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https://doi.org/10.17559/TV-20251017003074

Interval-Based Robust Optimisation Scheduling for Integrated Energy Systems Considering Energy Storage Lifespan and Flexible Thermal Load Response

Haoyu Mao ; College of Information Engineering, Nanchang University, Nanchang 330031, Jiangxi, China *

* Dopisni autor.


Puni tekst: engleski pdf 2.283 Kb

str. 1161-1174

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Sažetak

The widespread adoption of renewable energy within integrated energy systems introduces significant uncertainty, posing challenges to their stable and economical operation. Mitigating the costly degradation of electrochemical energy storage equipment while effectively managing fluctuations on both the generation and load sides has become a critical issue. Against this backdrop, this paper proposes a scheduling framework integrating interval-type robust optimisation with a two-layer model predictive control approach. During the day-ahead planning phase, an interval-type robust scheduling model is constructed. This model employs k-means clustering to partition uncertainty sets for renewable generation and load demand, thereby circumventing the excessive conservatism inherent in traditional robust optimisation. For the intraday phase, a two-layer model predictive control framework is established to smooth the rolling optimisation time scale differences across electricity, heat, gas, and hydrogen loads. Concurrently, a storage lifetime cost term is incorporated into the optimisation objective to extend the energy storage system's lifespan. This is combined with an electricity price-based demand response model to enhance scheduling flexibility. Simulation results demonstrate the proposed method's multifaceted advantages. Compared to conventional robust optimisation, the interval-based robust optimisation model maintains high user satisfaction (96.43%) while reducing average daily system operating costs by approximately 8.24% and lowering the monthly capacity degradation rate of the energy storage system from 1.831% to 1.617%. The intraday robust model predictive control (MPC) demonstrated robust performance under extreme scenarios, with total cost increases of merely 2.91%, significantly lower than the 16.23% observed in conventional MPC. The proposed scheduling strategy, integrating interval robust optimisation with model predictive control, offers an effective solution for addressing robustness, economic efficiency, and equipment lifespan management within integrated energy systems under renewable energy and load uncertainty.

Ključne riječi

demand side response; energy storage device ageing; integrated energy system scheduling; interval-based robust optimisation; model predictive control

Hrčak ID:

346728

URI

https://hrcak.srce.hr/346728

Datum izdavanja:

30.4.2026.

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