Unit commitment model and solution in the hybrid power system based on chaos embedded particle swarm optimization-scenario reduction algorithms

Large-scale grid-integration of new energy sources such as wind power generation and so on leads to new problems in secure and stable operation of traditional power grids. For a hybrid power grid containing thermal power plants, wind farms and energy storage equipments, by means of constructing a unit commitment model and the stochastic property of wind power output uncertainty is simulated by scenario tree. Leading chaos embedded particle swarm optimization (CEPSO) into scenario reduction algorithms (SRA) the results of stochastic simulation and the ability to search the optimal solution are improved. Taking a hybrid power system composed of a wind farm and a 10-machine system as simulation example, simulation results show that the obtained unit commitment scheme can dispatch as many wind power units as possible and the operational cost of thermal generation units can be reduced to suit to the demand of energy conservation and emission reduction.