Utility Analytics, Challenges & Solutions. Session Three September 24, 2014

The Place Analytics Leaders Turn to for Answers Member.UtilityAnalytics.com Utility Analytics, Challenges & Solutions Session Three September 24, 2014

The Place Analytics Leaders Turn to for Answers Member.UtilityAnalytics.com PowerRunner Advanced Analytics: Predicting Big Data with Enterprise Analytics

PowerRunner Energy Analytics Solutions PowerRunner provides energy market participants with predictive and actionable analytics software and services that can leverage advanced meter data to support enhanced operational decision management of critical business processes

PowerRunner Predictive Analytics Solutions Historical Predictive Actionable CIS/CRM MDM/AMI GIS/AMS EMS/DMS Weather Data Market Data FORrunner Forecasting Analytics REVrunner Revenue Analytics Exec. Dashboard Scheduling Demand Mgmt. EMS/DMS Pricing/Rates General Ledger

Business Analytics Across Disparate Systems To realize value from smart grid and smart meter investments and to support corporate strategic planning, utilities need business analytics to extract, analyze and present actionable information for the entire enterprise The dynamic nature of the smart grid requires a single source of truth in data shared across multiple business units to: Manage the integration of distributed energy resources (DER) such as solar, wind and other generation assets, as well as demand response and load control programs Measure the effectiveness and equitable compensation for DERs and other demand-side management incentives Develop new rate structures to incentivize consumer behavior, such as net metering, dynamic pricing and transactive energy rates Understand how the evolution of the smart grid and changing consumer habits will impact the bottom line

Need for Information Gathering Big Data Volume By the end of 2015 more than 65 million smart meters will be deployed in the US. With over 200 billion meter reads per month, more than 2 trillion meter reads per year, utilities need big data solutions that can manage the growing volume Utilities need to plan how: To manage the data deluge To extract value from this data Data will drive operational performance Data can be leveraged to improve the bottom line source: cesi.it

Need for Data Unification Disparate System Data Advanced big data solutions will have to manage multiple data sources to assemble information in a business application Utilities need to integrate: Usage Data Customer Data Operational Data Commercial Data source: nlinews.com

Need for Accuracy Data Quality Data integrity and completeness will be integrated as part of business continuity The integrity of the future grid will be more dependent on automated data quality processes to ensure reliability and security. Utilities strive to: Ensure overall data integrity and security Utilize comparison analytics tools Interpret data inconsistencies in the meter, at the node or on a centralized server Implement scalable, enterprise solutions that address business continuity in the events of data inconsistencies

Need for Speed Distributed Processing Near real-time data retrieval has paired the convergence of information technology (IT) and operational technology (OT) Centralized and nodal IT solutions have to be able to process data efficiently to support the dynamic OT requirements of the future grid Utilities look forward to: Processing data in near real-time Processing information at the edge, the node or in central data centers Integration of real-time data with critical OT

Incumbent Information Silos Utility information systems are traditionally siloed by business units and may not provide managers and executives with the consolidated view needed to support operational and commercial decisions across the enterprise. Customer Information CIS CRM MDM AMI Power System Information SCADA DMS/EMS GIS Company Information General Ledger Annual Reports Rate Case

Utility Forecasting and Revenue Analytics Acct # 4 Acct # 5 Acct # 6 System Operations Create hourly load forecasts for systems assets, such as, transformer, circuit or substation Acct # 3 Acct # 2 Acct # 5 Acct # 4 Demand Management Forecast, measure and integrate Distributed Energy Resources (DER) by service point, system location or customer segmentation Account # 1 Account # 2 Account # 3 Account # 4 Account # 5 Account # 6 Account #n Acct # 1 Acct # 2 Acct # 4 Acct # 5 Acct # 1 Acct # 2 Acct # 5 Acct # 6 Rate Analysis Scheduling & Settlement Evaluate the cost of service for dynamic and innovative rate structures Forecasting and settlement of wholesale power and capacity requirements with the ISO/RTO Acct # 1 Acct # 2 Acct # 3 Acct # 4 Financial Reporting Accurate and detailed financial analysis to support executive planning and reporting

Energy Company Forecasting & Revenue Analytics Acct # 4 Acct # 5 Acct # 6 Shadow Settlement Hourly shadow settlement by each retail account with your wholesale delivery obligations Acct # 3 Acct # 2 Acct # 5 Acct # 4 Supply Management Manage long-term electricity and natural gas obligations by contract type (fixed, variable, green, etc.) at each delivery point Account # 1 Account # 2 Account # 3 Account # 4 Account # 5 Account # 6 Account #n Acct # 1 Acct # 2 Acct # 4 Acct # 5 Acct # 1 Acct # 2 Acct # 5 Acct # 6 Pricing/Revenue Analytics Resource Planning Forward pricing by each accounts to effectively retain margins and accurately forecast revenues Identify regional constraints and locational DERs to plan for future dynamic load requirements Acct # 1 Acct # 2 Acct # 3 Acct # 4 Customer Segmentation Segment customers by rate class, SIC code, zip code or other defined attribute to analyze load and revenue trends

Predicting Big Data with Advanced Analytics Big Data PowerRunner s forecasting and analytics solutions are architected to be scaled to meet the growing data requirements with precision and performance Disparate Systems Easily managed from a central dashboard, data from disparate internal and external sources can be integrated into PowerRunner analytics solutions to power an overall business solution Nodal Processing PowerRunner solutions can be pushed to the edge, such as in the meter to forecast load and revenue at each and every metering point Data Quality PowerRunner s data integrity functionality processes data to ensure business continuity, ensuring business solutions will not get subverted by bad data

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The Place Analytics Leaders Turn to for Answers Member.UtilityAnalytics.com Streaming Analytics in the Utility Context

Intelligent Business Operations (IBO) By integrating real-time analytics and decisioning into an organisation s transactionexecuting systems, IBO enables informed decisions to be made at speed and at scale. To provide real-time visibility, to immediately seize revenue opportunities and to continuously manage risk.

Apama Streaming Analytics from Software AG Streaming Analytics Apama Streaming Analytics is one of Software AG s platforms for delivering the vision of Intelligent Business Operations Analyze and act on fast moving, streaming data immediately

What is a Streaming Analytics platform? Software that can filter, aggregate, enrich and analyze a high throughput of data from multiple disparate live data sources and in any data format to identify simple and complex patterns to visualize business in real-time, detect urgent situations, and automate immediate actions. Forrester Research, July 2014 66% increase in the use of Streaming Analytics in the last two years Forrester Research, July 2014

Streaming Analytics helps detect and exploit Perishable Insights Driving Alerts and Streaming Analytics (Apama) Real-Time Engine Data to Dashboard (Big Memory) Visualizations and Web Data with Streaming Data (Presto) Detect Urgent Situations in Streams of Data before the moment is lost Proactively Engage customers if they are having trouble with service Intervene when an SLA is at risk of being breached Prevent Fraud before damage is done Streaming data from Engine and Web (UM)

Relationship of Streaming Analytics to Hadoop and Big Data Sift Through High Volumes of Data in Motion INGEST Sift Through Petabytes of Data at Rest Real-Time Analytics What s Happening Now Real-Time Engagement with Customers Allow Applications to make Quick Decisions Proactively Notify someone to Intervene BATCH RESULTS AND DISCOVERED PATTERNS CLOSE THE LOOP! Historical Analytics What Happened last Month Discover Patterns of Customer Behavior Analyze Lots of Data to Make Off-Line Decisions Learn the Patterns of Predictive Maintenance

The Vision and Not So Distant Future: Internet of Everything Streaming Analytics is core for Internet of Things.

Utility Application Capabilities driven by Internet of Things: Real-Time Push for Applications Proactive Detection of Patterns in Streaming Data Real Time Pricing Load Curtailment Outage & Emergency Alerts Home automation Real-Time Analytics Mashed with the World Wide Web Substation & Feeder Automation Revenue Assurance/Recovery Distributed Generation (impact/control) Customer Engagement Energy consumption & efficiency

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The Place Analytics Leaders Turn to for Answers Member.UtilityAnalytics.com Bringing Clarity to Cloud Deployment Models for Grid Analytics Franco Castaldini GE Software

What We Are Hearing We need help turning this flood of data into actionable information which our people can use Our IT resources are stretched. Between the new DMS roll out, ERP upgrade we are pressed. We re not data architects. We don t have the expertise today. Data Budget Talent * Intermap survey of 250 decision makers at medium and large companies, 2/2014

But here s what concerns us all Security and privacy Performance and latency Loss of control and flexibility Lack of maturity Regulations Hidden Costs 79% of CIOs are concerned about hidden costs * CIOs are concerned about a range of hidden costs that may only surface after things are up and running such as poor performance, or issues with service availability. - Joe McKendrick 40% themselves as "cloud-wary" cited security as their biggest impediment to adoption. * - ComputerWorld - CloudTimes * Intermap survey of 250 decision makers at medium and large companies, 2/2014

Some things we should no longer argue Core Cloud Benefits Fast Deployment Operational cost and TCO Reduced set of skills required On-demand scalability Standardized integration Proven Use Cases Sentiment analysis Mobile access Sandboxes Development and Test Big data analytics Business-driven deployments * Intermap survey of 250 decision makers at medium and large companies, 2/2014

Treating data and use cases differently Grid Domain On Premise Mission Critical Control Systems (e.g. DMS, OMS, GIS) Regulated Systems Performance, security are of highest concern Services Domain On Premise / Cloud Customer Domain Cloud Enterprise, CIS, AMI Growing footprint of cloud deployments (e.g. Workday, Salesforce) Security and privacy concerns remain Already outside the firewall Transparency and customer communication driving deeper integration Ideal cloud use cases Data Domain Cloud * Intermap survey of 250 decision makers at medium and large companies, 2/2014

An Example: Grid IQ Insight = Cloud = On Premise Visualization Analytics Data Store Data Integration

Data On-Prem, Analytics in the Cloud Utility-Specific Advantages Keeps Grid Domain On Premise Overlay approach No co-mingling of domains Safe pathway to more value Opens up benchmarking (rates, assets, etc.) Balances control with performance Cautionary Advice Beware of critical skills loss Implement governance checks on data integration layer Bandwidth costs

Thank you! Member.UtilityAnalytics.com

Thank you! Member.UtilityAnalytics.com