期刊
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
卷 10, 期 2, 页码 905-917出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2018.2854662
关键词
Energy storage; Markov decision processes; multi-timescale energy management; renewable energy sources; stochastic optimization
资金
- Pomphrey Industries Corporation
- Mitacs Accelerate program
- Natural Sciences and Engineering Research Council of Canada
In this paper, we propose a stochastic multi-timescale energy management scheme of greenhouses with renewable energy sources (RES), including a photovoltaic (PV) system, combined heat and power (CHP) unit, and energy storage systems. The optimal energy management problem is formulated as a multi-timescale Markov decision process to address the randomness of RES and the outside weather conditions. In particular, a fast-timescale process is used to model the rapidly changing electrical process with fine granularity, while a slow-timescale process is used to model the gradually varying thermal process to reduce the computational complexity. Exact solution of the optimal energy management problem is derived to minimize the cost of green-house operation. To further reduce the computational complexity of finding the optimal energy management policy, an approximation solution is also derived. The proposed energy management scheme is evaluated based on a commercial greenhouse structure from Bonnyville Forest Nursery, Inc. for spruce, as well as real data of weather conditions, PV generation, CHP unit, and energy storage systems.
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