Analysis on demand-side interactive response capability for power system dispatch in a smart grid framework
► A mechanism is proposed to reflect the process of demand-side interactive response. ► A standard data format is defined to formulate the submission of DIRC. ► A fuzzy-C-mean clustering method is implemented to analyse historical data. ► A correction method based on similarity identification is dev...
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Published in | Electric power systems research Vol. 90; pp. 11 - 17 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Amsterdam
Elsevier B.V
01.09.2012
Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | ► A mechanism is proposed to reflect the process of demand-side interactive response. ► A standard data format is defined to formulate the submission of DIRC. ► A fuzzy-C-mean clustering method is implemented to analyse historical data. ► A correction method based on similarity identification is developed.
In a smart grid framework, relations between the system operator (SO) and terminal consumers will become interactive and demand-side response capacities can be integrated as dispatch-able resources. This paper proposes a systematic analysis on demand-side response mechanism in smart grid. A multi-agent (MA) system is established to describe interactive relations between the SO and different kinds of consumers. On this basis, a novel mechanism is proposed to reflect the process of interactive response, which consists of three schemes: data clustering and release scheme, demand-side interactive response capability (DIRC) submission scheme, and submission correction scheme. Then, a standard data format is defined to formulate the submission of DIRC from basic consumers and a fuzzy-C-mean clustering method is implemented to generate and release typical interactive response modes (IRM) for different kinds of consumers. Moreover, a correction method based on similarity identification is developed to modify submission of DIRC by taking into account deviations between historical submissions and real performances. Finally, a simulation case verifies the effectiveness and rationality of the proposed mechanism, models and methods. |
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ISSN: | 0378-7796 1873-2046 |
DOI: | 10.1016/j.epsr.2012.03.013 |