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Big Data Analytics in Energy & Utilities
The document discusses the transformation in the energy and utilities industry driven by big data and analytics, highlighting the increasing implementation of smart meters and customer demand for better energy insight. Organizations using big data are significantly outperforming competitors by enhancing operational efficiency, customer engagement, and regulatory compliance. Key challenges and opportunities include improving grid operations, asset management, and leveraging real-time data for decision-making and predictive analytics.
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Big Data Analytics in Energy & Utilities
- 1. © 2014 IBMCorporation Transforming Energy and Utilities through Big Data & Analytics Anders Quitzau, Innovation Executive, IBM 28. maj 2014
- 2. © 2014 IBMCorporation2 What is changing in the Energy and Utilities industry? Smart meters become mainstream The grid gets older Consumers want more control & insight into energy consumption Alternative energy enters the mix 60% of electric grid assets will need replacement in this decade In 2020, all Danish electric utilities will have smart metering infrastructure (AMI) installations Global installed wind power capacity increased by 12.4 percent to more than 318 gigawatts in 2013 The number of U.S. customers capable of accessing information on their energy use online increased from 5.4M in 2010 to 17.5M in 2012
- 3. © 2014 IBMCorporation3 To sustain growth, leaders across energy & utilities are prioritizing four imperatives… Transform the utility network Transform customer operations Improve generation performance Continually improve operational excellence
- 4. © 2014 IBMCorporation4 Big Data is not ’just’ data, there are a few new considerations Volume Data at Rest Terabytes to exabytes of existing data to process Velocity Data in Motion Streaming data, milliseconds to seconds to respond Data in Many Forms Variety Structured, unstructured, text, multimedia Veracity Data in Doubt Uncertainty due to data inconsistency & incompleteness, ambiguities, latency, deception, model approximations Value Data of Many Values Large range of data values from free (data philanthropy to high value monetization) ValueVisibility Data in the Open Open data is generally open to anyone. Which raises issues of privacy. Security and provenance Big Data ‘Big data’ is defined by IBM as any data that cannot be captured, managed and/or processed using traditional data management components and techniques Open Data
- 5. © 2014 IBMCorporation5 Big data makes a big difference Organizations using big data and analytics are up to 23xmore likely to report they are substantially outperforming their competitors than those who do not use big data and analytics Source: Analytics: The real-world use of big data, a collaborative research study by the IBM Institute for Business Value and the Saïd Business School at the University of Oxford. © IBM 2012
- 6. © 2014 IBMCorporation6 OutperformersUnderperformers Translate insight into action 54% 108% more likely Make data accessible 57% 84% more likely 54% 108% more likely Draw insights from data 26% 31% 26% Using data, outperformers excel in three key areas Source: Leading through connections, Insights from the 2012 Global Chief Executive Officer study, IBM Institute for Business Value © IBM 2012
- 7. © 2014 IBMCorporation7 Big Data & Analytics capabilities help utilities leverage data to meet the challenges of a connected world 45% Increasing consumer expectations and concerns 49% >50% of surveyed consumers with an opinion expect smart grid technologies will lower total household costs for energy use. But . . . of consumers were concerned that erroneous smart meter readings would result in overcharges By 2050, the Electric Power Research Institute estimates that the average electric bill will probably go up by about 50 percent if the smart grid is deployed. is the expected increase in the average electric bill if the smart grid is not deployed ca. 400% In the utilities industry, the number of connected devices – participants in the “Internet of things” – is growing exponentially: Compound annual growth rate, 2010-2015 Data explosion Cost and pricing pressures Data is emerging as the world’s newest resource for competitive advantage Decision-making is moving from the elite few to the empowered many As the value of data continues to grow – current systems won’t keep pace
- 8. © 2014 IBMCorporation8 Big data & analytics are transforming energy and utilities Energy and Utilities are turning knowledge into power by using big data & analytics to better understand and shape customer usage, improve service levels and availability, and detect and prevent energy theft.
- 9. © 2014 IBMCorporation9 Big data & analytics capabilities are required to address these challenges and opportunities ERP/ MRP Social Media Location Call Centers Fraud Mgmt Outage Management Regulatory Asset Management Warranty / Quality Telematics Grid Customers New/Enhanced ApplicationsAll Data Information Integration & Governance Systems Security On premise, Cloud, As a service Storage What action should I take? Decision management Landing, Exploration and Archive data zone EDW and data mart zone Operational data zone Real-time Data Processing & Analytics What is happening? Discovery and exploration Why did it happen? Reporting and analysis What could happen? Predictive analytics and modeling Deep Analytics data zone What did I learn, what’s best? Cognitive SCADA
- 10. © 2014 IBMCorporation10 Key usage patterns for big data & analytics have emerged Grid Operations Smart Metering Asset & Workforce Management
- 11. © 2014 IBMCorporation11 Grid Operations
- 12. © 2014 IBMCorporation12 Grid Operations Field Services MV & LV Grid Planning Asset Management Voltage Regulation & Protection Customer Operations Regulatory Reporting System Control • Detailed Load & voltage data • Embedded generation impacts • Load & Phase Balance • Topology & switching history • Events & alarms • Fault location • Grid conditions • Load History • Temperature & Condition • Ratings & Impedance • Voltage & PF profiles • Batteries & secondary equip • Exceptions & Excursions • Improved power quality • Fewer outages & events • Avoid manual collection • Load & voltage surveys • PQ & outage investigations • SAIDI/SAIFI • Improved risk assessment response • Lower technical and non-technical losses Big data & analytics capabilities can drive real business value from Grid Operations
- 13. © 2014 IBMCorporation13 Enhance Grid Operations Demand Forecasting Load Forecasting Distribution Mgmt Outage Mgmt Energy Trading SCADA ERP/ MRP EAM Social Location PMU AMI IBM Watson Foundations New/Enhanced Applications All Data Information Integration & Governance SystemsSystems SecuritySecurity On premise, Cloud, As a service StorageStorage What action should I take? Decision management Landing, Exploration and Archive data zone EDW and data mart zone Operational data zone Real-time Data Processing & Analytics What is happening? Discovery and exploration Why did it happen? Reporting and analysis What could happen? Predictive analytics and modeling Deep Analytics data zone What did I learn, what’s best? Cognitive Analyze data from continuous sources in real time. Import and execute predictive models. Discover and navigate through structured and unstructured data across the entire enterprise Deep analysis of energy demand and loads and the impact of distributed generation resources Master relationships and build / maintain a single view of the grid Cleanse and validate data from multiple customer or outage management systems prior to loading in the warehouse Monitor the performance and status of the grid via reports and dashboards.Increase generation capacity in response to demand Predict excessive loads on the grid before they occur High bandwidth time series data ingestion and recall Strong real-time, streaming data performance across distributed grid data
- 14. © 2014 IBMCorporation14 Big data & analytics capabilities are transforming Grid Operations Anticipate outages • Synthesized and analyzed a large stream of data from 5,500 cell relays and 2.3 million smart meters • Predict and prevent operational issues • Respond to outages more efficiently by dispatching crews to the right place at the right time How can I uncover anomalies in cell relay signals to predict and prevent power outages? Simulate energy demand • Forecasts national demand every 30 minutes for a full year in advance, versus daily in the past • 35 million load curves analyzed and modeled in near-real time How do I integrate renewable energies on the grid and forecast energy consumption ? Energy utility company in the United States Utility company in France Manage the flow of power through the grid automatically How can I manage the load capacity of the grid without relying on manual calculations ? Australian Power Company • Implemented a rules engine and advanced analytics to continually calculate the theoretical load limits of assets within the grid network • Extended asset life and subsequent deferred unnecessary capital investment via better asset load ratings.
- 15. © 2014 IBMCorporation15 Smart Metering
- 16. © 2014 IBMCorporation16 Big data and analytics capabilities drive real business value from Smart Meter data Smart Metering Grid Operations Field Service Resource Planning Customer Service / Customer Operations Regulatory Compliance Efficient Regulatory Compliance Detect Energy Loss, Theft & Fraud Improve acceptance rates for targeted offerings Improve load forecasting & demand accuracy Optimize maintenance & repair Reduce Outages & Downtime
- 17. © 2014 IBMCorporation17 Big data & analytics turns Smart Meter data into actionable insight Help customers reduce energy consumption • Used smart meter data for a customer web portal, where customers can access their personalized information and learn how much electricity • Reduced load times by more than 95 percent • Decreased query times more than 97 percent • Reduced TCO from 1.3 TB to 350 GB How can I give customers more control over their energy use ? End-to-end management of the grid • Implemented a smart meter infrastructure that provides real-time, integrated view of the grid • Will reduce demand on the grid by about 1,000 megawatts • Will reduce greenhouse gas emissions by at least 365,000 metric tons per year How can I use smart meter data to reduce energy consumption? US distributor & transmitter of electricity Large California Utility Manage the flow of power through the grid automatically How can I manage the load capacity of the grid without relying on manual calculations ? • Gathered & analyzed smart grid data representing diverse terrain, weather & demographics • 50% drop in short-term peak loads • 15% drop in overall peak loads • 10% reduction in electricity bills
- 18. © 2014 IBMCorporation18 Gain insight from Smart Meter big data Customer self- serve portals Fraud / theft protection Call Centers Outage Mgmt Billing systems Meters Grid Customers Location ERP IBM Watson Foundations Information Integration & Governance SystemsSystems SecuritySecurity On premise, Cloud, As a service StorageStorage What action should I take? Decision management Landing, Exploration and Archive data zone EDW and data mart zone Operational data zone Real-time Data Processing & Analytics What is happening? Discovery and exploration Why did it happen? Reporting and analysis What could happen? Predictive analytics and modeling Deep Analytics data zone What did I learn, what’s best? Cognitive New/Enhanced Applications All Data Collect, store and analyze up to 50,000 data points/ sec Complex query processing of historical meter usage data. Cleanse and validate data from multiple customer, billing or outage management systems prior to loading in the warehouse Master relationships and build / maintain a single view of the grid Discover and navigate through structured and unstructured data across the entire enterprise Analyze customer energy usage, detect energy theft or meter tampering Predict which customers are candidates for TOU pricing or demand / response offerings Offer TOU pricing or demand / response offerings High availability of data and analytics processing of customer preferences
- 19. © 2014 IBMCorporation19 Asset & Workforce Management
- 20. © 2014 IBMCorporation20 Asset & Workforce Management drives real business value for utilities Easy access to all documents needed to operate the assets Populate work packages with complete and accurate information Schedule maintenance based on equipment conditions, not fixed schedules Asset & Workforce Management Operate the Assets Schedule Use of the Assets Maintain the Assets Minimize planned and unplanned maintenance activity Capture changes so “As-Built” configuration is accurate Use analytics to perform Predictive Maintenance & Condition Based Maintenance Maintain accurate “As-Built” documentation Enforce business rules for asset operations
- 21. © 2014 IBMCorporation21 PMQ Capabilities Enhance Asset & Workforce Management with big data & analytics Load Forecasting Mobile workforce Asset Mgmt Outage Mgmt Warranty / Quality SCADA ERP/ MRP EAM Social Media DCS Telematics Grid Information Integration & Governance SystemsSystems SecuritySecurity On premise, Cloud, As a service StorageStorage What action should I take? Decision management Landing, Exploration and Archive data zone EDW and data mart zone Operational data zone Real-time Data Processing & Analytics What is happening? Discovery and exploration Why did it happen? Reporting and analysis What could happen? Predictive analytics and modeling Deep Analytics data zone What did I learn, what’s best? Cognitive Internetscalemessaging IBM Watson Foundations New/Enhanced Applications All Data Real-time analysis of grid / generation asset data Monitor the performance of equipment and assets during operation Predict an equipment failure and avoid an outage Recommend preventative maintenance Pre-built data schema for quality, machine and production data Define and manage the product master data Protocol conversion, message mediation & transformation of grid or power generation data Landing zone for data collected from grid assets for off-line analytics Consolidate grid data for a 360 degree view of the grid or generation plant Strong real-time, streaming data performance across distributed asset info
- 22. © 2014 IBMCorporation22 Big data & analytics is transforming Asset & Workforce Management Early failure detection • Used text mining methods for extracting insights from unstructured sources • Achieved 90% failure prediction accuracy for gas turbine compressor subsystem • Identified 11 month early warning of production and supplier issues How do I reduce unscheduled maintenance costs? Analytics Driven Mining Asset Management Performed analytics on data from trucks / mining equipment, weather, operational performance and ore price to assess asset health Estimated $3B increased profit on $30B operation • Reduced 10-day failure probability to less than 1% How can I minimize down time related to asset maintenance? Gas Turbine Manufacturer Large Mining Company Asset & Workforce Management Optimization How do I measure the risk of failure and optimize repair / replacement work? Water Utility Company • Used advanced analytics to identify potential problems based on location, time, weather and maintenance history • 25%+ increased crew utilization; 10-15% fuel savings • 30-50% savings on selected inspection and preventive maintenance
- 23. © 2014 IBMCorporation23 • Find the most compelling use- cases and the business sponsor • Enable and motivate your people • Infuse analytics into key business processes • Deploy the full range of analytics Build a culture that infuses analytics everywhere Be proactive about privacy, security and governance Invest in a big data & analytics platform How to move strategically to transform your business • To trust the insights you have to trust the facts. Big Data also requires data governance • Privacy and security to protect the data • Enable risk-aware decisions • Build towards a platform for all data and analytics • Analyze data in motion • Cultivate new partnerships and roles
- 24.