Optimum sizing of photovoltaic battery systems incorporating uncertainty through design space approach

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.