NDLI: Adapted multilayer feedforward ANN based power management control of solar photovoltaic and wind integrated power system

Content Provider	IEEE Xplore Digital Library
Author	Kumaravel, S. Ashok, S.
Copyright Year	2011
Description	Author affiliation: Department of Electrical Engineering, National Institute of Technology Calicut, Kerala, India (Kumaravel, S.; Ashok, S.)
Abstract	This paper proposes a DC linked hybrid solar photovoltaic/wind energy system for stand-alone applications. Solar and wind energy are utilized as primary energy sources and battery unit is considered as storage to meet the primary load demand. Loads are considered according to their priority such as primary, deferrable and dump loads. Among these loads primary load is having highest priority. Ratings of hybrid energy system components such as solar PV, wind generator, battery unit, power electronic converter is optimally selected for the given load profile. Adapted multilayer feed forward artificial neural network structure is utilized to compute the maximum power developed by nonlinear and intermittent nature of solar and wind energy sources. An overall power management strategy is designed for the proposed system to manage power flows among the different energy sources, the storage unit and loads in the system. A simulation model for the hybrid energy system has been developed using MATLAB/Simulink. The system performance under different scenarios has been verified by carrying out simulation studies using a practical load demand profile and real weather data.
Starting Page	223
Ending Page	228
File Size	282030
Page Count	6
File Format	PDF
ISBN	9781467303163
e-ISBN	9781467303156
DOI	10.1109/ISET-India.2011.6145386
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-01
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Solar photovoltaic Wind energy Microgrid Power management Artificial neural networks Wind power generation Generators Hybrid power systems Batteries Artificial neural network Mathematical model Load modeling
Content Type	Text
Resource Type	Article

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