A probabilistic economic dispatch model and methodology considering renewable energy, demand and generator uncertainties

In this paper a probabilistic economic dispatch model considering thermal units (fuel generators), photovoltaic arrays and wind energy conversion systems is proposed. Wind speed, solar radiation and power demand are recognized as random variables. Unavailability of each type of power source is also considered. The solution strategy is based on the Monte Carlo method and non-linear constrained optimization. The optimal solution involves single and multidimensional probabilities, descriptive statistics, cluster and bimodal analysis. The proposed methodology yields the probability distributions of system marginal price, thermal (fuel based), solar and wind power generation and load shedding. The proposed model and methodology are applied to a case study of the Northern Chilean electrical system.