Large-scale wind power integration constituted great challenges for the power system operation and dispatching, due to the volatile and peak-reversal nature of wind power.The multi-objective optimization model of the wind farm combined with pumped-storage was studied to solve the problem.An optimization model for wind-storage combined operation was established, aiming at tracking load changes ,improving wind power economic benefits and peak shaving benefits, using improved multi-objective particle swarm optimization.The optimization calculation attempted to reduce volatility of the remaining load after removal of wind-storage joint output and increase economic benefits of wind farrms. Through the optimization calculation the wind farm and storage plant scheduling values of each time are available. The calculation example shows that the model and method are conducive to large-scale wind power integration and have a certain practicality and effectiveness.
Risk-averse robust interval economic dispatch for power systems with large-scale wind power integration
