Smart Metering Value Realisation through Data Analytics

• Ashley Maistry

• Smart Grid Delivery Lead

• Accenture

• South Africa

Data Analytics is a shift in the mindset of how we think about analytics as an internal component to the organisation. It is a way to foster a culture around your organisation that focuses on letting data be productionalised in such a way that not only drives meaningful insights in a rapid fashion, but drives innovation to exploit missed opportunities in areas previously unlooked.

“The sexy job in the next 10 years will be statisticians”

-- Hal Varian, Chief Economist at Google

What is Data Analytics?

What are the different types of Data Analytics?

Optimisation

Predictive Modeling

Forecasting / Extrapolation

Statistical analysis

Alerts

Query/drill down

Ad hoc reporting

Standard Reports

Scholastic Optimisation

Co

mp

etit

ive

Ad

van

tage

Sophistication of Intelligence

“What’s the best that can happen?”

“What will happen next?”

“What if these trends continue?”

“Why is this happening?”

“What actions are needed?”

“What exactly is the problem?”

“How many, how often, where?”

“What happened?”

“Including variability, what’s the best that can happen?” Prescriptive Analytics

“The Consequence”

Predictive Analytics “The So What”

Descriptive Analytics “The What”

Typical AMI Solution Landscape

Meters Local Area

Network (LAN)

Data Concentrator

Wide Area

Network (WAN)

Master Station/

Head End System

Demand Management

Customer Premise Meters Communications Meter Data Back Channels Equipment Infrastructure Management System Office

Billing

Determinants

Generation

CIS

Customer

Interface

Demand

Response

Mgmt

Outage

Mgmt

Distribution

Planning &

Operation Load

Forecast

&

Settlement

Install.

&

Maint.

Revenue

Protection

Load

Forecasting

& Settlement

System

Demand

Response

Mgmt

System

Asset Mgmt

& Install. Planning;

Field Order Mgmt

Systems

GIS;

Field

Order

Mgmt

System

Outage

Mgmt

System

Meter Data

Repository

Utility Back Office

Applications

Customer Services

Are you realising value from your Smart Metering Investment?

Billing

Determinants

Generation

CIS

Customer

Interface

Demand

Response

Mgmt

Outage

Mgmt

Distribution

Planning &

Operation Load

Forecast

&

Settlement

Install.

&

Maint.

Revenue

Protection

Load

Forecasting

& Settlement

System

Demand

Response

Mgmt

System

Asset Mgmt

& Install. Planning;

Field Order Mgmt

Systems

GIS;

Field

Order

Mgmt

System

Outage

Mgmt

System

Meter Data

Repository

1. DATA 2. INFORMATION 3. INSIGHTS

Insights

Interpretable Uninterpretable

Relevant Irrelevant

Signal Noise

Interpretable

Uninterpretable

Relevant

Irrelevant • What is the hidden value?

• What can I know now what I couldn’t before?

• How do I do all this in a constrained environment?

However, the approach should be…

Value Pools for Smart Meter Data

Smart meter information can assist to pursue three primary opportunities:

Smart Meter Data

Optimise Revenue

Increase Operational Efficiency

Improve the Customer Experience

Typical Smart Metering Use Cases

Top Use Cases

Customer Profiling

• Customer consumption

trends • Customer segmentation • Standard load profiles vs

actual load patterns • Seasonal changes • Consumption benchmark

per segment • Usage views &

comparison with neighbourhoods

Event Analysis

• Device status • Tampering alarms • Outage management • Event trends • Event details • Event analysis • Correlation of event

trend and VEE exceptions

Grid Optimisation

• Technical losses • Enhanced outage

management • Transformer monitoring • Service restoration • Consumption forecasts

based on weather events • PQ analytics, Volt/VAR

optimisation • Fault location • Load control for DR

Building A Smart Metering Analytics Capability begins with a proven Analytics Operating Model

Vision & Leadership

Organisation

Structure

Capability

Development

Value Identification & Realisation

Process & Insight Management

Information & Data Management

Solution & Technology Management

Business Technology Jointly Owned Legend

The Future State creates a set of recommended initiatives, which will be sequenced in the roadmap and feed an iterative “Value Management” process

to prioritise, define, execute, and realise the value of analytics

opportunities.

“PROVE VALUE or FAIL FAST”

• Approach to Proceed – PoC, Pilot, Production

• Value Measurement Approach • Responsibility/Resource Plan • Business Case

PoC / Pilot / Production Project Charter

• Measure value realisation vs. plan

• Define learnings • Define recommended actions • Identify new opportunities

Value Outcomes “Opportunity Queue”

Logical Grouping

Prioritised Initiatives Recommended Initiative Profiles

Smart Meter Data

Smart Meter Data Value Management Strategy

Case Study: One utility identified 250+ total smart meter value opportunities across the enterprise

12

29

14

4

70

28

6

79

21 5

250+ Total

Capabilities

Captured

Digital Commercial Optimisation (Power Supply)

Finance

Intelligent Network Optimization (DG, PQ, Outages, DR, etc.)

Digital Field Worker (WFM, Logistics, Resource Mgt, Fleet, Safety)

Digital Customer Interaction (Touchpoints, etc.)

Digital Customer Products and Services

Digital Customer Operations (Billing Improvements)

Demand Optimisation (DSM)

Advanced Metering Operations (Meter Operations, NOC / SOC, Revenue Protection / Theft)

Digital Asset Management (includes Grid Design)

Case Study: These opportunities were consolidated into 150+ use cases

250+ Capabilities

Raw capabilities (including overlap amongst organizations)

150+ Use Cases

Overlapping/duplicate capabilities were consolidated into use cases

16 Projects

Use cases were grouped into projects based on actionable commonalities, which ultimately reduces costs associated with execution

Projects were then be prioritized / sequenced based on expected value and feasibility

Meter Error

Management

Capability

Meter System

Lifecycle Mgmt.

Capability

Automated "Pinging"

of the Smart Meter

Capability

Meter Optimisation

Initiative

Automated "Pinging"

of the Smart Meter

Use Case

Meter System

Health Checks

Use Case

Value + Difficulty + Priority

Wave 1 9-12 weeks

Wave 2 6-9 months

See

pe

rfo

rman

ce

Wave 3 1-3 years

Case Study: Example roadmap from a Water Utility

Water networks

Sewer networks

Water production

Waste treatment

KPI Reporting

Work Order Management

Remote Engineering

Optimise performance

Mobile Workforce Management

Quality monitoring

Operational Intelligence

Remote Monitoring Event Alarm Analysis

Real Time Control

Predictive Analytics

Network Comms Monitoring

Production Insight & Planning

Asset Monitoring

Field Sensors (customer)

Pipe/Network sensors

Control Optimisation Digital Customer

Enablement

Asset Optimisation

Event Alarms

Manage performance

We had the opportunity to deploy an analytics driven solution at Thames water, resulting in

$50M benefits over 5 years

• Thames Water’s vision was to embrace the Internet of Things with Data Analytics to transform decision-making on the frontline.

• Frontline Information Technology Program is all about the new ways of working made possible by insight at the point of action and collaboration spurred by a single view of assets (including Smart meters)

9 Months

$50M 5y benefits estimate

Real Time & Geospatial Analytics

5 year Benefits Estimate

Analytics Platform

Limited Scale Smart Meter Deployment

9 months & 40 team members

50M

• Advanced Analytics tools and solutions

• Information and analytics organisation

design, processes, & operating model

• Talent sourcing and delivery model

Smart Metering Data is in the midst of a “Data Renaissance,” don’t you want to start getting

the Value today?

Analyses and insights

Advanced Analytics

Reporting and data collection

Analyses and insights

Reporting and data collection

• Report rationalisation

and automation

• KPI / Metric alignment

• Information & Data

Management

From* To*

Advanced Analytics

* Percentage of Time

Industry Trending

• Issue-driven insights and measures

• “Just-in-time” Data Access

• Roles & Actors - Process automation

• Fact-based decision making