PVOLTAI4.0Development of Industry 4.0 O&M Technologies for PV

Plants Management

Dr. Juan Luis Carús CandásTSK Digital Innovation

Dr. Yehea IsmailAmerican University of Cairo – Center for Nanoelectronics and Devices

Dr. Amr HelmyEmpower Energy Systems

Agenda

• General overview of the Project

• TSK activities: activities and status

• AUC-CND activities: activities and status

• EES activities: activities and status

• Submission procedure

Idea conception

PartnerSearch

PVOLTAI4.0

General overview of the project

Objectives:1. To develop an Industry 4.0 system capable

of monitoring and controlling a solar PV power plant based on Industry 4.0 KETs

2. To construct an IIoT enabled PV power plant solving vertical and horizontal integration problems and taken into account cybersecurity issues

3. To design new sensors and inspection technologies for PV plants characterization

4. To define and implement novel O&M data science algorithms, based on Artificial Intelligence techniques to improve the maintenance of the PV plants as well as predict the production.

5. To build a 25-30 Kwp PV demo plant to test the system (TRL7)

General overview of the project

Work plan

Work plan

• Start date: 01/11/2019

• End date: 30/06/2021

• Duration: 24 + 6 months

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www.grupotsk.com

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www.grupotsk.com

TSK is a technological and services company that offers efficient, sustainable and digital solutions for the industrial

and power sector.

# Our Company

YEARS OF EXPERIENCE

35+EMPLOYEES

1000+M€ TURNOVER

1000+COUNTRIES WITH EXECUTED

PROJECTS

50+

SOLUTIONS FOR A SUSTAINAIBLE WORLD

About TSK

TSK Activities

Industrial protocols

IIoT Device

New sensor

IIoT management platform

Caption

Processing

Exposition

Storage

Algorithm deployment platform

Web platform

Algorithm development platform

Design and development of a solution of Industry 4.0 KETs for

O&M for PV plants

About AUC CND• Graphics, Helic INC, IBM, Intel, Semiconductor Research Corporation (SRC), Khalifa University, NUS, Global Foundries, Si-Vision, MCIT,

Extensive funding and fund raising in the order of 2.5M USD since Fall 2012

• More than 270 IEEE publications are published in top international Journals and Conferences since Fall 2012.

• Spinning off a US startup (Suitera) based on an agreement between Suitera and the American University in Cairo (AUC). Suitera company

has top notch partners in the US , a first product, and excellent prospects.

• Significantly impacted the ranking of SSE and AUC

• Graduated 35 students since Fall 2012 from AUC, and have 12 students currently enrolled at AUC, and around 30 students benefit from

CND.

• Many patents since establishment (9 are granted)

• Alumni at the top Universities worldwide on scholarships from these institutions such as Coronel, Ohio State, Caltec, MIT, Goergia Tech,

USC, UCSD, …

• Good relations with top local and international companies such as TSK, Mentor ASRT, ITIDA,/ITAC, ERI, …

• Many Prototypes and fabricated chips unmatched by any other unit in the region.

About Project PI (Prof. Yehea Ismail)- IEEE Fellow

- Director of the Nanoelectronics and Devices Center at AUC and Zewail City.

- Was a tenured professor, Northwestern University, USA 2000 - 2011.

- Selected among the top 2% impactful scientists globally in the Stanford University El-Sevier study

- Chairman of the Board of the IEEE Transaction on Very Large-Scale Integration (TVLSI) and the chair

elect of the IEEE VLSI technical committee.

- Was the Editor-in-Chief of the IEEE Transaction on Very Large Scale Integration (TVLSI)

- Published more than 450 papers in top refereed journals and conferences and many patents.

- 5718 Citations and h-index is 34

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Management

Prepare technical progress reports and closure report

Manage the project activities and deliverables.

Hardware

Implement 50 copies of the new sensing platform

Test the implemented platform

Build communication hardware

Networking

Site network implementation

Data collection network

Remote VPN Network

Pvoltai4.0: AUC-CND Activities

Software

Select and implement the Cybersecurity IIoT technologies for PV

management

Study and develop the data visualization module

Implementation of AI-Based System for faults detection Hotspots

Shading

Ageing

Cleaning

Build drivers and communicate with characterizers

Build energy production prediction algorithms and implement it

Integrate all the developed components

Install devices and deploy software modules

Test the whole system 11

• Empower Energy Systems is the merger of two startups (Sola and EnergyTechnik)

• An academic spinoff focused on R&D with a rich pipeline of products and aservice based engineering company specialized in power systems, energygeneration & efficiency.

• EES is specialized in building turn key solar photovoltaic power plants offering On-Grid, Off-Grid & Hybrid Solutions

• Examples of EES Projects

- 27 kWp On-Grid Solar station, Co-Op Gas Station Cairo Fayoum Road.

- 10 kWp Off-Grid Solar station, American University in Cairo, New Cairo Campus.

- 10 kWp On-Grid Solar Station, Zewail City for Science & Technology, 6th October.

- 60 kWp Solar Station for Water Pumping, Dr Shafei’s Farm, Wahat.

- 35 kWp On-Grid Solar Station, GPS Building, Matrouh.

- 75 kWp On-Grid solar station, GPS Farm, Cairo Alex Road.

AboutEES

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Review of existing similar plants and technologies

Define industry 4.0 Architecture on which the desired solution will be built

PV plant design

Construction of PV plant (Prototype)

Assist AUC team in the integration of all developed components, testing of

the system, and reporting

Prepare financial progress reports and closure report.

Pvoltai4.0: EES Activities

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GPS Location of PV Plant in AUC

The solar power plant is installed within the American

University in Cairo (AUC) campus, New Cairo

Site selection Satellite Image photograph

after construction showing the site

EES Activities’ Status

PV plant Installation in AUC

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1

5

Site Measurement and Control

DC Combiner Boxes Weather Station

Hardware Characterization Results:

The Solar Characterizer

Complete Board V2.5Site panels measurement 1

Site panels measurement 2

Hardware:AUC-CND Activities’ Status

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Enclosures for the 50 CharacterizersNew Sensing Platform Details

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Calibration and Testing

• Autonomous Calibration software was developed using LabVIEW which controls the lab bench programmable power

supplies to Calibrate the Voltage Sensors and the Current Sensors for the 50 boards

• Testing was done by using a network of programmable power supplies, a Solar Panel IV Curve Emulator software was

developed

• The final step was to combine both the Calibration and the Testing Software to have a fully automated Calibration

and Testing Software

Calibration Testing

Complete Network Components & Block Diagram

Site devices are connected through LAN

MODBUS TCP and MODBUS RTU over RS485 (Using custom-made protocol converters)

Characterizers network through MQTT over Wi-Fi

AUC CND, EES and TSK Networks for operations and management

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MQTT and Cybersecurity

MQTT Protocol TSK Proposal 2

MQTT Protocol Initial Proposal

Migrating from MQTT to MQTTs for the Characterizers

Private Wireless Network

Securing the server using HTTPS/SSL

Securing the network using IPsec tunnels

Four Local Area Networks connected through IPsec VPNs

Public IP NTRA Whitelisting to communicate with TSK

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Cybersecurity:

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Data collection methodology in cooperation with the visualization

module

Raspberry Pi

Characterizers

Wireless MQTT

Software Daemon

CND Server

JavaScript JSON API

IPsec Tunnel

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Software Block diagram

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CND Site Management Dashboard

Localization Options

English Interface Arabic Interface

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CND Site Management Dashboard

Site Visualization

Integration with Modelling• Invoking Modeling Algorithms

• Visualizing Descriptive Features

• Features Include:

• Efficiency

• Fill Factor (FF)

• Voltage at Maximum Power

• Current at Maximum Power

• Maximum Power Point (MPP)

• Open-circuit Voltage

• Short-circuit Current

• IV-Curve

Block diagram of requests from the dashboard to the modelling algorithm

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CND Site Management Dashboard

Integration with Modelling• Screenshot of parameters extracted from modelling algorithms, plotted vs. time

Panel IV Curve, Efficiency vs. time

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Multi-level Modelling Approaches

Modelling at different levels:• IV measurement for single panel

• Panel diode and PV cell

• PV Panel

• PV String

• PV Site

Faults detection using AI Algorithms:

• Shading

• Hotspots

• Cleaning (dust accumulation)

• Ageing

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AI Algorithms Implementations

• The implemented AI algorithms should detect and predict the following tasks:

• Differentiate between reduced energy production due to Dust or Shading

• Predict the whole site energy production

• Predict possible faults that can cause failures such as:

• Hotspots

• Ageing

• Notifies the Site operator for any upcoming faulty events

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Integration of all on-site devices

Integration of the on-site devices with the software:

Software integration architecture block diagram

Submission Procedure

International

proposal

Consortium

agreement

National

application

Final

funding

decision

February 2019 June 2019 October 2019

3rd Egyptian-Spanish Joint Call

for IT Technological co-Operation 2018-

2019

November 2018

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Thanks for your attention