DOI:10.1007/s40565-018-0389-1 |
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Optimal dynamic pricing for smart grid having mixed customers with and without smart meters |
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Net amount: 679 |
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Author:
Qian MA1, Fanlin MENG2, Xiao-Jun ZENG1
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Author Affiliation:
1. School of Computer Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK
2. School of Mathematics, University of Edinburgh, Edinburgh EH9 3FD, UK
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Foundation: |
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Abstract: |
This paper investigates an optimal day-ahead
dynamic pricing problem in an electricity market with
one electricity retailer and multiple customers. The main
objective of this paper is to support the retailer to make
the best day-ahead dynamic pricing decision, which
maximizes its profit under the realistic assumption that
mixed types of customers coexist in the electricity
market where some customers have installed smart
meters with the embedded home energy management
system in their home whereas other customers have not
installed smart meters. To this end, we propose a hybrid
demand modelling framework which firstly uses an
optimal energy management algorithm with bill minimization
to model the behavior of customers with smart
meters and secondly use a data-driven demand modelling
method to model the behavior of customers without
smart meters. Such a hybrid demand model can not only
schedule usages of home appliances to the interests of
customers with smart meters but also be used to
understand electricity usage behaviors of customers
without smart meters. Based on the established hybrid
demand model for all customers, a profit maximization
algorithm is developed to achieve optimal prices for the
retailer under relevant market constraints. Under the
condition of no growth of the revenue (i.e. no increase of
total bill from all customers), simulation results indicate
our optimization algorithm can improve the profit for
around 5% on average. |
Keywords: |
Demand response management, Day-ahead
dynamic pricing optimization, Demand modelling |
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Online Time:2018/11/11 |
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