Successfully reported this slideshow.
Your SlideShare is downloading. ×

Data Con LA 2022 - Pre-recorded - Data Science in water utility industry

Data Con LA 2022 - Pre-recorded - Data Science in water utility industry

Jay Kim, Data Scientist at Golden State Water Company
Data 4 Good
utilize SCADA data and monitoring in real time Water utilities have real time SCADA data in all the water plants and facilities. It is challenging to get the large amount SCADA data and make use of them. * forecasting chemical concentrations in water in advance For water quality, water engineers should know how chemicals concentrations in water are changing. By knowing how the concentrations are changing, they can make right decisions on what to do to make water quality good by optimizing their operations of water quality. For example, by knowing chlorine, nitrite concentrations in advance they can decide when to flush the water pipelines again next. By doing flushing in right time just right amount, they can save costs and labors as well as efficiently operating water quality. * optimize asset spending allocations to spend using machine learning throughout given years. in regulated water utilities, budgets are decided every 3 years by investors. Given budgets and assets should be well allocated to spend so that the given budgets and assets are all well used when the 3 years end. It should not be spent too little or too much. By using machine learning, the optimal asset spending allocation is efficiently decided. Based on the information, project managers and general managers can spend right amount budgets in each month and hit the target in earning test when the 3 years end. * forecasting water supply is for predicting how much water should be purchased for shortage of water or drought. In Southern California, it is very important to forecast how much water will be supplied by producing the water because oftentimes, drought comes. If too little water is supplied, water utilities company purchase the shortage from different areas' water utilities companies. To set up the budget and purchase right amount of water, it is very important to forecast water supply by water production of the water utilities company. By applying machine learning, the water supply can be forecasted. * by forecasting water depth change in wells, engineers can know which wells will dry out by drought. By applying machine learning, the water depth of the wells are forecasted and the wells that will be dry are identified.

Jay Kim, Data Scientist at Golden State Water Company
Data 4 Good
utilize SCADA data and monitoring in real time Water utilities have real time SCADA data in all the water plants and facilities. It is challenging to get the large amount SCADA data and make use of them. * forecasting chemical concentrations in water in advance For water quality, water engineers should know how chemicals concentrations in water are changing. By knowing how the concentrations are changing, they can make right decisions on what to do to make water quality good by optimizing their operations of water quality. For example, by knowing chlorine, nitrite concentrations in advance they can decide when to flush the water pipelines again next. By doing flushing in right time just right amount, they can save costs and labors as well as efficiently operating water quality. * optimize asset spending allocations to spend using machine learning throughout given years. in regulated water utilities, budgets are decided every 3 years by investors. Given budgets and assets should be well allocated to spend so that the given budgets and assets are all well used when the 3 years end. It should not be spent too little or too much. By using machine learning, the optimal asset spending allocation is efficiently decided. Based on the information, project managers and general managers can spend right amount budgets in each month and hit the target in earning test when the 3 years end. * forecasting water supply is for predicting how much water should be purchased for shortage of water or drought. In Southern California, it is very important to forecast how much water will be supplied by producing the water because oftentimes, drought comes. If too little water is supplied, water utilities company purchase the shortage from different areas' water utilities companies. To set up the budget and purchase right amount of water, it is very important to forecast water supply by water production of the water utilities company. By applying machine learning, the water supply can be forecasted. * by forecasting water depth change in wells, engineers can know which wells will dry out by drought. By applying machine learning, the water depth of the wells are forecasted and the wells that will be dry are identified.

More Related Content

More from Data Con LA

Data Con LA 2022 - Pre-recorded - Data Science in water utility industry

  1. 1. DATA SCIENCE IN WATER UTILITY INDUSTRY WATER UTILITY DATA SCIENTIST JAY KIM Golden State Water Company
  2. 2. WATER IS KEY ELEMENT TO ORIGIN OF LIVES. NO ONE CAN LIVE WITHOUT WATER Composed Transfer Temperature Why Water is important
  3. 3. WATER IS ORIGIN AND SOURCE OF LIVES  The discovery: Water vapor in the atmosphere of planet TOI-674 b.  Key facts: This recently discovered planet, a bit bigger than Neptune and orbiting a red-dwarf star about 150 light-years away, places it in an exclusive club: exoplanets, or planets around other stars, known to have water vapor in their atmospheres. Many questions remain, such as how much water vapor its atmosphere holds. But TOI-674 b’s atmosphere is far easier to observe than those of many exoplanets, making it a prime target for deeper investigation. Discovery Alert: Water Vapor Detected on a 'Super Neptune' Earth is the only planet where lives exist. Our planet is unique for many reasons, but its available water and oxygen are two defining features. Water covers roughly 71% of Earth's surface, with most of that water located in our planet's oceans. About a fifth of earth's atmosphere consists of oxygen, produced by plants.
  4. 4. UTILITY INDUSTRIES - Largely, Water, Gas and Electricity Water : Golden State Water Company, Gas : SoCalGas, Electricity: Southern California Edison Water Gas Electricity
  5. 5. AREAS DEALT IN WATER UTILITY INDUSTRY hydrology environmental Science chemistry climatology geophysics
  6. 6. REGULATED WATER UTILITY COMPANY  Strategic investment in water systems.  Safe and reliable water.  Unparalleled expertise.  Improving local economies.  Environmental stewardship.  Committed to safety and security.  Additional regulatory oversight.
  7. 7. PROBLEMS THAT CAN BE TACKLED BY DATA SCIENCE IN WATER UTILITY INDUSTRY  Drought forecasting  Flushing forecasting (when to flush)  Filter replacement forecasting  Water Leak Detection  Water demand forecasting  Automation
  8. 8. DATA AVAILABLE IN WATER UTILITIES  SCADA data  Customer data  Water production data  Water quality data  GIS data  Streamline data  Runoff, rainfall, temperature, pressure etc.  Government data (EPA, USGS, NOAA etc)
  9. 9. CONCLUSION / CHALLENGE Water utilities have no shortage of data. However, getting values out of the data help to reduce costs, drive efficiency as well as optimizing processes. By applying data science and AI in the water utilities data, previously unsolved problems in water quality, water supply and asset management are resolved. However, the people's mind not trying to change but to conserve what they have done makes difficult to adopt data science into the business since data science itself is all about trying new things, innovations and changes. By showing more advantages by actions from data science in businesses, I believe we can digitalize our old methods and systems to AI and data driven method
  10. 10. DATA SCIENTIST JAY KIM jay.kim07@yahoo.com

×