Trends in Soft Grid 2014

September 2014

Soft Grid Trends 2014

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1) Utilities Are Increasing the Number of Data Streams Used for Analytics

Increasing sources come from the integration, duplication, or transport of data from siloed groups that are not prohibited from collaborating (i.e. energy trading and T&D operations in a deregulated territory)

Traditional Utility Siloes Wholesale Generation

Transmission and Distribution Operations

Customer Service / Demand Management

Asset Management

Energy Marketing/Trading

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Custom Services / Engineering

Examples of Converging Data: 1. Using SCADA from operations with

traditional asset management systems to enable the creation of asset health scores.

2. Comparing monitoring data from T&D operations with measured consumption within AMI systems to pinpoint technical and non-technical losses.

3. Combining recent customer and topological data with public data sources and system characteristics to suggest EE or DSM retrofits in lieu of grid expansion.

4. Combine current renewables production and predictive production data with contract and status information from DERs located on the utility system or at the customer site for supply-following.

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2) Distributed Processing Is No Longer Just for Reliability

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Field Message Bus

Duke, BC Hydro, RWE, MECO, and San Diego Gas & Electric to research approaches that enable IIoT services over a distributed computing platform in the field for operations and energy management

Semantic Conversion and Processing

Communications Data Storage

Benefits1. Reduced Backhaul

Communications 2. Faster Event Response3. Flexible/Expandable App

Architecture4. Marginal Scaling Costs

Capabilities1. Real-Time Automation2. Application-Driven

Operations3. Local Area Situational

Awareness4. Federated Decision-Making

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3) Operational Analytics Are Just Starting To Be Real-Time

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Analytics use cases associated with AMI data are NOT real-time applications today

Theft Detection

Voltage Reads Load Forecasting

Customer Engagement

Asset Management

Within operations, SCADA and DMS systems operate in near-real-time, but still are limited by use case development, operational maturity, lack of utility demand, and existing IT structures

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3) Operational Analytics Are Just Starting To Be Real-Time

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Utility interest is migrating toward more real-time applications with processing and applications in the field (distributed processing) and in the enterprise to

provide real-time support for grid operations.

Batch Processing Complex Event Processing Stream Processing

2008-2012 2012-2014 2015-2017

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Siloed Post-Event Analysis

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Current Situational Awareness Predictive and Adaptive Modeling

Semantic Conversion and Processing Communications Data Storage

Control

Supervision

Supervision

Control

Real-time analytics are the next wave of investment as renewables proliferate and distribution utilities are subjected to new regulatory constructs

• Major focus on billing system advancement, MDM and traditional systems

• Utilization of traditional utility-owned systems

• Limited integration within the enterprise

• Utility-owned centralized processing used during off-hours

• Interest in crunching data from many sources

• Enabling utilities to seek out insights and explore anomalies from a multi-system view and “jump” to relevant systems so to execute a business process

• Major focus on visualization, permissions, and centralized management and control

• Major focus on machine-to-machine communications and response

• Increasing use of embedded apps and federated control structures

• Real-time M2M control coupled with near-real-time human supervision and global system management

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4) Accessibility and the Cloud Are Becoming Important

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• Cloud platform scalability is opening up analytics and data to wide groups of users, inside and potentially outside the utility, on a dynamic basis

• Access to cloud data streams and ease of data duplication is allowing utilities to provide wider sets of reliable data across the enterprise.

• Scalable processing is beginning to reduce processing time and improve the efficiency of query generation and data exploration

• Value of data access varies widely due to regulatory peculiarities in various territories, especially when a territory is deregulated or when utilities are required to provide usage data to customers or system status data to other parties

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Data Storage Processing

Government Consumers

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5) Consistent VC Funding Over the Last Five Quarters

Q1 2012

Q2 2012

Q3 2012

Q4 2012

Q1 2013

Q2 2013

Q3 2013

Q4 2013

Q1 2014

Q2 2014

Q3 2014

$0

$20

$40

$60

$80

$100

$120

$140

$160

0

2

4

6

8

10

$28$14

$52$45

$5

$137

$26

$47

$25$29 $31

Soft Grid Deal Count

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GE Ventures invests $105 million in Pivotal