Abstract
Microgrids are suitable electrical solutions for providing energy in rural zones. However, it is challenging to propose in advance a good design of the microgrid because the electrical load is difficult to estimate due to its highly dependence of the residential consumption. In this paper, a novel estimation methodology for the residential load profiles is proposed. Socio-demographic data and electrical power consumption are used to generate significant knowledge about the load behavior. Socio-demographic data are used as input for a neural network called Self-Organizing Maps (SOM). The SOM proposes a way to group dwelling according to their different features. Moreover, a probabilistic model based on Bayesian networks incorporates daily variations of the electrical load, simulating the behavior of the electrical appliances. The methodology, as a whole, is applied to a case study in a rural community located in Chile. The methodology is easily adaptable to other rural communities.
Original language | English |
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Title of host publication | 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America). Quito, Ecuador |
Publisher | IEEE |
Number of pages | 6 |
ISBN (Electronic) | 978-1-5386-3312-0 |
Publication status | Published - 2017 |
Event | 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America - JW Marriott Hotel, Quito, Ecuador Duration: 20 Sept 2017 → 22 Sept 2017 http://ieee-isgt-latam.org/files/2017/08/Technical-Program_IEEE_ISGT_LA_2017.pdf |
Conference
Conference | 2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America |
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Abbreviated title | 2017 ISGT Latin America |
Country/Territory | Ecuador |
City | Quito |
Period | 20/09/17 → 22/09/17 |
Internet address |
Keywords
- Microgrids
- residential load profiles
- rural communities