Mathematical Model for Economic Optimization of Tower-Type Solar Thermal Power Generation Systems via Coupled Monte Carlo Ray-Tracing and Multi-Mechanism Heat Loss Equations
Juanen Li,
Yao Chen and
Huanhao Su ()
Additional contact information
Juanen Li: Faculty of Arts and Sciences, Beijing Normal University, Beijing 519087, China
Yao Chen: Faculty of Arts and Sciences, Beijing Normal University, Beijing 519087, China
Huanhao Su: Faculty of Arts and Sciences, Beijing Normal University, Beijing 519087, China
Mathematics, 2025, vol. 13, issue 19, 1-45
Abstract:
With the global energy transition and decarbonization goals, tower-type solar thermal power generation is increasingly important for dispatchable clean energy due to its high efficiency, thermal storage capacity, and regulation performance. However, current research focuses on ideal conditions, ignoring real geographical constraints on heliostat layout and environmental impacts on receiver performance. More practical scene modeling and performance evaluation methods are urgently needed. To address these issues, we propose a heliostat field simulation algorithm based on heat loss mechanisms and real site characteristics. The algorithm includes optical performance evaluation (cosine efficiency, shading, truncation, atmospheric transmittance) and heat loss mechanisms (radiation, convection, conduction) for realistic net heat output estimation. Experiments revealed the following: (1) higher central towers improve optical efficiency by increasing solar elevation angle; (2) radiation losses dominate at high power and tower height, while convection losses dominate at low power and tower height. Using the Economic-Integrated Score (EIS) optimization algorithm, we achieved optimal tower and receiver configuration with 40.22% average improvement over other configurations (maximum 3.9× improvement). This provides a scientific design basis for improving tower-type solar thermal systems’ adaptability and economy in different geographical environments.
Keywords: solar thermal power; Monte Carlo ray-tracing; heat loss mechanisms; economic optimization; heliostat field optimization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/2227-7390/13/19/3132/pdf (application/pdf)
https://www.mdpi.com/2227-7390/13/19/3132/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:13:y:2025:i:19:p:3132-:d:1762100
Access Statistics for this article
Mathematics is currently edited by Ms. Emma He
More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().