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PHOTURGEN 1.0

AN OPEN-SOURCE RENEWABLE ENERGY MANAGEMENT TOOL

Daren Watson

CR2 Tutorial Room, Faculty of Science and Technology, UWI, Mona

Python Meet-Up, October 28, 2015

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

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General User InterfaceWhy Python?

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End

Rationale/Justification

High Resolution Simulation

The need for high resolution simulations for the optimization of various renewableenergy systems.

Regional Research

Lack of regional research on application of RE to small scaled load demands.

Void in regionally developed tools for HRES optimization.

Variability

Intermittent nature of wind and solar resources.

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Rationale/Justification

High Resolution Simulation

The need for high resolution simulations for the optimization of various renewableenergy systems.

Regional Research

Lack of regional research on application of RE to small scaled load demands.

Void in regionally developed tools for HRES optimization.

Variability

Intermittent nature of wind and solar resources.

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Rationale/Justification

High Resolution Simulation

The need for high resolution simulations for the optimization of various renewableenergy systems.

Regional Research

Lack of regional research on application of RE to small scaled load demands.

Void in regionally developed tools for HRES optimization.

Variability

Intermittent nature of wind and solar resources.

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Rationale/Justification

High Resolution Simulation

The need for high resolution simulations for the optimization of various renewableenergy systems.

Regional Research

Lack of regional research on application of RE to small scaled load demands.

Void in regionally developed tools for HRES optimization.

Variability

Intermittent nature of wind and solar resources.

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Rationale/Justification

High Resolution Simulation

The need for high resolution simulations for the optimization of various renewableenergy systems.

Regional Research

Lack of regional research on application of RE to small scaled load demands.

Void in regionally developed tools for HRES optimization.

Variability

Intermittent nature of wind and solar resources.

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Table of Contents

1 Introduction

2 Methodology

3 Data Collection

4 Software

5 Graphical Results

6 Website

7 General User Interface

8 Why Python?

9 Credits

10 Bibliography

11 End

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Table of Contents

1 Introduction

2 Methodology

3 Data Collection

4 Software

5 Graphical Results

6 Website

7 General User Interface

8 Why Python?

9 Credits

10 Bibliography

11 End

©2015 Watson Python Meet-Up

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Hybrid Renewable Energy Systems

So

lar

Pa

nel

So

lar

Pa

nel

WindTurbine

BiodieselGenerator

BatteryBank

Inverter

NationalElectric

Grid

Load Demand

AC 50 Hz

AC 50 Hz

DC

DC

DCAC 50 HZ

Figure : Diagram showing an example of a Hybrid Renewable Energy System (HRES)

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General Objectives of Research

Photurgen. Pronounced ’Pho-tur-gen’

Open-source simulation tool for hybrid renewable energy systems. Modelling of energysystem (i.e. battery, solar module, wind turbine etc.)

Correlation Analysis

Intrinsic look at variables involved in the performance of energy systems (temperature,wind, solar, air pressure etc.).

©2015 Watson Python Meet-Up

IntroductionMethodology

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General User InterfaceWhy Python?

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End

Table of Contents

1 Introduction

2 Methodology

3 Data Collection

4 Software

5 Graphical Results

6 Website

7 General User Interface

8 Why Python?

9 Credits

10 Bibliography

11 End

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Procedure

Data Collection

Collection of meteorological data for a period of one year (temperature, solarradiation, wind etc).

Collection of load consumption data for a period of not less than a week forresidential properties.

Figure : Onsite Installation: Weather Station Figure : Onsite Installation: Power Meter

©2015 Watson Python Meet-Up

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CreditsBibliography

End

Procedure

Data Collection

Collection of meteorological data for a period of one year (temperature, solarradiation, wind etc).

Collection of load consumption data for a period of not less than a week forresidential properties.

Figure : Onsite Installation: Weather Station Figure : Onsite Installation: Power Meter

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Procedure

Analysis

Identify methods of optimization for effective HRES design.

Identify mathematical models applicable to the simulation of HRES.

Perform statistical and numerical analysis of the collected data.

Example

Solar

Ppv = (Iph − Io

(exp

(q(Voc + Ipv Rs )

AKT

)− 1

)−

Voc

Rsh)Vpv (1)

Example

Wind

Pw = Pr

[exp(−( vcin

A)k ) − exp(−( vr

A)k )

( vrA

)k − ( vcinA

)k− exp(−(

vcout

A)k )

](2)

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Procedure

Analysis

Identify methods of optimization for effective HRES design.

Identify mathematical models applicable to the simulation of HRES.

Perform statistical and numerical analysis of the collected data.

Example

Solar

Ppv = (Iph − Io

(exp

(q(Voc + Ipv Rs )

AKT

)− 1

)−

Voc

Rsh)Vpv (1)

Example

Wind

Pw = Pr

[exp(−( vcin

A)k ) − exp(−( vr

A)k )

( vrA

)k − ( vcinA

)k− exp(−(

vcout

A)k )

](2)

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Procedure

Analysis

Identify methods of optimization for effective HRES design.

Identify mathematical models applicable to the simulation of HRES.

Perform statistical and numerical analysis of the collected data.

Example

Solar

Ppv = (Iph − Io

(exp

(q(Voc + Ipv Rs )

AKT

)− 1

)−

Voc

Rsh)Vpv (1)

Example

Wind

Pw = Pr

[exp(−( vcin

A)k ) − exp(−( vr

A)k )

( vrA

)k − ( vcinA

)k− exp(−(

vcout

A)k )

](2)

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Procedure

Analysis

Identify methods of optimization for effective HRES design.

Identify mathematical models applicable to the simulation of HRES.

Perform statistical and numerical analysis of the collected data.

Example

Solar

Ppv = (Iph − Io

(exp

(q(Voc + Ipv Rs )

AKT

)− 1

)−

Voc

Rsh)Vpv (1)

Example

Wind

Pw = Pr

[exp(−( vcin

A)k ) − exp(−( vr

A)k )

( vrA

)k − ( vcinA

)k− exp(−(

vcout

A)k )

](2)

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Procedure

Software

Create computational tools for the analysis of the collected data.

Model the performance of different energy systems (i.e. battery, solar module,wind turbine etc.).

Development of Photurgen; website, general user interface, etc.

Evaluate the tool using other software as benchmark eg. Homer Energy

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Procedure

Software

Create computational tools for the analysis of the collected data.

Model the performance of different energy systems (i.e. battery, solar module,wind turbine etc.).

Development of Photurgen; website, general user interface, etc.

Evaluate the tool using other software as benchmark eg. Homer Energy

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Procedure

Software

Create computational tools for the analysis of the collected data.

Model the performance of different energy systems (i.e. battery, solar module,wind turbine etc.).

Development of Photurgen; website, general user interface, etc.

Evaluate the tool using other software as benchmark eg. Homer Energy

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Procedure

Software

Create computational tools for the analysis of the collected data.

Model the performance of different energy systems (i.e. battery, solar module,wind turbine etc.).

Development of Photurgen; website, general user interface, etc.

Evaluate the tool using other software as benchmark eg. Homer Energy

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Procedure

Software

Create computational tools for the analysis of the collected data.

Model the performance of different energy systems (i.e. battery, solar module,wind turbine etc.).

Development of Photurgen; website, general user interface, etc.

Evaluate the tool using other software as benchmark eg. Homer Energy

©2015 Watson Python Meet-Up

IntroductionMethodology

Data CollectionSoftware

Graphical ResultsWebsite

General User InterfaceWhy Python?

CreditsBibliography

End

Table of Contents

1 Introduction

2 Methodology

3 Data Collection

4 Software

5 Graphical Results

6 Website

7 General User Interface

8 Why Python?

9 Credits

10 Bibliography

11 End

©2015 Watson Python Meet-Up

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Data CollectionSoftware

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Harbour View, Kingston

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Portmore, St. Catherine

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Windsor Castle, Portland

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Table of Contents

1 Introduction

2 Methodology

3 Data Collection

4 Software

5 Graphical Results

6 Website

7 General User Interface

8 Why Python?

9 Credits

10 Bibliography

11 End

©2015 Watson Python Meet-Up

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Photurgen (PTG)

Photurgen

Help PTGA

PTGGIS PTGO

ResourceAnalysis

System

Design

Output

Figure : Structural design of Photurgen

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Photurgen Analysis (PTGA)

Weather Analysis Load Analysis

Solar ModuleAnalysis

Wind TurbineAnalysis

WeatherStatistics

Load Statistics

Module Library

Maths Models

PTGA

Figure : Structural design of PTGA

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Photurgen Optimization (PTGO)

Load Economics

Solar ModuleEconomics

Wind TurbineEconomics

PTGO

Hybrid OptimizerModule Library

Figure : Structural design of PTGO

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Photurgen GIS (PTGGIS)

Shapefile Reader NetCDF Reader

Asc Reader

Module Library

PTGGIS

Figure : Structural design of PTGGIS

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Table of Contents

1 Introduction

2 Methodology

3 Data Collection

4 Software

5 Graphical Results

6 Website

7 General User Interface

8 Why Python?

9 Credits

10 Bibliography

11 End

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Digital Elevation Models

Source: PTGGIS

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Load Consumption

Source: PTGA

Figure : Load consumption patterns

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Load Consumption

Source: PTGA

Figure : Load consumption patterns

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Levelized Cost of Energy

Source: PTGO

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Optimal System Configuration

Source: PTGO

255 WModule

255 WModule

255 WModule

255 WModule

255 WModule

255 WModule

255 WModule

BatteryBank

Efficiency: 90%

BatteryBank

Efficiency: 90%

InverterEfficiency

: 90%

NationalElectric

GridOptional :

Net Billing,Standby

Load DemandDaily: kWh/d

Annual: kWh/yr

AC 50 Hz

DC

DC

AC 50 Hz

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PDF Report of Results

Source: All Modules

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Table of Contents

1 Introduction

2 Methodology

3 Data Collection

4 Software

5 Graphical Results

6 Website

7 General User Interface

8 Why Python?

9 Credits

10 Bibliography

11 End

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www.photurgen.com

Figure : Please visit www.photurgen.com for more information

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Table of Contents

1 Introduction

2 Methodology

3 Data Collection

4 Software

5 Graphical Results

6 Website

7 General User Interface

8 Why Python?

9 Credits

10 Bibliography

11 End

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Version 1

Current Version

Alpha

Testing

To Be Decided

Release Date

To Be Decided Figure : General User Interface

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Table of Contents

1 Introduction

2 Methodology

3 Data Collection

4 Software

5 Graphical Results

6 Website

7 General User Interface

8 Why Python?

9 Credits

10 Bibliography

11 End

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>>>import this

The Zen of Python

Beautiful is better than ugly. Explicit is better than implicit. Simple is better thancomplex. Complex is better than complicated. Flat is better than nested. Sparse isbetter than dense. Readability counts. Special cases aren’t special enough to breakthe rules. Although practicality beats purity. Errors should never pass silently. Unlessexplicitly silenced. In the face of ambiguity, refuse the temptation to guess. Thereshould be one– and preferably only one –obvious way to do it. Although that way maynot be obvious at first unless you’re Dutch. Now is better than never. Although neveris often better than *right* now. If the implementation is hard to explain, it’s a badidea. If the implementation is easy to explain, it may be a good idea. Namespaces areone honking great idea – let’s do more of those!

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Table of Contents

1 Introduction

2 Methodology

3 Data Collection

4 Software

5 Graphical Results

6 Website

7 General User Interface

8 Why Python?

9 Credits

10 Bibliography

11 End

©2015 Watson Python Meet-Up

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Special Mentions

Invitation

David Bain - Organizer

Advisors

Prof. M. Taylor - Deputy Dean

Dr. T. Stephenson - Acting H.O.D

Dr. J.F. Dorville - Supervisor

Dr. K.L. Duncan - Sponsor

Staff

Mrs. R. Simmonds - Equipment

Mr. J. Lothian - Site visits

Data Collection

Weather Resources

Mr. S. Simmonds

Load Consumption

Mrs. C. Scarlett

Mr. S. Simmonds

Biomass/Kitchen Waste

Mr. S. Simmonds

Mr. T. Lumsden

Mr. B. Dennis

Mr. D. Williams

Mr. S. Simms

First Class Tutoring JA

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Table of Contents

1 Introduction

2 Methodology

3 Data Collection

4 Software

5 Graphical Results

6 Website

7 General User Interface

8 Why Python?

9 Credits

10 Bibliography

11 End

©2015 Watson Python Meet-Up

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Bibliography I

Abbes, D., Martinez, A., and Champenois, G. (2013)Life cycle sot, embodied energy and loss of power supply probability for theoptimal design of hybrid power systemsMathematics and Computers in Simulation

Agrahari, R. P. and Tawari, G. N. (2013)The production of biogas using kitchen wasteInternational Journal of Energy Science

Agrahari, R. P. and Tawari, G. N. (2014)Comparative study of biogas production: Utilization of organic wasteInternational Journal of Environment and Resource

Anderson, P. and Bose, A. (1983)Stability simulation of wind turbine systems.IEEE Transactions on Power Apparatus and Systems

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Bibliography II

Bilal, B. O., Sambou, V., Ndiaye, P. and Ndongo, M. (2010)Optimal design of a hybrid solar-wind battery system using the minimization ofthe annualized cost system and the minimization of the loss of power supplyprobabilityRenewable Energy

Celik, A. N. (2013)Techno-economic analysis of autonomous pv-wind hybrid energy systems usingdifferent sizing methodsEnergy Conversion and Management

Connolly, D., Lund, H., Mathiesen, B. and Leahy, M. (2010)A review of computer tools for analysing the integration of renewable energy intovarious energy systemsApplied Energy

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Bibliography III

Feroldi, D., Degliuomini, L. N. and Basualdo, M. (2013)Energy management of a hybrid system based on wind solar power sources andbioethanolChemical Engineering Research and Design

Howells, M., Rogner. H., Strachan, N., Heaps, C., Huntington, H., Kypreos, S.,Hughes, A., Silveira, S., DeCarolis, J., Bazillian, M. and Roehrl, A. (2011)Osemosys: The open source energy modelling system: An introduction to itsethos, structure and developmentEnergy Policy

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Table of Contents

1 Introduction

2 Methodology

3 Data Collection

4 Software

5 Graphical Results

6 Website

7 General User Interface

8 Why Python?

9 Credits

10 Bibliography

11 End

©2015 Watson Python Meet-Up

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Data CollectionSoftware

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Questions?

All questions are welcomed!

©2015 Watson Python Meet-Up