Water affair comprehensive integrated intelligent management platform

Abstract

The invention, which relates to the technical field of intelligent water affair management, discloses a water affair integrated intelligent management platform comprising an operation management module, a production management module, an energy consumption management module and a basic management module. The operation management module is used for monitoring water affair production conditions and enterprise conditions and counting production and marketing conditions and operation conditions; the production management module is used for collecting and counting water affair production related data and managing plant station operation; the energy consumption management module is used for monitoring, counting and analyzing energy consumption data of the water affair system; the basic management module is used for managing equipment information and realizing butt joint and data interaction with other heterogeneous systems; according to the water affair comprehensive integrated intelligent management platform provided by the invention, the whole-process intelligentization of water affair production, operation, energy consumption and emergency disposal is realized.

Description

Technical Field

[0001] This invention relates to the field of smart water management technology, and in particular to an integrated intelligent management platform for water affairs. Background Technology

[0002] With the acceleration of urbanization and the continuous expansion of water systems, the drawbacks of traditional water management models have become increasingly apparent, making it difficult to meet the demands of modern water management for refinement and intelligence. In the production and sales management process, the lack of precise quantitative methods for controlling pipeline leakage is a core pain point. Under the traditional model, the pipeline leakage rate is often estimated by the simple difference between "water supply and water sales" without establishing a standardized mathematical model. Affected by factors such as manual meter reading errors and data statistics delays, the leakage rate calculation error often exceeds 10%. At the production management level, the consumption of chemicals and the control of water quality in the water treatment process rely excessively on manual experience. The dosage of chemicals is adjusted by operators based on visual observation of water quality, without establishing a quantitative model of "chemical consumption - treated water volume." This results in a fluctuation of up to 30% in chemical consumption per unit of water volume—insufficient dosage during periods of poor water quality may lead to effluent exceeding standards, while chemical waste occurs during periods of good water quality. Furthermore, the assessment of water quality compliance rate uses a "sampling inspection + manual statistics" model, resulting in poor data timeliness. Energy management suffers from a "rough" approach. Traditional water management only tracks the total electricity consumption of water plants, lacking a quantitative analysis model for electricity consumption per thousand tons of water, thus failing to accurately pinpoint high-energy-consuming processes. The scheduling of core equipment such as pumps and fans does not consider peak-valley electricity price differences, resulting in full-load operation during peak hours (e.g., 08:00-22:00, at a price of 0.8 yuan / kWh), leading to higher electricity costs. Furthermore, energy consumption trend analysis lacks a unified deviation rate standard, failing to provide early warnings of energy consumption anomalies and missing opportunities for energy-saving optimization. Pipeline maintenance and emergency response are inefficient. Locating pipeline leaks relies on manual inspections, and a quantitative model for monitoring minimum flow rates at night has not been established. The average time to detect leaks exceeds 6 hours, during which thousands of cubic meters of water are wasted. When pipe bursts occur, valve closure decisions depend on the experience of maintenance personnel, often leading to widespread water outages due to excessive valve closures. There are technical barriers to cross-system collaboration. Water utilities typically operate heterogeneous systems such as finance, equipment, and human resources, but there is a lack of standardized data interfaces between these systems, requiring manual export and import of data for interaction.

[0003] Although smart water management platforms exist in existing technologies, they only focus on data visualization and lack standardized quantitative analysis models. They also lack peak-valley electricity pricing optimization scheduling and GIS valve shut-off analysis functions, failing to meet the refined management needs of water utilities. Therefore, there is an urgent need for a comprehensive intelligent water management platform that integrates quantitative algorithms, multi-module collaboration, and spatial analysis technologies to break through the traditional management dilemmas. Summary of the Invention

[0004] The purpose of this invention is to provide an integrated intelligent water management platform to solve the problems of fragmented data, experience-based decision-making, and lack of systematic and quantitative models in traditional water management.

[0005] To achieve the above objectives, the present invention provides an integrated intelligent management platform for water affairs, including an operation management module, a production management module, an energy consumption management module, and a basic management module; The operations management module is used to monitor water production and enterprise status, and to compile statistics on production, sales, and operations. The production management module is used to collect and analyze water production-related data and manage the operation of water plants and stations. The energy management module is used to monitor, collect and analyze energy consumption data of the water system; The basic management module is used to manage equipment information and enable interface and data exchange with other heterogeneous systems.

[0006] Preferably, the production and sales situation is statistically analyzed in the operation and management module by calculating the pipeline leakage rate, as shown in the following expression: ; in, Indicates the pipeline leakage rate. This indicates the total water supply within a specified time period. This indicates the total water sales volume within the corresponding time period.

[0007] Preferably, the operation management module evaluates operational efficiency by calculating the water fee collection rate, as shown in the following expression: ; in, Indicates the water fee collection rate. This indicates the actual amount of water fees collected. This indicates the total amount of water fees receivable (calculated based on the user's water consumption and the corresponding water price).

[0008] Preferably, the water treatment process is optimized in the production management module by evaluating chemical consumption efficiency, as shown in the following expression: ; in, This indicates the amount of reagent consumed per unit volume of water. This indicates the total consumption of a certain reagent during water treatment. This indicates the total volume of water to be treated.

[0009] Preferably, the production management module uses monitoring of the minimum flow rate at night to help locate pipeline leaks. The determination method is as follows: during the set nighttime period... Intra-regional monitoring of instantaneous flow rate within the monitoring area or pipe section And calculate the average flow rate during that period. : ; In the formula, when At that time, the system determined that there was a suspected leakage in the area and issued an alert, among which, An empirical threshold set based on historical data.

[0010] Preferably, in the production management module, the water treatment effect is evaluated based on the water quality parameter pass rate, and its mathematical expression is: ; in, Indicates the water quality compliance rate. This indicates the number of samples that meet all testing criteria (pH, COD, ammonia nitrogen, etc.). Indicates the total number of samples tested; when At that time, the system automatically analyzes the non-compliant indicators and pushes adjustment suggestions (such as increasing aeration intensity and optimizing the dosage of chemicals) to the production control system to ensure that the effluent water quality meets the standards.

[0011] Preferably, the energy management module analyzes the energy consumption data of the water system by calculating the electricity consumption per thousand tons of water, as expressed by: ; in, This indicates the electricity consumption per thousand tons of water, expressed in kWh / kt. This represents the total power consumption, expressed in kWh. This indicates the total water supply, in tons.

[0012] Preferably, the energy management module performs energy consumption trend analysis and anomaly warning by comparing the electricity consumption per thousand tons of water in different periods. The mathematical expression for deviation judgment is as follows: ; ,in, Indicates the energy consumption deviation rate. This represents the electricity consumption per thousand tons of water in the current cycle. This represents the electricity consumption per thousand tons of water, used as a benchmark.

[0013] Preferably, the energy management module supports optimized scheduling of pump groups based on peak-valley electricity prices, and its cost calculation model is based on total electricity costs. Minimize, the expression is as follows: ; At the same time, the water supply flow rate must be met. The constraint is expressed as follows: ; in, The total number of scheduling periods. The total number of water pumps, For the first Taiwan water pump Power at any moment For its operating efficiency, for Electricity price at any time For time step, The decision variable is 0-1, where 1 represents on and 0 represents off. For the first Taiwan water pump Flow rate at any moment for The water supply demand flow rate at any given time.

[0014] Preferably, when a pipe burst event occurs, the basic management module performs valve closure analysis by integrating GIS topology relationships; specifically, it seeks a minimal set of valves. This caused the pipe to burst. The group of normal users who are isolated and affected. Minimize the number of , as shown in the following expression: ; subjectto ; in, Indicates the set of valves During the valve closure analysis process in the isolated pipe network zone, the system calls the pipe network GIS topology data and outputs the valve closure sequence table and the scope of affected users within 10 seconds, ensuring that the burst pipe point is isolated while minimizing the impact of water outage.

[0015] Therefore, the present invention employs the above-mentioned integrated intelligent water management platform, which has the following beneficial effects: (1) Construct a standardized mathematical model for five core indicators: leakage rate, drug consumption efficiency, energy consumption deviation, water quality qualification rate and water fee collection rate. All calculations are based on quantifiable parameters to avoid human experience errors, enabling management decisions to shift from "qualitative judgment" to "quantitative analysis" and filling the gap in the lack of a systematic quantitative model in existing technologies. (2) Break the traditional water system “data silos” and achieve deep collaboration between operation, production, energy consumption and basic modules. For example, abnormal water quality data from the production module can trigger the energy consumption module to adjust the power of aeration equipment, and GIS data from the basic module can support the operation module to locate leaks, forming a closed loop of “data collection-analysis-decision-execution” to improve management efficiency. (3) The valve shut-off optimization algorithm for burst pipes combines GIS topology with mathematical optimization to achieve the goal of "minimizing the number of affected users"; the peak-valley pump group scheduling is based on a mixed integer programming model to minimize electricity costs while meeting water supply demand, thus solving the problems of extensive emergency response and lack of scheduling optimization in the existing technology.

[0016] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0017] Figure 1 This is an overall architecture diagram of a comprehensive intelligent water management platform according to the present invention; Figure 2 This is a schematic diagram of the platform interface for operation management according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the platform interface for energy management according to an embodiment of the present invention. Detailed Implementation

[0018] The following detailed description of embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0019] Please see Figures 1-3 A comprehensive intelligent water management platform is proposed, comprising an operation management module, a production management module, an energy consumption management module, and a basic management module. Before implementation, hardware deployment and software configuration are required, specifically: Hardware deployment: Install 450 flow sensors and 380 pressure sensors at key nodes of the water supply network; install 15 sets of online water quality monitoring equipment and 120 smart meters at each water plant; deploy 2 GIS servers to achieve full data collection from the network and water plants; Software configuration: Input basic parameters (such as peak-valley electricity prices, water quality standards, and chemical consumption thresholds) into the platform; debug the algorithms of each module (such as leakage rate calculation and pump group scheduling optimization); and develop data interfaces with the financial system (Kingdee ERP) and the equipment management system (SAP).

[0020] The operations management module is responsible for production and sales statistics and operational efficiency assessment. Its core functions are pipeline leakage rate calculation and water fee collection rate statistics, providing quantitative data support for business decisions. Specifically, the production and sales situation is statistically analyzed by calculating the pipeline leakage rate. Based on the difference between water supply and sales, a standardized leakage rate model is constructed to accurately quantify the degree of pipeline leakage and avoid errors from manual estimation. The expression is as follows: ; in, Indicates the pipeline leakage rate. This indicates the total water supply within a specified time period. This represents the total water sales volume within the corresponding time period. The specific steps are as follows: S1, Data Collection: Automatically collect water supply data from each water plant (from the production management module) and water sales data from each region (from the user's smart water meter terminal) at 00:00 every day; S2, Data Cleaning: Remove abnormal data (such as water supply of 0 or water sales exceeding a reasonable range); S3, Leakage Rate Calculation: Substitute into the formula to calculate the daily leakage rate for each region and generate a monthly leakage rate report; S4, Anomaly Warning: When L>15% (a customizable threshold), the system issues a leakage anomaly warning, triggering the leak investigation process.

[0021] Operating efficiency is assessed by calculating the water fee collection rate, as shown in the following expression: ; in, Indicates the water fee collection rate. This indicates the actual amount of water fees collected. This indicates the total amount of water fees receivable (calculated based on the user's water consumption and the corresponding water price).

[0022] The production management module focuses on water treatment process optimization and water quality control, including three major functions: chemical consumption efficiency assessment, nighttime minimum flow monitoring, and water quality qualification rate calculation, to achieve quantitative management of the entire production process. Among them, the water treatment process is optimized by evaluating chemical consumption efficiency, as expressed below: ; in, This indicates the amount of reagent consumed per unit volume of water. This indicates the total consumption of a certain reagent during water treatment. This indicates the corresponding total treated water volume; the specific steps are as follows: S1, Real-time data acquisition: Collect the chemical consumption through the chemical dosing pump flow meter and the treated water volume through the water plant inlet flow meter, with a data acquisition frequency of 1 time / minute; S2, Data accumulation: Accumulate the chemical consumption and treated water volume every hour to calculate the hourly unit chemical consumption; S3, Optimization and adjustment: When When the dosage exceeds the standard range (e.g., 0.8-1.2 kg / ton of polyaluminum chloride), the system automatically adjusts the frequency of the reagent dosing pump; if >1.2kg / ton, reduce pump frequency and dosage; if <0.8kg / ton, increase pump frequency and dosage; S4, Effect feedback: After adjustment, continuously monitor water quality indicators (such as turbidity) to ensure water quality meets standards.

[0023] Monitoring the minimum flow rate at night can help locate pipeline leaks. The determination method is as follows: during a set nighttime period... Intra-regional monitoring of instantaneous flow rate within the monitoring area or pipe section And calculate the average flow rate during that period. : ; In the formula, when At that time, the system determined that there was a suspected leakage in the area and issued an alert, among which, An empirical threshold set based on historical data.

[0024] The mathematical expression for evaluating water treatment effectiveness by assessing the pass rate of water quality parameters is: ; in, Indicates the water quality compliance rate. This indicates the number of samples that meet all testing criteria (pH, COD, ammonia nitrogen, etc.). Indicates the total number of samples tested; when At that time, the system automatically analyzes the non-compliant indicators and pushes adjustment suggestions (such as increasing aeration intensity and optimizing the dosage of chemicals) to the production control system to ensure that the effluent water quality meets the standards.

[0025] The energy management module aims to achieve refined control over energy consumption by calculating the electricity consumption per thousand tons of water, analyzing energy consumption deviation rates, and scheduling pump groups based on peak and off-peak electricity prices to reduce the energy costs of the water system. Among them, the energy consumption data of the water system is analyzed by calculating the electricity consumption per thousand tons of water, and the expression is: ; in, This indicates the electricity consumption per thousand tons of water, expressed in kWh / kt. This represents the total power consumption, expressed in kWh. This represents the corresponding total water supply, in tons. The specific process is as follows: S1, Data Acquisition: Total power consumption of each water plant and pumping station is collected via smart meters, and total water supply is collected via flow meters in the water supply network. Data acquisition frequency is once per hour; S2, Calculation and Statistics: Daily calculation of power consumption per thousand tons of water for each water plant and pumping station is performed, generating an energy consumption ranking table; S3, Energy Consumption Diagnosis: [Further details needed for accurate translation] Diagnose the top 20% of units (e.g., a pumping station with a power consumption of 850 kWh / kt per thousand tons of water, far exceeding the average level of 600 kWh / kt) to identify equipment malfunctions (e.g., pump impeller wear) and unreasonable operating parameters (e.g., excessive pump head); S4, Optimization and Improvement: Develop improvement plans based on the diagnostic results, such as replacing worn impellers and adjusting pump operating conditions.

[0026] The energy management module performs energy consumption trend analysis and anomaly warning by comparing the electricity consumption per thousand tons of water in different periods. The mathematical expression for deviation judgment is as follows: ; in, Indicates the energy consumption deviation rate. This represents the electricity consumption per thousand tons of water in the current cycle. This represents the baseline energy consumption per thousand tons of water. In practice: S1. Baseline Setting: Set the baseline energy consumption per thousand tons of water for each month at the beginning of each year; S2. Deviation Calculation: Calculate the energy consumption deviation rate for the previous month before the 5th of each month; S3. Anomaly Judgment: When |δ|>10%, it is judged as an energy consumption anomaly; if δ>10%, it indicates an increase in energy consumption; if δ<-10%, it is necessary to confirm whether there is data anomaly or excessive energy saving by equipment affecting water supply; S4. Cause Investigation: For abnormal increases in energy consumption, investigate the equipment operating status (e.g., whether the equipment is running under no-load), pipeline resistance (e.g., whether pipeline blockage leads to increased pump energy consumption), etc.

[0027] The energy management module supports optimized scheduling of pump units based on peak-valley electricity prices, and its cost calculation model is based on total electricity costs. Minimize, the expression is as follows: ; At the same time, the water supply flow rate must be met. The constraint is expressed as follows: ; in, The total number of scheduling periods. The total number of water pumps, For the first Taiwan water pump Power at any moment For its operating efficiency, for Electricity prices at different times (peak hour high electricity price, such as 08:00-22:00 is 0.8 yuan / kWh; off-peak hour low electricity price, such as 22:00-08:00 the next day is 0.3 yuan / kWh). For time step, The decision variable is 0-1, where 1 represents on and 0 represents off. For the first Taiwan water pump Flow rate at any moment for The water supply demand flow rate at any given time. The specific implementation process is as follows: S1, Data Collection and Forecasting: Collect peak and off-peak electricity price data for the next day at 18:00 every day (obtained from the power grid system), combine it with water consumption data for the same period of the past 7 days, and use the ARIMA model to predict the water supply demand flow rate for each time period of the next 24 hours. S2. Model Building: Substitute parameters such as pump power, efficiency, electricity price, and predicted flow rate into the optimization model to clarify the objective function and constraints. S3. Solution Optimization: Use a mixed integer programming algorithm (such as branch and bound) to solve the model, determine the set of pumps to be turned on in each time period, and solve the problem in ≤30 seconds. S4. Scheme Output: Generate the pump group scheduling plan for the next day, specifying the pump number and running time for each time period, and push it to the pump station control system and the mobile terminal of maintenance personnel. S5. Real-time Adjustment: During operation, if the actual water supply demand deviates from the prediction by more than 10%, the system automatically re-solves the model and adjusts the scheduling scheme.

[0028] The basic management module is responsible for equipment information management, pipeline network GIS data maintenance, and cross-system data interaction. It integrates a burst valve closure optimization algorithm to improve emergency response efficiency. When a burst event occurs, the basic management module performs valve closure analysis by integrating GIS topology relationships; specifically, it seeks the minimum set of valves. This caused the pipe to burst. The group of normal users who were isolated (located by abnormal data from pressure sensors) and affected. Minimize the number of , as shown in the following expression: ; subjectto ; in, Indicates the set of valves In the isolated pipe network zone, during valve closure analysis, the system calls the pipe network GIS topology data and outputs the valve closure sequence list and the range of affected users within 10 seconds, ensuring isolation of the burst point while minimizing the impact of water outages. Specifically, the process is as follows: S1, Burst Location: When the pressure sensor detects a sudden pressure drop (e.g., a pressure decrease of 0.2 MPa within 10 minutes), combined with data from adjacent sensors, the burst point is initially located. S2. Topology Analysis: The system automatically calls the pipeline network GIS topology data to identify the pipeline zone where the burst point is located and the associated valves; S3. Optimization Calculation: A greedy algorithm is used to solve the optimization problem, selecting the set of valves that can isolate the burst point and minimize the number of affected users. Calculation time ≤ 10 seconds; S4, Solution output: Generate a valve closing sequence table (e.g., close the main pipe valve v1 first, then the branch pipe valves v3 and v5), mark the affected user range on the GIS map, and push it to the mobile terminal of the operation and maintenance personnel; S5, Handling feedback: After the operation and maintenance personnel close the valves according to the solution, the system monitors the pipeline pressure recovery and confirms that the burst point has been isolated.

[0029] Therefore, this invention employs the aforementioned integrated intelligent water management platform, comprising four core modules: operation management, production management, energy consumption management, and basic management. It quantifies key indicators such as pipeline leakage rate, chemical consumption efficiency, and electricity consumption per thousand tons of water through standardized mathematical models. Combined with GIS topology analysis and peak-valley electricity pricing optimization algorithms, it achieves intelligent management of the entire process of water production, operation, energy consumption, and emergency response. This effectively solves the problems of fragmented data and experience-based decision-making in traditional water management, significantly improving the operational efficiency and economic benefits of water companies.

[0030] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A comprehensive intelligent management platform for water affairs, characterized in that: It includes an operations management module, a production management module, an energy consumption management module, and a basic management module; The operations management module is used to monitor water production and enterprise status, and to compile statistics on production, sales, and operations. The production management module is used to collect and analyze water production-related data and manage the operation of water plants and stations. The energy management module is used to monitor, collect and analyze energy consumption data of the water system; The basic management module is used to manage equipment information and enable interface and data exchange with other heterogeneous systems.

2. The integrated intelligent management platform for water affairs according to claim 1, characterized in that: The operations management module calculates the pipeline leakage rate to statistically analyze production and sales, using the following expression: ； in, Indicates the pipeline leakage rate. This indicates the total water supply within a specified time period. This indicates the total water sales volume within the corresponding time period.

3. The integrated intelligent management platform for water affairs according to claim 2, characterized in that: The operations management module assesses operational efficiency by calculating the water fee collection rate, as shown in the following expression: ； in, Indicates the water fee collection rate. This indicates the actual amount of water fees collected. This indicates the total amount of water fees receivable.

4. The integrated intelligent management platform for water affairs according to claim 3, characterized in that: The production management module optimizes the water treatment process by evaluating chemical consumption efficiency, as shown in the following expression: ； in, This indicates the amount of reagent consumed per unit volume of water. This indicates the total consumption of a certain reagent during water treatment. This indicates the total volume of water to be treated.

5. The integrated intelligent management platform for water affairs according to claim 4, characterized in that: The production management module uses monitoring of the minimum flow rate at night to help locate pipeline leaks. The determination method is as follows: during the set nighttime period... Intra-regional monitoring of instantaneous flow rate within the monitoring area or pipe section And calculate the average flow rate during that period. : ； In the formula, when At that time, the system determined that there was a suspected leakage in the area and issued an alert, among which, An empirical threshold set based on historical data.

6. The integrated intelligent management platform for water affairs according to claim 5, characterized in that: In the production management module, the water treatment effect is evaluated based on the pass rate of water quality parameters. The mathematical expression for this evaluation is: ； in, Indicates the water quality compliance rate. This indicates the number of samples that passed all testing indicators. Indicates the total number of samples tested; when At that time, the system automatically analyzes the non-compliant indicators and pushes adjustment suggestions to the production control system to ensure that the effluent water quality meets the standards.

7. The integrated intelligent management platform for water affairs according to claim 6, characterized in that: The energy management module analyzes the energy consumption data of the water system by calculating the electricity consumption per thousand tons of water. The expression is: ； in, This indicates the electricity consumption per thousand tons of water, expressed in kWh / kt. This represents the total power consumption, expressed in kWh. This indicates the total water supply, in tons.

8. The integrated intelligent management platform for water affairs according to claim 7, characterized in that: The energy management module performs energy consumption trend analysis and anomaly warning by comparing the electricity consumption per thousand tons of water in different periods. The mathematical expression for deviation judgment is as follows: ； in, Indicates the energy consumption deviation rate. This represents the electricity consumption per thousand tons of water in the current cycle. This represents the electricity consumption per thousand tons of water, used as a benchmark.

9. The integrated intelligent management platform for water affairs according to claim 8, characterized in that: The energy management module supports optimized scheduling of pump units based on peak-valley electricity prices, and its cost calculation model is based on total electricity costs. Minimize, the expression is as follows: ； At the same time, the water supply flow rate must be met. The constraint is expressed as follows: ； in, The total number of scheduling periods. The total number of water pumps, For the first Taiwan water pump Power at any moment For its operating efficiency, for Electricity price at any time For time step, The decision variable is 0-1, where 1 represents on and 0 represents off. For the first Taiwan water pump Flow rate at any moment for The water supply demand flow rate at any given time.

10. The integrated intelligent management platform for water affairs according to claim 9, characterized in that: When a pipe burst occurs, the basic management module performs valve closure analysis by integrating GIS topology relationships; specifically, it seeks a minimal set of valves. This caused the pipe to burst. The group of normal users who are isolated and affected Minimize the number of , as shown in the following expression: ； subjectto ; in, Indicates the set of valves During the valve closure analysis process in the isolated pipe network zone, the system calls the pipe network GIS topology data and outputs the valve closure sequence table and the scope of affected users within 10 seconds, ensuring that the burst pipe point is isolated while minimizing the impact of water outage.

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