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  • SAS Real Time Windfarm Analytics Real time decisioning that accelerates time to value with AI/ML

    SAS and Cisco solutions designed to collect streaming data from wind turbines and windfarms

    Kumar Thangamuthu Principal Technical Architect, SAS Institute

  • Copyright © SAS Inst itute Inc. A l l r ights reserved.

    #1 AI and Advanced

    Analytics Software Platform

    IDC 2019

  • Real Time WindFarm Analytics

    • 25 Wind Farms in 5 Continents

    • 674 Wind Turbines with geolocation

    • ~ 15 Main Kpi’s (Production & Operational)

    • 5 different tags with different latency

    363,243,806 data records

  • Real Time Wind Farm Analytics Use Case Definition

    • Collecting streaming data from wind turbines and windfarms

    • Analyze, collect and distribute sensor data in real-time and alert possible issues

    • Intuitive visual exploration of near real-time and historical Business KPI’s

    • Real-time streaming report

  • Solution Overview Real Time Wind Farm Analytics

    OSIsoft PI Historian

    SQL Server

    Analyses at Rest

    Production KPI’s

    Status Reports

    Analyses in Stream

    Alarms

    Streaming Report

    Near Real Time Processing

    Real Time Processing

    Tags + Reference Data + Business Rules

    Tags + Reference Data + Business Rules

  • Main KPI’s

  • Data Trends

  • Power Curve & Load Factor Distributor

  • Real Time WindFarm Analytics Key TakeAways

    Real Time Monitoring

    Proven and Integrated Solution

    Scalable & Flexible & User-Friendly Solution

  • Cisco Kinetic IoT Platform w/ SAS IoT Analytics Bringing Distributed Services Architecture (DSA) to Scale IoT Securely

    Edge Enterprise Data Center (EDC)

    Data: power, frequency, voltage, current, phasor angle,…

    Cisco Kinetic EFM

    Cisco 829 ISR

    SAS ESP (Edge)

    Cisco Kinetic

    Powered with Cisco Kinetic DSLink for SAS ESP (Edge) | In alignment to Distributed Services Architecture (DSA), http://iot-dsa.org/

    Cisco EDC Infrastructure

    SAS Event Stream

    Manager

    SAS ESP

    Streamviewer

    SAS ESP Server

    Streaming Analytics Device Management

    ESP Model

    updates

    SAS Visual Data Mining and

    Machine Learning

    SAS Visual Analytics

    Cisco EFM Dataflow

    Editor

    EFM Dataflow updates

    ESP Streams

    ESP Model

    updates

    ESP Version updates

    EFM Dataflow updates

    SAS ESP Studio

    SAS Visual Statistics

    EFM = Edge & Fog Processing Module, for IoT Edge Processing ESP = Event Stream Processing , for IoT Edge and Cloud Analytics

    Enables enterprises to quickly collect, process, and analyze massive amounts of data in real-time, both at the network edge and in the enterprise data center – at scale, distributed, and securely

    http://iot-dsa.org/

  • Key Takeaways Summary

    IoT isn’t about the data … it’s about the value it enables!

    OUTCOMES

    Streaming/At-Rest, Advanced Analytics

    MULTI-PHASE ANALYTICS

    Edge-to-Cloud, Performance, Scalability

    DIFFERENTIATED TECHNOLOGY

    Full lifecycle support … Governance, Accountability,

    Management

    ENTERPRISE PLATFORM

    Growing investment, Expanding ecosystem, New

    channels

    OPPORTUNITY