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This book presents a new approach to analytically find a better way to reducing peak demand loads. A typical university campus loads are considered and artificial neural network is used in the training of the original university data to design a controller which helps reschedule loads based on the period of occupancy of each building on campus. Results obtained are compared to when this method is not applied and the difference in terms of the overall power consumed plus cost-difference favours the use of artificial neural network.

Produktbeschreibung
This book presents a new approach to analytically find a better way to reducing peak demand loads. A typical university campus loads are considered and artificial neural network is used in the training of the original university data to design a controller which helps reschedule loads based on the period of occupancy of each building on campus. Results obtained are compared to when this method is not applied and the difference in terms of the overall power consumed plus cost-difference favours the use of artificial neural network.
Autorenporträt
Adewuyi Philip Adesola holds a Bachelor of Technology degree from Ladoke Akintola University of Technology, Nigeria. He is a student member of IEEE and also a member of International Association of Engineers(IAENG). He has published journal articles in peer-reviewed international journals and now a PG student at University of Lagos,Nigeria.