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IET Renewable Power Generation
Article . 2019 . Peer-reviewed
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Real‐time stochastic operation strategy of a microgrid using approximate dynamic programming‐based spatiotemporal decomposition approach

Authors: Jianquan Zhu; Xiemin Mo; Tao Zhu; Ye Guo; Tianyun Luo; Mingbo Liu;

Real‐time stochastic operation strategy of a microgrid using approximate dynamic programming‐based spatiotemporal decomposition approach

Abstract

This study focuses on the real‐time operation of a microgrid (MG). A novel approximate dynamic programming based spatiotemporal decomposition approach is developed to incorporate efficient management of distributed energy storage systems into MG real‐time operation while considering uncertainties in renewable generation. The original dynamic energy management problem is decomposed into single‐period and single‐unit sub‐problems, and the value functions are used to describe the interaction among the sub‐problems. A two‐stage procedure is further designed for the real‐time decisions of those sub‐problems. In the first stage, empirical data is utilised offline to approximate the value functions. Then in the second stage, each sub‐problem can make immediate and independent decision in both temporal and spatial dimensions to mitigate adverse effects of intermittent renewable generation in a MG. No central operator intervention is required, and the near optimal decisions can be obtained at a very fast speed. Case studies based on a six‐bus MG and an actual island MG are conducted to demonstrate the effectiveness of the proposed algorithm.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Top 10%
Top 10%
Top 10%
gold