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Jul 3, 2024Keywords:
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An Optimization Tool for a Standalone Photovoltaic System Johanes Kasilima† , Enock William Nshama and Sarah Paul Ayeng’o
Abstract
Stand-alone photovoltaic systems (SAPV) are often used in remote
areas where access to grid electricity is limited. This system depends
on solar energy. However, Photovoltaic (PV) systems need a greater
initial investment than conventional sources of energy, and their
effectiveness is reliant on a number of environmental conditions such
as the unpredictable solar radiation. One step in reducing the
investment cost of a PV system is determining the optimal size of solar
PV components that minimize costs. This paper presents a Particle
Swarm based optimization tool for sizing Stand-alone PV systems. The
optimization tool selects the optimal Levelized Cost of Energy (LCOE)
of the PV system during its entire lifespan while maintaining its
reliability. The Particle Swarm Algorithm was implemented in order to
solve the optimization problem. The Loss of Power Supply Probability
(LSPS) is considered as the reliability index for this optimization. A
design example in Serengeti, Tanzania is used to validate the proposed
method. With an average daily load consumption of 94.3kWh, an
optimal size of 30kW of Solar PV, 82kWh of Li-ion battery and 13kW
of inverter was obtained at a LCOE of 0.22114 $/kWh. The Power
simulation for this system was also carried out based on the
mathematical models. The proposed method is investigated by
simulation with several meteorological data, and the effectiveness is
validated by using a similar tool which utilizes the mixed integer linear
programming method.
