🚨 Backwash Time: AI Technology Optimizing Water Treatment Plant Efficiency

Today Korean Social News | 2025.07.10

📌 AI Water Treatment Plant Expected to Save 9.2 Billion Won Annually Through Power Efficiency

💬 Korea Water Resources Corporation's AI system at Hwaseong AI Water Treatment Plant analyzes water levels and amounts in filter beds to find the best backwash times. By doing backwash work when electricity rates are lowest, they save on power costs and expect to save about 9.2 billion won annually. If this technology becomes an international standard, it could be the basis for AI water treatment plants worldwide, proving the excellence of Korean technology.

Summary

• Backwash time is the cleaning time for filters in water treatment plants.
• AI technology schedules backwash work during the lowest electricity rate periods.
• Smart water treatment plant technology greatly reduces operating costs and increases efficiency.

1️⃣ Definition

Backwash time means the time when water treatment plants clean their filters by reversing the water flow direction for cleaning work. Simply put, it's the time to clean the filters that make clean water.

Water treatment plants use filter beds (filters) to make water clean. Over time, dirt builds up in these filters. When this happens, backwash (reverse cleaning) work must be done to clean the filters. When to do this work is called backwash time.

💡 Why is this important?

• It's essential for water treatment plant operations to supply clean water.
• This work uses a lot of electricity, so choosing the best time is important.
• AI technology optimization can save huge amounts of money.
• It's directly connected to stable water supply, making it key technology.

2️⃣ Backwash Time Principles and AI Optimization Technology

📕 Basic Principles of Backwash Work

• Backwash work is a core process in water treatment plant operations. The main principles are:

  • During normal operation, water flows from top to bottom through filter beds, removing dirt.
  • Over time, dirt builds up on the filter surface and inside, making filtering less effective.
  • During backwash, water flow is reversed, shooting strong water streams from bottom to top.
  • This process removes dirt built up in the filters, restoring original filtering performance.
  • Backwash work uses large amounts of water and electricity, making it energy-intensive.

• Traditional backwash timing methods had limitations. Main problems were:

  • Previously, backwash work was done at set time intervals or simple standards.
  • Cleaning was done uniformly regardless of actual filter condition, making it inefficient.
  • Work was done randomly even during high electricity rate periods, costing a lot.
  • Problems occurred from energy waste due to excessive backwashing or poor filtering from insufficient backwashing.

📕 Smart Backwash Time Optimization Using AI Technology

• AI analyzes various data to determine optimal timing. Main analysis factors are:

  • Real-time operational data like water amounts, levels, and pressure in filter beds are analyzed comprehensively.
  • Prediction models are built considering water quality changes, inflow variations, and seasonal factors.
  • Past operational data and patterns are learned to find optimal backwash cycles.
  • Electricity rate systems are reflected to select the lowest cost time periods.
  • Water supply demand patterns are considered to minimize service interruptions.

• Economic effects and operational efficiency are greatly improved. Main improvement effects are:

  • Hwaseong AI Water Treatment Plant expects annual electricity cost savings of about 9.2 billion won.
  • Unnecessary backwash work is reduced, greatly saving water usage.
  • Filter bed lifespan is extended, reducing replacement and maintenance costs.
  • More accurate timing for cleaning improves water quality stability.
  • 24-hour unmanned operation becomes possible, saving labor costs.

Main Challenges of AI Backwash Time Optimization

1. System Stability: Need to secure safe backup operation methods when AI systems fail
2. Data Quality: High-quality sensor data is important for accurate AI decisions
3. Technology Standardization: Need to establish international standards for technology compatibility and spread
4. Expert Personnel: Training experts to operate and manage AI systems
5. Initial Investment: High initial costs for introducing AI systems

3️⃣ Domestic and International Smart Water Treatment Plant Technology Trends

✅ Development of Domestic Smart Water Treatment Plant Technology

• Korea has world-class smart water treatment plant technology. Main status:

  • Korea Water Resources Corporation's Hwaseong AI Water Treatment Plant is noted as the world's first fully unmanned AI water treatment plant.
  • All stages of the water treatment process are automated through real-time data analysis and machine learning.
  • Comprehensive AI management systems are built for water quality prediction, chemical dosing optimization, and preventive equipment maintenance.
  • K-water's technology is expected to be adopted as an international standard by ISO.
  • Several overseas countries are already inquiring about introducing Korea's smart water treatment plant technology.

• Nationwide water treatment plant smart transformation is accelerating. Main progress:

  • Plans to complete AI technology introduction to major water treatment plants nationwide by 2024.
  • Operational efficiency is being improved through digital transformation (DX) of existing water treatment plants.
  • Standardized AI solutions applicable to small and medium-sized water treatment plants are being developed.
  • The government is investing large budgets for smart water supply construction.

✅ Comparison with Overseas Smart Water Treatment Plant Technology

• Advanced countries are also actively investing in water treatment plant automation. Main examples:

  • Singapore introduced AI-based operation systems at NEWater plants.
  • Netherlands operates smart water management systems using IoT and big data.
  • Germany applies Industry 4.0 technology to water treatment plant operations to increase efficiency.
  • The US developed water quality prediction systems and automatic control technology using machine learning.

• Korean technology's competitiveness and differentiation factors are clear. Main features:

  • Automation technology enabling fully unmanned operation is a world first.
  • It's a comprehensive system that manages detailed operational elements like backwash time optimization with AI.
  • It shows excellent performance in energy efficiency.
  • Technology optimized for Asian region environments and conditions, advantageous for overseas expansion.
  • Excellent cost-effectiveness, applicable even to developing countries.

4️⃣ Related Term Explanations

🔎 Filter Bed

• Filter beds are filter facilities that make water clean in water treatment plants.
• Filter beds are facilities that act as filters installed to remove impurities from raw water (water before treatment) in water treatment plants. Think of them as giant filters made by layering sand, gravel, activated carbon and other filtering materials.
• Filter bed structure and functions include: First, fine sand layers at the top filter out tiny impurities. Second, medium-sized sand and gravel layers in the middle remove medium-sized impurities. Third, coarse gravel layers at the bottom facilitate smooth water flow and filter large impurities. Fourth, activated carbon layers improve smell and taste while removing chemicals.
• Filter beds accumulate dirt with continuous use, reducing performance, so they need regular backwash (reverse cleaning) work for cleaning. Optimizing backwash time becomes key to water treatment plant operational efficiency.

🔎 Smart Water Grid

• Smart water grid is an intelligent water supply management system using ICT technology.
• Smart water grid means an intelligent water management system that uses information and communication technology (ICT) to monitor and optimize the entire process from water intake to treatment, transmission, and distribution in real-time. It applies the smart grid concept from the power sector to water supply.
• Main components of smart water grid include: First, real-time water quality monitoring sensors and IoT devices. Second, demand prediction and supply optimization systems using big data and AI. Third, smart meters and pressure management systems for leak detection and prevention. Fourth, automatic control and alarm systems for emergency response.
• Smart water grid can achieve effects like minimizing water loss, improving energy efficiency, securing water quality safety, and reducing operating costs. Backwash time optimization is also one of the core functions of such smart water grids.

🔎 Water Treatment Process

• Water treatment process is a series of steps that turn raw water into safe tap water.
• Water treatment process means a series of treatment steps to turn raw water taken from rivers or dams into tap water that can be safely used at home. Impurities are removed and water quality is improved through multiple stages of physical, chemical, and biological treatment.
• Main stages of water treatment process include: First, intake stage brings water from rivers or dams to treatment plants. Second, sedimentation stage adds chemicals to settle large impurities. Third, filtration stage filters tiny impurities through filter beds. Fourth, disinfection stage adds chlorine to kill bacteria. Fifth, distribution stage supplies cleaned water to each home.
• Water quality testing and management occur at each stage, and especially backwash time management in the filtration stage directly affects the efficiency and water quality of the entire process. Recently, AI technology is being introduced to optimize and automate each process.

5️⃣ Frequently Asked Questions (FAQ)

Q: If AI optimizes backwash time, are there no problems with water quality safety?

A: AI backwash time optimization actually works to improve water quality safety. AI systems can monitor water quality data in real-time and detect early signs of declining filtration performance, performing backwash work at more accurate times than the existing method of cleaning at set time intervals. Also, several safety measures are in place. First, if water quality goes beyond standards, alarms sound immediately and backwash work starts automatically. Second, if AI systems have problems, they automatically switch to existing manual operation methods. Third, water quality changes are continuously tracked through 24-hour real-time monitoring. Fourth, double safety nets are built through regular water quality testing and system inspections. Actually, at Hwaseong AI Water Treatment Plant, water quality has been maintained more stably since AI introduction, with significantly fewer cases of exceeding water quality standards compared to before.

Q: Can this AI technology be applied to other water treatment plants?

A: Yes, it can be fully applied to other water treatment plants and expansion is actually happening. However, introduction methods and scope may differ depending on the scale and facility status of water treatment plants. For large-scale water treatment plants, fully unmanned automation systems like Hwaseong AI Water Treatment Plant can be built, with very high return on investment. For small and medium-sized water treatment plants, gradual introduction focusing on core functions is possible, and cost burden can be reduced through standardized AI solutions. Several conditions are needed to introduce AI technology to existing water treatment plants. First, sufficient sensors and measuring equipment must be installed. Second, stable communication infrastructure and data collection systems must be built. Third, expert personnel to operate AI systems must be secured. Korea Water Resources Corporation plans to complete AI technology introduction to major water treatment plants nationwide by 2024, and is also developing package-type solutions for small and medium water treatment plants. Also, overseas expansion is being actively pursued to spread Korea's smart water treatment plant technology worldwide.