Big Data Analytics Strategies for the Smart Grid  book cover
1st Edition

Big Data Analytics Strategies for the Smart Grid

ISBN 9781482218282
Published July 25, 2014 by Auerbach Publications
256 Pages 43 B/W Illustrations

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Book Description

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.

Table of Contents


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


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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