Economic Analysis of HRES Systems with Energy Storage During Grid Interruptions and Curtailment in Tamil Nadu, India: A Hybrid RBFNOEHO Technique

Karunakaran Venkatesan, Uma Govindarajan, Padmanathan Kasinathan, Sanjeevikumar Padmanaban, Jens Bo Holm-Nielsen and Zbigniew Leonowicz
Additional contact information
Uma Govindarajan: Department of Electrical and Electronics Engineering, College of Engineering, Anna University, Chennai 600025, Tamil Nadu, India
Padmanathan Kasinathan: Department of Electrical and Electronics Engineering, Agni College of Technology, Thalambur, Chennai, Tamil Nadu 600130, India
Sanjeevikumar Padmanaban: Center for Bioenergy and Green Engineering, Department of Energy Technology, Aalborg University, 6700 Esbjerg, Denmark
Jens Bo Holm-Nielsen: Center for Bioenergy and Green Engineering, Department of Energy Technology, Aalborg University, 6700 Esbjerg, Denmark
Zbigniew Leonowicz: Faculty of Electrical Engineering, Wroclaw University of Science and Technology, Wyb. Wyspianskiego 27, 50370 Wroclaw, Poland

Energies, 2019, vol. 12, issue 16, 1-26

Abstract: This work presents an economic analysis of a hybrid renewable energy source (HRES) integrated with an energy storage system (ESS) using batteries with a new proposed strategy. Here, the HRES system comprises wind turbines (WT) and a photovoltaic (PV) system. The hybrid WT, PV and energy storage system with battery offer several benefits, in particular, high wind generation utilization rate, and optimal generation for meeting supply-demand gaps. The real recorded data of various parameters of a 22 KV hybrid ‘Regen’ feeder of 110/22 KV Vagarai Substation of TANTRANSCO in Palani of Tamilnadu in India was gathered, studied for the entire year of 2018, and utilized in this paper. The proposed strategy is the hybridization of two algorithms called Radial Basis Function Neural Network (RBFNN) and Oppositional Elephant Herding Optimization (OEHO) named the RBFNOEHO technique. With the help of RBFNN, the continuous load demand required for the HRES and be tracked. OEHO is used to optimize a perfect combination of HRES with the predicted load demand. The aim of the proposed hybrid RBFNOEHO is to study the cost comparison of the HRES system with the existing conventional base method, energy storage method (ESS) with batteries and with HOMER. The proposed Hybrid RBFNOEHO technique is evaluated by comparing it with the other techniques; it is found that the proposed method yields a more optimal solution than the other techniques.

Keywords: energy storage system (ESS); hybrid renewable energy sources (HRES); grid; demand; load; RBFNOEHO technique (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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