1. State Key Laboratory of Advanced Electromagnetic Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology,Wuhan,China
2. School of Engineering, Cardiff University,Cardiff,UK
3. Contribution: Conceptualization, Methodology, Software, Writing - original draft, Writing - review & editing, Validation, Visualization, Formal analysis, Data curation, Investigation
4. PetroChina ShenZhen New Energy Research Institute Co., Ltd.,Shenzhen,China
5. Contribution: Writing - review & editing, Conceptualization, Resources
6. Contribution: Supervision, Project administration, Writing - original draft, Writing - review & editing
7. Contribution: Supervision, Writing - original draft, Writing - review & editing
8. Contribution: Writing - review & editing, Writing - original draft
9. PipeChina South China Company,Guangzhou,China
10. Contribution: Resources, Funding acquisition
11. CET Electric Technology Inc.,Shenzhen,China
12. Contribution: Software, Data curation, Resources
13. Contribution: Data curation, Investigation
14. Contribution: Software
15. Contribution: Software, Data curation, Investigation
纸质出版:2025
移动端阅览
Shengshi Wang, Danji Huang, Jiakun Fang, 等. Towards Continuous-Time Safe Energy Management in Shared Renewables and Refined Oil Transmission Systems[J]. Energy Internet, 2025,2(2).
Shengshi Wang, Danji Huang, Jiakun Fang, et al. Towards Continuous-Time Safe Energy Management in Shared Renewables and Refined Oil Transmission Systems[J]. Energy Internet, 2025, 2(2).
Shengshi Wang, Danji Huang, Jiakun Fang, 等. Towards Continuous-Time Safe Energy Management in Shared Renewables and Refined Oil Transmission Systems[J]. Energy Internet, 2025,2(2). DOI: 10.1049/ein2.12024.
Shengshi Wang, Danji Huang, Jiakun Fang, et al. Towards Continuous-Time Safe Energy Management in Shared Renewables and Refined Oil Transmission Systems[J]. Energy Internet, 2025, 2(2). DOI: 10.1049/ein2.12024.
This paper investigates the safe energy management of emerging shared renewables and refined oil transmission systems (SRROTSs) during the energy transition. Specifically
a continuous-time energy management model that considers the SRROTSs' multi-product sequential transmission characteristics is proposed to guide safe and efficient system operation. This model is also convenient for on-site dispatchers to operate. Correspondingly
a solver-free physics-informed particle swarm optimisation (PI-PSO) algorithm is tailored
utilising physical rules to regulate particle mutation and adapted to solve the proposed model
thereby enhancing the optimality and stability of the solution. Case studies on real-world SRROTSs are utilised to validate the proposed model and PI-PSO algorithm
which are expected to be generalised to other pipeline transmission systems. Especially
the PI-PSO algorithm achieves a 25.6% energy reduction compared to the original PSO algorithm
although a trade-off between improving the objective value and the number of iterations needed for convergence is observed.
0
浏览量
0
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621