Big Data Analytics Strategies For the Smart Grid

Big Data Analytics Strategies For the Smart Grid

by Carol L. Stimmel

Hardcover(New Edition)

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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.

Product Details

ISBN-13: 9781482218282
Publisher: Taylor & Francis
Publication date: 08/05/2014
Edition description: New Edition
Pages: 256
Product dimensions: 6.00(w) x 9.20(h) x 0.90(d)

About the Author

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.

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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