"

Incidence Of Load Profiles In The Levelized Cost Of Electricity For A Solar-Pv 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: #465

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 solar-PV generation system, for a load driven by night time energy demand, consists of an 81.5-kW solar PV generation system, a 657-kWh storage capacity, and a 44.87-kW DC-AC converter. On the other hand, a proposed solar-PV generation system, for a load driven by day time energy demand, consists of a 103-kW solar PV generation system, a 443-kWh storage capacity, and a 29.2-kW DC-AC converter. 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 solar radiation availability on hourly basis, play a significant role. Also, Demand-Side Management and End-Use Energy Efficiency would further contribute to optimize sizing of solar-PV generation systems.