It’s not.

Unrestricted © Siemens AG 2019

April 2019 Dr. Ralf Blumenthal | Siemens Smart Infrastructure

It’s not.Introducing Energy Efficiency Analytics,

the all inclusive Energy-Saving-as-a-Service (ESaaS).

Why is it so difficult to realize the full potential of

energy savings hidden in businesses across the world?

Green value from data:

State-of-the-art analytics for efficient

supply and use of energy

Hannover Messe 2019 | Integrated Energy Forum | April 2, 2019

Dr. Ralf Blumenthal | Siemens AG

siemens.com/already-esaasingUnrestricted © Siemens AG 2019


April 2019 Dr. Ralf Blumenthal | Siemens Smart Infrastructure

Energy efficiency is not new – but more important than ever!

ISO 50001Energy

audits§62 EEG

(Germany)

ISO 50003DIN EN

16247

Dashboarding

Real-time

Cloud

BI

And now? How to get value out of it?


April 2019Page 5 Dr. Ralf Blumenthal | Siemens Smart Infrastructure

Getting visibility onto process level at high frequency

is key to leverage the full potential of hidden energy savings

Robot

ERP

MES

SCADA

DCS

Big data

analytics

AI

Human

domain

expertise

EEA = Energy Saving

High-frequency sampling

Electricity

Gas

Water

Pump

EEA = Energy Saving as a Service

Additional energy savings and CO2

Better decision making

Improved process performance

101101101 101101101

1

0

1

0

0

0

1

Compressor

Transformer

Press

Furnace



EnergyIP Energy Efficiency Analytics works on a simple

principle – Turn the wealth of data in your facility into value

Massive DataAdditional insights with high-frequency sampling

down to 1 msec of energy consumption on asset level

Modern analyticsState-of-the-art big data and AI

algorithms for fast calculations

Renowned Expertise and Global FootprintDomain know-how, especially electrical,

built on strong legacy and global setup

Unmatched flexibilityModular approach tailored to your vertical,

specific needs and business environment

Save on reduced

energy consumption

and CO2 emissions

Reach better decisions and monetize

eco-certification

Improve process

performance across your

entire operations

Connect your assets to achieve continuously optimized business operations

various verticals with

no saving potential

0 customers across

energy reduction

Up to 25%

We

ISO 50001



Why high-frequency monitoring so important?

Example: Low resolution @ 1 sample per 5 minutes



Why high-frequency monitoring so important?

Example: High resolution @ 1 sample per 5 seconds



Our horizontal bottom-up approach to energy efficiency is

applicable to various areas in industry and infrastructure

Selection of typically monitored assets Selected industry verticals

Manufacturing Airports Water &

waste

Chemical &

petro-

chemical

Pulp & paper Generation Oil & gas Buildings

AND MORE…



Automotive

Creating measurable value in various areas of industry

and infrastructure – Selected customer examples

What is analyzed in this

customer example?

Thermosolar plant operation

Energy

Water waste and sludge

drying processes

Water and waste

Elevator usage, transformers

and heating

Building

Production processes

Example vertical?

Proven benefits for this

customer example? €200k savings in

auxiliary consumption per year

6% reduction in consumption

15%reduction in consumption

€8Msavings per year

7% reduction in consumption



First priority to create maximum value in minimum time –

Typical payback period of less than 2 years

Enablement of scaling across multiple sites through best-practice standardization

Maintenance cost reduction

through continuous monitoring of

smooth operations

Cost reduction

through reduced energy consumption

Process performance increase through

benchmarking and continuous optimization

Downtime reduction and avoidance

of breakdown cost through

continuous analysis of power quality

Failure reduction and equipment

lifetime increase through early

detection of defective operations

Decision support enhancement

through continuous high-quality

reporting in regular intervals

Monetized and certified CO2

reduction through continuous

monitoring with ISO 50001 certified tool

We ISO

50001



Flexible and modular service offerings

that fit to your environment and your needs

Basic modules Expert modules

Service levels: Copper, Silver, GoldApplication modules: 4 Basic + 8 Expert

E1 | Reporting

engine

B2 | Real-time

web interface

B1 | Scalable

data acquisition

and management

system

B3 | Statistical

analysis

B4 | Alarm

engine

E8 | Auxiliary

system

control

E2 | Integration

of data from

control systems

(e.g. MES, DCS,

SCADA)

E3 | Artificial

Intelligence

modeling

E4 | Big data

analytics

interface

Recommendations-as-a-service

Analysis-as-a-service

Software-as-a-service

Gold

Tier

Silver

Tier

Copper

Tier

= Silver Tier

+ recommendations for potential

improvements as part of monthly reports

= Copper Tier

+ automated weekly and monthly reports

(configured and made to order)

= Full access to all functionalities of

real-time web interface and basic

modules

E5 | Live models E6 | Advanced

visualization

elements

E7 | Advanced

reporting

engine



Identified efficiency measures stem from typical types of

analysis which address different main value drivers

No harmers

Quick

wins

Squeezers

Long

Game

changers

Short

Low HighInvestment

Payb

ack t

ime

Main value driversRough payback overview … … of analysis areas (selected, continuously adding)

High-frequency monitoring of energy consumption

Analysis and optimization of energy-based KPI’s per facility throughput

Active and reactive power analysis of transformers

Peak load analysis

Analysis of unnecessary loads and waste

A1

A2

A3

A4

A5

A1 A2

A8

A9

A4 A5A10

A3

A12

Decision support enhancement

Cost reduction

Electrical data Process data Auxiliary data Process Information

AI-based prediction of energy consumption and load patterns

Power quality analysis

Asset utilization analysis

AI-based optimization of operating parameters

Energy-based performance benchmarking

Analysis of unbalanced three-phase equipment and transformers

Anomaly detection and analysis of asset usage/load curve analysis

A7

A8

A9

A10

A11

A13

A14

Avoidance of breakdown cost

Process performance increase

Equipment lifetime increase

A11 A14

Required information:

Analysis of inefficient useA6

Analysis of process planning efficiencyA12

A6

A7A13



Example for

Optimization of energy-based KPI’s per throughput

Time [2 weeks]

Power [kW]

Volume

flow [m³]

Description Result

• 5 air compressors generating required pressure and volume flow

for process

• ~150 MWh of electricity consumption per month

• Monitoring of overall specific energy consumption per volume flow

resulted in ability to define best configuration for compressors to

operate

• Reduced energy consumption

of 24%

• Equivalent to saving >400

MWh of electric energy per

year

Measures implemented

• Change of control parameters



Example for

Asset utilization analysis

Description Result

• 1 air compressor

• An AI algorithm identified how an air compressor was operated

• Better knowledge and

traceability of how effectively

an asset is used

• Basis for performance

analysis leading to

maintenance efficiency


• n/a

Green: Normal behavior. OK

Blue: Programmed stop. STOP

Red: Mal functioning behavior. BAD



Example for

Energy-based performance benchmarking

Time [2 days]

Power [kW]

Description Result

• 2 presses at 0.9 MW nominal power each

• Presses produce same parts, but are manufactured by different

vendors

• Analysis showed that 1 press had higher consumption. The reason

was an unnoticed resetting of parameters

• Press consumption reduced

by 40%, leading to >140MWh

of energy savings per year

• Procurement team takes into

account energy consumption

into overall lifecycle costs of

an asset


• Press vendor carried out

adjustments



Example for Anomaly detection and analysis of asset

usage/load curve analysis

Time [14 hours]

Power

[kW]

Volume

flow [m³]

Description Result

• 4 water centrifuges at ~60kW nominal power each connected to 1

transformer

• Analysis showed that high peaks in the transformer load occurred

at times of high volume flow, although the loads of the centrifuges

remained constant

• Identification of unwanted

transformer behavior

detrimental to transformer

lifetime


• Detailed root cause analysis

ongoing by customer




Page 19 Siemens Energy Management

100 million tonsof CO2 saved by 20291)

[= yearly emissions of world’s Top 5 airlines ]

Our vision for impact

Become part of it!

1) How? We are currently enabling our customers to save an average of 18.2 kg of CO2 per MB of data analyzed



Already ESaaSing?

Get your personal live assessment

of additional energy saving potential

hidden in your business.

Right here and now.

Hall 9 – booth D35.

siemens.com/already-esaasing



We're happy to get in touch!

Dr. Ralf Blumenthal

Global Service Sales and Delivery

Mobile: +49 (173) 6961137

E-mail: [email protected]

Internet page:

www.siemens.com/already-esaasing

mailto:[email protected]

http://www.siemens.com/already-esaasing

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