A novel Traversal-and-Pruning algorithm for household load scheduling

► A novel Traversal-and-Pruning algorithm helps consumers create optimal load schedules both automatically and professionally. ► Both the payment and the comfort level are considered based on the nonlinear thermal dynamic. ► “Inferior Pruning” is defined to keep the balance between the speed and the...

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Bibliographic Details
Published in:Applied energy 2013-02, Vol.102, p.1430-1438
Main Authors: Wang, Chengshan, Zhou, Yue, Wang, Jidong, Peng, Peiyuan
Format: Article
Language:English
Subjects:
algorithms
Appliance commitment
appliances
Applied sciences
cost effectiveness
Economic data
Electric energy
Energy
Energy economics
Exact sciences and technology
General, economic and professional studies
Home energy management
Load scheduling
Methodology. Modelling
prices
pricing
pruning
Thermostatically controlled load
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Summary:► A novel Traversal-and-Pruning algorithm helps consumers create optimal load schedules both automatically and professionally. ► Both the payment and the comfort level are considered based on the nonlinear thermal dynamic. ► “Inferior Pruning” is defined to keep the balance between the speed and the optimality of the algorithm. ► In a case, about 20% electricity cost is saved under the same comfort settings compared to the original algorithm. ► The novel Traversal-and-Pruning algorithm is robust, fast and flexible as well. With the various detail pricing schemes designed by utilities and the development of the smart grid technologies, consumers are motivated and enabled to schedule their home appliances to save energy, reduce cost and help grid operation. This paper presents a novel Traversal-and-Pruning (TP) algorithm which schedules thermostatically controlled household loads to meet an optimization objective considering both payment and comfort settings. The novel TP algorithm is robust and a flexible method is developed to balance the optimality and speed of the algorithm. Simulation results show that an improved load schedule is obtained by the novel TP algorithm compared to an existing algorithm.
ISSN:0306-2619
1872-9118
DOI:10.1016/j.apenergy.2012.09.010