Hydroenergy coupling scheduling method and system

Abstract

The invention belongs to the technical field of comprehensive utilization of energy, and particularly relates to a hydraulic energy coupling scheduling method and system. The invention discloses a water power coupling intelligent control system, and aims to establish a water power coupling intelligent control platform oriented to an urban water affair system, realize linkage control of a sewage treatment plant, a water quantity adjusting facility and an energy facility, and solve the technical problem that a water and electricity collaborative optimization mechanism is not formed in the prior art. The acquisition module is used for acquiring running state information of each equipment unit in the hydraulic energy coupling dispatching system in real time; the prediction modeling module is used for predicting the hydroenergy coupling parameters in the future time period through the collected operation state information to obtain a prediction result; the strategy generation module is used for generating an operation strategy based on the prediction result and in combination with the current electricity price peak and valley time period; and the instruction control module is used for sending a scheduling instruction to each equipment unit according to the operation strategy and controlling each equipment unit to operate according to the scheduling instruction.

Description

Technical Field

[0001] This invention belongs to the field of comprehensive energy utilization technology, and in particular relates to a hydropower coupling scheduling method and system. Background Technology

[0002] As an important municipal infrastructure, urban wastewater treatment systems are increasingly attracting attention due to their energy consumption and carbon emissions. Currently, the wastewater treatment industry mainly focuses on biological treatment, oxygen supply and aeration, and wastewater transportation, which are characterized by high energy consumption and high carbon emissions.

[0003] In existing technologies, wastewater treatment plants generally operate under design conditions of "full load and all-weather," with wastewater treatment processes carried out through key equipment such as pumping stations, blowers, and sludge return pumps. In recent years, many wastewater treatment plants have deployed SCAD water-energy coupling scheduling systems, energy consumption monitoring platforms, and distributed photovoltaic facilities, achieving "visualization" of operational data.

[0004] The existing technology has the following technical problems: 1. Operating in a "full load, all-weather" mode, it lacks the ability to proactively respond to external conditions such as electricity prices and system load.

[0005] 2. Core equipment in water plants, such as influent pumps and blowers, consume a large proportion of energy and are significantly affected by fluctuations in influent water levels. Conventional adjustment methods are inefficient.

[0006] 3. Although the water system has certain capacity for regulation and load transfer, it has not effectively utilized energy storage, photovoltaics, electricity price information, etc. for dynamic scheduling, thus missing out on peak shaving and energy-saving potential.

[0007] 4. Although some power plants have deployed photovoltaic and energy consumption monitoring systems, they are still in the "visible but uncontrollable" stage and have not yet formed a "power plant-station integration" and "source-load-storage coordination" control system. Summary of the Invention

[0008] This invention provides a water-energy coupled scheduling method and system, aiming to solve the technical problems existing in the prior art, such as large rigidity of operating load, weak regulation capability, strong fluctuation of power consumption and high energy consumption level, lack of a coordinated optimization mechanism between water and electricity, and lack of control means and response mechanism.

[0009] The technical solution of the present invention to solve the above-mentioned technical problems is as follows: A hydropower coupled dispatching system, comprising: The information acquisition module is used to collect real-time operating status information of each equipment unit in the hydropower coupling scheduling system; The predictive modeling module is used to predict hydropower coupling parameters for future periods based on collected operational status information, and obtain prediction results; wherein, the hydropower coupling parameters include: load changes, electricity price trends and water demand trends; The strategy generation module is used to generate an operation strategy based on the prediction results and in combination with the current peak and off-peak electricity price periods; The instruction control module is used to send scheduling instructions to each device unit according to the operation strategy, and control each device unit to operate according to the scheduling instructions.

[0010] Furthermore, the aforementioned device unit includes: The water treatment unit, including an inlet pump, a blower, and a dosing system, is used to purify wastewater. The water flow control unit, including pumping stations and storage tanks, is used to buffer and regulate the flow of sewage. The energy facility unit, including photovoltaic power generation devices, energy storage devices and microgrid controllers, is used to provide local energy to the water treatment unit and to autonomously manage the local energy. The power grid interaction unit is used to establish two-way communication and interaction with the external power system, obtain electricity price signals, and respond to dispatch instructions.

[0011] Furthermore, the above also includes: The strategy optimization module is used to acquire monitoring information collected by the information acquisition module and optimize and adjust the operation strategy based on the monitoring information; wherein, the monitoring information includes the energy storage SOC curve, the liquid level of the storage tank, the processing load, and the unit power consumption.

[0012] Furthermore, the energy storage device described above includes an energy storage battery pack and an energy storage converter. The energy storage converter is electrically connected to the microgrid controller and the energy storage battery pack, respectively, and is used to realize the charging and discharging control of the energy storage battery pack.

[0013] Furthermore, the aforementioned microgrid controller is electrically connected to the water inlet pump, blower, and dosing system in the water treatment unit via low-voltage power distribution lines, and is used to allocate the power supply to the water inlet pump, blower, and dosing system in different time periods.

[0014] Furthermore, the aforementioned power grid interaction unit includes: A communication terminal used to receive load dispatch signals from the power grid side.

[0015] Furthermore, the aforementioned operating strategies include off-peak period strategies and peak period strategies; wherein, the off-peak period strategy specifically involves: during off-peak periods, controlling the water volume regulation unit to increase the operating frequency of the pumping station and inject water into the storage tank, while simultaneously controlling the energy facility unit to generate photovoltaic power and charge energy storage; the peak period strategy specifically involves: during peak periods, controlling the water treatment unit to reduce the influent load, and controlling the energy facility unit to release stored electrical energy to supply the operation of the load equipment.

[0016] Furthermore, the aforementioned buffering and regulation of sewage flow specifically involves: adjusting the liquid level in the storage tank and controlling the start-up and shutdown sequence of the pump station to achieve flexible transfer of sewage treatment load over time.

[0017] Furthermore, when the aforementioned equipment unit receives the scheduling instruction, it prioritizes responding to the photovoltaic power generation device and energy storage device of the energy facility unit, as well as the pump station of the water volume control unit or the inlet pump of the water treatment unit.

[0018] Secondly, to solve the above-mentioned technical problems, the present invention also provides a hydropower coupling scheduling method, applied to the above-described hydropower coupling scheduling system, the method comprising: Real-time acquisition of operational status information of each equipment unit in the hydropower coupling scheduling system; By collecting operational status information, the hydropower coupling parameters for future periods are predicted, and the prediction results are obtained; wherein, the hydropower coupling parameters include: load changes, electricity price trends and water demand trends; Based on the prediction results and combined with the current peak and off-peak electricity price periods, an operation strategy is generated; According to the operating strategy, scheduling instructions are sent to each device unit to control each device unit to operate according to the scheduling instructions.

[0019] Compared with the prior art, the present invention has the following advantages: 1. At the system operation level: Significantly reduce energy consumption during peak hours, reduce electricity costs, enhance the stability of the sewage treatment system, and reduce daily fluctuations; optimize operating load and reduce equipment losses from frequent start-ups and shutdowns.

[0020] 2. At the energy management level: realize local consumption of green energy (such as photovoltaic); build an energy storage charging and discharging model based on electricity price response to achieve economic operation; water plants have the basis to participate in virtual power plants to realize market response value realization.

[0021] 3. At the system construction level: Existing storage tanks, pumping stations, photovoltaic and other resources can be coordinated and dispatched to improve the comprehensive utilization rate of resources; and a flexible load regulation platform for future power systems can be created.

[0022] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 A schematic diagram of a hydropower coupling dispatching system according to an embodiment of the present invention is shown; Figure 2 A logic block diagram of a hydropower coupling scheduling system according to an embodiment of the present invention is shown; Figure 3 A flowchart illustrating a hydropower coupling scheduling method according to an embodiment of the present invention is shown. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] Figure 1 A schematic diagram of a hydropower coupling dispatching system according to an embodiment of the present invention is shown, as follows: Figure 1 As shown, an embodiment of the present invention provides a hydropower coupling scheduling system, comprising: A hydropower coupled dispatch system, comprising: The information acquisition module is used to collect real-time operating status information of each equipment unit in the hydropower coupling scheduling system; The predictive modeling module is used to predict hydropower coupling parameters for future periods based on collected operational status information, and obtain prediction results; wherein, the hydropower coupling parameters include: load changes, electricity price trends and water demand trends; The strategy generation module is used to generate an operation strategy based on the prediction results and in combination with the current peak and off-peak electricity price periods; The instruction control module is used to send scheduling instructions to each device unit according to the operation strategy, and control each device unit to operate according to the scheduling instructions.

[0027] In this embodiment, the information acquisition module, predictive modeling module, strategy generation module, and command control module are integrated to obtain an integrated data acquisition and AI regulation module, which is used to realize full data acquisition, real-time data interaction, model analysis, and generation of intelligent regulation commands. Specifically, a hybrid graph neural network is used to construct a "load-electricity price-water consumption" response model to achieve strategy generation and dynamic optimization.

[0028] Optionally, the device unit includes: The water treatment unit, including an inlet pump, a blower, and a dosing system, is used to purify wastewater. The water flow control unit, including pumping stations and storage tanks, is used to buffer and regulate the flow of sewage. In this embodiment, the pumping station and the regulating reservoir are connected through a pipeline network, and the regulating reservoir and the inlet pump are connected through a pipeline network; thus realizing the functions of time-sharing water storage and peak shaving and valley filling. The energy facility unit, including photovoltaic power generation devices, energy storage devices and microgrid controllers, is used to provide local energy to the water treatment unit and to autonomously manage the local energy. In this embodiment, the microgrid controller is electrically connected to the photovoltaic power generation device and the energy storage device, and the microgrid controller is electrically connected to the water inlet pump, blower and dosing system in the water treatment unit.

[0029] In this embodiment, the energy storage device is connected to the water plant's power distribution system through a microgrid controller to achieve photovoltaic absorption and strategic discharge control.

[0030] The power grid interaction unit is used to establish two-way communication and interaction with the external power system, obtain electricity price signals, and respond to dispatch instructions.

[0031] In this embodiment, an energy management unit is also included, which is equipped with a control system for load forecasting, dispatch optimization, and operation strategy formulation, and is communicatively connected to the aforementioned equipment unit; the energy management unit supports virtual power plant functions and performs response capability assessment and resource aggregation with the power grid dispatch center; Optional, also includes: The strategy optimization module is used to acquire monitoring information collected by the information acquisition module and optimize and adjust the operation strategy based on the monitoring information; wherein, the monitoring information includes the energy storage SOC curve, the liquid level of the storage tank, the processing load, and the unit power consumption.

[0032] Optionally, the energy storage device includes an energy storage battery pack and an energy storage converter. The energy storage converter is electrically connected to the microgrid controller and the energy storage battery pack, respectively, and is used to realize the charging and discharging control of the energy storage battery pack.

[0033] Optionally, the microgrid controller is electrically connected to the water inlet pump, blower, and dosing system in the water treatment unit via low-voltage power distribution lines, and is used to allocate the power supply of the water inlet pump, blower, and dosing system in different time periods.

[0034] Optionally, the power grid interaction unit includes: A communication terminal used to receive load dispatch signals from the power grid side.

[0035] Optionally, the operation strategy includes an off-peak period strategy and a peak period strategy; wherein, the off-peak period strategy specifically involves: during off-peak periods, controlling the water volume regulation unit to increase the operating frequency of the pumping station and inject water into the storage tank, while simultaneously controlling the energy facility unit to generate photovoltaic power and charge energy storage; the peak period strategy specifically involves: during peak periods, controlling the water treatment unit to reduce the influent load, and controlling the energy facility unit to release stored electrical energy to supply the operation of the load equipment.

[0036] Optionally, the buffering and regulation of sewage flow can be achieved by adjusting the liquid level in the storage tank and controlling the start-up and shutdown sequence of the pump station to realize the flexible transfer of sewage treatment load in the time dimension.

[0037] In this embodiment, the water level in the regulating tank is controlled within a set boundary to support peak-shaving and discharge regulation. By precisely controlling the liquid level change path and the start-up and shutdown sequence of the pump station, the power load of sewage treatment is shifted over time, realizing the proactive response of the "water system" to the "energy system".

[0038] Optionally, when the equipment unit receives the scheduling instruction, it shall give priority to responding to the photovoltaic power generation device and energy storage device of the energy facility unit, as well as the pumping station of the water volume control unit or the water inlet pump of the water treatment unit.

[0039] In this embodiment, a hierarchical, orderly, and intelligent scheduling and execution mechanism is constructed by establishing a priority response sequence of "photovoltaic-energy storage-water inflow load".

[0040] In one embodiment of the present invention, such as Figure 2 As shown, the system consists of the following units and modules: (a) Water treatment unit The water treatment unit is the load core of water-energy coupled control, containing the main energy-consuming equipment in the wastewater treatment plant, including: 1. Inlet pump station subunit: Used to lift sewage from the pipe network or storage tank to the main sewage treatment process, and has variable frequency control capability; 2. Aeration subunit (blower): Used to supply oxygen to the biological treatment tank, it is the most powerful load source in the system; 3. Dosing subunit: This includes dosing pumps, mixing devices, etc. Although the power is relatively small, it must be matched with the biochemical load during system operation; 4. Effluent Lifting Subunit: This unit delivers the treated wastewater to the tailwater outlet or the greywater reuse system, and its operation sequence is controllable. 5. Auxiliary equipment sub-units: including sludge dewatering units, online monitoring instruments, plant lighting and air conditioning, etc., which can be included in the dispatching scope.

[0041] This unit adjusts the operating time, frequency, and power of each water treatment device through control strategies to achieve coordinated control of treatment load and energy consumption.

[0042] (ii) Water Quantity Control Unit This unit includes hydraulic structures connected to the water treatment system, forming the liquid flow path at the front end of wastewater treatment and serving as a buffer zone for regulating the water treatment load. It mainly consists of the following components: 1. Pump station subunit: Located at the end of the pipeline network or at the junction, used to control the timing and flow rate of sewage being transported to the water plant; 2. Regulating tank subunit: Located at the front end of the pipeline network or water plant, it is used to store sewage for a short period of time and regulate the daily peak and valley of water volume; 3. Hydraulic level monitoring equipment: including level gauges, ultrasonic rangefinders, flow meters, etc., forming the data foundation for water storage and regulation; 4. Pipeline network simulation model: Models the hydrodynamic response of the pipeline system, supporting the prediction of storage capacity and drainage process.

[0043] The water volume control unit achieves peak shaving and valley filling of water volume by controlling the start and stop of the pump station and managing the liquid level of the storage tank, thereby regulating the load of the sewage treatment system from the water volume side.

[0044] (iii) Energy Facility Unit This unit mainly consists of a renewable energy system and its regulation components deployed within the water plant area, providing power replenishment and electricity price response capabilities. It includes: 1. Photovoltaic power generation devices: deployed on factory rooftops, above sewage ponds, green belts, etc., and connected to the factory's low-voltage or medium-voltage power distribution system via inverters; 2. Energy storage device: It can provide power support for water plants and has charging and discharging control functions. It mainly includes electrochemical energy storage batteries, PCS converters and EMS control units; 3. Microgrid controller: Coordinates the charging and discharging time and power control of photovoltaic power generation and energy storage systems with the coupling mode of plant load; 4. Consumption monitoring and strategy interface: used to monitor photovoltaic output, grid electricity price and electricity load, and generate "photovoltaic-storage synergy" operation strategy.

[0045] This unit, through strategic linkage, enables the water plant to have a certain degree of power self-sufficiency and peak shaving capacity, thereby optimizing the energy utilization structure.

[0046] (iv) Data Acquisition and AI Control Unit This unit is the core of the system's scheduling and optimization, responsible for data aggregation, strategy formulation, command issuance, and feedback monitoring. Its main components include: 1. Information Acquisition Module: Includes edge data acquisition devices such as edge data acquisition units, PLCs, and RTUs, which aggregate operational data from all pumping stations, water plants, and electrical equipment; 2. Predictive Modeling Module: Constructs response optimization models based on electricity price, water volume forecasting, and load forecasting, including water volume-load coupling models and electricity price forecasting models; 3. Strategy Generation Module: This module uses heuristic algorithms, linear / nonlinear programming algorithms, and multi-objective optimization models to generate joint water-energy operation strategies. 4. Command control module: Converts strategies into execution commands (such as start / stop, frequency, power settings, etc.) and monitors execution status feedback; 5. Operation monitoring and visualization module: Displays charts such as water volume curves, electricity price curves, processing load curves, photovoltaic output, and grid power to provide decision support for operators.

[0047] This integrated unit serves as a multi-system collaborative interface, possessing minute-level update capabilities and hour-level prediction capabilities.

[0048] (v) Power Grid Interaction Unit To enable interactive connectivity between the system and the power system, this system includes a power grid interaction unit, whose main functions include: 1. Electricity Price and Instruction Receiving Unit: Receives price curves and load control instructions from the virtual power plant platform, power dispatch platform, and electricity market; 2. Response Capability Assessment Model: This model performs an online assessment of the current system's available energy storage, power load, and water regulation capabilities. 3. Strategy compilation module: Transforms response requirements into pump station operation plans, water plant equipment load plans, and energy storage discharge plans; 4. Aggregation Control Interface: As a resource unit node participating in the scheduling market, it uploads response capability data and supports the aggregation and splitting of scheduling tasks.

[0049] This unit ensures that the hydropower coupled dispatch system has the capability for market-oriented operation and regulatory response.

[0050] (vi) Energy Management Unit The energy management unit is the core control hub of the hydropower coupled dispatch system, integrating functions such as load forecasting, dispatch optimization, and operation strategy formulation. It achieves coordinated energy management throughout the entire water treatment process through a unified intelligent control system. This unit achieves bidirectional data interaction with other equipment units via standard communication protocols, constructing a closed-loop control system of "sensing-analysis-decision-execution".

[0051] In one embodiment of the present invention, the water-energy coupled scheduling system is deployed in urban wastewater treatment scenarios with relatively complete water treatment, pumping station, and energy facilities. Without altering the core process flow of the water plant, the water-energy coupled scheduling system utilizes intelligent upgrades to existing equipment, supplements boundary equipment, and connects to a control platform to form a coordinated and adjustable "water-energy" system.

[0052] The entire system is centered around the "data acquisition and AI control unit," which connects various modules via industrial Ethernet or wireless communication to achieve unified monitoring, scheduling, and response.

[0053] (a) Interconnection relationships between systems 1. The water plant system and the water volume control unit are physically connected by a pumping station pipeline. The pumping station is controlled by a programmable logic controller (PLC) to start and stop, and is connected to a liquid level sensor, flow meter and electric valve. 2. The water plant system and energy facility units share the plant's power bus, enabling the photovoltaic, energy storage, and power load to be connected in parallel. The energy storage system has interfaces for collecting status information such as voltage, current, and SOC (state of charge). 3. The energy management unit connects with various systems and issues commands to key equipment (such as blowers, energy storage PCS, and pump station control cabinets) for starting, stopping, and power setting through remote terminal units (RTUs); 4. The connection between various modules within the data acquisition and AI control unit is achieved by the scheduling engine sending the operation strategy generated by the strategy generation module to the command control module, and then distributing it to the end device through industrial communication protocols (such as Modbus and IEC104) to realize a logical closed loop.

[0054] (II) Equipment Control Strategy In water treatment equipment, the following devices are the main adjustable objects in this invention: Inlet pump: Flow rate is regulated by speed control mode; the operating frequency is increased during off-peak electricity periods to increase the treatment capacity; the operating frequency is reduced during peak electricity periods to maintain basic load. Blower: As the most power-consuming equipment, its operating intensity is closely related to the aeration control strategy; the DO (dissolved oxygen) setpoint is controlled by an intelligent aeration system, and the blower power is controlled by frequency conversion. Storage tank control valves: By regulating the inlet and outlet gate valves of the storage tank, the liquid level is made to fluctuate within the target window range to complete the storage and discharge strategy of "valley inflow and peak outflow"; Energy storage equipment: During off-peak hours, it is charged by photovoltaic or grid power; during peak hours, it releases power according to control strategies, prioritizing the operation of the blower and water pump system.

[0055] (III) Control Strategy Generation and Distribution Process The data acquisition and AI control unit acts as the scheduling center, and its control strategy includes the following generation steps: 1. Information Aggregation: Collect data from pipeline networks, water plants, energy storage, photovoltaic systems, and electricity price platforms, including water levels, electricity prices, equipment status, and historical load data; 2. Predictive Calculation: Using the platform's built-in short-term water volume prediction models (such as ARIMA and LSTM), load prediction models, and electricity price curve prediction tools, the operating trend for the next 6-24 hours is obtained; 3. Strategy Formation: Based on the forecast results, an operation combination of "energy storage charging + pump station water intake enhancement + blower enhancement" was formulated during off-peak periods; During peak electricity price periods, an operational combination of "delayed water intake + reduced aeration power + energy storage discharge" is formulated. 4. Operational decomposition: The strategy is decomposed into specific control parameters, such as: water pump frequency 50Hz→62Hz; blower current from 220A→250A; energy storage discharge power from 0→200kW; 5. Control Execution: Control signals are sent to each device via PLC / RTU to correct the actual operating curve and ensure that the device operates within the allowable operating conditions.

[0056] (iv) Coordinated dispatch of energy and load Coordinated scheduling among photovoltaic (PV), energy storage, and hydropower loads is crucial for system operation. The data acquisition and AI control unit, based on a three-dimensional input of "PV output curve + electricity price curve + equipment response time lag," formulates the following coordination rules: During peak photovoltaic production periods (midday on sunny days), priority is given to powering equipment operation, with any excess used for energy storage. If electricity prices enter peak periods, water treatment capacity will be reduced first, and the energy storage system will make up for the load. If there is a low off-peak electricity price but insufficient photovoltaic output, the decision to expand the influent treatment load will be made based on the energy storage SOC level. If the platform detects a signal from the power grid that requires a response (such as a load reduction of 500kW), it will prioritize reducing aeration, delaying water intake, or suspending non-critical loads (such as the deodorization system).

[0057] (v) Monitoring, Calculation and Feedback Mechanism After all operating strategies are executed, the data acquisition and AI control unit continuously collects feedback from each node of the system, including: energy storage SOC curve, real-time photovoltaic power, liquid level trend of the regulating tank, total amount of sewage treated and instantaneous load, unit power consumption change and power saving magnitude.

[0058] Based on the collected data, the operational strategy is adjusted and optimized.

[0059] The implementation details for Region A and Region B are as follows: Region A Water treatment unit: It has 7 water purification plants (sewage treatment plants) with a total treatment capacity of 315,000 tons / day and an installed capacity of 10.6MW, covering key equipment such as influent pumps, blowers, and dosing systems.

[0060] Water volume control unit: includes 25 sewage pumping stations and 5 storage tanks. It realizes "integrated scheduling of plant-station" through intelligent control system. For example, on October 13, 2023 and 2024, the daily inflow was 69,276 tons and 69,218 tons, respectively. After control, the daily variation coefficient decreased significantly and the inflow tended to be stable.

[0061] Energy facilities unit: Distributed photovoltaic systems have been deployed in wastewater treatment plants, such as the photovoltaic system built in water purification plant A, which generates approximately 25% of the annual electricity consumption. A 250kW / 1MW energy storage system has also been built for peak-valley regulation.

[0062] Energy Management Unit: Based on a cloud-edge-device architecture, it collects data from various plants and stations on a minute-by-minute basis, and uses AI algorithms to analyze photovoltaics, energy storage, load, weather, etc., to achieve platform-level coordinated scheduling.

[0063] Grid Interaction Unit: Connects with the virtual power plant platform, receives grid dispatch requests, and completes peak shaving and valley filling responses. For example, if a 1030kW adjustable load is dispatched 10 times per year, each time for 2 hours, the revenue per dispatch is approximately RMB 8 per kW.

[0064] Data Acquisition and AI Control Unit: Utilizing a hybrid spatiotemporal graph convolutional network, it achieves load forecasting, electricity price sensing, and instruction generation; the specific steps are as follows: Data acquisition: Minute-level data collection is performed on wastewater treatment plant influent volume, electricity price curves, and energy storage charging and discharging status; Coupled modeling: Based on the water plant's operating characteristics, electricity price fluctuations, and energy storage capacity, a coupled model of "inflow-load-electricity price" is constructed; Peak shaving identification: For example, if the influent volume on October 13, 2023 and October 13, 2024 is similar but the fluctuations are significantly different, the model identifies and generates time-sharing treatment strategies, including off-peak and peak-peak strategies. Specifically: Off-peak strategy: During periods of low electricity price (such as at night), the pumping station is started in advance to inject sewage into the storage tank, increasing the influent treatment volume, charging the energy storage, and using the photovoltaic system for self-consumption; Peak-peak strategy: During periods of high electricity price, the treatment load is reduced, the storage tank temporarily stores untreated sewage, and the energy storage is released to supply power, achieving peak-valley arbitrage. Command issuance and execution: Generate scheduling commands based on the operation strategy to precisely control the start-up and shutdown of pump stations and the operation sequence of load equipment; Closed-loop feedback: Monitors and processes load, water quality, electricity price, and response status, optimizes strategies in real time, and achieves dynamic control.

[0065] In this embodiment, through data acquisition and scheduling by the AI ​​control unit, the total adjustable load of water purification plant A is 1030kW, with an estimated annual revenue of 82,400 yuan (10 scheduling cycles). Combined with the annual revenue of 15MW / 30MWh energy storage of approximately 720,000 yuan, diversified revenue and load fluctuation mitigation are achieved.

[0066] Region B Water treatment unit: Includes water purification plants M and N, with a wastewater treatment capacity of 805,000 m³. 3 / d, accounting for 85% of the treatment capacity in the central urban area of ​​region B. The M water purification plant operates at 80% load, with a power consumption of 0.31 kWh / t per ton of water and a power cost of 0.21 yuan per ton of water.

[0067] Water Quantity Control Unit: There are currently 42 sewage pumping stations, but only 7 are connected to the water management system, and they are "visible but not controllable," lacking effective "integrated plant-station scheduling" capabilities. The adjustable storage capacity for each area is 60,900 m³ for area A. 3 26,800 m² in area B 3 wait.

[0068] Energy facility unit: Each sewage treatment plant has deployed photovoltaic systems. For example, the water purification plant in area A has a chemical consumption of only 0.05 yuan per ton of water, and its photovoltaic absorption capacity is good. However, it lacks energy storage support and its energy transfer capability is weak.

[0069] Energy Management Unit: It has functions of scheduling optimization, data analysis and strategy formulation, but it has not yet fully realized unified access for all plants and stations.

[0070] Grid interaction unit: Currently, it mainly focuses on self-consumption of photovoltaic power generation and has not yet fully participated in grid dispatch response. Further improvement of response capabilities is needed through the construction of a virtual power plant platform.

[0071] Data Acquisition and AI Control Unit: This unit optimizes dosing points and aeration layout through the platform to promote energy conservation and emission reduction. The total investment in energy-saving renovations in Region B is approximately 9 million yuan, with an estimated annual saving of 2.8 million yuan, primarily due to the implementation of the AI ​​control unit.

[0072] Region B has not yet fully implemented integrated hydropower dispatching, and a preliminary strategy is adopted, with the following implementation method: 1. Data Acquisition: Collect data on influent fluctuations, electricity costs, and some photovoltaic system outputs from water purification plants such as M and N. 2. Operational Analysis: For example, the electricity cost per ton of water at the M water purification plant is 0.21 yuan. Due to large fluctuations in the influent water, the equipment starts and stops frequently, resulting in high operating costs. 3. Storage capacity identification: Based on model estimation, the storage capacity of area N is 60,900 m³. 3 M area 26,800 m 3 Storage tanks can participate in peak shaving regulation; 4. Time-sharing adjustment strategy: Implement an "early dispatch and late processing" strategy at the equipment scheduling level, and reduce peak energy consumption by operating blowers and pump stations during off-peak hours; 5. Energy-saving optimization measures: Implement process optimization and equipment modification, such as replacing aeration heads and optimizing the dosing system; 6. System Expansion Reserved: An interface is reserved for future integration with the virtual power plant platform, with plans to connect more pumping stations and storage tanks to enhance collaborative scheduling capabilities; 7. Assessment and Feedback: Based on the energy-saving renovation calculation, the project will save approximately RMB 2.8 million annually, with a reasonable investment payback period, supporting the further construction of a smart water-energy coupling system.

[0073] Based on and Figure 1 Using the same principle as the method shown, this embodiment of the invention also provides a hydropower coupling scheduling method, such as... Figure 3 As shown, it includes: Real-time acquisition of operational status information of each equipment unit in the hydropower coupling scheduling system; By collecting operational status information, the hydropower coupling parameters for future periods are predicted, and the prediction results are obtained; wherein, the hydropower coupling parameters include: load changes, electricity price trends and water demand trends; Based on the prediction results and combined with the current peak and off-peak electricity price periods, an operation strategy is generated; According to the operating strategy, scheduling instructions are sent to each device unit to control each device unit to operate according to the scheduling instructions.

[0074] The above description is merely a preferred embodiment of the present invention and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this invention is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this invention.

Claims

1. A water-energy coupled dispatch system, characterized in that, The system comprises: An information acquisition module for acquiring real-time operation state information of each device unit in the water-energy coupling scheduling system; A prediction modeling module for predicting water-energy coupling parameters in a future period based on the acquired operation state information to obtain a prediction result, wherein the water-energy coupling parameters include load variation, electricity price trend, and water demand trend; A strategy generation module for generating an operation strategy based on the prediction result and in combination with a current electricity price peak-valley period; An instruction control module for sending scheduling instructions to each device unit according to the operation strategy to control each device unit to operate according to the scheduling instructions.

2. The water energy coupling scheduling system of claim 1, wherein, The device unit comprises: A water treatment unit including a water inlet pump, a blower, and a dosing system for purifying sewage; A water volume regulation unit including a pump station and a regulating reservoir for buffering and adjusting sewage flow; An energy facility unit including a photovoltaic power generation device, an energy storage device, and a micro-grid controller for providing local energy for the water treatment unit and autonomously managing the local energy; A power grid interaction unit for establishing two-way communication and interaction with an external power system, acquiring an electricity price signal, and responding to scheduling instructions.

3. The water energy coupling scheduling system of claim 2, wherein, Further comprising: A strategy optimization module for acquiring monitoring information acquired by the information acquisition module and optimizing and adjusting the operation strategy based on the monitoring information, wherein the monitoring information includes an energy storage SOC curve, a regulating reservoir liquid level, a treatment load, and unit power consumption.

4. The water energy coupling scheduling system of claim 2, wherein, The energy storage device comprises an energy storage battery pack and an energy storage converter, the energy storage converter is electrically connected with the micro-grid controller and the energy storage battery pack respectively, and the energy storage converter is used for realizing charge and discharge control of the energy storage battery pack.

5. The water energy coupling scheduling system of claim 2, wherein, The micro-grid controller is electrically connected with the water inlet pump, the blower, and the dosing system in the water treatment unit through a low-voltage power distribution line, and is used for time-periodically allocating power supply of the water inlet pump, the blower, and the dosing system.

6. The water energy coupling scheduling system of claim 2, wherein, The power grid interaction unit comprises: A communication terminal for receiving a load scheduling signal from the power grid side.

7. The water-energy coupling scheduling system of claim 2, wherein, The operation strategy includes a valley period strategy and a peak period strategy, wherein the valley period strategy is specifically to control the water volume regulation unit to increase the pump station operation frequency and inject water into the regulating reservoir in the valley period, and control the energy facility unit to generate photovoltaic power and charge the energy storage device; and the peak period strategy is specifically to control the water treatment unit to reduce the water inlet load and control the energy facility unit to release energy storage electric energy to supply load equipment operation in the peak period.

8. The water energy coupling scheduling system of claim 2, wherein, Buffering and adjusting the sewage flow specifically refers to realizing flexible transfer of the sewage treatment load in the time dimension through regulating reservoir liquid level adjustment and pump station start-stop timing control.

9. The water energy coupling scheduling system of claim 2, wherein, When the device unit receives the scheduling instructions, the photovoltaic power generation device and the energy storage device of the energy facility unit, and the pump station of the water volume regulation unit or the water inlet pump of the water treatment unit are preferentially responded.

10. A water-energy coupling scheduling method, applied to the water-energy coupling scheduling system of any one of claims 1-9, characterized in that, Comprise: Acquiring real-time operation state information of each device unit in the water-energy coupling scheduling system; Predicting water-energy coupling parameters in a future period based on the acquired operation state information to obtain a prediction result, wherein the water-energy coupling parameters include load variation, electricity price trend, and water demand trend; generating a running strategy based on the prediction result and in combination with a current electricity price peak-valley period; sending a scheduling instruction to each device unit according to the running strategy to control each device unit to run according to the scheduling instruction.

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