Feasibility Model of Solar Energy Plants by ANN and MCDM Techniques

• Main Authors: Majumder, Mrinmoy (Author), Saha, Apu K. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Singapore : Springer Singapore : Imprint: Springer, 2016.
• Series: SpringerBriefs in Energy,
• Subjects: Energy.; Renewable energy resources.; Climate change.; Electric power production.; Computational intelligence.; Renewable energy sources.; Alternate energy sources.; Green energy industries.; Environmental economics.; Renewable and Green Energy.; Computational Intelligence.; Energy Technology.; Environmental Economics.; Climate Change/Climate Change Impacts.
• Physical Description: X, 49 p. 14 illus., 13 illus. in color. online resource.
• ISBN: 9789812873088
• ISSN: 2191-5520

This Brief highlights a novel model to find out the feasibility of any location to produce solar energy. The model utilizes the latest multi-criteria decision making techniques and artificial neural networks to predict the suitability of a location to maximize allocation of available energy for producing optimal amount of electricity which will satisfy the demand from the market. According to the results of the case studies further applications are encouraged.