模型预测控制
控制理论(社会学)
能源管理
能量(信号处理)
最优控制
作者
Shangshang Wei,Xianhua Gao,Yi Zhang,Yiguo Li,Jiong Shen,Zuyi Li
出处
期刊:Energy
[Elsevier]
日期:2021-11-15
卷期号:235: 121320-
被引量:2
标识
DOI:10.1016/j.energy.2021.121320
摘要
Abstract Economy, robustness and computational efficiency are of paramount metrics for an operation strategy of an integrated energy system (IES). To achieve the trade-off of the three metrics, a multi-layer framework is extensively exploited in existing operation strategies. This work, however, proposes a single-layer multi-timescale framework which can coordinate different operation performances associated with various timescales simultaneously. Based on the framework, an improved stochastic model predictive control (SMPC) operation strategy is further developed by embedding the proposed framework into its prediction horizon. To solve the multi-timescale optimization of the improved SMPC, the constraints and cost function are presented in the multi-timescale form, and the supplied and demands are forecast by the least square support vector machine. A simulator of an IES is thereafter constructed to mimic real system and used to evaluate the performance of the proposed strategy by operation cost, accumulative error and computation time with respect to economy, robustness and computational efficiency, respectively. Finally, the improved SMPC strategy is compared with a traditional single-layer and a hierarchical strategy by a case study. The results show that the improved strategy has the best tradeoff performance aforementioned. The multi-timescale framework can be also integrated into other operation strategies.
科研通智能强力驱动
Strongly Powered by AbleSci AI