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Title: Optimizing dispatch for a concentrated solar power tower

Abstract

Concentrating solar power (CSP) systems employ a sophisticated thermal receiver, power cycle, and a heliostat field, comprised of thousands of mirrors spread over hundreds of acres of land, and are most cost-effective with relatively large quantities of energy storage which can be scheduled for dispatch. We exercise an existing optimization model that maximizes revenue over a year-long time horizon, solved using a standard 48-h look-ahead policy at hourly fidelity on a CSP system under development in California. The system employs molten salt power tower technology with a 150 MWe (net) turbine, eight hours of thermal storage at full load, and a solar field that provides 1.75 times the rated turbine thermal power. The model considers system configuration and interoperability aspects, such as storage tank size, production capacities, and ramp rates, and determines decisions that expedite financing, permitting, and plant design. Relative to results achieved via industry practice, the existing optimization model reduces the number of power cycle (i.e., turbine) start-up events by 86.4%, thereby improving net revenue by more than 8.5% annually; this corresponds to an approximately $140 M increase in net revenue over the lifetime of the plant, taking a step towards advancing the long-term economic viability of large-scalemore » renewable energy systems. Sensitivity analysis on uncertain parameter values provides insight regarding those values that influence profit most significantly.« less

Authors:
 [1];  [2];  [2];  [3];  [3];  [2]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. Colorado School of Mines, Golden, CO (United States)
  3. SolarReserve, Santa Monica, CA (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1483063
Report Number(s):
NREL/JA-5500-72838
Journal ID: ISSN 0038-092X
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Solar Energy
Additional Journal Information:
Journal Volume: 174; Journal Issue: C; Journal ID: ISSN 0038-092X
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; 47 OTHER INSTRUMENTATION; concentrated solar power; dispatch scheduling; optimization applications

Citation Formats

Wagner, Michael J., Hamilton, William T., Newman, Alexandra, Dent, Jolyon, Diep, Charles, and Braun, Robert. Optimizing dispatch for a concentrated solar power tower. United States: N. p., 2018. Web. doi:10.1016/j.solener.2018.06.093.
Wagner, Michael J., Hamilton, William T., Newman, Alexandra, Dent, Jolyon, Diep, Charles, & Braun, Robert. Optimizing dispatch for a concentrated solar power tower. United States. doi:10.1016/j.solener.2018.06.093.
Wagner, Michael J., Hamilton, William T., Newman, Alexandra, Dent, Jolyon, Diep, Charles, and Braun, Robert. Fri . "Optimizing dispatch for a concentrated solar power tower". United States. doi:10.1016/j.solener.2018.06.093.
@article{osti_1483063,
title = {Optimizing dispatch for a concentrated solar power tower},
author = {Wagner, Michael J. and Hamilton, William T. and Newman, Alexandra and Dent, Jolyon and Diep, Charles and Braun, Robert},
abstractNote = {Concentrating solar power (CSP) systems employ a sophisticated thermal receiver, power cycle, and a heliostat field, comprised of thousands of mirrors spread over hundreds of acres of land, and are most cost-effective with relatively large quantities of energy storage which can be scheduled for dispatch. We exercise an existing optimization model that maximizes revenue over a year-long time horizon, solved using a standard 48-h look-ahead policy at hourly fidelity on a CSP system under development in California. The system employs molten salt power tower technology with a 150 MWe (net) turbine, eight hours of thermal storage at full load, and a solar field that provides 1.75 times the rated turbine thermal power. The model considers system configuration and interoperability aspects, such as storage tank size, production capacities, and ramp rates, and determines decisions that expedite financing, permitting, and plant design. Relative to results achieved via industry practice, the existing optimization model reduces the number of power cycle (i.e., turbine) start-up events by 86.4%, thereby improving net revenue by more than 8.5% annually; this corresponds to an approximately $140 M increase in net revenue over the lifetime of the plant, taking a step towards advancing the long-term economic viability of large-scale renewable energy systems. Sensitivity analysis on uncertain parameter values provides insight regarding those values that influence profit most significantly.},
doi = {10.1016/j.solener.2018.06.093},
journal = {Solar Energy},
issn = {0038-092X},
number = C,
volume = 174,
place = {United States},
year = {2018},
month = {10}
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on October 26, 2019
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