Two-Stage Compensation Algorithm for Dynamic Economic Dispatching Considering Copula Correlation of Multiwind Farms Generation

The dynamic economic dispatching of power system connected with multiple wind farms is a typical stochastic programming problem. How to model the randomness of wind power and how to solve this complex stochastic optimization problem are the key points. In this paper, copula theory is used to formulate the correlation of multiwind farms generation. Then, the dynamic economic dispatching model is founded with the fuel consumption, gas pollution emission fees, and electricity purchase costs as the optimized objective. The two-stage compensation algorithm is then introduced to solve the dispatching problem. In this algorithm, the conventional (nonstochastic) decision variables and stochastic variables are decoupled, which separate the dynamic dispatching model into two stage modes. The optimal dispatching result is worked out by iteration between the two stage models. Case studies on IEEE118-bus system and an actual provincial power grid show that the proposed algorithm can drastically reduce computational burden, and satisfy the actual requirements of engineering practice.