Genetic-programming-based multi-objective optimization of strategies for home energy-management systems
Created by W.Langdon from
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- @Article{ZUPANCIC:2020:Energy,
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author = "Jernej Zupancic and Bogdan Filipic and Matjaz Gams",
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title = "Genetic-programming-based multi-objective optimization
of strategies for home energy-management systems",
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journal = "Energy",
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volume = "203",
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pages = "117769",
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year = "2020",
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ISSN = "0360-5442",
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DOI = "doi:10.1016/j.energy.2020.117769",
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URL = "http://www.sciencedirect.com/science/article/pii/S0360544220308768",
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keywords = "genetic algorithms, genetic programming, Home
energy-management system (HEMS), Multi-objective
optimization, Tree-based strategy, Timetable-based
strategy, Multi-objective reinforcement learning
(MORL)",
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abstract = "Home energy-management systems can optimize
performance either by computing the next step
dynamically - online, or rely on a precomputed strategy
used to introduce the next decision - offline. Further,
such systems can optimize based on only one or several
objectives. In this paper, the multi-objective
optimization of offline strategies for home
energy-management systems is addressed. Two approaches
are compared: the common timetable-based versus our
approach based on decision trees. The timetable-based
strategy is optimized using a multi-objective genetic
algorithm, while the tree-based strategy is optimized
using multi-objective genetic programming. As a result,
a set of rules that comprise the trees for efficient
management of an energy system is generated
automatically. First, the approaches are addressed
theoretically, with the finding that the tree-based
approach is more powerful than the timetable-based
approach. Second, the performance of the tree-based
approach is compared with the performance of the
timetable-based approach and manually defined
strategies in an experiment involving real-world data.
A performance increase of up to 17percent in terms of
the cost objective was confirmed for the tree-based
approach. This is achieved without changing the user
habits, i.e., there is no need of having to adapt the
appliance usage to the energy-management system",
- }
Genetic Programming entries for
Jernej Zupancic
Bogdan Filipic
Matjaz Gams
Citations