Modeling of integrated renewable energy system for electrification of a remote area in India |
| |
| Affiliation: | 1. Laboratory of Energy, Mechanic and Conversion Systems, Science and Technology University Houari Boumédiène, BP 32 El Alia, 16111 Bab Ezzouar, Algiers, Algeria;2. Laboratory Sciences for Environment, University of Corsica Pascal Paoli, UMR CNRS 6134, Route des Sanguinaires, F20000 Ajaccio, France;3. Galatasaray University, Computer Science Department, Ç?ra?an Cad. No:36, Ortaköy 34357, Istanbul, Turkey;1. School of Chemistry and Biochemistry and Center for Organic Photonics and Electronics, Georgia Institute of Technology, Atlanta, GA 30332-0400, United States;2. College of Science, Physics Department, Al Faisal University, Riyadh 11533, Saudi Arabia;3. Department of Physics, Faculty of Science, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia;4. School of Physics, Georgia Institute of Technology, Atlanta, GA 30332-0400, United States;1. University of Enviromental and Life Sciences, The Faculty of Life Sciences and Technology, Institute of Agricultural Engineering, Wroc?aw, Poland;2. University of Enviromental and Life Sciences, The Faculty of Enviromental Engineering and Geodesy, Department of Mathematics, Wroc?aw, Poland;3. Wroc?aw University of Technology, Faculty of Computer Science and Management, Wroc?aw, Poland |
| |
| Abstract: | Over the years, renewable energy based power generation has proven to be a cost-effective solution in stand-alone applications in the regions where grid extension is difficult. The present study focused on the development of models for optimal sizing of integrated renewable energy (IRE) system to satisfy the energy needs in different load sectors of four different zones considered in Chamarajanagar district of Karnataka state in India. The objective of the study is to minimize the total cost of generation and cost of energy using genetic algorithm (GA) based approach. Considering optimization power factor (OPF) and expected energy not supplied (EENS), optimum system feasibility has been investigated. Based on the study, it has been found that IRES is able to provide a feasible solution between 1.0 and 0.8 OPF values. However, power deficit occurs at OPF values less than 0.8 and the proposed model becomes infeasible under such conditions. Customer interruption cost (CIC) and deficit energy (DE) for all zones were also computed to quantify the reliability of the systems. |
| |
| Keywords: | Genetic algorithm Off grid electrification Integrated renewable energy system Customer interruption cost Levelized cost of energy |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
