An Integrated Tool for Microgrid Designin Rural Areas

Hkon Duus

Master of Energy and Environmental Engineering

Supervisor: Olav B Fosso, ELKRAFTCo-supervisor: Marta Molinas, ITK

Department of Electric Power Engineering

Submission date: November 2015

Norwegian University of Science and Technology

A B S T R A C T

PV-microgrids are becoming an affordable alternative to provide electricity ac-cess to remote or isolated regions, due to both a reduction in prices on solarpanels and a strong focus on utilisation renewable energy resources.

When designing microgrids, the use of optimization methods has tradition-ally been rather limited. Flexible systematic design tools that covers the fullsystem path from data-acquisition to optimization and load-flow-analysis, areof limited availability.

This thesis will seek to present a methodology for a cost-effective design ofmicrogrids based on composable tools using optimization. Possible ways toovercome the lack of data will be discussed, along with the economic parame-ters used for the optimization process. A selection of already-existing tools willbe presented, along with the advantages of the using novel sizing methodologypresented in the thesis.

The methodology presented will be applied to a case-study in Bhutan. Us-ing measured data from the study, the accuracy of initial assumptions anddata-acquisition can be evaluated. The findings were that initial assumptionscan give a good idea on consumer behaviour, and thus system composition,however a more detailed study on local conditions will always be preferred.

Finally stable operation of the optimized system will be validated throughMatlab/Simulink-models.

S A M M E N D R A G

PV-mikrogrids blir et stadig mer prisgunstig alternativ for kraftproduksjon igrisgrente strk, bde grunnet det kraftige fallet i pris p solceller, i tillegg tilet kt fokus p bruk av fornybar energi.

Bruken av optimaliseringverkty i designprosessen til mikrogrids har tradis-jonelt vrt heller begrenset. Det finnes f fleksible verkty som dekker heleprosessen fra datainnsamling, til optimalisering og lastflytanalyse.

Denne oppgaven har som forml presentere en metodologi for kostnadsef-fektive design-lsninger for mikrogrids, basert p sammen-settbare optimalis-eringsverkty. Ulike mter takle manglende data p, samt de knomiskeparameterne som danner grunnlaget for optimaliseringen, vil bli diskutert. Etutvalg av slike verkty som allerede er p markedet kommer til bli presentert,sammen med fordelene til den nye metodologien.

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Dette nye verktyet vil bli anvendt p en case-studie i Bhutan. Ved brukav mlte data fra denne studien, kan treffsikkerheten til de opprinnelige an-tagelsene og dataene bli evaluert. Resultatene var at disse opprinnelige an-tagelsene gave en god pekepinn p forbruksmnster, og sledes systemsam-mensetning, men mer detaljert informasjon om lokale forhold er stadig fore-trekke.

Avslutningsvis vil det bli brukt Matlab/Simulink-modeller for bekrefte atdet optimaliserte systemet opererer stabilt.

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You westerners are too concerned with time

Karma Sampo

A C K N O W L E D G M E N T S

First of all i would like to thank Marta Molinas for giving me the great oppor-tunity to partake in this project, for insightful and rewarding discussions, andvaluable feedback throughout the process. Olav Fosso for helpful supervisionand guidance on technical writing.

My co-worker and travel-partner Geir Kulia for patience and support bothon the technical part, as well as during the field-trip to Bhutan.

The summer-internship-team at NTNU with especial emphasis on AnneLoz, Danielle Sakepa, Jeemijn Scheen and Honorad Quinard for great dis-cussion and cooperation.

And last, but not at all least, the students and staff at the College of Scienceand Technology in Phuentsholing, Bhutan, for making it all a life-changingexperience.

My most sincere thanks to you all.

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C O N T E N T S

1 introduction 11.1 Motivation for the topic . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Thesis scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.3 Relation to specialization project . . . . . . . . . . . . . . . . . . . 31.4 Thesis outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2 resource assessment 52.1 Explanation and description of the case study . . . . . . . . . . . 52.2 Acquiring solar irradiance data . . . . . . . . . . . . . . . . . . . . 6

2.2.1 Note on terminology . . . . . . . . . . . . . . . . . . . . . . 62.2.2 Satellite measurements . . . . . . . . . . . . . . . . . . . . . 102.2.3 Ground measurements . . . . . . . . . . . . . . . . . . . . . 12

2.3 Acquiring temperature data . . . . . . . . . . . . . . . . . . . . . . 133 consumption assessment 17

3.1 Tools for estimating load-profiles . . . . . . . . . . . . . . . . . . . 173.1.1 Analytical model . . . . . . . . . . . . . . . . . . . . . . . . 183.1.2 Simplified model . . . . . . . . . . . . . . . . . . . . . . . . 19

3.2 Estimation of load-profile . . . . . . . . . . . . . . . . . . . . . . . 193.3 Load profile - Annual features . . . . . . . . . . . . . . . . . . . . 24

4 investigating economic feasibility 294.1 Loss of Load probability as reliability parameter . . . . . . . . . . 294.2 Evaluating system Net Present Cost . . . . . . . . . . . . . . . . . 33

5 optimization tools 355.1 Existing optimization tools . . . . . . . . . . . . . . . . . . . . . . 35

5.1.1 HOMER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355.1.2 BlueSol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365.1.3 RETScreen . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375.1.4 PVSyst . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375.1.5 RAPSim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375.1.6 The novel sizing methodology . . . . . . . . . . . . . . . . 38

5.2 Concluding remarks - optimization tools . . . . . . . . . . . . . . 386 analysis of designed system 41

6.1 Evaluation and clarification of input data . . . . . . . . . . . . . . 416.1.1 Verification of solar-data . . . . . . . . . . . . . . . . . . . . 416.1.2 Economic variables . . . . . . . . . . . . . . . . . . . . . . . 43

6.2 System comparison and conclusions . . . . . . . . . . . . . . . . . 437 time domain model of optimized microgrid 49

7.1 Long term - Yearly simulation . . . . . . . . . . . . . . . . . . . . . 49

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vi contents

7.2 Time domain responses from measured case . . . . . . . . . . . . 507.2.1 System model components and composition . . . . . . . . 507.2.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

8 conclusions and further work 59a applications to other systems 61

a.1 Bangladesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61b measured consumption from cst 65

b.1 Measurement equipment and set-up . . . . . . . . . . . . . . . . . 65b.2 Results - energy consumption . . . . . . . . . . . . . . . . . . . . . 66b.3 Evaluation of initial assumptions compared to real case . . . . . . 68

bibliography 73

L I S T O F F I G U R E S

Figure 2.1 Areal view of CST . . . . . . . . . . . . . . . . . . . . . . . 7Figure 2.2 Solar-radiation components . . . . . . . . . . . . . . . . . 9Figure 2.3 Satellite orbits - Geostationary orbit . . . . . . . . . . . . 11Figure 2.4 Satellite orbits - Geostationary and polar orbit . . . . . . 12Figure 3.1 Shifted loads and irradiance . . . . . . . . . . . . . . . . . 18Figure 3.2 Application operation window . . . . . . . . . . . . . . . 20Figure 3.3 Synthesized load profile . . . . . . . . . . . . . . . . . . . 23Figure 3.4 Seasonal variation of power-consumption . . . . . . . . . 25Figure 3.5 Monthly power consumption at CST . . . . . . . . . . . . 26Figure 3.6 Seasonal variation of synthesized load . . . . . . . . . . . 27Figure 4.1 Loss of Load Probability to Net Present Cost . . . . . . . 30Figure 4.2 SAIDI in European countries . . . . . . . . . . . . . . . . 31Figure 6.1 Irradiance ground- and satellite-measurements . . . . . . 42Figure 6.2 Synthesized and measured load-profile . . . . . . . . . . 44Figure 6.3 Weather data from Phuentsholing, Bhutan . . . . . . . . 45Figure 6.4 Optimal system results . . . . . . . . . . . . . . . . . . . . 47Figure 7.1 Synthesized and measured load-profile . . . . . . . . . . 51Figure 7.2 System layout for the 24h model . . . . . . . . . . . . . . 52Figure 7.3 PV-array layout in 24h model . . . . . . . . . . . . . . . . 53Figure 7.4 Control loop for inverter . . . . . . . . . . . . . . . . . . . 55Figure 7.5 System phase-voltages . . . . . . . . . . . . . . . . . . . . 57Figure 7.6 FFT analysis for the 24 hour simulation . . . . . . . . . . 58Figure A.1 Synthesized load for Bangladesh-case . . . . . . . . . . . 63Figure B.1 Voltage masurements at CST . . . . . . . . . . . . . . . . 66Figure B.2 Power consumption measurement setup . . . . . . . . . . 67Figure B.3 Measured power consumption, Block E . . . . . . . . . . 67Figure B.4 Measured consumption at CST . . . . . . . . . . . . . . . 69Figure B.5 Averaged daily profiles from measurements . . . . . . . 70

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L I S T O F TA B L E S

Table 2.1 Test-conditions for PV-cells . . . . . . . . . . . . . . . . . 14Table 3.1 Input data for load-profile . . . . . . . . . . . . . . . . . . 19Table 3.2 Schematic representation of operating hours . . . . . . . 20Table 3.3 Electrical appliances in student hostel . . . . . . . . . . . 21Table 3.4 Electrical consumption per hostel-block . . . . . . . . . . 22Table 6.1 Assumed component cost . . . . . . . . . . . . . . . . . . 43Table 6.2 Optimal system composition . . . . . .