Modeling Renewables Based Hybrid Power System with Desalination Plant Load Using Neural Networks

ABSTRACT

Hybrid power system is seen as a viable alternative to the conventional systems. Estimating the potential of these hybrid power systems for a selected site is a major input required for making informed decisions. Often, estimation of the kWhr production is a very elaborate and tedious exercise due to lack of a reliable model for the same. This article proposed an Artificial Neural Network based model that can be used to easily estimate the total kWhr/year for a given combination of Solar PV, Wind generator and Battery. The variable load considered for the model is a desalination plant load. The data is modelled using Neural Network and validated. The proposed Neural Network model offers a reliable estimation on the total annual power generation for a given combination of Solar PV, Wind generator and battery capacity,

Keywords::

• Renewable energy
• Hybrid power system
• ANN, Desalination
• RO
• Solar
• Wind
• Battery, storage

Additional information

Notes on contributors

Nagaraj R.

ABOUT THE AUTHORS

Nagaraj R., corresponding author, is presently working as Scientific Officer/F in Bhabha Atomic Research Centre, Kalpakkam, India. He obtained his B.E. in Electrical and Electronics Engineering from University of Madras and M.E. in Power Electronics and Industrial Drives. Presently he is pursuing Ph.D. from Homi Bhabha National Institute, Mumbai. He is currently working on development of customized Hybrid power systems for desalination applications using Artificial Intelligence. He is also working on development of Pulsed Electric Field (PEF) based sterilization systems. He has designed, developed and deployed Solar PV-RO based systems. He was involved in design and detailed engineering of electrical systems for Nuclear Desalination Plant at Kalpakkam. He has provided expert services to various Desalination and Water Treatment plants at Kalpakkam, India. Email: [email protected]

D. Thirugnana Murthy

D. Thirugnana Murthy completed his B.E. in Electronics and Communication from AC College of Engg & Tech., India, M.Tech in Electronics Design from Indian Institute of Science, Bangalore and Ph.D. from HBNI, Mumbai, India. He has completed one year Orientation Programme on Nuclear Engineering at BARC Training School, Mumbai and has under gone advanced course on Software Project Management at NCST, Bangalore. He is presently the Head of Electronics and Instrumentation Division at Indira Gandhi Centre for Atomic Research, Govt. of India at Kalpakkam. He has over 31 years of experience in research of Electronics and Instrumentation systems for nuclear power applications particularly with respect to Fast Breeder Technologies. He has served as Guest Faculty for various universities including University of Madras and guided many post graduate students for their thesis work. Affiliation: NDDP, BARC Facilities, Kalpakkam-603 102, India.

M.M. Rajput

Manik Murthy Rajput completed his B.E. in Mechanical Engineering and also completed One year Orientation Programme on Nuclear Engineering at BARC Training School, India. Currently he is the Head for Nuclear Desalination activities at BARC, Kalpakkam. He has over 30 years of expertise in various aspects of nuclear energy programme. Affiliation: IGCAR, Kalpakkam — 603 102, India.