An Optimal Dispatch Method for Power Systems with High Penetration of Renewable Power and CHP Units Utilizing the Combined GA and PSO Algorithm

With the improvement scale of grid connection renewable power, accurately forecasting and effectively coordinating systems with various energy sources has become much more important for power system scheduling and operation. Considering the uncertain characteristics of renewable energy and CHP units, this paper proposes an optimal dispatch method with multi-prediction models and an improved solving method by series correction and parallel coupling analysis. Firstly, multiple-model stationary time series are obtained by EMD (empirical mode decomposition) of the prediction results from multiple models. Then, series decomposition is updated by the UKF (unscented Kalman filter). Using the least-squares method, the parallel coupling of the correction results is solved. A complex optimal scheduling model with multiple renewable energy sources and CHP units is proposed and solved with the help of the improved GA and PSO combined algorithm to avoid the algorithm falling into local optimal conditions. Simulations show that the proposed optimal dispatch model and algorithm are able to consider the uncertain characteristics of renewable energy and CHP units with better performance than some typical methods, such as the baseline method that combines single-model BP forecasting with conventional PSO-based dispatch. These results demonstrate that the proposed EMD–UKF-based multi-model forecasting combined with the improved GA–PSO-based dispatch framework provides an effective and practically applicable tool for enhancing the economic and low-carbon operation of multi-energy systems with high renewable penetration.