Ammonia-containing wastewater electrooxidation flexible regulation and control system and method for novel electric power system

Abstract

The invention discloses an ammonia-containing wastewater electrooxidation flexible regulation and control system and method for a novel electric power system. The system comprises a water inlet parameter monitoring module, an intelligent control module, an electrooxidation treatment module and a system monitoring platform. The water inlet parameter monitoring module collects ammonia nitrogen concentration, flow and liquid level signals of ammonia-containing wastewater in real time and synchronously obtains the load of a unit and the real-time electricity price of a power grid, and the intelligent control module compares the data with a preset threshold value, decides an operation mode, generates a current density set value and a water inlet flow set value, and sends the current density set value and the water inlet flow set value to the control module. The electrooxidation treatment module carries out treatment according to the instruction, the effluent quality is fed back in real time to form closed-loop control, and the system monitoring platform has a self-adaptive learning function and optimizes control parameters regularly. Through intelligent coupling of electricity price-load-water quality, flexible cooperation of the electrooxidation treatment process, the electricity market and power generation operation is achieved, it is guaranteed that effluent stably reaches the standard, and meanwhile the operation economy, the system adaptability and the intelligent level are improved.

Description

Technical Field

[0001] This invention belongs to the field of power environmental protection and industrial water treatment technology, specifically relating to a flexible control system and method for the electro-oxidation of ammonia-containing wastewater for new power systems. Background Technology

[0002] Against the backdrop of the construction of a new power system, high-proportion renewable energy sources, represented by wind power and photovoltaics, are being rapidly connected to the grid. To ensure the safe and stable operation of the power grid and promote the consumption of new energy, the strategic positioning of traditional coal-fired power units has shifted from traditional baseload power sources to core regulating power sources that ensure system balance and mitigate fluctuations in new energy sources. Consequently, frequent participation of coal-fired power units in deep peak shaving, rapid start-up and shutdown, and operation under large load fluctuations has become the new normal.

[0003] Coal-fired power plants generate ammonia-containing wastewater with high ammonia nitrogen concentrations and fluctuating water quality and quantity depending on operating conditions. Traditional biological treatment methods are prone to deactivation under such shock loads, while chemical precipitation methods suffer from problems such as large sludge production and high operating costs. Electrochemical oxidation technology (e-oxidation) shows great promise in the field of advanced ammonia-containing wastewater treatment due to its advantages such as rapid reaction, no need for reagent addition, and no secondary pollution.

[0004] However, under the new power system model, the fundamental shift in the operating mode of coal-fired units poses a severe challenge to their associated ammonia-containing wastewater electro-oxidation treatment systems: Firstly, frequent and deep adjustments to the unit load directly lead to continuous changes in the operating parameters of the SCR system, resulting in an increase in the ammonia nitrogen concentration (C) of the discharged ammonia-containing wastewater. NH3 The water quality and flow rate (Q(t)) exhibit rapid and significant random fluctuations. Traditional electro-oxidation systems, designed for fixed operating conditions, struggle to adapt to these source fluctuations, easily leading to incomplete treatment (excessive ammonia nitrogen) or over-oxidation (energy waste). Secondly, electricity costs dominate the operating costs of electro-oxidation. With the deepening of power market reforms, daily electricity prices show significant peak-valley differences, resulting in periods of low or even negative prices. However, existing electro-oxidation units mostly operate under a continuous constant power mode, lacking the ability to flexibly adjust load based on real-time electricity prices. They cannot enhance operation during low-price periods or reduce load or suspend operations during high-price periods, leading to persistently high costs per ton of water treated. Furthermore, the control of existing electro-oxidation systems is completely independent of the power plant's main generation system and the electricity market. Their operation neither considers the feedforward impact of upstream unit load changes on influent water quality nor responds to real-time changes in grid electricity prices, thus failing to participate in the plant's overall economic optimization scheduling as a "flexible load."

[0005] Therefore, under the background of new power systems, developing a flexible control method and system for the electro-oxidation of ammonia-containing wastewater that can intelligently respond to real-time electricity price signals, dynamically couple unit load changes, and adaptively match fluctuations in influent water quality is of urgent technical demand and significant engineering value for ensuring environmental compliance of coal-fired power plants, tapping into operating cost potential, and improving system regulation flexibility. Summary of the Invention

[0006] Based on the above-mentioned existing technologies, the purpose of this invention is to provide a flexible control system and method for the electro-oxidation of ammonia-containing wastewater in a new type of power system. This method establishes a real-time coupling relationship between "electricity price-load-water quality" and dynamically optimizes the operating power and process parameters of the electro-oxidation unit, achieving a real-time optimal match between treatment effect, operating energy consumption, and electricity market conditions. This solves the problems of poor stability and high operating costs in ammonia-containing wastewater treatment under deep peak shaving.

[0007] The specific technical solution is as follows: A flexible control system for electro-oxidation of ammonia-containing wastewater for new power systems includes an influent parameter monitoring module, an intelligent control module, an electro-oxidation treatment module, and a system monitoring platform. The influent parameter monitoring module includes an ammonia-containing wastewater equalization tank, a booster pump, a filter, an online ammonia nitrogen analyzer, a flow meter, and a buffer tank. The outlet of the ammonia-containing wastewater equalization tank is sequentially connected to the booster pump, the filter, and the buffer tank. The filter removes large particulate impurities from the wastewater. The online ammonia nitrogen analyzer and flow meter are installed at the outlet of the buffer tank to monitor the ammonia nitrogen concentration C in real time. NH3 The module is equipped with a flow rate Q(t); both the regulating tank and the buffer tank are equipped with level sensors; the module is also equipped with a data communication interface for receiving real-time load signals L from the distributed control system (DCS) of a coal-fired power plant. gen (t) and the real-time electricity price signal P from the electricity market information system grid (t); The intelligent control module includes a data acquisition unit, a decision-making unit, and an execution unit. The data acquisition unit's signal input terminal is connected to the signal output terminals of each sensor in the influent parameter monitoring module, for real-time data acquisition of C. NH3 Q(t), liquid level signal, L gen (t) and P grid (t); The decision-making unit, whose input is connected to the output of the acquisition unit, pre-stores core control parameters and a calculation model. The core control parameters include: enhanced processing electricity price threshold P. Boost Threshold P for reduced load operation electricity price Save Low load warning threshold L for generator units low and the shock threshold C of ammonia nitrogen concentration highThe decision-making unit has a built-in operating mode decision-making logic and parameter calculation model; the input end of the execution unit is connected to the output end of the decision-making unit, and its output end is connected to the control end of the controllable power supply and inlet water regulating valve in the electro-oxidation treatment module. This unit receives instructions from the decision-making unit, including the system operating mode M(t) and the current density reference value J. base (t) and the influent flow rate reference value Q base (t), and convert it into a specific equipment control command current density setpoint J. set (t) and influent flow rate setpoint Q set (t); The electrochemical oxidation treatment module includes an inlet regulating valve, a controllable power supply, an electro-oxidation reactor, and an effluent quality monitoring unit. The inlet regulating valve is installed on the inlet pipeline from the buffer tank to the electro-oxidation reactor. The control terminal of the inlet regulating valve is connected to the output terminal of the execution unit in the intelligent control module, used to precisely regulate the wastewater flow rate Q(t) entering the reactor, ensuring it tracks the set value Q. set (t); The control terminal of the controllable power supply is connected to the output terminal of the execution unit, and is used to receive the current density setpoint J. set (t). A controllable power supply powers the electro-oxidation reactor, and the reactor achieves the specified current density during actual operation by adjusting the output current. The electro-oxidation reactor is equipped with an electrode assembly electrically connected to the controllable power supply. An effluent water quality monitoring unit is installed at the outlet of the electro-oxidation reactor to monitor the effluent ammonia nitrogen concentration C in real time. out (t) and feeds back to the intelligent control module; The system monitoring platform communicates with the intelligent control module and includes: a monitoring unit, a historical database, and an adaptive learning unit. The monitoring interface is used to display the system operating mode and key process parameters (C) in real time. NH3 Q(t), L gen (t), P grid (t), J set (t), Q set (t), C out (t) etc.), operating cost statistical curves, and real-time alarm lists. The historical database is used to store all operating data, event logs, and operation records. The adaptive learning unit periodically calls historical data and uses data analysis and machine learning algorithms to evaluate the threshold parameters (such as P) in the intelligent control module decision unit. Boost P Save The system performs offline optimization and calibration of key coefficients in the calculation model and sends out the optimization results for updates, so that the system control strategy can continuously adapt to changes in external conditions.

[0008] Preferably, a reflux bypass with a control valve is provided between the buffer tank and the ammonia-containing wastewater regulating tank, and the control terminal of the control valve is connected to the execution unit of the intelligent control module.

[0009] A flexible control method for treating ammonia-containing wastewater using the above system includes the following steps: S1. Ammonia-containing wastewater from the upstream process flows into the equalization tank for homogenization and temporary storage. Then, it is transported by a booster pump and passes through a filter to remove suspended impurities. The pretreated wastewater enters the buffer tank. The system performs inlet water detection on the wastewater at the outlet of the buffer tank, and all data is transmitted to the intelligent control module. S2. The acquisition unit in the intelligent control module receives real-time data and feeds it back to the decision unit; the decision unit performs operational status assessment and mode decision-making, and generates the current optimal operating mode instruction M(t); the execution unit issues specific control instructions to the electro-oxidation treatment module according to the mode instruction M(t); S3. The ammonia-containing wastewater from the buffer tank enters the electro-oxidation treatment unit, where an electro-oxidation reaction occurs at a set current density, and the ammonia nitrogen is degraded into nitrogen gas. The treated water that meets the standards is then discharged or recycled. S4. The adaptive learning unit of the system monitoring platform periodically performs offline global optimization.

[0010] Furthermore, in step S1, the ammonia nitrogen concentration C of the wastewater at the outlet of the buffer tank is monitored in real time through the influent parameter monitoring module. NH3 The system collects flow rate Q(t), liquid level signals, and simultaneously acquires real-time electricity price signals P from the power grid. grid (t) and the unit's real-time load signal L gen (t), all data is transmitted to the intelligent control module;

[0011] Furthermore, the decision-making unit's operational status assessment and mode decision-making steps in step S2 include: a. The real-time electricity price P grid (t) and the preset enhanced processing electricity price threshold P Boost Threshold P for reduced load operation electricity price Save Compare; b. The real-time load L of the unit gen (t) and the preset low load warning threshold L of the unit low Compare them.

[0012] c. Analyze the influent ammonia nitrogen concentration C NH3 The changing trend is used to determine whether the impact threshold C has been exceeded. high Or there may be violent fluctuations; Based on the above comparison and judgment results, the decision-making unit calls the built-in operation mode decision logic to generate the system's optimal operation mode instruction M(t) at the current moment.

[0013] Further, the operating mode M(t) in step S2 is selected from a preset mode library, which includes at least: a. Enhanced processing mode: When P grid (t) ≤ P Boost Time-triggered, designed to maximize the use of low-cost electricity; b. Steady-state optimization mode: when P Boost < P grid (t)<P Save And L gen (t) ≥ L low Time-triggered, aiming to optimize operational economy while ensuring processing effectiveness; c. Load reduction and efficiency preservation mode: When P grid (t) ≥ P Save or L gen (t)< L low The system is triggered at specific times and is designed to proactively suppress energy consumption during periods of high electricity prices or when generating units are deeply shaving off peak loads, ensuring basic compliance. d. Impact response mode: When C NH3 >C high When its rate of change exceeds the limit, it is triggered immediately, aiming to prioritize and quickly respond to water quality shocks and ensure that the effluent meets the standards.

[0014] Furthermore, in step S2, after determining the operating mode M(t), the decision-making unit dynamically generates control strategy parameters: a. Calculate the current density reference value J base (t): Based on the electrochemical oxidation reaction kinetic model, according to the target removal rate, real-time influent load Q(t), C NH3 And the characteristic parameters of the device are calculated; b. Determine the baseline value Q for the influent flow rate. base (t): Determined by combining system design capabilities, buffer tank level, and optimal hydraulic residence time; c. Application Mode Correction: Based on the control intensity coefficient mapped by M(t), the reference parameters are dynamically corrected to generate the final command current density setpoint J. set (t) and flow setpoint Q set (t).

[0015] Further, the current density reference value J mentioned in step S2 base The formula for calculating (t) is: , Among them, K unit The comprehensive reaction rate coefficient is represented by Q(t), which is the real-time influent flow rate, and C is the total flow rate. NH3 C represents the influent ammonia nitrogen concentration.target The target is the ammonia nitrogen concentration in the effluent.

[0016] Furthermore, applying mode correction in step S2 specifically includes: a Enhanced processing mode: , where α > 1; b. Load Reduction and Efficiency Preservation Mode: , where β < 1; c. Steady-state optimization mode:

[0017] d. Impact response mode: ; Where α is the strengthening coefficient, β is the load reduction coefficient, and J max and J min These are the maximum and minimum current densities allowed by the device, respectively.

[0018] Furthermore, in step S2, the execution unit of the intelligent control module converts the above instructions into equipment control signals: it sends a current density setpoint J to the controllable power supply of the electro-oxidation treatment module. set (t) and the flow rate setting value Q issued by the regulating valve on the inlet pipe. set (t).

[0019] Furthermore, in step S2, if the system is operating in the load reduction and efficiency preservation mode and the level of the buffer tank exceeds the safety limit, the execution unit will control the control valve of the return bypass to open, and guide part of the wastewater back to the ammonia-containing wastewater regulating tank to maintain the system water balance.

[0020] Furthermore, the ammonia nitrogen concentration value C in the effluent after electro-oxidation treatment in step S3 is... out (t) Feedback to the intelligent control module: If C out (t) ≤ C target The system maintains the current policy; if C out (t) > C target The intelligent control module automatically initiates the emergency response procedure. The emergency response procedure controls the electro-oxidation treatment module to operate at a preset emergency current density J. emergency Run, and simultaneously reduce the influent flow rate to the preset emergency flow rate Q. emergency Until C out (t) recovers to below the target value. When C out After the emergency response is restored to the target (t), the intelligent control module automatically exits the emergency handling procedure and resumes the control strategy based on the current operating mode M(t). Wherein, the emergency current density J... emergency and emergency traffic Q emergency J is a constant preset according to the system's processing capacity, and satisfies: min< J emergency < J max .

[0021] Furthermore, the global optimization and self-learning process of the process parameters in step S4 is executed periodically through the system monitoring platform, and the steps are as follows: Specifically, the adaptive learning unit analyzes time-series data in the historical database, including P grid (t), L gen (t), C NH3 J set (t), Q set (t), C out (t) and cumulative power consumption, with the optimization objective of minimizing the total operating power cost within a set period and the constraint of ensuring that the effluent quality meets standards throughout the process, a machine learning algorithm is used to optimize the historical operating strategy. The optimization algorithm outputs an updated set of control parameters, mainly including: dynamic electricity price threshold P Boost_new P Save_new Load warning threshold L for unit operating characteristics low_new The validated set of optimized parameters is updated to the decision unit, thereby enabling continuous iteration of the control strategy and self-evolution of system performance.

[0022] The beneficial effects provided by this invention are: 1) Significantly improved economic efficiency: By actively shifting the operation of high-energy-consuming water treatment units to off-peak electricity periods and actively reducing load during periods of high electricity prices, the cost of electricity per ton of water treated can be significantly reduced.

[0023] 2) Enhanced System Synergy: The operational barriers between the water treatment system and the main power generation system have been broken down, achieving intelligent synergy between electricity price, load, and water quality. As an adjustable flexible load, the water treatment system participates in the overall plant economic optimization, enhancing the power plant's comprehensive regulation capabilities and competitiveness within the new power system.

[0024] 3) Improved operational adaptability and stability: By integrating the feedforward early warning of unit load and the multi-mode decision-making mechanism, the system can adaptively cope with the drastic fluctuations in influent water quality and quantity caused by deep peak shaving, reduce process impact, ensure stable effluent compliance, and extend the life of core equipment.

[0025] 4) High level of intelligence and automation: The system achieves offline optimization and continuous calibration of key control parameters through the adaptive learning unit of the monitoring platform, enabling the system to adapt to changes in power market rules, unit operating characteristics and influent water quality over a long period of time. Attached Figure Description

[0026] Figure 1 This is the system control logic diagram of the present invention. Detailed Implementation

[0027] The present invention will be further described below with reference to the accompanying drawings and embodiments, but the scope of protection of the present invention is not limited thereto.

[0028] A flexible control system for the electro-oxidation of ammonia-containing wastewater for novel power systems includes an influent parameter monitoring module, an intelligent control module, an electro-oxidation treatment module, and a system monitoring platform.

[0029] The influent parameter monitoring module includes an ammonia-containing wastewater equalization tank, a booster pump, a filter, a buffer tank, an online ammonia nitrogen analyzer, and an electromagnetic flow meter. Ammonia-containing wastewater from the upstream process of the power plant first enters the ammonia-containing wastewater equalization tank for homogenization and buffering. It is then pumped to the filter to remove suspended particulate matter, and the filtered wastewater enters the buffer tank. An online ammonia nitrogen analyzer and an electromagnetic flow meter are installed in series on the outlet pipe of the buffer tank to monitor the ammonia nitrogen concentration C of the wastewater in real time. NH3 The instantaneous flow rate Q(t) is measured. Level sensors are installed in both the regulating tank and the buffer tank. This module connects to the power plant's distributed control system (DCS) and the electricity market information platform via a data communication interface, receiving real-time load signals L from the generator units. gen (t) (unit: MW) and real-time electricity price signal P in the grid spot market grid (t) (unit: yuan / kWh).

[0030] The intelligent control module is a control unit built on a high-performance programmable logic controller (PLC), logically comprising a data acquisition unit, a decision-making unit, and an execution unit. The data acquisition unit is connected to all sensors and data interfaces of the influent parameter monitoring module, responsible for synchronous data acquisition and preprocessing. The decision-making unit pre-stores core control parameters: the enhanced processing electricity price threshold P. Boost Threshold P for reduced load operation electricity price Save Low load warning threshold L for generator units low and the ammonia nitrogen concentration shock threshold C high It incorporates built-in operating mode decision logic and parameter calculation models. The output of the execution unit is connected to the actuator of the electro-oxidation treatment module via a control cable. Furthermore, a reflux bypass with an electric valve is installed between the buffer tank and the ammonia-containing wastewater equalization tank, and its control terminal is also connected to the execution unit of the intelligent control module.

[0031] The electro-oxidation treatment module includes an inlet regulating valve, a controllable power supply, an electro-oxidation reactor, and an effluent water quality monitoring unit. The inlet regulating valve is installed on the inlet pipeline from the buffer tank to the electro-oxidation reactor, and its control signal comes from the execution unit of the intelligent control module. The controllable power supply powers the electrode assembly inside the electro-oxidation reactor, and its output current can be quickly and accurately adjusted according to received instructions. The effluent water quality monitoring unit mainly consists of an online ammonia nitrogen analyzer, installed at the reactor outlet, used to monitor the ammonia nitrogen concentration C of the treated effluent in real time. out (t), this signal is fed back to the data acquisition unit of the intelligent control module, forming a closed-loop control.

[0032] The system monitoring platform is a software system deployed on a host computer or plant-level monitoring network and communicates with the intelligent control module. This platform features a human-machine interface, a historical database, and an adaptive learning algorithm module, enabling real-time monitoring of system operation status, historical data querying, alarm management, and offline optimization of control parameters.

[0033] Before the system is put into operation for the first time, initial configuration must be completed. Core control parameters are pre-set in the decision-making unit of the intelligent control module, mainly including: enhanced processing of the electricity price threshold P. Boost Threshold P for reduced load operation electricity price Save Low load warning threshold L for generator units low and the shock threshold C of ammonia nitrogen concentration high Simultaneously, based on the results of small-scale or pilot-scale experiments of the electro-oxidation reactor, key model parameters are calibrated and input, including: the comprehensive reaction coefficient K, current density correction coefficients α and β, and the upper and lower limits of equipment operation J. max and J min and emergency response parameters J emergency and Q emergency Target effluent ammonia nitrogen concentration C target Configured according to environmental protection requirements. The historical database of the system monitoring platform is initialized synchronously with the adaptive learning unit.

[0034] like Figure 1 As shown, a flexible control method for treating ammonia-containing wastewater using the above system is implemented in the following steps: Step S1. After system startup, the influent parameter monitoring module continues to operate. Ammonia-containing wastewater, after homogenization in the equalization tank, is pumped to a filter to remove impurities, and then enters the buffer tank. An online ammonia nitrogen analyzer and electromagnetic flow meter installed at the buffer tank outlet collect the instantaneous ammonia nitrogen concentration signal C of the wastewater in real time and synchronously. NH3 This is related to the flow signal Q(t). Simultaneously, this module acquires the instantaneous load signal L of the generator set in real time from the power plant's distributed control system (DCS) via a data interface. gen(t), and obtain the real-time electricity price signal P from the electricity market information platform. grid (t). After all the raw signals are transmitted to the data acquisition unit of the intelligent control module, they are converted into synchronous data packets that can be used for decision analysis.

[0035] Step S2. The decision-making unit of the intelligent control module receives and parses the fused data packet generated in step S1, and executes the following core logic in sequence: S2.1. The real-time electricity price P grid (t) and the preset threshold P Boost P Save Compare; compare the real-time load L of the unit gen (t) and preset threshold L low Comparison; analysis of influent ammonia nitrogen concentration C NH3 Determine whether it exceeds the impact threshold C. high Whether its rate of change per unit time exceeds the safety limit. Based on pre-set priority rules (usually water quality safety takes priority), and considering the above judgment results, a unique current optimal operating mode M(t) is determined from the mode library; the mode library includes: enhanced treatment mode (when P grid (t) ≤ P Boost At that time, the aim is to maximize the use of the low-cost electricity window), and the steady-state optimization mode (when P Boost <P grid (t)<P Save And L gen (t) ≥ L low At that time, the aim is to balance economy and effectiveness under normal conditions), and the load reduction and efficiency preservation mode (when P grid (t) ≥ P Save or L gen (t)< L low At the same time, it aims to actively suppress energy consumption during periods of high electricity prices or deep peak shaving of generating units) and shock response mode (when C NH3 >C high (At the time, the aim was to prioritize and quickly address water quality impacts). S2.2. After determining the mode M(t), the decision-making unit calls the built-in process model to calculate parameters. Based on the electrochemical oxidation reaction kinetics, according to the target removal rate (C... NH3 -C target Based on the real-time influent load Q(t) and the device characteristic coefficient K, the theoretically required current density reference value J is calculated. base (t). Simultaneously, considering the optimal hydraulic retention time of the electro-oxidation reactor, the designed treatment capacity, and the real-time liquid level in the buffer tank, the baseline value of the influent flow rate Q was calculated. base(t) is used to ensure system water balance and treatment effect; the baseline parameters are dynamically corrected according to the control strategy mapped by the selected mode M(t). In the enhanced treatment mode, J base (t) multiplied by a strengthening factor α greater than 1, but not exceeding the equipment limit J. max In steady-state optimization mode, J is adopted. base (t), in the load reduction and efficiency preservation mode, J will be base (t) multiplied by a load reduction factor β less than 1, but not lower than the lower limit of maintaining operation J. min In the impact response mode, the maximum capability parameter J is directly used. max After correction, the final current density setpoint J, which will be issued to the execution equipment, is obtained. set (t) and influent flow rate setpoint Q set (t). The decision-making unit sends this instruction set along with the operating mode information to the execution unit; S2.3. The execution unit sends J to the controllable power supply of the electro-oxidation treatment module. set (t), sends Q to the inlet regulating valve set (t); The electro-oxidation reactor operates under set parameters.

[0036] Step S3. The controllable power supply is based on J set (t) Adjust the output current to make the electro-oxidation reactor operate at the set current density; the inlet water regulating valve adjusts according to Q. set (t) Adjust the opening degree to ensure the wastewater flow rate entering the reactor tracks the set value; if the system is operating in the load reduction and efficiency maintenance mode, and the buffer tank level is detected to be rising continuously and approaching the high limit due to the reduced treatment flow rate, the execution unit will automatically coordinate to control the opening of the reflux bypass valve to guide part of the wastewater back to the front-end equalization tank, thereby maintaining the material balance of the entire water system while meeting the load reduction requirements; the online monitoring instrument at the outlet of the electro-oxidation treatment module measures the effluent ammonia nitrogen concentration C in real time. out (t), and feeds back to the intelligent control module to continuously compare C. out (t) and the target value. Once C out If (t) exceeds the limit, the built-in safety interlock logic will be immediately triggered: the current operating mode will be suspended, and a forced switch to the preset emergency handling procedure will be initiated, i.e., using a fixed, optimized emergency current density J. emergency and emergency traffic Q emergency Run, waiting for C out (t) Once the system recovers and stabilizes within the target value limit, it will automatically exit the emergency procedure and revert to the operating mode determined by the current external conditions (electricity price, load).

[0037] Step S4. The adaptive learning unit of the system monitoring platform runs independently in the background, starting optimization tasks according to a preset cycle: This unit retrieves massive amounts of runtime data from the historical database for a complete cycle, including time-series P... grid (t), L gen (t), C NH3 J set (t), Q set (t), C out (t) and the energy consumption of each unit, with the core optimization objective of minimizing the total electricity consumption and operating cost within the cycle, and with the requirement that the effluent quality meets the standards throughout the entire process as a hard constraint, machine learning algorithms are used to evaluate and extrapolate historical operating strategies, and optimize and output a set of recommended updated parameters, including: dynamic electricity price threshold P. Boost_new P Save_new Load warning threshold L for unit operating characteristics low_new After the new parameters are verified and confirmed manually or automatically on the monitoring platform, they are updated to replace the old parameters in the decision-making unit of the intelligent control module.

[0038] Example

[0039] A 660 MW coal-fired power plant uses the system of this invention to treat its ammonia-containing wastewater (ammonia nitrogen concentration typically fluctuates between 50-300 mg / L). Before system commissioning, initial configuration was completed, and the core control parameters were set as follows: Enhanced treatment electricity price threshold P. Boost = 0.24 yuan / kWh, threshold P for derating operation Save = 0.42 yuan / kWh, low load warning threshold L for the unit low = 300 MW, ammonia nitrogen concentration shock threshold C high = 280 mg / L, target effluent ammonia nitrogen concentration C target = 8 mg / L, maximum / minimum current density J of electro-oxidation reactor max = 50 A / m 2 J min = 2 A / m 2 The overall reaction rate coefficient K unit = 0.015 A·h / (m 2 ·L·mg), reinforcement coefficient α = 1.2, load reduction coefficient β = 0.7, emergency current density J emergency = 40 A / m 2 Emergency flow Q emergency = 5 t / h.

[0040] Scenario 1: At time t1 (nighttime off-peak period), the influent parameter monitoring module synchronously collects and uploads the following real-time signals to the intelligent control module: C NH3(t1) = 120 mg / L, Q(t1) = 12 m 3 / h, buffer tank level = 65%, L gen (t1) = 380 MW, P grid (t1) = 0.20 yuan / kWh, electricity price P grid (t) When the price remains below 0.24 yuan / kWh and the load exceeds 300MW, the system operates stably in enhanced processing mode; at this time, J base (t1) = 20.16 A / m 2 Because it is in enhanced processing mode, it needs to be corrected using an enhancement coefficient α=1.2, and is subject to the equipment's upper limit J. max = 50 A / m 2 Constraints, therefore J set (t1) = min(50,1.2×20.16) = 24.19 A / m 2 Traffic setting Q set (t1) = Q(t1) = 12 m 3 / h; The execution unit will issue the setting command: control the controllable power supply to make the reactor current density 24.19 A / m 2 Control the inlet water regulating valve to make the inlet water flow rate 12 m³ / h 3 / h.

[0041] Scenario 2: At time t2 (morning flat period), the influent parameter monitoring module synchronously collects and uploads the following real-time signals to the intelligent control module: C NH3 (t2) = 180 mg / L, Q(t2) = 16 m 3 / h, buffer tank level = 60%, P grid (t2) = 0.35 yuan / kWh, L gen (t2) = 580 MW; at this time P Boost (0.24) < P grid (t2) (0.35) < P Save (0.42) and L gen (t2) (580) > L low (300), the decision-making process is a steady-state optimization mode; J set (t2)=J base (t2) = 41.28 A / m 2 The system automatically adjusted the current density to 41.28 A / m. 2 Run, flow rate setting Q set (t2) = Q(t2) = 16 m 3 / h; The execution unit will issue the setting command: control the controllable power supply to make the reactor current density 41.28 A / m 2 Control the inlet water regulating valve to make the inlet water flow rate 16 m³ / h 3 / h.

[0042] Scenario 3: At time t3 (deep peak shaving), the influent parameter monitoring module synchronously collects and uploads the following real-time signals to the intelligent control module: C NH3 (t3) = 100 mg / L, Q(t3) = 8 m 3 / h,P grid (t3) = 0.50 yuan / kWh, L gen (t3) = 280 MW; at this time P grid (t3) (0.50) > P Save (0.42) and L gen (t3) (280) < L low (300), the decision is to adopt a load reduction and efficiency preservation mode; J set (t3) = 11.04 A / m 2 Because it is in a load reduction and efficiency preservation mode, it needs to be corrected using an enhancement coefficient β=0.7, and is subject to the equipment's lower limit J. min = 2 A / m 2 Constraint, J set (t3) = max(2,0.7×11.04) = 7.73 A / m 2 Traffic setting Q set (t1) = Q(t1) = 8 m 3 / h; The execution unit will issue the setting command: control the controllable power supply to make the reactor current density 7.73 A / m 2 Control the inlet water regulating valve to make the inlet water flow rate 8 m³ / h. 3 / h; maintains basic operation with minimal power consumption, greatly avoiding high electricity prices.

[0043] Scenario 4: At time t4, a sudden change in water quality occurs due to rapid load changes in the generating unit: C NH3 (t4) increases rapidly from 150 mg / L to 310 mg / L within 30 minutes, Q(t4) = 18 m 3 / h,P grid (t4) = 0.43 yuan / kWh, L gen (t4) = 300 MW; at this time, C NH3 (t4) (310) > C high (280), immediately trigger the highest priority shock response mode. Execute: J set (t4) = J max =50 A / m2 Q set (t4)=18 m 3 / h, the system switches to maximum processing capacity.

[0044] Scenario 5: During the impact response process in Scenario 4, the impact intensity exceeded the instantaneous processing capacity, and the effluent C was detected. out The concentration rose to 10 mg / L (exceeding Ctarget = 8 mg / L); the intelligent control module immediately activated the emergency response procedure: controlling the reactor to J emergency = 40 A / m 2 Run, while forcibly reducing the influent flow rate to Q. emergency = 5 t / h. Waiting for C out After recovering and stabilizing to the target value, the system automatically exits the emergency procedure. Because at this time C NH3 The current density remains high (290 mg / L). After reassessment, the system remains in impact response mode and reduces the current density from the emergency value of 40 A / m. 2 Restore to J max =50 A / m 2 Inlet flow rate setpoint Q set Restored to 18 m 3 / h.

[0045] Since the system was put into operation a year ago, the adaptive learning unit of the system monitoring platform analyzed historical data and found that in spring and autumn, the large-scale generation of new energy sources led to longer periods of low-priced electricity during the day, and the original P Boost The threshold of 0.25 yuan / kWh is too conservative; with the core optimization objective of minimizing the total operating cost within the cycle, the optimization algorithm suggests adjusting P... Boost The price will be dynamically adjusted from 0.25 yuan / kWh to 0.22 yuan / kWh. This suggestion, once confirmed, will be applied to the new parameter P. Boost new The price of 0.22 yuan / kWh was sent to the decision-making unit of the intelligent control module. Subsequently, the system would initiate enhanced processing when the electricity price fell below 0.22 yuan / kWh, further reducing the average electricity cost.

[0046] One year after the system was put into operation, statistical analysis showed that the constant current before the upgrade (J=35 A / m) was... 2 By comparing the operating modes, the system of the present invention exhibits the following significant beneficial effects:

[0047] 1) Significantly improved operational economy

[0048] Through intelligent coupling and flexible regulation of "electricity price-load-water quality," the system's operating strategy has undergone a fundamental transformation. During off-peak electricity price windows (P... gridWithin the range of ≤ 0.24 yuan / kWh, the system automatically enhances processing, shifting approximately 60% of the daily processing volume to this low-cost period, significantly reducing the unit electricity cost; during peak electricity price periods (P... grid ≥ 0.42 yuan / kWh) or deep peak shaving of the unit (L gen During periods of < 300 MW, the system rapidly reduces load to a low-power state (current density maintained at 7-8 A / m). 2 This strategy effectively avoids high electricity costs. Under this strategy, the average electricity cost per ton of water treated is reduced by about 40% compared to the traditional constant current operation mode, resulting in a significant improvement in economic efficiency.

[0049] 2) Enhanced system synergy

[0050] The system breaks down information barriers between water treatment and the main power generation system, achieving intelligent coordination of "electricity price-load-water quality". By receiving real-time unit load and grid price signals, the water treatment system, as an adjustable and flexible load within the plant, actively participates in the plant's overall economic optimization scheduling. This not only optimizes water treatment costs but also enhances the power plant's comprehensive ability and competitiveness in responding to new energy fluctuations and participating in market regulation within the new power system.

[0051] 3) Enhanced stability and adaptability

[0052] Faced with drastic fluctuations in influent ammonia nitrogen concentration and flow rate due to deep peak shaving, the system successfully handled three shock events with influent ammonia nitrogen concentrations exceeding 280 mg / L by integrating feedforward early warning of unit load and multi-mode decision-making mechanisms. The effluent water quality compliance rate remained 100%, and the overall response and adjustment time was less than 5 minutes. The system's adaptive capability effectively ensured stable water quality compliance and extended the service life of core equipment such as the electro-oxidation reactor.

[0053] 4) The system's intelligence and self-evolution capabilities are evident.

[0054] The adaptive learning unit built into the monitoring platform analyzes historical operating data and periodically adjusts key control parameters (such as P). Boos t, P Save Offline global optimization and calibration are performed. Over the course of a year, this unit has completed six parameter iterations, ensuring that the system's decision-making logic continuously aligns with actual power market patterns and unit operating characteristics. This effectively avoids unnecessary frequent switching of operating modes, reduces operational volatility, and drives the system to maintain its economically optimal operating state in the long term.

[0055] By flexibly controlling the electro-oxidation treatment of ammonia-containing wastewater, the power plant has not only achieved a significant reduction in treatment costs and multiple guarantees for stable compliance, but also transformed the wastewater treatment unit from a rigid load into a flexible resource that can respond to the needs of the power grid and generating units. This provides an effective solution for energy conservation, consumption reduction, and flexible operation of the power plant under the new power system.

Claims

1. A flexible control system for electro-oxidation of ammonia-containing wastewater for a new power system, characterized in that, The system comprises a water inlet parameter monitoring module, an intelligent control module, an electro-oxidation treatment module and a system monitoring platform. The water inlet parameter monitoring module is configured to collect the ammonia nitrogen concentration C of the ammonia-containing wastewater in real time NH3 , flow rate Q(t) and liquid level, and synchronously acquire a real-time load signal L of the coal-fired unit gen (t) and a real-time power grid price signal P grid (t); The intelligent control module is in communication connection with the water inlet parameter monitoring module and is configured to determine the operation mode M(t) and dynamically generate the current density setting value J NH3 (t) and the water inlet flow setting value Q gen (t) based on the C grid (t), the liquid level L set (t) and the P set (t) signal, wherein the operation mode M(t) comprises a reinforced treatment mode, a steady-state optimization mode, a load reduction and efficiency preservation mode and a shock response mode. The electric oxidation treatment module is connected with the intelligent control module, and is configured to perform electric oxidation treatment according to J set (t) and Q set (t) and Q out (t) and feedback to the intelligent control module. The system monitoring platform is in communication connection with the intelligent control module and is configured to monitor the system running state and to adaptively optimize the control parameters based on historical data.

2. The ammonia-containing wastewater electro-oxidation flexible regulation system for new power systems according to claim 1, characterized in that, The influent parameter monitoring module comprises an ammonia-containing wastewater adjusting tank, a lifting pump, a filter, a buffer water tank, an ammonia nitrogen online analyzer and a flow meter; the effluent outlet of the ammonia-containing wastewater adjusting tank is connected with the lifting pump, the filter and the buffer water tank in sequence; the filter is used for removing suspended impurities in the wastewater; the outlet of the buffer water tank is installed with the ammonia nitrogen online analyzer and the flow meter, which are respectively used for monitoring the ammonia nitrogen concentration C NH3 and the flow Q(t) of the wastewater; the ammonia-containing wastewater adjusting tank and the buffer water tank are both provided with liquid level sensors.

3. The ammonia-containing wastewater electro-oxidation flexible regulation system for new power systems according to claim 2, characterized in that, A reflux bypass with a control valve is arranged between the buffer water tank and the ammonia-containing wastewater adjusting tank, and a control end of the control valve is connected with the intelligent control module.

4. The ammonia-containing wastewater electro-oxidation flexible regulation system for new power systems according to claim 3, characterized in that, The intelligent control module comprises a data acquisition unit, a decision unit and an execution unit. The data acquisition unit is connected with the water inlet parameter monitoring module and is used for collecting signals in real time; the decision unit is connected with the data acquisition unit, the decision unit pre-stores the enhanced treatment electricity price threshold P Boost , the load reduction operation electricity price threshold P Save , the unit low load early warning threshold L low , and the ammonia nitrogen concentration impact threshold C high , and is built-in with operation mode decision logic and parameter calculation model; the execution unit is connected with the decision unit and is used for issuing J set (t) and Q set (t) to the electro-oxidation treatment module.

5. The ammonia-containing wastewater electro-oxidation flexible regulation system for new power systems according to claim 4, characterized in that, The electro-oxidation treatment module comprises a water inlet adjusting valve, a controllable power supply, an electro-oxidation reactor and a water outlet quality monitoring unit; the outlet of the buffer water tank is connected with the water inlet adjusting valve and the electro-oxidation reactor in sequence, and the control end of the water inlet adjusting valve is connected with the intelligent control module execution unit; the controllable power supply is connected with the electro-oxidation reactor to supply power for the electro-oxidation reactor, and the control end of the controllable power supply is connected with the intelligent control module execution unit; the water outlet quality monitoring unit is used for monitoring the ammonia nitrogen concentration C out (t) and feeding back to the intelligent control module.

6. A flexible regulation method for treating ammonia-containing wastewater by using the ammonia-containing wastewater electro-oxidation flexible regulation system for new power systems in claim 5, characterized in that, The method comprises the following steps: S1. Real-time collection of ammonia-nitrogen concentration C of influent ammonia-containing wastewater by influent parameter monitoring module NH3 , flow rate Q(t) and liquid level of buffer tank, and simultaneously receiving real-time load signal L of the unit gen (t) and real-time electricity price signal P of the power grid grid (t); S2. The intelligent control module determines the operation mode M(t) based on C NH3 , Q(t), liquid level L gen (t) and P grid (t) signals, and generates the current density set value J set (t) and the water inflow set value Q set (t); S3. Electro-oxidation treatment module according to J set (t) and Q set (t) Electro-oxidation treatment is performed, and the ammonia nitrogen concentration C in the effluent is monitored in real time. out (t); S4. The system monitoring platform adaptively optimizes and updates the control parameters in the intelligent control module based on historical running data.

7. The flexible regulation method of claim 6, wherein, In step S2, the decision logic of the running mode M(t) is as follows: If P grid (t) ≤ P Boost , the decision is the reinforcement processing mode; If P Boost < P grid (t) < P Save and L gen (t) ≥ L low , the decision is steady state optimization mode; If P grid (t) ≥ P Save or L gen (t) < L low , the decision is to reduce the load to maintain the mode; If C NH3 ≥ C high or its rate of change is out of limits, immediately decide to impact response mode.

8. The flexible regulation method of claim 6, wherein, In step S2, the current density reference value J base (t) is calculated according to the formula J base (t) = K unit × Q(t) × (C NH3 - C target ), where K unit is a reaction rate coefficient, C target is the target effluent ammonia nitrogen concentration; and J base (t) is corrected according to the operation mode M(t) to generate J set (t).

9. The flexible regulation method of claim 8, wherein, In step S2, the correction comprises: In the reinforcement processing mode, J set (t) = min(J max , α·J base (t)), where a > 1. In the load shedding maintenance mode, J set (t) = max(J min , β·J base (t)), where β < 1. In the steady-state optimization mode, J set (t) = J base (t) = J In the impact response mode, J set (t) = J max ; where a is a strengthening coefficient, β is a load reduction coefficient, J max and J min are the maximum and minimum current densities allowed by the device, respectively.

10. The flexible regulation method of claim 6, wherein, In step S3, when the effluent ammonia nitrogen concentration C out (t) is monitored to exceed the target value C target , the safety interlock control is triggered, and the electro-oxidation treatment module can be controlled to operate at an emergency current density J emergency and an emergency flow rate Q emergency until C out (t) returns to the standard; in step S4, the adaptive optimization takes the minimum total power consumption as the optimization objective, and the threshold parameters P Boost , P Save , L low and C high are calibrated and updated through a machine learning algorithm.

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