Optimal sizing for a hybrid power system with wind/energy storage
based in stochastic environment
For isolated power networks supplied by intermittent energy sources, several doubts have emerged
regarding the impact of the uncertainties on the networks reliability. This paper performs optimal sizing
for a hybrid power system with wind/energy storage sources based on stochastic modeling of historical
wind speed and load demand. The autoregressive moving average is used to stochastically model the
uncertainty of the load demand/wind speed and, the sequential Monte Carlo simulation is performed to
chronologically sample the system states. The contribution of the paper can be summarized as follows:
(1) an objective function based on self-adapted evolutionary strategy in combination with the 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 the
decision makers with the flexibility to choose the suitable capacity installation at different values of
reliability and load shifting levels.