Abstract
The scope of this study is the optimal sizing of distributed generation in a hybrid power system with wind and energy storage units considering uncertainties. The load demand and wind speed uncertainties are modelled using the autoregressive moving average technique, and the system states are chronologically sampled using the sequential Monte Carlo simulation. The contribution of the paper can be stated as follows: (1) an objective function based on self-adapted evolutionary strategy in combination with Fischer–Burmeister algorithm is proposed to minimize the one-time investment and annual operational costs of the wind/energy storage sources; and (2) the effect of the cycle efficiency and charging/discharging rate of different energy storage units on the system cost is investigated under different reliability and load shifting levels. The computational performance of the proposed optimization solver is proven in order to obtain the minimum possible investment cost. The presented case studies in this paper provide remarkable insights for the suitable capacity installation at different values of reliability and load shifting levels.
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