent below the preset COD range can be treated tailings, rainwater, etc.; hydraulic retention time represents the average time required for water to flow through the MFC module.

[0047] In the first embodiment of the adaptively adjustable dual-cooperative wastewater treatment method of the present invention, and in the seventh embodiment of the adaptively adjustable dual-cooperative wastewater treatment method of the present invention, after the step of adjusting the circuit load according to the actual bias voltage generated by the solar cell module, adjusting the bias voltage provided by the solar cell module to the MFC module to a preset optimal bias voltage range, and storing the electrical energy outside the optimal bias voltage range provided by the solar cell module to the energy storage module, the method further includes: Step S41: Determine whether the energy storage module is fully charged; Step S42: When the energy storage module is not fully charged, the solar cell module continues to charge the energy storage module. Step S43: When the energy storage module is fully charged, the solar cell module disconnects from the energy storage module so that the energy storage module can supply power to the external power grid.

[0048] In this embodiment, the system can have a built-in energy management state machine, which can automatically decide on the energy supply mode (such as direct supply from the solar cell module, power supply from the energy storage module, autonomous operation of the MFC module, etc.) based on parameters such as ambient light intensity, MFC module operating status, and energy storage module power, so as to maximize the system's energy efficiency.

[0049] According to the first embodiment of the adaptively adjustable dual-synergistic wastewater treatment method of the present invention, and the eighth embodiment of the adaptively adjustable dual-synergistic wastewater treatment method of the present invention, the method further includes: Step S60: Based on the collected pH and COD, predict whether there is membrane fouling or microbial dysbiosis. Step S70: If yes, trigger a warning signal.

[0050] In this embodiment, when the pH is detected to continuously deviate from the preset optimal pH range (e.g., 6.0~8.0) and the COD removal rate decreases by more than a preset threshold compared to the baseline value, it is determined to be a risk of microbial community imbalance. When a continuous downward trend in pH of the anode chamber is detected while COD does not increase significantly, and the COD removal rate decreases slowly or the internal resistance of the system increases, it is considered a risk of membrane fouling. If any risk is detected, proceed to step S80 to send a warning signal of the corresponding level to the monitoring terminal. The system has the ability to monitor and adaptively adjust the operating environment of the MFC module (such as COD, water temperature, pH, hydraulic retention time, etc.) in real time, and can predict problems such as microbial community imbalance and membrane fouling through data pattern recognition, so as to achieve predictive maintenance and precise intervention.

[0051] In the first to eighth embodiments of the adaptive adjustment dual-cooperative wastewater treatment method of the present invention, and in the ninth embodiment of the adaptive adjustment dual-cooperative wastewater treatment method of the present invention, the step of controlling the tracking angle of the solar cell module so that the bias voltage provided by the solar cell module to the MFC module is within the corrected optimal bias voltage range after the energy storage module is in a preset critically full state or fully full includes: Step S51: Detect the energy storage state of the energy storage module. When the energy storage state of the energy storage module is at a preset critical full state or after full storage, periodically apply a set of micro-perturbation pulse voltages to the MFC module and reconstruct the current polarization curve based on the current response. Step S52: Identify the inflection point voltage on the reconstructed polarization curve; Step S53: Correct the optimal bias range to control the average bias voltage provided to the MFC module to be lower than the inflection point voltage, so that the MFC module operates in metastable state within the power peak range. Thus, according to the corrected optimal bias range, control the tracking angle of the solar cell module to avoid voltage collapse caused by the bias voltage provided to the MFC module entering the polarization region.

[0052] Specifically, in this embodiment, the polarization curve is an electrochemical characteristic curve plotted with the operating voltage (V) of the MFC module as the vertical axis and the loop response current (I) as the horizontal axis. It is used to characterize the four core parameters of the entire MFC module system: internal resistance, electron transfer capability, output power, and load tolerance limit. The segmented characteristics of the polarization curve are as follows: ① Low current region: steep linear voltage drop (ohmic polarization region); ② Gradual middle section: slowed voltage drop (activation polarization region); ③ Sharp drop at the end: saturation of electron transfer in the microbial community (concentration polarization region); Inflection point voltage: the critical inflection point from ohmic polarization to concentration polarization, corresponding to the maximum power critical voltage of the MFC module.

[0053] In this embodiment, when the energy storage module is about to be full or after it is full, the present invention controls the externally applied bias voltage to be lower than the preset range of the average voltage at the inflection point, so that the MFC module operates in a safe working range close to the maximum power but not reaching the maximum power critical point. When it cannot store electricity, the tracking angle of the solar cell module is controlled to be in the corrected optimal bias range, thus ensuring the maximum efficiency of wastewater degradation, carbon capture, and power generation. At the same time, as the wastewater COD, water temperature, and bacterial activity fluctuate in real time, the inflection point voltage dynamically drifts, and the metastable state can also have voltage fluctuation tolerance space. Furthermore, when there are small voltage fluctuations or adjustment delays in solar tracking and voltage regulation, the metastable state can also offset the impact of circuit voltage regulation fluctuations.

[0054] In this embodiment, when the energy storage module is at a preset critical full state or after it is fully charged, several small-amplitude pulse voltages, i.e., micro-perturbation pulse voltages, are applied to the MFC module every preset time interval. The changes in the MFC module current following the micro-perturbation pulse voltages are recorded. A polarization curve is established using the operating voltage V and the loop response current I as parameters. The inflection point on the polarization curve from steep to flat is defined as the inflection point. Metastable operation refers to the MFC module operating within the power peak range. The power peak range refers to a preset length range smaller than the inflection point.

[0055] In the first embodiment of the adaptively adjustable dual-cooperative wastewater treatment method of the present invention, and in the tenth embodiment of the adaptively adjustable dual-cooperative wastewater treatment method of the present invention, the step of determining the optimal bias range of the MFC module based on the operating parameters of the MFC module includes: Step S31: Monitor the redox potential of the anode chamber of the MFC module in real time; Step S32: Based on the rate of change of redox potential, dynamically set the reference value of the bias voltage applied between the positive and negative electrodes of the MFC module so that the anode potential is always maintained within the potential window of the optimal electron transfer activity of the electrogenic bacteria. Step S33: When the rate of change of redox potential exceeds a preset threshold, the reference value of the bias voltage applied between the positive and negative electrodes of the MFC module is adjusted in reverse to suppress the structural instability of the anode microbial community.

[0056] In this embodiment, a standard reference electrode is installed in the anode chamber. The reference electrode can be an Ag electrode or an AgCl electrode. This electrode is used to measure the potential of the anode relative to the reference electrode in real time. A lower potential indicates more active electrogenic bacteria and a more abundant substrate; a higher potential indicates insufficient substrate, decreased bacterial activity, or inhibition. Measurement data is collected at fixed intervals. If the anode potential is slowly rising, indicating weakened electrogenic bacteria activity or reduced substrate, the bias voltage of the MFC module is increased to accelerate electron extraction. If the anode potential is rapidly decreasing, indicating a sudden increase in substrate or abnormally active bacterial community, the bias voltage of the MFC module is reduced. The bias voltage of the MFC module is reduced to alleviate the electron forcing on microorganisms and prevent them from entering an over-reduced state. If the potential rises or falls sharply in a short period of time, the anode environment has changed drastically, such as a sudden change in the influent load, the introduction of toxic substances, or an imbalance in microbial competition. When the potential drops sharply (risk of over-reduction), the bias voltage of the MFC module is immediately reduced to reduce the electron extraction pressure on the electrogenic bacteria and give the microorganisms room for self-regulation. If the potential rises sharply (risk of activity decline), the bias voltage of the MFC module is immediately increased to force the extraction of more electrons, inhibit the competition from fermenting bacteria and other miscellaneous bacteria, and protect the dominant position of the electrogenic bacteria.

[0057] According to the first embodiment of the adaptive adjustment dual-cooperative wastewater treatment method of the present invention, and the eleventh embodiment of the adaptive adjustment dual-cooperative wastewater treatment method of the present invention, the step of adjusting the circuit load according to the actual bias voltage generated by the solar cell module, adjusting the bias voltage provided by the solar cell module to the MFC module to the optimal bias voltage range through the voltage divider adjustment unit, and storing the electrical energy outside the optimal bias voltage range provided by the solar cell module to the energy storage module includes: Step S44: Detect the instantaneous escape rate of the gas generated in the cathode chamber of the MFC module; Step S45: Establish the mapping relationship between the cathode gas escape rate and the internal resistance of the MFC module; Step S46: Based on the mapping relationship between the gas escape rate and the internal resistance of the MFC module, adjust the voltage divider regulating unit connected in series between the solar cell module and the MFC module to limit the cathode gas escape rate to below the critical value for the occurrence of gas evolution side reaction, thereby reducing the internal resistance of the cell and improving the coulombic efficiency.

[0058] In this embodiment, microbubbles are generated on the cathode surface. As the bubbles grow larger, the charge transfer resistance increases, thus hindering proton transfer and significantly increasing the internal resistance of the MFC module. Gas evolution side reaction refers to the situation where, when the applied bias voltage is too high, the cathode potential exceeds the electrolysis potential of water, resulting in hydrogen or oxygen evolution and the generation of bubbles. The critical value for the occurrence of gas evolution side reaction can be determined by setting a micro gas phase sensor for gas phase detection. In reality, some electrons will enter the fermentation byproducts, be consumed by non-electrogenic bacteria, or have their microbial activity suppressed due to excessively high bias voltage. Coulomb efficiency refers to the proportion of electrons actually generated by the oxidation of organic matter by microorganisms to the total electrons that should have been released by the oxidation of organic matter by microorganisms.

[0059] To achieve the above objectives, this invention also proposes an adaptive dual-cooperative wastewater treatment system. The system employs an adaptive dual-cooperative wastewater treatment method, comprising an MFC module, a solar cell module, a voltage regulator unit, an energy storage module, and a sensing module. The voltage regulator unit regulates the bias voltage provided by the solar cell module to the MFC module. The energy storage module is electrically connected to both the MFC module and the solar cell module. The sensing module monitors the operating parameters during the wastewater treatment process in real time. The MFC module and the solar cell module provide dual-cooperative power for the wastewater treatment process, and the operating parameters include COD, water temperature, pH, light intensity, voltage, and current.

[0060] In this embodiment, the processing system is built on an STM32 (STM32 microcontrollers by STMicroelectronics, 32-bit ARM microcontroller) to construct an intelligent control system. It revolves around the coordinated operation of the MFC module and the solar cell module to achieve energy conservation and emission reduction in the wastewater treatment process. The STM32, as the system core, follows a closed-loop control architecture from perception to decision-making to execution. It collects key parameters such as light intensity, voltage, current, pH, water temperature, COD, and dissolved oxygen in real time through multiple types of sensors, performs intelligent analysis based on preset algorithms, and dynamically generates the optimal control strategy. In the solar cell module, the STM32 implements maximum power point tracking control to improve light energy conversion efficiency and provides dynamically adjustable bias voltage to the MFC module to enhance electron transfer. Power source: In the anode chamber of the MFC module, the optimal activity of electrogenic microorganisms is maintained by regulating pH, water temperature, and substrate concentration; in the cathode chamber, oxidation-reduction conditions are optimized to enhance pollutant removal; the system intelligently switches operating modes according to ambient light: when there is sufficient light, the solar cell module generates electricity at full capacity, and the MFC module is in a highly efficient pressurized state, achieving net energy output and efficient purification; when there is insufficient light, the MFC module maintains operation autonomously, with the lowest system energy consumption, ensuring continuous purification; at the same time, the STM32 has intelligent early warning and predictive maintenance capabilities to ensure long-term stable operation of the system, thereby achieving energy self-sufficiency and emission reduction goals in wastewater treatment.

[0061] The present invention has the following advantages: Energy efficiency has been significantly improved, achieving energy self-sufficiency or even surplus in the wastewater treatment process: Through the synergistic effect of solar cell modules (PSCs) and microbial fuel cells (MFCs), the system can efficiently convert the chemical energy and solar energy in wastewater into electrical energy, reducing dependence on the external power grid. In actual operation, the system can achieve net power output when there is sufficient sunlight, and the overall energy self-sufficiency rate can reach more than 85%, effectively overcoming the problem of high energy consumption in traditional wastewater treatment processes.

[0062] Improved pollutant removal efficiency with no secondary pollution: The MFC module simultaneously degrades organic pollutants while achieving nitrogen removal and carbon resource recovery. Combined with a localized aerobic environment driven by solar cell modules, it significantly improves the removal efficiency of ammonia nitrogen and recalcitrant organic matter (COD removal rate >90%, ammonia nitrogen removal rate >85%). Compared to traditional activated sludge processes, this system produces virtually no residual sludge and generates no secondary pollution.

[0063] Operating costs are significantly reduced, and operation and control are much simpler: The system achieves fully automatic operation through intelligent control, and can adaptively adjust operating parameters according to influent water quality and environmental conditions, reducing manual intervention. Compared with traditional processes, the dosage of chemicals is reduced by more than 70%, maintenance costs are reduced by 50%, and there is no need for complex aeration systems and sludge disposal facilities.

[0064] The system is highly adaptable and can be flexibly deployed in various scenarios: With its modular design, the system can be quickly assembled and deployed, making it suitable for urban wastewater treatment plants, remote areas, and decentralized rural areas.

[0065] High degree of resource utilization, turning waste into treasure: In the cathode chamber, carbon dioxide can be reduced to formic acid, methane and other economically valuable chemicals, realizing the recycling and utilization of carbon resources and promoting the transformation of wastewater treatment from treatment-oriented to resource-oriented.

[0066] It has a high degree of intelligence and is equipped with early warning and maintenance functions. Intelligent control based on STM32 and sensor networks can monitor key parameters in real time and perform predictive maintenance by predicting system anomalies (such as membrane fouling and microbial imbalance), thereby improving system stability and lifespan.

[0067] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a computer-readable storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to enter the methods of the various embodiments of the present invention.

[0068] In the description of this specification, references to terms such as "one embodiment," "another embodiment," "other embodiments," or "first embodiment to Xth embodiment," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is 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, method steps, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0069] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0070] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0071] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. An adaptive and synergistic dual-effect wastewater treatment method, characterized in that, Wastewater treatment employs an adaptive, dual-cooperative wastewater treatment system. The system includes an MFC module, a solar cell module, a voltage regulator unit, an energy storage module, and a sensing module. The voltage regulator unit adjusts the bias voltage provided by the solar cell module to the MFC module. The energy storage module is electrically connected to both the MFC module and the solar cell module. The sensing module monitors operating parameters in real time during the wastewater treatment process. The MFC module and the solar cell module provide dual-cooperative power for the wastewater treatment process. Operating parameters include COD, water temperature, pH, light intensity, voltage, and current. The method includes: Based on meteorological parameters, the solar cell module adjusts the angle of the solar panel to be perpendicular to the angle of solar incidence in order to enable the solar cell module to generate electricity at maximum power. The system monitors the operating parameters of the MFC module in real time, predicts the optimal operating conditions, and automatically adjusts the control parameters of the MFC module based on the predicted optimal operating conditions to ensure that the wastewater treatment system is in an optimized state of production capacity and carbon capture. Determine the optimal bias range for the MFC module based on its operating parameters; Based on the actual bias voltage generated by the solar cell module, the circuit load is adjusted through the voltage divider adjustment unit to adjust the bias voltage provided by the solar cell module to the MFC module to the optimal bias voltage range, and the electrical energy outside the optimal bias voltage range provided by the solar cell module is stored in the energy storage module. When the energy storage module is at or after it is fully charged, the tracking angle of the solar cell module is controlled so that the bias voltage provided by the solar cell module to the MFC module is within the corrected optimal bias voltage range.

2. The adaptive adjustment dual-synergistic wastewater treatment method according to claim 1, characterized in that, The step of adjusting the angle of the solar panel to be perpendicular to the angle of solar incidence based on meteorological parameters, so as to enable the solar panel to generate electricity at maximum power, includes: Preset light intensity threshold; When the actual monitored light intensity is less than the light intensity threshold, the energy storage module or the external power grid is used to provide the MFC module with a bias voltage that meets the optimal bias voltage range. When the actual monitored light intensity reaches the light intensity threshold, based on the current date and the latitude and longitude of the location of the sewage treatment system, the sunrise and sunset times of the solar panel location and the solar incidence angle at each moment are predicted, and the solar cell module is controlled to adjust the angle of the solar panel to be perpendicular to the solar incidence angle at each moment.

3. The adaptive adjustment dual-synergistic wastewater treatment method according to claim 1, characterized in that, The steps of real-time monitoring of the operating parameters of the MFC module, predicting optimal operating conditions, and automatically adjusting the control parameters of the MFC module based on the predicted optimal operating conditions to ensure that the wastewater treatment system is in an optimized state of production capacity and carbon capture include: Obtain the measured running parameters of each MFC module, and obtain the static optimal range corresponding to each running parameter. Based on the static optimal range of each running parameter, determine the optimal running conditions. Determine whether each running parameter is within its corresponding static optimal range; If not, the operating parameters that exceed the static optimal range will be determined as the target operating parameters; According to the preset adjustment strategy, the control parameters of the MFC module are automatically adjusted to bring the target operating parameters into the corresponding static optimal range. When the target operating parameters fail to be adjusted to the static optimal range, the parameter range for dynamic optimization is determined based on the actual values ​​of the target operating parameters in order to adaptively adjust the optimal operating conditions and keep the wastewater treatment system in an optimized capacity and carbon capture state.

4. The adaptive adjustment dual-synergistic wastewater treatment method according to claim 3, characterized in that, The step of automatically adjusting the control parameters of the MFC module according to a preset adjustment strategy to adjust the target operating parameters to the corresponding static optimal range includes: When the water temperature is higher than the optimal water temperature range, the MFC module is controlled to reduce the afternoon sewage flow and increase the proportion of nighttime water intake in order to lower the water temperature through nighttime water intake. When the water temperature is below the optimal range, the MFC module is moved closer to the anaerobic tank and placed in a sunny, south-facing position to increase the water temperature by absorbing heat from the sunlight.

5. The adaptive adjustment dual-synergistic wastewater treatment method according to claim 3, characterized in that, The step of automatically adjusting the control parameters of the MFC module according to a preset adjustment strategy to adjust the target operating parameters to the corresponding static optimal range further includes: When the pH is below the optimal pH range, the alkaline sludge from the aerobic or anaerobic section of the wastewater treatment system is returned to the MFC module. When the pH is greater than the optimal pH range, remove the amount of alkaline sludge from the aerobic or anaerobic section.

6. The adaptive adjustment dual-synergistic wastewater treatment method according to claim 3, characterized in that, The step of automatically adjusting the control parameters of the MFC module according to a preset adjustment strategy to adjust the target operating parameters to the corresponding static optimal range further includes: When the COD is greater than the optimal COD range, use influent water that is lower than the preset COD range to reduce the COD value; When the COD is below the optimal COD range, reduce the influent flow rate of the MFC module and extend the hydraulic retention time.

7. The adaptive adjustment dual-synergistic wastewater treatment method according to claim 1, characterized in that, The steps following the first step of adjusting the bias voltage supplied by the solar cell module to the MFC module to the optimal bias voltage range by adjusting the circuit load through the voltage divider adjustment unit based on the actual bias voltage generated by the solar cell module, and storing the electrical energy outside the optimal bias voltage range supplied by the solar cell module to the energy storage module, include: Determine if the energy storage module is fully charged; When the energy storage module is not fully charged, the solar cell module continues to charge the energy storage module. When the energy storage module is fully charged, the solar cell module disconnects from the energy storage module so that the energy storage module can supply power to the external power grid.

8. The adaptive adjustment dual-synergistic wastewater treatment method according to claim 1, characterized in that, The method further includes: Based on the collected pH and COD, predict whether there is membrane fouling or microbial dysbiosis; If so, trigger a warning signal.

9. A dual-synergistic wastewater treatment method with adaptive adjustment according to any one of claims 1 to 8, characterized in that, The step of controlling the tracking angle of the solar cell module so that the bias voltage provided by the solar cell module to the MFC module is within the corrected optimal bias voltage range when the energy storage module is at a preset critical full state or after it is fully charged includes: The energy storage status of the energy storage module is detected. When the energy storage status of the energy storage module is at a preset critical full state or after it is full, a set of micro-perturbation pulse voltages are periodically applied to the MFC module, and the current polarization curve is reconstructed based on the current response. Identify the inflection point voltage on the reconstructed polarization curve; The optimal bias range is corrected to control the average bias voltage provided to the MFC module to be lower than the inflection point voltage, so that the MFC module operates in metastable state within the power peak range. Thus, based on the corrected optimal bias range, the tracking angle of the solar cell module is controlled to avoid voltage collapse caused by the bias voltage provided to the MFC module entering the polarization region.

10. An adaptively adjustable dual-cooperative wastewater treatment system, characterized in that, Wastewater treatment is performed using an adaptive, dual-coordinated wastewater treatment method as described in any one of claims 1 to 9. The wastewater treatment system includes an MFC module, a solar cell module, a voltage regulator unit, an energy storage module, and a sensing module. The voltage regulator unit is used to regulate the bias voltage provided by the solar cell module to the MFC module. The energy storage module is electrically connected to both the MFC module and the solar cell module. The sensing module is used to monitor the operating parameters during the wastewater treatment process in real time. The MFC module and the solar cell module provide dual-coordinated power supply for the wastewater treatment. The operating parameters include COD, water temperature, pH, light intensity, voltage, and current.

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