Towards Continuous‐Time Safe Energy Management in Shared Renewables and Refined Oil Transmission Systems

ABSTRACT 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.

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Publication Details

Journal
Energy internet.
Published
2025-04-15
DOI
https://doi.org/10.1049/ein2.12024
Citations
1
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.73

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article

Towards Continuous‐Time Safe Energy Management in Shared Renewables and Refined Oil Transmission Systems

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1 citations
Energy internet.
Integrated Energy Systems Optimization
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article

Towards Continuous‐Time Safe Energy Management in Shared Renewables and Refined Oil Transmission Systems

Xiaomeng Ai, Yan Ge, Qicong Liu, Kun Mei, Jiakun Fang, Shichang Cui, Danji Huang, Shengshi Wang, Miao Li, Hao Li, Sen Li
article en
1 citations

Abstract

ABSTRACT 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.

Energy internet.Vol. 2(2)
Energy Research Institute (CN), Huazhong University of Science and Technology (CN), Cardiff University (GB)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 30%
Integrated Energy Systems Optimization
0.73
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