Sameer Tiku

How Operational Analytics can transform the grid

Product Architect

Bentley Systems

Data Analytics

Data – heart of the digital transformation

Remote Operations

The Environment

Man-made Data

Wi-Fi Enabled Devices

Data Historians

IT Systems

Real-time Data

Remote sensing of objects and machines

Multiple data types from various sources with great volume and velocity of change

Challenge lies in gaining access to the data, bringing it into one place, and using it correctly.

• With all of the information available, how do you know you are making the right decision?

• When is the best time to make the decision?

• Are you making the decision too late or after the event?

• How do you aid decision making?

• Is lack of visibility into asset and operational performance hindering decision making?

Making the right decision

Data is growing at an exponential rate due to advances in sensor technology and costs, access, and devices that can produce data.

Data complexity then calls out for applications that can manage these diverse data types.

The Growth of Data

Big data

Velocity Volume

Variety Veracity

?

?

?

Common Buzzword Definitions

Operational Analytics

Helps companies improve their situation awareness and ability to sense and respond

quickly to changing business conditions

Dig Data

High volume, velocity and variety information assets that demand cost effective, innovative forms of information processing for enhanced

insight and decision making.

ITOT

The IT and OT convergence in brings two worlds together – operational technology data and IT data - to deliver new levels of decision

support.

Internet of Things

Is the network of physical objects that contain embedded technology to communicate and sense or interact with their internal states or

the external environment.

?

Analytics within the Smart Grid

• Ageing Infrastructure • Solutions: Asset Health Monitoring, Structural Integrity, Corrosion

Management, Condition Monitoring

• Reliability • Solutions: RCM, Condition Monitoring, Asset Health

• Environmental Regulation • Solutions: Emissions Monitoring, Reporting

• Ageing Workforce • Solutions: Capturing and Institutionalizing domain knowledge, User defined

analytics / templates, Modeling Specific Domain Expertise, Reducing need for field visits

• Rising costs • In asset failure, loss of production, unplanned downtime, operational

expenditure

Electric Utilities – Top 5 Priorities

• Business Intelligence

• Descriptive Analytics

• Diagnostic Analytics

• Predictive Analytics

Why Operational Analytics?

} Operational Analytics

Operational Analytics

Capture Structured & unstructured data from

any source

Advanced calculation and analysis, rules

engine and R modeling

Real-time dashboards

Predictive capability to identify forward looking opportunities & events

Prescriptive analytics for automated decision

making

Operational Technology

Engineering Technology /Digital Engineering Models

Information Technology Advancing

Asset Performance

Schematics | 3D Models | Catalogs | Analysis | Network Models | …

Control Systems

Smart Machines

Location Systems

Environment Sensors

Barcodes / RFID

ERP

CRM

Demand Management

Financial Planning

Network Optimization

IT-OT-ET Convergence for Operational Analytics

||

||

|

||

||

|

Typically associated with field-based devices connected to thedistribution system, and theinfrastructure for monitoringand controlling those devices.This includes control centerbased systems such as SCADAand DMS.

Converging IT and OT in the Smart Grid

Traditionally associated with back-office information systems used forconducting business-typetransactions, such as cost and taxaccounting, billing and revenuecollection, asset tracking anddepreciation, human resourcerecords and time-keeping, andcustomer records.

Operational Technology Information Technology

• Only going to get bigger.

• Due to growth of connected devices, open standards & the cost of smart technology decreasing.

• Using analytics to take advantage of the data can lead to lowering energy costs and realizing the potential of a complete Smart Grid.

Take advantage of the Industrial Internet of Things

Go from reactionary to proactive

Analytics in the real world

CHALLENGES• Fleet management

• Large numbers of diverse assets, large geography, built in redundancy

• Asset Life and Reliability

• 40-80 year life, Condition Monitoring reliability less than 10 years

• Proprietary Software

• Every Condition Monitoring device has bespoke software

• Remote Connectivity

• Need to get the data off site to those who need it

• Reliability and Confidence

• History of poor reliability of Condition Monitoring systems and signal processing

• Sharing Data

• Data from different systems needs to be combined

Large Electricity Transmission Company - Substations

• Collect data from Hydran dissolved gas monitoring systems, and transmit data via GPRS to a Web server.

• Visualization allows users to view all assets

• Drill down to view oil levels, temperatures, compressors etc in real-time on dashboards

• Notifications sent to engineers based on alarm levels when required

Solutions

Typical transformer condition monitoring dashboard

• Improved reaction times resulting from the introduction of real-time monitoring and alerting

• Reduced costs due to scheduled maintenance

• Extended asset life by quantifying and managing risk

• Reduced disruption due to event alerts

• Increased decision making

Benefits

Gas Levels and Alarm Dashboard

CHALLENGES

• Unable to predict the corrosion rate of steel tower network

• Needed to identify problem lines and individual towers

• Unable to plan best financial strategies

Large Electricity Transmission Company Overhead Lines and Towers

• This was created through a care and risk evaluation model

• Use the Amulet system to take all data that affects the degradation of steel, zinc, and organic coatings on all above ground steelwork

• This involved taking data from a variety of sources including:• temperature, humidity, time of wetness; pollution in the form of air-

borne sulfur dioxide; location in altitude, proximity to sea, lakes, reservoirs, rivers, minor and major roads; and history, including installation date, coating records, and maintenance history

• Analytic techniques were used to calculate the long term risk

Solutions

Typical example of corrosion index across a line

• First time it was possible to predict the expected condition of transmission towers across a selection of the network.

• This allowed preventive and replacement strategies to be planned

• Reduced maintenance costs

• Manage and plan costs over a long-term strategy.

• Move from unplanned to proactive

Benefits

The Future: Context Capture - Asset Performance Remodeling

Operational Technology

Engineering Technology /Digital Engineering Models

Information Technology Advancing

Asset Performance

Schematics | 3D Models | Catalogs | Analysis | Network Models | …

Control Systems

Smart Machines

Location Systems

Environment Sensors

Barcodes / RFID

ERP

CRM

Demand Management

Financial Planning

Network Optimization

IT-OT-ET Convergence for Operational Analytics

||

||

|

||

||

|

“THANK YOU”