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Peak Load Scheduling in Smart Grid Communication Environment

Authors: Mahnoor Khan; Nadeem Javaid; S. Saud; Umar Qasim; Muhammad Arif; Zahoor Ali Khan;

Peak Load Scheduling in Smart Grid Communication Environment

Abstract

In this paper, we consider an Energy Consumption Scheduler (ECS) unit inside a smart meter. The function of ECS is to flatten the peaks in the load curve of residential type users. The ECS dually communicates with the user as well as power utility in smart grid real time communication environment. Each user has a specific power capacity limit for their appliances operation. The ECS keeps check and balance condition whenever a user exceeds its power capacity limit. Also the most urgent appliance operations are given priority based on their internalpreemption state. By adopting ECS unit, the total peaks in the load curve are reduced up to 33.3%. Also the user's payment to the power utility becomes less due to efficiently managing their appliance operations. Additionally, the cost of per unit energy generation is also reduced by avoiding the peak power plants. Matlab/Simulink is used as a simulation tool for the realization of this model.

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    citations
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    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.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Found an issue? Give us feedback
citations
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!
10
Top 10%
Top 10%
Average