@Article{ee.2026.079755,
AUTHOR = {Zhi Xu, Min Ren, Zhiwei Yuan, He Jiang, Risheng Qin, Xinze Xi, Yinfeng Ma},
TITLE = {Multi-Time-Scale Optimization of Rural Integrated Energy Systems Based on Whole-Process Dynamic Simulation under Complex Operating Conditions},
JOURNAL = {Energy Engineering},
VOLUME = {},
YEAR = {},
NUMBER = {},
PAGES = {{pages}},
URL = {http://www.techscience.com/energy/online/detail/26407},
ISSN = {1546-0118},
ABSTRACT = {The integration of high-penetration renewable energy and multi-energy loads introduces significant volatility and complexity into the operation of Rural Integrated Energy Systems (RIES). To address the challenges of ensuring economic efficiency and operational resilience, this paper proposes a novel multi-time-scale optimization framework grounded in a whole-process dynamic simulation. Initially, a dynamic simulation model is developed to accurately capture system behavior under typical rural disturbance scenarios. This model underpins a two-stage scheduling strategy: a day-ahead steady-state plan aimed at global economic optimization, followed by an intra-day rolling optimization that leverages real-time data to correct forecast deviations. The core innovation lies in a steady-state-dynamic hybrid simulation mechanism, integrated with an adaptive convex relaxation strategy. The hybrid mechanism facilitates seamless coupling of energy conversion, storage, and transmission by explicitly modeling equipment dynamic responses. To resolve the computational intractability of the original Mixed-Integer Nonlinear Programming (MINLP) problem, it is transformed into a computationally efficient Second-Order Cone Programming (SOCP) model via a convex relaxation technique, which is then solved using the SCS solver. This approach balances engineering accuracy and computational efficiency, enabling real-time scheduling of RIES under complex operating conditions. The proposed strategy presents a viable and robust solution for achieving secure, efficient, and low-carbon operation of RIES.},
DOI = {10.32604/ee.2026.079755}
}