big data analytics & iot challenges

© BaxEnergy GmbH 2010-2017. All rights reserved. Specifications are subject to change without notice. Energy Studio Pro® and its modules are registered trademarks of BaxEnergy GmbH. Other product and company names mentioned herein may be trademarks of their respective owners.

Speaker: Carmelo Floridia

Big Data Analytics & IoT challenges: Innovative Solutions for a Greener World

Big Data For You Conference 25th February 2017 Catania

BaxEnergy ItalySenior Engineer – Data Processing

©2017 BaxEnergy GmbH. All rights reserved

INNOVATIVE SOLUTIONS FOR A GREENER WORLD

© BaxEnergy GmbH 2010-2016. All rights reserved. Specifications are subject to change without notice. Energy Studio Pro® and its modules are registered trademarks of BaxEnergy GmbH. Other product and company names mentioned herein may be trademarks of their respective owners.© BaxEnergy GmbH 2010-2017. All rights reserved. Specifications are subject to change without notice. Energy Studio Pro® and its modules are registered trademarks of BaxEnergy GmbH. Other product and company names mentioned herein may be trademarks of their respective owners.

Carmelo Floridia

Software Architect for Real-Time data solutions

Joined Bax Energy in 2012

Worked for companies in the field of sofware development and industrial automation

Microsoft Certified Solution Developer

Computer Engineering Degree - Catania University



Data Driven Renewable Energy



IoT in BaxEnergy

Group- Critical Value Monitoring Hydro Power Curve

Hydro Power Plant



IoT in BaxEnergy

Photovoltaic Power Plant Solar Power Curve

Solar Power Plant



Power Curve Analysis

kW

m/s


© BaxEnergy GmbH 2010-2016. All rights reserved. Specifications are subject to change without notice. Energy Studio Pro® and its modules are registered trademarks of BaxEnergy GmbH. Other product and company names mentioned herein may be trademarks of their respective owners.©2016 BaxEnergy GmbH. All rights reserved



Power Plants Globally DistributedPower Plants Globally Distributed



Distributed Data

DA

TA V

OLU

ME

TIME

INCREASING DATA VOLUME

HydroelectricGeothermal

Wind

Solar

Smarthomes



Do we have a Big Data problem?

Big Data is typified by the "3 V’s":• Volume – huge amount of data to process

• Variety – a mixture of structured and unstructured data

• Velocity – new data generated extremely frequent

Volume Variety Velocity



Services based on big data

Frequenting shops Google Traffic



Technology is all around us

The way you see things changes the way you live them...



Benefits of estimating energy production and demand

Forecast of how much renewable energy will be generated and demanded brings many benefits:

• efficiently control the number and capacity of turbines in operation to meet electricity demand.

• allow system operators to make better use of existing backup capacities.

• allow grid operators to more accurately schedule not only backup generation, but also manage consumer demand.



Predictive Analysis

Historical Data:

Warnings

Failure

Working Conditions

Machine Learning Models:

Next-Gen Predictive Platforms

Failure Prediction:

Working Conditions

Warnings

Forecast

Cost ReductionA tool able to provide the data necessary for a proper statistical predictive analysis, to improve maintenance of power generators and field devices



Business Intelligence Evolution



What is machine learning?

• Machine learning is a technique of data science that helps computers learn from existing data in order to forecast future behaviors, outcomes, and trends.

• These forecasts or predictions from machine learning can make apps and devices smarter. When you shop online, machine learning helps recommend other products you might like based on what you've purchased.



What is machine learning?

Traditional Programming Machine Learning



Kinect –Human Model Learning



Azure Machine Learning

• Azure Machine Learning is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions.

• You can work from a ready-to-use library of algorithms, use them to create models on an internet-connected PC, and deploy your predictive solution quickly.

• Web API as RESTful service.

big data analytics & iot challenges

Environment