Abstract
Photovoltaic-battery system is an option for decentralized power
generation for isolated locations receiving abundant sunshine. A
methodology for the optimum sizing of photovoltaic-battery system
for remote electrification incorporating the uncertainty associated
with solar insolation is proposed in this paper. The proposed methodology
is based on the design space approach involving a time series simulation
of the entire system. The design space approach was originally proposed
for sizing of the system with deterministic resource and demand.
In the present paper, chance constrained programming approach has
been utilized for incorporating the resource uncertainty in the system
sizing and the concept of design space is extended to incorporate
resource uncertainty. The set of all feasible design configurations
is represented by a sizing curve. The sizing curve for a given confidence
level, connects the combinations of the photovoltaic array ratings
and the corresponding minimum battery capacities capable of meeting
the specified load, plotted on an array rating vs. battery capacity
diagram.The methodology is validated using a sequential Monte Carlo
simulation approach with illustrative examples. It is shown that
for the case of constant coefficient of variation of solar insolation,
the set of sizing curves for different confidence levels may be represented
by a generalized curve. Selection of optimum system configuration
for different reliability levels based on the minimum cost of energy
is also presented. The effect of ambient temperature on sizing a
stand-alone photovoltaic-battery system is also illustrated through
a representative example.
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