Load estimation based on self-organizing maps and bayesian networks for microgrid design in rural zones

Load estimation based on self-organizing maps and bayesian networks for microgrid design in rural zones

Caquilpan, V. (Universidad de Santiago de Chile)
Sáez, Doris (Universidad de Santiago de Chile)
Hernández, Roberto (Universidad de Santiago de Chile)
Llanos, Jacqueline (Universidad de Santiago de Chile)
Roje, T. (Universidad de Santiago de Chile)
Nunez, Alfredo (TU Delft Railway Engineering)

2017

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.

Microgrids
residential load profiles
rural communities

http://resolver.tudelft.nl/uuid:e09b73a1-e94a-45d6-a7fd-74846fd10e47

IEEE

978-1-5386-3312-0

2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America). Quito, Ecuador

2017 IEEE PES Innovative Smart Grid Technologies Conference - Latin America, 2017-09-20 → 2017-09-22, JW Marriott Hotel, Quito, Ecuador

Institutional Repository

conference paper

© 2017 V. Caquilpan, Doris Sáez, Roberto Hernández, Jacqueline Llanos, T. Roje, Alfredo Nunez