LAPSE:2019.0014
Published Article
LAPSE:2019.0014
Combined Two-Stage Stochastic Programming and Receding Horizon Control Strategy for Microgrid Energy Management Considering Uncertainty
Zhongwen Li, Chuanzhi Zang, Peng Zeng, Haibin Yu
January 7, 2019
Microgrids (MGs) are presented as a cornerstone of smart grids. With the potential to integrate intermittent renewable energy sources (RES) in a flexible and environmental way, the MG concept has gained even more attention. Due to the randomness of RES, load, and electricity price in MG, the forecast errors of MGs will affect the performance of the power scheduling and the operating cost of an MG. In this paper, a combined stochastic programming and receding horizon control (SPRHC) strategy is proposed for microgrid energy management under uncertainty, which combines the advantages of two-stage stochastic programming (SP) and receding horizon control (RHC) strategy. With an SP strategy, a scheduling plan can be derived that minimizes the risk of uncertainty by involving the uncertainty of MG in the optimization model. With an RHC strategy, the uncertainty within the MG can be further compensated through a feedback mechanism with the lately updated forecast information. In our approach, a proper strategy is also proposed to maintain the SP model as a mixed integer linear constrained quadratic programming (MILCQP) problem, which is solvable without resorting to any heuristics algorithms. The results of numerical experiments explicitly demonstrate the superiority of the proposed strategy for both island and grid-connected operating modes of an MG.
Keywords
energy management, microgrid, recording horizon control, stochastic programming, uncertainty
Suggested Citation
Li Z, Zang C, Zeng P, Yu H. Combined Two-Stage Stochastic Programming and Receding Horizon Control Strategy for Microgrid Energy Management Considering Uncertainty. (2019). LAPSE:2019.0014
Author Affiliations
Li Z: Lab. of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; University of Chinese Academy of Sciences, Beijing 100049, China
Zang C: Lab. of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
Zeng P: Lab. of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
Yu H: Lab. of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
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Journal Name
Energies
Volume
9
Issue
7
Article Number
E499
Year
2016
Publication Date
2016-06-30
Published Version
ISSN
1996-1073
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Original Submission
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PII: en9070499, Publication Type: Journal Article
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LAPSE:2019.0014
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doi:10.3390/en9070499
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Jan 7, 2019
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Calvin Tsay
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