Dependent probabilistic sequence operations for wind power output analyses

Dependent probabilistic sequence operation theory was developed to use arithmetic operations between correlated stochastic variables.The Copulas function is used to derive the equation with each iteration multiplying the variable by the probability of the point of each sequence and by an additional modifier determined by the dependent structure relating the variables.A framework for modeling correlated stochastic variables using this theory is also presented.A case study shows its application in calculating the distribution of the aggregate output from multiple wind farms to demonstrate its effectiveness.The theory expands existing sequence operation theory and has wide applications.