1st Edition

Big Data Analytics Strategies for the Smart Grid

By Carol L. Stimmel Copyright 2015
    256 Pages 43 B/W Illustrations
    by Auerbach Publications

    By implementing a comprehensive data analytics program, utility companies can meet the continually evolving challenges of modern grids that are operationally efficient, while reconciling the demands of greenhouse gas legislation and establishing a meaningful return on investment from smart grid deployments.

    Readable and accessible, Big Data Analytics Strategies for the Smart Grid addresses the needs of applying big data technologies and approaches, including Big Data cybersecurity, to the critical infrastructure that makes up the electrical utility grid. It supplies industry stakeholders with an in-depth understanding of the engineering, business, and customer domains within the power delivery market.

    The book explores the unique needs of electrical utility grids, including operational technology, IT, storage, processing, and how to transform grid assets for the benefit of both the utility business and energy consumers. It not only provides specific examples that illustrate how analytics work and how they are best applied, but also describes how to avoid potential problems and pitfalls.

    Discussing security and data privacy, it explores the role of the utility in protecting their customers’ right to privacy while still engaging in forward-looking business practices. The book includes discussions of:

    • SAS for asset management tools
    • The AutoGrid approach to commercial analytics
    • Space-Time Insight’s work at the California ISO (CAISO)

    This book is an ideal resource for mid- to upper-level utility executives who need to understand the business value of smart grid data analytics. It explains critical concepts in a manner that will better position executives to make the right decisions about building their analytics programs.

    At the same time, the book provides sufficient technical depth that it is useful for data analytics professionals who need to better understand the nuances of the engineering and business challenges unique to the utilities industry.


    Putting the Smarts in the Smart Grid
    Chapter Goal
    The Imperative for the Data-Driven Utility
    Big Data: We’ll Know It When We See It
    What Are Data Analytics?
         The Data Analytics Infrastructure
    Starting from Scratch 
         Mind the Gap 
         Culture Shift
         A Personal Case Study 
         Ouija Board Economics 
         Business as Usual Is Fatal to the Utility 
         To Be or Not to Be
    Finding Opportunity with Smart Grid Data Analytics

    Building the Foundation for Data Analytics
    Chapter Goal
    Perseverance Is the Most Important Tool
         "It’s Too Hard" Is Not an Answer
    Building the Analytical Architecture 
         The Art of Data Management 
         Managing Big Data Is a Big Problem 
         The Truth Won’t Set You Free 
         One Size Doesn’t Fit All 
         Solving the "Situation-Specific" Dilemma 
         The Build-Versus-Buy War Rages On 
          When the Cloud Makes Sense 
         Change Is Danger and Opportunity

    Transforming Big Data for High-Value Action
    Chapter Goal
    The Utility as a Data Company 
         Creating Results with the Pareto Principle
         The Business of Algorithms 
         Data Classes 
         Just in Time
    Seeing Intelligence 
         Remember the Human Being
         The Problem with Customers 
         The Transformation of the Utility
         Bigger Is Not Always Better
    Assessing the Business Issues 
         Start with a Framework


    Applying Analytical Models in the Utility
    Chapter Goal
    Understanding Analytical Models 
         What Exactly Are Models? 
         Warning: Correlation Still Does Not Imply Causation
    Using Descriptive Models for Analytics
    Using Diagnostic Models for Analytics 
         How Diagnostic Tools Help Utilities
    Predictive Analytics
    Prescriptive Analytics
    An Optimization Model for the Utility
    Toward Situational Intelligence

    Enterprise Analytics
    Chapter Goal
    Moving Beyond Business Intelligence 
         Energy Forecasting 
         Asset Management 
         Demand Response and Energy Analytics 
         Dynamic-Pricing Analytics 
         Revenue-Protection Analytics
         Breaking Down Functional Barriers

    Operational Analytics
    Chapter Goal
    Aligning the Forces for Improved Decision-Making
    The Opportunity for Insight 
         Adaptive Models
    Focus on Effectiveness 
         Visualizing the Grid 
         Distributed Generation Operations: Managing the Mix-Up
    Grid Management
         The Relationship Between Standards and Analytics
    Resiliency Analytics
    Extracting Value from Operational Data Analytics

    Customer Operations and Engagement Analytics
    Chapter Goal
    Increasing Customer Value 
         Customer Service 
         Advanced Customer Segmentation
         Sentiment Analysis 
         Revenue Collections
         Call Center Operations 
         Utility Communications
    What’s in It for the Customer? 
         Enhanced Billing and Customer-Facing Web Portals 
         Home Energy Management 
         Strategic Value

    Analytics for Cybersecurity
    Chapter Goal
    Cybersecurity in the Utility Industry
         The Threat Against Critical Infrastructure
         How the Smart Grid Increases Risk 
         The Smart Grid as Opportunity for Dark Mischief
    The Role of Big Data Cybersecurity Analytics 
         Predict and Protect 
         Cybersecurity Applications 
         Proactive Approaches 
         Global Action for Coordinated Cybersecurity 
         The Changing Landscape of Risk


    Sourcing Data
    Chapter Goal
    Sourcing the Data 
         Smart Meters 
         Control Devices 
         Intelligent Electronic Devices 
         Distributed Energy Resources 
         Consumer Devices 
         Historical Data 
         Third-Party Data
    Working with a Variety of Data Sources 
         Data Fusion

    Big Data Integration, Frameworks, and Databases
    Chapter Goal
    This Is Going to Cost
    Storage Modalities 
         Network-Attached Storage
         Object Storage
    Data Integration
    The Costs of Low-Risk Approaches
    Let the Data Flow 
         Hadoop Distributed File System 
         How Does This Help Utilities?
    Other Big Data Databases 
         In-Memory or Main Memory Databases 
         Object-Oriented Database Management Systems
         Time Series Database Servers 
         Spatial and GIS Databases
    The Curse of Abundance

    Extracting Value
    Chapter Goal
    We Need Some Answers Here 
         How Long Does This Take?
    Mining Data for Information and Knowledge
    The Process of Data Extraction 
         When More Isn’t Always Better 
          Running for Performance 
         Hadoop: A Single-Purpose Batch-Data Platform?
    Stream Processing 
         Complex Event Processing 
         Process Historians
    Avoid Irrational Exuberance

    Envisioning the Utility
    Chapter Goal
    Big Data Comprehension
    Why Humans Need Visualization 
         Walking Toward the Edge
    The Role of Human Perception
         Preattentive Processing
    The Utility Visualized 
         Advancing Business Intelligence 
         High-Impact Operations 
         Improving Customer Value
    Making Sense of It All

    A Partnership for Change
    Chapter Goal
    With Big Data Comes Big Responsibility
         Abandon All Hope, Ye Who Enter Here?
    Privacy, Not Promises 
         Data Management
    Privacy Enhancement 
         Enabling Consent 
         Data Minimization
         The Role of Metadata
    The Utility of the Future Is a Good Partner



    Carol L. Stimmel began working with "big data analytics" in 1991 while hacking code and modeling 3D systems for meteorological research—years before that combination of words ever became buzzword compliant. In those 23 years, she has spent the last 7 focusing on the energy industry, including smart grid data analytics, microgrids, home automation, data security and privacy, smart grid standards, and renewables generation. She has participated in emerging technology markets for the majority of her career, including engineering, designing new products, and providing market intelligence and analysis to utilities and other energy industry stakeholders.

    Carol has owned and operated a digital forensics company, worked with cutting-edge entrepreneurial teams; co-authored a standard text on organizational management, The Manager Pool; and held leadership roles with Gartner, E Source, Tendril, and Navigant Research. She is the founder and CEO of the research and consulting sustainability company, Manifest Mind, LLC, which brings rigorous, action-based insight to advanced technology projects that create and maintain healthy ecosystems for people and the environment. Carol holds a BA in Philosophy from Randolph-Macon Woman’s College.

    This book provides an in-depth analysis that will help utility executives, as well as regulators, investors, large power users and entrepreneurs, understand some of the tectonic changes coming to an industry that from the outside can seem impervious to change. Making sense of a chaotic future, Carol charts a path where everyone can benefit.
    –Amit Narayan, PhD, CEO, AutoGrid

    After more than a century providing a mission-critical resource to consumers around the world, traditional energy providers are realizing the power of big data and predictive analytics. Not only will adopting these technologies improve the transmission and distribution of energy, it more importantly will enable providers to adopt a services mentality. In her exceptional book, Carol examines these trends and breaks down very complex topics into prose that is easy to understand. I highly recommend this book to anyone in the energy industry looking to grow and evolve their business.
    –Adrian Tuck, CEO, Tendril

    Carol Stimmel defines utility data analytics as the application of techniques within the digital energy ecosystem that are designed to reveal insights that help explain, predict, and expose hidden opportunities to improve operational and business efficiency and to deliver real-world situational awareness. She then provides the framework, methodology, insight, and experiential observations to help utilities conceive, plan, implement, enhance, and sustain the imperative smart grid analytics required to achieve the inexorable change taking place in the energy delivery ecosystem. Volume, velocity, variety, and value—the characteristics ascribed to ‘big data’ will aptly characterize the reader's and practitioner's view of Ms. Stimmel's book.
    –Ivo Steklac, GM Residential & Commercial Energy Solutions, SunPower Corporation

    The author has done an excellent job of leveraging her experience in the industry and her strong technical background to create a book that is a very easy-to-read, useful tool for anyone trying to get started in applying big data analytics to the utility industry.  She not only provides the reader with a solid base knowledge and background but provides solid examples of how data analytics can be applied within a utility environment and the advantages that can be gained by doing so.
    –Ron Gerrans, CEO, Genus Zero and former CEO, E Source