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Research Papers

A Methodology for Determining Optimum Solar Tower Plant Configurations and Operating Strategies to Maximize Profits Based on Hourly Electricity Market Prices and Tariffs

[+] Author and Article Information
Rafael Guédez

Department of Energy Technology,
Royal Institute of Technology,
Stockholm SE-100 44, Sweden
e-mail: rafael.guedez@energy.kth.se

Monika Topel

Department of Energy Technology,
Royal Institute of Technology,
Stockholm SE-100 44, Sweden
e-mail: monika.topel@energy.kth.se

Inés Conde

Gas Natural Fenosa Engineering,
Solar Energy and Biomass Unit,
Madrid 28045, Spain
e-mail: iconde@gasnaturalfenosa.com

Francisco Ferragut

Gas Natural Fenosa Engineering,
Solar Energy and Biomass Unit,
Madrid 28045, Spain
e-mail: ussolarybiomasaFFF@gasnaturalfenosa.com

Irene Callaba

Gas Natural Fenosa Engineering,
Solar Energy and Biomass Unit,
Madrid 28045, Spain
e-mail: icallaban@gasnaturalfenosa.com

James Spelling

High Temperature Processes Unit,
IMDEA Energy Institute,
Móstoles 28935, Spain
e-mail: james.spelling@outlook.com

Zhor Hassar

Concentrated Solar Technologies,
Total New Energies, R&D,
Paris 92069, France
e-mail: zhor.hassar@total.com

Carlos David Perez-Segarra

Heat and Mass Transfer Centre,
Technical University of Catalonia,
Terrassa 08222, Spain
e-mail: segarra@cttc.upc.edu

Björn Laumert

Department of Energy Technology,
Royal Institute of Technology,
Stockholm SE-100 44, Sweden
e-mail: bjorn.laumert@energy.kth.se

1Corresponding author.

Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received July 21, 2015; final manuscript received December 2, 2015; published online February 1, 2016. Assoc. Editor: Mary Jane Hale.

J. Sol. Energy Eng 138(2), 021006 (Feb 01, 2016) (12 pages) Paper No: SOL-15-1226; doi: 10.1115/1.4032244 History: Received July 21, 2015; Revised December 02, 2015

The present study analyzes the influence that market conditions have on determining optimum molten salt solar tower plants with storage that maximizes profits (in terms of plant configuration, sizing, and operation) for a location in South Africa. Three different scenarios based on incentive programs and local wholesale electricity prices are considered. A multi-objective optimization modeling approach was followed, showing the tradeoff curves between minimizing investment and maximizing profits when varying critical size-related parameters (such as nameplate capacity, solar multiple (SM), and storage capacity) together with power-cycle design and operating specifications including dynamic startup curves and different storage dispatchability strategies. Results are shown by means of a comparative analysis between optimal plants found for each scenario, highlighting the value that storage has under the current two-tier tariff scheme and the relevance of designing a suitable policy for technology development. Finally, a final analysis is performed with regard to the indicators used for economic evaluation of power plants, by comparing the differences between optimum designs found when using the levelized cost of electricity (LCoE) solely as performance indicator instead of cash-flows and profit-based indicators, such as the internal rate of return (IRR).

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Figures

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Fig. 1

Schematic flowsheet of the STPP

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Fig. 2

Schematics of information flow in DYESOPT for multi-objective optimization analysis

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Fig. 3

Market scenarios for typical winter week

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Fig. 4

Logical control for determining peaking hours

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Fig. 5

Logical dispatch controlling for TES

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Fig. 6

IRR–CAPEX tradeoffs and influence of gross power for all scenarios considered

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Fig. 7

Storage and SF size influence on overall IRR results for all scenarios

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Fig. 8

Storage dispatch strategy influence on IRR–CAPEX tradeoffs for all scenarios

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Fig. 9

CAPEX–LCoE tradeoff for S1

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