期刊
IEEE TRANSACTIONS ON POWER SYSTEMS
卷 37, 期 2, 页码 1264-1273出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2021.3099336
关键词
Real-time systems; Microgrids; Processor scheduling; Cost function; State of charge; Load modeling; Dynamic scheduling; Microgrid; real-time scheduling; two-layer scheduling; future cost function
资金
- National Key R&D Program of China [2018YFA0702200]
- Fundamental Research Funds of Shandong University [TPWRS-00122-2021]
This paper proposes a two-layer real-time scheduling model for optimizing microgrid operations based on future cost function. The effectiveness of the model is validated through experiments.
Microgrids incorporate an increasing number of distributed energy resources (DERs), which induce a higher variability and faster dispatch capabilities in power systems. This paper proposes a two-layer real-time scheduling model for microgrids, based on approximate future cost function (AFCF), where the future cost represents the opportunity cost for the microgrid operation in subsequent periods. At the upper layer, the look-ahead rolling scheduling is adopted to optimize microgrid operations, in which the future cost function (FCF) in deterministic and stochastic scenarios is approximated by a piecewise linear function. At the lower layer, a real-time parameter updating strategy based on real-time data is proposed. In this case, the real-time scheduling readjusts the look-ahead schedule using the immediate cost in the current period and the future cost calculated by the updated AFCF. The proposed two-layer real-time scheduling model uses an offline optimization, in which most of the computation tasks are completed at the upper layer, and applies a real-time optimization, in which the time-consuming problem is avoided at the lower layer. The effectiveness of the proposed two-layer real-time scheduling model of microgrids is validated by using a grid-connected microgrid system. For comparison, other existing real-time scheduling methods are also implemented in the same microgrid system.
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