Data · dataset · 2025
Optimization of power control parameters for molten salt reactor based on multi-objective particle swarm optimization algorithm
Listed in ScienceDB
Abstract [Background] Molten Salt Reactors (MSRs), distinguished by their inherent safety and flexible deployment, have a wide range of applications in various scenarios.
Description
Power control system (PCS) plays a critical role in ensuring the safe and stable operation of MSRs. [Purpose] This study aims to develop an advanced controller gains tuning method for PCS to simultaneously regulate reactor fuel temperature and achieve rapid load-following performance, addressing the demands of future composite energy systems.
[Methods] The Proportional-Integral- Derivative (PID) controller, which is widely employed in reactor power control systems, is adopted to regulate the temperature and power of the Molten Salt Breeder Reactor (MSBR). A nonlinear model of the MSBR primary loop is developed using MATLAB/Simulink software. Based on the nonlinear model, Multi-Objective Particle Swarm Optimization (MOPSO) algorithm is adopted applied for tuning the controller gains.
Read the rest (2 more)
The sensitivity ratio deviation is introduced to automatically select Pareto-optimal solutions that balance competing control objectives. The tuned PID controllers are then evaluated under different working conditions. [Results] The results demonstrate that the tuned PID controllers with the MOPSO exhibit better load-following capability and achieve a balance between the power and temperature objectives.
The system effectively suppresses overshoot to within 2% under step-change conditions, while maintaining rapid response speed and strong anti-interference ability [Conclusions] The proposed MOPSO-based tuning method has been proved to be a viable and efficient approach for optimizing PID controllers in MSR power control systems
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.hjs.00374 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Physics · Social Science
- Inferred from text
- Chemical engineering 70%
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.hjs.00374 | 7 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:4004 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (70%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:physics | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |