Hybrid Renewable Energy for Residential Loads using HOMER Software & Neuro-Fuzzy Network
Majid S. M. Al-Hafidh1, Muthana S. Salih2
1M. S. Al-Hafid, Department of Electrical Engineering, Mosul University, College, Engineering, Ninava, Iraq.
2Muthana S. Salih, Department of Electrical Engineering, Mosul University, College, Engineering, Ninava, Iraq.
Manuscript received on December 01, 2014. | Revised Manuscript Received on December 09, 2014. | Manuscript published on January 20, 2015. | PP: 7-10 | Volume-3 Issue-2, January 2015. | Retrieval Number: G0482062714/2015©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Electric load consists of multiple components, residential, commercial, industrial, agricultural. . . Etc. The residential load is the largest component of the electrical load in the Iraqi power system nowadays. The study of residential load connected to the grid with the ability to energy change (buy and sale) has been carried in a previous research. Optimal hybrid renewable energy system has been found using HOMER software.The current research aims to implement HOMER software for different residential load with extent scale of change and to find the optimal hybrid renewable energy system for each load. In this way a database is to be obtained. This database is to be used in the formation of Neuro-Fuzzy system, which can be used to find the optimal hybrid renewable energy system for residential loads in the city of Mosul.
Keywords: Hybrid renewable power system ; grid connecting lods; Residential load; HOMER; Neuro-Fuzzy.