Multi-objective optimization of parabolic trough concentrated solar power with thermal energy storage plant parameters using elitist nondominated sorting genetic Algorithm

Issue Date

11-2020

Abstract

Large-scale concentrated solar power (CSP) with thermal energy storage (TES) is the most viable option in a centralized generation for a sustainable energy system. To have a successful CSP-TES plant operation, selecting the best plant configuration is deemed necessary. Thus, this study presented a flexible method to determine the optimal plant parameters while considering the electricity demand curve of the location. Modeling and performance simulation were done in the System Advisor Model. Elitist Nondominated Sorting Genetic Algorithm of MATLAB was used to solve the multi-objective optimization problem. Results showed the optimal performance of the plant in terms of its energy, economic, and environmental aspects. Also, it was established that the parabolic trough CSP-TES plant can provide high electrical output to meet peak demands during nighttime.

Source or Periodical Title

IEEE Region 10 Annual International Conference, Proceedings/TENCON

ISSN

2159-3442

Page

314-319

Document Type

Conference Paper

Language

English

Subject

Concentrated solar power, Entropy-based TOPSIS, Multi-objective optimization, NSGA-II, Thermal energy storage

Identifier

doi: 10.1109/TENCON50793.2020.9293735

Digital Copy

yes

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