LET YOUR DATA SPEAK! Data Analytics Strategy for Water Utilities

Transcription

1 LET YOUR DATA SPEAK! Data Analytics Strategy for Water Utilities Date: February 2018

2 Outline 2 Data Analysis Overview Data Infrastructure Database Technologies Data Sources Data Analysis Methodologies & Examples Ad-hoc analysis Real-time analysis (dashboard) Machine Learning Model-based Data Analysis Case Studies

3 Data Analysis Overview

4 Data Analysis Steps 4 Visualize Import Cleanse Transform Information Model 80% 20% Prepare Data Analyze Data

5 Three Pillars of Successful Data Analysis 5 Data Analytics Data Infrastructure W&WW Domain Knowledge

6 Data Infrastructure

7 Data Infrastructure 7 Operational Data Management System Data Collection Data Storage Data Availability VISUALIZATION ANALYSIS REPORTING OPTIMIZATION PCS/SCADA OPERATOR LOGS CMMS GIS, LIMS, & OTHERS

8 Data Infrastructure 8 Database Technology SQL vs NoSQL (not only SQL) The benefits of NoSQL database More suitable for time-series data (e.g., SCADA data) * From R for Data Science, H Wickham, 2017

9 Data Sources 9 SCADA data Computerized Maintenance Management System (CMMS) Asset data Lab data Financial data

10 Data Analysis Methodologies & Examples

11 Ad-hoc vs Real-Time Analysis 11 Ad-hoc analysis with historical data Real-time analysis with real time data Tools

12 Ad-hoc vs Real-Time Analysis 12 Real time pump control is implemented in City of Toronto & Peel Region Different technologies, but same underlining ideas Reduce energy cost through smart scheduling Utilize storage to delay pumping to time periods with lower electricity cost Reduce peak demand charges

13 Machine Learning 13 Regression

14 Machine Learning 14 Classification

15 Machine Learning 15 Clustering

16 Machine Learning 16 Deep Learning * From Deep Learning with Python, F Chollet, 2017

17 Machine Learning 17 Deep Learning Total params: 235,146

18 Case Studies

19 Ad-hoc Analysis 19 Case Study 1 City of Toronto Watermain Breaks Watermain Breaks data from City 35,465 records 26 Years: Daily entries Weather data from Environment Canada

20 Ad-hoc Analysis 20 Case Study 1 City of Toronto Watermain Breaks Demonstration Temperature correlation:

21 System Optimization 21 Case Study 2 Pumping Optimization Current operation Pump operating efficiency What improvements can be made to save energy?

22 Head (m) Pump Efficiency (%) System Optimization 22 Case Study - 2 Best Efficiency Point (BEP) Preferred Operating Region (POR) Factory Pump Curve EPANET Pump Curve MAP_PMP1 MAP_PMP2 Factory Pump Efficiency PMP1_Efficiency PMP2_Efficiency 190% 170% 150% BEP 130% 110% 90% 70% 30 50% Flow (L/s)

23 System Optimization 23 Case Study - 2 Current Operation

24 System Optimization 24 Pump Speed Controls o Strategy 1 - Ramp down pump speed on rising reservoir level o Strategy 2 - Ramp up pump speed on rising reservoir level o Strategy 3 - Fixed pump speed Duty 1 Stop WL = 6.00m Duty 2 Stop WL = 5.50m Duty 1 Start WL = 5.00m Duty 2 Start WL = 4.00m Duty 1 Pump Reservoir Flow Out to Distribution System Duty 2 Pump Pumping Station

25 System Optimization 25 Treatment of Data Hydraulic Data Level, Flow, and Pressure EPANET Matlab Pump On/Off Status, And Pump Speed

26 Speed Flow (L/s) Level (m) System Optimization 26 Pump Flow and Speed of Duty Pump 1 against Reservoir Level 6.5 Reservoir Level (m) Time (hr) 800 Duty 1 Pump Flow Time (hr) Duty 1 Pump Speed Time (hr)

27 System Optimization 27 What Can Data Tell Us? Strategy 1 Decrease pump speed on rising reservoir level Strategy 2 Increase pump speed on rising reservoir level Strategy 3 Fixed pump speed (Current practice) Volume of water being pumped (m 3 ) 75,627 71,238 75,557 Energy Intensity (kwh/m 3 water) Difference (% of energy intensity under Strategy 3) This is how much energy we can save! -6.03% -7.93% 0%

28 Let Data Speak Food for Thought 28 Establish a Value Proposition Benchmarking existing operations Improve operating efficiency and effectiveness Reduce operating and maintenance cost Improve the level of service Confirmation of improvement with new benchmarks Assist informed decision-making

29 Thank You & About Us 29 History: Incorporated in 2010 Market: Water and Wastewater Services: Multi-disciplinary Consulting Office: Richmond Hill, Ontario Municipal Client: