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Incidence Of Load Profiles In The Levelized Cost Of Electricity For A Wind Power Generation System Located In Lambayeque-Perú. | ||
| Published in: | Prospective and trends in technology and skills for sustainable social development. Leveraging emerging technologies to construct the future: Proceedings of the 19th LACCEI International Multi-Conference for Engineering, Education and Technology |  |
| Date of Conference: | July 19-23, 2021 | |
| Location of Conference: | Virtual | |
| Authors: | Johnny Nahui-Ortiz (National University of Engineering, PE) Amado Aguinaga (Universidad Nacional Pedro Ruiz Gallo, PE) Fredy Dávila (Universidad Nacional Pedro Ruiz Gallo, PE) Oscar Méndez (Universidad Nacional Pedro Ruiz Gallo, PE) | |
| Full Paper: | #508 | |
Abstract:In this research work, a comparative cost analysis of electricity produced by a renewable energy system is carried out considering two reference electric load profiles. A 165.4-kWh daily electric load is established on the basis of a community-type profile, with a 20.5-kW peak load and a load factor of 0.34. Using simulation built-in features from HOMER Pro, optimum sizing for both a load profile driven by night time energy demand and a load profile driven by day time energy demand is carried out. A proposed wind power generation system, for a load driven by night time energy demand, consists of a 168-kW wind power generation system, an 820-kWh storage capacity, and a 90.2-kW DC-AC converter. Also, a proposed wind power generation system, for a load driven by day time energy demand, consists of the same component configuration. A levelized cost of electricity (LCOE) approach is used for comparison purposes. Also, net present cost (NPC) is calculated for the proposed energy supply alternatives. It is concluded that for comparative cost analysis key aspects, such electric load profile and its correlation with wind speed availability on hourly basis, may not play a significant role for this particular case. Also, gathering local measured data as opposed to using reference databases could further contribute to optimize sizing of wind power generation systems | ||