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Model Predictive Control Technique for Energy Optimization in Residential Sector

Title
Model Predictive Control Technique for Energy Optimization in Residential Sector
Type
Article in International Conference Proceedings Book
Year
2016
Authors
Godina, R
(Author)
Other
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Rodrigues, EMG
(Author)
Other
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Pouresmaeil, E
(Author)
Other
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Matias, JCO
(Author)
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Conference proceedings International
IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)
Florence, ITALY, JUN 07-10, 2016
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Authenticus ID: P-00K-XKX
Abstract (EN): Over the years the energy needs have increased dramatically and we have become aware that our needs were and are having implications on the environment in which we live. Increasingly people are aware to saving electricity by turning off the equipment that is not been used, or connect electrical loads just outside the on-peak hours. However, these few efforts are not enough to reduce the global energy consumption, which is increasing. Regarding the field of optimization, researchers throughout the world have been making an effort in introducing better control schemes, both in industry and domestic sectors, for all types of loads from small lamps to large motors. Much of the reduction was due to mechanical improvements; however, with the advancing of the years' new types of control arise. All these factors provide a motive in this paper for introducing a new consumption reduction method in some residential loads via the implementation of Model Predictive Control ( MPC). A single cost function is required to set the reference output near the goal, and consequently through the variation of this cost function by changing the weights, thus specific control actions have priority over the remaining actions. Therefore, it is possible to have different goals during the day, determining the possible savings for each appliance that can be made during on-peak, mid-peak, off-peak and by providing simulations upon 24 hours in the household.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 6
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