Constant pressure water supply system for water, electricity and gas systems

Abstract

The present application relates to the technical field of constant pressure water supply system, and discloses a constant pressure water supply system for water, electricity and gas system, comprising a central control unit, the central control unit is integrated with a data acquisition and verification module, a data storage unit, an energy collaborative allocation module, a flow leakage module, a prediction control module and a block chain control module, the data acquisition and verification module acquires flow data of key nodes of the pipe network, and connects a water pump motor variable frequency speed regulation control system to obtain motor parameters to back calculate pipe network pressure and flow data, through data fusion and data comparison, data acquisition abnormalities are judged, and fault elimination is started when the abnormality occurs, and the flow leakage module is used for leakage detection of the pipe network, and the like.

Description

Technical Field

[0001] This invention relates to the field of constant pressure water supply system technology, and more specifically, to a constant pressure water supply system for water, electricity and gas systems. Background Technology

[0002] In the field of constant pressure water supply systems, with the acceleration of urbanization and the continuous expansion of industrial production scale, higher requirements are placed on the stability, efficiency, and intelligent management of water supply systems. However, existing constant pressure water supply systems have many technical problems:

[0003] 1. Data acquisition and processing issues: Traditional water supply systems rely on a single data source, resulting in poor accuracy.

[0004] 2. Pipeline network leakage detection and handling issues: Existing technologies have difficulty accurately distinguishing between normal and abnormal flow changes, making it impossible to detect pipeline network leaks in a timely manner, and making it difficult to maintain stable water supply pressure after a leak occurs;

[0005] 3. Energy utilization issues: Low energy utilization efficiency. The power source configuration of water pumps in traditional water supply systems is unreasonable. It often does not take into account factors such as energy cost, stability and water pump operating efficiency, resulting in energy waste and high operating costs.

[0006] 4. Water and energy consumption forecasting and control issues: Existing technologies cannot accurately predict water and energy consumption trends;

[0007] 5. Community water supply network management issues: Unscientific operation and management of water pumps, lack of reasonable alternating operation strategies, resulting in shortened pump lifespan and increased maintenance costs;

[0008] Based on this, the present invention provides a constant pressure water supply system for water, electricity and gas systems to solve the technical problems mentioned in the background art. Summary of the Invention

[0009] To overcome the shortcomings of existing technologies, this invention provides a constant pressure water supply system for water, electricity, and gas systems. This invention utilizes a data acquisition and verification module, employing a high-precision flow sensor and a motor parameter monitoring unit to collect multi-source data. The data is then fused, verified, and compared using a Kalman filter algorithm by a data fusion unit. This multi-source data fusion and real-time verification mechanism significantly improves data accuracy and reliability. In case of data anomalies, a fault diagnosis process can be initiated promptly, providing a solid data foundation for precise control of the water supply system. This effectively avoids control errors caused by inaccurate data and ensures the stable operation of the water supply system, a feat unmatched by existing technologies.

[0010] To achieve the above objectives, the present invention provides the following technical solution: a constant pressure water supply system for water, electricity and gas systems, including a central control unit, which integrates a data acquisition and verification module, a data storage unit, an energy collaborative allocation module, a flow leakage module, a prediction and control module, and a blockchain control module;

[0011] The data acquisition and verification module collects flow data from key nodes in the pipeline network and connects to the variable frequency speed control system of the water pump motor to obtain motor parameters to infer the pressure and flow data of the pipeline network. Through data fusion and data comparison, it judges data acquisition abnormalities and initiates fault investigation when abnormalities occur.

[0012] The flow leakage module collects pipeline network data and water usage pattern information, uses a recurrent neural network to build a prediction model, and distinguishes between normal and abnormal flow changes. When an anomaly is detected, it extracts multi-dimensional features and uses a decision tree model to determine whether the pipeline network is leaking, thus realizing adaptive adjustment of pipeline network flow and leak detection.

[0013] The energy coordination and allocation module collects multi-energy data such as water, electricity, and gas, optimizes the power source configuration of water pumps, coordinates pressure regulation, and recovers residual pressure to generate electricity;

[0014] The prediction and control module collects, processes and stores multi-source data, uses technology and models to predict water and energy consumption trends in different regions and transmits the results. Based on the results, it constructs pump operation plans and establishes model strategies to simulate pump status under different operating conditions in order to optimize and adjust the pump operation plans.

[0015] The blockchain control module deploys smart contracts on the Ethereum blockchain platform in the community-level water supply network to collect, process, and utilize data on water demand, pump operation, and pipeline structure to achieve dynamic allocation of pump output, complementary pressure regulation, alternating operation management, data security processing, and network rule monitoring.

[0016] As a preferred embodiment of the present invention, the data acquisition and verification module includes:

[0017] High-precision flow sensor: Deployed at key nodes of the pipeline network to collect pipeline flow data, convert analog signals into digital signals, and transmit them to the data fusion unit through redundant communication lines;

[0018] Motor parameter monitoring unit: Connects to the water pump motor frequency conversion speed control system, acquires motor current and speed parameters, uses a pressure estimation model based on motor characteristic curves and the principles of motor electromagnetics and fluid mechanics to back-calculate pipeline pressure and flow, and transmits it to the data fusion unit;

[0019] Data fusion unit: Receives data feedback from high-precision flow sensors and motor parameter monitoring units, uses intelligent algorithms to fuse, verify and compare data in real time, initiates fault diagnosis when data is abnormal, and feeds back abnormal information to the central control unit. The data collected and analyzed by the data fusion unit is backed up to the data storage unit in real time.

[0020] As a preferred embodiment of the present invention, the motor parameter monitoring unit also monitors motor temperature and vibration parameters, and when the motor parameter monitoring unit detects abnormal data, it promptly sends an early warning to the data fusion unit.

[0021] The data fusion unit uses the Kalman filter algorithm to fuse data from different sources.

[0022] As a preferred embodiment of the present invention, the flow leakage module includes:

[0023] The intelligent algorithm processing unit collects flow data from the pipeline network over historical periods using high-precision flow sensors, simultaneously collects information related to water usage patterns, cleans the raw flow data and smooths it using methods such as moving averages, and integrates it into a structured dataset.

[0024] The intelligent algorithm processing unit uses a recurrent neural network as the basic model, divides the structured dataset into a training set, a validation set, and a test set, and trains the model with historical flow and water usage pattern information as input. The model performance is optimized by adjusting the loss function, parameter update algorithm, and hyperparameters. The trained model receives high-precision flow sensor data in real time, predicts the normal flow range based on real-time time series data and water usage pattern information, and compares the real-time flow with the predicted range, using ±10% as the judgment standard.

[0025] When the intelligent algorithm processing unit detects abnormal flow changes, it extracts the magnitude, duration, and rate of the flow change, uses a leak detection model based on decision tree algorithm and trained with actual leak cases to determine whether there is a leak, and combines the pipeline physical parameters to assess the degree of leak.

[0026] The intelligent algorithm processing unit is equipped with an alarm output interface. When a pipeline leak is detected, an alarm signal is promptly sent to the central control unit, which then triggers the emergency response process.

[0027] After the intelligent algorithm processing unit generates an alarm signal, the water pump operating parameter control unit adjusts the water pump operating parameters and compensates for the pressure loss caused by leakage by adjusting the flow rate, thereby maintaining a constant water supply pressure.

[0028] As a preferred embodiment of the present invention, the energy coordinated allocation module includes:

[0029] The energy data acquisition unit communicates with the monitoring equipment at the water, electricity, and gas energy production ends. It is used to collect data on the generation of water, electricity, and gas energy, as well as the pressure data of the three networks in real time. After standardizing, encrypting, and verifying the data, it is transmitted to the data analysis and decision-making unit and the pressure coordination and control unit, respectively.

[0030] The data analysis and decision-making unit has built-in optimization algorithms and intelligent models. It receives energy generation data transmitted from the energy data acquisition unit, comprehensively considers energy costs, stability, pump operating efficiency and overall system energy consumption factors, calculates a suitable power source combination scheme for pump operation, and transmits the scheme instructions to the power source switching control unit. It can also learn and adjust parameters based on historical system operating data and real-time feedback.

[0031] The power source switching control unit controls the water pump power source switching device according to the instructions of the data analysis and decision-making unit, so as to realize the rapid and smooth switching of the water pump between different power sources, and ensure that the water pump operates under the optimal power source configuration. The power source switching control unit is connected to the water pump power source switching device by redundant communication lines.

[0032] The pressure coordination and control unit receives pressure data from the three networks transmitted by the energy data acquisition unit. When the water pressure fluctuates, it uses air pressure to compensate for the water pressure and adjusts the pump operating parameters and energy distribution strategy according to the coordinated pressure of the three networks.

[0033] The energy recovery unit is equipped with a residual pressure power generation device to detect residual pressure in the pipeline network and use it to generate electricity, feeding the recovered electrical energy back to the power energy system.

[0034] As a preferred embodiment of the present invention, the energy coordination and allocation module is provided with an energy allocation strategy adjustment interface. Operators can manually adjust the energy allocation strategy according to actual needs through an external control terminal, thereby intervening in the calculation results of the data analysis and decision-making unit.

[0035] As a preferred embodiment of the present invention, the predictive control module includes:

[0036] The multi-source data fusion acquisition unit is connected to the meteorological data interface, geographic information system, urban population flow monitoring system and regional economic activity monitoring platform respectively. It is used to collect weather conditions, topographic features, population flow density, commercial activity activity data and water supply system equipment energy consumption data in real time. The collected data is standardized and cleaned to remove outliers and noise data before being classified and stored.

[0037] The water and energy consumption prediction unit uses big data analysis technology and neural network models, combined with data provided by the multi-source data fusion acquisition unit and historical water and energy consumption data, to predict changes in water demand and energy consumption trends in different regions, and transmits the prediction results to the control and prediction unit.

[0038] The control and prediction unit, based on the water demand prediction results provided by the water and energy consumption prediction unit, constructs a predictive operation plan for water pumps that includes differences in water demand in different time periods and regions, and establishes a water pump operation model strategy to simulate the water pump operation status under predicted and extreme unpredictable conditions, so as to optimize and adjust the water pump operation plan.

[0039] As a preferred embodiment of the present invention, the blockchain control module includes:

[0040] Contract Deployment and Management Unit: Deploy smart contracts based on the blockchain platform in the community-level water supply network, predefine data processing, pump control and reward / penalty rules, and monitor and manage network operation;

[0041] Water demand collection and uploading unit: Smart water meters are installed at the user end. The smart water meters collect, process and encrypt water demand data, and upload it to the blockchain platform at set intervals.

[0042] Dynamic pump output allocation unit: The system uses a particle swarm optimization algorithm to construct a multi-objective optimization model based on water demand, pump operation and pipeline structure data on the blockchain, and dynamically allocates pump output to achieve regional pressure balance and optimal energy consumption.

[0043] Water pressure complementary regulation unit: The blockchain platform records the pressure data of each node, the smart contract analyzes the pressure deviation and generates regulation instructions, the instructions are broadcast to the water pump control equipment via the blockchain, the equipment executes and feeds back the operating status, and the smart contract adjusts the instructions accordingly to maintain constant pressure.

[0044] Pump Alternating Operation Management Unit: The smart contract formulates the pump alternating operation strategy, arranges the operation sequence according to the pump operation time, maintenance cycle and water demand, records the number of start-ups and shutdowns, issues maintenance reminders when the threshold is reached, and interacts with the equipment maintenance management platform to optimize the strategy.

[0045] As a preferred embodiment of the present invention, the water pressure complementary regulation unit has an emergency regulation mode to cope with sudden changes in water usage or equipment failure. The smart water meter in the water demand acquisition and uploading module can update the data acquisition and processing algorithm through remote firmware upgrades. The particle swarm optimization algorithm treats the output allocation scheme of each water pump as a particle and searches for the optimal solution in the solution space. At the same time, combined with fuzzy control theory, the search parameters of the particle swarm are dynamically adjusted according to the water demand, water pump operation and pipeline structure data uploaded to the blockchain platform in real time. Fuzzy control theory uses fuzzy rules to fuzzify the regional pressure deviation and pressure change rate, and determines the adjustment amount of inertia weight and acceleration constant according to fuzzy inference to achieve regional pressure balance and optimal water pump energy consumption.

[0046] As a preferred technical solution of the present invention, it also includes a three-dimensional dynamic monitoring platform that is bidirectionally connected to the central control unit. The three-dimensional dynamic monitoring platform, by accessing and integrating data from multiple modules, constructs a 3D scene of the water supply network, and displays in real time and intuitively the pipeline flow, pressure, equipment parameters and water, electricity and gas energy data information, so as to realize abnormal monitoring and early warning, prediction and control visualization, and data interaction.

[0047] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0048] 1. This invention utilizes a data acquisition and verification module to collect multi-source data using a high-precision flow sensor and a motor parameter monitoring unit. The data is then fused, verified, and compared using a Kalman filter algorithm by a data fusion unit. This multi-source data fusion and real-time verification mechanism greatly improves the accuracy and reliability of the data. In case of data anomalies, a fault investigation process can be initiated in a timely manner, providing a solid data foundation for the precise control of the water supply system. This effectively avoids control errors caused by inaccurate data and ensures the stable operation of the water supply system, which is unparalleled by existing technologies.

[0049] 2. The flow leakage module of this invention uses a recurrent neural network to build a prediction model, which can accurately distinguish between normal and abnormal flow changes. When an anomaly is detected, it extracts multi-dimensional features and uses a decision tree model to determine whether the pipeline is leaking. It can also assess the degree of leakage. Once a leak is detected, the pump operation parameter control unit will automatically adjust the pump operation parameters to compensate for the pressure loss caused by the leak, maintain constant water supply pressure, effectively reduce water waste, reduce the impact of water supply accidents on residents' lives and production, and significantly improve the pipeline leakage detection and handling capabilities.

[0050] 3. The energy coordination and allocation module of this invention collects multi-energy data of water, electricity, and gas, optimizes the power source configuration of water pumps, and calculates the optimal power source combination scheme by comprehensively considering energy costs, stability, water pump operating efficiency, and overall system energy consumption factors, and achieves rapid and stable switching. At the same time, it uses air pressure to compensate for water pressure fluctuations, recovers residual pressure in the pipeline network to generate electricity, and feeds the recovered electrical energy back to the electrical energy system, which greatly improves energy utilization efficiency, reduces operating costs, and realizes efficient energy utilization and recycling, which is difficult to achieve with traditional technologies.

[0051] 4. The prediction and control module of this invention collects multi-source data such as meteorological, geographical, population flow, commercial activities and equipment energy consumption through a multi-source data fusion acquisition unit. It uses big data analysis technology and neural network models to accurately predict changes in water demand and energy consumption trends in different regions. Based on the prediction results, it constructs a water pump operation plan and optimizes and adjusts the plan by simulating different operating conditions. It plans water pump operation in advance to avoid insufficient or excessive water supply, reduce energy consumption, improve the stability and reliability of the water supply system, and ensure normal water use for residents and enterprises. It has significant advantages in water use and energy consumption prediction and control.

[0052] 5. The blockchain control module of this invention deploys smart contracts on the Ethereum blockchain platform in a community-level water supply network. It uses blockchain technology to ensure data security and trustworthiness, realizes dynamic allocation of water pump output, complementary pressure regulation, and alternating operation management. The reward and punishment rules formulated by the smart contract can also promote rational water use by users. Through these functions, the intelligence level and operating efficiency of the water supply system are improved, the service life of water pumps is extended, and the problems of traditional community water supply network management are solved. Attached Figure Description

[0053] Figure 1 This is a schematic diagram of the constant pressure water supply system for water, electricity, and gas systems according to the present invention.

[0054] Figure 2 This is a schematic diagram of the data acquisition and verification module of the present invention.

[0055] Figure 3 This is a schematic diagram of the flow leakage module of the present invention;

[0056] Figure 4 This is a schematic diagram of the energy coordinated allocation module of the present invention. Detailed Implementation

[0057] 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, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] like Figures 1 to 4 As shown, the present invention provides a constant pressure water supply system for water, electricity and gas systems, including a central control unit, which integrates a data acquisition and verification module, a data storage unit, an energy collaborative allocation module, a flow leakage module, a prediction and control module and a blockchain control module;

[0059] The data acquisition and verification module collects flow data from key nodes in the pipeline network and connects to the variable frequency speed control system of the water pump motor to obtain motor parameters to infer the pressure and flow data of the pipeline network. Through data fusion and data comparison, it judges data acquisition abnormalities and initiates fault investigation when abnormalities occur.

[0060] The data acquisition and verification module includes:

[0061] High-precision flow sensor: Deployed at key nodes of the pipeline network to collect pipeline flow data, convert analog signals into digital signals, and transmit them to the data fusion unit through redundant communication lines;

[0062] Motor parameter monitoring unit: Connects to the water pump motor frequency conversion speed control system, acquires motor current and speed parameters, uses a pressure estimation model based on motor characteristic curves and the principles of motor electromagnetics and fluid mechanics to back-calculate pipeline pressure and flow, and transmits it to the data fusion unit;

[0063] The motor parameter monitoring unit also monitors motor temperature and vibration parameters. When the motor parameter monitoring unit detects abnormal data, it promptly sends an alert to the data fusion unit.

[0064] Data fusion unit: Receives data feedback from high-precision flow sensor and motor parameter monitoring unit, uses intelligent algorithm to fuse, verify and compare data in real time, initiates fault diagnosis when data is abnormal, and feeds back abnormal information to central control unit. The data collected and analyzed by the data fusion unit is backed up to the data storage unit in real time.

[0065] The data fusion unit uses the Kalman filter algorithm to fuse data from different sources;

[0066] The high-precision flow sensor selected is the SN450 flow sensor, which features high precision and high reliability and can accurately measure pipeline flow data.

[0067] This solution addresses the technical problems of inaccurate data acquisition, low reliability of single data sources, and untimely fault diagnosis in traditional water supply systems.

[0068] Compared to existing technologies, its outstanding advantages lie in the fact that by integrating multiple data sources and implementing a real-time verification mechanism, it greatly improves the accuracy and reliability of data, enabling timely detection of data anomalies and rapid initiation of investigation processes. This effectively ensures the stability and reliability of water supply system data, providing a solid data foundation for subsequent precise regulation and control.

[0069] In the water supply system of a large residential community, there was a situation where the flow data was abnormal due to slight blockage in some pipes. Traditional monitoring methods failed to detect it in time, but this data acquisition and verification module quickly detected the data abnormality by working together with a high-precision flow sensor and a motor parameter monitoring unit.

[0070] By using the Kalman filter algorithm for fusion analysis, not only were the anomalies in the flow data identified, but the blockage was also accurately located by combining the motor parameters, allowing for the rapid restoration of water supply and ensuring normal water use for residents.

[0071] When performing data verification, the data fusion unit not only compares the currently collected data, but also analyzes historical data within a certain time period.

[0072] A time window of 1 hour is set. If abnormal data fluctuations occur multiple times within this time period, even if the fluctuation amplitude does not exceed the threshold each time, a more in-depth troubleshooting process will be triggered to ensure the accuracy of the data and the stability of the system.

[0073] The flow leakage module collects pipeline network data and water usage pattern information, uses a recurrent neural network to build a prediction model, and distinguishes between normal and abnormal flow changes. When an anomaly is detected, it extracts multi-dimensional features and uses a decision tree model to determine whether the pipeline network is leaking, thus realizing adaptive adjustment of pipeline network flow and leak detection.

[0074] The traffic leakage module includes:

[0075] The intelligent algorithm processing unit collects flow data from the pipeline network over historical periods using high-precision flow sensors, simultaneously collects information related to water usage patterns, cleans the raw flow data and smooths it using methods such as moving averages, and integrates it into a structured dataset.

[0076] The intelligent algorithm processing unit uses a recurrent neural network as the basic model. The structured dataset is divided into a training set, a validation set, and a test set. The model is trained by taking historical flow and water usage pattern information as input. The model performance is optimized by adjusting the loss function, parameter update algorithm, and hyperparameters. The trained model receives high-precision flow sensor data in real time and predicts the normal flow range based on real-time time series data and water usage pattern information. The real-time flow is compared with the predicted range, and ±10% is used as the judgment standard.

[0077] When the intelligent algorithm processing unit detects abnormal flow changes, it extracts the magnitude, duration, and rate of the flow change, uses a leak detection model based on decision tree algorithm and trained with actual leak cases to determine whether there is a leak, and combines the pipeline physical parameters to assess the degree of leak.

[0078] The intelligent algorithm processing unit is equipped with an alarm output interface. When a pipeline leak is detected, an alarm signal is promptly sent to the central control unit, which then triggers the emergency response process.

[0079] After the intelligent algorithm processing unit generates an alarm signal, the water pump operating parameter control unit adjusts the water pump operating parameters and compensates for the pressure loss caused by leakage by adjusting the flow rate, thereby maintaining a constant water supply pressure.

[0080] This solution solves the technical problems in existing technologies, such as the difficulty in accurately distinguishing between normal and abnormal flow changes, the inability to detect pipeline leaks in a timely manner, and the difficulty in maintaining stable water supply pressure after a leak occurs.

[0081] Compared to traditional methods, its outstanding advantages lie in its ability to accurately detect pipeline leaks, issue timely alarms, and automatically adjust water pump operating parameters to quickly compensate for pressure losses caused by leaks, effectively reducing water waste and mitigating the impact of water supply accidents on residents' lives and production.

[0082] In the water supply system of an old urban area, there are multiple potential leakage risks due to aging pipes. In the past, it was difficult to detect small leaks in time by relying on manual inspections. However, after adopting this flow leakage module, multiple small leaks were successfully detected.

[0083] The energy coordination and allocation module collects multi-energy data such as water, electricity, and gas, optimizes the power source configuration of water pumps, coordinates pressure regulation, and recovers residual pressure to generate electricity;

[0084] The energy coordination and allocation module includes:

[0085] The energy data acquisition unit communicates with the monitoring equipment at the water, electricity, and gas energy production ends. It is used to collect data on the generation of water, electricity, and gas energy, as well as the pressure data of the three networks in real time. After standardizing, encrypting, and verifying the data, it is transmitted to the data analysis and decision-making unit and the pressure coordination and control unit, respectively.

[0086] The data analysis and decision-making unit has built-in optimization algorithms and intelligent models. It receives energy generation data transmitted from the energy data acquisition unit, comprehensively considers energy costs, stability, pump operating efficiency and overall system energy consumption factors, calculates a suitable power source combination scheme for pump operation, and transmits the scheme instructions to the power source switching control unit. It can also learn and adjust parameters based on historical system operating data and real-time feedback.

[0087] The power source switching control unit controls the water pump power source switching device according to the instructions of the data analysis and decision-making unit, so as to realize the rapid and smooth switching of the water pump between different power sources, and ensure that the water pump operates under the optimal power source configuration. The power source switching control unit is connected to the water pump power source switching device by redundant communication lines.

[0088] The power source switching control unit and the water pump power source switching device are connected via an RS-485 communication interface and use the Modbus communication protocol for redundant communication.

[0089] The pressure coordination and control unit receives pressure data from the three networks transmitted by the energy data acquisition unit. When the water pressure fluctuates, it uses air pressure to compensate for the water pressure and adjusts the pump operating parameters and energy distribution strategy according to the coordinated pressure of the three networks.

[0090] The energy recovery unit is equipped with a residual pressure power generation device to detect residual pressure in the pipeline network and use it to generate electricity, feeding the recovered electrical energy back to the power energy system.

[0091] The energy coordination and allocation module is equipped with an energy allocation strategy adjustment interface. Operators can manually adjust the energy allocation strategy according to actual needs through an external control terminal, and intervene in the calculation results of the data analysis and decision-making unit.

[0092] The residual pressure power generation device can be a small-scale hydroelectric power generation device;

[0093] This solution addresses the technical problems in traditional water supply systems, such as low energy efficiency, unreasonable power source configuration, uncoordinated pressure control, and waste of residual pressure energy.

[0094] Compared with existing technologies, its outstanding advantages lie in the coordinated allocation of multiple energy sources such as water, electricity, and gas, the optimization of water pump power source configuration, the improvement of energy utilization efficiency, the reduction of operating costs, and the realization of energy recovery and reuse through residual pressure power generation.

[0095] In the past, the water supply system of a certain industrial park consumed a lot of energy and had high costs.

[0096] After adopting this energy coordination and allocation module, the power source of the water pump can be switched reasonably according to the energy price and production demand at different times.

[0097] During periods of low electricity prices, electric-powered water pumps should be used preferentially.

[0098] Switch to natural gas power when natural gas supply is stable and prices are low;

[0099] At the same time, air pressure is used to compensate for water pressure fluctuations, reducing energy waste;

[0100] The waste heat power generation device can recover enough electricity each month to meet the power needs of some auxiliary equipment, greatly reducing the energy costs of the park.

[0101] The prediction and control module collects, processes and stores multi-source data, uses technology and models to predict water and energy consumption trends in different regions and transmits the results. Based on the results, it constructs pump operation plans and establishes model strategies to simulate pump status under different operating conditions in order to optimize and adjust the pump operation plans.

[0102] The predictive regulation module includes:

[0103] The multi-source data fusion acquisition unit is connected to the meteorological data interface, geographic information system, urban population flow monitoring system and regional economic activity monitoring platform respectively. It is used to collect weather conditions, topographic features, population flow density, commercial activity activity data and water supply system equipment energy consumption data in real time. The collected data is standardized and cleaned to remove outliers and noise data before being classified and stored.

[0104] The water and energy consumption prediction unit uses big data analysis technology and neural network models, combined with data provided by the multi-source data fusion acquisition unit and historical water and energy consumption data, to predict changes in water demand and energy consumption trends in different regions, and transmits the prediction results to the control and prediction unit.

[0105] The control and prediction unit, based on the water demand prediction results provided by the water and energy consumption prediction unit, constructs a predictive operation plan for water pumps that includes differences in water demand in different time periods and regions, and establishes a water pump operation model strategy to simulate the water pump operation status under predicted and extreme unpredictable conditions, so as to optimize and adjust the water pump operation plan.

[0106] This solution addresses the technical problems of existing technologies, such as the inability to accurately predict water and energy consumption trends and the lack of scientific planning and reasonable control of water pump operation.

[0107] Compared to traditional methods, its outstanding advantages lie in its ability to accurately predict water demand and energy consumption trends in advance, providing scientific and reasonable plans for water pump operation, optimizing water pump operation strategies, reducing energy consumption, improving the stability and reliability of the water supply system, and ensuring normal water use for residents and businesses.

[0108] In the water supply system of a large city, in the past, during the hot summer months, due to the inability to accurately predict water demand, there were often situations where water pumps supplied insufficient or excessive water, resulting in water outages or energy waste in some areas.

[0109] After adopting this forecasting and control module, by collecting meteorological data, population flow data, and commercial activity data, and combining them with historical water use data, the changes in water demand in different regions can be accurately predicted.

[0110] Based on the forecast results, the water pump operation plan was adjusted in advance, and the operating frequency and power of the water pumps were increased before the peak water consumption period, which ensured the stability of water supply and avoided energy waste.

[0111] When collecting data, the multi-source data fusion acquisition unit performs time synchronization processing on data from different data sources;

[0112] Meteorological data is updated every hour, and population flow data is updated every 15 minutes. Time synchronization ensures that data fusion and analysis are performed on the same time dimension, thereby improving the accuracy of predictions.

[0113] Meanwhile, when the control and forecasting unit constructs the pump operation plan, it will not only consider normal water demand changes, but also set a certain safety margin.

[0114] Based on the predicted water demand, an additional 10%-20% margin is added as a reference for water pump operation to cope with sudden increases in water demand and ensure the reliability of water supply.

[0115] The blockchain control module deploys smart contracts on the Ethereum blockchain platform in the community-level water supply network to collect, process, and utilize data on water demand, pump operation, and pipeline structure to achieve dynamic allocation of pump output, complementary pressure regulation, alternating operation management, data security processing, and network rule monitoring.

[0116] The blockchain control module includes:

[0117] Contract Deployment and Management Unit: Deploy smart contracts based on the blockchain platform in the community-level water supply network, predefine data processing, pump control and reward / penalty rules, and monitor and manage network operation;

[0118] Water demand collection and uploading unit: Smart water meters are installed at the user end. The smart water meters collect, process and encrypt water demand data, and upload it to the blockchain platform at set intervals.

[0119] Smart water meters collect and upload data via the LoRa wireless communication protocol;

[0120] Dynamic pump output allocation unit: The system uses a particle swarm optimization algorithm to construct a multi-objective optimization model based on water demand, pump operation and pipeline structure data on the blockchain, and dynamically allocates pump output to achieve regional pressure balance and optimal energy consumption.

[0121] Water pressure complementary regulation unit: The blockchain platform records the pressure data of each node, the smart contract analyzes the pressure deviation and generates regulation instructions, the instructions are broadcast to the water pump control equipment via the blockchain, the equipment executes and feeds back the operating status, and the smart contract adjusts the instructions accordingly to maintain constant pressure.

[0122] Pump Alternating Operation Management Unit: The smart contract formulates the pump alternating operation strategy, arranges the operation sequence according to the pump operation time, maintenance cycle and water demand, records the number of start-ups and shutdowns, issues maintenance reminders when the threshold is reached, and interacts with the equipment maintenance management platform to optimize the strategy.

[0123] The water pressure complementary regulation unit has an emergency regulation mode to cope with sudden changes in water usage or equipment failure. The smart water meter in the water demand acquisition and uploading module can update the data acquisition and processing algorithm through remote firmware upgrades. The particle swarm optimization algorithm treats the output allocation scheme of each water pump as a particle and searches for the optimal solution in the solution space. At the same time, combined with fuzzy control theory, the search parameters of the particle swarm are dynamically adjusted according to the water demand, water pump operation and pipeline structure data uploaded to the blockchain platform in real time. Fuzzy control theory uses fuzzy rules to fuzzify the regional pressure deviation and pressure change rate, and determines the adjustment amount of inertia weight and acceleration constant according to fuzzy inference to achieve regional pressure balance and optimal water pump energy consumption.

[0124] This solution addresses the technical problems of low data security, unscientific pump operation and management, inaccurate pressure regulation, and lack of effective incentive mechanisms in traditional community water supply networks.

[0125] Compared to existing technologies, its outstanding benefits lie in using blockchain technology to ensure data security and credibility, enabling scientific management and precise pressure regulation of water pumps, improving the intelligence level and operational efficiency of the water supply system, and promoting rational water use by users through reward and punishment rules.

[0126] In the water supply system of a newly built smart community, the scientific management and precise pressure regulation of water pumps were achieved through a blockchain control module;

[0127] During peak water usage periods, the dynamic allocation unit of water pump output rationally allocates water pump output based on water demand data on the blockchain to ensure stable water supply pressure in each area.

[0128] Meanwhile, the smart contract rationally arranges the alternating operation of the water pumps based on their operating time and maintenance cycle, thus extending the service life of the water pumps.

[0129] When an abnormal pressure occurs in a certain area, the water pressure complementary regulation unit will quickly start emergency regulation.

[0130] It also includes a three-dimensional dynamic monitoring platform that has a two-way data connection with the central control unit. The three-dimensional dynamic monitoring platform, by accessing and integrating data from multiple modules, constructs a 3D scene of the water supply network, and displays in real time and intuitively the pipeline flow, pressure, equipment parameters and water, electricity and gas energy data information, so as to realize abnormal monitoring and early warning, prediction and control visualization, and data interaction.

[0131] During operation, the 3D dynamic monitoring platform accesses and integrates data from multiple modules to construct a 3D scene of the water supply network, displaying real-time data on pipeline flow, pressure, equipment parameters, and water, electricity, and gas energy.

[0132] This solution addresses the technical problems of traditional monitoring methods failing to intuitively and comprehensively display the operating status of the water supply system, as well as the lack of visualization in abnormal monitoring, early warning, and predictive regulation.

[0133] Compared to existing technologies, its outstanding advantage lies in its ability to present water supply system operation data in an intuitive 3D scene, making it convenient for operators to monitor the system status in real time and detect abnormalities in a timely manner.

[0134] By realizing the visualization of abnormal monitoring, early warning, and predictive control, the efficiency of fault handling and the accuracy of control are greatly improved, which helps to improve the overall management level of the water supply system.

[0135] At the city's water supply dispatch center, staff can use a three-dimensional dynamic monitoring platform to quickly locate areas with abnormal pipeline pressure and take timely control measures to ensure the stability and safety of water supply.

[0136] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0137] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A constant pressure water supply system for water, electricity, and gas systems, characterized in that: It includes a central control unit, which integrates a data acquisition and verification module, a data storage unit, an energy collaborative allocation module, a flow leakage module, a prediction and control module, and a blockchain control module; The data acquisition and verification module collects flow data from key nodes in the pipeline network and connects to the variable frequency speed control system of the water pump motor to obtain motor parameters to infer the pressure and flow data of the pipeline network. Through data fusion and data comparison, it judges data acquisition abnormalities and initiates fault investigation when abnormalities occur. The flow leakage module collects pipeline network data and water usage pattern information, uses a recurrent neural network to build a prediction model, and distinguishes between normal and abnormal flow changes. When an anomaly is detected, it extracts multi-dimensional features and uses a decision tree model to determine whether the pipeline network is leaking, thus realizing adaptive adjustment of pipeline network flow and leak detection. The energy coordination and allocation module collects multi-energy data such as water, electricity, and gas, optimizes the power source configuration of water pumps, coordinates pressure regulation, and recovers residual pressure to generate electricity; The prediction and control module collects, processes and stores multi-source data, uses technology and models to predict water and energy consumption trends in different regions and transmits the results. Based on the results, it constructs pump operation plans and establishes model strategies to simulate pump status under different operating conditions in order to optimize and adjust the pump operation plans. The blockchain control module deploys smart contracts on the Ethereum blockchain platform in the community-level water supply network to collect, process and utilize data on water demand, pump operation and pipeline structure to achieve dynamic allocation of pump output, complementary pressure regulation, alternating operation management, data security processing and network rule monitoring. The energy coordination and allocation module includes: an energy data acquisition unit, which communicates with monitoring equipment at the water, electricity, and gas production ends to collect real-time data on the generation of water, electricity, and gas, as well as pressure data from the three networks. After standardizing, encrypting, and verifying the data, it transmits the data to the data analysis and decision-making unit and the pressure coordination and control unit, respectively. The data analysis and decision-making unit, with built-in optimization algorithms and intelligent models, receives the energy generation data transmitted from the energy data acquisition unit, comprehensively considers energy costs, stability, pump operating efficiency, and overall system energy consumption factors, calculates a suitable power source combination scheme for pump operation, and transmits the scheme command to the power source switching control unit. It can also adjust the power source allocation based on the specific energy needs of the pumps. The system learns and adjusts parameters based on historical operating data and real-time feedback; the power source switching control unit, according to instructions from the data analysis and decision-making unit, controls the water pump power source switching device to achieve rapid and smooth switching between different power sources, ensuring the water pump operates under the optimal power source configuration, and is connected to the water pump power source switching device using redundant communication lines; the pressure coordination and regulation unit receives pressure data from the three networks transmitted by the energy data acquisition unit, and uses air pressure to compensate for water pressure fluctuations, and adjusts the water pump operating parameters and energy distribution strategy in a coordinated manner according to the pressure of the three networks; the energy recovery unit is equipped with a residual pressure power generation device, which detects residual pressure in the pipeline network and uses it to generate electricity, feeding the recovered electrical energy back to the electrical energy system.

2. The constant pressure water supply system for water, electricity, and gas systems according to claim 1, characterized in that: The data acquisition and verification module includes: High-precision flow sensor: Deployed at key nodes of the pipeline network to collect pipeline flow data, convert analog signals into digital signals, and transmit them to the data fusion unit through redundant communication lines; Motor parameter monitoring unit: Connects to the water pump motor frequency conversion speed control system, acquires motor current and speed parameters, uses a pressure estimation model based on motor characteristic curves and the principles of motor electromagnetics and fluid mechanics to back-calculate pipeline pressure and flow, and transmits it to the data fusion unit; Data fusion unit: Receives data feedback from high-precision flow sensors and motor parameter monitoring units, uses intelligent algorithms to fuse, verify and compare data in real time, initiates fault diagnosis when data is abnormal, and feeds back abnormal information to the central control unit. The data collected and analyzed by the data fusion unit is backed up to the data storage unit in real time.

3. The constant pressure water supply system for water, electricity, and gas systems according to claim 2, characterized in that: The motor parameter monitoring unit also monitors motor temperature and vibration parameters. When the motor parameter monitoring unit detects abnormal data, it promptly sends an alert to the data fusion unit. The data fusion unit uses a Kalman filter algorithm to fuse data from different sources.

4. The constant pressure water supply system for water, electricity, and gas systems according to claim 1, characterized in that: The flow leakage module includes: an intelligent algorithm processing unit, which collects historical flow data from the pipeline network using a high-precision flow sensor, simultaneously gathers water usage pattern correlation information, cleans the raw flow data and smooths it using methods such as moving averages, and integrates it into a structured dataset; the intelligent algorithm processing unit uses a recurrent neural network as the basic model, divides the structured dataset into training, validation, and test sets, trains the model using historical flow and water usage pattern information as input, optimizes model performance by adjusting the loss function, parameter update algorithm, and hyperparameters, and the trained model receives high-precision flow sensor data in real time, predicts the normal flow range based on real-time time-series data and water usage pattern information, and compares it with actual flow data. The flow rate and prediction range are judged with ±10% as the standard. When the intelligent algorithm processing unit detects abnormal flow rate changes, it extracts the magnitude, duration, and rate of the flow rate change, and uses a leak judgment model based on decision tree algorithm and trained with actual leak cases to determine whether there is a leak. It also combines the physical parameters of the pipeline network to assess the degree of leak. The intelligent algorithm processing unit is equipped with an alarm output interface. When a pipeline leak is detected, it promptly sends an alarm signal to the central control unit, which triggers the emergency response process. After the intelligent algorithm processing unit generates an alarm signal, the water pump operation parameter control unit adjusts the water pump operation parameters to compensate for the pressure loss caused by the leak by adjusting the flow rate, thereby maintaining a constant water supply pressure.

5. The constant pressure water supply system for water, electricity, and gas systems according to claim 1, characterized in that: The energy coordination and allocation module is equipped with an energy allocation strategy adjustment interface. Operators can manually adjust the energy allocation strategy according to actual needs through an external control terminal, and intervene in the calculation results of the data analysis and decision-making unit.

6. The constant pressure water supply system for water, electricity, and gas systems according to claim 1, characterized in that: The forecasting and control module includes: a multi-source data fusion acquisition unit, which is connected to a meteorological data interface, a geographic information system, an urban population flow monitoring system, and a regional economic activity monitoring platform, respectively. It is used to collect real-time data on weather conditions, topographic features, population flow density, commercial activity levels, and energy consumption data of water supply system equipment. The acquired data undergoes standardization and cleaning to remove outliers and noise before being categorized and stored. A water and energy consumption forecasting unit uses big data analytics and neural network models, combined with data from the multi-source data fusion acquisition unit and historical water and energy consumption data, to predict changes in water demand and energy consumption trends in different regions, and transmits the forecast results to the control and prediction unit. The control and prediction unit, based on the water demand forecast results provided by the water and energy consumption prediction unit, constructs a predictive operation plan for water pumps that includes differences in water demand across different time periods and regions, and establishes a water pump operation model strategy to simulate the water pump operation status under predicted and extreme unpredictable conditions, thereby optimizing and adjusting the water pump operation plan.

7. The constant pressure water supply system for water, electricity, and gas systems according to claim 6, characterized in that: The blockchain control module includes: a contract deployment and management unit: deploying smart contracts based on the blockchain platform in the community-level water supply network, predefining data processing, pump control, and reward / penalty rules, and monitoring and managing network operation; a water demand collection and uploading unit: smart water meters are installed at the user end, collecting, processing, and encrypting water demand data, and uploading it to the blockchain platform at set intervals; a dynamic pump output allocation unit: the system uses a particle swarm optimization algorithm to construct a multi-objective optimization model based on water demand, pump operation, and pipeline structure data on the blockchain, dynamically allocating pump output to achieve regional pressure balance and optimal energy consumption; a water pressure complementary regulation unit: the blockchain platform records pressure data from each node, smart contracts analyze pressure deviations to generate regulation commands, which are broadcast to the pump control equipment via the blockchain. After the equipment executes the commands, it provides feedback on its operating status, and the smart contracts adjust the commands accordingly to maintain constant pressure; and a pump alternating operation management unit: smart contracts formulate pump alternating operation strategies, arranging the operation sequence based on pump operating time, maintenance cycle, and water demand, recording the number of start-ups and shutdowns, issuing maintenance reminders when thresholds are reached, and interacting with the equipment maintenance management platform to optimize the strategy.

8. The constant pressure water supply system for water, electricity, and gas systems according to claim 7, characterized in that: The water pressure complementary regulation unit has an emergency regulation mode to cope with sudden changes in water usage or equipment failure. The smart water meter in the water demand acquisition and uploading module can update the data acquisition and processing algorithm through remote firmware upgrades. The particle swarm optimization algorithm treats the output allocation scheme of each water pump as a particle and searches for the optimal solution in the solution space. At the same time, combined with fuzzy control theory, the search parameters of the particle swarm are dynamically adjusted according to the water demand, water pump operation and pipeline structure data uploaded to the blockchain platform in real time. Fuzzy control theory uses fuzzy rules to fuzzify the regional pressure deviation and pressure change rate, and determines the adjustment amount of inertia weight and acceleration constant according to fuzzy inference to achieve regional pressure balance and optimal water pump energy consumption.

9. The constant pressure water supply system for water, electricity, and gas systems according to claim 1, characterized in that: It also includes a three-dimensional dynamic monitoring platform that has a two-way data connection with the central control unit. The three-dimensional dynamic monitoring platform, by accessing and integrating data from multiple modules, constructs a 3D scene of the water supply network, and displays in real time and intuitively the pipeline flow, pressure, equipment parameters and water, electricity and gas energy data information, so as to realize abnormal monitoring and early warning, prediction and control visualization, and data interaction.

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