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Real-time dispatch optimization for concentrating solar power with thermal energy storage

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Abstract

Concentrating solar power (CSP) plants present a promising path towards utility-scale renewable energy. The power tower, or central receiver, configuration can achieve higher operating temperatures than other forms of CSP, and, like all forms of CSP, naturally pairs with comparatively inexpensive thermal energy storage, which allows CSP plants to dispatch electricity according to market price incentives and outside the hours of solar resource availability. Currently, CSP plants commonly include a steam Rankine power cycle and several heat exchange components to generate high-pressure steam using stored thermal energy. The efficiency of the steam Rankine cycle depends on the temperature of the plant’s operating fluid, and so is a main concern of plant operators. However, the variable nature of the solar resource and the conservatism with which the receiver is operated prevent perfect control over the receiver outlet temperature. Therefore, during periods of solar variability, collection occurs at lower-than-design temperature. To support operator decisions in a real-time setting, we develop a revenue-maximizing non-convex mixed-integer, quadradically-constrained program which determines a dispatch schedule with sub-hourly time fidelity and considers temperature-dependent power cycle efficiency. The exact nonlinear formulation proves intractable for real-time decision support. We present exact and inexact techniques to improve problem tractability that include a hybrid nonlinear and linear formulation. Our approach admits solutions within approximately 3% of optimality, on average, within a five-minute time limit, demonstrating its usability for decision support in a real-time setting.

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Acknowledgements

This material is based upon work supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under the Solar Energy Technologies Office Award Number 34245. This paper was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe on privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

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Authors and Affiliations

  1. Operations Research with Engineering Graduate Program, Colorado School of Mines, 1500 Illinois St., Golden, CO, 80401, USA

    John L. Cox & Alexandra M. Newman

  2. Thermal Sciences Group, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO, 80401, USA

    William T. Hamilton & Alex J. Zolan

  3. Department of Mechanical Engineering, University of Wisconsin-Madison, 1500 Engineering Drive, Madison, WI, 53706, United States

    Michael J. Wagner

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Correspondence to Alexandra M. Newman.

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Cox, J.L., Hamilton, W.T., Newman, A.M. et al. Real-time dispatch optimization for concentrating solar power with thermal energy storage. Optim Eng 24, 847–884 (2023). https://doi.org/10.1007/s11081-022-09711-w

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